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<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">Soil legacy data rescue via GlobalSoilMap and other international and
national initiatives</title><author><name sortKey="Arrouays, Dominique" sort="Arrouays, Dominique" uniqKey="Arrouays D" first="Dominique" last="Arrouays">Dominique Arrouays</name><affiliation><nlm:aff id="aff0001">INRA, InfoSol Unit, 45075 Orleans, France</nlm:aff></affiliation></author><author><name sortKey="Leenaars, Johan G B" sort="Leenaars, Johan G B" uniqKey="Leenaars J" first="Johan G. B." last="Leenaars">Johan G. B. Leenaars</name><affiliation><nlm:aff>NONE</nlm:aff></affiliation></author><author><name sortKey="Richer De Forges, Anne C" sort="Richer De Forges, Anne C" uniqKey="Richer De Forges A" first="Anne C." last="Richer-De-Forges">Anne C. Richer-De-Forges</name><affiliation><nlm:aff id="aff0001">INRA, InfoSol Unit, 45075 Orleans, France</nlm:aff></affiliation></author><author><name sortKey="Adhikari, Koushik" sort="Adhikari, Koushik" uniqKey="Adhikari K" first="Koushik" last="Adhikari">Koushik Adhikari</name><affiliation><nlm:aff id="aff0003">Department of Agroecology, Faculty of science and technology, Aarhus University, Tjele, Denmark</nlm:aff></affiliation></author><author><name sortKey="Ballabio, Cristiano" sort="Ballabio, Cristiano" uniqKey="Ballabio C" first="Cristiano" last="Ballabio">Cristiano Ballabio</name><affiliation><nlm:aff id="aff0005">European Commission - DG JRC, Via E. Fermi, 2749, 21027 Ispra (VA), Italy</nlm:aff></affiliation></author><author><name sortKey="Greve, Mogens" sort="Greve, Mogens" uniqKey="Greve M" first="Mogens" last="Greve">Mogens Greve</name><affiliation><nlm:aff id="aff0003">Department of Agroecology, Faculty of science and technology, Aarhus University, Tjele, Denmark</nlm:aff></affiliation></author><author><name sortKey="Grundy, Mike" sort="Grundy, Mike" uniqKey="Grundy M" first="Mike" last="Grundy">Mike Grundy</name><affiliation><nlm:aff id="aff0006">CSIRO, Australia</nlm:aff></affiliation></author><author><name sortKey="Guerrero, Eliseo" sort="Guerrero, Eliseo" uniqKey="Guerrero E" first="Eliseo" last="Guerrero">Eliseo Guerrero</name><affiliation><nlm:aff id="aff0007">National Institute of Statistics and Geography, INEGI, Aguascalientes, Mexico</nlm:aff></affiliation></author><author><name sortKey="Hempel, Jon" sort="Hempel, Jon" uniqKey="Hempel J" first="Jon" last="Hempel">Jon Hempel</name><affiliation><nlm:aff id="aff0008">Retired. US department of Agriculture, Natural Resources Conservation Services, Lincoln, Nebraska, USA</nlm:aff></affiliation></author><author><name sortKey="Hengl, Tomislav" sort="Hengl, Tomislav" uniqKey="Hengl T" first="Tomislav" last="Hengl">Tomislav Hengl</name><affiliation><nlm:aff id="aff0002">ISRIC - World Soil Information, PO Box 353, 6700 AJ, Wageningen, The Netherlands</nlm:aff></affiliation></author><author><name sortKey="Heuvelink, Gerard" sort="Heuvelink, Gerard" uniqKey="Heuvelink G" first="Gerard" last="Heuvelink">Gerard Heuvelink</name><affiliation><nlm:aff id="aff0002">ISRIC - World Soil Information, PO Box 353, 6700 AJ, Wageningen, The Netherlands</nlm:aff></affiliation></author><author><name sortKey="Batjes, Niels" sort="Batjes, Niels" uniqKey="Batjes N" first="Niels" last="Batjes">Niels Batjes</name><affiliation><nlm:aff id="aff0002">ISRIC - World Soil Information, PO Box 353, 6700 AJ, Wageningen, The Netherlands</nlm:aff></affiliation></author><author><name sortKey="Carvalho, Eloi" sort="Carvalho, Eloi" uniqKey="Carvalho E" first="Eloi" last="Carvalho">Eloi Carvalho</name><affiliation><nlm:aff id="aff0002">ISRIC - World Soil Information, PO Box 353, 6700 AJ, Wageningen, The Netherlands</nlm:aff></affiliation></author><author><name sortKey="Hartemink, Alfred" sort="Hartemink, Alfred" uniqKey="Hartemink A" first="Alfred" last="Hartemink">Alfred Hartemink</name><affiliation><nlm:aff id="aff0009">University of Wisconsin, Department of Soil Science, Madison, USA</nlm:aff></affiliation></author><author><name sortKey="Hewitt, Alan" sort="Hewitt, Alan" uniqKey="Hewitt A" first="Alan" last="Hewitt">Alan Hewitt</name><affiliation><nlm:aff id="aff0010">Landcare research, Manaaki Whenua, New-Zealand</nlm:aff></affiliation></author><author><name sortKey="Hong, Suk Young" sort="Hong, Suk Young" uniqKey="Hong S" first="Suk-Young" last="Hong">Suk-Young Hong</name><affiliation><nlm:aff id="aff0011">Department of Agricultural Environment, National Academy of Agricultural Science, Suwon 441-707, Korea</nlm:aff></affiliation></author><author><name sortKey="Krasilnikov, Pavel" sort="Krasilnikov, Pavel" uniqKey="Krasilnikov P" first="Pavel" last="Krasilnikov">Pavel Krasilnikov</name><affiliation><nlm:aff id="aff0012">Eurasian Center for Food Security, Lomonosov Moscow State University, Moscow, Russia</nlm:aff></affiliation></author><author><name sortKey="Lagacherie, Philippe" sort="Lagacherie, Philippe" uniqKey="Lagacherie P" first="Philippe" last="Lagacherie">Philippe Lagacherie</name><affiliation><nlm:aff id="aff0013">INRA-IRD-Supagro, UMR Lisah, Montpellier, France</nlm:aff></affiliation></author><author><name sortKey="Lelyk, Glen" sort="Lelyk, Glen" uniqKey="Lelyk G" first="Glen" last="Lelyk">Glen Lelyk</name><affiliation><nlm:aff id="aff0014">Agriculture and Agri-Food Canada, Ottawa, Canada</nlm:aff></affiliation></author><author><name sortKey="Libohova, Zamir" sort="Libohova, Zamir" uniqKey="Libohova Z" first="Zamir" last="Libohova">Zamir Libohova</name><affiliation><nlm:aff id="aff0015">US department of Agriculture, Natural Resources Conservation Services, Lincoln Nebraska, USA</nlm:aff></affiliation></author><author><name sortKey="Lilly, Allan" sort="Lilly, Allan" uniqKey="Lilly A" first="Allan" last="Lilly">Allan Lilly</name><affiliation><nlm:aff id="aff0016">The James Hutton Institute, Craigiebuckler, Aberde<bold>l</bold>and, UK</nlm:aff></affiliation></author><author><name sortKey="Mcbratney, Alex" sort="Mcbratney, Alex" uniqKey="Mcbratney A" first="Alex" last="Mcbratney">Alex Mcbratney</name><affiliation><nlm:aff id="aff0017">University of Sydney, Sydney, Australia</nlm:aff></affiliation></author><author><name sortKey="Mckenzie, Neil" sort="Mckenzie, Neil" uniqKey="Mckenzie N" first="Neil" last="Mckenzie">Neil Mckenzie</name><affiliation><nlm:aff id="aff0006">CSIRO, Australia</nlm:aff></affiliation></author><author><name sortKey="Vasquez, Gustavo M" sort="Vasquez, Gustavo M" uniqKey="Vasquez G" first="Gustavo M." last="Vasquez">Gustavo M. Vasquez</name><affiliation><nlm:aff id="aff0018">Embrapa Solos, Rio de janeiro, Brazil</nlm:aff></affiliation></author><author><name sortKey="Leatitia Mulder, Vera" sort="Leatitia Mulder, Vera" uniqKey="Leatitia Mulder V" first="Vera" last="Leatitia Mulder">Vera Leatitia Mulder</name><affiliation><nlm:aff id="aff0019">Biogeochemistry and Earth System Modelling, Sciences de la Terre et de l’Environnement, Universite Libre de Bruxelles, Bruxelles, Belgium</nlm:aff></affiliation></author><author><name sortKey="Minasny, Budiman" sort="Minasny, Budiman" uniqKey="Minasny B" first="Budiman" last="Minasny">Budiman Minasny</name><affiliation><nlm:aff id="aff0017">University of Sydney, Sydney, Australia</nlm:aff></affiliation></author><author><name sortKey="Luca, Montanarella" sort="Luca, Montanarella" uniqKey="Luca M" first="Montanarella" last="Luca">Montanarella Luca</name><affiliation><nlm:aff id="aff0005">European Commission - DG JRC, Via E. Fermi, 2749, 21027 Ispra (VA), Italy</nlm:aff></affiliation></author><author><name sortKey="Odeh, Inakwu" sort="Odeh, Inakwu" uniqKey="Odeh I" first="Inakwu" last="Odeh">Inakwu Odeh</name><affiliation><nlm:aff id="aff0017">University of Sydney, Sydney, Australia</nlm:aff></affiliation></author><author><name sortKey="Padarian, Jose" sort="Padarian, Jose" uniqKey="Padarian J" first="Jose" last="Padarian">Jose Padarian</name><affiliation><nlm:aff id="aff0017">University of Sydney, Sydney, Australia</nlm:aff></affiliation></author><author><name sortKey="Poggio, Laura" sort="Poggio, Laura" uniqKey="Poggio L" first="Laura" last="Poggio">Laura Poggio</name><affiliation><nlm:aff id="aff0016">The James Hutton Institute, Craigiebuckler, Aberde<bold>l</bold>and, UK</nlm:aff></affiliation></author><author><name sortKey="Roudier, Pierre" sort="Roudier, Pierre" uniqKey="Roudier P" first="Pierre" last="Roudier">Pierre Roudier</name><affiliation><nlm:aff id="aff0010">Landcare research, Manaaki Whenua, New-Zealand</nlm:aff></affiliation></author><author><name sortKey="Saby, Nicolas" sort="Saby, Nicolas" uniqKey="Saby N" first="Nicolas" last="Saby">Nicolas Saby</name><affiliation><nlm:aff id="aff0001">INRA, InfoSol Unit, 45075 Orleans, France</nlm:aff></affiliation></author><author><name sortKey="Savin, Igor" sort="Savin, Igor" uniqKey="Savin I" first="Igor" last="Savin">Igor Savin</name><affiliation><nlm:aff id="aff0020">Dokutchaev Soil Science Institute, Moscow, Russia</nlm:aff></affiliation><affiliation><nlm:aff id="aff0052">People’s Friendship University of Russia (RUDN University), Moscow, Russia</nlm:aff></affiliation></author><author><name sortKey="Searle, Ross" sort="Searle, Ross" uniqKey="Searle R" first="Ross" last="Searle">Ross Searle</name><affiliation><nlm:aff id="aff0006">CSIRO, Australia</nlm:aff></affiliation></author><author><name sortKey="Solbovoy, Vladimir" sort="Solbovoy, Vladimir" uniqKey="Solbovoy V" first="Vladimir" last="Solbovoy">Vladimir Solbovoy</name><affiliation><nlm:aff id="aff0020">Dokutchaev Soil Science Institute, Moscow, Russia</nlm:aff></affiliation></author><author><name sortKey="Thompson, James" sort="Thompson, James" uniqKey="Thompson J" first="James" last="Thompson">James Thompson</name><affiliation><nlm:aff id="aff0021">West Virginia University, West Virginia, USA</nlm:aff></affiliation></author><author><name sortKey="Smith, Scott" sort="Smith, Scott" uniqKey="Smith S" first="Scott" last="Smith">Scott Smith</name><affiliation><nlm:aff id="aff0014">Agriculture and Agri-Food Canada, Ottawa, Canada</nlm:aff></affiliation></author><author><name sortKey="Sulaeman, Yiyi" sort="Sulaeman, Yiyi" uniqKey="Sulaeman Y" first="Yiyi" last="Sulaeman">Yiyi Sulaeman</name><affiliation><nlm:aff id="aff0022">Indonesian Center for Agricultural Land Resource Research and Development, Bogor, West Javal Indonesia</nlm:aff></affiliation></author><author><name sortKey="Vintila, Ruxandra" sort="Vintila, Ruxandra" uniqKey="Vintila R" first="Ruxandra" last="Vintila">Ruxandra Vintila</name><affiliation><nlm:aff id="aff0023">National Research and Development Institute for Soil Science, Agro-chemistry and Environment (ICPA), Bucharest, Romania</nlm:aff></affiliation></author><author><name sortKey="Rossel, Raphael Viscarra" sort="Rossel, Raphael Viscarra" uniqKey="Rossel R" first="Raphael Viscarra" last="Rossel">Raphael Viscarra Rossel</name><affiliation><nlm:aff id="aff0006">CSIRO, Australia</nlm:aff></affiliation></author><author><name sortKey="Wilson, Peter" sort="Wilson, Peter" uniqKey="Wilson P" first="Peter" last="Wilson">Peter Wilson</name><affiliation><nlm:aff id="aff0006">CSIRO, Australia</nlm:aff></affiliation></author><author><name sortKey="Zhang, Gan Lin" sort="Zhang, Gan Lin" uniqKey="Zhang G" first="Gan-Lin" last="Zhang">Gan-Lin Zhang</name><affiliation><nlm:aff id="aff0024">State Key Laboratory of Soil and Sustainable Agriculture, Institute of Soil Science, Chinese Academy of Sciences, Nanjing, China</nlm:aff></affiliation></author><author><name sortKey="Swerts, Martine" sort="Swerts, Martine" uniqKey="Swerts M" first="Martine" last="Swerts">Martine Swerts</name><affiliation><nlm:aff id="aff0025">Land and Soil Protection Service, Flemish Government, Brussels, Belgium</nlm:aff></affiliation></author><author><name sortKey="Oorts, Katrien" sort="Oorts, Katrien" uniqKey="Oorts K" first="Katrien" last="Oorts">Katrien Oorts</name><affiliation><nlm:aff id="aff0025">Land and Soil Protection Service, Flemish Government, Brussels, Belgium</nlm:aff></affiliation></author><author><name sortKey="Karklins, Aldis" sort="Karklins, Aldis" uniqKey="Karklins A" first="Aldis" last="Karklins">Aldis Karklins</name><affiliation><nlm:aff id="aff0026">Latvia Agricultural University, Jelgava, Latvia</nlm:aff></affiliation></author><author><name sortKey="Feng, Liu" sort="Feng, Liu" uniqKey="Feng L" first="Liu" last="Feng">Liu Feng</name><affiliation><nlm:aff id="aff0024">State Key Laboratory of Soil and Sustainable Agriculture, Institute of Soil Science, Chinese Academy of Sciences, Nanjing, China</nlm:aff></affiliation></author><author><name sortKey="Ibelles Navarro, Alexandro R" sort="Ibelles Navarro, Alexandro R" uniqKey="Ibelles Navarro A" first="Alexandro R." last="Ibelles Navarro">Alexandro R. Ibelles Navarro</name><affiliation><nlm:aff id="aff0007">National Institute of Statistics and Geography, INEGI, Aguascalientes, Mexico</nlm:aff></affiliation></author><author><name sortKey="Levin, Arkadiy" sort="Levin, Arkadiy" uniqKey="Levin A" first="Arkadiy" last="Levin">Arkadiy Levin</name><affiliation><nlm:aff id="aff0027">National Scientific Center, Institute for Soil Science and Agrochemistry Research, Kharkiv, Ukraine</nlm:aff></affiliation></author><author><name sortKey="Laktionova, Tetiana" sort="Laktionova, Tetiana" uniqKey="Laktionova T" first="Tetiana" last="Laktionova">Tetiana Laktionova</name><affiliation><nlm:aff id="aff0027">National Scientific Center, Institute for Soil Science and Agrochemistry Research, Kharkiv, Ukraine</nlm:aff></affiliation></author><author><name sortKey="Dell Cqua, Martin" sort="Dell Cqua, Martin" uniqKey="Dell Cqua M" first="Martin" last="Dell Cqua">Martin Dell Cqua</name><affiliation><nlm:aff id="aff0028">Sistema de Informacion Geografica, Direccion General de Recursos Naturales, Ministerio de Ganaderia Agricultura y Pesca, Montevideo, Uruguay</nlm:aff></affiliation></author><author><name sortKey="Suvannang, Nopmanee" sort="Suvannang, Nopmanee" uniqKey="Suvannang N" first="Nopmanee" last="Suvannang">Nopmanee Suvannang</name><affiliation><nlm:aff id="aff0029">Land Development Department, Land Development Department, Ladyao, Chatuchak, Bangkok, Thailand</nlm:aff></affiliation></author><author><name sortKey="Ruam, Waew" sort="Ruam, Waew" uniqKey="Ruam W" first="Waew" last="Ruam">Waew Ruam</name><affiliation><nlm:aff id="aff0029">Land Development Department, Land Development Department, Ladyao, Chatuchak, Bangkok, Thailand</nlm:aff></affiliation></author><author><name sortKey="Prasad, Jagdish" sort="Prasad, Jagdish" uniqKey="Prasad J" first="Jagdish" last="Prasad">Jagdish Prasad</name><affiliation><nlm:aff id="aff0030">National Bureau of Soil Survey and Land Use Planning (NBSSLUP) Indian Council of Agricultural Research (ICAR), Nagpur, Maharashtra, India</nlm:aff></affiliation></author><author><name sortKey="Patil, Nitin" sort="Patil, Nitin" uniqKey="Patil N" first="Nitin" last="Patil">Nitin Patil</name><affiliation><nlm:aff id="aff0030">National Bureau of Soil Survey and Land Use Planning (NBSSLUP) Indian Council of Agricultural Research (ICAR), Nagpur, Maharashtra, India</nlm:aff></affiliation></author><author><name sortKey="Husnjak, Stjepan" sort="Husnjak, Stjepan" uniqKey="Husnjak S" first="Stjepan" last="Husnjak">Stjepan Husnjak</name><affiliation><nlm:aff id="aff0031">Faculty of Agriculture, Deptartment of Soil Science, Zagreb, Croatia</nlm:aff></affiliation></author><author><name sortKey="Pasztor, Laszlo" sort="Pasztor, Laszlo" uniqKey="Pasztor L" first="Laszlo" last="Pasztor">Laszlo Pasztor</name><affiliation><nlm:aff id="aff0032">Research Institute for Soil Science and Agricultural Chemistry (RISSAC) of the. Hungarian Academy of Sciences, Budapest, Hungary</nlm:aff></affiliation></author><author><name sortKey="Okx, Joop" sort="Okx, Joop" uniqKey="Okx J" first="Joop" last="Okx">Joop Okx</name><affiliation><nlm:aff id="aff0033">Alterra - Wageningen UR, 6700 AA, Wageningen, The Netherlands</nlm:aff></affiliation></author><author><name sortKey="Hallet, Stephen" sort="Hallet, Stephen" uniqKey="Hallet S" first="Stephen" last="Hallet">Stephen Hallet</name><affiliation><nlm:aff id="aff0034">Cranfield University, Soils and Agrifood Institute, NSRI, United Kingdc</nlm:aff></affiliation></author><author><name sortKey="Keay, Caroline" sort="Keay, Caroline" uniqKey="Keay C" first="Caroline" last="Keay">Caroline Keay</name><affiliation><nlm:aff id="aff0034">Cranfield University, Soils and Agrifood Institute, NSRI, United Kingdc</nlm:aff></affiliation></author><author><name sortKey="Farewell, Timothy" sort="Farewell, Timothy" uniqKey="Farewell T" first="Timothy" last="Farewell">Timothy Farewell</name><affiliation><nlm:aff id="aff0034">Cranfield University, Soils and Agrifood Institute, NSRI, United Kingdc</nlm:aff></affiliation></author><author><name sortKey="Lilja, Harri" sort="Lilja, Harri" uniqKey="Lilja H" first="Harri" last="Lilja">Harri Lilja</name><affiliation><nlm:aff id="aff0035">MTT, Plant Production Research, Soil and Plant Nutrition, Jokioinen, Finland</nlm:aff></affiliation></author><author><name sortKey="Juilleret, Jerome" sort="Juilleret, Jerome" uniqKey="Juilleret J" first="Jerome" last="Juilleret">Jerome Juilleret</name><affiliation><nlm:aff id="aff0036">Luxembourg Institute of Science and Technology, Belvaux, Grand Duchy of Luxembourg</nlm:aff></affiliation></author><author><name sortKey="Marx, Simone" sort="Marx, Simone" uniqKey="Marx S" first="Simone" last="Marx">Simone Marx</name><affiliation><nlm:aff id="aff0036">Luxembourg Institute of Science and Technology, Belvaux, Grand Duchy of Luxembourg</nlm:aff></affiliation></author><author><name sortKey="Takata, Yusuke" sort="Takata, Yusuke" uniqKey="Takata Y" first="Yusuke" last="Takata">Yusuke Takata</name><affiliation><nlm:aff id="aff0037">Institute for Agro-Environmental Sciences, NARO, Tsukuba, Ibaraki, Japan</nlm:aff></affiliation></author><author><name sortKey="Kazuyuki, Yagi" sort="Kazuyuki, Yagi" uniqKey="Kazuyuki Y" first="Yagi" last="Kazuyuki">Yagi Kazuyuki</name><affiliation><nlm:aff id="aff0037">Institute for Agro-Environmental Sciences, NARO, Tsukuba, Ibaraki, Japan</nlm:aff></affiliation></author><author><name sortKey="Mansuy, Nicolas" sort="Mansuy, Nicolas" uniqKey="Mansuy N" first="Nicolas" last="Mansuy">Nicolas Mansuy</name><affiliation><nlm:aff id="aff0038">Nat Resources Canada, Canadian Forest Serv, Ste Foy, Quebec City, Canada</nlm:aff></affiliation></author><author><name sortKey="Panagos, Panos" sort="Panagos, Panos" uniqKey="Panagos P" first="Panos" last="Panagos">Panos Panagos</name><affiliation><nlm:aff id="aff0005">European Commission - DG JRC, Via E. Fermi, 2749, 21027 Ispra (VA), Italy</nlm:aff></affiliation></author><author><name sortKey="Van Liedekerke, Mark" sort="Van Liedekerke, Mark" uniqKey="Van Liedekerke M" first="Mark" last="Van Liedekerke">Mark Van Liedekerke</name><affiliation><nlm:aff id="aff0005">European Commission - DG JRC, Via E. Fermi, 2749, 21027 Ispra (VA), Italy</nlm:aff></affiliation></author><author><name sortKey="Skalsky, Rastislav" sort="Skalsky, Rastislav" uniqKey="Skalsky R" first="Rastislav" last="Skalsky">Rastislav Skalsky</name><affiliation><nlm:aff id="aff0039">Soil Science and Conservation Research Institute, Gagarinova 10, Bratislava, Slovakia</nlm:aff></affiliation></author><author><name sortKey="Sobocka, Jaroslava" sort="Sobocka, Jaroslava" uniqKey="Sobocka J" first="Jaroslava" last="Sobocka">Jaroslava Sobocka</name><affiliation><nlm:aff id="aff0039">Soil Science and Conservation Research Institute, Gagarinova 10, Bratislava, Slovakia</nlm:aff></affiliation></author><author><name sortKey="Kobza, Josef" sort="Kobza, Josef" uniqKey="Kobza J" first="Josef" last="Kobza">Josef Kobza</name><affiliation><nlm:aff id="aff0039">Soil Science and Conservation Research Institute, Gagarinova 10, Bratislava, Slovakia</nlm:aff></affiliation></author><author><name sortKey="Eftekhari, Kamran" sort="Eftekhari, Kamran" uniqKey="Eftekhari K" first="Kamran" last="Eftekhari">Kamran Eftekhari</name><affiliation><nlm:aff id="aff0040">Soil genesis and classification department, Soil and water research institute, Karaj, I. R. Iran</nlm:aff></affiliation></author><author><name sortKey="Kacem Alavipanah, Seyed" sort="Kacem Alavipanah, Seyed" uniqKey="Kacem Alavipanah S" first="Seyed" last="Kacem Alavipanah">Seyed Kacem Alavipanah</name><affiliation><nlm:aff id="aff0040">Soil genesis and classification department, Soil and water research institute, Karaj, I. R. Iran</nlm:aff></affiliation></author><author><name sortKey="Moussadek, Rachid" sort="Moussadek, Rachid" uniqKey="Moussadek R" first="Rachid" last="Moussadek">Rachid Moussadek</name><affiliation><nlm:aff id="aff0041">INRA, Rabat, Morocco</nlm:aff></affiliation></author><author><name sortKey="Badraoui, Mohamed" sort="Badraoui, Mohamed" uniqKey="Badraoui M" first="Mohamed" last="Badraoui">Mohamed Badraoui</name><affiliation><nlm:aff id="aff0041">INRA, Rabat, Morocco</nlm:aff></affiliation></author><author><name sortKey="Da Silva, Mayesse" sort="Da Silva, Mayesse" uniqKey="Da Silva M" first="Mayesse" last="Da Silva">Mayesse Da Silva</name><affiliation><nlm:aff id="aff0042">International Center for Tropical Agriculture (CIAT) - Headquarters and Regional Office for Latin America and the Caribbean, Cali, Colombia</nlm:aff></affiliation></author><author><name sortKey="Paterson, Garry" sort="Paterson, Garry" uniqKey="Paterson G" first="Garry" last="Paterson">Garry Paterson</name><affiliation><nlm:aff id="aff0043">ARC-Institute for Soil, Climate and Water, Pretoria, South Africa</nlm:aff></affiliation></author><author><name sortKey="Da Conceicao Gonsalves, Maria" sort="Da Conceicao Gonsalves, Maria" uniqKey="Da Conceicao Gonsalves M" first="Maria" last="Da Conceicao Gonsalves">Maria Da Conceicao Gonsalves</name><affiliation><nlm:aff id="aff0044">Instituto Nacional de Investigagao Agraria e Veterinaria, Laboratorio de Solos de Oeiras, Oeiras, Portugal</nlm:aff></affiliation></author><author><name sortKey="Theocharopoulos, Sid" sort="Theocharopoulos, Sid" uniqKey="Theocharopoulos S" first="Sid" last="Theocharopoulos">Sid Theocharopoulos</name><affiliation><nlm:aff id="aff0045">Soil Science Institute of Athens, NAGREF, Athens, Greece</nlm:aff></affiliation></author><author><name sortKey="Yemefack, Martin" sort="Yemefack, Martin" uniqKey="Yemefack M" first="Martin" last="Yemefack">Martin Yemefack</name><affiliation><nlm:aff id="aff0046">International Institute of Tropical Agriculture (IITA) and Institute of Agricultural Research for Development (IRAD), Yaounde, Cameroon</nlm:aff></affiliation></author><author><name sortKey="Tedou, Silatsa" sort="Tedou, Silatsa" uniqKey="Tedou S" first="Silatsa" last="Tedou">Silatsa Tedou</name><affiliation><nlm:aff id="aff0046">International Institute of Tropical Agriculture (IITA) and Institute of Agricultural Research for Development (IRAD), Yaounde, Cameroon</nlm:aff></affiliation></author><author><name sortKey="Vrscaj, Borut" sort="Vrscaj, Borut" uniqKey="Vrscaj B" first="Borut" last="Vrscaj">Borut Vrscaj</name><affiliation><nlm:aff id="aff0047">Agricultural Institute of Slovenia, Ljubljana, Slovenia</nlm:aff></affiliation></author><author><name sortKey="Grob, Urs" sort="Grob, Urs" uniqKey="Grob U" first="Urs" last="Grob">Urs Grob</name><affiliation><nlm:aff id="aff0048">NABODAT, Agroscope, Institut fur Nachhaltigkeitswissenschaft, INH, Zurich, Switzerland</nlm:aff></affiliation></author><author><name sortKey="Kozak, Josef" sort="Kozak, Josef" uniqKey="Kozak J" first="Josef" last="Kozak">Josef Kozak</name><affiliation><nlm:aff id="aff0049">Faculty of Agrobiology, Czech University of Life Sciences, Prague, Czech Republic</nlm:aff></affiliation></author><author><name sortKey="Boruvka, Lubos" sort="Boruvka, Lubos" uniqKey="Boruvka L" first="Lubos" last="Boruvka">Lubos Boruvka</name><affiliation><nlm:aff id="aff0049">Faculty of Agrobiology, Czech University of Life Sciences, Prague, Czech Republic</nlm:aff></affiliation></author><author><name sortKey="Dobos, Endre" sort="Dobos, Endre" uniqKey="Dobos E" first="Endre" last="Dobos">Endre Dobos</name><affiliation><nlm:aff id="aff0050">University of Miskolc, geography Institute, Miskolc-Egyetemvaros, Hungary</nlm:aff></affiliation></author><author><name sortKey="Taboada, Miguel" sort="Taboada, Miguel" uniqKey="Taboada M" first="Miguel" last="Taboada">Miguel Taboada</name><affiliation><nlm:aff id="aff0051">Institute of Soils, INTA, Buenos Aires, Argentina</nlm:aff></affiliation></author><author><name sortKey="Moretti, Lucas" sort="Moretti, Lucas" uniqKey="Moretti L" first="Lucas" last="Moretti">Lucas Moretti</name><affiliation><nlm:aff id="aff0051">Institute of Soils, INTA, Buenos Aires, Argentina</nlm:aff></affiliation></author><author><name sortKey="Rodriguez, Dario" sort="Rodriguez, Dario" uniqKey="Rodriguez D" first="Dario" last="Rodriguez">Dario Rodriguez</name><affiliation><nlm:aff id="aff0051">Institute of Soils, INTA, Buenos Aires, Argentina</nlm:aff></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">PMC</idno><idno type="pmid">32864337</idno><idno type="pmc">7450209</idno><idno type="url">http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7450209</idno><idno type="RBID">PMC:7450209</idno><idno type="doi">10.1016/j.grj.2017.06.001</idno><date when="2017">2017</date><idno type="wicri:Area/Pmc/Corpus">000190</idno><idno type="wicri:explorRef" wicri:stream="Pmc" wicri:step="Corpus" wicri:corpus="PMC">000190</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en" level="a" type="main">Soil legacy data rescue via GlobalSoilMap and other international and
national initiatives</title><author><name sortKey="Arrouays, Dominique" sort="Arrouays, Dominique" uniqKey="Arrouays D" first="Dominique" last="Arrouays">Dominique Arrouays</name><affiliation><nlm:aff id="aff0001">INRA, InfoSol Unit, 45075 Orleans, France</nlm:aff></affiliation></author><author><name sortKey="Leenaars, Johan G B" sort="Leenaars, Johan G B" uniqKey="Leenaars J" first="Johan G. B." last="Leenaars">Johan G. B. Leenaars</name><affiliation><nlm:aff>NONE</nlm:aff></affiliation></author><author><name sortKey="Richer De Forges, Anne C" sort="Richer De Forges, Anne C" uniqKey="Richer De Forges A" first="Anne C." last="Richer-De-Forges">Anne C. Richer-De-Forges</name><affiliation><nlm:aff id="aff0001">INRA, InfoSol Unit, 45075 Orleans, France</nlm:aff></affiliation></author><author><name sortKey="Adhikari, Koushik" sort="Adhikari, Koushik" uniqKey="Adhikari K" first="Koushik" last="Adhikari">Koushik Adhikari</name><affiliation><nlm:aff id="aff0003">Department of Agroecology, Faculty of science and technology, Aarhus University, Tjele, Denmark</nlm:aff></affiliation></author><author><name sortKey="Ballabio, Cristiano" sort="Ballabio, Cristiano" uniqKey="Ballabio C" first="Cristiano" last="Ballabio">Cristiano Ballabio</name><affiliation><nlm:aff id="aff0005">European Commission - DG JRC, Via E. Fermi, 2749, 21027 Ispra (VA), Italy</nlm:aff></affiliation></author><author><name sortKey="Greve, Mogens" sort="Greve, Mogens" uniqKey="Greve M" first="Mogens" last="Greve">Mogens Greve</name><affiliation><nlm:aff id="aff0003">Department of Agroecology, Faculty of science and technology, Aarhus University, Tjele, Denmark</nlm:aff></affiliation></author><author><name sortKey="Grundy, Mike" sort="Grundy, Mike" uniqKey="Grundy M" first="Mike" last="Grundy">Mike Grundy</name><affiliation><nlm:aff id="aff0006">CSIRO, Australia</nlm:aff></affiliation></author><author><name sortKey="Guerrero, Eliseo" sort="Guerrero, Eliseo" uniqKey="Guerrero E" first="Eliseo" last="Guerrero">Eliseo Guerrero</name><affiliation><nlm:aff id="aff0007">National Institute of Statistics and Geography, INEGI, Aguascalientes, Mexico</nlm:aff></affiliation></author><author><name sortKey="Hempel, Jon" sort="Hempel, Jon" uniqKey="Hempel J" first="Jon" last="Hempel">Jon Hempel</name><affiliation><nlm:aff id="aff0008">Retired. US department of Agriculture, Natural Resources Conservation Services, Lincoln, Nebraska, USA</nlm:aff></affiliation></author><author><name sortKey="Hengl, Tomislav" sort="Hengl, Tomislav" uniqKey="Hengl T" first="Tomislav" last="Hengl">Tomislav Hengl</name><affiliation><nlm:aff id="aff0002">ISRIC - World Soil Information, PO Box 353, 6700 AJ, Wageningen, The Netherlands</nlm:aff></affiliation></author><author><name sortKey="Heuvelink, Gerard" sort="Heuvelink, Gerard" uniqKey="Heuvelink G" first="Gerard" last="Heuvelink">Gerard Heuvelink</name><affiliation><nlm:aff id="aff0002">ISRIC - World Soil Information, PO Box 353, 6700 AJ, Wageningen, The Netherlands</nlm:aff></affiliation></author><author><name sortKey="Batjes, Niels" sort="Batjes, Niels" uniqKey="Batjes N" first="Niels" last="Batjes">Niels Batjes</name><affiliation><nlm:aff id="aff0002">ISRIC - World Soil Information, PO Box 353, 6700 AJ, Wageningen, The Netherlands</nlm:aff></affiliation></author><author><name sortKey="Carvalho, Eloi" sort="Carvalho, Eloi" uniqKey="Carvalho E" first="Eloi" last="Carvalho">Eloi Carvalho</name><affiliation><nlm:aff id="aff0002">ISRIC - World Soil Information, PO Box 353, 6700 AJ, Wageningen, The Netherlands</nlm:aff></affiliation></author><author><name sortKey="Hartemink, Alfred" sort="Hartemink, Alfred" uniqKey="Hartemink A" first="Alfred" last="Hartemink">Alfred Hartemink</name><affiliation><nlm:aff id="aff0009">University of Wisconsin, Department of Soil Science, Madison, USA</nlm:aff></affiliation></author><author><name sortKey="Hewitt, Alan" sort="Hewitt, Alan" uniqKey="Hewitt A" first="Alan" last="Hewitt">Alan Hewitt</name><affiliation><nlm:aff id="aff0010">Landcare research, Manaaki Whenua, New-Zealand</nlm:aff></affiliation></author><author><name sortKey="Hong, Suk Young" sort="Hong, Suk Young" uniqKey="Hong S" first="Suk-Young" last="Hong">Suk-Young Hong</name><affiliation><nlm:aff id="aff0011">Department of Agricultural Environment, National Academy of Agricultural Science, Suwon 441-707, Korea</nlm:aff></affiliation></author><author><name sortKey="Krasilnikov, Pavel" sort="Krasilnikov, Pavel" uniqKey="Krasilnikov P" first="Pavel" last="Krasilnikov">Pavel Krasilnikov</name><affiliation><nlm:aff id="aff0012">Eurasian Center for Food Security, Lomonosov Moscow State University, Moscow, Russia</nlm:aff></affiliation></author><author><name sortKey="Lagacherie, Philippe" sort="Lagacherie, Philippe" uniqKey="Lagacherie P" first="Philippe" last="Lagacherie">Philippe Lagacherie</name><affiliation><nlm:aff id="aff0013">INRA-IRD-Supagro, UMR Lisah, Montpellier, France</nlm:aff></affiliation></author><author><name sortKey="Lelyk, Glen" sort="Lelyk, Glen" uniqKey="Lelyk G" first="Glen" last="Lelyk">Glen Lelyk</name><affiliation><nlm:aff id="aff0014">Agriculture and Agri-Food Canada, Ottawa, Canada</nlm:aff></affiliation></author><author><name sortKey="Libohova, Zamir" sort="Libohova, Zamir" uniqKey="Libohova Z" first="Zamir" last="Libohova">Zamir Libohova</name><affiliation><nlm:aff id="aff0015">US department of Agriculture, Natural Resources Conservation Services, Lincoln Nebraska, USA</nlm:aff></affiliation></author><author><name sortKey="Lilly, Allan" sort="Lilly, Allan" uniqKey="Lilly A" first="Allan" last="Lilly">Allan Lilly</name><affiliation><nlm:aff id="aff0016">The James Hutton Institute, Craigiebuckler, Aberde<bold>l</bold>and, UK</nlm:aff></affiliation></author><author><name sortKey="Mcbratney, Alex" sort="Mcbratney, Alex" uniqKey="Mcbratney A" first="Alex" last="Mcbratney">Alex Mcbratney</name><affiliation><nlm:aff id="aff0017">University of Sydney, Sydney, Australia</nlm:aff></affiliation></author><author><name sortKey="Mckenzie, Neil" sort="Mckenzie, Neil" uniqKey="Mckenzie N" first="Neil" last="Mckenzie">Neil Mckenzie</name><affiliation><nlm:aff id="aff0006">CSIRO, Australia</nlm:aff></affiliation></author><author><name sortKey="Vasquez, Gustavo M" sort="Vasquez, Gustavo M" uniqKey="Vasquez G" first="Gustavo M." last="Vasquez">Gustavo M. Vasquez</name><affiliation><nlm:aff id="aff0018">Embrapa Solos, Rio de janeiro, Brazil</nlm:aff></affiliation></author><author><name sortKey="Leatitia Mulder, Vera" sort="Leatitia Mulder, Vera" uniqKey="Leatitia Mulder V" first="Vera" last="Leatitia Mulder">Vera Leatitia Mulder</name><affiliation><nlm:aff id="aff0019">Biogeochemistry and Earth System Modelling, Sciences de la Terre et de l’Environnement, Universite Libre de Bruxelles, Bruxelles, Belgium</nlm:aff></affiliation></author><author><name sortKey="Minasny, Budiman" sort="Minasny, Budiman" uniqKey="Minasny B" first="Budiman" last="Minasny">Budiman Minasny</name><affiliation><nlm:aff id="aff0017">University of Sydney, Sydney, Australia</nlm:aff></affiliation></author><author><name sortKey="Luca, Montanarella" sort="Luca, Montanarella" uniqKey="Luca M" first="Montanarella" last="Luca">Montanarella Luca</name><affiliation><nlm:aff id="aff0005">European Commission - DG JRC, Via E. Fermi, 2749, 21027 Ispra (VA), Italy</nlm:aff></affiliation></author><author><name sortKey="Odeh, Inakwu" sort="Odeh, Inakwu" uniqKey="Odeh I" first="Inakwu" last="Odeh">Inakwu Odeh</name><affiliation><nlm:aff id="aff0017">University of Sydney, Sydney, Australia</nlm:aff></affiliation></author><author><name sortKey="Padarian, Jose" sort="Padarian, Jose" uniqKey="Padarian J" first="Jose" last="Padarian">Jose Padarian</name><affiliation><nlm:aff id="aff0017">University of Sydney, Sydney, Australia</nlm:aff></affiliation></author><author><name sortKey="Poggio, Laura" sort="Poggio, Laura" uniqKey="Poggio L" first="Laura" last="Poggio">Laura Poggio</name><affiliation><nlm:aff id="aff0016">The James Hutton Institute, Craigiebuckler, Aberde<bold>l</bold>and, UK</nlm:aff></affiliation></author><author><name sortKey="Roudier, Pierre" sort="Roudier, Pierre" uniqKey="Roudier P" first="Pierre" last="Roudier">Pierre Roudier</name><affiliation><nlm:aff id="aff0010">Landcare research, Manaaki Whenua, New-Zealand</nlm:aff></affiliation></author><author><name sortKey="Saby, Nicolas" sort="Saby, Nicolas" uniqKey="Saby N" first="Nicolas" last="Saby">Nicolas Saby</name><affiliation><nlm:aff id="aff0001">INRA, InfoSol Unit, 45075 Orleans, France</nlm:aff></affiliation></author><author><name sortKey="Savin, Igor" sort="Savin, Igor" uniqKey="Savin I" first="Igor" last="Savin">Igor Savin</name><affiliation><nlm:aff id="aff0020">Dokutchaev Soil Science Institute, Moscow, Russia</nlm:aff></affiliation><affiliation><nlm:aff id="aff0052">People’s Friendship University of Russia (RUDN University), Moscow, Russia</nlm:aff></affiliation></author><author><name sortKey="Searle, Ross" sort="Searle, Ross" uniqKey="Searle R" first="Ross" last="Searle">Ross Searle</name><affiliation><nlm:aff id="aff0006">CSIRO, Australia</nlm:aff></affiliation></author><author><name sortKey="Solbovoy, Vladimir" sort="Solbovoy, Vladimir" uniqKey="Solbovoy V" first="Vladimir" last="Solbovoy">Vladimir Solbovoy</name><affiliation><nlm:aff id="aff0020">Dokutchaev Soil Science Institute, Moscow, Russia</nlm:aff></affiliation></author><author><name sortKey="Thompson, James" sort="Thompson, James" uniqKey="Thompson J" first="James" last="Thompson">James Thompson</name><affiliation><nlm:aff id="aff0021">West Virginia University, West Virginia, USA</nlm:aff></affiliation></author><author><name sortKey="Smith, Scott" sort="Smith, Scott" uniqKey="Smith S" first="Scott" last="Smith">Scott Smith</name><affiliation><nlm:aff id="aff0014">Agriculture and Agri-Food Canada, Ottawa, Canada</nlm:aff></affiliation></author><author><name sortKey="Sulaeman, Yiyi" sort="Sulaeman, Yiyi" uniqKey="Sulaeman Y" first="Yiyi" last="Sulaeman">Yiyi Sulaeman</name><affiliation><nlm:aff id="aff0022">Indonesian Center for Agricultural Land Resource Research and Development, Bogor, West Javal Indonesia</nlm:aff></affiliation></author><author><name sortKey="Vintila, Ruxandra" sort="Vintila, Ruxandra" uniqKey="Vintila R" first="Ruxandra" last="Vintila">Ruxandra Vintila</name><affiliation><nlm:aff id="aff0023">National Research and Development Institute for Soil Science, Agro-chemistry and Environment (ICPA), Bucharest, Romania</nlm:aff></affiliation></author><author><name sortKey="Rossel, Raphael Viscarra" sort="Rossel, Raphael Viscarra" uniqKey="Rossel R" first="Raphael Viscarra" last="Rossel">Raphael Viscarra Rossel</name><affiliation><nlm:aff id="aff0006">CSIRO, Australia</nlm:aff></affiliation></author><author><name sortKey="Wilson, Peter" sort="Wilson, Peter" uniqKey="Wilson P" first="Peter" last="Wilson">Peter Wilson</name><affiliation><nlm:aff id="aff0006">CSIRO, Australia</nlm:aff></affiliation></author><author><name sortKey="Zhang, Gan Lin" sort="Zhang, Gan Lin" uniqKey="Zhang G" first="Gan-Lin" last="Zhang">Gan-Lin Zhang</name><affiliation><nlm:aff id="aff0024">State Key Laboratory of Soil and Sustainable Agriculture, Institute of Soil Science, Chinese Academy of Sciences, Nanjing, China</nlm:aff></affiliation></author><author><name sortKey="Swerts, Martine" sort="Swerts, Martine" uniqKey="Swerts M" first="Martine" last="Swerts">Martine Swerts</name><affiliation><nlm:aff id="aff0025">Land and Soil Protection Service, Flemish Government, Brussels, Belgium</nlm:aff></affiliation></author><author><name sortKey="Oorts, Katrien" sort="Oorts, Katrien" uniqKey="Oorts K" first="Katrien" last="Oorts">Katrien Oorts</name><affiliation><nlm:aff id="aff0025">Land and Soil Protection Service, Flemish Government, Brussels, Belgium</nlm:aff></affiliation></author><author><name sortKey="Karklins, Aldis" sort="Karklins, Aldis" uniqKey="Karklins A" first="Aldis" last="Karklins">Aldis Karklins</name><affiliation><nlm:aff id="aff0026">Latvia Agricultural University, Jelgava, Latvia</nlm:aff></affiliation></author><author><name sortKey="Feng, Liu" sort="Feng, Liu" uniqKey="Feng L" first="Liu" last="Feng">Liu Feng</name><affiliation><nlm:aff id="aff0024">State Key Laboratory of Soil and Sustainable Agriculture, Institute of Soil Science, Chinese Academy of Sciences, Nanjing, China</nlm:aff></affiliation></author><author><name sortKey="Ibelles Navarro, Alexandro R" sort="Ibelles Navarro, Alexandro R" uniqKey="Ibelles Navarro A" first="Alexandro R." last="Ibelles Navarro">Alexandro R. Ibelles Navarro</name><affiliation><nlm:aff id="aff0007">National Institute of Statistics and Geography, INEGI, Aguascalientes, Mexico</nlm:aff></affiliation></author><author><name sortKey="Levin, Arkadiy" sort="Levin, Arkadiy" uniqKey="Levin A" first="Arkadiy" last="Levin">Arkadiy Levin</name><affiliation><nlm:aff id="aff0027">National Scientific Center, Institute for Soil Science and Agrochemistry Research, Kharkiv, Ukraine</nlm:aff></affiliation></author><author><name sortKey="Laktionova, Tetiana" sort="Laktionova, Tetiana" uniqKey="Laktionova T" first="Tetiana" last="Laktionova">Tetiana Laktionova</name><affiliation><nlm:aff id="aff0027">National Scientific Center, Institute for Soil Science and Agrochemistry Research, Kharkiv, Ukraine</nlm:aff></affiliation></author><author><name sortKey="Dell Cqua, Martin" sort="Dell Cqua, Martin" uniqKey="Dell Cqua M" first="Martin" last="Dell Cqua">Martin Dell Cqua</name><affiliation><nlm:aff id="aff0028">Sistema de Informacion Geografica, Direccion General de Recursos Naturales, Ministerio de Ganaderia Agricultura y Pesca, Montevideo, Uruguay</nlm:aff></affiliation></author><author><name sortKey="Suvannang, Nopmanee" sort="Suvannang, Nopmanee" uniqKey="Suvannang N" first="Nopmanee" last="Suvannang">Nopmanee Suvannang</name><affiliation><nlm:aff id="aff0029">Land Development Department, Land Development Department, Ladyao, Chatuchak, Bangkok, Thailand</nlm:aff></affiliation></author><author><name sortKey="Ruam, Waew" sort="Ruam, Waew" uniqKey="Ruam W" first="Waew" last="Ruam">Waew Ruam</name><affiliation><nlm:aff id="aff0029">Land Development Department, Land Development Department, Ladyao, Chatuchak, Bangkok, Thailand</nlm:aff></affiliation></author><author><name sortKey="Prasad, Jagdish" sort="Prasad, Jagdish" uniqKey="Prasad J" first="Jagdish" last="Prasad">Jagdish Prasad</name><affiliation><nlm:aff id="aff0030">National Bureau of Soil Survey and Land Use Planning (NBSSLUP) Indian Council of Agricultural Research (ICAR), Nagpur, Maharashtra, India</nlm:aff></affiliation></author><author><name sortKey="Patil, Nitin" sort="Patil, Nitin" uniqKey="Patil N" first="Nitin" last="Patil">Nitin Patil</name><affiliation><nlm:aff id="aff0030">National Bureau of Soil Survey and Land Use Planning (NBSSLUP) Indian Council of Agricultural Research (ICAR), Nagpur, Maharashtra, India</nlm:aff></affiliation></author><author><name sortKey="Husnjak, Stjepan" sort="Husnjak, Stjepan" uniqKey="Husnjak S" first="Stjepan" last="Husnjak">Stjepan Husnjak</name><affiliation><nlm:aff id="aff0031">Faculty of Agriculture, Deptartment of Soil Science, Zagreb, Croatia</nlm:aff></affiliation></author><author><name sortKey="Pasztor, Laszlo" sort="Pasztor, Laszlo" uniqKey="Pasztor L" first="Laszlo" last="Pasztor">Laszlo Pasztor</name><affiliation><nlm:aff id="aff0032">Research Institute for Soil Science and Agricultural Chemistry (RISSAC) of the. Hungarian Academy of Sciences, Budapest, Hungary</nlm:aff></affiliation></author><author><name sortKey="Okx, Joop" sort="Okx, Joop" uniqKey="Okx J" first="Joop" last="Okx">Joop Okx</name><affiliation><nlm:aff id="aff0033">Alterra - Wageningen UR, 6700 AA, Wageningen, The Netherlands</nlm:aff></affiliation></author><author><name sortKey="Hallet, Stephen" sort="Hallet, Stephen" uniqKey="Hallet S" first="Stephen" last="Hallet">Stephen Hallet</name><affiliation><nlm:aff id="aff0034">Cranfield University, Soils and Agrifood Institute, NSRI, United Kingdc</nlm:aff></affiliation></author><author><name sortKey="Keay, Caroline" sort="Keay, Caroline" uniqKey="Keay C" first="Caroline" last="Keay">Caroline Keay</name><affiliation><nlm:aff id="aff0034">Cranfield University, Soils and Agrifood Institute, NSRI, United Kingdc</nlm:aff></affiliation></author><author><name sortKey="Farewell, Timothy" sort="Farewell, Timothy" uniqKey="Farewell T" first="Timothy" last="Farewell">Timothy Farewell</name><affiliation><nlm:aff id="aff0034">Cranfield University, Soils and Agrifood Institute, NSRI, United Kingdc</nlm:aff></affiliation></author><author><name sortKey="Lilja, Harri" sort="Lilja, Harri" uniqKey="Lilja H" first="Harri" last="Lilja">Harri Lilja</name><affiliation><nlm:aff id="aff0035">MTT, Plant Production Research, Soil and Plant Nutrition, Jokioinen, Finland</nlm:aff></affiliation></author><author><name sortKey="Juilleret, Jerome" sort="Juilleret, Jerome" uniqKey="Juilleret J" first="Jerome" last="Juilleret">Jerome Juilleret</name><affiliation><nlm:aff id="aff0036">Luxembourg Institute of Science and Technology, Belvaux, Grand Duchy of Luxembourg</nlm:aff></affiliation></author><author><name sortKey="Marx, Simone" sort="Marx, Simone" uniqKey="Marx S" first="Simone" last="Marx">Simone Marx</name><affiliation><nlm:aff id="aff0036">Luxembourg Institute of Science and Technology, Belvaux, Grand Duchy of Luxembourg</nlm:aff></affiliation></author><author><name sortKey="Takata, Yusuke" sort="Takata, Yusuke" uniqKey="Takata Y" first="Yusuke" last="Takata">Yusuke Takata</name><affiliation><nlm:aff id="aff0037">Institute for Agro-Environmental Sciences, NARO, Tsukuba, Ibaraki, Japan</nlm:aff></affiliation></author><author><name sortKey="Kazuyuki, Yagi" sort="Kazuyuki, Yagi" uniqKey="Kazuyuki Y" first="Yagi" last="Kazuyuki">Yagi Kazuyuki</name><affiliation><nlm:aff id="aff0037">Institute for Agro-Environmental Sciences, NARO, Tsukuba, Ibaraki, Japan</nlm:aff></affiliation></author><author><name sortKey="Mansuy, Nicolas" sort="Mansuy, Nicolas" uniqKey="Mansuy N" first="Nicolas" last="Mansuy">Nicolas Mansuy</name><affiliation><nlm:aff id="aff0038">Nat Resources Canada, Canadian Forest Serv, Ste Foy, Quebec City, Canada</nlm:aff></affiliation></author><author><name sortKey="Panagos, Panos" sort="Panagos, Panos" uniqKey="Panagos P" first="Panos" last="Panagos">Panos Panagos</name><affiliation><nlm:aff id="aff0005">European Commission - DG JRC, Via E. Fermi, 2749, 21027 Ispra (VA), Italy</nlm:aff></affiliation></author><author><name sortKey="Van Liedekerke, Mark" sort="Van Liedekerke, Mark" uniqKey="Van Liedekerke M" first="Mark" last="Van Liedekerke">Mark Van Liedekerke</name><affiliation><nlm:aff id="aff0005">European Commission - DG JRC, Via E. Fermi, 2749, 21027 Ispra (VA), Italy</nlm:aff></affiliation></author><author><name sortKey="Skalsky, Rastislav" sort="Skalsky, Rastislav" uniqKey="Skalsky R" first="Rastislav" last="Skalsky">Rastislav Skalsky</name><affiliation><nlm:aff id="aff0039">Soil Science and Conservation Research Institute, Gagarinova 10, Bratislava, Slovakia</nlm:aff></affiliation></author><author><name sortKey="Sobocka, Jaroslava" sort="Sobocka, Jaroslava" uniqKey="Sobocka J" first="Jaroslava" last="Sobocka">Jaroslava Sobocka</name><affiliation><nlm:aff id="aff0039">Soil Science and Conservation Research Institute, Gagarinova 10, Bratislava, Slovakia</nlm:aff></affiliation></author><author><name sortKey="Kobza, Josef" sort="Kobza, Josef" uniqKey="Kobza J" first="Josef" last="Kobza">Josef Kobza</name><affiliation><nlm:aff id="aff0039">Soil Science and Conservation Research Institute, Gagarinova 10, Bratislava, Slovakia</nlm:aff></affiliation></author><author><name sortKey="Eftekhari, Kamran" sort="Eftekhari, Kamran" uniqKey="Eftekhari K" first="Kamran" last="Eftekhari">Kamran Eftekhari</name><affiliation><nlm:aff id="aff0040">Soil genesis and classification department, Soil and water research institute, Karaj, I. R. Iran</nlm:aff></affiliation></author><author><name sortKey="Kacem Alavipanah, Seyed" sort="Kacem Alavipanah, Seyed" uniqKey="Kacem Alavipanah S" first="Seyed" last="Kacem Alavipanah">Seyed Kacem Alavipanah</name><affiliation><nlm:aff id="aff0040">Soil genesis and classification department, Soil and water research institute, Karaj, I. R. Iran</nlm:aff></affiliation></author><author><name sortKey="Moussadek, Rachid" sort="Moussadek, Rachid" uniqKey="Moussadek R" first="Rachid" last="Moussadek">Rachid Moussadek</name><affiliation><nlm:aff id="aff0041">INRA, Rabat, Morocco</nlm:aff></affiliation></author><author><name sortKey="Badraoui, Mohamed" sort="Badraoui, Mohamed" uniqKey="Badraoui M" first="Mohamed" last="Badraoui">Mohamed Badraoui</name><affiliation><nlm:aff id="aff0041">INRA, Rabat, Morocco</nlm:aff></affiliation></author><author><name sortKey="Da Silva, Mayesse" sort="Da Silva, Mayesse" uniqKey="Da Silva M" first="Mayesse" last="Da Silva">Mayesse Da Silva</name><affiliation><nlm:aff id="aff0042">International Center for Tropical Agriculture (CIAT) - Headquarters and Regional Office for Latin America and the Caribbean, Cali, Colombia</nlm:aff></affiliation></author><author><name sortKey="Paterson, Garry" sort="Paterson, Garry" uniqKey="Paterson G" first="Garry" last="Paterson">Garry Paterson</name><affiliation><nlm:aff id="aff0043">ARC-Institute for Soil, Climate and Water, Pretoria, South Africa</nlm:aff></affiliation></author><author><name sortKey="Da Conceicao Gonsalves, Maria" sort="Da Conceicao Gonsalves, Maria" uniqKey="Da Conceicao Gonsalves M" first="Maria" last="Da Conceicao Gonsalves">Maria Da Conceicao Gonsalves</name><affiliation><nlm:aff id="aff0044">Instituto Nacional de Investigagao Agraria e Veterinaria, Laboratorio de Solos de Oeiras, Oeiras, Portugal</nlm:aff></affiliation></author><author><name sortKey="Theocharopoulos, Sid" sort="Theocharopoulos, Sid" uniqKey="Theocharopoulos S" first="Sid" last="Theocharopoulos">Sid Theocharopoulos</name><affiliation><nlm:aff id="aff0045">Soil Science Institute of Athens, NAGREF, Athens, Greece</nlm:aff></affiliation></author><author><name sortKey="Yemefack, Martin" sort="Yemefack, Martin" uniqKey="Yemefack M" first="Martin" last="Yemefack">Martin Yemefack</name><affiliation><nlm:aff id="aff0046">International Institute of Tropical Agriculture (IITA) and Institute of Agricultural Research for Development (IRAD), Yaounde, Cameroon</nlm:aff></affiliation></author><author><name sortKey="Tedou, Silatsa" sort="Tedou, Silatsa" uniqKey="Tedou S" first="Silatsa" last="Tedou">Silatsa Tedou</name><affiliation><nlm:aff id="aff0046">International Institute of Tropical Agriculture (IITA) and Institute of Agricultural Research for Development (IRAD), Yaounde, Cameroon</nlm:aff></affiliation></author><author><name sortKey="Vrscaj, Borut" sort="Vrscaj, Borut" uniqKey="Vrscaj B" first="Borut" last="Vrscaj">Borut Vrscaj</name><affiliation><nlm:aff id="aff0047">Agricultural Institute of Slovenia, Ljubljana, Slovenia</nlm:aff></affiliation></author><author><name sortKey="Grob, Urs" sort="Grob, Urs" uniqKey="Grob U" first="Urs" last="Grob">Urs Grob</name><affiliation><nlm:aff id="aff0048">NABODAT, Agroscope, Institut fur Nachhaltigkeitswissenschaft, INH, Zurich, Switzerland</nlm:aff></affiliation></author><author><name sortKey="Kozak, Josef" sort="Kozak, Josef" uniqKey="Kozak J" first="Josef" last="Kozak">Josef Kozak</name><affiliation><nlm:aff id="aff0049">Faculty of Agrobiology, Czech University of Life Sciences, Prague, Czech Republic</nlm:aff></affiliation></author><author><name sortKey="Boruvka, Lubos" sort="Boruvka, Lubos" uniqKey="Boruvka L" first="Lubos" last="Boruvka">Lubos Boruvka</name><affiliation><nlm:aff id="aff0049">Faculty of Agrobiology, Czech University of Life Sciences, Prague, Czech Republic</nlm:aff></affiliation></author><author><name sortKey="Dobos, Endre" sort="Dobos, Endre" uniqKey="Dobos E" first="Endre" last="Dobos">Endre Dobos</name><affiliation><nlm:aff id="aff0050">University of Miskolc, geography Institute, Miskolc-Egyetemvaros, Hungary</nlm:aff></affiliation></author><author><name sortKey="Taboada, Miguel" sort="Taboada, Miguel" uniqKey="Taboada M" first="Miguel" last="Taboada">Miguel Taboada</name><affiliation><nlm:aff id="aff0051">Institute of Soils, INTA, Buenos Aires, Argentina</nlm:aff></affiliation></author><author><name sortKey="Moretti, Lucas" sort="Moretti, Lucas" uniqKey="Moretti L" first="Lucas" last="Moretti">Lucas Moretti</name><affiliation><nlm:aff id="aff0051">Institute of Soils, INTA, Buenos Aires, Argentina</nlm:aff></affiliation></author><author><name sortKey="Rodriguez, Dario" sort="Rodriguez, Dario" uniqKey="Rodriguez D" first="Dario" last="Rodriguez">Dario Rodriguez</name><affiliation><nlm:aff id="aff0051">Institute of Soils, INTA, Buenos Aires, Argentina</nlm:aff></affiliation></author></analytic><series><title level="j">Georesj</title><idno type="eISSN">2214-2428</idno><imprint><date when="2017">2017</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><p>Legacy soil data have been produced over 70 years in nearly all countries of the world.
Unfortunately, data, information and knowledge are still currently fragmented and at risk
of getting lost if they remain in a paper format. To process this legacy data into
consistent, spatially explicit and continuous global soil information, data are being
rescued and compiled into databases. Thousands of soil survey reports and maps have been
scanned and made available online. The soil profile data reported by these data sources
have been captured and compiled into databases. The total number of soil profiles rescued
in the selected countries is about 800,000. Currently, data for 117, 000 profiles are
compiled and harmonized according to GlobalSoilMap specifications in a world level
database (WoSIS). The results presented at the country level are likely to be an
underestimate. The majority of soil data is still not rescued and this effort should be
pursued. The data have been used to produce soil property maps. We discuss the pro and
cons of top-down and bottom-up approaches to produce such maps and we stress their
complementarity. We give examples of success stories. The first global soil property maps
using rescued data were produced by a top-down approach and were released at a limited
resolution of 1km in 2014, followed by an update at a resolution of 250m in 2017. By the
end of 2020, we aim to deliver the first worldwide product that fully meets the
GlobalSoilMap specifications.</p></div></front><back><div1 type="bibliography"><listBibl><biblStruct><analytic><author><name sortKey="Hartemink, Ae" uniqKey="Hartemink A">AE Hartemink</name></author><author><name sortKey="Mcbratney, Ab" uniqKey="Mcbratney A">AB. McBratney</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Koch, A" uniqKey="Koch A">A Koch</name></author><author><name sortKey="Mcbratney, A" uniqKey="Mcbratney A">A McBratney</name></author><author><name sortKey="Adams, M" uniqKey="Adams M">M Adams</name></author><author><name sortKey="Field, D" uniqKey="Field D">D Field</name></author><author><name sortKey="Hill, R" uniqKey="Hill R">R Hill</name></author><author><name sortKey="Crawford, J" uniqKey="Crawford J">J Crawford</name></author><author><name sortKey="Minasny, B" uniqKey="Minasny B">B Minasny</name></author><author><name sortKey="Lal, R" uniqKey="Lal R">R Lal</name></author><author><name sortKey="Abbott, L" uniqKey="Abbott L">L Abbott</name></author><author><name sortKey="O Onnell, A" uniqKey="O Onnell A">A O’Donnell</name></author><author><name sortKey="Angers, D" uniqKey="Angers D">D Angers</name></author><author><name sortKey="Baldock, J" uniqKey="Baldock J">J Baldock</name></author><author><name sortKey="Barbier, E" uniqKey="Barbier E">E Barbier</name></author><author><name sortKey="Binkley, D" uniqKey="Binkley D">D Binkley</name></author><author><name sortKey="Parton, W" uniqKey="Parton W">W Parton</name></author><author><name sortKey="Wall, Dh" uniqKey="Wall D">DH Wall</name></author><author><name sortKey="Bird, M" uniqKey="Bird M">M Bird</name></author><author><name sortKey="Bouma, J" uniqKey="Bouma J">J Bouma</name></author><author><name sortKey="Chenu, C" uniqKey="Chenu C">C Chenu</name></author><author><name sortKey="Butler X0a Flora, C" uniqKey="Butler X0a Flora C">C Butler
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contrib-type="author"><name><surname>Juilleret</surname><given-names>Jerome</given-names></name><xref ref-type="aff" rid="aff0036">36</xref></contrib><contrib contrib-type="author"><name><surname>Marx</surname><given-names>Simone</given-names></name><xref ref-type="aff" rid="aff0036">36</xref></contrib><contrib contrib-type="author"><name><surname>Takata</surname><given-names>Yusuke</given-names></name><xref ref-type="aff" rid="aff0037">37</xref></contrib><contrib contrib-type="author"><name><surname>Kazuyuki</surname><given-names>Yagi</given-names></name><xref ref-type="aff" rid="aff0037">37</xref></contrib><contrib contrib-type="author"><name><surname>Mansuy</surname><given-names>Nicolas</given-names></name><xref ref-type="aff" rid="aff0038">38</xref></contrib><contrib contrib-type="author"><name><surname>Panagos</surname><given-names>Panos</given-names></name><xref ref-type="aff" rid="aff0005">5</xref></contrib><contrib contrib-type="author"><name><surname>Van Liedekerke</surname><given-names>Mark</given-names></name><xref ref-type="aff" rid="aff0005">5</xref></contrib><contrib contrib-type="author"><name><surname>Skalsky</surname><given-names>Rastislav</given-names></name><xref ref-type="aff" rid="aff0039">39</xref></contrib><contrib contrib-type="author"><name><surname>Sobocka</surname><given-names>Jaroslava</given-names></name><xref ref-type="aff" rid="aff0039">39</xref></contrib><contrib contrib-type="author"><name><surname>Kobza</surname><given-names>Josef</given-names></name><xref ref-type="aff" rid="aff0039">39</xref></contrib><contrib contrib-type="author"><name><surname>Eftekhari</surname><given-names>Kamran</given-names></name><xref ref-type="aff" rid="aff0040">40</xref></contrib><contrib contrib-type="author"><name><surname>Kacem Alavipanah</surname><given-names>Seyed</given-names></name><xref ref-type="aff" rid="aff0040">40</xref></contrib><contrib contrib-type="author"><name><surname>Moussadek</surname><given-names>Rachid</given-names></name><xref ref-type="aff" rid="aff0041">41</xref></contrib><contrib contrib-type="author"><name><surname>Badraoui</surname><given-names>Mohamed</given-names></name><xref ref-type="aff" rid="aff0041">41</xref></contrib><contrib contrib-type="author"><name><surname>Da Silva</surname><given-names>Mayesse</given-names></name><xref ref-type="aff" rid="aff0042">42</xref></contrib><contrib contrib-type="author"><name><surname>Paterson</surname><given-names>Garry</given-names></name><xref ref-type="aff" rid="aff0043">43</xref></contrib><contrib contrib-type="author"><name><surname>da Conceicao Gonsalves</surname><given-names>Maria</given-names></name><xref ref-type="aff" rid="aff0044">44</xref></contrib><contrib contrib-type="author"><name><surname>Theocharopoulos</surname><given-names>Sid</given-names></name><xref ref-type="aff" rid="aff0045">45</xref></contrib><contrib contrib-type="author"><name><surname>Yemefack</surname><given-names>Martin</given-names></name><xref ref-type="aff" rid="aff0046">46</xref></contrib><contrib contrib-type="author"><name><surname>Tedou</surname><given-names>Silatsa</given-names></name><xref ref-type="aff" rid="aff0046">46</xref></contrib><contrib contrib-type="author"><name><surname>Vrscaj</surname><given-names>Borut</given-names></name><xref ref-type="aff" rid="aff0047">47</xref></contrib><contrib contrib-type="author"><name><surname>Grob</surname><given-names>Urs</given-names></name><xref ref-type="aff" rid="aff0048">48</xref></contrib><contrib contrib-type="author"><name><surname>Kozak</surname><given-names>Josef</given-names></name><xref ref-type="aff" rid="aff0049">49</xref></contrib><contrib contrib-type="author"><name><surname>Boruvka</surname><given-names>Lubos</given-names></name><xref ref-type="aff" rid="aff0049">49</xref></contrib><contrib contrib-type="author"><name><surname>Dobos</surname><given-names>Endre</given-names></name><xref ref-type="aff" rid="aff0050">50</xref></contrib><contrib contrib-type="author"><name><surname>Taboada</surname><given-names>Miguel</given-names></name><xref ref-type="aff" rid="aff0051">51</xref></contrib><contrib contrib-type="author"><name><surname>Moretti</surname><given-names>Lucas</given-names></name><xref ref-type="aff" rid="aff0051">51</xref></contrib><contrib contrib-type="author"><name><surname>Rodriguez</surname><given-names>Dario</given-names></name><xref ref-type="aff" rid="aff0051">51</xref></contrib><aff id="aff0001"><label>1</label>INRA, InfoSol Unit, 45075 Orleans, France</aff><aff id="aff0002"><label>2</label>ISRIC - World Soil Information, PO Box 353, 6700 AJ, Wageningen, The Netherlands</aff><aff id="aff0003"><label>3</label>Department of Agroecology, Faculty of science and technology, Aarhus University, Tjele, Denmark</aff><aff id="aff0004"><label>4</label>Departamento de Suelos, National Agrarian University, La Molina, Peru</aff><aff id="aff0005"><label>5</label>European Commission - DG JRC, Via E. Fermi, 2749, 21027 Ispra (VA), Italy</aff><aff id="aff0006"><label>6</label>CSIRO, Australia</aff><aff id="aff0007"><label>7</label>National Institute of Statistics and Geography, INEGI, Aguascalientes, Mexico</aff><aff id="aff0008"><label>8</label>Retired. US department of Agriculture, Natural Resources Conservation Services, Lincoln, Nebraska, USA</aff><aff id="aff0009"><label>9</label>University of Wisconsin, Department of Soil Science, Madison, USA</aff><aff id="aff0010"><label>10</label>Landcare research, Manaaki Whenua, New-Zealand</aff><aff id="aff0011"><label>11</label>Department of Agricultural Environment, National Academy of Agricultural Science, Suwon 441-707, Korea</aff><aff id="aff0012"><label>12</label>Eurasian Center for Food Security, Lomonosov Moscow State University, Moscow, Russia</aff><aff id="aff0013"><label>13</label>INRA-IRD-Supagro, UMR Lisah, Montpellier, France</aff><aff id="aff0014"><label>14</label>Agriculture and Agri-Food Canada, Ottawa, Canada</aff><aff id="aff0015"><label>15</label>US department of Agriculture, Natural Resources Conservation Services, Lincoln Nebraska, USA</aff><aff id="aff0016"><label>16</label>The James Hutton Institute, Craigiebuckler, Aberde<bold>l</bold>and, UK</aff><aff id="aff0017"><label>17</label>University of Sydney, Sydney, Australia</aff><aff id="aff0018"><label>18</label>Embrapa Solos, Rio de janeiro, Brazil</aff><aff id="aff0019"><label>19</label>Biogeochemistry and Earth System Modelling, Sciences de la Terre et de l’Environnement, Universite Libre de Bruxelles, Bruxelles, Belgium</aff><aff id="aff0020"><label>20</label>Dokutchaev Soil Science Institute, Moscow, Russia</aff><aff id="aff0021"><label>21</label>West Virginia University, West Virginia, USA</aff><aff id="aff0022"><label>22</label>Indonesian Center for Agricultural Land Resource Research and Development, Bogor, West Javal Indonesia</aff><aff id="aff0023"><label>23</label>National Research and Development Institute for Soil Science, Agro-chemistry and Environment (ICPA), Bucharest, Romania</aff><aff id="aff0024"><label>24</label>State Key Laboratory of Soil and Sustainable Agriculture, Institute of Soil Science, Chinese Academy of Sciences, Nanjing, China</aff><aff id="aff0025"><label>25</label>Land and Soil Protection Service, Flemish Government, Brussels, Belgium</aff><aff id="aff0026"><label>26</label>Latvia Agricultural University, Jelgava, Latvia</aff><aff id="aff0027"><label>27</label>National Scientific Center, Institute for Soil Science and Agrochemistry Research, Kharkiv, Ukraine</aff><aff id="aff0028"><label>28</label>Sistema de Informacion Geografica, Direccion General de Recursos Naturales, Ministerio de Ganaderia Agricultura y Pesca, Montevideo, Uruguay</aff><aff id="aff0029"><label>29</label>Land Development Department, Land Development Department, Ladyao, Chatuchak, Bangkok, Thailand</aff><aff id="aff0030"><label>30</label>National Bureau of Soil Survey and Land Use Planning (NBSSLUP) Indian Council of Agricultural Research (ICAR), Nagpur, Maharashtra, India</aff><aff id="aff0031"><label>31</label>Faculty of Agriculture, Deptartment of Soil Science, Zagreb, Croatia</aff><aff id="aff0032"><label>32</label>Research Institute for Soil Science and Agricultural Chemistry (RISSAC) of the. Hungarian Academy of Sciences, Budapest, Hungary</aff><aff id="aff0033"><label>33</label>Alterra - Wageningen UR, 6700 AA, Wageningen, The Netherlands</aff><aff id="aff0034"><label>34</label>Cranfield University, Soils and Agrifood Institute, NSRI, United Kingdc</aff><aff id="aff0035"><label>35</label>MTT, Plant Production Research, Soil and Plant Nutrition, Jokioinen, Finland</aff><aff id="aff0036"><label>36</label>Luxembourg Institute of Science and Technology, Belvaux, Grand Duchy of Luxembourg</aff><aff id="aff0037"><label>37</label>Institute for Agro-Environmental Sciences, NARO, Tsukuba, Ibaraki, Japan</aff><aff id="aff0038"><label>38</label>Nat Resources Canada, Canadian Forest Serv, Ste Foy, Quebec City, Canada</aff><aff id="aff0039"><label>39</label>Soil Science and Conservation Research Institute, Gagarinova 10, Bratislava, Slovakia</aff><aff id="aff0040"><label>40</label>Soil genesis and classification department, Soil and water research institute, Karaj, I. R. Iran</aff><aff id="aff0041"><label>41</label>INRA, Rabat, Morocco</aff><aff id="aff0042"><label>42</label>International Center for Tropical Agriculture (CIAT) - Headquarters and Regional Office for Latin America and the Caribbean, Cali, Colombia</aff><aff id="aff0043"><label>43</label>ARC-Institute for Soil, Climate and Water, Pretoria, South Africa</aff><aff id="aff0044"><label>44</label>Instituto Nacional de Investigagao Agraria e Veterinaria, Laboratorio de Solos de Oeiras, Oeiras, Portugal</aff><aff id="aff0045"><label>45</label>Soil Science Institute of Athens, NAGREF, Athens, Greece</aff><aff id="aff0046"><label>46</label>International Institute of Tropical Agriculture (IITA) and Institute of Agricultural Research for Development (IRAD), Yaounde, Cameroon</aff><aff id="aff0047"><label>47</label>Agricultural Institute of Slovenia, Ljubljana, Slovenia</aff><aff id="aff0048"><label>48</label>NABODAT, Agroscope, Institut fur Nachhaltigkeitswissenschaft, INH, Zurich, Switzerland</aff><aff id="aff0049"><label>49</label>Faculty of Agrobiology, Czech University of Life Sciences, Prague, Czech Republic</aff><aff id="aff0050"><label>50</label>University of Miskolc, geography Institute, Miskolc-Egyetemvaros, Hungary</aff><aff id="aff0051"><label>51</label>Institute of Soils, INTA, Buenos Aires, Argentina</aff><aff id="aff0052"><label>52</label>People’s Friendship University of Russia (RUDN University), Moscow, Russia</aff></contrib-group><pub-date pub-type="epub"><month>12</month><year>2017</year></pub-date><volume>14</volume><issue>9</issue><fpage>1</fpage><lpage>19</lpage><history><date date-type="received"><day>16</day><month>12</month><year>2016</year></date><date date-type="rev-recd"><day>30</day><month>5</month><year>2017</year></date><date date-type="accepted"><day>05</day><month>6</month><year>2017</year></date></history><permissions><copyright-statement>© 2017</copyright-statement><copyright-year>2017</copyright-year><license license-type="open-access" xlink:href="http://creativecommons.org/licenses/by/4.0/"><license-p>All rights reserved. This is an Open Access article distributed under the terms
of the Creative Commons Attribution License (<ext-link ext-link-type="uri" xlink:href="http://creativecommons.org/licenses/by/4.0/">http://creativecommons.org/licenses/by/4.0/</ext-link>), which permits unrestricted
reuse, distribution, and reproduction in any medium, provided the original work is
properly cited.</license-p></license></permissions><abstract><p>Legacy soil data have been produced over 70 years in nearly all countries of the world.
Unfortunately, data, information and knowledge are still currently fragmented and at risk
of getting lost if they remain in a paper format. To process this legacy data into
consistent, spatially explicit and continuous global soil information, data are being
rescued and compiled into databases. Thousands of soil survey reports and maps have been
scanned and made available online. The soil profile data reported by these data sources
have been captured and compiled into databases. The total number of soil profiles rescued
in the selected countries is about 800,000. Currently, data for 117, 000 profiles are
compiled and harmonized according to GlobalSoilMap specifications in a world level
database (WoSIS). The results presented at the country level are likely to be an
underestimate. The majority of soil data is still not rescued and this effort should be
pursued. The data have been used to produce soil property maps. We discuss the pro and
cons of top-down and bottom-up approaches to produce such maps and we stress their
complementarity. We give examples of success stories. The first global soil property maps
using rescued data were produced by a top-down approach and were released at a limited
resolution of 1km in 2014, followed by an update at a resolution of 250m in 2017. By the
end of 2020, we aim to deliver the first worldwide product that fully meets the
GlobalSoilMap specifications.</p></abstract><kwd-group><kwd>Soil data rescue</kwd><kwd>legacy data</kwd><kwd>GlobalSoilMap</kwd></kwd-group></article-meta></front><body><sec sec-type="intro" id="sec1"><title>Introduction</title><p>Unprecedented demands are being placed on the world’s soil resources [<xref rid="cit0001" ref-type="bibr">1</xref>–<xref rid="cit0005" ref-type="bibr">5</xref>]. Responding to these challenging demands requires relevant, reliable and
applicable information [<xref rid="cit0006" ref-type="bibr">6</xref>–<xref rid="cit0007" ref-type="bibr">7</xref>]. Unfortunately, data, information and knowledge of
the world’s soil resources are currently fragmented and even at risk of being lost or
forgotten, due to the costs involved with maintaining analogue paper based soil data
holdings and archives and the physical deterioration or disintegration of these paper based
sources, especially in tropical conditions, together with the risk of the storage buildings
(fire, storm, war...). If this were to happen, it would be a disaster not only because soil
data are central to many of the major global issues the world is facing [<xref rid="cit0003" ref-type="bibr">3</xref>–<xref rid="cit0005" ref-type="bibr">5</xref>], but also because tremendous resources went into the efforts to collect and
analyze these data and comparable future soil data collection would certainly be cost
prohibitive in many countries and not justifiable without first having made optimal use of
earlier collected data.. Therefore, existing legacy and heritage soil survey data holdings
across the world are being rescued, compiled and processed into a common, consistent and
geographically contiguous applicable dataset of relevant soil properties covering the
planet’s land surface. The legacy soil data holdings, including tens of thousands of
published soil reports and soil maps, have been produced over 70 years by nearly all
countries and numerous institutions using different procedures, laboratory methods,
standards, scales, taxonomic classification systems and geo-referencing systems. They
represent a true myriad of primary data (millions of soil profile point observations) and
secondary data (derived properties and conventional soil polygon maps).</p><p>The GlobalSoilMap project [<xref rid="cit0006" ref-type="bibr">6</xref>–<xref rid="cit0008" ref-type="bibr">8</xref>] provides a collaborative scientific framework to
process this legacy soil data into consistent, spatially explicit and continuous global soil
information, freely accessible and in a gridded format at a high resolution, thus being both
globally complete and locally accurate and thus relevant from global to local applications.
The targeted information includes predicted values of selected key soil properties at 6
standard depth intervals (0-5; 5-15; 15-30; 30-60; 60-100; and 100-200 cm), at a global
scale on a 3 arc-second support grid (approximately 90x90 m) along with their uncertainties.
The key primary soil properties include clay, silt and sand content, coarse elements, pH,
soil organic carbon (SOC), effective cation exchange capacity (ECEC) and soil depth to
bedrock and effective root zone depth. Additional key properties include bulk density,
plant-available water holding capacity and electrical conductivity. The predictions and
estimations are generated using state-of-the- art Digital Soil Mapping techniques [<xref rid="cit0009" ref-type="bibr">9</xref>-%<xref rid="cit0010" ref-type="bibr">10</xref>].</p><p>Hence, obtaining the required amount of primary soil data to produce the above mentioned
products, by sampling through new soil surveys, would entail astronomic costs. In
comparison, it is relatively cost efficient to utilize existing soil data and make them
available and suitable for use. However, one of the major challenges is to integrate the
best available legacy data from various local and national sources. This challenge became
vital to the GlobalSoilMap project as it relies upon soil data rescue from a myriad of
fragmented analogue soil data holdings worldwide to a globally coherent and complete soil
information product.</p><p>Rescuing soil data includes three major steps: 1) the maintenance of libraries and holdings
including scanning of thousands and thousands of analogue paper reports and maps into
digital formats and assigning metadata to each object, allowing each object to be queryable,
accessible and available online. In addition, it is also ensuring the safety of the data
through proper backup of existing digital data entries. 2) compilation of the soil data
under a common standard from the rescued data sources. This is done by entry and collation
of legacy soil profiles and data (e.g. lineage, point location and year of recording, soil
classification and, for soil depth intervals, soil morphologic observations and soil
analytical measurements including values, units and methods used) from soil reports into a
dedicated soil profile database and by digitizing legacy soil maps from published paper soil
maps into a digital soil polygon database, followed by data standardization, harmonization
and quality control.</p><p>3) when compiled under a common standard the legacy data are then used to generate gridded
soil property maps within the GlobalSoilMap initiative according to the GlobalSoilMap
specifications [%<xref rid="cit0011" ref-type="bibr">11</xref>]. The gridded maps are
subsequently made freely available online to a wider user community. This community is
potentially very large and includes soil scientists and soil mappers, agronomists, climate
change modelers, biodiversity conservation specialists, economists, hydrologists, land-use
planners, governments and policy makers, among others.</p><p>In this paper we provide an overview of the recent soil data rescuing activities linked to
the GlobalSoilMap project and other international and national initiatives. Finally, we give
some examples of success stories at the world, continental and country level from selected
projects that achieved Soil Grids or final GlobalSoilMap products, thereby demonstrating the
importance of data rescue activities of existing soil data.</p></sec><sec id="sec2"><label>2</label><title>Digital Soil Mapping, by GlobalSoilMap and other initiatives, and its use of soil
profile point data</title><p>The GlobalSoilMap group was formed as an outgrowth of the International Union of Soil
Sciences (IUSS) Working Group for Digital Soil Mapping with the purpose of providing
consistently produced soil property information at 90m resolution across the world to aid in
solving some of the key environment and societal issues including food security, global
climate change, land degradation and carbon sequestration. The idea for the project was
initiated at the 2006 IUSS Working Group for Digital Soil Mapping held in Rio de Janeiro,
Brazil. A meeting of the working group to more formalize the concept was then held at the
World Congress of Soil Science in Philadelphia shortly after the Rio meeting. In December of
2006, a meeting was called by key members of the soil science community at the Earth
Institute at Columbia University to further discuss the concept. From these discussions, a
foundational concept for how a global project could be structured was formulated. Over the
next few years progress included signing a GlobalSoilMap consortium agreement, securing
funding for producing data in Sub Saharan Africa, thanks to a grant from the Bill and
Melinda Gates’ Fundation, and producing project standards and specifications. The
first international conference on GlobalSoilMap was held in Orleans, France in 2013. In
2016, the IUSS established a GlobalSoilMap working group under the IUSS commission 1.5
‘Pedometrics’.</p><p>Dissemination of soil profile data, at point locations, is in many countries strongly
hampered by legislations concerning soil privacy and ownership, except for increasing
numbers of countries and institutions which acknowledge the importance for sharing the data
and results from publicly funded works (e.g., United States Department of
Agriculture-Natural Resources Conservation Service (USDA-NRCS), ISRIC (International Soil
Reference and Information Centre- World Soil Information, the European Soil Data Centre
(ESDAC). A way to overcome this problem, which the project since the beginning aimed for, is
to develop a globally distributed soil profiles database where the data are being managed by
the data owners and made online and queryable through interoperable standards as defined by
the community and in process of development. Another way is to compile and share the
relatively still limited number of publicly available soil profile data and use those for
global mapping. A third alternative is to only share and distribute the final soil data
products, containing the predicted soil properties in a gridded format, without giving
access to the original soil profile point data that was used for these predictions. The
final GlobalSoilMap product represents an updateable outcome i.e. when new or additional
soil profile data are available a new updated soil map can be quickly produced thus
continuously improving the accuracy of the collaborative product.</p><p>The final product will be a globally and harmonized distributed grid map. However, besides
data availability, achieving these global results would require distributed datasets to be
harmonized at national, continental and global levels [e.g. <xref rid="cit0012" ref-type="bibr">12</xref>–<xref rid="cit0014" ref-type="bibr">14</xref>]. In order to
achieve this goal the GlobalSoilMap project developed guidelines and specifications [%<xref rid="cit0011" ref-type="bibr">11</xref>]. Distributed and strong computational capacities
are needed to generate the maps at aimed for resolution.</p><p>Regardless of being national, continental and/or global, the following data rescue and grid
map production steps are generally necessary, including references to GlobalSoilMap specific
activities:</p><list list-type="simple"><list-item><label>1</label><p>Identify and rescue legacy soil reports and maps and make digital scans with metadata
publicly available (analogue carriers of data),</p></list-item><list-item><label>2a</label><p>Capture and rescue legacy soil profile data from soil reports into digital soil point
datasets, including geo-referencing,</p></list-item><list-item><label>2b</label><p>Capture and rescue legacy soil maps into digital soil polygon datasets (i.e., build a
vector dataset by vectorization of scanned (rasterized) data in a GIS),</p></list-item><list-item><label>3a</label><p>Transform the original data in a common standard, for defining the soil property, the
soil property measurement method and the units of expression,</p></list-item><list-item><label>3b</label><p>Transform the standardized data from the original sequences of depth intervals to the
standard sequence of soil depth intervals as defined by the GlobalSoilMap
specifications,</p></list-item><list-item><label>4</label><p>Harmonize the data from the procedures and methods originally used to data according to
reference procedures and methods conforming to the GlobalSoilMap specifications,</p></list-item><list-item><label>5</label><p>Assemble spatially exhaustive co-variates (e.g. from digital elevation models (DEM),
remote sensing imagery, geological maps, vegetation maps; legacy soil type maps)
including co-variates at a 3 arc-second resolution required for meeting GlobalSoilMap
specifications,</p></list-item><list-item><label>6</label><p>Develop digital soil mapping models to predict soil properties, according to
GlobalSoilMap specifications on a 3 arc-second grid.</p></list-item><list-item><label>7</label><p>Produce the maps including maps of the uncertainties,</p></list-item><list-item><label>8</label><p>Assess accuracy and validate the predicted soil property maps,</p></list-item><list-item><label>9</label><p>Deliver soil grid data products according to the GlobalSoilMap specifications.</p></list-item></list><p>A general framework has been proposed by Minasny and McBratney [%<xref rid="cit0015" ref-type="bibr">15</xref>] and the complete process is fully described in the GlobalSoilMap
specifications [%<xref rid="cit0011" ref-type="bibr">11</xref>] and in a synthesis paper
[<xref rid="cit0007" ref-type="bibr">7</xref>]. In this paper, we illustrate steps 1 to 4
and the efforts made for rescuing the primary soil data; we then provide a few examples of
success stories achieving final products derived from the rescued primary data (steps 5-8)
and we discuss the potential of future soil profile data rescue and the main issues related
to their 9.use.</p></sec><sec id="sec3"><label>3</label><title>Synthesis of legacy soil profile data</title><p>Table 1 illustrates the progress in soil profile data rescue at various geographical levels
from 2009 to 2015. This tremendous effort in soil profile data rescue resulted in nearly
doubling the number of soil profiles stored in country databases. At the world level,
(ISRIC- World Soil Information Service (WoSIS) database), the increase is tenfold [16-18;
134] and those data are, for the GlobalSoilMap properties, all standardized and available at
<ext-link ext-link-type="uri" xlink:href="http://www.isric.org/explore/wosis/accessing-wosis-derived-datasets">www.isric.org/explore/wosis/accessing-wosis-derived-datasets</ext-link>. In absolute
terms, the total of soil profiles existing and stored in the selected countries databases is
obviously much higher and is currently about 800,000. Regrettably, large numbers of soil
profiles stored in many country databases are yet not standardized and harmonized according
to a global standard and are not shared. Note that the numbers given in the table of soil
profiles at the world level, at the continental level (ISRIC [%<xref rid="cit0016" ref-type="bibr">16</xref>-%<xref rid="cit0018" ref-type="bibr">18</xref>], Sub-Saharan
Africa [%<xref rid="cit0019" ref-type="bibr">19</xref>-%<xref rid="cit0021" ref-type="bibr">21</xref>], Latin America and Caribbean [%<xref rid="cit0022" ref-type="bibr">22</xref>],
European Union [%<xref rid="cit0023" ref-type="bibr">23</xref>-%<xref rid="cit0026" ref-type="bibr">26</xref>]) and at the country level cannot be summed together. Large
numbers of profiles compiled in the world database originate from the continental databases
which originate to large extents from the national ones and from national survey reports.
The difference in the number of data in the WoSIS database (World Soil Information Service)
and the continental databases compared to the selected countries data is likely due to the
time and capacity needed to identify the data sources and to capture, translate and
harmonize the data, which is a job most efficiently and effectively done by the national
data holders. Indeed, as stated by Rossiter [%<xref rid="cit0027" ref-type="bibr">27</xref>], much of the data are still proprietary and regrettably not generally accessible
and unfortunately the question of open access to primary soil data is not resolved.
Nevertheless, considerable successful efforts have been made since 2009 by ISRIC to rescue
and add value to soil data in many countries where quality soil data have been generated and
reported over the years, but where the data infrastructure is not up to standards and the
data is in great danger of being lost (e.g. Sub-Saharan countries, [%<xref rid="cit0019" ref-type="bibr">19</xref>-%<xref rid="cit0021" ref-type="bibr">21</xref>]). Overall, we
observe large discrepancies between countries, either in the total number of soil profiles
compiled or in the efforts put in place in data rescuing, over the years 2009 and 2015
[%<xref rid="cit0028" ref-type="bibr">28</xref>-%<xref rid="cit0094" ref-type="bibr">94</xref>]. <xref rid="t0002" ref-type="table">Table 2</xref> provides the links to
databases when they are available on the web. Database models and management systems are
described by Batjes [17, 18, 134] at the world level, by Leenaars et al., 19,20] for Africa
and by Hiederer [%<xref rid="cit0023" ref-type="bibr">23</xref>] and Hollis et al., [%<xref rid="cit0025" ref-type="bibr">25</xref>] for Europe.</p><p>Table 1</p><p>List of soil profile data rescue between 2009 and 2015 for selected countries and at world
and continetal level</p><table-wrap orientation="portrait" id="d38e1221" position="float"><label>Tab 1.1</label><caption><p>Global and continental datadanses</p></caption><table frame="hsides" rules="groups"><thead valign="bottom"><tr><th align="left" rowspan="1" colspan="1">Geographical level</th><th align="left" rowspan="1" colspan="1">area in km<sup>2</sup></th><th align="left" rowspan="1" colspan="1">Number of soil profiles in 2009</th><th align="left" rowspan="1" colspan="1">Number of soil profiles in 2015</th><th align="left" rowspan="1" colspan="1">number of new profiles</th><th align="left" rowspan="1" colspan="1">% of increase</th><th align="left" rowspan="1" colspan="1">key references</th></tr></thead><tbody valign="top"><tr><td align="left" rowspan="1" colspan="1">World</td><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1"></td></tr><tr><td align="left" rowspan="1" colspan="1">World</td><td align="center" rowspan="1" colspan="1">130 000 000</td><td align="center" rowspan="1" colspan="1">10 250</td><td align="center" rowspan="1" colspan="1">117 446</td><td align="center" rowspan="1" colspan="1">107 196</td><td align="center" rowspan="1" colspan="1">1 046</td><td align="center" rowspan="1" colspan="1">[%<xref rid="cit0016" ref-type="bibr">16</xref>-%<xref rid="cit0018" ref-type="bibr">18</xref>]</td></tr><tr><td align="left" rowspan="1" colspan="1">Continental</td><td align="center" rowspan="1" colspan="1"></td><td align="center" rowspan="1" colspan="1"></td><td align="center" rowspan="1" colspan="1"></td><td align="center" rowspan="1" colspan="1"></td><td align="center" rowspan="1" colspan="1"></td></tr><tr><td align="left" rowspan="1" colspan="1">Sub-Saharian Africa</td><td align="center" rowspan="1" colspan="1">23 589 596</td><td align="center" rowspan="1" colspan="1">0</td><td align="center" rowspan="1" colspan="1">18 532</td><td align="center" rowspan="1" colspan="1">18 532</td><td align="center" rowspan="1" colspan="1">uncalculable</td><td align="center" rowspan="1" colspan="1">[%<xref rid="cit0019" ref-type="bibr">19</xref>-%<xref rid="cit0021" ref-type="bibr">21</xref>]</td></tr><tr><td align="left" rowspan="1" colspan="1">Latin America and carabean</td><td align="center" rowspan="1" colspan="1">20 199 984 sum of the 20 countries in SISLAC</td><td align="center" rowspan="1" colspan="1">unknown</td><td align="center" rowspan="1" colspan="1">6 099</td><td align="center" rowspan="1" colspan="1">unknown</td><td align="center" rowspan="1" colspan="1">uncalculable</td><td align="center" rowspan="1" colspan="1">[22]</td></tr><tr><td align="left" rowspan="1" colspan="1">European Union</td><td align="center" rowspan="1" colspan="1">4 500 000</td><td align="center" rowspan="1" colspan="1"></td><td align="center" rowspan="1" colspan="1"></td><td align="center" rowspan="1" colspan="1"></td><td align="center" rowspan="1" colspan="1"></td><td align="center" rowspan="1" colspan="1"></td></tr><tr><td align="center" rowspan="1" colspan="1">Europe (18 countries: Albania, Belgium, Denmark, Denmark, France,
Greece, Hungary, Italy, Italy, Slovak Republic, Luxembourg, Netherlands, Portugal,
Romania, United Kingdom, Slovenia, Spain, Switzerland)</td><td align="center" rowspan="1" colspan="1">3 000 000 (the extension of the participating countries)</td><td align="center" rowspan="1" colspan="1">560</td><td align="center" rowspan="1" colspan="1">560</td><td align="center" rowspan="1" colspan="1">0</td><td align="center" rowspan="1" colspan="1">0</td><td align="center" rowspan="1" colspan="1">[23]</td></tr><tr><td align="left" rowspan="1" colspan="1">Europe (18 countries: Albania, Belgium, Denmark, Denmark, France,
Greece, Hungary, Italy, Italy, Slovak Republic, Luxembourg, Netherlands, Portugal,
Romania, United Kingdom, Slovenia, Spain,Switzerland)</td><td align="center" rowspan="1" colspan="1">3 000 000 (the extension of the participating countries)</td><td align="center" rowspan="1" colspan="1">588</td><td align="center" rowspan="1" colspan="1">588</td><td align="center" rowspan="1" colspan="1">0</td><td align="center" rowspan="1" colspan="1">0</td><td align="center" rowspan="1" colspan="1">[<xref rid="cit0024" ref-type="bibr">24</xref>]</td></tr><tr><td align="left" rowspan="1" colspan="1">Europe (19 Countries: Belgium and Luxembourg, Denmark, England Wales
Scotland, Finland, Germany, Italy, Netherlands, Portugal, France, Ireland, Bulgaria,
Estonia, France, Hungary, Ireland, Romania, Slovakia and Switzerland)</td><td align="center" rowspan="1" colspan="1">3 000 000 (the extension of the participating countries)3</td><td align="center" rowspan="1" colspan="1">1 897</td><td align="center" rowspan="1" colspan="1">1 897</td><td align="center" rowspan="1" colspan="1">0</td><td align="center" rowspan="1" colspan="1">0</td><td align="center" rowspan="1" colspan="1">[25]</td></tr><tr><td align="left" rowspan="1" colspan="1">Europe (28 Countres: EU + Norway, Albania, Switzerland)</td><td align="center" rowspan="1" colspan="1">4 500 000 (whole EU plus Norway, Albania, Switzerland)</td><td align="center" rowspan="1" colspan="1">1 078</td><td align="center" rowspan="1" colspan="1">1 078</td><td align="center" rowspan="1" colspan="1">0</td><td align="center" rowspan="1" colspan="1">0</td><td align="center" rowspan="1" colspan="1">[26]</td></tr></tbody></table></table-wrap><table-wrap orientation="portrait" id="d38e1393" position="float"><label>Tab 1.2</label><caption><p>Countries databases</p></caption><table frame="hsides" rules="groups"><thead valign="bottom"><tr><th align="left" rowspan="1" colspan="1">Geographical level</th><th align="left" rowspan="1" colspan="1">area in km<sup>2</sup></th><th align="left" rowspan="1" colspan="1">Number of soil profiles in 2009</th><th align="left" rowspan="1" colspan="1">Number of soil profiles in 2015</th><th align="left" rowspan="1" colspan="1">number of new profiles</th><th align="left" rowspan="1" colspan="1">% of increase</th><th align="left" rowspan="1" colspan="1">key references</th></tr></thead><tbody valign="top"><tr><td align="left" rowspan="1" colspan="1">Argentina</td><td align="center" rowspan="1" colspan="1">2 780 400</td><td align="center" rowspan="1" colspan="1">0</td><td align="center" rowspan="1" colspan="1">2200</td><td align="center" rowspan="1" colspan="1">2200</td><td align="center" rowspan="1" colspan="1">0</td><td align="center" rowspan="1" colspan="1"></td></tr><tr><td align="left" rowspan="1" colspan="1">Australia</td><td align="center" rowspan="1" colspan="1">7 692 060</td><td align="center" rowspan="1" colspan="1">281 202</td><td align="center" rowspan="1" colspan="1">290 000</td><td align="center" rowspan="1" colspan="1">798</td><td align="center" rowspan="1" colspan="1">0</td><td align="center" rowspan="1" colspan="1">[<xref rid="cit0028" ref-type="bibr">28</xref>–<xref rid="cit0029" ref-type="bibr">29</xref>]</td></tr><tr><td align="left" rowspan="1" colspan="1">Belgium</td><td align="center" rowspan="1" colspan="1">30 528</td><td align="center" rowspan="1" colspan="1">7 020</td><td align="center" rowspan="1" colspan="1">7766</td><td align="center" rowspan="1" colspan="1">746</td><td align="center" rowspan="1" colspan="1">11</td><td align="center" rowspan="1" colspan="1">[<xref rid="cit0030" ref-type="bibr">30</xref>]</td></tr><tr><td align="left" rowspan="1" colspan="1">Cameroon</td><td align="center" rowspan="1" colspan="1">475 000</td><td align="center" rowspan="1" colspan="1">unknown</td><td align="center" rowspan="1" colspan="1">1040</td><td align="center" rowspan="1" colspan="1">unknown</td><td align="center" rowspan="1" colspan="1">uncalculable</td><td align="center" rowspan="1" colspan="1"></td></tr><tr><td align="left" rowspan="1" colspan="1">Chile</td><td align="center" rowspan="1" colspan="1">756 102</td><td align="center" rowspan="1" colspan="1">0</td><td align="center" rowspan="1" colspan="1">400</td><td align="center" rowspan="1" colspan="1">400</td><td align="center" rowspan="1" colspan="1"></td><td align="center" rowspan="1" colspan="1">[<xref rid="cit0031" ref-type="bibr">31</xref>]</td></tr><tr><td align="left" rowspan="1" colspan="1">China</td><td align="center" rowspan="1" colspan="1">9 629 091</td><td align="center" rowspan="1" colspan="1">23 000</td><td align="center" rowspan="1" colspan="1">25 300</td><td align="center" rowspan="1" colspan="1">2300</td><td align="center" rowspan="1" colspan="1">10</td><td align="center" rowspan="1" colspan="1">[<xref rid="cit0032" ref-type="bibr">32</xref>]</td></tr><tr><td align="left" rowspan="1" colspan="1">Brazil</td><td align="center" rowspan="1" colspan="1">8 515 767</td><td align="center" rowspan="1" colspan="1">unknown</td><td align="center" rowspan="1" colspan="1">6 456</td><td align="center" rowspan="1" colspan="1">unknown</td><td align="center" rowspan="1" colspan="1">uncalculable</td><td align="center" rowspan="1" colspan="1">[<xref rid="cit0033" ref-type="bibr">33</xref>–<xref rid="cit0036" ref-type="bibr">36</xref>]</td></tr><tr><td align="left" rowspan="1" colspan="1">Canada</td><td align="center" rowspan="1" colspan="1">9 984 670</td><td align="center" rowspan="1" colspan="1">4 050</td><td align="center" rowspan="1" colspan="1">8 615</td><td align="center" rowspan="1" colspan="1">4 565</td><td align="center" rowspan="1" colspan="1">113</td><td align="center" rowspan="1" colspan="1">[<xref rid="cit0037" ref-type="bibr">37</xref>–<xref rid="cit0039" ref-type="bibr">39</xref>]</td></tr><tr><td align="left" rowspan="1" colspan="1">Mexico</td><td align="center" rowspan="1" colspan="1">1 964 375</td><td align="center" rowspan="1" colspan="1">22 430</td><td align="center" rowspan="1" colspan="1">22 430</td><td align="center" rowspan="1" colspan="1">0</td><td align="center" rowspan="1" colspan="1">0</td><td align="center" rowspan="1" colspan="1">[<xref rid="cit0040" ref-type="bibr">40</xref>]</td></tr><tr><td align="left" rowspan="1" colspan="1">France (mainland)</td><td align="center" rowspan="1" colspan="1">551 500</td><td align="center" rowspan="1" colspan="1">37 937</td><td align="center" rowspan="1" colspan="1">64 123</td><td align="center" rowspan="1" colspan="1">26 186</td><td align="center" rowspan="1" colspan="1">69</td><td align="center" rowspan="1" colspan="1">[<xref rid="cit0041" ref-type="bibr">41</xref>–<xref rid="cit0042" ref-type="bibr">42</xref>]</td></tr><tr><td align="left" rowspan="1" colspan="1">France (French west Indies)</td><td align="center" rowspan="1" colspan="1">2 835</td><td align="center" rowspan="1" colspan="1">148</td><td align="center" rowspan="1" colspan="1">682</td><td align="center" rowspan="1" colspan="1">554</td><td align="center" rowspan="1" colspan="1">374</td><td align="center" rowspan="1" colspan="1">[<xref rid="cit0043" ref-type="bibr">43</xref>]</td></tr><tr><td align="left" rowspan="1" colspan="1">France (La Réunion)</td><td align="center" rowspan="1" colspan="1">2 512</td><td align="center" rowspan="1" colspan="1">0</td><td align="center" rowspan="1" colspan="1">256</td><td align="center" rowspan="1" colspan="1">256</td><td align="center" rowspan="1" colspan="1">uncalculable</td><td align="center" rowspan="1" colspan="1">[<xref rid="cit0043" ref-type="bibr">43</xref>]</td></tr><tr><td align="left" rowspan="1" colspan="1">France (Guyana)</td><td align="center" rowspan="1" colspan="1">91 000</td><td align="center" rowspan="1" colspan="1">0</td><td align="center" rowspan="1" colspan="1">256</td><td align="center" rowspan="1" colspan="1">256</td><td align="center" rowspan="1" colspan="1">uncalculable</td><td align="center" rowspan="1" colspan="1">[<xref rid="cit0043" ref-type="bibr">43</xref>]</td></tr><tr><td align="left" rowspan="1" colspan="1">Slovakia</td><td align="center" rowspan="1" colspan="1">49 035</td><td align="center" rowspan="1" colspan="1">1 871</td><td align="center" rowspan="1" colspan="1">18 171</td><td align="center" rowspan="1" colspan="1">0</td><td align="center" rowspan="1" colspan="1">0</td><td align="center" rowspan="1" colspan="1">[<xref rid="cit0092" ref-type="bibr">92</xref>]</td></tr><tr><td align="left" rowspan="1" colspan="1">Denmark (Greenland)</td><td align="center" rowspan="1" colspan="1">2 166 086</td><td align="center" rowspan="1" colspan="1">0</td><td align="center" rowspan="1" colspan="1">650</td><td align="center" rowspan="1" colspan="1">650</td><td align="center" rowspan="1" colspan="1">uncalculable</td><td align="center" rowspan="1" colspan="1"></td></tr><tr><td align="left" rowspan="1" colspan="1">(Denmark (mainland)</td><td align="center" rowspan="1" colspan="1">43 094</td><td align="center" rowspan="1" colspan="1">2 250</td><td align="center" rowspan="1" colspan="1">12 456</td><td align="center" rowspan="1" colspan="1">10 206</td><td align="center" rowspan="1" colspan="1">454</td><td align="center" rowspan="1" colspan="1">[<xref rid="cit0044" ref-type="bibr">44</xref>–<xref rid="cit0045" ref-type="bibr">45</xref>]</td></tr><tr><td align="left" rowspan="1" colspan="1">Croatia</td><td align="center" rowspan="1" colspan="1">56 594</td><td align="center" rowspan="1" colspan="1">6 500</td><td align="center" rowspan="1" colspan="1">6 500</td><td align="center" rowspan="1" colspan="1">0</td><td align="center" rowspan="1" colspan="1">0</td><td align="center" rowspan="1" colspan="1"></td></tr><tr><td align="left" rowspan="1" colspan="1">Russia</td><td align="center" rowspan="1" colspan="1">17 098 242</td><td align="center" rowspan="1" colspan="1">0</td><td align="center" rowspan="1" colspan="1">863</td><td align="center" rowspan="1" colspan="1">863</td><td align="center" rowspan="1" colspan="1">uncalculable</td><td align="center" rowspan="1" colspan="1">[<xref rid="cit0046" ref-type="bibr">46</xref>]</td></tr><tr><td align="left" rowspan="1" colspan="1">Indonesia</td><td align="center" rowspan="1" colspan="1">1 910 931</td><td align="center" rowspan="1" colspan="1">0</td><td align="center" rowspan="1" colspan="1">30 867</td><td align="center" rowspan="1" colspan="1">30 867</td><td align="center" rowspan="1" colspan="1">uncalculable</td><td align="center" rowspan="1" colspan="1">[<xref rid="cit0047" ref-type="bibr">47</xref>]</td></tr><tr><td align="left" rowspan="1" colspan="1">Portugal</td><td align="center" rowspan="1" colspan="1">92 090</td><td align="center" rowspan="1" colspan="1">0</td><td align="center" rowspan="1" colspan="1">3 470</td><td align="center" rowspan="1" colspan="1">3 470</td><td align="center" rowspan="1" colspan="1">uncalculable</td><td align="center" rowspan="1" colspan="1">[<xref rid="cit0048" ref-type="bibr">48</xref>]</td></tr><tr><td align="left" rowspan="1" colspan="1">Scotland</td><td align="center" rowspan="1" colspan="1">77 800</td><td align="center" rowspan="1" colspan="1">14 722</td><td align="center" rowspan="1" colspan="1">14 722</td><td align="center" rowspan="1" colspan="1">0</td><td align="center" rowspan="1" colspan="1">0</td><td align="center" rowspan="1" colspan="1">[<xref rid="cit0093" ref-type="bibr">93</xref>–<xref rid="cit0094" ref-type="bibr">94</xref>]</td></tr><tr><td align="left" rowspan="1" colspan="1">Thailand</td><td align="center" rowspan="1" colspan="1">513 120</td><td align="center" rowspan="1" colspan="1">244</td><td align="center" rowspan="1" colspan="1">300</td><td align="center" rowspan="1" colspan="1">66</td><td align="center" rowspan="1" colspan="1">27</td><td align="center" rowspan="1" colspan="1"></td></tr><tr><td align="left" rowspan="1" colspan="1">USA</td><td align="center" rowspan="1" colspan="1">9 629 091</td><td align="center" rowspan="1" colspan="1">37 937</td><td align="center" rowspan="1" colspan="1">64 123</td><td align="center" rowspan="1" colspan="1">26 186</td><td align="center" rowspan="1" colspan="1">69</td><td align="center" rowspan="1" colspan="1">[<xref rid="cit0049" ref-type="bibr">49</xref>–<xref rid="cit0055" ref-type="bibr">55</xref>]</td></tr><tr><td align="center" rowspan="1" colspan="1">South Korea</td><td align="center" rowspan="1" colspan="1">99 828</td><td align="center" rowspan="1" colspan="1">390</td><td align="center" rowspan="1" colspan="1">405</td><td align="center" rowspan="1" colspan="1">15</td><td align="center" rowspan="1" colspan="1">4</td><td align="center" rowspan="1" colspan="1">[<xref rid="cit0056" ref-type="bibr">56</xref>–<xref rid="cit0058" ref-type="bibr">58</xref>]</td></tr><tr><td align="left" rowspan="1" colspan="1">The Netherlands</td><td align="center" rowspan="1" colspan="1">37 354</td><td align="center" rowspan="1" colspan="1">7 859</td><td align="center" rowspan="1" colspan="1">7 965</td><td align="center" rowspan="1" colspan="1">106</td><td align="center" rowspan="1" colspan="1">1</td><td align="center" rowspan="1" colspan="1">[<xref rid="cit0059" ref-type="bibr">59</xref>–<xref rid="cit0060" ref-type="bibr">60</xref>]</td></tr><tr><td align="left" rowspan="1" colspan="1">Hungary</td><td align="center" rowspan="1" colspan="1">93 030</td><td align="center" rowspan="1" colspan="1">10 898</td><td align="center" rowspan="1" colspan="1">45 068</td><td align="center" rowspan="1" colspan="1">34 170</td><td align="center" rowspan="1" colspan="1">314</td><td align="center" rowspan="1" colspan="1">[<xref rid="cit0061" ref-type="bibr">61</xref>–<xref rid="cit0064" ref-type="bibr">64</xref>]</td></tr><tr><td align="left" rowspan="1" colspan="1">Ireland</td><td align="center" rowspan="1" colspan="1">70 273</td><td align="center" rowspan="1" colspan="1">430</td><td align="center" rowspan="1" colspan="1">667</td><td align="center" rowspan="1" colspan="1">237</td><td align="center" rowspan="1" colspan="1">55</td><td align="center" rowspan="1" colspan="1">[<xref rid="cit0065" ref-type="bibr">65</xref>–<xref rid="cit0066" ref-type="bibr">66</xref>]</td></tr><tr><td align="left" rowspan="1" colspan="1">Finland</td><td align="center" rowspan="1" colspan="1">338 424</td><td align="center" rowspan="1" colspan="1">36</td><td align="center" rowspan="1" colspan="1">36</td><td align="center" rowspan="1" colspan="1">0</td><td align="center" rowspan="1" colspan="1">0</td><td align="center" rowspan="1" colspan="1">[<xref rid="cit0067" ref-type="bibr">67</xref>]</td></tr><tr><td align="left" rowspan="1" colspan="1">Iran</td><td align="center" rowspan="1" colspan="1">1 648 195</td><td align="center" rowspan="1" colspan="1">0</td><td align="center" rowspan="1" colspan="1">25 909</td><td align="center" rowspan="1" colspan="1">25 909</td><td align="center" rowspan="1" colspan="1">uncalculable</td><td align="center" rowspan="1" colspan="1">[<xref rid="cit0068" ref-type="bibr">68</xref>]</td></tr><tr><td align="left" rowspan="1" colspan="1">Japan</td><td align="center" rowspan="1" colspan="1">377 930</td><td align="center" rowspan="1" colspan="1">0</td><td align="center" rowspan="1" colspan="1">7 150</td><td align="center" rowspan="1" colspan="1">7 150</td><td align="center" rowspan="1" colspan="1">uncalculable</td><td align="center" rowspan="1" colspan="1">[<xref rid="cit0069" ref-type="bibr">69</xref>]</td></tr><tr><td align="left" rowspan="1" colspan="1">India</td><td align="center" rowspan="1" colspan="1">3 287 363</td><td align="center" rowspan="1" colspan="1">88 900</td><td align="center" rowspan="1" colspan="1">91 900</td><td align="center" rowspan="1" colspan="1">3 000</td><td align="center" rowspan="1" colspan="1">3</td><td align="center" rowspan="1" colspan="1"></td></tr><tr><td align="left" rowspan="1" colspan="1">Nigeria</td><td align="center" rowspan="1" colspan="1">923 768</td><td align="center" rowspan="1" colspan="1">1 634</td><td align="center" rowspan="1" colspan="1">1 825</td><td align="center" rowspan="1" colspan="1">191</td><td align="center" rowspan="1" colspan="1">12</td><td align="center" rowspan="1" colspan="1">[<xref rid="cit0070" ref-type="bibr">70</xref>–<xref rid="cit0073" ref-type="bibr">73</xref>]</td></tr><tr><td align="left" rowspan="1" colspan="1">England&Wales</td><td align="center" rowspan="1" colspan="1">151 000</td><td align="center" rowspan="1" colspan="1">5 518</td><td align="center" rowspan="1" colspan="1">10 796</td><td align="center" rowspan="1" colspan="1">5 278</td><td align="center" rowspan="1" colspan="1">96</td><td align="center" rowspan="1" colspan="1">[<xref rid="cit0074" ref-type="bibr">74</xref>–<xref rid="cit0075" ref-type="bibr">75</xref>]</td></tr><tr><td align="left" rowspan="1" colspan="1">New Zealand</td><td align="center" rowspan="1" colspan="1">270 467</td><td align="center" rowspan="1" colspan="1">2 990</td><td align="center" rowspan="1" colspan="1">7 651</td><td align="center" rowspan="1" colspan="1">4 661</td><td align="center" rowspan="1" colspan="1">156</td><td align="center" rowspan="1" colspan="1">[<xref rid="cit0076" ref-type="bibr">76</xref>–<xref rid="cit0079" ref-type="bibr">79</xref>]</td></tr><tr><td align="left" rowspan="1" colspan="1">Greece</td><td align="center" rowspan="1" colspan="1">131 957</td><td align="center" rowspan="1" colspan="1">0</td><td align="center" rowspan="1" colspan="1">200</td><td align="center" rowspan="1" colspan="1">200</td><td align="center" rowspan="1" colspan="1">uncalculable</td><td align="center" rowspan="1" colspan="1">[<xref rid="cit0080" ref-type="bibr">80</xref>]</td></tr><tr><td align="left" rowspan="1" colspan="1">Romania</td><td align="center" rowspan="1" colspan="1">238 391</td><td align="center" rowspan="1" colspan="1">3 338</td><td align="center" rowspan="1" colspan="1">3 839</td><td align="center" rowspan="1" colspan="1">501</td><td align="center" rowspan="1" colspan="1">15</td><td align="center" rowspan="1" colspan="1">[<xref rid="cit0081" ref-type="bibr">81</xref>–<xref rid="cit0084" ref-type="bibr">84</xref>]</td></tr><tr><td align="left" rowspan="1" colspan="1">Switzerland</td><td align="center" rowspan="1" colspan="1">41 290</td><td align="center" rowspan="1" colspan="1">0</td><td align="center" rowspan="1" colspan="1">6 000</td><td align="center" rowspan="1" colspan="1">6 000</td><td align="center" rowspan="1" colspan="1">uncalculable</td><td align="center" rowspan="1" colspan="1">[<xref rid="cit0092" ref-type="bibr">92</xref>]</td></tr><tr><td align="left" rowspan="1" colspan="1">Ukraine</td><td align="center" rowspan="1" colspan="1">603 548</td><td align="center" rowspan="1" colspan="1">1 500</td><td align="center" rowspan="1" colspan="1">2 075</td><td align="center" rowspan="1" colspan="1">575</td><td align="center" rowspan="1" colspan="1">38</td><td align="center" rowspan="1" colspan="1">[<xref rid="cit0085" ref-type="bibr">85</xref>]</td></tr><tr><td align="left" rowspan="1" colspan="1">Uruguay</td><td align="center" rowspan="1" colspan="1">176 215</td><td align="center" rowspan="1" colspan="1">1 386</td><td align="center" rowspan="1" colspan="1">1 556</td><td align="center" rowspan="1" colspan="1">170</td><td align="center" rowspan="1" colspan="1">12</td><td align="center" rowspan="1" colspan="1"></td></tr><tr><td align="left" rowspan="1" colspan="1">NorthenTunisia</td><td align="center" rowspan="1" colspan="1">2 822</td><td align="center" rowspan="1" colspan="1">0</td><td align="center" rowspan="1" colspan="1">180</td><td align="center" rowspan="1" colspan="1">180</td><td align="center" rowspan="1" colspan="1">uncalculable</td><td align="center" rowspan="1" colspan="1">[<xref rid="cit0086" ref-type="bibr">86</xref>]</td></tr><tr><td align="left" rowspan="1" colspan="1">Latvia</td><td align="center" rowspan="1" colspan="1">64 589</td><td align="center" rowspan="1" colspan="1">0</td><td align="center" rowspan="1" colspan="1">746</td><td align="center" rowspan="1" colspan="1">746</td><td align="center" rowspan="1" colspan="1">uncalculable</td><td align="center" rowspan="1" colspan="1">[<xref rid="cit0087" ref-type="bibr">87</xref>]</td></tr><tr><td align="left" rowspan="1" colspan="1">Luxembourg</td><td align="center" rowspan="1" colspan="1">2 593</td><td align="center" rowspan="1" colspan="1">805</td><td align="center" rowspan="1" colspan="1">860</td><td align="center" rowspan="1" colspan="1">55</td><td align="center" rowspan="1" colspan="1">7</td><td align="center" rowspan="1" colspan="1"></td></tr><tr><td align="left" rowspan="1" colspan="1">Morocco</td><td align="center" rowspan="1" colspan="1">710 850</td><td align="center" rowspan="1" colspan="1">394</td><td align="center" rowspan="1" colspan="1">1 106</td><td align="center" rowspan="1" colspan="1">712</td><td align="center" rowspan="1" colspan="1">181</td><td align="center" rowspan="1" colspan="1"></td></tr><tr><td align="left" rowspan="1" colspan="1">Sri Lanka</td><td align="center" rowspan="1" colspan="1">65 610</td><td align="center" rowspan="1" colspan="1">118</td><td align="center" rowspan="1" colspan="1">118</td><td align="center" rowspan="1" colspan="1">0</td><td align="center" rowspan="1" colspan="1">0</td><td align="center" rowspan="1" colspan="1">[<xref rid="cit0088" ref-type="bibr">88</xref>–<xref rid="cit0090" ref-type="bibr">90</xref>]</td></tr><tr><td align="left" rowspan="1" colspan="1">Slovenia</td><td align="center" rowspan="1" colspan="1">20 273</td><td align="center" rowspan="1" colspan="1">1 899</td><td align="center" rowspan="1" colspan="1">1 975</td><td align="center" rowspan="1" colspan="1">76</td><td align="center" rowspan="1" colspan="1">4</td><td align="center" rowspan="1" colspan="1"></td></tr><tr><td align="left" rowspan="1" colspan="1">Czech Republic</td><td align="center" rowspan="1" colspan="1">78 866</td><td align="center" rowspan="1" colspan="1">3 500</td><td align="center" rowspan="1" colspan="1">4 110</td><td align="center" rowspan="1" colspan="1">610</td><td align="center" rowspan="1" colspan="1">17</td><td align="center" rowspan="1" colspan="1">[<xref rid="cit0084" ref-type="bibr">84</xref>]</td></tr><tr><td align="left" rowspan="1" colspan="1">South Africa</td><td align="center" rowspan="1" colspan="1">1 220 000</td><td align="center" rowspan="1" colspan="1">16 000</td><td align="center" rowspan="1" colspan="1">17 750</td><td align="center" rowspan="1" colspan="1">1 750</td><td align="center" rowspan="1" colspan="1">11</td><td align="center" rowspan="1" colspan="1">[<xref rid="cit0091" ref-type="bibr">91</xref>]</td></tr><tr><td align="left" rowspan="1" colspan="1">Total world databases</td><td align="center" rowspan="1" colspan="1"></td><td align="center" rowspan="1" colspan="1"></td><td align="center" rowspan="1" colspan="1">10 250</td><td align="center" rowspan="1" colspan="1">117 456</td><td align="center" rowspan="1" colspan="1">107 206</td><td align="center" rowspan="1" colspan="1">1046</td></tr><tr><td align="center" rowspan="1" colspan="1">Total countries data bases</td><td align="center" rowspan="1" colspan="1"></td><td align="center" rowspan="1" colspan="1"></td><td align="center" rowspan="1" colspan="1">565 507</td><td align="center" rowspan="1" colspan="1">821 533</td><td align="center" rowspan="1" colspan="1">256 026</td><td align="center" rowspan="1" colspan="1">45</td><td align="center" rowspan="1" colspan="1"></td></tr></tbody></table></table-wrap><table-wrap id="t0002" orientation="portrait" position="float"><label>Tab 2</label><caption><p>Links to national databases available on the web</p></caption><table frame="hsides" rules="groups"><thead valign="bottom"><tr><th align="left" rowspan="1" colspan="1">Geographical level</th><th align="center" rowspan="1" colspan="1">name of the database</th><th align="center" rowspan="1" colspan="1">web site</th></tr></thead><tbody valign="top"><tr><td align="left" rowspan="1" colspan="1">World</td><td align="center" rowspan="1" colspan="1">WoSIS (World Soil Information Service)</td><td align="center" rowspan="1" colspan="1">http://www.isric.org/data/wosis</td></tr><tr><td align="center" rowspan="1" colspan="1">World</td><td align="center" rowspan="1" colspan="1">ISRIC-WISE Global Soil Profile Data</td><td align="center" rowspan="1" colspan="1">http://www.isric.org/data/isric-wise-derived-soil-property-estimates-30--s
30-arcsec-global-grid-wise30sec</td></tr><tr><td align="left" rowspan="1" colspan="1">Continental</td><td align="center" rowspan="1" colspan="1"></td><td align="center" rowspan="1" colspan="1"></td></tr><tr><td align="center" rowspan="1" colspan="1">Sub-Saharian Africa Latin America and carabean</td><td align="center" rowspan="1" colspan="1">AfSP (Africa Soil Profiles database) SISLAC</td><td align="center" rowspan="1" colspan="1">http://www.isric.org/data/africa-soil-profiles-database-version-01-2www.sislac.org</td></tr><tr><td align="left" rowspan="1" colspan="1">European Union</td><td align="center" rowspan="1" colspan="1"></td><td align="center" rowspan="1" colspan="1"></td></tr><tr><td align="left" rowspan="1" colspan="1">Europe (18 countries: Albania, Belgium, Denmark, Denmark, France,
Greece, Hungary, Italy, Italy, Slovak Republic, Luxembourg, Netherlands, Portugal,
Romania, United Kingdom, Slovenia, Spain, Switzerland)</td><td align="center" rowspan="1" colspan="1">SPADE/M : Soil Profile Analytical Database of Europe of Measured
parameters</td><td align="center" rowspan="1" colspan="1">http://esdac.jrc.ec.europa.eu/content/spadem</td></tr><tr><td align="left" rowspan="1" colspan="1">Europe (18 countries: Albania, Belgium, Denmark, Denmark, France,
Greece, Hungary, Italy, Italy, Slovak Republic, Luxembourg, Netherlands, Portugal,
Romania, United Kingdom, Slovenia, Spain,Switzerland)</td><td align="center" rowspan="1" colspan="1">SPADE-1: Soil Profiles in Europe</td><td align="center" rowspan="1" colspan="1">http://esdac.jrc.ec.europa.eu/content/european-soil-database-v20-vector-and-attribute-data</td></tr><tr><td align="center" rowspan="1" colspan="1">Europe (19 Countries: Belgium and Luxembourg, Denmark, England
Wales Scotland, Finland, Germany, Italy, Netherlands, Portugal, France, Ireland,
Bulgaria, Estonia, France, Hungary, Ireland, Romania, Slovakia and Switzerland)</td><td align="center" rowspan="1" colspan="1">SPADE-2: Soil Profiles in Europe</td><td align="center" rowspan="1" colspan="1">http://esdac.jrc.ec.europa.eu/content/soil-profile-analytical-database-2</td></tr><tr><td align="left" rowspan="1" colspan="1">Europe (28 Countres: EU + Norway, Albania,Switzerland)</td><td align="center" rowspan="1" colspan="1">SPADE-14: SOIL PROFILE ANALYTICAL DATABASE</td><td align="center" rowspan="1" colspan="1">Not yet available</td></tr><tr><td align="left" rowspan="1" colspan="1">Countries</td><td align="center" rowspan="1" colspan="1"></td><td align="center" rowspan="1" colspan="1"></td></tr><tr><td align="left" rowspan="1" colspan="1">Argentina</td><td align="center" rowspan="1" colspan="1">Sistema de Informacion de Suelos de INTA</td><td align="center" rowspan="1" colspan="1">http://sisinta.inta.gob.ar/</td></tr><tr><td align="left" rowspan="1" colspan="1">Australia</td><td align="center" rowspan="1" colspan="1">National soil site data collation (NSSDC)</td><td align="center" rowspan="1" colspan="1">http://www.clw.csiro.au/aclep/soilandlandscapegrid/index.html</td></tr><tr><td align="left" rowspan="1" colspan="1">Belgium</td><td align="center" rowspan="1" colspan="1">Databank Ondergrond Vlaanderen (DOV)</td><td align="center" rowspan="1" colspan="1">dov.vlaanderen.be</td></tr><tr><td align="left" rowspan="1" colspan="1">Cameroon</td><td align="center" rowspan="1" colspan="1">Ongoing Digital Soil mapping Project for Cameroon (University of
Dschang and IITA Cameroon)</td><td align="center" rowspan="1" colspan="1">Not kown yet</td></tr><tr><td align="left" rowspan="1" colspan="1">Chile</td><td align="center" rowspan="1" colspan="1"></td><td align="center" rowspan="1" colspan="1"></td></tr><tr><td align="left" rowspan="1" colspan="1">China</td><td align="center" rowspan="1" colspan="1">China Soil Database</td><td align="center" rowspan="1" colspan="1">http://vdb3.soil.csdb.cn/</td></tr><tr><td align="left" rowspan="1" colspan="1">Brazil</td><td align="center" rowspan="1" colspan="1">Sistema de Informagao de Solos Brasileiros & ESALQ Brazilian
Soil Profile Database</td><td align="center" rowspan="1" colspan="1"><ext-link ext-link-type="uri" xlink:href="https://www.bdsolos.cnptia.embrapa.br/consulta_publica.html">https://www.bdsolos.cnptia.embrapa.br/consulta_publica.html</ext-link> &
<ext-link ext-link-type="uri" xlink:href="http://www.esalq.usp.br/gerd">http://www.esalq.usp.br/gerd</ext-link></td></tr><tr><td align="left" rowspan="1" colspan="1">Canada</td><td align="center" rowspan="1" colspan="1">Canadian Soil Information Service</td><td align="center" rowspan="1" colspan="1">http://sis.agr.gc.ca/cansis/</td></tr><tr><td align="center" rowspan="1" colspan="1"></td><td align="center" rowspan="1" colspan="1">Canadian Digital Soil Data Consortium</td><td align="center" rowspan="1" colspan="1">http://soilinfo.ca/</td></tr><tr><td align="left" rowspan="1" colspan="1">Mexico</td><td align="center" rowspan="1" colspan="1">Natinal Forest Inventory formacion Nacional sobre Perfiles de Suelo
(Serie I)</td><td align="center" rowspan="1" colspan="1">http :
//www.inegi.org.mx/geo/contenidos/recnat/edafologia/vectorial_seriei.aspx</td></tr><tr><td align="left" rowspan="1" colspan="1"></td><td align="center" rowspan="1" colspan="1">Conjunto de Datos de Perfiles de Suelos Escala 1: 250 000 Serie II
(Continuo Nacional)</td><td align="center" rowspan="1" colspan="1">http://www.inegi.org.mx/geo/contenidos/recnat/edafologia/vectorial_serieii.aspx</td></tr><tr><td align="left" rowspan="1" colspan="1">France (mainland)</td><td align="center" rowspan="1" colspan="1">soil profiles in the 1:50,000 maps database DoneSol</td><td align="center" rowspan="1" colspan="1">www.gissol.fr</td></tr><tr><td align="center" rowspan="1" colspan="1">France (French west Indies)</td><td align="center" rowspan="1" colspan="1">Donesol and Valsol</td><td align="center" rowspan="1" colspan="1">www.gissol.fr</td></tr><tr><td align="left" rowspan="1" colspan="1">Geographical level</td><td align="center" rowspan="1" colspan="1">name of the database</td><td align="center" rowspan="1" colspan="1">web site</td></tr><tr><td align="left" rowspan="1" colspan="1">France (La Réunion)</td><td align="center" rowspan="1" colspan="1">Donesol and Valsol</td><td align="center" rowspan="1" colspan="1">www.gissol.fr</td></tr><tr><td align="left" rowspan="1" colspan="1">France (Guyana)</td><td align="center" rowspan="1" colspan="1">Donesol and Valsol</td><td align="center" rowspan="1" colspan="1">www.gissol.fr</td></tr><tr><td align="left" rowspan="1" colspan="1">France (New-caledonia)</td><td align="center" rowspan="1" colspan="1">Valsol</td><td align="center" rowspan="1" colspan="1">www.gissol.fr</td></tr><tr><td align="left" rowspan="1" colspan="1">Slovakia</td><td align="center" rowspan="1" colspan="1">National Agricultural Soils Inventory Database (AISOP),
agricultural soil dadatabe, foest soil datadase</td><td align="center" rowspan="1" colspan="1"></td></tr><tr><td align="left" rowspan="1" colspan="1">Denmark (Greenland)</td><td align="center" rowspan="1" colspan="1"></td><td align="center" rowspan="1" colspan="1"></td></tr><tr><td align="left" rowspan="1" colspan="1">Denmark (mainland)</td><td align="center" rowspan="1" colspan="1">Danish Soil Profile Database</td><td align="center" rowspan="1" colspan="1"></td></tr><tr><td align="left" rowspan="1" colspan="1"></td><td align="center" rowspan="1" colspan="1">Wetland database</td><td align="center" rowspan="1" colspan="1">SINKS</td></tr><tr><td align="left" rowspan="1" colspan="1">Croatia</td><td align="center" rowspan="1" colspan="1">National Soil Database of Croatia</td><td align="center" rowspan="1" colspan="1">no website</td></tr><tr><td align="left" rowspan="1" colspan="1">Russia</td><td align="center" rowspan="1" colspan="1">Unique State Registr of Soil Resources of Russia</td><td align="center" rowspan="1" colspan="1">http://atlas.mcx.ru/materials/egrpr/content/1DB.html</td></tr><tr><td align="left" rowspan="1" colspan="1">Indonesia</td><td align="center" rowspan="1" colspan="1">SIMADAS (Sistem Informasi Manajemen Data Sumberdaya Lahan)</td><td align="center" rowspan="1" colspan="1"></td></tr><tr><td align="left" rowspan="1" colspan="1">Portugal</td><td align="center" rowspan="1" colspan="1">INFOSOLO</td><td align="center" rowspan="1" colspan="1"></td></tr><tr><td align="left" rowspan="1" colspan="1">Scotland</td><td align="center" rowspan="1" colspan="1">Scottish Soil Database</td><td align="center" rowspan="1" colspan="1">http://www.soils-scotland.gov.uk/data/nsis</td></tr><tr><td align="left" rowspan="1" colspan="1">Thailand</td><td align="center" rowspan="1" colspan="1">Thailand soil database</td><td align="center" rowspan="1" colspan="1">www.ldd.go.th</td></tr><tr><td align="left" rowspan="1" colspan="1">USA</td><td align="center" rowspan="1" colspan="1">NCSS Microsoft Access Soil Characterization Database</td><td align="center" rowspan="1" colspan="1">http://ncsslabdatamart.sc.egov.usda.gov/</td></tr><tr><td align="left" rowspan="1" colspan="1">South Korea</td><td align="center" rowspan="1" colspan="1">Korean Soil Database</td><td align="center" rowspan="1" colspan="1">http://soil.rda.go.kr</td></tr><tr><td align="left" rowspan="1" colspan="1">The Netherlands</td><td align="center" rowspan="1" colspan="1">BIS Nederland</td><td align="center" rowspan="1" colspan="1">www.bodemdata.nl</td></tr><tr><td align="left" rowspan="1" colspan="1">Hungary</td><td align="center" rowspan="1" colspan="1">Digital Kreybig Soil Information System (DKSIS)</td><td align="center" rowspan="1" colspan="1"><ext-link ext-link-type="uri" xlink:href="http://medaphon.rissac.hu/kreybig/login/login_ui.php">http://medaphon.rissac.hu/kreybig/login/login_ui.php</ext-link>; <ext-link ext-link-type="uri" xlink:href="http://maps.rissac.hu/kreybig_bodrogkoz/">http://maps.rissac.hu/kreybig_bodrogkoz/</ext-link></td></tr><tr><td align="left" rowspan="1" colspan="1"></td><td align="center" rowspan="1" colspan="1">MARTHA ( Hungarian Detailed Soil Physical and Hydrological
Database)</td><td align="center" rowspan="1" colspan="1">https://www.researchgate.net/publication/250979646_Introduction_of_the_Hungarian_Detailed_Soil_Hydrophysical_Database_MARTHA_and_its_use_to_test_external_pedotransfer_functions</td></tr><tr><td align="left" rowspan="1" colspan="1"></td><td align="center" rowspan="1" colspan="1">TIM - talajinformációs és monitoring rendszer
- Soil information and monitoring network</td><td align="center" rowspan="1" colspan="1">http://portal.nebih.gov.hu/-/a-tim-azaz-a-talajvedelmi-informacios-esmonitoring-rendszer-</td></tr><tr><td align="left" rowspan="1" colspan="1">Ireland</td><td align="center" rowspan="1" colspan="1">Irish Soil Information System</td><td align="center" rowspan="1" colspan="1">www.http://erc.epa.ie/safer/</td></tr><tr><td align="left" rowspan="1" colspan="1">Finland</td><td align="center" rowspan="1" colspan="1">Finnish Soildatabase 1:250 000</td><td align="center" rowspan="1" colspan="1">http://www.paikkatietohakemisto.fi/geonetwork/srv/fi/main.home</td></tr><tr><td align="left" rowspan="1" colspan="1">Iran</td><td align="center" rowspan="1" colspan="1">INSDB=Iran National soil Data Base</td><td align="center" rowspan="1" colspan="1">http://www.insdb.swri.ir</td></tr><tr><td align="left" rowspan="1" colspan="1">Japan</td><td align="center" rowspan="1" colspan="1">Soil Information Web viewer</td><td align="center" rowspan="1" colspan="1">http://agrimesh.dc.affrc.go.jp/soil_db/</td></tr><tr><td align="left" rowspan="1" colspan="1">India</td><td align="center" rowspan="1" colspan="1">Bhoomi (tentative name)</td><td align="center" rowspan="1" colspan="1">http://www.nbsslup.in/ (under construction)</td></tr><tr><td align="left" rowspan="1" colspan="1">Nigeria</td><td align="center" rowspan="1" colspan="1">Nigeria Soil Dbase</td><td align="center" rowspan="1" colspan="1"></td></tr><tr><td align="left" rowspan="1" colspan="1">England&Wales</td><td align="center" rowspan="1" colspan="1">LandIS - Land Information System (for England and Wales)</td><td align="center" rowspan="1" colspan="1">www.landis.org.uk</td></tr><tr><td align="left" rowspan="1" colspan="1">New Zealand</td><td align="center" rowspan="1" colspan="1">National Soil Data Repository (NSDR)</td><td align="center" rowspan="1" colspan="1">https://soils.landcareresearch.co.nz/</td></tr><tr><td align="left" rowspan="1" colspan="1">Greece</td><td align="center" rowspan="1" colspan="1">elgo soil data base</td><td align="center" rowspan="1" colspan="1">www.gssoil-nagref.gr</td></tr><tr><td align="left" rowspan="1" colspan="1">Romania</td><td align="center" rowspan="1" colspan="1">PROFISOL</td><td align="center" rowspan="1" colspan="1"></td></tr><tr><td align="left" rowspan="1" colspan="1">Switzerland</td><td align="center" rowspan="1" colspan="1">Soil Information System NABODAT</td><td align="center" rowspan="1" colspan="1">www.nabodat.ch</td></tr><tr><td align="left" rowspan="1" colspan="1">Romania</td><td align="center" rowspan="1" colspan="1">MoniSol-RO</td><td align="center" rowspan="1" colspan="1"></td></tr><tr><td align="left" rowspan="1" colspan="1">Ukraine</td><td align="center" rowspan="1" colspan="1">Ukraine Soil Properties Database</td><td align="center" rowspan="1" colspan="1"></td></tr><tr><td align="left" rowspan="1" colspan="1">Uruguay</td><td align="center" rowspan="1" colspan="1"></td><td align="center" rowspan="1" colspan="1"></td></tr><tr><td align="left" rowspan="1" colspan="1">NorthenTunisia</td><td align="center" rowspan="1" colspan="1"></td><td align="center" rowspan="1" colspan="1"></td></tr><tr><td align="left" rowspan="1" colspan="1">Latvia</td><td align="center" rowspan="1" colspan="1">Digital Land and Soil Database of Latvia</td><td align="center" rowspan="1" colspan="1">Not known yet</td></tr><tr><td align="center" rowspan="1" colspan="1">Luxembourg</td><td align="center" rowspan="1" colspan="1">BD_SOL</td><td align="center" rowspan="1" colspan="1">Not known yet</td></tr><tr><td align="left" rowspan="1" colspan="1">Morocco</td><td align="center" rowspan="1" colspan="1">Moroccan Soil Profile Database</td><td align="center" rowspan="1" colspan="1"></td></tr><tr><td align="center" rowspan="1" colspan="1">Sri Lanka</td><td align="center" rowspan="1" colspan="1">SICANSOL</td><td align="center" rowspan="1" colspan="1">No known yet</td></tr><tr><td align="left" rowspan="1" colspan="1">Slovenia</td><td align="left" rowspan="1" colspan="1">Several databases and data collections available at three
institutions.</td><td align="center" rowspan="1" colspan="1">http://www.kis.si/eTLA</td></tr><tr><td align="left" rowspan="1" colspan="1">Czech Republic</td><td align="center" rowspan="1" colspan="1">PUGIS</td><td align="center" rowspan="1" colspan="1">http://pedologie.czu.cz/</td></tr><tr><td align="left" rowspan="1" colspan="1">South Africa</td><td align="center" rowspan="1" colspan="1">South African Soil Profile Database</td><td align="center" rowspan="1" colspan="1">www.arc.agric.za</td></tr></tbody></table></table-wrap><p><xref ref-type="fig" rid="f0001">Figure 1</xref> shows the relation between the total
surface area of the selected countries and i) the total number of soil profiles stored in
their database and ii) the soil profiles rescued between 2009 and 2015. As expected, there
is no clear relation between a country’ area and data rescuing effort. Some rather
small countries are in a very advanced stage of data rescuing (e.g., Belgium [<xref rid="cit0030" ref-type="bibr">30</xref>], The Netherlands [<xref rid="cit0059" ref-type="bibr">59</xref>–<xref rid="cit0060" ref-type="bibr">60</xref>], Denmark
[<xref rid="cit0044" ref-type="bibr">44</xref>–<xref rid="cit0045" ref-type="bibr">45</xref>]), whereas some very large countries are just beginning their data rescuing
efforts (e.g., Russia [<xref rid="cit0046" ref-type="bibr">46</xref>]).</p><fig id="f0001" orientation="portrait" position="float"><label>Figure 1</label><caption><p>Log-Log scatterplot of countries areas versus soil profiles</p></caption><graphic xlink:href="CIAT-2017-j-grj-2017-06-001-g001"></graphic></fig></sec><sec id="sec4"><label>4</label><title>Soil profile data rescue efforts</title><p>In the following sections, we present a few of many soil profile data rescue efforts. We
focus on data rescue efforts that have led to final products in line with the GlobalSoilMap
specifications.</p><sec id="sec4.1"><label>4.1</label><title>Case studies at the world level</title><sec id="sec4.1.1"><label>4.1.1</label><title>WoSIS data (World Soil Information Service)</title><p>The World Soil Information Service (WoSIS) database is developed at ISRIC [<xref rid="cit0134" ref-type="bibr">134</xref>] within the conceptual framework of the
Global Soil Information Facility which facilitates collaborative bottom-up initiatives
to process and exchange soil data at the global level (www.isric.org/explore/wosis).
Ideally, primary soil profile data are being managed and maintained by the national data
owners whereby the data are connected and made queryable online by an interoperable
infrastructure through data exchange standards. Since 2009 these standards continue to
be defined and developed by the global soil community, but is a very slow process.
Anticipating these standards being developed further, the configuration of WoSIS is that
of a centralized database which accommodates current, more conventional, data exchange
mechanisms between collaborative organizations to collate and harmonize soil data and
which therewith meets both short term and long term goals of collaborative soil
mapping.</p><p>The databases at the higher level (world, continent) are actually compilations of data,
under a common standard, from databases and reports originating at the lower level
(national and subnational) shared by collaborative partner organizations. So far, one
snapshot of the WoSIS data has been released in July 2016
(http://geonode.isric.org/layers/geonode:wosis 201607 profiles). The world level data
are spatially irregularly distributed, with some parts of the world being relatively
dense while other parts having still very sparse point data or no data at all (<xref ref-type="fig" rid="f0002">Fig. 2</xref>).</p><fig id="f0002" orientation="portrait" position="float"><label>Figure 2</label><caption><p>Location of the soil profiles rescued in WoSIS</p></caption><graphic xlink:href="CIAT-2017-j-grj-2017-06-001-g002"></graphic></fig><p>This distribution is strongly related to the amount of data previously shared through
collaborative projects and to the amounts of data currently published by the various
countries and institutions due to current and recent data policies, but is also
influenced by limited capacities and a prioritization of the effort. Very large
differences are observed between densities at the country level and the density at the
world level (for instance in France, Iran, Indonesia). More generally, we hope that a
map such as presented in <xref ref-type="fig" rid="f0002">Figure 2</xref> will encourage
countries to collaborate through a bottom-up approach and to provide data access to
WoSIS and/or to develop and share their own country level products according to the
GlobalSoilMap specifications similar to the most recent ones developed in some countries
[e.g. France, Scotland, USA, Australia, Denmark]. The WoSIS data collection effort has
proven to be very useful in producing the first world-wide SoilGrids at 1 km resolution
[<xref rid="cit0016" ref-type="bibr">16</xref>] followed by a world-wide grid at a 250
m resolution [<xref rid="cit0095" ref-type="bibr">95</xref>]. These global grids were
preceded by grids at similar resolution for the Sub- Saharan Africa region [<xref rid="cit0096" ref-type="bibr">96</xref>–<xref rid="cit0097" ref-type="bibr">97</xref>] using the data compiled in the African Soil Profiles database [<xref rid="cit0019" ref-type="bibr">19</xref>–<xref rid="cit0021" ref-type="bibr">21</xref>].</p></sec><sec id="sec4.1.2"><label>4.1.2</label><title>SoilGrid-250m</title><p>A new worldwide SoilGrids-250m has just been released ([<xref rid="cit0095" ref-type="bibr">95</xref>];http://www.soilgrids.org). The new version of SoilGrids
predictions comes with an open data license. SoilGrids data are available for viewing
and download via the data portal at <ext-link ext-link-type="uri" xlink:href="http://www.soilgrids.org">http://www.soilgrids.org</ext-link> and can also
be accessed through web coverage services. A bottom-up approach has been applied to
rescue and use the soil profile data available from the country level and a top-down
approach for producing the gridded maps through global modelling. A fully bottom-up
approach (i.e., both data rescuing and subsequent modelling are done at country level)
including the rescue and use of the large amounts of not yet publicly accessible soil
profile data available at country level. A few initiatives have been initiated to
encourage in-country capacity building for data rescue and subsequent digital soil
mapping process. Top-down approaches will still be used within the collaborative global
consortium to fill gaps where bottom-up approaches are not yet feasible. The global
SoilGrids-250m would also serve as covariate and help harmonization between country
level products and development of ensemble methods, mixing different predictions (e.g.
[<xref rid="cit0098" ref-type="bibr">98</xref>]).</p></sec></sec><sec id="sec4.2"><label>4.2</label><title>Case studies at the continental level</title><sec id="sec4.2.1"><label>4.2.1</label><title>Europe</title><p>In Europe, several soil profile databases have been developed, covering countries
belonging to the EU and other bordering countries, for example, SPADE2
(http://esdac.jrc.ec.europa.eu/content/soil-profile-analytical-database-2). This
database includes around 1,800 soil profiles covering the following countries: Belgium
and Luxembourg, Denmark, England and Wales, Finland, Germany, Italy, Netherlands,
Portugal and Scotland [<xref rid="cit0023" ref-type="bibr">23</xref>–<xref rid="cit0026" ref-type="bibr">26</xref>].</p><p>LUCAS is a topsoil database at European scale including more than 22,000 soil samples
from the 27 member states of the European Union [<xref rid="cit0099" ref-type="bibr">99</xref>–<xref rid="cit0103" ref-type="bibr">103</xref>]. In 2009, the
European Commission extended the periodic Land Use/Land Cover Area Frame Survey (LUCAS)
to sample the main properties of topsoil (0-30 cm) in 25 Member States of the European
Union. This sampling exercise has been extended in Romania and Bulgaria in 2012. The
samples have been analyzed and the compiled LUCAS-topsoil database is available in
European Soil Data Centre (ESDAC). The LUCAS soil sampling campaign was repeated in 2015
and the data will become available in 2017.</p></sec><sec id="sec4.2.3"><label>4.2.3</label><title>Sub-Saharan Africa</title><p>The Africa Soil Profiles database [<xref rid="cit0019" ref-type="bibr">19</xref>–<xref rid="cit0021" ref-type="bibr">21</xref>], version 1.2,
compiles standardized and original soil data from 18,572 soil profiles of Sub-Saharan
Africa, of which 17,160 are georeferenced (Fig. 3).</p><fig id="f0003" orientation="portrait" position="float"><label>Figure 3</label><caption><p>Location of the data rescued in the Sub-Saharan Africa Soil Profiles database</p></caption><graphic xlink:href="CIAT-2017-j-grj-2017-06-001-g003"></graphic></fig><p>The data were captured from 540 data sources with full lineage specified; about 25% of
the profiles were extracted from earlier ISRIC datasets, 30% from other digital datasets
and 45% from analogue reports (503). It includes data for approximately 140 soil
properties, including soil analytical data measured in over 100 specified laboratories,
using over 350 specified laboratory methods. The original values were standardized
according to standard data conventions (Soil and Terrain database, SOTER, <ext-link ext-link-type="uri" xlink:href="http://www.isric.org/projects/soil-and-terrain-database-soter-programme">http://www.isric.org/projects/soil-and-terrain-database-soter-programme</ext-link>)
for 25 soil properties observed from the profile and the profile site and for 75 soil
properties, both morphologically observed and analytically measured, reported from the
soil profile layer features (depth intervals; 4 on average to 110 cm depth on average).
The standardized values for some 60 soil analytical properties, evaluated in the
laboratory, were subjected to routine quality assurance protocols. The temporal
distribution of the data spans over 60 years peaking in the 1980’s, and the
spatial distribution of the data covers 40 countries. The Africa Soil Profiles database
[<xref rid="cit0019" ref-type="bibr">19</xref>–<xref rid="cit0021" ref-type="bibr">21</xref>] is compiled within the context of the Africa Soil Information
Service (AfSIS) project, with collaborative contributions from Cameroon, Nigeria, Ghana,
Mali, Ethiopia, Kenya, Tanzania and Malawi, and is accessible at <ext-link ext-link-type="uri" xlink:href="http://www.isric.org/content/africa-soil-profiles-database">www.isric.org/content/africa-soil-profiles-database</ext-link> and <ext-link ext-link-type="uri" xlink:href="http://africasoils.net/services/data/soil-databases/africa-soil-profile-database/">http://africasoils.net/services/data/soil-databases/africa-soil-profile-database/</ext-link>).
At present, the effort is ongoing through collaboration with bottom-up initiatives of
organizations in a number of SSA countries (i.e., Ghana, Cameroon, Burkina Faso).</p><p>The data rescue in Sub-Saharan Africa has resulted in gridded soil maps for all primary
and derived soil properties mentioned in the GlobalSoilMap specifications [<xref rid="cit0011" ref-type="bibr">11</xref>], including electrical conductivity, bulk
density, plant-available water holding capacity and depth l to bedrock and effective
root zone depth (for maize) [<xref rid="cit0104" ref-type="bibr">104</xref>–<xref rid="cit0107" ref-type="bibr">107</xref>]; In this region, legacy data proved
particularly relevant, compared to newly sampled topsoil data, 1) to allow cost
effective mapping detailed and consistent at both the continental and national extent
and 2) to assess the effective depth and volume of the soil in which soil water and
nutrients are retained and in which plants do actually grow. These Africa SoilGrids were
used as input for yield gap analyses and quantitative evaluation of the fertility of
soils.</p></sec></sec><sec id="sec4.3"><label>4.3</label><title>Case studies at the national level</title><sec id="sec4.3.1"><label>4.3.1</label><title>United States of America</title><p>In the United States of America (USA), a tremendous effort led to an approximate
doubling of the number of soil profiles between 2000 to 2016 (<xref ref-type="fig" rid="f0004">Fig. 4</xref>). The majority of the rescued data came from Universities
that collected and analyzed the data during the field soil survey campaigns under
cooperative agreements with the USA national Cooperative Soil Survey [<xref rid="cit0108" ref-type="bibr">108</xref>]. Some historical data were also rescued
[<xref rid="cit0109" ref-type="bibr">109</xref>]</p><fig id="f0004" orientation="portrait" position="float"><label>Figure 4</label><caption><p>USA National Cooperative Soil Survey soil profile data rescued between 2009 and
2016. Green dots represent the 2009 soil profile data and the red dots represent the
2016 soil profile data showing an increase in their number from 29, 130 to 60,
962.</p></caption><graphic xlink:href="CIAT-2017-j-grj-2017-06-001-g004"></graphic></fig></sec><sec id="sec4.3.2"><label>4.3.2</label><title>France</title><p>In France, an important data rescue effort led to a 69% increase of the number of soil
profiles data from 2009 to 2015 (<xref ref-type="fig" rid="f0005">Fig. 5</xref>) [<xref rid="cit0041" ref-type="bibr">41</xref>–<xref rid="cit0042" ref-type="bibr">42</xref>] giving an impressive coverage at adequate density of the French
territory.</p><fig id="f0005" orientation="portrait" position="float"><label>Figure 5</label><caption><p>Rescued soil profiles in France between 2009 (left) and 2015 (right) (France).
Complete soil profiles with full description are in red, auger borings are in green.
The total number of points in 2009 is 76, 400, and 160, 103 in 2015.</p></caption><graphic xlink:href="CIAT-2017-j-grj-2017-06-001-g005"></graphic></fig></sec><sec id="sec4.2.2"><label>4.2.2</label><title>Australia</title><p>Australia has a rich but non-uniform and incomplete archive of existing soil mapping
and site data. The state and territory government agencies are primarily responsible for
the collection and management of soil data within their territories, in addition, CSIRO,
Universities and Geoscience institutions have collected data and hold records. Thus,
there are at least 13 independent and unique soils data management systems, some eight
with formal responsibilities for regional, national or specific data [<xref rid="cit0028" ref-type="bibr">28</xref>]. For at least the last 70 years, these
agencies have been collecting soil site data, and for some 40 years have used various
forms of data systems (in most cases developed within the institution). Before the
GlobalSoilMap project initiation, these soil site datasets were not compiled into a
consistent data set conforming to a single standard. The GlobalSoilMap project provided
the impetus for combining some 281,000 soil profiles into a single uniform database
using data interoperability approaches and a consistent database schema for the project
data collation [<xref rid="cit0028" ref-type="bibr">28</xref>–<xref rid="cit0029" ref-type="bibr">29</xref>]. Also contained in this database are 2.5
million laboratory measurements. <xref ref-type="fig" rid="f0006">Figure 6</xref> shows
the progress between 2009 (the launch of the GlobalSoilMap project) and 2015. Very large
areas that had very sparse information in a consistent national collation (for instance
in western and northern parts of the country) are now covered by a large amount of soil
profile data now available for new mapping and estimation</p><fig id="f0006" orientation="portrait" position="float"><label>Figure 6</label><caption><p>(a) Distribution of sites contained in the previously existing national NatSoil
Database of Australia (11, 500 sites) and (b) distribution of sites contained in the
new National Site Data Collation (NSSC) database (281, 000 Sites)</p></caption><graphic xlink:href="CIAT-2017-j-grj-2017-06-001-g006"></graphic></fig></sec><sec id="sec4.3.3"><label>4.3.3</label><title>Other</title><p>It was found that some countries not only rescue soil profile data but also soil
descriptions captured by hand auger borings. This is partly the case for France (see
Fig. 5). The Netherlands is and outstanding example where more than 327,000 auger
descriptions have been rescued, leading to a total density of observation points of
about 13 km<sup>-2</sup> in agricultural, forest and natural lands. These auger
descriptions are very supportive in predicting the spatial distribution of soil types
and soil properties. For instance, a recent use of this data led to probability mapping
of iron pan presence in sandy podzols in South-West France [<xref rid="cit0135" ref-type="bibr">135</xref>].</p></sec></sec></sec><sec id="sec5"><label>5</label><title>Soil map data rescue efforts</title><p>Legacy soil maps are available in quite a large number of countries and are a valuable soil
covariate along with soil profile point data, for use in digital soil mapping. Therefore,
soil maps from legacy soil survey data holdings across the world are being rescued and
compiled and serve as input for a number of countries to developing techniques for digital
soil mapping. This legacy information contributes through a bottom-up approach to a common,
consistent and geographically contiguous applicable dataset of relevant soil properties
covering the planet’s land surface. The legacy soil data holdings, including tens of
thousands of published soil maps and associated reports, have been produced over an extended
period of time by numerous institutions using different methods, standards, scales and
taxonomic classification systems.</p><sec id="sec5.1"><label>5.1</label><title>Case studies at the world and continental level</title><p>The largest collection of soil survey archives publicly accessible online is the ISRIC -
World Soil Information document database (library: <ext-link ext-link-type="uri" xlink:href="http://www.isric.org/content/search-library-and-map-collection">http://www.isric.org/content/search-library-and-map-collection</ext-link>). The ISRIC
library has built up a collection of nearly 35,000 maps, reports and books. The many soil
maps accompanied by the associated soil reports and related thematic information provide
rich soil survey data and complementary information. Much of these materials, each with a
unique identifier and full metadata, has been scanned through a huge effort since 2009,
including an effort at the EU level. This resulted in the Digital Archive of Soil Maps
(EuDASM) which includes around 6,000 maps from the ISRIC library for 140 countries
worldwide [<xref rid="cit0110" ref-type="bibr">110</xref>], and can be queried and
accessed online at the ISRIC website. EuDASM is available in the European Soil Data Centre
(ESDAC)at:(http://esdac.jrc.ec.europa.eu/resource-type/national-soil-maps-eudasm).</p><p>The Food and Agriculture Organization (FAO) has recently finished uploading 1228 soil and
land legacy maps (mainly soil maps, but also land use, geological and land cover legacy
maps): <ext-link ext-link-type="uri" xlink:href="http://www.fao.org/soils-portal/soil-survey/soil-maps-and-databases/fao-soil-legacy-maps/en/">http://www.fao.org/soils-portal/soil-survey/soil-maps-and-databases/fao-soil-legacy-maps/en/</ext-link>.</p><p>During the AfSIS/GlobalSoilMap project [<xref rid="cit0019" ref-type="bibr">19</xref>–<xref rid="cit0021" ref-type="bibr">21</xref>], thousands of selected
soil reports and maps of Sub- Saharan Africa were scanned at ISRIC and made available
online. Moreover, thousands of additional soil maps, and associated soil reports, of
Africa were identified from other libraries and holdings in Europe and Africa (i.e., IRD,
WOSSAC, FAO, UGhent) and after duplicate removal were added to the ISRIC library
collection, including online access to digital scans with full metadata (Fig. 7).</p><p>The Africa Soil Maps database represents a spatial inventory of approximately 5,000
legacy soil maps recently made available online at the ISRIC library. Soil maps
originating from six European archives and a few African national countries were
identified and added to the library through a large effort to harmonize metadata and
exclude duplicates (<xref ref-type="fig" rid="f0007">Figure 7</xref>). Some legacy soil
maps that had been scanned have also been digitized into a GIS-database format, including
information about the topology, geometry and legends. The Malawi data has been used by
ISRIC for producing a Soil and Terrain (SoTer) database [<xref rid="cit0111" ref-type="bibr">111</xref>].</p><fig id="f0007" orientation="portrait" position="float"><label>Figure 7</label><caption><p>Contour map of the (Sub-Saharan) Africa Soil Maps database.</p></caption><graphic xlink:href="CIAT-2017-j-grj-2017-06-001-g007"></graphic></fig></sec><sec id="sec5.2"><label>5.2</label><title>Case studies at the national level</title><sec id="sec5.2.1"><label>5.2.1</label><title>Nigeria</title><p>For Nigeria, soil data holdings have been identified and collected from various
libraries, including numerous analogue soil reports and maps from the ISRIC library, a
digital soil GIS-map from the University of Amsterdam and a few items from holdings in
Nigeria (Zaria University, Niger River Basin Management authority, Federal Department of
Agricultural Land Resources). Selected items not yet in the ISRIC library were
photocopied and brought to the Netherlands and added to the ISRIC collection, scanned
(rescued) and brought online. For the AfSIS project, ISRIC digitized, georeferenced and
compiled the soil data of 1,250 profiles from Nigeria into the Africa Soil Profiles
database version 1.0 , [<xref rid="cit0019" ref-type="bibr">19</xref>–<xref rid="cit0021" ref-type="bibr">21</xref>], of which 45 profiles were available through
earlier ISRIC databases (27 in ISIS and 19 in WISE). Georeferencing and data quality
control proved to be major challenges in collating these legacy soil data, and are
described in [<xref rid="cit0070" ref-type="bibr">70</xref>–<xref rid="cit0071" ref-type="bibr">71</xref>] the first soil mapping applications in [<xref rid="cit0072" ref-type="bibr">72</xref>]. The national database of Nigerian soil profiles currently
contains about1,900 profiles, nearly 50% more soil profiles has been added since 2011
and used for a range of applications [<xref rid="cit0072" ref-type="bibr">72</xref>–<xref rid="cit0074" ref-type="bibr">74</xref>] and we expect these
additional soil profile data from Nigeria to be made publicly available online with the
original collaborative initiative.</p></sec><sec id="sec5.2.2"><label>5.2.2</label><title>India</title><p>In India, the National Bureau of Soil Survey and Land Use Planning (NBSS&LUP),
under the Indian Council of Agricultural Research (ICAR), is the agency for collecting
and generating soil data in India. With a network of centers throughout the country, the
agency has generated soil resources maps at the 1:1,000,000 scale at the country level,
at the 1:250,000 at state and union territory levels, at 1:50,000 for 83 out of 640
districts, and at 1:5,000 scale for 70 watersheds. These resource maps provide
layer-wise soil information on soil texture, organic carbon contents, pH, nutrients,
cation exchange capacity and in limited cases, water holding capacity. There are few
other organizations who also compile such data; however, a harmonized and searchable
soil database is yet to be developed.</p></sec><sec id="sec5.2.3"><label>5.2.3</label><title>Indonesia</title><p>In Indonesia, soil resource inventories have been conducted since 1905 by the
Indonesian Centre for Agricultural Land Resource Research and Development (ICALRD) and
its colonial and post-independence predecessors for various purposes (e.g. agricultural
planning, erosion hazard assessment, and soil fertility monitoring). This has resulted
in soil survey reports and soil maps (e.g. [<xref rid="cit0047" ref-type="bibr">47</xref>]). Various databases have been developed to store soil data in Indonesia.
As of 2016, 100% of Indonesia is covered by a 1:250,000 scale map and 40% by detailed
maps (≤1:50,000 scale). In addition, a land system map at the scale of 1:250,000
is available for the whole country and there is an ongoing effort to scan soil survey
reports and hardcopy maps.</p></sec><sec id="sec5.2.4"><label>5.2.4</label><title>South Korea</title><p>In South Korea, detailed soil maps (1:25,000) are now available for the entire country,
both in hard copies and digital format. Furthermore, highly detailed soil maps
(1:5,000), surveyed from 1995 to 1999 for the entire country, were digitized and made
available for the public, through the website (http://soil.rda.go.kr). Two soil
databases were constructed, as part of the soil information system of Korea. The first
is a spatial database of computerized soil maps at a variety of scales (1:250,000,
1:50,000, 1:25,000, and 1:5,000). The second database is a parcel-based soil fertility
(chemical properties) database, containing around 7,000,000 data objects.</p></sec><sec id="sec5.2.5"><label>5.2.5</label><title>United States of America</title><p>In the USA, a “Digital Collection of Selected Historical Publications on Soil
Survey and Soil Classification in the United States of America” was assembled
comprising a selection of scanned maps, photographs, unpublished reports and government
publications that provide some historical perspective on soil survey activities and the
development of soil classification in the United States [<xref rid="cit0109" ref-type="bibr">109</xref>]. The scanned documents cover various topics such as tropical
soils; the history of the National Cooperative Soil Survey; historical development and
theory of soil classification; field excursions organized for 1st and 7th International
Congresses of Soil Science; soil survey investigations; and Soil Taxonomy. The series of
historical soil maps, 1909-1998, illustrates several conceptual changes in soil
geography and soil classification at the national and regional (province-based) scales
(http://www.nrcs.usda.gov/wps/portal/nrcs/detail/soils/survey/publication/). Also a
large number of published soil survey manuscripts in paper format have been scanned and
digitized and made publicly available at <ext-link ext-link-type="uri" xlink:href="http://www.nrcs.usda.gov/wps/portal/nrcs/soilsurvey/soils/survey/state/">http://www.nrcs.usda.gov/wps/portal/nrcs/soilsurvey/soils/survey/state/</ext-link>(accessed on August 27, 2016). Efforts to rescue documentations collected during soil
survey campaigns (a field notes, pedon descriptions, transect data) are also underway
and conducted at regional levels. For example, the project in Region 10 comprising of 8
states located in northcentral US has rescued and georeferenced close to 47,364 pedon
descriptions [<xref rid="cit0098" ref-type="bibr">98</xref>] that are available on an
ArcGIS platform
(http://www.arcgis.com/home/webmap/viewer.html?webmap=80c4349331754aada7572c54a1377d66
&extent=-116.5399,36.0679,-84.0863,52.1478, accessed on July 27, 2016).</p></sec><sec id="sec5.2.6"><label>5.2.6</label><title>France</title><p>In France, a preliminary analysis of national soil information and potential for
delivering GlobalSoilMap products has been made in 2013 and published in 2014 [<xref rid="cit0112" ref-type="bibr">112</xref>]. At the end of 2015, a catalogue of 5,854
soil maps became available at <ext-link ext-link-type="uri" xlink:href="http://www.gissol.fr/outils/refersols-340">http://www.gissol.fr/outils/refersols-340</ext-link>. About half of the collection is
currently being digitized and 407 soil maps are accessible as complete database. This
effort is a long-term ongoing process, with major emphasis on building a harmonized
database. Priority is given to maps with scales ranging between 1:250,000 - 1:50,000.
[<xref rid="cit0041" ref-type="bibr">41</xref>–<xref rid="cit0042" ref-type="bibr">42</xref>].</p></sec><sec id="sec5.2.7"><label>5.2.7</label><title>Scotland</title><p>In Scotland, the 1:25,000 scale soil maps were created by the Macaulay Institute for
Soil Research (now the James Hutton Institute) and are based on data collected mainly
between 1947 and 1987. The soil classification has evolved since the 1940s and the
updated maps follow the 2013 revised soil classification system. The 1:25,000 scale soil
maps were created by the Macaulay Institute for Soil Research and are also based on data
collected mainly between 1947 and 1987. Scotland has a major programme to update their
1:25,000 scale soil maps and make them available for download, see <ext-link ext-link-type="uri" xlink:href="http://www.soils-scotland.gov.uk/data/soil-survey25k.php">http://www.soils-scotland.gov.uk/data/soil-survey25k.php</ext-link>. Further
information on how the maps were made, how the soils were classified and the state of
progress of soil maps rescue can be found at <ext-link ext-link-type="uri" xlink:href="http://www.soils-scotland.gov.uk/">http://www.soils-scotland.gov.uk/</ext-link>.</p></sec><sec id="sec5.2.8"><label>5.2.8</label><title>Latvia</title><p>In Latvia, analogous soil maps (1976-1997) of agricultural land at the scale of 1:10,
000 were digitized and a database was created. The database consists of two data sets:
1) polygon characterization, including the year of mapping, soil type according to
genetic classification and the textural group) and 2) soil profile data, including the
year of mapping, soil type according to genetic classification, the textural group
(topsoil, bottom layer), and integrated textural group (topsoil and bottom layer), pH
value, depth of CaCO3. Altogether, the database contains data from 543601 polygons and
746 soil profile descriptions [<xref rid="cit0087" ref-type="bibr">87</xref>]. Some
attempt was done to convert the soil units from National classification to the WRB 2014.
The technical work is finished but the database is not yet publically available due to
the discussions in which portal to place it and who will be responsible for its
maintenance.</p></sec><sec id="sec5.2.9"><label>5.2.9</label><title>Russia</title><p>In Russia, detailed soil maps, at scales 1:10, 000-1:50, 000, are available for all
arable lands, both in hard and scanned copies. The total number of maps is about 20,
000. The majority of the maps is accompanied by explanatory notes with characteristics
of main soils, and representative profiles description. The map collection is stored in
the Soil Data Center of V.V. Dokuchaev Soil Science Institute (Moscow) and are not
publicly available. They are used as an additional source for the development of the
Unique State Register of Soils of Russia, and for different databases compilation.
Additionally the Soil Data Center contains regional soil maps at scale 1:200,000 -
1:500,000 for the most regions of Russia, as well as near 140 sheets of State Soil Map
of USSR (scale 1:1,000,000) with explanatory notes. Some of these maps were digitized,
or updated based on digital soil mapping approaches [<xref rid="cit0136" ref-type="bibr">136</xref>].</p></sec><sec id="sec5.2.10"><label>5.2.10</label><title>Hungary</title><p>Soil mapping has a long tradition in Hungary, several small scale soil maps were
compiled in the first decades of the 20th century. Large scale mapping at a scale of
1:25, 000 started in the 1930s and continued till the end of the 1950s. Large scale
mapping campaign at 1:10, 000 scale supporting the intensive large scale agriculture
continued till the early 1980s. These datasets have been used as a source for smaller
scale soil maps between 1:100, 000 and 1:1, 000, 000 scales. The 1:25, 000 scale maps
have already been digitized, all the polygons and the related points has been organized
into digital soil datasets. The 1:10, 000 scale maps are partially digitized, the
process is still ongoing. Due to the tremendous amount of emerging soil profile data and
new observations and to the innovative digital soil mapping tools being available,
several new data products have been or being produced as new, independent data sources
serving the new kind of data needs, and increasing the data diversity.</p></sec></sec><sec id="sec5.3"><label>5.3</label><title>Usefulness and limitations of rescued soil maps for GlobalSoilMap</title><p>Soil properties can be derived from both detailed soil maps (generally a cartographic
scale of 1:100,000 or more detailed) and soil point data (i.e. measurements down the soil
profile at a georeferenced location). When using soil maps only, the most used methods
are: extracting soil properties from a soil map, using a spatially weighted measure of
central tendency (e.g. the mean), or spatial disaggregation of soil maps (e.g., [<xref rid="cit0038" ref-type="bibr">38</xref>, <xref rid="cit0054" ref-type="bibr">54</xref>,
<xref rid="cit0113" ref-type="bibr">113</xref>–<xref rid="cit0115" ref-type="bibr">115</xref>]).</p><p>When only soil maps are available, soil properties can be extracted from soil maps
according to the distributional concepts underlying the soil mapping units. In some cases,
it will be appropriate to estimate soil properties using an area-weighted mean, as was
done for example in the United States [<xref rid="cit0051" ref-type="bibr">51</xref>–<xref rid="cit0052" ref-type="bibr">52</xref>]. However, in most
circumstances, the original soil map will have information on the factors controlling soil
distribution within an individual map unit. This is most commonly based on terrain (e.g. a
catena or characteristic toposequence). The widespread availability of fine-resolution
terrain variables, now allows the soil properties to be ‘disaggregated’ at
soil type levels occurring within soil mapping polygons. Recent examples of this kind of
approach canbe found in [<xref rid="cit0038" ref-type="bibr">38</xref>, <xref rid="cit0054" ref-type="bibr">54</xref>, <xref rid="cit0113" ref-type="bibr">113</xref>–<xref rid="cit0115" ref-type="bibr">115</xref>].</p><p>An extension of this approach is to use areas where there is a detailed understanding of
soil distribution as a basis for extrapolation to a broader domain, examples can be found
in [<xref rid="cit0116" ref-type="bibr">116</xref>–<xref rid="cit0118" ref-type="bibr">118</xref>]. Moreover, soil map units and soil point data can be used
together to improve gridded predictions of soil properties. Soil map units can be used as
a co-variate for scorpan kriging (i.e. a prediction method using both spatial co-variates
linked to the controlling factors of soil distribution and to the points location, [<xref rid="cit0009" ref-type="bibr">9</xref>]), for instance [<xref rid="cit0119" ref-type="bibr">119</xref>–<xref rid="cit0124" ref-type="bibr">124</xref>]. This
often implies merging different soil map units in order to reduce their number [<xref rid="cit0123" ref-type="bibr">123</xref>–<xref rid="cit0124" ref-type="bibr">124</xref>]. Specific information can be extracted from soil maps (e.g., parent
material, broad soil classes, soil textural classes, eg., [<xref rid="cit0124" ref-type="bibr">124</xref>]) and also used as a co-variate. This will often require some
merging of classes too. Note that depending on the target soil property the most efficient
merging of classes can differ and often requires the soil surveyor expert knowledge. For
instance, in France, different parent material classifications may be used as co-variates
for soil texture and for pH mapping [<xref rid="cit0124" ref-type="bibr">124</xref>].
Finally, independent predictions from soil maps and from point data can be merged and
weighted through ensemble methods (e.g. [<xref rid="cit0098" ref-type="bibr">98</xref>]).</p><p>Using soil maps over large territories often requires huge harmonizing efforts. Indeed
different soil maps may have been produced by different soil surveyors, having different
objectives and various pedological concepts. The scales may also differ between soil maps.
For instance huge efforts have been invested in harmonizing the European geographical Soil
Database (e.g., [<xref rid="cit0125" ref-type="bibr">125</xref>]) and the US soil map
(e.g., [<xref rid="cit0108" ref-type="bibr">108</xref>]). Attempts to update the world
soil map using SOTER methodology are still ongoing in various parts of the world (e.g.,
[111; 126]).</p><p>Finally, even if soil maps cannot be considered as truly independent validation data,
they are often useful to evaluate some gridded products and to check inconstancies between
gridded predictions and expert delineations of broad soil classes</p></sec></sec><sec id="sec6"><label>6</label><title>Success stories</title><p>The final goal of the project is to provide a global freely available high-resolution
dataset on key soil properties which is either downloadable or accessible through
web-services. This dataset will include 18 billion of point data on a 3x3-arcsec grid and 18
billion of block data on 3x3-arcsec cells (i.e., we predict soil properties and their
uncertainties at each node of a 3x3-arcsec grid and their mean values and their
uncertainties on 3x3-arcsec cells centered on the grid nodes), on six standard depths for 12
soil properties with associated uncertainties (90 % confidence interval). The project
includes tiered specifications depending on the spatial entity (point or block) and on
uncertainty and validation specifications [<xref rid="cit0011" ref-type="bibr">11</xref>].</p><sec id="sec6.1"><label>6.1</label><title>World-level</title><p>SoilGrids (e.g., [<xref rid="cit0016" ref-type="bibr">16</xref>; <xref rid="cit0095" ref-type="bibr">95</xref>]) are the first globally consistent and contiguous complete
gridded soil properties maps of the world, derived from rescued legacy soil profile data
through DSM techniques, and was released by ISRIC. Despite some limitations (grid cell
area, and rather low accuracy in some areas); they constitute a first proof of concept and
example on what can potentially be achieved at the world level. However, they do not
describe sufficient variability at short distances. Despite these limitations at the local
level, the SoilGrids provide key support for global modeling efforts.</p><p>Soilgrids250 m [<xref rid="cit0095" ref-type="bibr">95</xref>] was recently released on
the ISRIC website, showing significant improvements compared to the 1 km product. ISRIC is
waiting from feedback from countries. However, the number of soil profiles available for
model calibration remained limited (only just over 100,000). One of the main advantages of
releasing such products may be to identify the parts of the world where data is obviously
missing. This may convince countries either to provide data to ISRIC and therewith to the
global soil science community, to develop their own bottom-up products through
collaborative efforts to fill the gaps, to correct the obvious errors or to simply enhance
the accuracy where insufficient for national purposes. Obviously there will also be parts
of the world where there will be no data at all or where data has been lost. SoilGrids
will therefore be useful to fill these gaps. Another possibility is to collaborate by
evaluating and validating global SoilGrids products with national profile datasets or
predictions or to make national datasets available to improve the global predictions.</p></sec><sec id="sec6.2"><label>6.2</label><title>Continent-level</title><p>The situation in Sub-Saharan Africa is similar to that of the world level, with two
products released: AfSoilgrids1km [<xref rid="cit0096" ref-type="bibr">96</xref>] and
AfSoilgrids250m [<xref rid="cit0097" ref-type="bibr">97</xref>]. A considerable effort has
been made to rescue soil profile data that were in danger of being lost and that are now
compiled into the Africa Soil Profiles database [14, 19-21]. This effort involved two full
time positions over a period of nearly five years, plus a number of students assisting in
the digitization process and collaboration with six countries, including training
sessions. The data rescue in this region has resulted in maps for all properties mentioned
in the GlobalSoilMap specifications [<xref rid="cit0011" ref-type="bibr">11</xref>].</p><p>Considerable efforts have been made in training and raising technical capacity at
locations in seven countries as well as more generally through the yearly Springschool and
guest research at ISRIC. These efforts included the compilation and standardization of
soil profiles data, the theories and practices of digital soil mapping and even the
development of data infrastructures including hardware, software and setting up of data
servers. Nowadays, some countries are currently working to develop country level products,
based on bottom-up approaches (e.g. Nigeria, Niger, Cameroon, South-Africa, Ghana,
Ethiopia), through joining a new GlobalSoilMap consortium and through various bilateral
collaborations.</p></sec><sec id="sec6.3"><label>6.3</label><title>Country-level</title><sec id="sec6.3.1"><label>6.3.1</label><title>Australia</title><p>The Australia Soil and Landscape Grids were produced based on the legacy soil data
compiled in the National Soil Site Collation database, meeting the GlobalSoilMap
specifications on a support of 3x3 arc-seconds [<xref rid="cit0028" ref-type="bibr">28</xref>–<xref rid="cit0029" ref-type="bibr">29</xref>]. There are 13 soil
attribute surfaces publically available. The predictions were performed using
cubist-kriging. The soil organic carbon content was shown to be distributed according
large climatic gradients [<xref rid="cit0127" ref-type="bibr">127</xref>].</p></sec><sec id="sec6.3.2"><label>6.3.2</label><title>United States of America</title><p>The US has produced digital soil maps for the following soil properties: Soil pH;
Organic Carbon; Effective Cation Exchange Capacity (ECEC); Soil Bulk Density; Sand,
Silt, Clay, Coarse Fragments; Available Water Capacity (AWC); and Rooting Zone Depth,
for the standard GlobalSoilMap depths (0-5-15, 15-30, 30-60, 60-100 and 100-200 cm). The
predictions are supported by uncertainty measures; the estimated Upper and Lower Limits
for each property are considered as the 90% Confidence Limits. <xref ref-type="fig" rid="f0008">Figure 8</xref> shows the Version 0.1 map of soil organic carbon [<xref rid="cit0052" ref-type="bibr">52</xref>].</p><p>Here, the highest amounts of organic carbon are found in north central and north east
US, mainly associated with forest and south east mainly associated with wetlands. The US
product has been produced by mainly using harmonized soil maps from the Digital General
Soil Map of the United States or STATSGO2. This is a broad-based inventory of soils at
scales 1:250,000, available online at <ext-link ext-link-type="uri" xlink:href="http://websoilsurvey.nrcs.gov">http://websoilsurvey.nrcs.gov</ext-link></p><fig id="f0008" orientation="portrait" position="float"><label>Figure 8</label><caption><p>Maps of mean soil organic carbon (g.kg<sup>-</sup>) at the 6 standard depths for
continental USA.</p></caption><graphic xlink:href="CIAT-2017-j-grj-2017-06-001-g008"></graphic></fig></sec><sec id="sec6.3.3"><label>6.3.3</label><title>Other countries</title><p>Other countries in advanced stages of producing and delivering soil property maps
according to the GlobalSoilMap specifications are France [<xref rid="cit0120" ref-type="bibr">120</xref>–<xref rid="cit0123" ref-type="bibr">123</xref>],
Denmark [<xref rid="cit0044" ref-type="bibr">44</xref>–<xref rid="cit0045" ref-type="bibr">45</xref>], Scotland [<xref rid="cit0093" ref-type="bibr">93</xref>–<xref rid="cit0094" ref-type="bibr">94</xref>] and Nigeria [<xref rid="cit0070" ref-type="bibr">70</xref>, <xref rid="cit0072" ref-type="bibr">72</xref>–<xref rid="cit0073" ref-type="bibr">73</xref>]. France recently
produced the primary soil properties at 3 arc-second to 3 arc-second resolution [<xref rid="cit0123" ref-type="bibr">123</xref>] and developed an automated to map these
properties down to 2-m depth. Several more local trials have been made in regions of
some countries [e;g, <xref rid="cit0037" ref-type="bibr">37</xref>–<xref rid="cit0038" ref-type="bibr">38</xref>, <xref rid="cit0076" ref-type="bibr">76</xref>–<xref rid="cit0077" ref-type="bibr">77</xref>, <xref rid="cit0086" ref-type="bibr">86</xref>, <xref rid="cit0119" ref-type="bibr">119</xref>, <xref rid="cit0124" ref-type="bibr">124</xref>, <xref rid="cit0128" ref-type="bibr">128</xref>]. In addition to that, numerous countries have indicated their willingness
to join the GlobalSoilMap project.</p></sec></sec></sec><sec id="sec7"><label>7</label><title>Discussion</title><p>The number of soil profiles available in national databases is likely underestimated, since
responses to our questionnaire from a large number of countries were missed. Moreover,
rescuing soil data is an ongoing effort and the number of rescued soil profiles is
anticipated to increase substantially. Some countries are involved in long-term soil data
rescuing efforts and are far from having completed their programmes. France, for instance,
continues an effort to to enrich the national soil database. The year 2015 was chosen for
relative comparisons of national soil databases, at the time this paper is published some of
them have achieved new data rescue. For instance, data rescuing is still very active in
Iran, where about 22,500 new profiles were prepared during 2016 and this process is still
ongoing. The Czech Republic indicated that there are about 350,000 scanned soil profiles
available from the soil survey of agricultural soils from 1960s. This set of scanned copies
is managed by the Research Institute of Soil and Water Conservation (RISWC) and represents a
very large potential for improving soil profiles density in the national database of the
Czech Republic. Some countries with intensive agriculture, such as Hungary, where national
agricultural subsidy systems are linked to compulsory soil tests have produced tremendous
amount of soil data with measured coordinates. Unfortunately, no organized data archiving
systems exist in these countries to integrate these data and make it available for further
use, so these data sources remain only in personal datasets. Making the use of the WoSIS
database could contribute to solving this issue.</p><p>Other countries (e.g., India, China, Russia, South Korea) have indicated their legacy
databases were still under construction. Indeed, most of the these countries are still
actively searching for legacy soil information with the potential of many survey reports
still to be rescued or retrieved. Therefore, it seems that an enormous potential remains in
many countries. The largest country of the world, Russia, undertook many soil surveys in the
past, most of which are not yet rescued; this may represent many hundreds of thousands of
soil profiles. The global potential for rescuing soil profile data could be in the millions
of profiles.</p><p>Rescue efforts of legacy soil maps should be pursued. Indeed, in some places of the world
this maybe the only available information on soils. This information can be used as default
input data to predict a set of soil properties. They can also be used as co-variates for
quantitative prediction of these properties. Finally, they are useful to facilitate expert
evaluation of digital maps of soil properties. As objectives and concepts of traditional
soil mapping varied among countries and evolved with time and advances in knowledge, the
issue of harmonization is central if we want to use them for global predictions.</p><p>Indeed, very large discrepancies exist among, and even within, national soil databases
irrespective of their geographical support (points of polygons). These databases strongly
differ in their range of measured soil parameters and in the analytical measurement
standards used. Moreover, uniformity in methodology and coverage, albeit existing in some
countries, is far from common even among national systems. In view of this situation, it is
clear that harmonisation and co-ordination are necessary in order to develop approaches that
rescue, harmonize, and curate the existing amount of legacy soil data that is being
collected [e.g. 14, 17, 20, 22, 35, 47, 53, 79, 134]. Furthermore, converting results from
different analytical protocols to one standard can be done by applying pedotransfer
functions, such as listed in [<xref rid="cit0011" ref-type="bibr">11</xref>], which was
recently done in the US for pH and bulk density [<xref rid="cit0012" ref-type="bibr">12</xref>–<xref rid="cit0013" ref-type="bibr">13</xref>] and in Africa for
available water holding capacity and root zone depth [<xref rid="cit0105" ref-type="bibr">105</xref>].</p><p>Nevertheless, soil data rescue efforts have already proven effective in delivering
harmonized gridded products of soil properties, with various degrees of resolution and
accuracy, and in some cases even covering the world. Numerous countries and institutions
have indicated their willingness to join the GlobalSoilMap initiative. A new working group
of the International Union of Soil Sciences has been recently created at the end of 2016. As
the number of rescued soil data will greatly increase in the near future, it will enable us
to deliver consistent high quality products more easily, updated when newly collected data
become available. We define a process as ‘bottom-up’ when it comes from a
country level action. Most data rescue programmes are based on curating original data from
countries and may therefore be considered as ‘bottom-up’. However, the spatial
modelling for prediction can be done at the country level, or at the world level as a whole.
One of the major expected outcomes of data rescuing is the encouragement and development of
country specific bottom-up products (or ‘mixed’ products using ensemble
techniques) and capacity development. This should limit the use of generic top-down product
approaches, which will nevertheless remain necessary to fill gaps where soil data is missing
or lost. We emphasize that GlobalSoilMap is not a static product, but is planned to evolve
continuously, as new data or new techniques become available. Legal restrictions related to
data property and privacy are serious issues for building an operational worldwide
centralized or distributed database of soil profiles and to the complete worldwide and
consistent product, useable by global modelers and a host of other users. This is why, when
possible, bottom-up approaches in compiling data and producing maps are preferable to
top-down.. Another advantage of local modelling is that it may give better results than
global modelling which generalizes more the relations between co-variates and soil
properties. Indeed, the relative importance of driving factors and co-variates may strongly
differ between physiographic areas. This is why utilizing all the data available at country
level generally allows to deliver better quality products. It also encourages countries to
develop their own capacities, have ownership and support future developments of revised
versions of maps representing their mandated country territories. Nevertheless, top-down
products, in soil modelling as well as soil data compilation, are certainly useful for
GlobalSoilMap as a whole, for a number of reasons:</p><list list-type="bullet"><list-item><p>They provided early proof of concept,</p></list-item><list-item><p>They provide a generic product which is complete and covers the globe, being relevant
for global users and updateable through country specific possibly collaborative
initiatives,</p></list-item><list-item><p>They allow to fill gaps where soil data is missing or lost,</p></list-item><list-item><p>They provide geographically continuous data products that are synchronized/harmonized
at state/country boundaries and will certainly be useful for final worldwide
harmonization,</p></list-item><list-item><p>They can be combined with country level products, for instance by using ensemble They
can be combined with country level products, for instance by using ensemble approaches
(refs)</p></list-item></list><p>Ultimately, the 90x90 m grid resolution sought by GlobalSoilMap, in addition to providing a
seamless product for the global modeling community, is aimed to provide suitable data to a
wide variety of communities that makes decisions at various levels from local (field) to
national scale and beyond. In this context, the end-user must be informed about the quality
of the products, since these maps are predictions which come along with a prediction
uncertainty. However, how to properly estimate the prediction uncertainties (and even the
uncertainty of the uncertainty) is still a matter of discussion and a question of further
research. Several options are described in the GlobalSoilMap specifications [<xref rid="cit0011" ref-type="bibr">11</xref>] and in [<xref rid="cit0129" ref-type="bibr">129</xref>]. Higher level products can be relatively easily validated with lower level
data. Furthermore, there is an ongoing effort to better define the accuracy of predictions
[<xref rid="cit0051" ref-type="bibr">51</xref>, <xref rid="cit0078" ref-type="bibr">78</xref>, <xref rid="cit0086" ref-type="bibr">86</xref>, <xref rid="cit0093" ref-type="bibr">93</xref>, <xref rid="cit0129" ref-type="bibr">129</xref>–<xref rid="cit0131" ref-type="bibr">131</xref>] and the sources of uncertainties. Another
challenge is how to take into account some large uncertainties, or imprecision in original
locations of soil profiles. This is especially relevant and challenging when data of
high-resolution are envisioned to be the final products (3 arc-sec). Also, the question of
influence on the age of the data rescued has to be solved. Most soil properties are rather
stable and have little change (coarse fragments, texture, CEC, soil depth) or change only
slowly and steadily over time. However, some properties are rather rapidly changing due to
changes in land-use (e.g. pH, soil organic carbon). For instance, a significant change in
peat extension in the Netherlands has been recently shown leading to updating soil maps
[<xref rid="cit0132" ref-type="bibr">132</xref>]. Moreover, some soil properties may also
change very rapidly, at a very local scale, due to farm management practices and thus
becoming obsolete for representing the current state of soil. At least, a map of the
sampling dates should be added to the GlobalSoilMap specifications. A first draft of this
map could be produced rather simply, e.g. by kriging the dates of sampling of the original
point data, and would indicate places where data is obviously obsolete.</p><p>The issues related to dates not only apply to sampling periods but also to the co-variates
used. Obviously, given the long time needed for soil formation, a large number of
co-variates used in digital soil mapping do not reflect the reality at some periods of the
pedogenesis. Topographic indexes are generally computed using up to date digital terrain
models and do not reflect the various steps of geomorphological changes over time. Current
climatic data relevance can also be discussed as many soils developed under largely
different climatic periods. Indeed as outlined by Grunwald [<xref rid="cit0010" ref-type="bibr">10</xref>] the time factor is much less used in digital soil mapping than
other scorpan factors.Ideally, if GlobalSoilMap products are to be used for monitoring, the
products should be harmonized to a common date (e.g. 2010), and if funds permit, the
products should also be based on newly sampled data. Commonly, most of the current
initiatives emphasizing the need for newly sampled data, based on the arguments presented
here, focus on collecting new data from topsoil only (e.g. [<xref rid="cit0099" ref-type="bibr">99</xref>–<xref rid="cit0103" ref-type="bibr">103</xref>]). Compared
to topsoil sampling, a major advantage of the legacy soil profiles data is that these were
sampled to a depth of generally 120 cm or more, providing a more in-depth understanding of
soil functions related to various environmental aspects and adequate data for analyses and
modelling. Therefore, we recommend that new sampling campaigns sample the full soil profile
as well. Indeed, collecting data at different times may be used to assess temporal changes
and to perform multi-temporal data updates and queries. Using legacy soil profiles data,
Stockmann et al., [<xref rid="cit0133" ref-type="bibr">133</xref>] recently generated
products following GlobalSoilMap specifications and incorporating a dynamic component.</p></sec><sec sec-type="conclusions" id="sec8"><label>8</label><title>Conclusion</title><p>GlobalSoilMap is the first digital soil mapping project having set specifications which
have been agreed upon by an international soil science community. Its aim is to cover the
entire world with a high resolution grid of predicted key soil properties along with their
prediction uncertainties, thereby supporting other scientific disciplines and local
management efforts. Significant progress has been achieved since its launch. Data rescue is
considered an essential prerequisite to achieve the products and tremendous progress has
been made. It is essential that this process be continued; myriads of soil reports and soil
maps are certainly still collecting dust on shelves. We encourage soil scientists and
librarians to make them available to the soil science community, ideally with digitized
georeferenced soil profile data, either at country, continental or world level. Fortunately,
numerous countries have indicated their willingness to join the project and continue this
important work.</p><p>We believe that combining countries and worldwide predictions could lead to a first product
completely meeting the GlobalSoilMap specifications by the end of 2020, and that for this
purpose both top-down and bottom up approaches are necessary and complementary. Although
progress has been made on quantifying the uncertainties of the soil predictions, we believe
that further research is still needed on this topic. Ideally, an independent set of
validation points, selected through a proper statistical design and possibly from national
data holdings, would help to ultimately validate the predictions and to map uncertainties.
Providing these uncertainties is essential for the end-users of this product. Also, it would
point out those areas in the world where data is too scarce and where new sampling or more
data rescue efforts are necessary.</p></sec></body><back><ack><title>Acknowledgements</title><p>GlobalSoilMap has been funded by the Bill and Melinda Gates foundation, by the European
Commission and by various country’s grants and various institutes and universities.
We are grateful to all the soil scientists, soil surveyors, librarians, universities,
institutes and agencies that contributed to the ongoing effort of soil data rescue.
GlobalSoilMap won an honorable mention at the International Data Rescue Award in the
Geosciences 2015. We are grateful to Elsevier and to the International Interdisciplinary
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