Using Imaging Spectroscopy to study soil properties
Identifieur interne : 000F38 ( Main/Exploration ); précédent : 000F37; suivant : 000F39Using Imaging Spectroscopy to study soil properties
Auteurs : E. Ben-Dor [Israël] ; S. Chabrillat [Allemagne] ; J. A. M. Dematte [Brésil] ; G. R. Taylor [Australie] ; J. Hill [Allemagne] ; M. L. Whiting [États-Unis] ; S. Sommer [Italie]Source :
- Remote sensing of environment [ 0034-4257 ] ; 2009.
Descripteurs français
- Pascal (Inist)
- Utilisation, Capteur imagerie hyperspectral, Caractéristique sol, Imagerie, Spectrométrie, Signal, Bruit, Contamination, Atmosphère, Technologie, Pédologie, Science du sol, Détérioration du sol, Salinité, Erosion sol, Dépôt, Carte pédologique, Cartographie, Classification, Télédétection, Pouvoir réflecteur.
- Wicri :
- topic : Spectrométrie, Bruit, Atmosphère, Technologie, Cartographie, Classification, Télédétection.
English descriptors
- KwdEn :
Abstract
Imaging Spectroscopy (IS) is a promising tool for studying soil properties in large spatial domains. Going from point to image spectrometry is not only a journey from micro to macro scales, but also a long stage where problems such as dealing with data having a low signal-to-noise level, contamination of the atmosphere, large data sets, the BRDF effect and more are often encountered. In this paper we provide an up-to-date overview of some of the case studies that have used IS technology for soil science applications. Besides a brief discussion on the advantages and disadvantages of IS for studying soils, the following cases are comprehensively discussed: soil degradation (salinity, erosion, and deposition), soil mapping and classification, soil genesis and formation, soil contamination, soil water content, and soil swelling. We review these case studies and suggest that the IS data be provided to the end-users as real reflectance and not as raw data and with better signal-to-noise ratios than presently exist. This is because converting the raw data into reflectance is a complicated stage that requires experience, knowledge, and specific infrastructures not available to many users, whereas quantitative spectral models require good quality data. These limitations serve as a barrier that impedes potential end-users, inhibiting researchers from trying this technique for their needs. The paper ends with a general call to the soil science audience to extend the utilization of the IS technique, and it provides some ideas on how to propel this technology forward to enable its widespread adoption in order to achieve a breakthrough in the field of soil science and remote sensing.
Affiliations:
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Ben-Dor</name><affiliation wicri:level="1"><inist:fA14 i1="01"><s1>Deparhnent of Geography and Human Environment, Tel Aviv University</s1><s3>ISR</s3><sZ>1 aut.</sZ></inist:fA14><country>Israël</country><wicri:noRegion>Deparhnent of Geography and Human Environment, Tel Aviv University</wicri:noRegion></affiliation></author><author><name sortKey="Chabrillat, S" sort="Chabrillat, S" uniqKey="Chabrillat S" first="S." last="Chabrillat">S. Chabrillat</name><affiliation wicri:level="3"><inist:fA14 i1="02"><s1>GeoForchungsZentrum(GFZ) Potsdam, Section 1.4: Remote Sensing</s1><s2>Potsdam</s2><s3>DEU</s3><sZ>2 aut.</sZ></inist:fA14><country>Allemagne</country><placeName><region type="land" nuts="2">Brandebourg</region><settlement type="city">Potsdam</settlement></placeName></affiliation></author><author><name sortKey="Dematte, J A M" sort="Dematte, J A M" uniqKey="Dematte J" first="J. A. M." last="Dematte">J. A. M. Dematte</name><affiliation wicri:level="1"><inist:fA14 i1="03"><s1>Department of Soil Science, São Paulo University, ESALQ</s1><s2>Piracicaba</s2><s3>BRA</s3><sZ>3 aut.</sZ></inist:fA14><country>Brésil</country><wicri:noRegion>Piracicaba</wicri:noRegion></affiliation></author><author><name sortKey="Taylor, G R" sort="Taylor, G R" uniqKey="Taylor G" first="G. R." last="Taylor">G. R. Taylor</name><affiliation wicri:level="3"><inist:fA14 i1="04"><s1>School of Biological, Earth and Environmental Science, University of New South Wales</s1><s2>Sydney</s2><s3>AUS</s3><sZ>4 aut.</sZ></inist:fA14><country>Australie</country><placeName><settlement type="city">Sydney</settlement></placeName></affiliation></author><author><name sortKey="Hill, J" sort="Hill, J" uniqKey="Hill J" first="J." last="Hill">J. Hill</name><affiliation wicri:level="1"><inist:fA14 i1="05"><s1>Remote Sensing Department, Faculty of Geography/Geosciences, Trier University</s1><s3>DEU</s3><sZ>5 aut.</sZ></inist:fA14><country>Allemagne</country><wicri:noRegion>Trier University</wicri:noRegion><wicri:noRegion>Remote Sensing Department, Faculty of Geography/Geosciences, Trier University</wicri:noRegion></affiliation></author><author><name sortKey="Whiting, M L" sort="Whiting, M L" uniqKey="Whiting M" first="M. L." last="Whiting">M. L. Whiting</name><affiliation wicri:level="2"><inist:fA14 i1="06"><s1>Department of Land Air Water Resources, University of California</s1><s2>Davis, California</s2><s3>USA</s3><sZ>6 aut.</sZ></inist:fA14><country>États-Unis</country><placeName><region type="state">Californie</region></placeName></affiliation></author><author><name sortKey="Sommer, S" sort="Sommer, S" uniqKey="Sommer S" first="S." last="Sommer">S. Sommer</name><affiliation wicri:level="1"><inist:fA14 i1="07"><s1>European Commission, DG Joint Research Centre, Institute for Environment and Sustainability</s1><s2>Ispra</s2><s3>ITA</s3><sZ>7 aut.</sZ></inist:fA14><country>Italie</country><wicri:noRegion>Ispra</wicri:noRegion></affiliation></author></analytic><series><title level="j" type="main">Remote sensing of environment</title><title level="j" type="abbreviated">Remote sens. environ.</title><idno type="ISSN">0034-4257</idno><imprint><date when="2009">2009</date></imprint></series></biblStruct></sourceDesc><seriesStmt><title level="j" type="main">Remote sensing of environment</title><title level="j" type="abbreviated">Remote sens. environ.</title><idno type="ISSN">0034-4257</idno></seriesStmt></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Hyperspectral imaging sensor</term><term>Property of soil</term><term>Soil deterioration</term><term>Soil science</term><term>atmosphere</term><term>cartography</term><term>classification</term><term>contamination</term><term>deposition</term><term>imagery</term><term>noise</term><term>reflectance</term><term>remote sensing</term><term>salinity</term><term>signals</term><term>soil erosion</term><term>soil sciences</term><term>soils maps</term><term>spectroscopy</term><term>technology</term><term>utilization</term></keywords><keywords scheme="Pascal" xml:lang="fr"><term>Utilisation</term><term>Capteur imagerie hyperspectral</term><term>Caractéristique sol</term><term>Imagerie</term><term>Spectrométrie</term><term>Signal</term><term>Bruit</term><term>Contamination</term><term>Atmosphère</term><term>Technologie</term><term>Pédologie</term><term>Science du sol</term><term>Détérioration du sol</term><term>Salinité</term><term>Erosion sol</term><term>Dépôt</term><term>Carte pédologique</term><term>Cartographie</term><term>Classification</term><term>Télédétection</term><term>Pouvoir réflecteur</term></keywords><keywords scheme="Wicri" type="topic" xml:lang="fr"><term>Spectrométrie</term><term>Bruit</term><term>Atmosphère</term><term>Technologie</term><term>Cartographie</term><term>Classification</term><term>Télédétection</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">Imaging Spectroscopy (IS) is a promising tool for studying soil properties in large spatial domains. Going from point to image spectrometry is not only a journey from micro to macro scales, but also a long stage where problems such as dealing with data having a low signal-to-noise level, contamination of the atmosphere, large data sets, the BRDF effect and more are often encountered. In this paper we provide an up-to-date overview of some of the case studies that have used IS technology for soil science applications. Besides a brief discussion on the advantages and disadvantages of IS for studying soils, the following cases are comprehensively discussed: soil degradation (salinity, erosion, and deposition), soil mapping and classification, soil genesis and formation, soil contamination, soil water content, and soil swelling. We review these case studies and suggest that the IS data be provided to the end-users as real reflectance and not as raw data and with better signal-to-noise ratios than presently exist. This is because converting the raw data into reflectance is a complicated stage that requires experience, knowledge, and specific infrastructures not available to many users, whereas quantitative spectral models require good quality data. These limitations serve as a barrier that impedes potential end-users, inhibiting researchers from trying this technique for their needs. The paper ends with a general call to the soil science audience to extend the utilization of the IS technique, and it provides some ideas on how to propel this technology forward to enable its widespread adoption in order to achieve a breakthrough in the field of soil science and remote sensing.</div></front></TEI><affiliations><list><country><li>Allemagne</li><li>Australie</li><li>Brésil</li><li>Israël</li><li>Italie</li><li>États-Unis</li></country><region><li>Brandebourg</li><li>Californie</li></region><settlement><li>Potsdam</li><li>Sydney</li></settlement></list><tree><country name="Israël"><noRegion><name sortKey="Ben Dor, E" sort="Ben Dor, E" uniqKey="Ben Dor E" first="E." last="Ben-Dor">E. Ben-Dor</name></noRegion></country><country name="Allemagne"><region name="Brandebourg"><name sortKey="Chabrillat, S" sort="Chabrillat, S" uniqKey="Chabrillat S" first="S." last="Chabrillat">S. Chabrillat</name></region><name sortKey="Hill, J" sort="Hill, J" uniqKey="Hill J" first="J." last="Hill">J. Hill</name></country><country name="Brésil"><noRegion><name sortKey="Dematte, J A M" sort="Dematte, J A M" uniqKey="Dematte J" first="J. A. M." last="Dematte">J. A. M. Dematte</name></noRegion></country><country name="Australie"><noRegion><name sortKey="Taylor, G R" sort="Taylor, G R" uniqKey="Taylor G" first="G. R." last="Taylor">G. R. Taylor</name></noRegion></country><country name="États-Unis"><region name="Californie"><name sortKey="Whiting, M L" sort="Whiting, M L" uniqKey="Whiting M" first="M. L." last="Whiting">M. L. Whiting</name></region></country><country name="Italie"><noRegion><name sortKey="Sommer, S" sort="Sommer, S" uniqKey="Sommer S" first="S." last="Sommer">S. Sommer</name></noRegion></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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