Criterion definition for the identification of physical-geographical boundaries of Khorezm oasis through remotely sensed data.
Identifieur interne : 000051 ( PubMed/Curation ); précédent : 000050; suivant : 000052Criterion definition for the identification of physical-geographical boundaries of Khorezm oasis through remotely sensed data.
Auteurs : Muzaffar Matchanov [Ouzbékistan] ; Ana Teodoro [Portugal] ; Christoph Schroder [Espagne]Source :
- Environmental monitoring and assessment [ 1573-2959 ] ; 2016.
English descriptors
- KwdEn :
- MESH :
- geographic : Asia.
- methods : Environmental Monitoring.
- Agriculture, Ecosystem, Geographic Information Systems, Geography, Remote Sensing Technology.
Abstract
The Khorezm oasis is one of the main ancient agricultural and cultural centers of Asia. Different studies have used administrative boundaries, without regard to the ecosystem complexity. Remote sensing is a technique that provides many advantages in relation to traditional land cover monitoring approaches. The main objective of this study was to identify the physical-geographical boundaries of Khorezm oasis and analyzed area change dynamics of the oasis using remote sensing data. Landsat 4-5 Thematic Mapper (TM) and Landsat 8 Operational Land Imager (OLI) images from 1998, 2010, and 2014 were used in order to identify the oasis boundaries by analyzing the normalized difference vegetation index (NDVI). The Landsat data were radiometric normalized before the NDVI estimation. Several NDVI cutoff values were tested in order to define the more adequate value to identify the oasis boundaries (NDVI ≥ 0.1 for 1998 and 2010 images and NDVI ≥ 0.2 for 2014 images). Geographical Information System (GIS) techniques were then used to calculate the oasis area (31,885.49, 30,005.58, and 28,966.08 km(2), for 1998, 2010, and 2014, respectively) and analyze the land cover changes. The oasis presents a total area loss of 2919.41 km(2) between 1998 and 2014. The mean percentage variations between 2010 and 1998 and from 2014 to 1998 were -5.9 and -9.2 %, respectively. Therefore, the Khorezm oasis lost more than 9 % of this area between 1998 and 2014. The main areas of decrease appeared in the southern parts of the Aral Sea where the last tributaries of the Amudarya River were located. This work allowed mapping the physical-geographical boundaries of Khorezm oasis and identifying its dynamics for the analyzed period. The methodology presented in this work can be applied to other oasis regions, located in different parts of the world.
DOI: 10.1007/s10661-015-5035-z
PubMed: 26676411
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FCUP, University of Porto, Rua do Campo Alegre, 4169-007, Porto, Portugal.</nlm:affiliation><country xml:lang="fr">Portugal</country><wicri:regionArea>Earth Sciences Institute (ICT), Pole of the FCUP, University of Porto, Rua do Campo Alegre, 4169-007, Porto</wicri:regionArea></affiliation></author><author><name sortKey="Schroder, Christoph" sort="Schroder, Christoph" uniqKey="Schroder C" first="Christoph" last="Schroder">Christoph Schroder</name><affiliation wicri:level="1"><nlm:affiliation>European Topic Centre for Spatial Information and Analysis, University of Malaga, 29071, Malaga, Spain.</nlm:affiliation><country xml:lang="fr">Espagne</country><wicri:regionArea>European Topic Centre for Spatial Information and Analysis, University of Malaga, 29071, Malaga</wicri:regionArea></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">PubMed</idno><date when="2016">2016</date><idno type="RBID">pubmed:26676411</idno><idno type="pmid">26676411</idno><idno 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Cartography, Geography, Faculty of Natural Sciences, Urgench State University, 220100, Khorezm</wicri:regionArea></affiliation></author><author><name sortKey="Teodoro, Ana" sort="Teodoro, Ana" uniqKey="Teodoro A" first="Ana" last="Teodoro">Ana Teodoro</name><affiliation wicri:level="1"><nlm:affiliation>Earth Sciences Institute (ICT), Pole of the FCUP, University of Porto, Rua do Campo Alegre, 4169-007, Porto, Portugal.</nlm:affiliation><country xml:lang="fr">Portugal</country><wicri:regionArea>Earth Sciences Institute (ICT), Pole of the FCUP, University of Porto, Rua do Campo Alegre, 4169-007, Porto</wicri:regionArea></affiliation></author><author><name sortKey="Schroder, Christoph" sort="Schroder, Christoph" uniqKey="Schroder C" first="Christoph" last="Schroder">Christoph Schroder</name><affiliation wicri:level="1"><nlm:affiliation>European Topic Centre for Spatial Information and Analysis, University of Malaga, 29071, Malaga, Spain.</nlm:affiliation><country xml:lang="fr">Espagne</country><wicri:regionArea>European Topic Centre for Spatial Information and Analysis, University of Malaga, 29071, Malaga</wicri:regionArea></affiliation></author></analytic><series><title level="j">Environmental monitoring and assessment</title><idno type="eISSN">1573-2959</idno><imprint><date when="2016" type="published">2016</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Agriculture</term><term>Asia</term><term>Ecosystem</term><term>Environmental Monitoring (methods)</term><term>Geographic Information Systems</term><term>Geography</term><term>Remote Sensing Technology</term></keywords><keywords scheme="MESH" type="geographic" xml:lang="en"><term>Asia</term></keywords><keywords scheme="MESH" qualifier="methods" xml:lang="en"><term>Environmental Monitoring</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Agriculture</term><term>Ecosystem</term><term>Geographic Information Systems</term><term>Geography</term><term>Remote Sensing Technology</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">The Khorezm oasis is one of the main ancient agricultural and cultural centers of Asia. Different studies have used administrative boundaries, without regard to the ecosystem complexity. Remote sensing is a technique that provides many advantages in relation to traditional land cover monitoring approaches. The main objective of this study was to identify the physical-geographical boundaries of Khorezm oasis and analyzed area change dynamics of the oasis using remote sensing data. Landsat 4-5 Thematic Mapper (TM) and Landsat 8 Operational Land Imager (OLI) images from 1998, 2010, and 2014 were used in order to identify the oasis boundaries by analyzing the normalized difference vegetation index (NDVI). The Landsat data were radiometric normalized before the NDVI estimation. Several NDVI cutoff values were tested in order to define the more adequate value to identify the oasis boundaries (NDVI ≥ 0.1 for 1998 and 2010 images and NDVI ≥ 0.2 for 2014 images). Geographical Information System (GIS) techniques were then used to calculate the oasis area (31,885.49, 30,005.58, and 28,966.08 km(2), for 1998, 2010, and 2014, respectively) and analyze the land cover changes. The oasis presents a total area loss of 2919.41 km(2) between 1998 and 2014. The mean percentage variations between 2010 and 1998 and from 2014 to 1998 were -5.9 and -9.2 %, respectively. Therefore, the Khorezm oasis lost more than 9 % of this area between 1998 and 2014. The main areas of decrease appeared in the southern parts of the Aral Sea where the last tributaries of the Amudarya River were located. This work allowed mapping the physical-geographical boundaries of Khorezm oasis and identifying its dynamics for the analyzed period. The methodology presented in this work can be applied to other oasis regions, located in different parts of the world.</div></front></TEI><pubmed><MedlineCitation Status="MEDLINE" Owner="NLM"><PMID Version="1">26676411</PMID><DateCreated><Year>2015</Year><Month>12</Month><Day>17</Day></DateCreated><DateCompleted><Year>2016</Year><Month>06</Month><Day>17</Day></DateCompleted><DateRevised><Year>2015</Year><Month>12</Month><Day>17</Day></DateRevised><Article PubModel="Print-Electronic"><Journal><ISSN IssnType="Electronic">1573-2959</ISSN><JournalIssue CitedMedium="Internet"><Volume>188</Volume><Issue>1</Issue><PubDate><Year>2016</Year><Month>Jan</Month></PubDate></JournalIssue><Title>Environmental monitoring and assessment</Title><ISOAbbreviation>Environ Monit Assess</ISOAbbreviation></Journal><ArticleTitle>Criterion definition for the identification of physical-geographical boundaries of Khorezm oasis through remotely sensed data.</ArticleTitle><Pagination><MedlinePgn>35</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.1007/s10661-015-5035-z</ELocationID><Abstract><AbstractText>The Khorezm oasis is one of the main ancient agricultural and cultural centers of Asia. Different studies have used administrative boundaries, without regard to the ecosystem complexity. Remote sensing is a technique that provides many advantages in relation to traditional land cover monitoring approaches. The main objective of this study was to identify the physical-geographical boundaries of Khorezm oasis and analyzed area change dynamics of the oasis using remote sensing data. Landsat 4-5 Thematic Mapper (TM) and Landsat 8 Operational Land Imager (OLI) images from 1998, 2010, and 2014 were used in order to identify the oasis boundaries by analyzing the normalized difference vegetation index (NDVI). The Landsat data were radiometric normalized before the NDVI estimation. Several NDVI cutoff values were tested in order to define the more adequate value to identify the oasis boundaries (NDVI ≥ 0.1 for 1998 and 2010 images and NDVI ≥ 0.2 for 2014 images). Geographical Information System (GIS) techniques were then used to calculate the oasis area (31,885.49, 30,005.58, and 28,966.08 km(2), for 1998, 2010, and 2014, respectively) and analyze the land cover changes. The oasis presents a total area loss of 2919.41 km(2) between 1998 and 2014. The mean percentage variations between 2010 and 1998 and from 2014 to 1998 were -5.9 and -9.2 %, respectively. Therefore, the Khorezm oasis lost more than 9 % of this area between 1998 and 2014. The main areas of decrease appeared in the southern parts of the Aral Sea where the last tributaries of the Amudarya River were located. This work allowed mapping the physical-geographical boundaries of Khorezm oasis and identifying its dynamics for the analyzed period. The methodology presented in this work can be applied to other oasis regions, located in different parts of the world.</AbstractText></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Matchanov</LastName><ForeName>Muzaffar</ForeName><Initials>M</Initials><AffiliationInfo><Affiliation>Department of Geodesy, Cartography, Geography, Faculty of Natural Sciences, Urgench State University, 220100, Khorezm, Uzbekistan. mmuzaffar@yandex.ru.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Teodoro</LastName><ForeName>Ana</ForeName><Initials>A</Initials><AffiliationInfo><Affiliation>Earth Sciences Institute (ICT), Pole of the FCUP, University of Porto, Rua do Campo Alegre, 4169-007, Porto, Portugal.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Schroder</LastName><ForeName>Christoph</ForeName><Initials>C</Initials><AffiliationInfo><Affiliation>European Topic Centre for Spatial Information and Analysis, University of Malaga, 29071, Malaga, Spain.</Affiliation></AffiliationInfo></Author></AuthorList><Language>eng</Language><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType></PublicationTypeList><ArticleDate DateType="Electronic"><Year>2015</Year><Month>12</Month><Day>16</Day></ArticleDate></Article><MedlineJournalInfo><Country>Netherlands</Country><MedlineTA>Environ Monit Assess</MedlineTA><NlmUniqueID>8508350</NlmUniqueID><ISSNLinking>0167-6369</ISSNLinking></MedlineJournalInfo><CitationSubset>IM</CitationSubset><MeshHeadingList><MeshHeading><DescriptorName UI="D000383" MajorTopicYN="N">Agriculture</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D001208" MajorTopicYN="N" Type="Geographic">Asia</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D017753" MajorTopicYN="N">Ecosystem</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D004784" MajorTopicYN="N">Environmental Monitoring</DescriptorName><QualifierName UI="Q000379" MajorTopicYN="Y">methods</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D040362" MajorTopicYN="N">Geographic Information Systems</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D005843" MajorTopicYN="N">Geography</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D058998" MajorTopicYN="Y">Remote Sensing Technology</DescriptorName></MeshHeading></MeshHeadingList><KeywordList Owner="NOTNLM"><Keyword MajorTopicYN="N">Change detection</Keyword><Keyword MajorTopicYN="N">Landsat data</Keyword><Keyword MajorTopicYN="N">NDVI</Keyword><Keyword MajorTopicYN="N">Oasis ecosystems</Keyword><Keyword MajorTopicYN="N">Physical-geographical boundaries</Keyword></KeywordList></MedlineCitation><PubmedData><History><PubMedPubDate PubStatus="received"><Year>2015</Year><Month>05</Month><Day>06</Day></PubMedPubDate><PubMedPubDate PubStatus="accepted"><Year>2015</Year><Month>12</Month><Day>07</Day></PubMedPubDate><PubMedPubDate PubStatus="entrez"><Year>2015</Year><Month>12</Month><Day>18</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="pubmed"><Year>2015</Year><Month>12</Month><Day>18</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="medline"><Year>2016</Year><Month>6</Month><Day>18</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate></History><PublicationStatus>ppublish</PublicationStatus><ArticleIdList><ArticleId IdType="pubmed">26676411</ArticleId><ArticleId IdType="doi">10.1007/s10661-015-5035-z</ArticleId><ArticleId IdType="pii">10.1007/s10661-015-5035-z</ArticleId></ArticleIdList></PubmedData></pubmed></record>Pour manipuler ce document sous Unix (Dilib)
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