Land Cover Conversion and Degradation Analyses Through Coupled Soil-Plant Biophysical Parameters Derived From Hyperspectral EO-1 Hyperion

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dc.contributor.author Huete, Alfredo en_US
dc.contributor.author Miura, Tomoaki en_US
dc.contributor.author Gao, Xiang en_US
dc.contributor.editor en_US
dc.date.accessioned 2010-05-28T09:43:51Z
dc.date.available 2010-05-28T09:43:51Z
dc.date.issued 2003 en_US
dc.identifier 2009001450 en_US
dc.identifier.citation Huete Alfredo, Miura Tomoaki, and Gao Xiang 2003, 'Land Cover Conversion and Degradation Analyses Through Coupled Soil-Plant Biophysical Parameters Derived From Hyperspectral EO-1 Hyperion', IEEE, vol. 41, no. 6, pp. 1268-1276. en_US
dc.identifier.issn 0196-2892 en_US
dc.identifier.other C1UNSUBMIT en_US
dc.identifier.uri http://hdl.handle.net/10453/8540
dc.description.abstract Land degradation in semiarid areas results from various factors, including climate variations and human activity, and can lead to desertification. The process of degradation results in simultaneous and complex variations of many interrelated soil and vegetation biophysical parameters, rendering it difficult to develop simple and robust remote sensing mapping and monitoring approaches. In this study, we tested the use of Earth Observing 1 (EO-1) Hyperion hyperspectral data to analyze land degradation patterns within the protected Nacunan Biosphere Reserve and surrounding areas in the Monte Desert region of Argentina. The floristically diverse vegetation communities included mesquite forest (algarrobal), creosotebush (jarillal), sand-dune (medanal), and severely degraded (peladal) sites. Various optical measures of land degradation were employed, including vegetation indexes, spectral derivatives, albedo, and spectral mixture analysis. Spectral mixture analysis provided the best characterization of the unstable and spatially variable landscape encountered at the Nacunan Biosphere Reserve. Spectral unmixing provided simultaneous measures of green vegetation, nonphotosynthetic vegetation, and soil, all of which were deemed essential in characterizing land degradation. In conjunction with multitemporal data from the more commonly employed broadband sensors, hyperspectral data can provide a powerful methodology toward understanding environmental degradation. en_US
dc.language en_US
dc.publisher IEEE en_US
dc.relation.isbasedon http://dx.doi.org/10.1109/TGRS.2003.813209 en_US
dc.title Land Cover Conversion and Degradation Analyses Through Coupled Soil-Plant Biophysical Parameters Derived From Hyperspectral EO-1 Hyperion en_US
dc.parent IEEE Transactions on Geoscience and Remote Sensing en_US
dc.journal.volume 41 en_US
dc.journal.number 6 en_US
dc.publocation United States en_US
dc.identifier.startpage 1268 en_US
dc.identifier.endpage 1276 en_US
dc.cauo.name SCI.Faculty of Science en_US
dc.conference Verified OK en_US
dc.for 040400 en_US
dc.personcode 108636 en_US
dc.personcode 0000058680 en_US
dc.personcode 0000058987 en_US
dc.percentage 100 en_US
dc.classification.name Geophysics en_US
dc.classification.type FOR-08 en_US
dc.edition en_US
dc.custom en_US
dc.date.activity en_US
dc.location.activity en_US
dc.description.keywords 400 to 2500 nm , AD 2000 , AD 2001 , Argentina , EO-1 , Hyperion , IR , Monte Desert region , Nacunan , algarrobal , biophysical parameters , creosotebush , degradation analysis , desertification , environmental science , forestry , geophysical measurement technique , hyperspectral remote sensing , infrared , jarillal , land cover conversion , land degradation , land surface , medanal , mesquite forest , peladal , planet , sand-dune , satellite remote sensing , semiarid areas , severely degraded sites , soil , terrain mapping , vegetation mapping , visible en_US


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