Satellite-based analysis and monitoring of agro-ecosystems and land degradation and desertification in Central Asia

cg.contactc.biradar@gmail.comen_US
cg.contributor.centerInternational Center for Agricultural Research in the Dry Areas - ICARDAen_US
cg.contributor.crpCGIAR Research Program on Dryland Systems - DSen_US
cg.contributor.funderCGIAR System Organization - CGIARen_US
cg.contributor.project-lead-instituteInternational Center for Agricultural Research in the Dry Areas - ICARDAen_US
cg.coverage.countryUZen_US
cg.coverage.regionCentral Asiaen_US
cg.creator.idBiradar, Chandrashekhar: 0000-0002-9532-9452en_US
cg.date.embargo-end-dateTimelessen_US
cg.subject.agrovocagricultureen_US
cg.subject.agrovocanalysisen_US
cg.subject.agrovocdesertificationen_US
cg.subject.agrovocland degradationen_US
cg.subject.agrovocgeodataen_US
dc.creatorBiradar, Chandrashekharen_US
dc.date.accessioned2016-02-01T21:26:46Z
dc.date.available2016-02-01T21:26:46Z
dc.description.abstractThe Central Asia includes six countries (Kazakstan, Uzbekistan, Kyrgystan, Tajistan, Afganistan, Turkmenistan). Grassland degradation and desertification in the Central Asia has been accelerated over the past few decades due to increasing livestock grazing intensity and climate variability (Berger et al. 2013; Chuluun and Ojima 2002; von Wehrden et al. 2010). To restore, maintain, and enhance grassland condition and productivity in the Central Asia is the goal of many research and development projects in the region. However, these efforts have been hampered by the lack of (1) updated and accurate information on grassland dynamics, conditions, and productivity; and (2) the capacity to generate such information in timely manner. Satellite remote sensing has been playing an increasing role in characterization and monitoring of grassland condition and productivity (Kariyeva and van Leeuwen 2011; Li and Yang 2014; Sternberg et al. 2011). Most previous studies have used Normalized Difference Vegetation Index (NDVI) data from optical images to evaluate grassland condition and productivity in the context of land degradation and desertification (Emerson et al. 2010; Sternberg et al. 2011; Wang et al. 2014). Recently, a few studies in North American grasslands and Mongolia grasslands show that Enhanced Vegetation Index (EVI) and Land Surface Water Index (LSWI) are better indicators of grassland condition and productivity (John et al. 2013; Wagle et al. 2014; Wang et al. 2010b). Here we reported preliminary results from a pilot project that evaluated satellite-based three vegetation indices (NDVI, EVI and LSWI) and land surface temperature (LST) for characterization and monitoring of grassland degradation and desertification in the Central Asia. It used MODIS data from 2000-2013 at selected areas (H22V04, H23V04). If proved to be useful, we will incorporate it into our satellite-based monitoring program and implement it for regional mapping and monitoring of grassland degradation and desertification in the Central Asia.en_US
dc.formatPDFen_US
dc.identifierhttps://mel.cgiar.org/dspace/limiteden_US
dc.identifier.citationChandrashekhar Biradar. (1/1/2015). Satellite-based analysis and monitoring of agro-ecosystems and land degradation and desertification in Central Asia.en_US
dc.identifier.statusTimeless limited accessen_US
dc.identifier.urihttps://hdl.handle.net/20.500.11766/3234
dc.languageenen_US
dc.subjectagroecosystemen_US
dc.titleSatellite-based analysis and monitoring of agro-ecosystems and land degradation and desertification in Central Asiaen_US
dc.typeReporten_US
dcterms.available2015-01-01en_US
mel.sub-typeDonor Reporten_US

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