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dc.contributorPrishchepov, Alexanderen_US
dc.contributorWaldner, Françoisen_US
dc.contributorDubovyk, Olenaen_US
dc.contributorAkramkhanov, Akmalen_US
dc.contributorBiradar, Chandrashekharen_US
dc.contributorLamers, Johannesen_US
dc.creatorLoew, Fabianen_US
dc.date2018-01-23en_US
dc.date.accessioned2018-03-12T01:41:32Z
dc.date.available2018-03-12T01:41:32Z
dc.identifierhttps://mel.cgiar.org/reporting/download/hash/dZvFQhGZen_US
dc.identifier.citationFabian Loew, Alexander Prishchepov, François Waldner, Olena Dubovyk, Akmal Akramkhanov, Chandrashekhar Biradar, Johannes Lamers. (23/1/2018). Mapping Cropland Abandonment in the Aral Sea Basin with MODIS Time Series. Remote Sensing, 10.en_US
dc.identifier.urihttps://hdl.handle.net/20.500.11766/8076
dc.description.abstractCropland abandonment is globally widespread and has strong repercussions for regional food security and the environment. Statistics suggest that one of the hotspots of abandoned cropland is located in the drylands of the Aral Sea Basin (ASB), which covers parts of post-Soviet Central Asia, Afghanistan and Iran. To date, the exact spatial and temporal extents of abandoned cropland remain unclear, which hampers land-use planning. Abandoned land is a potentially valuable resource for alternative land uses. Here, we mapped the abandoned cropland in the drylands of the ASB with a time series of the Normalized Difference Vegetation Index (NDVI) from the Moderate Resolution Imaging Spectroradiometer (MODIS) from 2003–2016. To overcome the restricted ability of a single classifier to accurately map land-use classes across large areas and agro-environmental gradients, “stratum-specific” classifiers were calibrated and classification results were fused based on a locally weighted decision fusion approach. Next, the agro-ecological suitability of abandoned cropland areas was evaluated. The stratum-specific classification approach yielded an overall accuracy of 0.879, which was significantly more accurate (p < 0.05) than a “global” classification without stratification, which had an accuracy of 0.811. In 2016, the classification results showed that 13% (1.15 Mha) of the observed irrigated cropland in the ASB was idle (abandoned). Cropland abandonment occurred mostly in the Amudarya and Syrdarya downstream regions and was associated with degraded land and areas prone to water stress. Despite the almost twofold population growth and increasing food demand in the ASB area from 1990 to 2016, abandoned cropland was also located in areas with high suitability for farming. The map of abandoned cropland areas provides a novel basis for assessing the causes leading to abandoned cropland in the ASB. This contributes to assessing the suitability of abandoned cropland for food or bioenergy production, carbon storage, or assessing the environmental trade-offs and social constraints of recultivation.en_US
dc.formatPDFen_US
dc.languageenen_US
dc.publisherMDPIen_US
dc.rightsCC-BY-4.0en_US
dc.sourceRemote Sensing;10,(2018)en_US
dc.subjectaral sea basinen_US
dc.subjectchange detectionen_US
dc.subjectabandoned croplanden_US
dc.subjectdecision fusionen_US
dc.titleMapping Cropland Abandonment in the Aral Sea Basin with MODIS Time Seriesen_US
dc.typeJournal Articleen_US
cg.creator.idLoew, Fabian: 0000-0002-0632-890Xen_US
cg.creator.idAkramkhanov, Akmal: 0000-0002-4316-5580en_US
cg.creator.idBiradar, Chandrashekhar: 0000-0002-9532-9452en_US
cg.creator.ID-typeORCIDen_US
cg.creator.ID-typeORCIDen_US
cg.creator.ID-typeORCIDen_US
cg.subject.agrovocland useen_US
cg.subject.agrovocmodisen_US
cg.contributor.centerInternational Center for Agricultural Research in the Dry Areas - ICARDAen_US
cg.contributor.centerLeibniz Institute of Agricultural Development in Transition Economies - IAMOen_US
cg.contributor.centerUniversite Catholique de Louvain - UCLen_US
cg.contributor.centerUniversity of Bonn - Uni-Bonnen_US
cg.contributor.centerUniversity of Bonn, Center for Development Research - Uni-Bonn - ZEFen_US
cg.contributor.funderInternational Center for Agricultural Research in the Dry Areas - ICARDAen_US
cg.contributor.projectGeoinformatics and Data Management for integrated agroecosystem research, development and outreachen_US
cg.contributor.project-lead-instituteInternational Center for Agricultural Research in the Dry Areas - ICARDAen_US
cg.coverage.regionCentral Asiaen_US
cg.coverage.countryKZen_US
cg.coverage.countryUZen_US
cg.contactfabian.loew@maptailor.neten_US
cg.identifier.doihttps://dx.doi.org/10.3390/rs10020159en_US
dc.identifier.statusOpen accessen_US
mel.project.openhttp://www.icarda.org/en_US
mel.impact-factor3.406en_US


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