Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/7268
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dc.contributorDepartment of Land Surveying and Geo-Informatics-
dc.creatorAbbas, Sen_US
dc.creatorNichol, Jen_US
dc.creatorQamer, FMen_US
dc.creatorXu, Jen_US
dc.date.accessioned2015-11-10T08:32:45Z-
dc.date.available2015-11-10T08:32:45Z-
dc.identifier.urihttp://hdl.handle.net/10397/7268-
dc.language.isoenen_US
dc.publisherMolecular Diversity Preservation International (MDPI)en_US
dc.rights© 2014 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/3.0/).en_US
dc.rightsThe following publication Abbas, S., Nichol, J. E., Qamer, F. M. & Xu, J. (2014). Characterization of drought development through remote sensing : a case study in Central Yunnan, China. Remote Sensing, 6(6), 4998-5018 is available at http://dx.doi.org/10.3390/rs6064998en_US
dc.subjectNDVIen_US
dc.subjectNVSWIen_US
dc.subjectdrought indexen_US
dc.subjectLSTen_US
dc.subjectTRMMen_US
dc.titleCharacterization of drought development through remote sensing : a case study in Central Yunnan, Chinaen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.spage4998en_US
dc.identifier.epage5018en_US
dc.identifier.volume6en_US
dc.identifier.issue6en_US
dc.identifier.doi10.3390/rs6064998en_US
dcterms.abstractThis study assesses the applicability of remote sensing data for retrieval of key drought indicators including the degree of moisture deficiency, drought duration and areal extent of drought within different land cover types across the landscape. A Normalized Vegetation Supply Water Index (NVSWI) is devised, combining remotely sensed climate data to retrieve key drought indicators over different vegetation cover types and a lag-time relationship is established based on preceding rainfall. The results indicate that during the major drought event of spring 2010, Evergreen Forest (EF) experienced severe dry conditions for 48 days fewer than Cropland (CL) and Shrubland (SL). Testing of vegetation response to drought conditions with different lag-time periods since the last rainfall indicated a highest correlation for CL and SL with the 4th lag period (i.e., 64 days) whereas EF exhibited maximum correlation with the 5th lag period (i.e., 80 days). Evergreen Forest, which includes tree crops, appears to act as a green reservoir of water, and is more resistant than CL and SL to drought due to its water retention capacity with deeper roots to tap sub-surface water. Identifying differences in rainfall lag-time relationships among land cover types using a remote sensing-based integrated drought index enables more accurate drought prediction, and can thus assist in the development of more specific drought adaptation strategies.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationRemote sensing, May 2014, v. 6, no. 6, p. 4998-5018en_US
dcterms.isPartOfRemote sensingen_US
dcterms.issued2014-
dc.identifier.eissn2072-4292en_US
dc.identifier.rosgroupidr69580-
dc.description.ros2013-2014 > Academic research: refereed > Publication in refereed journal-
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumberOA_IR/PIRA-
dc.description.pubStatusPublisheden_US
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