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dc.contributorAl-Shafie, Waleed M.en_US
dc.contributorMhaimeed, Ahmad S.en_US
dc.contributorZiadat, Feras M.en_US
dc.contributorNangia, Vinayen_US
dc.contributorPayne, Williamen_US
dc.creatorWu, Weichengen_US
dc.date2014-11-11en_US
dc.date.accessioned2017-07-24T01:19:21Z
dc.date.available2017-07-24T01:19:21Z
dc.identifierhttps://mel.cgiar.org/dspace/limiteden_US
dc.identifierhttp://dx.doi.org/10.1109/JSTARS.2014.2360411en_US
dc.identifier.citationWeicheng Wu, Waleed M. Al-Shafie, Ahmad S. Mhaimeed, Feras M. Ziadat, Vinay Nangia, William Payne. (11/11/2014). Soil Salinity Mapping by Multiscale Remote Sensing in Mesopotamia, Iraq. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 7(11), pp. 4442 -4452.en_US
dc.identifier.urihttp://hdl.handle.net/20.500.11766/7313
dc.description.abstractSoil salinity has become one of the major problems affecting crop production and food security in Mesopotamia, Iraq. There is a pressing need to quantify and map the spatial extent and distribution of salinity in the country in order to provide relevant references for the central and local governments to plan sustainable land use and agricultural development. The aim of this study was to conduct such quantification and mapping in Mesopotamia using an integrated, multiscale modeling approach that relies on remote sensing. A multiyear, multiresolution, and multisensor dataset composed of mainly Landsat ETM+ and MODIS data of the period 2009-2012 was used. Results show that the local-scale salinity models developed from pilot sites with vegetated and nonvegetated areas can reliably predict salinity. Salinity maps produced by these models have a high accuracy of about 82.5-83.3% against the ground measurements. Regional salinity models developed using integrated samples from all pilot sites could predict soil salinity with an accuracy of 80% based on comparison to regional measurements along two transects. It is hence concluded that the multiscale models are reasonably reliable for assessment of soil salinity at local and regional scales. The methodology proposed in this paper can minimize problems induced by crop rotation, fallowing, and soil moisture content, and has clear advantages over other mapping approaches. Further testing is needed while extending the mapping approaches and models to other salinity-affected environments.en_US
dc.formatPDFen_US
dc.languageenen_US
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)en_US
dc.sourceIEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing;7,(2014) Pagination 4442 ,4452en_US
dc.subjectSoil Salinityen_US
dc.subjectMultiscale Remote Sensingen_US
dc.subjectMultiyear Maximaen_US
dc.subjectNew Processing Algorithmen_US
dc.subjectSalinity Modelsen_US
dc.titleSoil Salinity Mapping by Multiscale Remote Sensing in Mesopotamia, Iraqen_US
dc.typeJournal Articleen_US
cg.contributor.centerIraq Ministry of Agricultureen_US
cg.contributor.centerUniversity of Baghdad, College of Agricultureen_US
cg.contributor.centerFood and Agriculture Organization of the United Nations - FAOen_US
cg.contributor.centerThe International Center for Agriculture Research in the Dry Areas - ICARDAen_US
cg.contributor.crpCRP on Dryland Systems - DSen_US
cg.contributor.funderThe International Center for Agriculture Research in the Dry Areasen_US
cg.contributor.projectCommunication and Documentation Information Services (CODIS)en_US
cg.contributor.project-lead-instituteThe International Center for Agriculture Research in the Dry Areas (ICARDA)en_US
cg.date.embargo-end-date2114-11-11en_US
cg.coverage.regionWestern Asiaen_US
cg.coverage.countryIraqen_US
cg.contactw.wu@cgiar.orgen_US
dc.identifier.statusLimited accessen_US
cg.countryIraqen_US


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