CART and IDC – based classification of irrigated agricultural fields using multi-source satellite data

cg.contactrmadugundu@ksu.edu.saen_US
cg.contributor.centerInternational Center for Agricultural Research in the Dry Areas - ICARDAen_US
cg.contributor.centerKing Saud University, College of Food and Agriculture Sciences - KSU - CFASen_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.countrySAen_US
cg.coverage.regionWestern Asiaen_US
cg.creator.idBiradar, Chandrashekhar: 0000-0002-9532-9452en_US
cg.date.embargo-end-date2116-07-31en_US
cg.identifier.doihttps://dx.doi.org/10.1080/10106049.2016.1232312en_US
cg.isijournalISI Journalen_US
cg.issn1010-6049en_US
cg.issue1en_US
cg.journalGeocarto Internationalen_US
cg.volume33en_US
dc.contributorAl-Gaadi, Khalid A.en_US
dc.contributorMadugundu, Rangaswamyen_US
dc.contributorTola, ElKamil H. M.en_US
dc.contributorZeyadaa, Ahmed M.en_US
dc.contributorMarey, Samyen_US
dc.contributorBiradar, Chandrashekharen_US
dc.creatorPatil, Virupakshagowda. C.en_US
dc.date.accessioned2017-04-10T22:31:34Z
dc.date.available2017-04-10T22:31:34Z
dc.description.abstractTo understand water productivity of crops cultivated in the Eastern Province of Saudi Arabia, this study was conducted to generate a reliable crop type map using a multi-temporal satellite data (ASTER, Landsat-8 and MODIS) and crop phenology. Classification And Regression Tree (CART) and ISO-DATA Cluster (IDC) classification techniques were utilized for the identification of crops. The Ideal Crop Spectral Curves were generated and utilized for the formulation of CART decision rules. For IDC, the stacked images of the phenology-integrated Normalized Difference Vegetation Index were utilized for the classification. The overall accuracy of the classified maps of CART was 76, 77 and 81% for ASTER, MODIS and Landsat-8, respectively. For IDC, the accuracy was determined at 67, 63 and 60% for ASTER, MODIS and Landsat-8, respectively. The developed decision rules can be efficiently used for mapping of crop types for the same agro-climatic region of the study area.en_US
dc.formatPDFen_US
dc.identifierhttps://mel.cgiar.org/dspace/limiteden_US
dc.identifierhttps://www.tandfonline.com/doi/abs/10.1080/10106049.2016.1232312?journalCode=tgei20en_US
dc.identifier.citationVirupakshagowda. C. Patil, Khalid A. Al-Gaadi, Rangaswamy Madugundu, ElKamil H. M. Tola, Ahmed M. Zeyadaa, Samy Marey, Chandrashekhar Biradar. (1/1/2018). CART and IDC – based classification of irrigated agricultural fields using multi-source satellite data. Geocarto International, 33 (1), pp. 70-88.en_US
dc.identifier.statusLimited accessen_US
dc.identifier.urihttps://hdl.handle.net/20.500.11766/6694
dc.languageenen_US
dc.publisherTaylor & Francis: STM, Behavioural Science and Public Health Titlesen_US
dc.sourceGeocarto International;33,(2016) Pagination 70-88en_US
dc.subjectcrop phenologyen_US
dc.subjectvegetation indicesen_US
dc.subjectdecision treeen_US
dc.subjectspectral separabilityen_US
dc.titleCART and IDC – based classification of irrigated agricultural fields using multi-source satellite dataen_US
dc.typeJournal Articleen_US
dcterms.available2016-09-18en_US
dcterms.extent70-88en_US
dcterms.issued2018-01-01en_US
mel.impact-factor1.759en_US

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