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dc.contributorKumaraCharyulu, Deevien_US
dc.contributorIrshad Ahmed, Mohammeden_US
dc.contributorVarshney, Rajeeven_US
dc.contributorGaur, Pooranen_US
dc.contributorWhitbread, Anthonyen_US
dc.creatorGumma, Murali Krishnaen_US
dc.date2016-04-11en_US
dc.date.accessioned2017-02-09T23:58:09Z
dc.date.available2017-02-09T23:58:09Z
dc.identifierhttp://oar.icrisat.org/id/eprint/9424en_US
dc.identifierhttp://dx.doi.org/10.1080/01431161.2016.1165889en_US
dc.identifierhttps://mel.cgiar.org/reporting/download/hash/q9BOaf4Jen_US
dc.identifier.citationMurali Krishna Gumma, Deevi KumaraCharyulu, Mohammed Irshad Ahmed, Rajeev Varshney, Pooran Gaur, Anthony Whitbread. (11/4/2016). Satellite imagery and household survey for tracking chickpea adoption in Andhra Pradesh, India. International Journal of Remote Sensing, 37(8), pp. 1955-1972.en_US
dc.identifier.urihttp://hdl.handle.net/20.500.11766/5658
dc.description.abstractThe objective of this study was to map the temporal changes in chickpea cropped area over the last decade in Andhra Pradesh using remote-sensing imagery. Moderate Resolution Imaging Spectroradiometer (MODIS) data composited for every 16 days were used to map the spatial distribution of seasonal crop extent in Andhra Pradesh. MODIS derived 16 day normalized difference vegetation index (NDVI) and maximum value composite (MVC) with seasonal ground survey information for the years 2005– 2006 and 2012–2013 were used. A subset of ground survey information was also used to assess the pixel-based accuracies of the MODIS-derived major cropland extent. Chickpea-growing areas were identified and mapped based on their characteristic growing periods during the post-rainy season. Significant growth in the chickpea-growing areas was observed in the four districts of Andhra Pradesh between 2001 and 2012. The area cropped to chickpea almost tripled from 0.22 million ha during 2000–2001 to 0.6 million ha by 2012–2013. Furthermore, survey data were also used to assess the accuracy of the MODIS estimates of chickpeagrowing areas. When compared with ground survey, the 10 landuse and land-cover classes derived from the MODIS temporal imagery resulted in overall accuracies of 86% of actual. The accuracy of areas identified as cropped to chickpea was 94%. To complement this remote-sensing study, a state-level representative primary household survey was conducted to elicit information on the socio-economic characteristics of chickpea-growing farmers, the extent of adoption of improved cultivars, costs and returns from chickpea cultivation, competitiveness of chickpea with other post-rainy crops, etc. during 2012–13. The findings revealed that nearly 98% of the chickpea cropped area is now under improved cultivars, with an average increase in yield of 37% over yields achieved with unimproved varieties. The average annual per capita incomes have increased to US$ 1.89 day−1 with this silent chickpea revolution across the rain-fed areas of Andhra Pradesh.en_US
dc.formatPDFen_US
dc.languageenen_US
dc.publisherTaylor & Francisen_US
dc.sourceInternational Journal of Remote Sensing;37,(2016) Pagination 1955,1972en_US
dc.subjectandhra pradeshen_US
dc.subjectsatellite imageryen_US
dc.subjecthousehold analysisen_US
dc.subjectcultivar technologyen_US
dc.subjectchickpea adoptionen_US
dc.titleSatellite imagery and household survey for tracking chickpea adoption in Andhra Pradesh, Indiaen_US
dc.typeJournal Articleen_US
cg.creator.ID0000-0003-4840-7670en_US
cg.creator.ID-typeORCIDen_US
cg.subject.agrovocagricultureen_US
cg.subject.agrovoclegumesen_US
cg.subject.agrovocgisen_US
cg.subject.agrovocremote sensingen_US
cg.contributor.centerInternational Crops Research Institute for the Semi-Arid Tropics - ICRISATen_US
cg.contributor.crpCRP on Dryland Cereals - DCen_US
cg.contributor.crpCRP on Dryland Systems - DSen_US
cg.contributor.funderNot Applicableen_US
cg.contributor.project-lead-instituteInternational Crops Research Institute for the Semi-Arid Tropics - ICRISATen_US
cg.date.embargo-end-date2017-02-28en_US
cg.coverage.regionSouthern Asiaen_US
cg.coverage.countryINen_US
cg.contactM.Gumma@cgiar.orgen_US
dc.identifier.statusLimited accessen_US


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