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dc.contributorSingh, Rajkumaren_US
dc.contributorBehera, Mukundaen_US
dc.contributorSarker, Ashutoshen_US
dc.contributorAgrawal, Shiv Kumaren_US
dc.contributorXiao, Xiangmingen_US
dc.contributorZhang, Gelien_US
dc.contributorEl-Shamaa, Khaleden_US
dc.contributorPujar, Girishen_US
dc.contributorAtassi, Layalen_US
dc.contributorTomar, Sat Kumaren_US
dc.contributorAcharya, Prasenjiten_US
dc.contributorSahoo, Rabien_US
dc.contributorSwain, Nigamanandaen_US
dc.contributorOmary, Jalalen_US
dc.contributorPrajapati, Praveenen_US
dc.contributorNath, Rajiben_US
dc.contributorChandna, Parveshen_US
dc.contributorGumma, Murali Krishnaen_US
dc.contributorJain, Abhineeten_US
dc.creatorBiradar, Chandrashekharen_US
dc.identifier.citationChandrashekhar Biradar, Rajkumar Singh, Mukunda Behera, Ashutosh Sarker, Shiv Kumar Agrawal, Xiangming Xiao, Geli Zhang, Khaled El-Shamaa, Girish Pujar, Layal Atassi, Sat Kumar Tomar, Prasenjit Acharya, Rabi Sahoo, Nigamananda Swain, Jalal Omary, Praveen Prajapati, Rajib Nath, Parvesh Chandna, Murali Krishna Gumma, Abhineet Jain. (7/5/2018). Spatial big data analytics for sustainable intensification of pulse crops in South Asia.en_US
dc.description.abstractSustainable intensification has become a foremost goal of agricultural research and development in the recent years. The mono-crop based production systems in South Asia retains nearly 30 percent of cultivated area left as fallows, while demand for the nutritional food grains continues to rise. Several initiatives are underway towards bridging the gaps and achieving sustainable food as well as nutritional security. One of the opportunities lies in the potential use of the crop-fallows for growing pulses. The lentil, grasspea and chickpea are most preferred food legume crops for fallow intensification. However often lack of the adequate and updated information on the crop follow areas, its dynamics, soil moisture, suitability range, etc. lead to poor intervention on the ground level. The recent advances in harnessing the power of big-data analytics, artificial intelligence and machine learning with access to near real-time remote sensing, in-situ observations including drones, soil moisture, water harvesting provided a unique capability for quantifying suitable matrix for intensification of pulses such as lentil, grasspea and chickpea in the rice-fallows. The dynamics of the rice fallows has been mapped using multi-source satellite data (MODIS, Landsat, Sentinel, Worldview, SMOS, AMSR-E and UAVs/drones) and in-situ observations. The hotspots (priority areas) were delineated with respect to multi-year maps (2000-2016) of fallow dynamics such a start and end dates, length of the fallows, biophysical parameters for specific pulse crops and varieties. The high-resolution farm typology was built along with soil moisture regimes and suitable area for rain water harvesting for providing supplemental irrigation during dry season. Resultant big data analytics envisage empowering decision makers, researchers, extension systems and farmers by providing a holistic perspective to fine tune decisions and actions from on-ground implementation to resource management, sustainable intensification and values chains.en_US
dc.titleSpatial big data analytics for sustainable intensification of pulse crops in South Asiaen_US
dc.typeConference Paperen_US
cg.creator.idBiradar, Chandrashekhar: 0000-0002-9532-9452en_US
cg.creator.idSingh, Rajkumar: 0000-0002-3576-8971en_US
cg.creator.idSarker, Ashutosh: 0000-0002-9074-4876en_US
cg.creator.idAgrawal, Shiv Kumar: 0000-0001-8407-3562en_US
cg.creator.idEl-Shamaa, Khaled: 0000-0002-7668-3798en_US
cg.creator.idAtassi, Layal: 0000-0002-7271-7591en_US
cg.creator.idSwain, Nigamananda: 0000-0001-9593-4911en_US
cg.subject.agrovocbig dataen_US
cg.contributor.centerInternational Center for Agricultural Research in the Dry Areas - ICARDAen_US
cg.contributor.centerInternational Crops Research Institute for the Semi-Arid Tropics - ICRISATen_US
cg.contributor.centerBidhan Chandra Krishi Viswavidyalaya University - BCKVen_US
cg.contributor.centerIndian Institute of Technology Kharagpur - IITKen_US
cg.contributor.centerIndian Council of Agricultural Research, Indian Agricultural Research Institute - ICAR-IARIen_US
cg.contributor.centerInternational Rice Research Institute - IRRIen_US
cg.contributor.centerUniversity of Oklahoma, Center for Spatial Analysis - OU - CSAen_US
cg.contributor.centerIndian Space Research Organisation, National Remote Sensing Centre - ISRO-NRSCen_US
cg.contributor.centerVidyasagar University, department of Geography & Environment Managementen_US
cg.contributor.centerSatyukt Analyticsen_US
cg.contributor.centerIndrones Solutions Pvt. Ltd.en_US
cg.contributor.centerDigital Globesen_US
cg.contributor.crpCGIAR Research Program on Dryland Systems - DSen_US
cg.contributor.crpCGIAR Research Program on Grain Legumes - GLen_US
cg.contributor.crpBig Data in Agriculture - BDAen_US
cg.contributor.funderIndian Council of Agricultural Research - ICARen_US
cg.contributor.projectIndia Collaborative Program: Restricted funding for breeding for resistance to abiotic stresses in pulses & for 2017/2018 - 2017/2020 - 2020/2021en_US
cg.contributor.project-lead-instituteInternational Center for Agricultural Research in the Dry Areas - ICARDAen_US
dc.identifier.statusTimeless limited accessen_US

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