The advent of big data, which incorporates geo- informatics, remote sensing, and the large volumes of data being generated by technological advances in genomics, will revolutionize the way we work in the future. The use of this information to increase research efficiencies and decision-making, from the farm level to the policy level, is beginning to take place. Using big data in an effective manner will be a key element in addressing the challenges facing research programs and dry areas as a whole. We intend to capitalize on big data to the benefit of our breeding programs, thereby ensuring a continuous supply of improved varieties to smallholder farmers. We will also build digital platforms to generate maps of crop productivity and water consumption in near real time, which can be used for water accounting and agro-ecosystem assessment. In order to make full use of big data and ICT, we will partner with other CGIAR centers, CGIAR Research Programs (CRPs), ARIs, and the public and private sectors. ICARDA’s geo-informatics research focuses on knowledge-based prioritization of agricultural landscapes for improved interventions, implementation, and impacts through the use of multi-sensor, multi-scale observations of agro-ecosystem productivity, resource use efficiency, land potential, and associated drivers to assist addressing issues related to food and nutritional security, natural resource management, and resilience. We will develop advanced analytics (machine learning, artificial intelligence) for research, development, and outreach in collaboration with research programs, partners, collaborators, and citizen science. We will support the work in the SRPs by working on quantification of yield gaps and land potential for better targeting developmental interventions towards bridging the yield gaps in dry areas.
ICARDA Strategic Plan 2017 - 2026: https://dx.doi.org/20.500.11766/8237
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11 to 20 of 112 Results
Jan 14, 2026
Biradar, Chandrashekhar; Loew, Fabian; Fliemann, Elisabeth, 2016, "Cotton Yield Map (Pixel Based), 2010", https://hdl.handle.net/20.500.11766.1/FK2/1PJUNL, MELDATA, V8
Yield map for cotton in Fergana valley, Uzbekistan in 2010. The map is part of a series on crop distribution from 2004 to 2015.
Jan 14, 2026
Biradar, Chandrashekhar; Loew, Fabian; Fliemann, Elisabeth, 2016, "Yield Map Winter Wheat, 2007", https://hdl.handle.net/20.500.11766.1/FK2/IV0EBI, MELDATA, V11
Yield map for winter wheat in Fergana valley, Uzbekistan in 2007. The map is part of a series on crop distribution from 2004 to 2015.
Jan 14, 2026
Biradar, Chandrashekhar; Loew, Fabian; Fliemann, Elisabeth, 2016, "Land Cover Map of Fergana 2013", https://hdl.handle.net/20.500.11766.1/TYRWGS, MELDATA, V9
Land use map shows the spatial distribution of dominant crop types (at the per-parcel level) in the major part of the Fergana Valley in 2012. The map is part of a series on crop distribution from 2010 to 2014. Major crop types like cotton or rice were classified as separately, wh...
Jan 14, 2026
Biradar, Chandrashekhar; Loew, Fabian; Fliemann, Elisabeth, 2016, "Major Land Use (key crops), 2014", https://hdl.handle.net/20.500.11766.1/WMCR1B, MELDATA, V9
Land use map shows the spatial distribution of dominant crop types (at the per-parcel level) in the major part of the Fergana Valley in 2014. The map is part of a series on crop distribution from 2010 to 2014. Major crop types like cotton or rice were classified as separately, wh...
Jan 14, 2026
Atassi, Layal; Al-Shamaa, Khaled; Biradar, Chandrashekhar, 2018, "Rahba Potential Hot-spots Of Red Palm Weevil (RPW) Risk Based On Trap-data 2016", https://hdl.handle.net/20.500.11766.1/FK2/CS0SOE, MELDATA, V12
The layer was part of enhancing date palm integrated pest management and agricultural extension and technology transfer systems in Abu Dhabi project, the layer was generated from survey information on date palm in Abu Dhabi obtained from Abu Dhabi Farmers Services Center. The tra...
Jan 14, 2026
De Pauw, Eddy; Atassi, Layal, 2019, "Annual Rainfall Likely To Be Exceeded In 1 Year Out Of 2", https://hdl.handle.net/20.500.11766.1/FK2/85RZD9, MELDATA, V11
Annual rainfall likely to be exceeded in 1 year out of 2, in millimeters, at 30 arcsecond resolution, was prepared for the IFAD-ICARDA Project "Poverty Assessment in Sudan". Map prepared as part of three reports that detail the results of a poverty assessment and mapping project...
Jan 14, 2026
De Pauw, Eddy; Atassi, Layal, 2019, "Annual Rainfall Likely To Be Exceeded In 9 Years Out Of 10", https://hdl.handle.net/20.500.11766.1/FK2/GLYCLI, MELDATA, V13
Annual rainfall likely to be exceeded in 9 years out of 10, in millimeters, at 30 arcsecond resolution, was prepared for the IFAD-ICARDA Project "Poverty Assessment in Sudan". Map prepared as part of three reports that detail the results of a poverty assessment and mapping projec...
Jan 14, 2026
Jani, Sara; Bonaiuti, Enrico; Wery, Jacques, 2019, "ICARDA ISI Journal Articles 2018 dataset", https://hdl.handle.net/20.500.11766.1/C4OABW, MELDATA, V8
The data contains the list of journal articles published in ISI Journals by the International Center for Agricultural Research in the Dry Areas (ICARDA) Scientists during the year 2018 with the quartiles analysis to study the journal article relevance to each research topic based...
Jan 14, 2026
Biradar, Chandrashekhar; Atassi, Layal; Oweis, Theib; Haddad, Mira, 2017, "Agricultural water productivity for irrigated areas in 2002", https://hdl.handle.net/20.500.11766.1/EWB8JR, MELDATA, V7
The dataset contains one of the layers produced for “Supporting Coordination and Cooperation in Water Management in the Euphrates and Tigris Area CPET” project. The project aims to assess the status of water use in agriculture in the Euphrates-Tigress basin, determine and map the...
Jan 14, 2026
Biradar, Chandrashekhar; Loew, Fabian; Fliemann, Elisabeth, 2016, "Cotton Yield Map (Pixel Based), 2012", https://hdl.handle.net/20.500.11766.1/FK2/NZ7ZGH, MELDATA, V8
Yield map for cotton in Fergana valley, Uzbekistan in 2012. The map is part of a series on crop distribution from 2004 to 2015.
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