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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51 to 60 of 112 Results
Jun 20, 2024
Biradar, Chandrashekhar; Loew, Fabian; Fliemann, Elisabeth, 2016, "Yield Map Cotton, 2008", https://hdl.handle.net/20.500.11766.1/FK2/NYTW37, MELDATA, V4
Yield map for cotton in Fergana valley, Uzbekistan in 2008. The map is part of a series on crop distribution from 2004 to 2015.
Jun 20, 2024
Biradar, Chandrashekhar; Loew, Fabian; Fliemann, Elisabeth, 2016, "Yield Map Winter Wheat, 2010", https://hdl.handle.net/20.500.11766.1/FK2/NRPXR0, MELDATA, V4
Yield map for winter wheat in Fergana valley, Uzbekistan in 2010. The map is part of a series on crop distribution from 2004 to 2015.
Nov 7, 2023
Biradar, Chandrashekhar; Loew, Fabian; Fliemann, Elisabeth, 2016, "Major Land Use (key crops), 2010", https://hdl.handle.net/20.500.11766.1/FEMSKO, MELDATA, V6
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 2010. 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...
Nov 7, 2023
Biradar, Chandrashekhar, 2015, "Vegetation dynamics in central Asia: Normalized Differential Vegetation Index 2000-2014", https://hdl.handle.net/20.500.11766.1/FK2/UQ39C8, MELDATA, V5
Normalized Differential Vegetation Index (NDVI) from derived MODIS time series data from 2000-2014
Nov 7, 2023
Biradar, Chandrashekhar; Loew, Fabian; Fliemann, Elisabeth, 2016, "Major Land Use (key crops), 2014", https://hdl.handle.net/20.500.11766.1/WMCR1B, MELDATA, V5
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...
Nov 7, 2023
Biradar, Chandrashekhar, 2015, "Vegetation dynamics in central Asia: Enhanced Vegetation Index 2000-2014", https://hdl.handle.net/20.500.11766.1/FK2/F4DCR8, MELDATA, V4
Enhanced Vegetation Index (EVI) derived from modis time-series satellite data at 8 days interval from 2000-2014
Nov 7, 2023
Biradar, Chandrashekhar, 2015, "Ground truth data from the Ferghana valley for remote sensing analysis and validation", https://hdl.handle.net/20.500.11766.1/FK2/NSXDEA, MELDATA, V4
Ground truth data from the Ferghana vallet for land use and land cover mapping, crop productivity and land degradation assessment
Nov 7, 2023
Biradar, Chandrashekhar; Loew, Fabian; Fliemann, Elisabeth, 2016, "Major Land Use (key crops), 2012", https://hdl.handle.net/20.500.11766.1/E1TIUQ, MELDATA, V4
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...
Nov 7, 2023
Biradar, Chandrashekhar, 2015, "Vegetation dynamics in central Asia: Land Surface Water Index 2000-2014", https://hdl.handle.net/20.500.11766.1/FK2/PDAP3M, MELDATA, V5
Land Surface Water Index (LSWI) derived from MODIS time-series satellite data at 8 days interval from 2000-2014
Nov 7, 2023
Biradar, Chandrashekhar; Loew, Fabian; Fliemann, Elisabeth, 2016, "Major Land Use (key crops), 2011", https://hdl.handle.net/20.500.11766.1/IGXRWU, MELDATA, V5
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 2011. 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...
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