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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91 to 100 of 112 Results
Feb 11, 2023
Biradar, Chandrashekhar, 2015, "Central Asia and NW China absolute change of the annual minimum temperature 2020s_A1b", https://hdl.handle.net/20.500.11766.1/FK2/OPNQUD, MELDATA, V5
Central Asia and North-West China (Xingjiang province) absolute change of annual minimum temperature in 2020 according to IPCC near-term climate change scenario A1b
Feb 11, 2023
Biradar, Chandrashekhar, 2015, "Central Asia and NW China absolute change of annual minimum temperature 2020s_A2", https://hdl.handle.net/20.500.11766.1/FK2/LRM1Z7, MELDATA, V4
Central Asia and North-West China (Xingjiang province) absolute change of annual minimum temperature in 2020 according to IPCC near-term climate change scenario A2
Feb 11, 2023
Biradar, Chandrashekhar, 2015, "Central Asia and NW China absolute change of annual mean precipitation 2020s_A1b", https://hdl.handle.net/20.500.11766.1/FK2/AHVZDB, MELDATA, V5
Central Asia and North-West China (Xingjiang province) absolute change of annual mean precipitation in 2020 according to IPCC near-term climate change scenario A1b
Feb 11, 2023
Biradar, Chandrashekhar, 2015, "Central Asia and NW China annual average of monthly minimum temperature 2020s_A1b", https://hdl.handle.net/20.500.11766.1/FK2/WDL6EV, MELDATA, V4
Central Asia and North-West China (Xingjiang province) annual average in monthly minimum temperature in 2020 according to IPCC near-term climate change scenario A1b
Feb 11, 2023
Biradar, Chandrashekhar, 2015, "Central Asia and NW China absolute change of the annual maximum temperature 2020s_A2", https://hdl.handle.net/20.500.11766.1/FK2/H4RWHJ, MELDATA, V4
Central Asia and North-West China (Xingjiang province) absolute change of annual maximum temperature in 2020 according to IPCC near-term climate change scenario A2
Feb 10, 2023
Biradar, Chandrashekhar, 2015, "Central Asia and NW China annual mean precipitation 2020s_A2", https://hdl.handle.net/20.500.11766.1/FK2/8HWJXZ, MELDATA, V7
Central Asia and North-West China (Xingjiang province) annual mean precipitation in 2020 according to IPCC near-term climate change scenario A2
Feb 10, 2023
Biradar, Chandrashekhar, 2015, "Central Asia and NW China agro-climatic zones 10_40_A1b", https://hdl.handle.net/20.500.11766.1/FK2/BL66QR, MELDATA, V2
Central Asia and North-West China (Xingjiang province) agroclimatic zones 2011-2040 based on the averaged output of 4 GCM models under Greenhouse Gas Emission Scenario 10_40_A1b
Feb 10, 2023
Biradar, Chandrashekhar, 2015, "Central Asia and NW China monthly potential evapotranspiration 10_40_A1b", https://hdl.handle.net/20.500.11766.1/FK2/YO2TU6, MELDATA, V3
Central Asia and North-West China (Xingjiang province) monthly potential evapo transpiration 2011-2040 based on the averaged output of 4 GCM models under Greenhouse Gas Emission Scenario 10_40_A1b
Feb 10, 2023
Kosimov, Sherzod, 2020, "Spatial data from Fergana valley", https://hdl.handle.net/20.500.11766.1/FK2/IQEHTS, MELDATA, V3
This dataset contains information about soil in specific locations in the Fergana Valley in Uzbekistan. It also includes related images of land cover and soil information of the area.
Sep 30, 2019
De Pauw, Eddy; Atassi, Layal; Tulaymat, Mohammad Fawaz; Omary, Jalal, 2019, "West Asia And Egypt. Relative Precipitation Change 2010-2040/Current Climate: Year", https://hdl.handle.net/20.500.11766.1/FK2/I3J3ZG, MELDATA, V1
West Asia and Egypt. Relative precipitation change 2010-2040/current climate: Year (based on the averaged output of 7 GCM models under Greenhouse Gas Emission Scenario A1b), it is baseline data to assist development agencies in planning for adaptation strategies to climate change...
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