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55 p, 1.9 MB Spatio-temporal downscaling of gridded crop model yield estimates based on machine learning / Folberth, Christian (International Institute for Applied Systems Analysis (Àustria)) ; Baklanov, Artem (International Institute for Applied Systems Analysis (Àustria)) ; Balkovic, Juraj (Comenius University in Bratislava. Department of Soil Science) ; Skalský, Rastislav (National Agricultural and Food Centre, Soil Science and Conservation Research Institute) ; Khabarov, Nikolay (International Institute for Applied Systems Analysis (Àustria)) ; Obersteiner, Michael (International Institute for Applied Systems Analysis (Àustria))
Global gridded crop models (GGCMs) are essential tools for estimating agricultural crop yields and externalities at large scales, typically at coarse spatial resolutions. Higher resolution estimates are required for robust agricultural assessments at regional and local scales, where the applicability of GGCMs is often limited by low data availability and high computational demand. [...]
2019 - 10.1016/j.agrformet.2018.09.021
Agricultural and forest meteorology, Vol. 264 (January 2019) , p. 1-15  
Detailed record - Creative Commons

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