Predicting yields using biophysical crop simulations, machine learning and remote sensing in India
We tested the innovation and piloted it using ground truth yield data collected by means of crop cutting experiments in Odisha. Before starting to finalize the tool for adoption by insurance providers, the tool will be fine-tuned in the course of 2021.
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| Format: | Informe técnico |
| Language: | Inglés |
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2020
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| Online Access: | https://hdl.handle.net/10568/122969 |
| _version_ | 1855518610204655616 |
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| author | CGIAR Platform for Big Data in Agriculture |
| author_browse | CGIAR Platform for Big Data in Agriculture |
| author_facet | CGIAR Platform for Big Data in Agriculture |
| author_sort | CGIAR Platform for Big Data in Agriculture |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | We tested the innovation and piloted it using ground truth yield data collected by means of crop cutting experiments in Odisha. Before starting to finalize the tool for adoption by insurance providers, the tool will be fine-tuned in the course of 2021. |
| format | Informe técnico |
| id | CGSpace122969 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2020 |
| publishDateRange | 2020 |
| publishDateSort | 2020 |
| record_format | dspace |
| spelling | CGSpace1229692023-03-14T11:47:41Z Predicting yields using biophysical crop simulations, machine learning and remote sensing in India CGIAR Platform for Big Data in Agriculture yields remote sensing development innovation rural development data insurance learning adoption systems agrifood systems experiments machine learning cutting We tested the innovation and piloted it using ground truth yield data collected by means of crop cutting experiments in Odisha. Before starting to finalize the tool for adoption by insurance providers, the tool will be fine-tuned in the course of 2021. 2020-12-31 2022-10-06T14:15:19Z 2022-10-06T14:15:19Z Report https://hdl.handle.net/10568/122969 en Open Access application/pdf CGIAR Platform for Big Data in Agriculture. 2020. Predicting yields using biophysical crop simulations, machine learning and remote sensing in India. Reported in Platform for Big Data in Agriculture Annual Report 2020. Innovations. |
| spellingShingle | yields remote sensing development innovation rural development data insurance learning adoption systems agrifood systems experiments machine learning cutting CGIAR Platform for Big Data in Agriculture Predicting yields using biophysical crop simulations, machine learning and remote sensing in India |
| title | Predicting yields using biophysical crop simulations, machine learning and remote sensing in India |
| title_full | Predicting yields using biophysical crop simulations, machine learning and remote sensing in India |
| title_fullStr | Predicting yields using biophysical crop simulations, machine learning and remote sensing in India |
| title_full_unstemmed | Predicting yields using biophysical crop simulations, machine learning and remote sensing in India |
| title_short | Predicting yields using biophysical crop simulations, machine learning and remote sensing in India |
| title_sort | predicting yields using biophysical crop simulations machine learning and remote sensing in india |
| topic | yields remote sensing development innovation rural development data insurance learning adoption systems agrifood systems experiments machine learning cutting |
| url | https://hdl.handle.net/10568/122969 |
| work_keys_str_mv | AT cgiarplatformforbigdatainagriculture predictingyieldsusingbiophysicalcropsimulationsmachinelearningandremotesensinginindia |