A critical synthesis of remote sensing and machine learning approaches for climate hazard impact on crop yield
This review critically assesses the application of machine learning (ML) algorithms and remote sensing (RS) products in detecting and predicting climate hazards, as well as their impacts on crop yields. Using the PRISMA approach, it examines 177 studies on climate hazards and 197 on RS–ML applicatio...
| Main Authors: | , , , |
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| Format: | Journal Article |
| Language: | Inglés |
| Published: |
IOP Publishing
2025
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10568/177349 |
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