A new multivariate agricultural drought composite index based on random forest algorithm and remote sensing data developed for Sahelian agrosystems
This manuscript aims to develop a new multivariate composite index for monitoring agricultural drought. To achieve this, the AVHRR, VIIRS, CHIRPS data series over a period of 40 years, rainfall and crop yield data as references were used. Variables include parameters for vegetative stress (SVCI, PV,...
| Main Authors: | , , , , , , |
|---|---|
| Format: | Journal Article |
| Language: | Inglés |
| Published: |
Informa UK Limited
2023
|
| Subjects: | |
| Online Access: | https://hdl.handle.net/10568/139779 |
Similar Items: A new multivariate agricultural drought composite index based on random forest algorithm and remote sensing data developed for Sahelian agrosystems
- Drought vulnerability of central Sahel agrosystems: a modelling-approach based on magnitudes of changes and machine learning techniques
- Evaluating the impact of improved crop varieties in the Sahelian farming systems of Niger
- Modelling agricultural drought: a review of latest advances in big data technologies
- Godwill Address by Executive Director of CORAF
- How to navigate climate security and resilience in the Sahel: From fragility to stability
- Sahel Workshop Official Opening by Dr Nteranya Sanginga, DG IITA