Automated cropland mapping of continental Africa using Google Earth Engine cloud computing
The automation of agricultural mapping using satellite-derived remotely sensed data remains a challenge in Africa because of the heterogeneous and fragmental landscape, complex crop cycles, and limited access to local knowledge. Currently, consistent, continent-wide routine cropland mapping of Afric...
| Autores principales: | , , , , , , , |
|---|---|
| Formato: | Journal Article |
| Lenguaje: | Inglés |
| Publicado: |
Elsevier
2017
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| Materias: | |
| Acceso en línea: | https://hdl.handle.net/10568/81208 |
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