Autor:
Xiong, Jun
Thenkabail, Prasad S.
Gumma, Murali K.
Teluguntla, P.
Poehnelt, J.
Congalton, Russell
Yadav, K.
Thau, D.
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 Af...
Enlace original:
https://cgspace.cgiar.org/handle/10568/81208
Xiong, Jun
,
Thenkabail, Prasad S.
,
Gumma, Murali K.
,
Teluguntla, P.
,
Poehnelt, J.
,
Congalton, Russell
,
Yadav, K.
,
Thau, D.
,
[Automated cropland mapping of continental Africa using Google Earth Engine cloud computing]
,
Automated cropland mapping of continental Africa using Google Earth Engine cloud computing
