Automated cropland mapping of continental Africa using Google Earth Engine cloud computing-Reference-Cited by-同舟云学术

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Automated cropland mapping of continental Africa using Google Earth Engine cloud computing

Published:2017-04 Issue: Volume:126 Page:225-244
ISSN:0924-2716
Container-title:ISPRS Journal of Photogrammetry and Remote Sensing
language:en
Short-container-title:ISPRS Journal of Photogrammetry and Remote Sensing

Author:

Xiong Jun,Thenkabail Prasad S.,Gumma Murali K.,Teluguntla Pardhasaradhi,Poehnelt Justin,Congalton Russell G.,Yadav Kamini,Thau David

Funder

NASA MEaSUREs

USGS

United States Geological Survey

USGS Climate and Land Use Change Mission Area

Africa Research in Sustainable Intensification for the Next Generation (Africa RISING) program

Publisher

Elsevier BV

Subject

Computers in Earth Sciences,Computer Science Applications,Engineering (miscellaneous),Atomic and Molecular Physics, and Optics

Reference101 articles.

1. GlobCover: ESA service for global land cover from MERIS;Arino,2007

2. Differences between cropland and rangeland MODIS phenology (start-of-season) in Mali;Bégué;Int. J. Appl. Earth Obser. Geoinform.,2014

3. A global map of rainfed cropland areas (GMRCA) at the end of last millennium using remote sensing;Biradar;Int. J. Appl. Earth Obser. Geoinform.,2009

4. Scarcity amidst abundance? Reassessing the potential for cropland expansion in Africa;Chamberlin;Food Policy,2014

5. Global land cover mapping at 30m resolution: a POK-based operational approach;Chen;ISPRS J. Photogramm. Remote Sens.,2015

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