Accuracies of support vector machine and random forest in rice mapping with Sentinel-1A, Landsat-8 and Sentinel-2A datasets

Geocarto International - Tập 35 Số 10 - Trang 1088-1108 - 2020
Lamin R. Mansaray1,2,3, Fumin Wang1,2, Jingfeng Huang1,2, Lingbo Yang1,2, Adam Sheka Kanu4
1Institute of Applied Remote Sensing and Information Technology, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou, China;
2Key Laboratory of Agricultural Remote Sensing and Information Systems, Zhejiang Province, Zhejiang University, Hangzhou, China;
3Laboratory of Agro-meteorology and Geo-informatics, Magbosi Land, Water and Environment Research Centre (MLWERC), Sierra Leone Agricultural Research Institute (SLARI), Freetown, Sierra Leone;
4Laboratory of Agronomy, Rokupr Agricultural Research Centre (RARC), Sierra Leone Agricultural Research Institute (SLARI), Freetown, Sierra Leone

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Geocarto International

Tập 35 Số 10

1088-1108

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