Delineation of Cocoa Agroforests Using Multiseason Sentinel-1 SAR Images: A Low Grey Level Range Reduces Uncertainties in GLCM Texture-Based Mapping

Delineation of Cocoa Agroforests Using Multiseason Sentinel-1 SAR Images: A Low Grey Level Range Reduces Uncertainties in GLCM Texture-Based Mapping

Delineating the cropping area of cocoa agroforests is a major challenge in quantifying the contribution of land use expansion to tropical deforestation. Discriminating cocoa agroforests from tropical transition forests using multispectral optical images is difficult due to the similarity of the spec...

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Bibliographic Details
Main Authors:	Frederick N. Numbisi, Frieke M. B. Van Coillie, Robert De Wulf
Format:	Article
Language:	English
Published:	MDPI AG 2019-04-01
Series:	ISPRS International Journal of Geo-Information
Subjects:	mapping cocoa agroforests Congo Basin rainforest Sentinel-1 SAR GLCM textures grey level quantization random forest algorithm machine learning classification uncertainty
Online Access:	https://www.mdpi.com/2220-9964/8/4/179

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