Record Details

Delineation of Cocoa Agroforests Using Multi-Season Sentinel-1 SAR Images versus RapidEye multi-spectral image

World Agroforestry - Research Data Repository Dataverse OAI Archive

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Title Delineation of Cocoa Agroforests Using Multi-Season Sentinel-1 SAR Images versus RapidEye multi-spectral image
 
Identifier https://doi.org/10.34725/DVN/2OXNYM
 
Creator Numbisi, Frederick N.
Van Coillie, Frieke M.B.
De Wulf, Robert
 
Publisher World Agroforestry - Research Data Repository
 
Description The data is based on field inventory from 2015 to 2017 to map cocoa agroforests and other vegetation and non-vegetation land cover. The dataset consists of geospatial data (shapefiles) of the land cover and land use in the study landscape in Bokito - within the forest-savannah transition zone of Centre Cameroon.
The main aim of the study was to discriminate cocoa agroforest from transition forest; we compare the performance of texture-based classification of SAR (Synthetic Aperture Radar) images of Sentinel-1 with the result of "business as usual" multi-spectral optical image classification using a RapidEye image mosaic for the study landscape.
 
Subject Agricultural Sciences
Earth and Environmental Sciences
Engineering
Mapping
Perennials
Agroforestry
Sentinel-1 SAR
RapidEye Multi-spectral Image
GLCM Textures
Random Forest Algorithm
 
Contributor Nkeumoe, Frederick