A High-Resolution Cropland Map for the West African Sahel Based on High-Density Training Data, Google Earth Engine, and Locally Optimized Machine Learning

A High-Resolution Cropland Map for the West African Sahel Based on High-Density Training Data, Google Earth Engine, and Locally Optimized Machine Learning

The West African Sahel Cropland map (WASC30) is a new 30-m cropland extent product for the nominal year of 2015. We used the computing resources provided by Google Earth Engine (GEE) to fit and apply Random Forest models for cropland detection in each of 189 grid cells (composed of 100 km<sup>...

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Bibliographic Details
Main Authors: Kaboro Samasse, Niall P. Hanan, Julius Y. Anchang, Yacouba Diallo
Format: Article
Language:English
Published: MDPI AG 2020-05-01
Series:Remote Sensing
Subjects:
agricultural land area
Sahel
West Africa
machine learning
Earth Engine
Online Access:https://www.mdpi.com/2072-4292/12/9/1436

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