Soil Organic Carbon Mapping Through Remote Sensing and In Situ Data with Random Forest by Using Google Earth Engine: A Case Study in Southern Africa

Soil Organic Carbon Mapping Through Remote Sensing and In Situ Data with Random Forest by Using Google Earth Engine: A Case Study in Southern Africa

This study, conducted within the SteamBioAfrica project, assessed the potential of Digital Soil Mapping (DSM) to estimate Soil Organic Carbon (SOC) across key regions of southern Africa: Otjozondjupa and Omusati (Namibia), Chobe (Botswana), and KwaZulu-Natal (South Africa). Random Forest (RF) models...

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Bibliographic Details
Main Authors: Javier Bravo-García, Juan Mariano Camarillo-Naranjo, Francisco José Blanco-Velázquez, María Anaya-Romero
Format: Article
Language:English
Published: MDPI AG 2025-07-01
Series:Land
Subjects:
digital soil mapping
organic carbon soil
remote sensing
Google Earth Engine
random forest
Online Access:https://www.mdpi.com/2073-445X/14/7/1436
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