Logo Lanfrica
  • Home
  • Atlas
  • Insights
  • Docs
  • Sign in

© 2026 Lanfrica. All rights reserved. All copyrights of the resources shown on the Lanfrica website belong to the original copyright holders, unless explicitly stated otherwise.

Digital Soil Mapping of Soil Organic Carbon in Namibia Using Google Earth Engine

Domain:

geospatialagriculture

Record type:

dataset
Creator:
YurMarÁdáEri
Publisher:
Cop
Host:
The Namibian Soil Profile Database contains 4960 entries, all samples with geographic coordinates. Each soil property presents a different number of observations, which decreases with depth. To perform the Digital Soil Map of Soil Organic Carbon (SOC) up to 30 cm, 1298 sample points were used. The covariates used in the model were composed from land cover, geology, terrain characteristics extracted from the digital elevation model and remote sensing data. Most of the covariates carry 30 m of spatial resolution. The Random Forest model implemented in Google Earth Engine (GEE) was applied with an external validation split of 80/20 %. As the second validation layer, samples from the Namibian tier of the Soils4Africa project were applied. The use of GEE facilitated the generation of a SOC distribution map for Namibia at a spatial resolution of 30 × 30 m. The highest amounts of SOC are stored in the central region of Namibia, with SOC values ranging from 0.1 to 1.9 %. The map is suitable for national and regional decision-making, offering a baseline for determining SOC stocks, monitoring changes in SOC, assessing the effects of bush encroachment/thickening and bush control, and for agriculture implications. Mapping of soil properties in other depths are scheduled for the near future.

Visit

doi.org

Similar

NamSoil v1.0 – R and Google Earth Engine (GEE) code for digital soil mapping of Namibia at 90 m resolutionSoil Organic Carbon Mapping Through Remote Sensing and In Situ Data with Random Forest by Using Google Earth Engine: A Case Study in Southern AfricaDigital Soil Mapping of Soil Organic Carbon in Smallholder Robusta Coffee Landscapes of South–Central UgandaExtrapolation of Digital Soil Mapping Approaches for Soil Organic Carbon Stock Predictions in an Afromontane EnvironmentLeveraging the Google Earth Engine for Drought Assessment Using Global Soil Moisture DataMapping soil organic carbon stocks in Tunisian topsoils

NamSoil v1.0 – R and Google Earth Engine (GEE) code for digital soil mapping of Namibia at 90 m resolution

Overview This repository contains the complete set of R and Google Earth Engine (GEE) scripts used

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 Mapp

Digital Soil Mapping of Soil Organic Carbon in Smallholder Robusta Coffee Landscapes of South–Central Uganda

Reliable spatial information on soil organic carbon (SOC) is important for soil-fertility management

Extrapolation of Digital Soil Mapping Approaches for Soil Organic Carbon Stock Predictions in an Afromontane Environment

Soil scientists can aid in an essential part of ecological conservation and rehabilitation by quanti

Leveraging the Google Earth Engine for Drought Assessment Using Global Soil Moisture Data

Soil moisture is considered to be a key variable to assess crop and drought conditions. However, rea

Mapping soil organic carbon stocks in Tunisian topsoils

International audience Better knowledge of the amount and spatial distribution of soi