Loading...

Ag DataHub

A data hub in Ethiopia that integrates the disparate systems/data available at the different government agencies that work in the agriculture domain at the federal and regional levels.

Project

About Us
News
Events

Important Links

Persistent URIs
Metadata Standards
Validation Survey

How to

Help Center
Developers
Privacy Policy

Contacts

info@datahub.moa.gov.et

Copyright ©2026 Ministry of Agriculture

powered byAcatech Technology

soc_60-100cm_Q0.05 - SoilGrids250m 2.0 - Soil organic carbon content - Ag Datahub

Datasets
SoilGrids250m 2.0 - Soil organic carbon content
soc_60-100cm_Q0.05

WMS

Map service (WMS)Part of SoilGrids250m 2.0 - Soil organic carbon content

soc_60-100cm_Q0.05

Connect to the serviceBack to the dataset

Preview

maps.isric.org

Asking the service for this layer…

Drawn live by the publisher's service, so it shows the data as it is today. Drag to move, use the buttons to zoom.

Legend of soc_60-100cm_Q0.05

Connect to this service

A map service draws this layer as images on request. Use the address and layer name below to add it to desktop GIS or to a web map.

Service address

https://maps.isric.org/mapserv?map=/map/soc.map

Layer name

soc_60-100cm_Q0.05

In QGIS, open Layer › Add Layer › Add WMS/WMTS Layer and create a new connection.
Paste the service address as the connection's URL and connect.
Pick soc_60-100cm_Q0.05 from the list and add it to your map.

See everything this service offers

Details

Format: WMS
Kind of access: Map service (WMS)
Protocol: OGC:WMS
Address: https://maps.isric.org/mapserv?map=/map/soc.map
Added to this catalogue: 6 Oct 2026
Last updated here: 6 Oct 2026
Resource identifier: 12aed79c-e99b-4451-9de6-4c043dc7c6a7

At a glance

Format: WMS
Access: Map service (WMS)
Kept at: maps.isric.org
Licence: Attribution 4.0 International (CC BY 4.0), https://creativecommons.org/licenses/by/4.0/

Part of the dataset

SoilGrids250m 2.0 - Soil organic carbon content

FDRE - Ministry of Agriculture (MoA)

Soil organic carbon content (fine earth fraction) in dg/kg at 6 standard depths. Predictions were derived using a digital soil mapping approach based on Quantile Random Forest, drawing on a global compilation of soil profile data and environmental layers. To visualize these layers please use www.soilgrids.org.

In this dataset 34