Somalia Soil Organic Carbon

Global Soil Organic Carbon Map v1.5 is the first global soil organic carbon map ever produced through a consultative and participatory process involving member countries, which makes this map totally new and unique. In fact, the map was prepared by member countries, under the guidance of the Intergovernmental Technical Panel on Soils and the Global Soil Partnership Secretariat. Countries agreed on the methodology to produce the map and were trained on modern tools and methodologies to develop national maps. The Global Soil Partnership then gathered all national maps to produce the final product, ensuring a thorough harmonization process. The dataset comes along with a technical report presenting methodologies and process of compiling the Global Soil organic Carbon Map. The link to download the report is available in the on-line resources. **Data revision:** 2019-06-01 **Supplemental Information:** No data value : -3 Unit : t/ha Scale Factor : 1.0 Map code : GSOCMAP1-5-0 **Contact points:** Resource Contact: [Yusuf Yigini](mailto:GSP-Secretariat@fao.org) Metadata Contact: [CBL Global Soil Partnership](mailto:GSP-Secretariat@fao.org) **Data lineage:** Information on data quality at https://openknowledge.fao.org/server/api/core/bitstreams/c3ccec0d-fe75-49b7-9a4c-ee0a8777fed9/content **Resource constraints:** This work is made available under the Creative Commons Attribution 4.0 International licence (CC-BY-4.0) **Online resources:** Download the data from Google Cloud Storage Download - GSOC-Map Technical Report Global Soil Partnership GSOCmap Contributors

Soil organic carbon content (measured by either wet oxidation or dry combustion at 900 C) in g/kg (fine earth) at 6 standard depths predicted using two sets of Africa soil profiles data. For details see published paper here below (Hengl T., G.B.M. Heuvelink, B. Kempen, J.G.B. Leenaars, M.G. Walsh, K.D. Shepherd, A. Sila, R.A. MacMillan, J. Mendes de Jesus, L.T. Desta, J.E. Tondoh, 2015. Mapping Soil Properties of Africa at 250 m Resolution: Random Forests Significantly Improve Current Predictions. PLoS ONE 10(6)

Soil organic carbon stock in tons per ha for 6 standard depth intervals predicted using the global compilation of soil ground observations. Accuracy assessement of the maps is availble in Hengl et at. (2017) DOI: 10.1371/journal.pone.0169748. Data provided as GeoTIFFs with internal compression (co='COMPRESS=DEFLATE'). Measurement units: t / ha.

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Soil organic carbon stock in tons per ha for ICCP depth intervals predicted using the global compilation of soil ground observations. Accuracy assessement of the maps is availble in Hengl et at. (2017) DOI: 10.1371/journal.pone.0169748. Data provided as GeoTIFFs with internal compression (co='COMPRESS=DEFLATE'). Measurement units: t / ha.

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. This map is the result of resampling the mean SoilGrids 250 m predictions (Poggio et al. 2021) for each 5000 m cell.