Soil Organic Carbon Stock Estimates with Uncertainty across Latin America

This dataset provides 5 x 5 km gridded estimates of soil organic carbon (SOC) across Latin America that were derived from existing point soil characterization data and compiled environmental prediction factors for SOC. This dataset is representative for the period between 1980 to 2000s corresponding with the highest density of observations available in the WoSIS system and the covariates used as prediction factors for soil organic carbon across Latin America. SOC stocks (kg/m2) were estimated for the SOC and bulk density point measurements and a spatially explicit measure of the SOC estimation error was also calculated. A modeling ensemble, using a linear combination of five statistical methods (regression Kriging, random forest, kernel weighted nearest neighbors, partial least squared regression and support vector machines) was applied to the SOC stock data at (1) country-specific and (2) regional scales to develop gridded SOC estimates (kg/m2) for all of Latin America. Uncertainty estimates are provided for the two model predictions based on independent model residuals and their full conditional response to the SOC prediction factors.

Data and Resources

Additional Info

Field Value
Maintainer Earthdata Forum
Last Updated September 15, 2026, 04:01 (UTC)
Created April 1, 2025, 19:08 (UTC)
accessLevel public
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catalog_conformsTo https://project-open-data.cio.gov/v1.1/schema
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harvest_source_id b99e41c6-fe79-4c19-bbc3-9b6c8111bfac
harvest_source_title Science Discovery Engine
identifier 10.3334/ORNLDAAC/1615
license https://www.usa.gov/government-works
modified 2026-09-07T22:16:03Z
programCode {026:000}
publisher ORNL_DAAC
resource-type Dataset
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source_hash 78665805b9490653d59860e4863c65e2bd610508033dd80641578679dc572114
source_schema_version 1.1
spatial ["CARTESIAN", [{"WestBoundingCoordinate": -121.288, "NorthBoundingCoordinate": 35.5592, "EastBoundingCoordinate": -31.2372, "SouthBoundingCoordinate": -58.5761}]]
temporal 2018-06-14/2018-06-14
theme {"Earth Science"}