After almost 3 years of data preparation, testing, optimization, we have finished the v1 of the 30 m resolution global
#soilcarbon density, soil carbon content, pH, texture fractions, bulk density and soil types (USDA subgroups). Soil carbon and soil pH are mapped as dynamic soil variables for 5-year intervals; soil texture fractions, bulk density and soil types as static vars. The preprint of the paper is at:
doi.org/10.5194/essd-2025-33…
Maps are available under CC-BY license
#OpenData as COGs from:
github.com/openlandmap/soild… (almost 6TB of data).
Our results show that
#landdegradation & intensive urbanization leads to losses in SOC; in some places these losses are significant. Although the uncertainty of the predictions is still relatively limited, we believe that investing in processing
#Landsat archive and investing in harmonizing soil laboratory data was worth the effort.
But this is just a start! We plan to update predictions and build a community of users and developers (compatible with the Open Soil Spectral Library
@soilspec and similar initiatives) around this initiative. If you spot an issue or artifacts please report using Github link. If you are curator of the soil laboratory data and soil observations, please share your data with us, so we can make even more accurate
#worldsoildata for everyone.
PS: If you are at
#LPS25 please find us for a demo of the predictions and data use tutorial.