LGRB-BW BOPA: Near-surface organic soil carbon content on arable land in Baden-Württemberg
Description
This dataset shows percentages of soil surface organic soil carbon content (Corg) modelled using Sentinel-2 time series of 2018, 2019, 2020 and 2021 and a Random Forest (RF) approach. The Corg forecasts refer exclusively to agricultural land in Baden-Württemberg. The RF modeling was carried out using the statistical software R. The reference data required for modelling consist of information derived from classical soil mapping (Landesamt für Geology, Raw Materials and Mining, LGRB), permanent observation areas (Landesamt für Umwelt Baden-Württemberg, LUBW), and current field campaigns carried out by both the LGRB and the Federal Institute for Geosciences and Raw Materials (BGR). A total of 380 laboratory measurements from Corg were available for training, all of which were generated by combustion analysis. Applied to an independent sample of approximately 30 % of the total sample size, a certainness measure (R²) of 0.18.
The spatial ground resolution of the grid data is 10 m per pixel.
This dataset was carried out within the framework of the project BopaBW, funded by DLR and led by the State Office of Geology, Raw Materials and Mining (LGRB) (funding code: 50EW1703A) in cooperation with the Federal Institute for Geosciences and Raw Materials (BGR) and the Geoforschungszentrum Potsdam (GfZ).
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https://services.lgrb-bw.de/ms/lgrb_bopa?REQUEST=GetCapabilities&SERVICE=WMS&VERSION=1.3.0 |
Tags
- fernerkundung
- bodeneigenschaftenkarte
- maschinelles-lernen