Soil Composite Mapping Processor (SCMaP) product suite as EO soil monitoring data base - potential and challenges

Kurzfassung

Due to the joint effort of environmental institutes, there are a number of large-scale regional soil information systems such as the European Soil Database (Panagos, 2006), the Africa Soil Information Service (Hengl et al. 2015), the Soil Map of China (Shi et al., 2004) but also global maps such as the Soil Map of the World (FAO/UNESCO) and the Harmonized World Soil Database (FAO/IIASA/ISRIC/ISS-CAS/JRC, 2009). Most of the recent maps are generated using digital soil mapping approaches that combine medium resolution EO-based information about vegetation presence and dynamics, terrain metrics and derived land cover / land use information as covariates with soil profile information. With the ability to access the archives of high-resolution multispectral data such as Landsat 4-8 and Sentinel-2, new opportunities using high resolution EO data arise that allow direct information retrieval from exposed soils. Thus, EO-based soil monitoring systems can be improved due to higher spatial detail of top soil formation, higher thematic detail (continuous soil parameter) as well as the ability to investigate the potential of such systems for soil monitoring. High spatial and temporal soil information is crucial to analyse soil developments and for monitoring long term changes to assess soil degradation. This information is essential to achieve sustainable food security, health and high productivity of soils. The Soil Composite Mapping Processor (SCMaP) is a fully automated approach to make use of per-pixel based bare-soil compositing (Rogge et al. 2018). It results in a Landsat-based (L4-8) product suite consisting of multispectral soil reflectance composites, albedo, distribution of exposed soils, statistical information related to soil use and intensity as well as information about the used number of pixels for evaluating the reliability of the generated data sets. The products will be presented for several European regions and different time periods. Major technical studies such as the threshold analysis across Europe to differentiate between exposed soils and covered soils will be presented. This is important since different climatic conditions, land use and agricultural practices can have an influence on the extraction of the bare soil composites. Thus, several European countries have been processed to test the transferability of the method to different climatic conditions and agricultural practices. Validation with German statistical data and with CORINE layer shows the high accuracy of the derivation of exposed soils from multispectral data archives. The presentation also reveals the potential of a combined analysis of the various existing soil profile archives with the SCMaP exposed soil composites. In future, SCMaP will be adapted to Sentinel-2 and the harmonized L8/S2 data sets to continue the provision of SCMaP data products. Further, the combination of top-soil profile data bases with SCMaP exposed soil reflectance composites to continuous and high-resolution information about soil parameter such as soil units, SOC and texture and mineralogy will be explored. References 1. Panagos Panos. The European soil database (2006) GEO: connexion, 5 (7), pp. 32-33. 2. Hengl T, Heuvelink GBM, Kempen B, Leenaars JGB, Walsh MG, Shepherd KD, et al. (2015) Mapping Soil Properties of Africa at 250 m Resolution: Random Forests Significantly Improve Current Predictions. PLoS ONE 10(6): e0125814. doi:10.1371/journal.pone.0125814 3. Shi X. Z. et al., 2009, Soil and Tillage Research, 105(2):322-327 4. Rogge et al. 2018. Building an exposed soil composite processor (SCMaP) for mapping spatial and temporal characteristics of soils with Landsat imagery (1984-2014), RSE, 205, 1-17. 5. FAO/IIASA/ISRIC/ISS-CAS/JRC, 2009. Harmonized World Soil Database (version 1.1). FAO, Rome, Italy and IIASA, Laxenburg, Austria.