The potential of the Soil Composite Mapping Processor (SCMaP) for analyzing temporal changes of exposed soils in Germany between 1984-2014

Abstract

High spatial and temporal resolution soil information is crucial for monitoring long term changes to avoid soil degradation and ultimately to achieve sustainable food security. The Soil Composite Mapping Processor (SCMaP) is a new fully automated approach designed to make use of per-pixel bare-soil compositing. The SCMaP allows generating cloud-free multispectral soil reflectance composites that can support large scale top soil analysis. Three primary products are generated that include the distribution of exposed soils, a statistical information related to soil use and intensity and the generation of exposed soil reflectance image composites. The output each are time series (1984-2014) of composites over five year periods based on multispectral Landsat imagery. The aim of this work is 1) to expand the technology by improving the threshold definition required for the composite generation, 2) to show the resulting multitemporal products of the different time periods that have the potential to detect exposed soil changes in Germany and 3) to analyse the coverage and transformation of exposed soils in Germany to other land cover types. Plausibility of the results is shown and a first validation is presented using statistical data from regional agricultural surveys of the german statistical bureau (Destatis). Results of statistical analyses of the composite images show that there was an increase of areas predominantly used for agricultural purposes before and after 1989, which coincides with the reunification of Germany. After 1995, a decrease of these agricultural areas can be observed. It can be shown, that the results are not affected by the use of different Landsat sensors and emphasise the potential for retrospective analyses of the development of soils using this type of data product.