Differentiation of Crop Types and Grassland by Multi-Scale Analysis of Seasonal Satellite Data

The implementation of productive and sustainable cultivation procedures is a major effort regarding the agricultural production in the European Community. However, political, economic and environmental factors impact the cultivation strategies directly and indirectly, and therewith strongly determine the condition and transformation of the cultivated and natural landscape. To assess the actual status, identify basic trends and mitigate major threats with respect to the agricultural production and its impact on the cultural and natural landscape, a frequent and area-wide monitoring of cropland and grassland is required. Satellite-based earth observation (EO) provides ideal capabilities for the area-wide and spatially detailed provision of up-to-date geo-information on the agricultural land use and the properties of the cultivated landscape. A specific benefit of EO is given by analysing multi-seasonal data acquisitions. Intra-annual time series facilitate the analysis of the phenological behaviour of the main crop and grassland types – key information with respect to the characterisation of the land use intensity and its impacts on the environment. The presented approach focuses on a seasonal analysis of multi-scale EO time series to classify main crop types and differentiate between cropland and grassland for given areas of interest on the basis of field parcels. The areas of interest are typically existing land use / land cover (LULC) data sets (e.g. national topographic data, CORINE Land Cover, etc.) that show a limited resolution in the semantic and/or spatial domain. Hence, the presented approach is primarily designed to improve the level of thematic/geometric detail for given LULC data sets