Combined Use of Multi-seasonal High and Medium Resolution Satellite Imagery for Parcel-related Updating of Crop- and Grassland Distribution.

Abstract

A key factor in the implementation of productive and sustainable cultivation procedures is the frequent and area-wide monitoring of cropland and grassland. In particular, attention is focused on assessing the actual status, identifying basic trends and mitigating major threats with respect to landuse intensity and its changes in agricultural and semi-natural areas. Here, multi-seasonal analyses based on satellite Earth observation (EO) data can provide area-wide, spatially detailed and up-to-date geo-information on the distribution and intensity of land use in agricultural and grassland areas. This study introduces the combined use of multi-seasonal high (HR) and medium resolution (MR) satellite imagery for both a land parcel-based determination of crop types as well as a cropland and grassland differentiation, respectively. First, HR IRS-P6 LISS-3 imagery is used to delineate the field parcels in potential agricultural and grassland areas. Next, a stack of seasonality indices is generated based on 5 image acquisitions (i.e., two LISS scenes and three MR IRS-P6 AWiFS scenes). Finally, a C5.0 tree classifier is applied to identify main crop types and grassland based on the input imagery and the derived seasonality indices. The classifier is trained using sample points provided by the European Land Use/Cover Area Frame Survey (LUCAS). Experimental results for a test area in Germany assess the effectiveness of the proposed approach and demonstrate that a multi-scale and multi-temporal analysis of satellite data can provide spatially detailed and thematically accurate geo-information on crop types and the cropland-grassland distribution, respectively.