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ENHANCING THE AUTOMATIC VERIFICATION OF CROPLAND IN HIGH-RESOLUTION SATELLITE IMAGERY

Segmentation is one of the first steps in the field of image analyzing and image understanding. It is the basis for the interpretation of images, or it supports other techniques which is the motivation for the in this paper introduced segmentation algorithm. In this paper, a segmentation algorithm and its application to enhance an approach for the automatic verification of tilled cropland objects in a GIS. For this application, cropland objects in a GIS that may contain more than one field should be segmented into individual management units. The algorithm starts with a Watershed segmentation that results in a strong over-segmentation of the image. A region adjacency graph is generated, and neighbouring segments are merged based on similarity of grey levels, noise levels, and the significance of the boundary between the segments. After segmentation, the verification algorithm can be applied separately to the individual segments, and finally, these verification results have to be combined, taking into consideration the specifications of the GIS. Several examples show how the segmentation process can help to improve the verification of the cropland objects in the GIS from IKONOS images covering a test area in Germany, but also the limitations of the segmentation algorithm. * Corresponding author.