Quantitative Comparison of Segmentation Results from ADS40 Images in Swiss NFI

Abstract

Image segmentation is an important component in object based forest management with increasing high resolution remote sensing data such as ADS40 images. However, evaluation of segmentation algorithms has been largely subjective. To be able to evaluate image segmentation methods quantitatively and objectively, we applied a new error measurement which quantifies the performance of an image segmentation algorithm based on object shape and size as well. Experimental results show that the applied measurement is sensitive to over-segmentation and under-segmentation that can be served as a useful tool for further establishing an evaluation system.