Updating LiDAR DSM using high resolution stereo-based DSM from Worldview-2

Abstract

In recent years, the acquisition and processing techniques of high resolution Digital Surface Models (DSM) have been rapidly improved. Airborne LiDAR production as a well-known and high quality DSM is still unbeatable in elevation accuracy and highly produced dense point clouds. In this paper, the objective is to update an old but high quality DSM produced by LiDAR data using a DSM generated from high resolution stereo satellite images. A classification-base algorithm is proposed to extract building changes between DSMs in two epochs. For image classification procedure, the DSM and Worldview-2 orthorectified images have been used as input data for a fuzzy-based classification method. Then, extracted buildings are classified into unchanged, destroyed, new, and changed classes. In this study a dataset related to Munich city, has been utilized to test the experimental investigation. The implemented qualitative and quantitative assessments demonstrate high quality as well as high feasibility of the proposed approach.