Automatic generation of digital terrain models from Cartosat-1 stereo images

Abstract

This paper proposes a novel algorithm for automatic Digital Terrain Model (DTM) generation from high resolution CARTOSAT-1 satellite images generating accurate and reliable results. It consists of two major steps: Generation of Digital Surface Models (DSM) from CARTOSAT-1 stereo scenes and hierarchical image filtering for DTM generation. High resolution stereo satellite imagery is well suited for the creation of DSM. A system for automated and operational DSM and orthoimage generation based on CARTOSAT-1 imagery is presented, with emphasis on fully automated georeferencing. It processes level-1 stereo scenes using the rational polynomial coefficients (RPC) universal sensor model. A novel, automatic georeferencing method is used to derive a high quality RPC correction from lower resolution reference dataset, such as Landsat ETM+ Geocover and SRTM C Band DSM. Digital surface models (DSM) are derived from dense stereo matching and forward intersection and subsequent interpolation into a regular grid. In the second step which is dedicated to DSM filtering, the DSM pixels are classified into ground and non-ground using the algorithm motivated from the gray-scale image reconstruction to suppress unwanted elevated pixels. In this method, non-ground regions, i.e., 3D objects as well as outliers (very low or very high elevated regions) are hierarchically separated from the ground regions. The generated DTM is qualitatively and quantitatively evaluated. Profiles in the image as well as a comparison of the derived DTM to the original data and ground truth data are presented. The ground truth data consist of a high quality DTM produced from aerial images which is generated by the Institut Cartografic de Catalunya (ICC) in Barcelona, Spain. The evaluation result indicates that almost all non-ground objects regardless of their size are eliminated and the iterative approach gives good results in hilly as well as smooth residential areas.