Automatic Generation of High Quality DSM Based on IRS-P5 Cartosat-1 Stereo Data
Pablo d’Angelo, Andreas Uttenthaler, Sebastian Carl, Frithjof Barner, Peter H. Reinartz · elib (German Aerospace Center) · 2010
IRS-P5 Cartosat-1 high resolution stereo satellite imagery is well suited for the creation of digital surface models (DSM). A system for highly automated and operational DSM and orthoimage generation based on IRS-P5 Cartosat-1 imagery is presented, with an emphasis on automated processing and product quality. The proposed system processes IRS-P5 level-1 stereo scenes using the rational polynomial coefficients (RPC) universal sensor model. The described method uses an RPC correction based on DSM alignment instead of using reference images with a lower lateral accuracy, this results in improved geolocation of the DSMs and orthoimages. Following RPC correction, highly detailed DSMs with 5 m grid spacing are derived using Semiglobal Matching. The proposed method is part of an operational Cartosat-1 processor for the generation of a high resolution DSM. Evaluation of 18 scenes against independent ground truth measurements indicates a mean lateral error (CE90) of 6.7 meters and a mean vertical accuracy (LE90) of 5.1 meters.