Digital Surface Models from High Resolution Satellite Imagery

Abstract

Automated processes in commercial-off-the-shelf (COTS) systems are increasingly prevalent as new technology, and new knowledge is fused to enhance accessibility to spatial information. Automated terrain extraction is becoming a standard capability implemented into photogrammetric software. This paper focuses on digital surface model (DSM) generation from high-resolution satellite imagery (HRSI) using three COTS systems, SOCET SET ® , Z/I Imaging, and Imagine ® OrthoBASE, which each have their own image matching strategy. By generating DSMs of a test field diverse in landcover, we assess the performance of the COTS terrain extraction methodologies. In checkpoints favorable to image matching, accuracy to a few meters in height can be achieved from COTS generated DSMs, however the isolated points are unlikely to be representative of the entire scene. Therefore, we look to alternative sources of control, such as the newly available DLR- and NASA-generated SRTM DEMs. A comparison to X-band SRTM DEMs demonstrated that height RMSE values range from 4 to 9 metres, though most of this uncertainty is attributed to the SRTM data.