POINT-TO-SURFACE MATCHING FOR DEM CORRECTION USING ICESAT DATA

Abstract. Vendor-provided rational polynomial coefficients (RPCs) are commonly used to generate digital elevation models (DEMs) from high-resolution satellite images. This results in a level of accuracy that can be improved using ground control points (GCPs). It is well known that due to the inherent bias of sensor orientation the generated DEM is distorted. In the traditional way of working, the bias is corrected by integrating GCPs into the standard processing chain. This involves additional effort, since the provision of GCPs and the measurement of their image coordinates are required.

In this paper, we examine whether and how the data recorded by NASA's ICESat (Ice, Cloud, and Land Elevation Satellite) mission can be used as GCPs without measuring image coordinates. The starting point are DEMs that are generated by image matching from KOMPSAT-3 satellite images with given RPCs. We developed a point-to-surface matching method that matches the ICESat points to the DEM in order to correct the DEM and improve its precision. For the experimental investigations a KOMPSAT 3 image pair is used that covers an area of 20 by 16 km² in the Yangsan city regions. The generated DEM has a height accuracy of about 9 m. The point-to-surface algorithm with 505 ICESat points led to an improvement of the DEM height accuracy to about 2 m.