Refinement of Digital Surface Models Through Constrained Connectivity Partitioning of Optical Imagery

Abstract

ABSTRACT:One of the tasks of ISFEREA action at the Joint Research Center (JRC) in Ispra, Italy, is to assess changes in land cover after natural disasters using satellite imagery. To describe the pre-event and post-event scenarios the available heterogeneous data are analysed and eventually fused in order to achieve the most accurate and reliable information. With respect to automatic 3D information extraction, the availability of accurate and detailed Digital Surface Models (DSMs) is a crucial for automatic building detection and subsequent damage estimation. This paper proposes a methodology for the geometric refinement of an arbitrary DSM using high or very high resolution satellite scenes. The main idea is to fuse the DSM and the scene through an advanced hierarchical image partitioning. The method is applied on a dataset over Catalonia, Spain, provided by ISPRS WGI/4 through the project "Benchmarking and quality analysis of DEM generated from high and very high resolution optical stereo satellite data". During this experiment a WorldView-1 quasi-nadir scene was used for the enhancement of the DSM generated by a Cartosat-1 stereopair. The original and final DSM are compared to the Lidar DSM on the same area for quality analysis. After the description of the methodology, the first results are reported and commented.

Lossless data compression of grid-based digital elevation models: A png image format evaluation

“…DEMs represent a continuous surface and depending on the application they can be very dense, with grid point distances ranging from one metre to less than one hundred metres, thus incorporating large amounts of data (Poli and Soille, 2011). It should be pointed out that this work relates to rectangular, regularly sampled elevation datasets.…”