Investigating the Applicability of Cartosat-1 DEMs and Topographic Maps to Localize Large-Area Urban Mass concentrations

Abstract

Building models are a valuable information source for urban studies and in particular for analyses of urban mass concentrations. Most commonly, LiDAR is used for their generation. The trade-off for the high geometric detail of these data is the low spatial coverage, comparably high costs and low actualization rates. Space-borne stereo data from Cartosat-1 is able to cover large areas on the one hand, but hold a lower geometric resolution on the other hand. In this paper we investigate to which extent the geometric shortcomings of Cartosat-1 can be overcome integrating building footprints from topographic maps for the derivation of large-area building models. Therefore, we describe the methodology to derive digital surface models from Cartosat-1 data and the derivation of building footprints from topographic maps at 1:25,000 (DTK-25). Both data is fused to generate building block models for four metropolitan regions in Germany with an area of ~16,000km². Building block models are further aggregated to 1 x 1 km grid cells and volume densities are computed. Volume densities are classified to various levels of urban mass concentrations (UMCs). Performance evaluation of the building block models reveals that building footprints are larger in the DTK-25 and building heights are lower with a mean absolute error of 3.21 m. Both factors influence the building volume which is linearly lower than the reference. However, this error does not affect the classification of UMC which can be classified with accuracies between 77-97 %.