Fusing stereo and multispectral data from WorldView-2 for urban modeling

Kurzfassung

Using the capability of WorldView-2 to acquire very high resolution (VHR) stereo imagery together with as much as eight spectral channels allows the worldwide monitoring of any built up areas, like cities in evolving states. In this paper we show the benefit of generating a high resolution digital surface model (DSM) from multi-view stereo data (PAN) and fusing it with pan sharpened multi-spectral data to arrive at very detailed information in city areas. The fused data allow accurate object detection and extraction and by this also automated object oriented classification and future change detection applications. The methods proposed in this paper exploit the full range of capacities provided by WorldView-2, which are the high agility to acquire a minimum of two but also more in-orbit-images with small stereo angles, the very high ground sampling distance (GSD) of about 0.5 m and also the full usage of the standard four multispectral channels blue, green, red and near infrared together with the additional provided channels special to WorldView-2: coastal blue, yellow, red-edge and a second near infrared channel. From the very high resolution stereo panchromatic imagery a so called height map is derived using the semi global matching (SGM) method developed at DLR. This height map fits exactly on one of the original pan sharpened images. This in turn is used for an advanced rule based fuzzy spectral classification. Using these classification results the height map is corrected and finally a terrain model and an improved normalized digital elevation model (nDEM) generated. Fusing the nDEM with the classified multispectral imagery allows the extraction of urban objects like like buildings or trees. If such datasets from different times are generated the possibility of an expert object based change detection (in quasi 3D space) and automatic surveillance will become possible.