Analysis and comparison of different high-resolution data sets for urban applications

The use of remote sensing for urban applications requires high resolution data with respect to geometry and spectral information in order to deal with the complexity and the variability of urban scenes. Unfortunately, the available sensors provide data of either high geometrical or high spectral information. Optical satellite sensors improved a lot with respect to the available ground sampling distance (gsd). Most prominent examples are IKONOS, QuickBird and OrbView. But this improvement was made at the expense of the spectral information by focussing on the visible and near-infrared using four spectral channels. Optical airborne sensors always had high geometric resolution. Nowadays hyperspectral sensors are available delivering almost continuous spectral information from visible to shortwave infrared with a resolution of a few meters depending on flying height and velocity. Such data offer the possibility to discern different surface materials showing differences in their spectral response not visible in multispectral data, but may not have the same high geometric resolution. This paper compares the use of different high resolution data for urban remote sensing applications focussing on hyperspectral data and its fusion with laser scanning data.