In this paper we analyse a multiple sensor dataset corresponding to three-dimensional data coming from interferometric radar (InSAR) or laser ranging (LIDAR) measurements. We consider digital elevation models (DEMs) extracted from a single LIDAR scan plus multiple SAR scans of the same area, downtown Denver, CO, USA. Horizontal resolution for both datasets is 2.5 m, a value allowing good characterization of sparse tall buildings. Fusion of DEMs extracted from InSAR data originated during flights orthogonal to each other allows reduction of layover and shadowing. A novel strategy combining advantages of existing fusion techniques is proposed. Results from individual and combined techniques are presented, compared and discussed. The ability of characterizing buildings allows us to raise the fusion strategy scope from the pixel-level up to the feature level, once 3D features are extracted. Related results are presented and discussed. Finally, fusion of InSAR and LIDAR data is considered. LIDAR can reliably determine building footprints, thus relieving the problem of multiple bouncing radar pulses. Some results show that analysis of combined InSAR and LIDAR data on a small area can provide an improvement in DEMs extracted from a much larger area where only InSAR data are available.
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