The first aim of this paper is to show how the joint use of Digital Surface Models (DSMs) coming from different sources may improve the understanding of an urban environment. More specifically, we consider laser and radar three-dimensional data over the same urban area and show that they can be profitably combined to improve building extraction. We exploit the better vertical and horizontal accuracy of the laser DSM, assumed to be available only on a small area, to ease the deformation of Interferometric Synthetic Aperture Radar (InSAR) DSM with built structures. To achieve this, we propose a method based on subsequent steps of geometrical correction, and mainly on a simple “stretching step” that uses laser data as a reference to adjust InSAR-derived building footprints. We show quantitative results obtained from two different urban areas, using different laser and radar data sets, to assess advantages and drawbacks of the proposed method.

Improving Building Footprints in InSAR Data by Comparison with a Lidar DSM

GAMBA, PAOLO ETTORE;DELL'ACQUA, FABIO;LISINI, GIANNI;
2006

Abstract

The first aim of this paper is to show how the joint use of Digital Surface Models (DSMs) coming from different sources may improve the understanding of an urban environment. More specifically, we consider laser and radar three-dimensional data over the same urban area and show that they can be profitably combined to improve building extraction. We exploit the better vertical and horizontal accuracy of the laser DSM, assumed to be available only on a small area, to ease the deformation of Interferometric Synthetic Aperture Radar (InSAR) DSM with built structures. To achieve this, we propose a method based on subsequent steps of geometrical correction, and mainly on a simple “stretching step” that uses laser data as a reference to adjust InSAR-derived building footprints. We show quantitative results obtained from two different urban areas, using different laser and radar data sets, to assess advantages and drawbacks of the proposed method.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11571/104844
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