Potential and limits of InSAR data for building reconstruction in built-up areas

Abstract

The automatic reconstruction of buildings for the generation of city models is of great interest for different tasks. 3D information can be directly obtained from both, laser (LIDAR) and radar (InSAR) measurements. The features of both sensors are compared.The data acquisition by SAR is described, with emphasis on the special properties of the interferometric SAR principle. A segmentation approach for building reconstruction is proposed. The results show that building reconstruction is possible from InSAR, but the achievable level of detail cannot compete with LIDAR. The main source of limitation is the inherent side-looking scene illumination of SAR, giving rise to disturbing phenomena interfering with often large parts of the scene. Geometric constraints for the location and size of such problem areas are derived. In order to identify areas of unreliable data in SAR images of a built-up area corresponding elevation data are analysed. The impact of the phenomena layover, shadow and dominant scattering at building locations is considered. For this task a hybrid elevation reference is required. The buildings and the surrounding ground are represented as CAD planes. Natural objects like trees and bushes remain in the raster representation.

Applications of 3D City Models: State of the Art Review

“…A typical 3D city model is derived from various acquisition techniques, for instance, photogrammetry and laser scanning [5][6][7][8], extrusion from 2D footprints [9,10], synthetic aperture radar [11][12][13][14][15], architectural models and drawings [16][17][18], handheld devices [19,20], procedural modelling [21][22][23][24][25][26], and volunteered geoinformation [27][28][29]. Seemingly, visualisation dominated the early uses of 3D city models.…”

Classifying the Built-Up Structure of Urban Blocks with Probabilistic Graphical Models and TerraSAR-X Spotlight Imagery

“…On SAR intensity images, bright areas frequently appear due to the inherent effects of corner reflection and layover, whereas dark areas are frequently caused by the shadowing effect [46]. The shape, size and orientation of bright and dark areas in SAR intensity images from urban areas strongly correspond to the buildings shape and orientation [47,48]. Therefore, as valuable indicators of the built-up structure from each urban block, bright and dark areas were extracted from the SAR intensity image of each block.…”

“…The use of images from both orbits has significantly increased the potential for extracting meaningful attributes from the blocks, as discussed in [49]. The minimum and maximum incidence angles of all four acquisitions range from 22 • -26 • , which has avoided that either the layover or shadowing effects become critical [48]. The only auxiliary data used in this work are the network of streets, rivers and railroads, as well as the official UST map from the city of Munich (Germany).…”

Using Landscape Characteristics to Predict Distribution of Temperate-Breeding Canada Geese

“…Over the past decade, the use of IFSAR data to derive two-dimensional land cover has matured considerably (Zebker et al, 1991;Madsen et al, 1993;Zebker et al, 1994;Wegmuller and Werner, 1995;Hagberg et al, 1995;Luckman et al, 2000;Weydahl et al, 2001;Corr, 2003;Stilla et al, 2003;Yan et al, 2006;Huang et al, 2007;Santoro et al, 2007). This source of data was used in this paper to determine its feasibility in the production of land cover maps.…”