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Matching Persistent Scatterers to Buildings : Volume Xxxix-b7, Issue 1 (31/07/2012)

By Schunert, A.

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Book Id: WPLBN0004016909
Format Type: PDF Article :
File Size: Pages 6
Reproduction Date: 2015

Title: Matching Persistent Scatterers to Buildings : Volume Xxxix-b7, Issue 1 (31/07/2012)  
Author: Schunert, A.
Volume: Vol. XXXIX-B7, Issue 1
Language: English
Subject: Science, Isprs, International
Collections: Periodicals: Journal and Magazine Collection, Copernicus Publications
Publication Date:
Publisher: Copernicus Publications, Göttingen, Germany
Member Page: Copernicus Publications


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Schack, L., Soergel, U., & Schunert, A. (2012). Matching Persistent Scatterers to Buildings : Volume Xxxix-b7, Issue 1 (31/07/2012). Retrieved from

Description: Leibniz Universität Hannover, Institute of Photogrammetry and GeoInformation, Nienburger Strasse 1, 30167 Hannover, Germany. Persistent Scatterer Interferometry (PSI) is by now a mature technique for the estimation of surface deformation in urban areas. In contrast to the classical interferometry a stack of interferograms is used to minimize the influence of atmospheric disturbances and to select a set of temporarily stable radar targets, the so called Persistent Scatterers (PS). As a result the deformation time series and the height for all identified PS are obtained with high accuracy. The achievable PS density depends thereby on the characteristics of the scene at hand and on the spatial resolution of the used SAR data. This means especially that the location of PS cannot be chosen by the operator and consequently deformation processes of interest may be spatially undersampled and not retrievable from the data. In case of the newly available high resolution SAR data, offering a ground resolution around one metre, the sampling is potentially dense enough to enable a monitoring of single buildings. However, the number of PS to be found on a single building highly depends on its orientation to the viewing direction of the sensor, its facade and roof structure, and also the surrounding buildings. It is thus of major importance to assess the PS density for the buildings in a scene for real world monitoring scenarios. Besides that it is interesting from a scientific point of view to investigate the factors influencing the PS density. In this work, we fuse building outlines (i.e. 2D GIS data) with a geocoded PS point cloud, which consists mainly in estimating and removing a shift between both datasets. After alignment of both datasets, the PS are assigned to buildings, which is in turn used to determine the PS density per building. The resulting map is a helpful tool to investigate the factors influencing PS density at buildings.



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