Investigations on the nature of Persistent Scatterers based on simulation methods

Auer, Stefan; Gernhardt, Stefan; Bamler, Richard

doi:10.1109/jurse.2011.5764719

Cited by 11 publications

(7 citation statements)

References 5 publications

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“…Windows of type 2c produce a sharp point like response, which we assume is due to a trihedral reflection mechanism having its center in the lower left or right corner depending on the façade orientation (here: the left one). The dominance of such scattering mechanisms in urban areas and its importance for the PS technique has already been reported elsewhere (Auer et al, 2010(Auer et al, , 2011. The PS pattern looks very regular.…”

Section: Automatic Selection Of Groupssupporting

confidence: 58%

Grouping of Persistent Scatterers in high-resolution SAR data of urban scenes

Schunert

Soergel

2012

ISPRS Journal of Photogrammetry and Remote Sensing

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Section: Automatic Selection Of Groupssupporting

confidence: 58%

Grouping of Persistent Scatterers in high-resolution SAR data of urban scenes

Schunert

Soergel

2012

ISPRS Journal of Photogrammetry and Remote Sensing

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“…The most important factor is the facade and roof structure. It has been shown, that PS most likely originate from three-or fivefold bounce reflections (Auer et al, 2011). Thus, a high PS density can be expected for facades accommodating for instance Figure 4.…”

Section: The Highest Values (20-25 Ps/1000mmentioning

confidence: 92%

Matching of Persistent Scatterers to buildings

Schunert

Schack

Soergel

2012

2012 IEEE International Geoscience and Remote Sensing Symposium

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ABSTRACT: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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“…But there are also applications which require a more detailed façade reconstruction. To analyse Persistent Scatterers for radar image interpretation façade details are of special interest (Auer et al 2011), for energetic assessment of buildings with thermal cameras the area of the façade without the window regions is needed (Iwaszczuk et al 2011). Also the visualisation of a building can be made more realistic by modelling geometric structures like windows and doors.…”

Section: Motivationmentioning

confidence: 99%

Window Detection in Sparse Point Clouds Using Indoor Points

Tuttas

Stilla

2013

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:This paper describes an approach for detecting windows from multi-aspect airborne laser scanning point clouds which were recorded in a forward looking view. Since the resolution of the point cloud is much lower than from terrestrial laser scanning, new methods have to be developed to detect and, in a further step, reconstruct façade structures. The façade planes are detected using point normals and a regiongrowing algorithm. The approach for window detection uses the points which are lying behind the detected façades planes (indoor points). Regularities in the appearance of these points are of special interest to enable the detection of windows which are only weakly represented in the point cloud. Therefore it is checked with a Fourier Transform if a repetitive structure can be extracted. Otherwise peaks in the density of the indoor points are used to detect the windows. The approach is tested on data from four overflights over the area around the TU München. The tests show that windows having a repetitive structure can be detected well for larger façade parts which provide enough samples but the approach shows deficits for small façade parts and in the case of disturbing intrusions.

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Investigations on the nature of Persistent Scatterers based on simulation methods

Cited by 11 publications

References 5 publications

Grouping of Persistent Scatterers in high-resolution SAR data of urban scenes

Grouping of Persistent Scatterers in high-resolution SAR data of urban scenes

Matching of Persistent Scatterers to buildings

Window Detection in Sparse Point Clouds Using Indoor Points

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