Analysis of Gable-Roofed Building Signature in Multiaspect InSAR Data

Thiele, Antje; Cadario, Erich; Schulz, Karsten; Soergel, Uwe

doi:10.1109/lgrs.2009.2023476

Cited by 26 publications

(12 citation statements)

References 12 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…It should also be noted that gable-roof buildings have different backscattering characteristics from the flat roof buildings (Bennett and Blacknell, 2003). The SAR image of gable-roof buildings is also characterized by layover area, corner reflector, roof signal and radar shadow (Thiele et al, 2010). Because the gable roof has a slope angle, the backscatter from the roof is mapped to a narrow area and become very strong.…”

Section: Building Features In Airborne Sar Imagementioning

confidence: 99%

Post-earthquake building damage assessment in Yushu using airborne SAR imagery

et al. 2011

View full text Add to dashboard Cite

The synthetic aperture radar (SAR) plays an important role in earthquake emergency response because of its all-time and all-weather imaging capabilities. On April 14, 2010, an MS7.1 earthquake occurred in Yushu county, Qinghai province of China, causing a lot of buildings collapsed. In this paper, the building damage in Yushu city due to the earthquake was assessed quantitatively using high-resolution X-band airborne SAR image. The features of the buildings with different damage levels (collapsed, partial collapsed, non-collapsed) in the SAR image were analyzed first. Based on these building features, we interpreted the individual building damage in Yushu city block by block and got the numbers of the collapsed, partial collapsed and non-collapsed buildings separately for each block, referring to pre-earthquake QuickBird image when necessary. Let the damage index of individual collapsed, partial collapsed, non-collapsed building be 1, 0.5, 0 respectively, the remote sensing damage index of each block was then calculated through remote sensing damage index equation. Finally, the preliminary quantitative relationship between the remote sensing damage index interpreted from the SAR image and that interpreted from the optical image was built up. It can be concluded that a desirable damage assessment result can be derived from high-resolution airborne SAR imagery.

show abstract

Section: Building Features In Airborne Sar Imagementioning

confidence: 99%

Post-earthquake building damage assessment in Yushu using airborne SAR imagery

et al. 2011

View full text Add to dashboard Cite

show abstract

“…8.1. This effect was discussed thoroughly for flat-roofed buildings in Thiele et al (2007a) and for gable-roofed buildings in Thiele et al (2009). Received signal of DSM points of same distance to the sensor (e.g., ground, building wall and roof) is integrated in the same image cell.…”

Section: Magnitude Signature Of Buildingsmentioning

confidence: 99%

Radar Remote Sensing of Urban Areas

Soergel¹

2010

Remote Sensing and Digital Image Processing

View full text Add to dashboard Cite

“…Behind the building, the ground is partly occluded by the building shadow, which appears as a dark region. Magnitude changes of the building signature due to illumination direction and building geometry are described in more detail for flat-roofed buildings in [1] and for gable-roofed buildings in [7], respectively.…”

Section: Magnitude and Phase Signature In Sar Datamentioning

confidence: 99%

Segmentation and fusion of building features based on InSAR and optical data

et al. 2009

Self Cite

View full text Add to dashboard Cite

The new generation of space borne SAR sensors provides geometric resolution of one meter, airborne systems even higher. In this high resolution data many features of urban objects become visible, which were beyond the scope of radar remote sensing only a few years ago. Focusing on elevated objects (e.g., urban area), layover, and occlusion issues inevitably arise because of the side-looking SAR sensor principle. In order to support interpretation, SAR data are often analyzed using additional information provided by maps or other remote sensing imagery. The focus of this paper is on building extraction in urban scenes by means of combined InSAR data and optical aerial imagery

show abstract

Analysis of Gable-Roofed Building Signature in Multiaspect InSAR Data

Cited by 26 publications

References 12 publications

Post-earthquake building damage assessment in Yushu using airborne SAR imagery

Post-earthquake building damage assessment in Yushu using airborne SAR imagery

Radar Remote Sensing of Urban Areas

Segmentation and fusion of building features based on InSAR and optical data

Contact Info

Product

Resources

About