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

Jin, Dingjian; Wang, Xiaoqing; Dou, Aixia; Dong, Yanfang

doi:10.1007/s11589-011-0808-0

Cited by 16 publications

(6 citation statements)

References 25 publications

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“…Jin et al [120] describe a comparison of post-event high spatial resolution X-band airborne SAR data with pre-event optical imagery based on manual interpretation. This approach was successfully applied at the Magnitude 7.1 Yushu County Earthquake, China, which happened in April 2010.…”

Section: Post-event Methods For Sar Data Based Damage Assessmentmentioning

confidence: 99%

Rapid Damage Assessment by Means of Multi-Temporal SAR — A Comprehensive Review and Outlook to Sentinel-1

2014

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Fast crisis response after natural disasters, such as earthquakes and tropical storms, is necessary to support, for instance, rescue, humanitarian, and reconstruction operations in the crisis area. Therefore, rapid damage mapping after a disaster is crucial, i.e., to detect the affected area, including grade and type of damage. Thereby, satellite remote sensing plays a key role due to its fast response, wide field of view, and low cost. With the increasing availability of remote sensing data, numerous methods have been developed for damage assessment. This article gives a comprehensive review of these techniques focusing on multi-temporal SAR procedures for rapid damage assessment: interferometric coherence and intensity correlation. The review is divided into six parts: First, methods based on coherence; second, the ones using intensity correlation; and third, techniques using both methodologies combined to increase the accuracy of the damage assessment are reviewed. Next, studies using additional data (e.g., GIS and optical imagery) to support the damage assessment and increase its accuracy are reported. Moreover, selected studies on post-event SAR damage assessment techniques and examples of other applications of the interferometric coherence are presented. Then, the preconditions for a successful worldwide application of multi-temporal SAR methods for damage assessment and the limitations of current SAR satellite missions are reported. Finally, an outlook to the Sentinel-1 SAR mission shows possible solutions of these limitations, enabling a worldwide applicability of the presented damage assessment methods.

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Section: Post-event Methods For Sar Data Based Damage Assessmentmentioning

confidence: 99%

Rapid Damage Assessment by Means of Multi-Temporal SAR — A Comprehensive Review and Outlook to Sentinel-1

2014

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“…The 2010 Yushu Earthquake is another large earthquake causing many buildings collapsed in China. For the Yushu earthquake, Jin et al [791] derived a building damage assessment from VHR SAR images. After analyzing the features of collapsed, partial collapsed and non-collapsed buildings in the SAR images, they counted the number of buildings with different damage levels and built the damage index for each block.…”

Section: Remote Sensing For Disaster Assessmentmentioning

confidence: 99%

Computational Socioeconomics

Gao,

Zhang,

Zhou

2019

Preprint

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Uncovering the structure of socioeconomic systems and timely estimation of socioeconomic status are significant for economic development. The understanding of socioeconomic processes provides foundations to quantify global economic development, to map regional industrial structure, and to infer individual socioeconomic status. In this review, we will make a brief manifesto about a new interdisciplinary research field named Computational Socioeconomics, followed by detailed introduction about data resources, computational tools, data-driven methods, theoretical models and novel applications at multiple resolutions, including the quantification of global economic inequality and complexity, the map of regional industrial structure and urban perception, the estimation of individual socioeconomic status and demographic, and the real-time monitoring of emergent events. This review, together with pioneering works we have highlighted, will draw increasing interdisciplinary attentions and induce a methodological shift in future socioeconomic studies.

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“…By acquiring multi-polarization SAR data, it is possible to retrieve object information in detail. Although the previous studies have demonstrated the feasibility and significance of building damage assessments using only post-event SAR datasets, two critical problems still exist: (1) Previously, the radar scattering characteristics of earthquake-affected buildings were explained only by the backscattering coefficient of single-polarization SAR data due to a lack of polarimetric SAR data (Balz and Liao 2010; Jin et al 2011); and (2) existing earthquake damage assessment methods can only be applied to fully polarimetric SAR data (Zhai and Huang 2016)—these methods evaluate the damage in units of irregular block areas (see Figure 4b, Dell'Acqua et al 2011). These limitations make such methods difficult to utilize for real applications.…”

Section: Introductionmentioning

confidence: 99%

Building Damage Assessment in the 2015 Gorkha, Nepal, Earthquake Using Only Post-Event Dual Polarization Synthetic Aperture Radar Imagery

et al. 2017

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This paper takes the 2015 Nepal earthquake as a case study to explore the use of post-event dual polarimetric synthetic aperture radar images for earthquake damage assessment. The radar scattering characteristics of damaged and undamaged urban areas were compared by using polarimetric features derived from PALSAR-2 and Sentinel-1 images, and the results showed that distinguishing between damaged and undamaged urban areas with a single polarimetric feature is challenging. A split-based image analysis, feature selection, and supervised classification were employed on a PALSAR-2 image. The texture features derived from the intensity of cross-polarization show higher correlations with the damage class. Additionally, feature selection revealed a positive influence on the overall performance. Employing 70% of the data for training and 30% data for testing, the support vector machine classifier achieved an accuracy of 80.5% compared with the reference data generated from the damage map that was provided by the United Nations Operational Satellite Applications Programme.

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

Cited by 16 publications

References 25 publications

Rapid Damage Assessment by Means of Multi-Temporal SAR — A Comprehensive Review and Outlook to Sentinel-1

Rapid Damage Assessment by Means of Multi-Temporal SAR — A Comprehensive Review and Outlook to Sentinel-1

Computational Socioeconomics

Building Damage Assessment in the 2015 Gorkha, Nepal, Earthquake Using Only Post-Event Dual Polarization Synthetic Aperture Radar Imagery

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