Estimation of earthquake casualties using high-resolution remote sensing: a case study of Dujiangyan city in the May 2008 Wenchuan earthquake

Feng, Tienan; Hong, Zhonghua; Wu, Honglei; Fu, Qiuping; Wang, Chaoxin; Jiang, Chenghua; Tong, Xiaohua

doi:10.1007/s11069-013-0764-1

Cited by 31 publications

(21 citation statements)

References 29 publications

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“…Radar sensors such as synthetic aperture radars (SARs) can avoid this problem. SAR systems have been used widely in disaster situations such as earthquakes, volcanic eruptions, tsunamis, typhoons and floods (Weissel et al, 2004;Feng et al, 2013;Liu et al, 2013;Dumitru et al, 2015;Yulianto et al, 2015). Klemas (2015) and Lin et al (2016) summarized recent research on flood assessments using optical and SAR sensors.…”

Section: Introductionmentioning

confidence: 99%

Review article: Detection of inundation areas due to the 2015 Kanto and Tohoku torrential rain in Japan based on multi-temporal ALOS-2 imagery

Yamazaki

2018

Nat. Hazards Earth Syst. Sci.

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Abstract. Torrential rain triggered by two typhoons hit the Kanto and Tohoku regions of Japan from 9 to 11 September 2015. Due to the record-breaking amount of rainfall, several riverbanks were overflowed and destroyed, causing floods over wide areas. The PALSAR-2 sensor on board the ALOS-2 satellite engaged in emergency observations of the affected areas during and after the heavy rain. Two pre-event and three co-event PALSAR-2 images were employed in this study to extract flooded areas in the city of Joso, Ibaraki Prefecture. The backscattering coefficient of the river water was investigated first using the PALSAR-2 intensity images and a land-cover map with a 10 m resolution. The inundation areas were then extracted by setting threshold values for backscattering from water surfaces in the three temporal synthetic aperture radar (SAR) images. The extracted results were modified by considering the land cover and a digital elevation model (DEM). Next, the inundated built-up urban areas were extracted from the changes in SAR backscattering. The results were finally compared with those from visual inspections of airborne imagery by the Geospatial Information Authority of Japan (GSI), and more than 85 % of the maximum inundation areas were extracted successfully.

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Section: Introductionmentioning

confidence: 99%

Review article: Detection of inundation areas due to the 2015 Kanto and Tohoku torrential rain in Japan based on multi-temporal ALOS-2 imagery

Yamazaki

2018

Nat. Hazards Earth Syst. Sci.

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“…Compared to other factors, such as traffic accessability, the areas filled with damaged buildings had a lower weighted value. The change in the survival of buildings Coburn (1994) More than 1 week More than five cases 32 % Feng et al (2013) Fewer than 2 days One case (three subcases) 10 % Method of this study Fewer than 2 days Three cases 10 % (0.1, 25 %) 3 was helpful, particularly at the initial stage of earthquake relief. In the disaster areas following an earthquake, the relief supplies and rescuers were in short supply at the beginning (Li et al, 2013).…”

Section: Change In Survival Ratementioning

confidence: 98%

“…In the first step, the pre-earthquake DSM was generated by a point cloud (Ma, 2005), which was marked on the digital topographic map when the resolution of images prior to the earthquake was not high enough to generate the DSM. Otherwise, the pre-earthquake DSM was generated by stereo images (Tong et al, 2012;Feng et al, 2013). The post-earthquake DSM should be generated by stereo images because the digital topographic map post earthquake cannot be obtained.…”

Section: Damage Detectionmentioning

confidence: 99%

Application and prospect of a high-resolution remote sensing and geo-information system in estimating earthquake casualties

Feng

Hong

et al. 2014

Nat. Hazards Earth Syst. Sci.

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Abstract. An accurate estimation of a casualty rate is critical in response to earthquake disasters, and could allow an increase in the survival rate. Building damage is considered to be a major cause of earthquake casualties in developing countries. High-resolution satellite imagery (HRSI) can be used to detect the building damage in a period of a short time. This makes it possible to use a model to estimate earthquake casualties immediately after the occurrence of an earthquake. With respect to the capability of HRSI, this study built a new model for estimating the casualty rate in an earthquake disaster based on remote sensing and a geographical information system. Three groups of earthquake data, the 2003 Bam earthquake, the 2008 Wenchuan earthquake, and the 2010 Yushu earthquake, were used to evaluate this model. The results indicated that our new model significantly improved the accuracy in predicting the casualty rate. The parameters used in the model vary between developed and developing countries. This study could provide valuable information for a more efficient rescue operation in response to earthquakes.

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“…(2) The construction of Gaussian pyramids image is accelerated on the GPU by the use of a separable Gaussian convolution. (6) The sixth step is to compute the corrections of each parameter. (3) The critical points are detected and localized.…”

Section: Graphics Processing Unit-based Parallel Processing For Tie Pmentioning

confidence: 99%

“…Therefore, building damage detection is attracting the attention of many researchers. Furthermore, Feng et al 5,6 estimated the number of casualties based on the detected building damage information. Tong et al 3 proposed an approach to detect the collapsed buildings by calculating the difference between the preseismic and postseismic digital surface models (DSMs) generated from the preseismic and postseismic stereo images.…”

Section: Introductionmentioning

confidence: 99%

Rapid three-dimensional detection approach for building damage due to earthquakes by the use of parallel processing of unmanned aerial vehicle imagery

Hong

Tong

Cao

et al. 2015

J. Appl. Remote Sens

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Rapid damage assessment after an earthquake is vital for an efficient emergency response. With the rapid development of unmanned aerial vehicles (UAVs), they can now be used to rapidly assess the building damage and have the advantages of real-time operation, flexibility, low cost, etc. However, UAV images are "big data," and UAVs can obtain hundreds of scene images in a short period of time. It is, therefore, important to speed up the processing time for UAV images. This paper proposes a parallel processing approach for accelerating the speed of automatic three-dimensional (3-D) building damage detection, using a preseismic digital topographical map and postseismic UAV images. From the experimental results obtained from 3-D building damage detection of the 2013 Ya'an earthquake in Baoxing County, Sichuan province of China, the comparison of the parallel processing in terms of digital surface model generation using postseismic UAV images shows that the total cost of the multicores central processing units (CPUs) and graphics processing unit-based implementation is about 11.0 times faster than the single-core CPU implementation.

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Estimation of earthquake casualties using high-resolution remote sensing: a case study of Dujiangyan city in the May 2008 Wenchuan earthquake

Cited by 31 publications

References 29 publications

Review article: Detection of inundation areas due to the 2015 Kanto and Tohoku torrential rain in Japan based on multi-temporal ALOS-2 imagery

Review article: Detection of inundation areas due to the 2015 Kanto and Tohoku torrential rain in Japan based on multi-temporal ALOS-2 imagery

Application and prospect of a high-resolution remote sensing and geo-information system in estimating earthquake casualties

Rapid three-dimensional detection approach for building damage due to earthquakes by the use of parallel processing of unmanned aerial vehicle imagery

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