Paper
23 November 2011 Remote sensing hazard monitoring and assessment in Yushu earthquake disaster
Qi Wen, Feng Xu, Shirong Chen
Author Affiliations +
Proceedings Volume 8006, MIPPR 2011: Remote Sensing Image Processing, Geographic Information Systems, and Other Applications; 80061W (2011) https://doi.org/10.1117/12.899746
Event: Seventh International Symposium on Multispectral Image Processing and Pattern Recognition (MIPPR2011), 2011, Guilin, China
Abstract
Yushu Earthquake of magnitude 7.1 Richter in 2010 has brought a huge loss of personal lives and properties to China. National Disaster Reduction Center of China implemented the disaster assessment by using remote sensing images and field investigation. Preliminary judgment of disaster scope and damage extent was acquired by change detection. And the building region of hard-hit area Jiegu town was partitioned into 3-level grids in airborne remote sensing images by street, type of use, structure, and about 685 girds were numbered. Hazard assessment expert group were sent to implement field investigation according to each grid. The housing damage scope and extent of loss were defined again integrated field investigation data and local government reported information. Though remote sensing technology has played an important role in huge disaster monitoring and assessment, the automatic capability of disaster information extraction flow, three-dimensional disaster monitoring mode and bidirectional feedback mechanism of products and services should still be further improved.
© (2011) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Qi Wen, Feng Xu, and Shirong Chen "Remote sensing hazard monitoring and assessment in Yushu earthquake disaster", Proc. SPIE 8006, MIPPR 2011: Remote Sensing Image Processing, Geographic Information Systems, and Other Applications, 80061W (23 November 2011); https://doi.org/10.1117/12.899746
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Cited by 2 scholarly publications.
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KEYWORDS
Earthquakes

Remote sensing

Airborne remote sensing

Roads

Landslide (networking)

Data integration

Mining

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