Paper
17 December 2015 The application of residential distribution monitoring based on GF-1 images
Yan Cui, Suju Li, Wei Wu, He Huang, Ming Liu
Author Affiliations +
Proceedings Volume 9811, MIPPR 2015: Multispectral Image Acquisition, Processing, and Analysis; 981114 (2015) https://doi.org/10.1117/12.2205705
Event: Ninth International Symposium on Multispectral Image Processing and Pattern Recognition (MIPPR2015), 2015, Enshi, China
Abstract
Earthquake is one of the major natural disasters in the world. Since the twentieth century, it caused a large number of casualties and lots of direct economic losses. With the advantage of wide-coverage, high spatial-temporal resolution, remote sensing technology has been used for residential distribution monitoring of different earthquake intensity. In this paper, based on interpretation of GF-1 remote sensing data, Digital Elevation Model (DEM), reference image, earthquake intensity, resident population statistics data, residential distribution analyzing model has been formed which including: GF-1 remote sensing data processing sub-model, residential distribution monitoring sub-model and residential distribution analyzing sub-model. Case analysis in Nie lamu, Ji long, Ding ri in Tebet during Nepal's 8.1 magnitude earthquake shows that: the proposal model has a high precision and could be used in residential distribution monitoring, combined with resident population statistics data, affected population in earthquake intensity influence region can be acquired, quickly assessment the possibly influence degree of earthquake can be qualitative analyzed.
© (2015) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Yan Cui, Suju Li, Wei Wu, He Huang, and Ming Liu "The application of residential distribution monitoring based on GF-1 images", Proc. SPIE 9811, MIPPR 2015: Multispectral Image Acquisition, Processing, and Analysis, 981114 (17 December 2015); https://doi.org/10.1117/12.2205705
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KEYWORDS
Earthquakes

Remote sensing

Data modeling

Statistical analysis

Data processing

Statistical modeling

Satellites

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