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The method for semi-automatic extraction of residential area from high resolution remote sensing images |
| LI Jinxiang1, LI Zhiqiang2, LI Shuai1, WANG Wei1, CHEN Yong1 |
1. Earthquake Administration of Xinjiang Uygur Autonomous Region, Urumqi 830011, China;
2. Institute of Geology, China Earthquake Administration, Beijing 100029, China |
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Abstract Residential area, as an important hazard-bearing body of earthquake disasters, usually constitutes the basis of earthquake emergency preparation. In this paper, 2 m resolution GF-1 satellite remote sensing data were used to extract the spatial distribution information of residential area, which could provide data support for the earthquake emergency preparation. The results reveal that more accurate residential area information of the high resolution GF-1 2 m image can be extracted based on gray level co-occurrence matrix, binarization and mathematical morphology. This proposed algorithm has high accuracy and good robustness. However, higher false alarm rate factor was shown in the extraction of sparse vegetation and non-residential buildings. Thus, in order to ensure data accuracy, the authors compared and analyzed the extraction results and the images, and extracted the ultimate data results semi-automatically by the artificial intervention.
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| Keywords
SBAS InSAR
offset tracking
large scale deformation
mining working diagram
spatial and temporal evolution law
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Issue Date: 15 August 2017
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2017,
Vol. 29
