| Record |
| Author |
Linlin Ge; Alex Ng; Zheyuan Du |
| Title |
Time Series Satellite InSAR Technique for Disaster Prevention? |
Type |
Conference Article |
| Year |
2018 |
Publication |
Proceedings of ISCRAM Asia Pacific 2018: Innovating for Resilience – 1st International Conference on Information Systems for Crisis Response and Management Asia Pacific. |
Abbreviated Journal |
Iscram Ap 2018 |
| Volume |
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Issue |
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Pages |
200-212 |
| Keywords |
InSAR, Foshan, Guangzhou, CSK, subsidence |
| Abstract |
Interferometric synthetic aperture radar (InSAR) has been widely used for mapping terrain and monitoring ground deformation. For example, the advanced time series InSAR (TS-InSAR) technique has been increasingly used to measure mm-level urban deformation. Subsidence from underground tunnel excavation has been known for more than a decade in Guangzhou and Foshan in Southern China, but past studies have only monitored the subsidence patterns as far as 2011 using InSAR. In this study, the deformation occurring during the most recent time-period between 2011 and 2017 has been measured using COSMO-SkyMed (CSK). We found that significant surface displacement rates occurred in the study area varying from -35 mm/year to 10 mm/year. A comparison between temporal and spatial patterns of deformations from our TS-InSAR measurements and different land use types in Guangzhou shows that there is no clear relationship between them. A detailed analysis on the sinkhole collapsed in early 2018 has been conducted, suggesting that surface loading may be a controlling factor of the subsidence, especially along the road and highway. Continuous monitoring of the deforming areas is important in order to minimise the risk of land subsidence and prevention of disasters. |
| Address |
UNSW Sydney; Guangdong University of Technology; UNSW Sydney |
| Corporate Author |
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Thesis |
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| Publisher |
Massey Univeristy |
Place of Publication |
Albany, Auckland, New Zealand |
Editor |
Kristin Stock; Deborah Bunker |
| Language |
English |
Summary Language |
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Original Title |
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| Series Editor |
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Series Title |
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Abbreviated Series Title |
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| Series Volume |
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Series Issue |
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Edition |
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| ISSN |
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ISBN |
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Medium |
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| Track |
Geospatial and temporal information capture, management, and analytics in support of Disaster Decision Making |
Expedition  |
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Conference |
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| Notes |
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Approved |
no |
| Call Number |
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Serial |
1674 |
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