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Conference Paper: Roles of Remote Sensing Technology in Landslide Risk Management of Hong Kong
Title | Roles of Remote Sensing Technology in Landslide Risk Management of Hong Kong |
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Authors | |
Keywords | Remote sensing Natural terrain Slope safety management Machine learnin |
Issue Date | 2021 |
Publisher | Springer. |
Citation | The 5th World Landslide Forum (WLF5): Implementing and Monitoring the Sendai Landslide Partnerships 2015-2025, online virtual meeting, Kyoto, Japan, 2-6 November 2021. In Tiwari, B ... et al( eds.), Understanding and Reducing Landslide Disaster Risk, v. 4: Testing, Modeling and Risk Assessment, p. 471-477 How to Cite? |
Abstract | Natural terrain covers over 60% of the land area of Hong Kong. With the close proximity of developments to hillsides and high annual rainfall, Hong Kong is under a constant threat from natural terrain landslides. Over the past years, the Geotechnical Engineering Office (GEO) of the Civil Engineering and Development Department of the Hong Kong Special Administrative Region Government has applied state-of-the-art remote sensing techniques, for example, laser scanning, photogrammetry and interferometric synthetic aperture radar, in landslide risk management. These include landslide hazard identification and monitoring, post-landslide responses and residual risk management, design of landslide prevention and mitigation measures etc. This paper discusses the advantages of remote sensing technology and their applications to enhance the slope safety of Hong Kong. Pilot studies applying machine learning on identification of geological features from aerial imageries and further studies being/to be conducted are also covered. |
Description | Theme 4 Testing, Modeling and Risk Assessment - Session 4.5 Recent Development in Disaster Risk Assessment - no. 4-50 |
Persistent Identifier | http://hdl.handle.net/10722/284219 |
ISBN | |
ISSN | |
Series/Report no. | ICL Contribution to Landslide Disaster Risk Reduction (CLDRR) |
DC Field | Value | Language |
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dc.contributor.author | Kwan, JSH | - |
dc.contributor.author | Leung, WK | - |
dc.contributor.author | Choi, CE | - |
dc.date.accessioned | 2020-07-20T05:57:00Z | - |
dc.date.available | 2020-07-20T05:57:00Z | - |
dc.date.issued | 2021 | - |
dc.identifier.citation | The 5th World Landslide Forum (WLF5): Implementing and Monitoring the Sendai Landslide Partnerships 2015-2025, online virtual meeting, Kyoto, Japan, 2-6 November 2021. In Tiwari, B ... et al( eds.), Understanding and Reducing Landslide Disaster Risk, v. 4: Testing, Modeling and Risk Assessment, p. 471-477 | - |
dc.identifier.isbn | 9783030607050 | - |
dc.identifier.issn | 2662-1894 | - |
dc.identifier.uri | http://hdl.handle.net/10722/284219 | - |
dc.description | Theme 4 Testing, Modeling and Risk Assessment - Session 4.5 Recent Development in Disaster Risk Assessment - no. 4-50 | - |
dc.description.abstract | Natural terrain covers over 60% of the land area of Hong Kong. With the close proximity of developments to hillsides and high annual rainfall, Hong Kong is under a constant threat from natural terrain landslides. Over the past years, the Geotechnical Engineering Office (GEO) of the Civil Engineering and Development Department of the Hong Kong Special Administrative Region Government has applied state-of-the-art remote sensing techniques, for example, laser scanning, photogrammetry and interferometric synthetic aperture radar, in landslide risk management. These include landslide hazard identification and monitoring, post-landslide responses and residual risk management, design of landslide prevention and mitigation measures etc. This paper discusses the advantages of remote sensing technology and their applications to enhance the slope safety of Hong Kong. Pilot studies applying machine learning on identification of geological features from aerial imageries and further studies being/to be conducted are also covered. | - |
dc.language | eng | - |
dc.publisher | Springer. | - |
dc.relation.ispartof | Understanding and Reducing Landslide Disaster Risk | - |
dc.relation.ispartof | Workshop on World Landslide Forum (WLF 2020) / The 5th World Landslide Forum (WLF5) | - |
dc.relation.ispartofseries | ICL Contribution to Landslide Disaster Risk Reduction (CLDRR) | - |
dc.subject | Remote sensing | - |
dc.subject | Natural terrain | - |
dc.subject | Slope safety management | - |
dc.subject | Machine learnin | - |
dc.title | Roles of Remote Sensing Technology in Landslide Risk Management of Hong Kong | - |
dc.type | Conference_Paper | - |
dc.identifier.email | Choi, CE: cechoi@hku.hk | - |
dc.identifier.authority | Choi, CE=rp02576 | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1007/978-3-030-60706-7_51 | - |
dc.identifier.hkuros | 311466 | - |
dc.identifier.volume | 4 | - |
dc.identifier.spage | 471 | - |
dc.identifier.epage | 477 | - |
dc.publisher.place | Cham | - |
dc.identifier.issnl | 2662-1894 | - |