AIGIS-based methodology for natural terrain landslide susceptibility mapping in Hong Kong

C. F. Lee; H. Ye; M. R. Yeung; X. Shan; G. Chen

doi:10.18814/epiiugs/2001/v24i3/001

AIGIS-based methodology for natural terrain landslide susceptibility mapping in Hong Kong

C. F. Lee, H. Ye, M. R. Yeung, X. Shan, G. Chen

Research output: Contribution to journal › Article › peer-review

30 Citations (Scopus)

Abstract

This paper presents a novel application of Artificial Intelligence (AI) and Geographic Information System (GIS) to the mapping of natural terrain landslide susceptibility in Hong Kong. The method is applied to the central part of Lantau Island as a pilot study. First, we discuss the key technical concepts of AI and GIS, the advantages of their integrated application, and the growing importance of remote sensing data. We then describe the working procedure including the construction of the GIS database, pre-treatment of input data, and training of the network classifier. High prediction rates and positive outcomes from reliability tests demonstrate the success of the methodology and show its great potential for use in landslide disaster mitigation planning in Hong Kong.

Original language	English
Pages (from-to)	150-158
Number of pages	9
Journal	Episodes
Volume	24
Issue number	3
DOIs	https://doi.org/10.18814/epiiugs/2001/v24i3/001
Publication status	Published - Sept 2001
Externally published	Yes

All Science Journal Classification (ASJC) codes

Earth and Planetary Sciences(all)

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10.18814/epiiugs/2001/v24i3/001

Cite this

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abstract = "This paper presents a novel application of Artificial Intelligence (AI) and Geographic Information System (GIS) to the mapping of natural terrain landslide susceptibility in Hong Kong. The method is applied to the central part of Lantau Island as a pilot study. First, we discuss the key technical concepts of AI and GIS, the advantages of their integrated application, and the growing importance of remote sensing data. We then describe the working procedure including the construction of the GIS database, pre-treatment of input data, and training of the network classifier. High prediction rates and positive outcomes from reliability tests demonstrate the success of the methodology and show its great potential for use in landslide disaster mitigation planning in Hong Kong.",

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AB - This paper presents a novel application of Artificial Intelligence (AI) and Geographic Information System (GIS) to the mapping of natural terrain landslide susceptibility in Hong Kong. The method is applied to the central part of Lantau Island as a pilot study. First, we discuss the key technical concepts of AI and GIS, the advantages of their integrated application, and the growing importance of remote sensing data. We then describe the working procedure including the construction of the GIS database, pre-treatment of input data, and training of the network classifier. High prediction rates and positive outcomes from reliability tests demonstrate the success of the methodology and show its great potential for use in landslide disaster mitigation planning in Hong Kong.

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AIGIS-based methodology for natural terrain landslide susceptibility mapping in Hong Kong

Abstract

All Science Journal Classification (ASJC) codes

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