Abstract
This study utilizes and explores the feasibility and application of swarm intelligence for landslide susceptibility modeling based on collected inventory of rainfall-induced shallow landslide events. Eleven geospatial factors are considered, including topographic, vegetative, environmental, geological and man-made information. Landslide inventory and factors are overlapped to obtain the training data for modeling (classification) and verification. Experimental results indicate that swarm intelligence algorithms can provide plausible results for landslide susceptibility modeling, comparing with conventional landslide detection and prediction methods.
Original language | English |
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State | Published - 2014 |
Event | 35th Asian Conference on Remote Sensing 2014: Sensing for Reintegration of Societies, ACRS 2014 - Nay Pyi Taw, Myanmar Duration: 27 Oct 2014 → 31 Oct 2014 |
Conference
Conference | 35th Asian Conference on Remote Sensing 2014: Sensing for Reintegration of Societies, ACRS 2014 |
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Country/Territory | Myanmar |
City | Nay Pyi Taw |
Period | 27/10/14 → 31/10/14 |
Keywords
- Ant colony optimization
- Landslide susceptibility
- Particle swarm optimization