Abstract
According to observations over the few years before and after typhoon and extreme rainfall events in the Laonong catchment of Kaohsiung, Southern Taiwan, this study combined a genetic adaptive neural network architecture, image texture analysis, and a geographic information system (GIS) in satellite image interpretation and land use change analysis to obtain disaster records and surface information. A multivariate hazards evaluation method was applied to quantitatively analyze the weights of various natural environmental and slope development hazard factors. Furthermore, this study established a slope landslide potential assessment model and depicted a slope landslide potential diagram by using the GIS platform. The impact of extreme rainfall events on slope landslide and landslide developmental characteristics were discussed. The findings can be a reference for subsequent slope development countermeasures and as an assessment for the academia and engineering fields involved in predicting landslide disasters caused by slope development.
| Original language | English |
|---|---|
| Pages (from-to) | 705-716 |
| Number of pages | 12 |
| Journal | Journal of Marine Science and Technology (Taiwan) |
| Volume | 23 |
| Issue number | 5 |
| DOIs | |
| Publication status | Published - 2015 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 15 Life on Land
All Science Journal Classification (ASJC) codes
- Oceanography
- Ocean Engineering
- Mechanics of Materials
- Mechanical Engineering
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