An analysis of landslide susceptibility zonation using a subjective geomorphic mapping and existing landslides |
| |
| Authors: | Mihai Pavel John D. NelsonR. Jonathan Fannin |
| |
| Affiliation: | a Department of Forest Resources Management, Faculty of Forestry, University of British Columbia, 2424 Main Mall, Vancouver, BC, Canada V6T 1Z4
b Department of Civil Engineering, University of British Columbia, 6250 Applied Science Lane, Vancouver, BC, Canada V6T 1Z4 |
| |
| Abstract: | This study explores the possibility of creating landslide susceptibility mappings by using two types of data: (i) an existing subjective geomorphic mapping; and (ii) landslides already identified in the area analyzed. The analysis is conducted using a type of Artificial Neural Network (ANN) named Learning Vector Quantization. For the subjective geomorphic mapping various definitions of stability were considered/analyzed, some using a 2-class system and some using a 5-class system.The study concludes that mappings using an existing subjective geomorphic classification and based on two stability classes can be successfully replicated with the ANN-based approach. However, mappings based on existing landslides and on the 5-class system do not yield results sufficiently accurate for practical applications. Creation of landslide susceptibility mappings involved utilization of data of numerous types (numerical and class-type variables). This study also investigated various methods of data coding and identified the most appropriate method for this type of analysis. |
| |
| Keywords: | Landslide susceptibility mapping Subjective geomorphic mapping Artificial Neural Networks (ANN) Learning Vector Quantization (LVQ) Geographic Information Systems (GIS) |
| 本文献已被 ScienceDirect 等数据库收录！ |
|
