|
Assessment of landslide susceptibility using geoinformatics and a frequency ratio model: a case study of Mae Tha River Watershed in Northern Thailand |
|---|---|
| รหัสดีโอไอ | |
| Creator | Pichawut Manopkawee |
| Title | Assessment of landslide susceptibility using geoinformatics and a frequency ratio model: a case study of Mae Tha River Watershed in Northern Thailand |
| Contributor | Niti Mankhemthong |
| Publisher | Asia-Pacific Journal of Science and Technology |
| Publication Year | 2567 |
| Journal Title | Asia-Pacific Journal of Science and Technology |
| Journal Vol. | 29 |
| Journal No. | 4 |
| Page no. | 10 (10 pages) |
| Keyword | Frequency ratio model, Landslide inventory, Landslide susceptibility, Mae Tha fault, Mae Tha River |
| URL Website | https://so01.tci-thaijo.org/index.php/APST/ |
| Website title | https://so01.tci-thaijo.org/index.php/APST/article/view/266866 |
| ISSN | 2539-6293 |
| Abstract | A landslide is one form of geological hazard that causes socioeconomic impacts, geo-environmental changes, and damage to human lives and properties globally. The Mae Tha River watershed, located in a complex faulted- and high-slope terrain, is considered to be especially susceptible to occurrences of landslides. This study aimed to evaluate landslide susceptibility across this unique watershed using the integration of geoinformatics and a statistical frequency ratio model. Across the watershed, 67 landslide scars in the mountainous region were observed and examined for use as landslide inventory data. The landslide inventory data were combined with causative factors to produce a landslide susceptibility index as well as zones. The analysis revealed that approximately 36% of the entire watershed was highly susceptible to landslides, particularly the high terrain in the watershed's east and west. The accuracy, reliability, and predictability of the landslide susceptibility data were validated using the values of the area under the receiver operating characteristic (ROC) curve analysis (AUC). AUC values between 0.6 and 0.8 indicated that the model's performance in identifying and predicting landslide susceptibility classes was reasonably satisfactory to good. The results suggested that the frequency ratio model was an efficient statistical tool for landslide susceptibility assessment. Effective landslide susceptibility classes can be produced for community planning and mitigation purposes in this watershed as well as other areas with similar conditions. |
