ESTIMATING SUITABLE CATEGORIZATION METHOD FOR LANDSLIDE SUSCEPTIBILITY MAPPING OF MANDI DISTRICT

被引:1
|
作者
Singh, Ankit [1 ]
Gupta, Sharad Kumar [2 ]
Nitesh [1 ]
Shukla, Dericks Praise [1 ]
机构
[1] IIT Mandi, Sch Engn, Mandi, Himachal Prades, India
[2] Punjab Remote Sensing Ctr, PAU Campus, Ludhiana, Punjab, India
来源
2022 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS 2022) | 2022年
关键词
Landslide Susceptibility Zonation (LSZ); Frequency Ratio; Data categorization; Natural break; Mandi district;
D O I
10.1109/IGARSS46834.2022.9884424
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
Due to significant increase in landslide activity in all over the world, landslide susceptibility mapping has proven to be an effective tool for mitigation and management of this problem. Present study aims to prepare landslide susceptibility map of Mandi district using frequency ratio method. Total 981 landslide points were identified of past occurrence and were randomly divided into 697 points as training and 294 points as testing. Eight causative factors (slope, aspect, distance to road, distance to streams, distance to lineament, lithology, geomorphology, distance to road and elevation) were identified for landslide. Based on the methods lithology, geomorphology, and aspect were identified important to generate landslides. LSI was prepared using the FR values and were classified into five zones using quantile, natural break, and equal interval classification. For validation the Area under Curve (AUC) for all the classification types were calculated out of which equal interval classification found to be most accurate.
引用
收藏
页码:5481 / 5484
页数:4
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