scholarly journals LANDSLIDE SUSCEPTIBILITY ASSESSMENT OF KOKAP AREA USING MULTIPLE LOGISTIC REGRESSION

2015 ◽  
Vol 6 (2) ◽  
Author(s):  
Somyot Makealoun ◽  
Doni Prakasa Eka Putra ◽  
Wahyu Wilopo

A number of landslides have occured in Kokap SubDistrict, Kulon Progo Regency, Yogyakarta Special Province, Indonesia, which have influenced the communities. The natural disaster is commonly associated with a few days of heavy rainfall events. To mitigate the impact of landslides in this area, a landslide susceptibility assessment needs to be carried out. The main objective of this research is to develop a landslide susceptibility zonation in the research area by applying a logistic regression (LR) method. Field observation was conducted at 68 locations in the research area, in which 46 landslides occured. Data of slope angle, lithology, geologic structure and groundwater conditions were collected. The relationship between landslide occurrence and the slope angle, lithology, geologic structure and groundwater conditions was analysed using the LR method. The analysis results showed a 0.984 standard error, implying a good-fit model. The study area was classified into very low, low, moderate, high and very high landslide susceptibility zones with 0–20%, 20–40%, 40–60%, 60–80%, and 80–100%, respectively, probabilities of occurrence. A 60% area of the total study area was classified as a moderate to very high susceptibility to landslide. From 47 landslides, 80% landslides occured in high and very high landslide susceptibility zones, 17% landslides occured in the moderate susceptibility zone and 2% landslides occured in the low susceptible zone. None of landslides occured in the very low landslide susceptibility zone. The analysis results show that LR method is a very useful method for landslide prediction. Keywords: landslide susceptibility, multiple logistic regression, Kokap Kulon Progo-Indonesia

2017 ◽  
Vol 6 (3) ◽  
pp. 57-60
Author(s):  
Денис Кривогуз ◽  
Denis Krivoguz

Modern approaches to the region’s landslide susceptibility assessment are considered in this paper. Have been presented descriptions of the most used techniques for landslide susceptibility assessment: logistic regression, indicator validity, linear discriminant analysis and application of artificial neural networks. These techniques’ advantages and disadvantages are discussed in the paper. The most suitable techniques for various conditions of analysis have been marked. It has been concluded that the most acceptable techniques of analysis for a large number of input data related to the studied region are the method of logistic regression and indicator validity method. With these methods the most accurate results are achieved. When there is a lack of information, it is more expedient to use linear discriminant analysis and artificial neural networks that will minimize potential analysis inaccuracies.


2013 ◽  
Vol 864-867 ◽  
pp. 2756-2759
Author(s):  
Zhi Wang Wang ◽  
Jian Hua Zhang ◽  
Duan You Li

This paper deals with landslide hazards susceptibility assessment in the study area from Zigui to Badong counties in TGP reservoir region using RS and GIS technology. The causative factors including lithology, distance to faults, elevation, slope aspect, slope angle, drainage network, distance to river and distribution of plant are derived from geological map, Digital Elevation Model (DEM) and Spot imagery data using RS and GIS technology. The paper analyzes landslide susceptibility assessment using fuzzy weights of evidence method, which could combine knowledge-based fuzzy membership values with data-based conditional probabilities to improve the accuracy of landslide susceptibility assessment. The research result is very coincident with the occurrence of the known landslides in the study area.


Sign in / Sign up

Export Citation Format

Share Document