Application of gis and frequency ratio model in mapping the potential surface failure sites in the poonjar sub-watershed of meenachil river in western ghats of kerala

2007 ◽  
Vol 35 (3) ◽  
pp. 275-285 ◽  
Author(s):  
H. Vijith ◽  
G. Madhu
Keyword(s):  
Frequency Ratio ◽  
Western Ghats ◽  
Potential Surface ◽  
Ratio Model ◽  
Surface Failure ◽  
Meenachil River ◽  
Frequency Ratio Model ◽  
Application Of Gis

Flood Susceptibility Analysis in Chennai Corporation Using Frequency Ratio Model

2021 ◽  
Author(s):  
Logesh Natarajan ◽  
Tune Usha ◽  
Muthusankar Gowrappan ◽  
Bavinaya Palpanabhan Kasthuri ◽  
Prabhakaran Moorthy ◽  
...  
Keyword(s):  
Frequency Ratio ◽  
Ratio Model ◽  
Susceptibility Analysis ◽  
Flood Susceptibility ◽  
Frequency Ratio Model

Fuzzy–frequency ratio model for avalanche susceptibility mapping

2016 ◽  
Vol 9 (12) ◽  
pp. 1168-1184 ◽  
Author(s):  
Satish Kumar ◽  
Pankaj Kumar Srivastava ◽  
Akshay Gore ◽  
Mritunjay Kumar Singh
Keyword(s):  
Frequency Ratio ◽  
Susceptibility Mapping ◽  
Ratio Model ◽  
Frequency Ratio Model

Application of Airborne LiDAR-Derived Parameters and Probabilistic-Based Frequency Ratio Model in Landslide Susceptibility Mapping

2012 ◽  
Vol 225 ◽  
pp. 442-447 ◽  
Author(s):  
Biswajeet Pradhan ◽  
Zulkiflee Abd. Latif ◽  
Siti Nur Afiqah Aman
Keyword(s):  
High Resolution ◽  
Landslide Susceptibility ◽  
Frequency Ratio ◽  
Susceptibility Mapping ◽  
Airborne Lidar ◽  
Landslide Susceptibility Mapping ◽  
Susceptibility Map ◽  
Ratio Model ◽  
Landslide Susceptibility Map ◽  
Frequency Ratio Model

The escalating number of occurrences of natural hazards such as landslides has raised a great interest among the geoscientists. Due to the extremely high number of point’s returns, airborne LiDAR permits the formation of more accurate DEM compared to other space borne and airborne remote sensing techniques. This study aims to assess the capability of LiDAR derived parameters in landslide susceptibility mapping. Due to frequent occurrence of landslides, Ulu Klang in Selangor state in Malaysia has been considered as application site. A high resolution of airborne LiDAR DEM was constructed to produce topographic attributes such as slope, curvature and aspect. These data were utilized to derive secondary deliverables of landslide parameters such as topographic wetness index (TWI), surface area ratio (SAR) and stream power index (SPI). A probabilistic based frequency ratio model was applied to establish the spatial relationship between the landslide locations and each landslide related factors. Subsequently, factor ratings were summed up to yield Landslide Susceptibility Index (LSI) and finally a landslide susceptibility map was prepared. To test the model performance, receiver operating characteristics (ROC) curve was carried out together with area under curve (AUC) analysis. The produced landslide susceptibility map demonstrated that high resolution airborne LiDAR data has huge potential in landslide susceptibility mapping.

scholarly journals Integrating Landslide Typology with Weighted Frequency Ratio Model for Landslide Susceptibility Mapping: A Case Study from Lanzhou City of Northwestern China

2021 ◽  
Vol 13 (18) ◽  
pp. 3623
Author(s):  
Heping Shu ◽  
Zizheng Guo ◽  
Shi Qi ◽  
Danqing Song ◽  
Hamid Reza Pourghasemi ◽  
...  
Keyword(s):  
Influencing Factors ◽  
Landslide Susceptibility ◽  
Frequency Ratio ◽  
Assessment Process ◽  
Northwestern China ◽  
Formation Mechanisms ◽  
Ratio Model ◽  
Lanzhou City ◽  
Different Types ◽  
Frequency Ratio Model

Although numerous models have been employed to address the issue of landslide susceptibility at regional scale, few have incorporated landslide typology into a model application. Thus, the aim of the present study is to perform landslide susceptibility zonation taking landslide classification into account using a data-driven model. The specific objective is to answer the question: how to select reasonable influencing factors for different types of landslides so that the accuracy of susceptibility assessment can be improved? The Qilihe District in Lanzhou City of northwestern China was undertaken as the test area, and a total of 12 influencing factors were set as the predictive variables. An inventory map containing 227 landslides was created first, which was divided into shallow landslides and debris flows based on the geological features, distribution, and formation mechanisms. A weighted frequency ratio model was proposed to calculate the landslide susceptibility. The weights of influencing factors were calculated by the integrated model of logistic regression and fuzzy analytical hierarchy process, whereas the rating among the classes within each factor was obtained by a frequency ratio algorithm. The landslide susceptibility index of each cell was subsequently calculated in GIS environment to create landslide susceptibility maps of different types of landslide. The analysis and assessment process were separately performed for each type of landslide, and the final landslide susceptibility map for the entire region was produced by combining them. The results showed that 73.3% of landslide pixels were classified into “very high” or “high” susceptibility zones, while “very low” or “low” susceptibility zones covered only 3.6% of landslide pixels. The accuracy of the model represented by receiver operating characteristic curve was satisfactory, with a success rate of 70.4%. When the landslide typology was not considered, the accuracy of resulted maps decreased by 1.5~5.4%.

Sign in / Sign up

Export Citation Format

Share Document