A fuzzy set based approach for integration of thematic maps for landslide susceptibility zonation

Author(s):  
D. P. Kanungo ◽  
M. K. Arora ◽  
S. Sarkar ◽  
R. P. Gupta
Author(s):  
S. Prasanna Venkatesh ◽  
S. E. Saranaathan

<p><strong>Abstract.</strong> Among the various natural hazards, landslide is the most widespread and damaging hazard. In recent times, throughout a lot of attention is being drawn to evaluate the risk due to landslides. The invention of remote sensing and GIS have been new vistas in the field of geo scientific studies viz. geomorphological mapping, groundwater potential mapping, disaster management etc. The present study has been undertaken to study different thematic maps like, contour, drainage, slope, aspect, curvature, DEM, DTM, drainage density, drainage intensity, geology, lineament, lineament density, lineament intensity, geomorphology, land use, weathering thickness, run off, soil thickness and buffer maps like road, drainage, lineament etc. in CNG ghat section, Gudalur, The Nilgiris. For this purpose, the satellite image IRS – RS2, LISS III January 2014 used to prepare different thematic maps. The contour, drainage and road network were incorporate from SoI Toposheets. The slope, curvature, aspects and buffer maps were prepared from GIS environments. Based on field studies, above said thematic maps (22 nos.) were prepared and were grouped into 3 categories viz. Geology, Hydrology and Terrain. In each category the input maps were assigned different score as well as each layer has been given different weightage. Finally the categories are analysed through multi – criteria analysis to find out 5 different vulnerability classes. The 5 different land susceptibility zones are classified as very low, low, moderate, high and very high. The percentages of area under different susceptibility classes are 3%, 20%, 51%, 25%, and 1% respectively. The locations of small area major landslides and slip locations were calculated from different years using (2010 and 2014) Trimble GPS in the field. The field data was converted into point layer in GIS and landslide inventory map was prepared. This map was superimposed in landslide susceptibility zonation map. As per field data 0%, 9.25%, 57.5%, 32% and 1.25% Slide points are come under very low, low, moderate, high, very high susceptibility zones respectively.</p>


2021 ◽  
Vol 30 (4) ◽  
pp. 683-691
Author(s):  
G. Kavitha ◽  
S. Anbazhagan ◽  
S. Mani

Landslides are among the most prevalent and harmful hazards. Assessment of landslide susceptibility zonation is an important task in reducing the losses of lifeand properties. The present study aims to demarcate the landslide prone areas along the Vathalmalai Ghat road section (VGR) using remote sensing and GIS techniques. In the first step, the landslide causative factors such as geology, geomorphology, slope, slope aspect, land use / land cover, drainage density, lineament density, road buffer and relative relief were assessed. All the factors were assigned to rank and weight based on the slope stability of the landslide susceptibility zones. Then the thematic maps were integrated using ArcGIS tool and landslide susceptibility zonation was obtained and classified into five categories ; very low, low, moderate, high and very high. The landslide susceptibility map is validated with R-index and landslide inventory data collected from the field using GPS measurement. The distribution of susceptibility zones is ; 16.5% located in very low, 28.70% in low, 24.70% in moderate, 19.90% in high and 10.20% in very high zones. The R-index indicated that about 64% landslide occurences correlated with high to very high landslide susceptiblity zones. The model validation indicated that the method adopted in this study is suitable for landslide disaster mapping and planning.


Landslides ◽  
2005 ◽  
Vol 2 (1) ◽  
pp. 61-69 ◽  
Author(s):  
Ashis K. Saha ◽  
Ravi P. Gupta ◽  
Irene Sarkar ◽  
Manoj K. Arora ◽  
Elmar Csaplovics

2019 ◽  
Vol 47 (3) ◽  
pp. 497-511 ◽  
Author(s):  
Amit Chawla ◽  
Srinivas Pasupuleti ◽  
Sowmiya Chawla ◽  
A. C. S. Rao ◽  
Kripamoy Sarkar ◽  
...  

Sign in / Sign up

Export Citation Format

Share Document