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ORIGINAL ARTICLE
Year : 2017  |  Volume : 5  |  Issue : 3  |  Page : 57-62

Geospatial landslide hazard zonation for district pauri garhwal, Uttarakhand, India, Using quantitative methods


Uttarakhand Space Application Centre, Dehradun, Uttarakhand, India

Correspondence Address:
Neelam Rawat
Uttarakhand Space Application Centre, Dehradun - 248 001, Uttarakhand
India
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/ijhsdm.ijhsdm_14_17

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Introduction: Landslides are one of the critical natural processes, which cause enormous damage to life and property..Uttarakhand Himalaya is vital to sustainity of region. This region is very fragile due to topographic and climatic condition. Landslides in the mountainous terrains are natural derivational processes and one of the most. There is a need for Landslide Hazard Zonation for identification of potential landslide areas. Keeping this in mind one hilly district, Pauri district of Uttarakhand, India was selected. Materials and Methods: The present study is an attempt towards development of a landslide model by using multi-criteria decision analysis in GIS and remote sensing techniques for landslide hazard zonation. The IRS LISS-4 satellite imageries, Survey of India topographical maps, and ancillary data were used as inputs to the study. The data layers of land use–land cover and geology were interpreted from satellite image and available ancillary data. Other raster thematic layers, i.e., slope, aspect, elevation, and drainage density, have been generated in Arc info three-dimensional analyst tool using ASTER DEM of 30 m resolution. A numerical rating scheme for the factors was developed for spatial data analysis in GIS. Results and Decision: Using high-resolution LISS-IV and Cartosat-2A, merged data of 2011–2012 landslides were mapped by visual interpretation of satellite image. A total of 167 landslides have been identified. Elevation map of Pauri district was prepared by classifying digital elevation model into 5 elevation categories. Distribution of landslides in different elevation categories is also done. Maximum landslides have occurred in elevation category (710–1134 m) and (185–709 m). Slope map has been generated and classifi ed into 6 slope classes, i.e. 0°–5°, 5°–10°, 10°–20°, 20°–30°, 30°–40°, and more than 40°. Distribution of landslides in different slope categories is also done. Maximum landslides have occurred in slopecategories (10°–20°), (20°–30°), and (30°–40°). Aspect map has been generated and classified into 8 aspect classes. Maximum landslides have occurred in aspect categories South-West (14.37%), South (35.97%), and South East (15.57%) directions. The Southern aspect (SW-S-SE) contributes to 65.91% of total landslides. Drainage density map has been generated from ASTER DEM using three-dimensional Analyst tool and classified into 6 classes, namely 0–2, 2–4, 4–6, 6–8, and more than 8 (km/sq.km). Geological map of Pauri district has been adopted from Geological map from Geological SOI. Rock types such as phyllites, quartzites, slates, siltstone, sandstones, graywacks, granitoids, alluvium, crystallines and metamorphics, and limestones are present in the district. Distribution of landslides in different drainage density categories is also done. Maximum landslides have occurred in drainage density category 2–4, 4–6, and 6–8 (km/sq.km). LULC map of Pauri was classified into various classes such as water body, forest scrub, wasteland/scrub, tree-clad, forest evergreen, agriculture land, built up, forest deciduous open, and forest deciduous dense/close. Maximum landslides have occurred in forest deciduous open category (84) followed by agriculture land (22), forest scrub (14), forest evergreen and forest deciduous dense/close (13 each), and water body. Conclusion: The above-mentioned 6 layers were integrated in the weighted overlay model of Arc Info and weights were assigned corresponding to landslide occurrence in these layers. The influence of the layer in causing landslide has also assigned. The final LHZ map generated after processing 6 themes. The final map has been classified into 3 categories, namely high, moderate, and low hazard categories. Of a total of 167 landslides, 110Landslides fall in the high HZ and 43 landslides fall in moderate HZ category while only 14 landslides fall in the low HZ category. 34.01% of the district falls under low HZ category and 40.73% falls under moderate HZ category while 25.26 under high HZ category. More layers need to be added in the model to obtain more precision. This map is not checked in the fi eld ground truth.


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