landslide susceptibility mapping of north sikkim using geospatial techniques (original) (raw)
Related papers
2020
Occurrence of landslides is very common and frequent phenomenon in hilly terrain of Indian Himalayan region leading to severe environmental and socio-economic issues. The current research used the method of weighted parameter, Remote Sensing (RS) and Geographic Information System (GIS) for landslide susceptibility mapping in the study area, East Sikkim district of Sikkim Himalaya. The different thematic layers were produced from high-resolution terrain corrected ALOS PALSAR DEM of 12.5 meter spatial resolution, Sentinel-2A data of 10 meter spatial resolution multi-spectral satellite information, LANDSAT 8 multi-spectral satellite information and multiple other landslide-related sources such as rainfall distribution, slope and structural/linear features (faults, thrusts, roads). These thematic map layers were integrated in a GIS platform (ArcGIS10.7) to delineate vulnerable landslide prone zones. The weighted assigned values were used for assigning weightage ranging from 0 to 10 for ...
GIS Application in Landslide Susceptibility Mapping of Indian Himalayas
GIS Landslide
The paper presents GIS based spatial data analysis for landslide susceptibility mapping in parts of Sikkim Himalaya. Six important causative factors for landslides were selected and corresponding thematic data layers were prepared in GIS. The input data were collected from the topographic maps, satellite image, field data and published maps. Numerical weights for different categories of these factors were determined based on a statistical approach and then integrated in GIS environment to arrive at landslide susceptibility map of the area. The landslide susceptibility map classifies the area into five classes of landslide susceptible zones i.e., very high, high, moderate, low and very low. An attempt was also made to validate the map with the existing landslides of the area.
GIS based spatial data analysis for landslide susceptibility mapping
Journal of Mountain Science, 2008
Landslide susceptibility map delineates the potential zones for landslides occurrence. The paper presents a statistical approach through spatial data analysis in GIS for landslide susceptibility mapping in parts of Sikkim Himalaya. Six important causative factors for landslide occurrences were selected and corresponding thematic data layers were prepared in GIS. Topographic maps, satellite image, field data and published maps constitute the input data for thematic layer preparation. Numerical weights for different categories of these factors were determined based on a statistical approach and the weighted thematic layers were integrated in GIS environment to generate the landslide susceptibility map of the area. The landslide susceptibility map classifies the area into five different landslide susceptible zones i.e., very high, high, moderate, low and very low. This map was validated using the existing landslide distribution in the area.
GIS Based Landslide Susceptibility Mapping — A Case Study in Indian Himalaya
The paper presents GIS based spatial data analysis for landslide susceptibility mapping in parts of Sikkim Himalaya. Six important causative factors for landslides were selected and corresponding thematic data layers were prepared in GIS. The input data were collected from the topographic maps, satellite image, field data and published maps. Numerical weights for dierent categories of these factors were determined based on a statistical approach and then integrated in GIS environment to arrive at landslide susceptibility map of the area. The landslide susceptibility map classifies the area into five classes of landslide susceptible zones i.e., very high, high, moderate, low and very low. An attempt was also made to validate the map with the existing landslides of the area.
International Journal of Engineering Research and Technology (IJERT), 2013
https://www.ijert.org/mapping-of-landslide-susceptibility-using-geospatial-technique-a-case-study-in-kothagiri-region-western-ghats-tamil-nadu-india https://www.ijert.org/research/mapping-of-landslide-susceptibility-using-geospatial-technique-a-case-study-in-kothagiri-region-western-ghats-tamil-nadu-india-IJERTV2IS121059.pdf Landslides present a significant constraint to development in many parts of the study area which experience frequent landslides. Landslides are among the costliest and more damaging natural hazards in mountainous regions, triggered mainly under the influence of earthquakes and/or rainfall. Landslides cause adverse effects on human lives and economy worldwide. Through scientific analysis of landslides, we can assess and predict landslide-susceptible areas, and thus decrease landslide damage though proper preparation. This paper presents modeling of landslide susceptibility mapping using remote sensing data, GIS tools In this study, the landslide susceptibility maps are prepared based on the causative factors of slope, aspect, geology, geomorphology, soil, drainage density, lineament density and land use and land cover. All these factors are extracted from the spatial database constructed using remotely sensed data and topographic maps. The different classes of thematic layers were assigned the corresponding rating value, as non spatial information in the GIS was used to generate for each data layer. The weighted parametric approach was applied to determine degree of susceptibility to landslides. The landslide susceptibility map was prepared using this technique and is reclassified into four classes showing low to very high susceptibility classes. The analysis of the susceptibility modeling results shows the high significance of slope, drainage density, geological and land cover parameters. The landslide susceptibility map can be used to reduce damage associated with landslides and to land cover planning
The research presented in this paper employs a simple yet straightforward deterministic technique that is based on the rationale that the landslide vulnerability of an area would be determined by the aggregation of the landslide densities of the various causative factors present therein. The landslide density of a causative factor is computed as the ratio of the frequency of the landslides to the area covered by the causative factor. In the present study, the thematic layers for fourteen important causative factors that were further subdivided into a total of 39 sub-categories were collected and intersected in the GIS environment that resulted in the division of study area into a number of spatial units. The landslide inventory layer prepared through the satellite map and the field survey was also intersected in the spatial data set. Landslide density was then computed for each of the sub-categories of the landslide causative parameters. Landslide Information Value (LSIV) for each individual spatial unit was determined by summing up of the landslide densities of the different causative factors present in individual spatial unit. The LSIVs determined for the various spatial units of the entire study area were grouped into five zones of landslide vulnerability based on natural breaks (Jenks) technique. The research was carried out in the Rumtek-Samdung Study area in the Central Himalayas located in the Sikkim state in India. The zonation map prepared through this technique showed significant amount of agreement with the field occurrences of landslides that is further ascertained by the prevalence of a Vulnerability Assessment Accuracy of 80%.
2013
Landslides present a significant constraint to development in many parts of the study area which experience frequent landslides. Landslides are among the costliest and more damaging natural hazards in mountainous regions, triggered mainly under the influence of earthquakes and/or rainfall. Landslides cause adverse effects on human lives and economy worldwide. Through scientific analysis of landslides, we can assess and predict landslide-susceptible areas, and thus decrease landslide damage though proper preparation. This paper presents modeling of landslide susceptibility mapping using remote sensing data, GIS tools In this study, the landslide susceptibility maps are prepared based on the causative factors of slope, aspect, geology, geomorphology, soil, drainage density, lineament density and land use and land cover. All these factors are extracted from the spatial database constructed using remotely sensed data and topographic maps. The different classes of thematic layers were ass...
Landslide Susceptibility Mapping Using Image Satellite and GIS Technology
Landslides are among the great destructive factors which cause lots of fatalities and financial losses all over the world every year. The aim of the research was landslide susceptibility mapping by remote sensing data processing and GIS spatial analysis. The area study in research is central Zab basin in west Azerbaijan province, Iran. In this research, through geological maps and field studies, we primarily prepared a map for landslide distributions in Zab basin. Then, applying other information sources such as the existing thematic maps, we studied and defined the 8 factors such as, lithology, slope, slope aspect, annual rainfall, land use, distance to waterway, distance to the fault , and distance to road. That affect occurrence of the landslides. To get more precision, speed and facility in our analysis all descriptive and spatial information was entered into GIS system. After preparation of the needed information layers by influential parameters on landslides, we drew the zoning maps of landslide hazard via information coming from satellite image classification (Quickbird, Ikonos), and then evaluated and compared them. According to the obtained index, and the comparison of landslide distribution map and zoning map of landslide hazard prepared by each of the methods in GIS environment, This model gives also indications about the relevant factors influencing slope instability.
Disaster prevention and …, 2010
Purpose -The purpose of this research is to produce the landslide susceptibility map of Fraser's Hill and its surroundings in Pahang (Malaysia), utilizing remote sensing data and Geographic Information System (GIS) as a way to monitor sustainable highland development. Design/methodology/approach -Ancillary data are collected, processed, and constructed into a spatial database in a GIS platform to produce the satellite image. The factors chosen that influence landslide occurrence are land cover, vegetation index (NDVI), precipitation, and geology. Landslide-hazardous areas are analyzed and mapped using the landslide-occurrence factors through the heuristic approach Analytic Hierarchy Process (AHP). Findings -It is demonstrated that the integration of remote sensing data and GIS database is of assistance in managing land-use planning of sustainable development. The verification with the existing landslides record shows a noteworthy accuracy.
IJERT-Landslide Susceptibility Mapping Using Image Satellite and GIS Technology
International Journal of Engineering Research and Technology (IJERT), 2014
https://www.ijert.org/landslide-susceptibility-mapping-using-image-satellite-and-gis-technology https://www.ijert.org/research/landslide-susceptibility-mapping-using-image-satellite-and-gis-technology-IJERTV1IS6011.pdf Landslides are among the great destructive factors which cause lots of fatalities and financial losses all over the world every year. The aim of the research was landslide susceptibility mapping by remote sensing data processing and GIS spatial analysis. The area study in research is central Zab basin in west Azerbaijan province, Iran. In this research, through geological maps and field studies, we primarily prepared a map for landslide distributions in Zab basin. Then, applying other information sources such as the existing thematic maps, we studied and defined the 8 factors such as, lithology, slope, slope aspect, annual rainfall, land use, distance to waterway, distance to the fault , and distance to road. That affect occurrence of the landslides. To get more precision, speed and facility in our analysis all descriptive and spatial information was entered into GIS system. After preparation of the needed information layers by influential parameters on landslides, we drew the zoning maps of landslide hazard via information coming from satellite image classification (Quickbird, Ikonos), and then evaluated and compared them. According to the obtained index, and the comparison of landslide distribution map and zoning map of landslide hazard prepared by each of the methods in GIS environment, This model gives also indications about the relevant factors influencing slope instability.