Landslide Hazard Zonation Map Research Articles

Landslide susceptibility analysis and hazard zonation of Koh-e-Suleman range using weighted overlay technique

A healthy environment improves the quality of life on Earth, while natural disasters affect the quality of the environment. An area’s Landslide Hazard Zonation (LHZ) provides key information about the susceptibility to natural or manmade disasters. Using the Weighted Overlay Technique, this research aims to develop the landslide susceptibility and zonation mapping of Koh-e-Suleman Range (a hill station around the heritage site). Six causative factors are evaluated: geology, elevation, slope inclination, distance from streams, type of soil, and annual rainfall intensity, considering equal risk influence for all the factors. All causative factor maps were generated to yield equal classes and provide uniformity to the results except for soil types found in the study area. The findings indicate that the study area may comprise four landslide hazard zones with high, medium, low, and very low-intensity susceptibility of landslides. The accuracy of the final LHZ map is verified by comparing the hazard zonation area percentages with the global landslide inventory map from a macro-study of NASA. It was found that the study areas largely fall within low- and very low-hazard zones.

Landslide hazard zonation (LHZ) mapping of Doon Valley using multi-criteria analysis method based on remote sensing and GIS techniques

The occurrence of landslides is a costly and cataclysmic natural hazard that mainly occurs in hilly areas due to factors like earthquakes, cloud burst, extreme rainfall, human pressure, etc. leading to loss of biodiversity, property, and life. Effective and comprehensive landslide risk management is crucial to address landslide susceptibility. Utilizing remote sensing and Geographic Information System (GIS) techniques, this work focuses on the landslide hazard zonation (LHZ) mapping. The study is specifically conducted in the Doon Valley. These advanced technologies help in identifying and categorizing the areas prone to landslides. The Shuttle Radar Topography Mission (SRTM) Digital Elevation Model (DEM) data at 30 m resolution and Sentinel-2B data at 10 m resolution were used to perform the remote sensing and GIS operations in ArcGIS Software. Thematic layers such as Land Use/Land Cover (LULC), Slope, Geology, Soil Type, Elevation, Drainage Density, Vegetation, and Aspect were produced utilizing remote sensing and GIS data. The weighted overlay, a multi-criteria analysis method, was applied to assign attribute values to each thematic layer based on their importance, which was then combined to calculate the landslide hazard zone. The findings of this study demonstrate that landslides are more likely to occur near and above the Main Boundary Thrust/Fault (MBT). The high to very high hazard zone covers 16.64% of the total area, making landslides occurring more frequently. Additionally, the study found that the Doon Valley rivers’ upper segments are more susceptible to landslides than their lower segments. By integrating Remote Sensing and GIS techniques, it is possible to obtain extensive knowledge of regions prone to landslides. This information will be helpful for decision-makers and planners to reduce the impact of landslides in the near future.

GIS-based MCDM approach for landslide hazard zonation mapping in east Gojjam zone, central Ethiopia

Landslides are prevalent in the Ethiopian highlands, particularly in the east Gojjam zone, which is highly affected by landslide problems. This research was carried out in the east Gojjam zone, northwestern Ethiopia. The study area is part of an economically important area in the country, and it is the main source of water for the Grand Ethiopian Renaissance Dam (GERD). The main objective of this work was to undertake a detailed inventory of past landslide locations and prediction of present and future landslide hazards, as well as the preparation of a landslide zonation map in the East Gojjam zone by using the Analytical Hierarchy Process (AHP) with the GIS technique. The parameters used for this study were slope degree, slope aspect, land use and land cover, road proximity, rainfall, lithology, altitude, and river proximity. The various causative parameters were collected from the field, and suitable modifications were made to the thematic maps. Finally, the ratings for various parameters were used as the basis to prepare the LHZ map in GIS windows. The landslide susceptibility and inventory mapping were produced in the GIS environment. The results of the study show that the main driving factors for the landslide hazards in the area were river proximity, rainfall, and manmade activities. Validation of this LHZ map revealed that more than 80% of past landslides match within the "high hazard zone" and reasonably accepted the rationality of the adopted methodology. The considered parameters, as well as their evaluation of the production of LHZ-Map, were confirmed. The produced landslide inventory map is very important for urban planners, agricultural studies, environmentalists, and future landslide hazardous prevention and mitigation strategies.

InSAR-based landslide hazard mapping and identification of at-risk infrastructures in a selected district of North Shewa Zone, Ethiopia.

The devastating nature of landslides demands a thorough understanding of their spatial distribution and the risks they pose to human settlements and infrastructural assets. In this study, we employed a combination of Interferometric Synthetic Aperture Radar (InSAR) and Geographic Information System (GIS) techniques to explore the western escarpment of the Main Ethiopian Rift, with a focus on selected districts within the northern Shewa Zone, Ethiopia. By analyzing the SAR data, we derived 28 displacement maps and utilized them to create a comprehensive landslide hazard zonation map. The results indicated significant ground displacement, particularly along the rift margins and areas characterized by rugged terrain. The hazard zones were classified based on their level of risk, with 44% classified as very low, 24% as low, 5% as moderate, 13% as high, and 14% as very high hazard zones. The accuracy of our results was evaluated using receiver operating characteristic (ROC) analysis, which was conducted utilizing landslide inventory data. The analysis demonstrated a remarkable area under the curve (AUC) value of 0.848, providing strong evidence for the validity of our findings. Additionally, our study involved a spatial and statistical assessment of major infrastructure, revealing that 20 to 28% of these properties were in hazard zones ranging from moderate to very high levels, which calls for efficient risk-reduction actions. Therefore, this finding enables stakeholders to identify high-risk areas, prioritize mitigation efforts, and minimize the impact of landslide disasters.

Landslide Hazard Zonation Mapping using MCDM Techniques – A study over Kodagu District, Karnataka

Landslides pose significant and recurring hazards in various parts of India, particularly during the rainy season, causing extensive damage to infrastructure and loss of life. To address this issue, it is crucial to map the hazardous zones, raise awareness among local communities and guide authorities in disaster management efforts. This study aimed to develop a landslide hazard zonation map using different thematic maps such as aspect, drainage density, geology, lineament density, land use land cover, rainfall, road network, slope and soil layers. The study employing methods such as AHP and a modified power method was based on AHP for the development of landslide hazard zonation maps. The findings indicated that the PM-AHP technique yielded superior results in identifying highly risky zones. According to this method, approximately 250.65 sq.km. of the area was classified as falling within the highly risky zone.

Landslide hazard zonation using Bivariate Frequency Ratio Method along National highway-1 from Baramulla-Uri Road stretch, North Kashmir Himalayas, India

The study focuses on the application of frequency ratio method (FRM) for the creation of landslide hazard map along the National Highway-1(NH-1) road between Baramulla and Uri in North Kashmir Himalaya, India. The landslide hazard zonation (LHZ) map was prepared by integrating all the landslide-inducing factors with frequency ratio values. A database of notable landslides in the study area was integrated with the hazard map for validation. The overall study showed that 22.28% of the study area falls under very high and high hazard zones. Finally, the output map was validated using the 40% landslide validation data. Moreover, ROC curve method was utilized to validate the model which showed the acceptable result of 0.803 AUC value for the landslide hazard map of the study area. Therefore, LHZ map produced by this study can be used to guide planners or engineers in identifying safe zones for carrying out development projects and for future risk assessment studies in the study region.

Landslide Hazard Zonation of Tehri Reservoir Rim Area Using Modified LHEF Rating Scheme

The study aimed to utilize the capabilities of geospatial technology for landslide hazard evaluation factor (LHEF) scheme recorded in the Bureau of Indian Standard (BIS) code to prepare a landslide hazard zonation (LHZ) map of the Tehri reservoir rim area at the macro-scale. Multisource remote sensing data were visually and digitally interpreted to produces thematic layers and slope facet as recorded in BIS method. LHEF method is suited for meso and macro scale mapping thus, to broaden the scope of LHEF scheme, novel approaches were adopted namely, the mapping unit ‘slope facet’ was more precisely extracted through digital and visual interpretation of remote sensing data, the structural favorability map was extracted using photo-lineament density criteria. Additionally, two external factors, rainfall and seismicity were incorporated in LHEF rating scheme and used a matrix-based system to propose their combined rating. With the modified LHEF rating scheme, we have succeeded in identifying LHZ with reasonable accuracy. The bar chart method used to validate LHZ results that clearly indicated a high number of landslides falling in high to very high hazard zone conversely, very few landslides observed in low to very low hazard zone identified from current approach.

Landslide hazard, susceptibility and risk assessment (HSRA) based on remote sensing and GIS data models: a case study of Muzaffarabad Pakistan

The notion of this research is based on the two devastating earthquake events that happened on October 8, 2005, and September 24, 2019, in the regions of Azad Kashmir and Muzaffarabad. This study aims to (i) identification of the susceptible zones where landslides can occur in the future; (ii) preparation of landslide inventory maps using vector data, satellite imagery, Shuttle Radar Topographic Mission (STRM) and Advanced Space-borne Thermal Emission and Reflection Radiometer (ASTER) DEM; (iii) implementation of Analytical Hierarchy Process (AHP) model using weighted overlay analysis (WOA). For this purpose, key factors such as land use, faults, slope, contours, soil, and seismology maps are used to develop a landslide hazard zonation map. The output landslide susceptibility map has four susceptibility levels such as low, medium, high, and very high vulnerable zones. The results indicated that a highly susceptible landslide zone is found in the northwestern part of Muzaffarabad, which is a metropolitan region. Moreover, there are 127 active landslides are identified and collectively about 9% of the study area is very highly susceptible to future landslides. Furthermore, research findings are helpful in tactful thinking for future infrastructure development, and ecological protection in high-susceptible landslide regions in Muzaffarabad. It also helps the Government to make strategies based on any specific zones on a priority basis to reduce the casualties and destruction in future landslide events.

Landslide hazard zonation along Phulmawi village andTlungvel village road, Thingsulthliah Rural Development Block, Aizawl District, Mizoram, India

Landslides are the most common hazard in the state of Mizoram. Rapid development and the uncontrolled interaction with the nature are the reason for l and slide in Mizoram. Landslide vulnerability of Mizoram is already high due to lithology, land use and land cover, geomorphology and slope factor. The extensive mining activities along the highways for road construction and building materials also cause one of major landslide along the highways in the state of Mizoram. The present study investigates the Landslide Hazard Zones along the national highway 54 between Phulmawi village and Tlungvel village. The National Highway Number 54 is the most important road connecting Aizawl city and Northern, Southern and Eastern part of the State of Mizoram. Thematic layers such as slope morphometry, geomorphology, Lithology and land use / land cover were created using Remote Sensing and Geographic Information System (GIS) techniques. On the different groups of thematic layers, a weight age rating system dependent on the relative importance of various causative factors is used. In the GIS setting, the classes were given the corresponding rating value as attribute information. An ordinal ranking of 0 to 10 was allocated to each class within a thematic layer. Landslide hazard zonation map generated could be utilized as a reliable database for mitigation measures and planning for secured growth of the village.

Landslide Hazard Zonation Mapping Techniques on Himalayan Region in India: A Survey

This review article is focused on the modern mapping techniques for creating a near-accurate landslide hazard zonation (LSZ) map focused on the different parts of the Himalayan Mountain region in India. The necessity of an LSZ map has been discussed by some given examples showing the vulnerability that comes with every landslide. As one of the youngest folded mountain ranges, The Himalayas are very much prone to landslides, with the development of modern technologies, the way of research has also transformed. In this article, the focus is identifying some recent techniques based on GIS and Remote sensing technologies which proves the accuracy and necessity of more research work. There are many areas that are vulnerable to landslides but completely untouched. The focus is to merge different techniques to create an understanding of how the technology can be a useful tool to create more accurate LHZ maps for different locations. Key Words: Landslide Hazard Zonation (LHZ), Technologies, GIS, Remote Sensing

Landslide hazard zonation and evaluation around Debre Markos town, NW Ethiopia—a GIS-based bivariate statistical approach

The main purpose of this study was to perform landslide hazard zonation and evaluation around Debre Markos town, Northwest Ethiopia. This was achieved using a GIS-based bivariate statistical technique. Initially, a landslide inventory map containing information on past and active landslide locations was prepared. In this study, eight conditioning factors, including slope material (lithology and soil mass), elevation, aspect, slope, land use, land cover, curvature, distance to fault, and distance to drainage, were identified and integrated with the ArcGIS platform. Data were collected from field mapping, satellite images, and digital elevation models. All conditioning factors were statistically analyzed to determine their relationship to previous landslides. The hazard map revealed that 17.15% (40.60 km2) of the study area falls under no hazard zone, 25.53% (60.45 km2) in low hazard zone, 28.04% (66.39 km2) in moderate hazard zone, 18.93% (44.83 km2) in high hazard zone, and the remaining 10.36% (24.54 km2) in very high hazard zone. The validation of the landslide hazard zonation map shows that 94% of past landslides fall in high or very high hazard zones, while 3% fall in moderate hazard zone, 2% fall in low hazard zone, and 1% fall in no hazard zone. The validation of the LHZ map thus, reasonably showed that the adopted methodology produced satisfactory results. The delineated hazard zones may practically be applied for the regional planning and development of infrastructures in the area. The results also indicated that slope angle, distance to fault, distance to drainage, and slope material types were statistically significant in controlling the landslides.

Landslide Hazard Assessment and Zonation by using Slope Susceptibility Evaluation Parameter (SSEP) Rating Scheme- a Case from Debre Sina, Northern Ethiopia

Rainfall-induced landslides of different types and sizes frequently affect the hilly and mountainous terrains of the highlands of Ethiopia. The principal objective of the proposed research study was intended to prepare a landslide hazard zonation map of the area, particularly for hazardous zones. In the present study, the Slope Susceptibility Evaluation Parameter rating scheme has been implemented as a relevant approach to map the landslide hazard of the Debresina area, which has experienced slope failure problems for a long period of time. The geology of the area includes quaternary sediments, ignimbrite, rhyolite, different kinds of basalts, and tuff deposits, which are highly weathered and changed into unconsolidated sediments at some localities. Locally observed geological structures such as joints, dykes, and other discontinuities have a considerable role in the initiation of landslide hazards. As a general methodology, a facet map was prepared from a topographic map (1:50,000) and rating values were assigned to each causative parameter (both intrinsic and external) based on its severity in triggering landslide hazard. The study area was classified into three hazard classes, of which 25 % of the slopes fall into a moderate hazard zone, while 58 % and 17 %were found to be high and very high hazard zones, respectively. Validation of the landslide hazard zonation map with past landslide activities suggests the rationality of the considered governing parameters, the adopted technique, tools, and procedures in developing the study area's landslide hazard map. Further, in order to validate the landslide hazard map prepared during the present study, active landslide activities and potential instability areas, delineated through inventory mapping, were overlaid on it, which yielded promising results.

Implications and inclusion of size-dependent scenario earthquakes on landslide hazard zonation: A case study of the Indian Himalayas

Seismically induced landslide hazard zonation (LHZ) studies typically examine the correlation between the magnitude of a single earthquake event with the spatial patterns of coseismic landslides. However, studies on the impact of different scenario earthquakes (in terms of their return periods) on landslide hazards are found to be rare, especially in case of the Himalayas. The study presents a novel approach to integrate scenario earthquakes generated probabilistically for different return periods with the persistent landslide hazards in the Himalayas. The Peak Ground Acceleration (PGA) is estimated for scenario earthquakes with 10, 50, 100, 225, and 475 years return periods. A dynamic weightage system is developed to rank the scenario earthquakes. Subsequently five LHZ maps under different seismic conditions have been prepared. The results indicate that the maximum static Landslide Potential Index (LPI) for the study area increased by 25% and 35% respectively when scenario earthquakes with return periods of 225 and 475 years were considered. When the scenario earthquake with 475 years return period was considered, 51% of the total area fell in the very high landslide hazard zone. Even with a moderate earthquake size viz. 100 years’ return period, the seismic LHZ map demarcated 28% of the study area as very high landslide hazard zone. This was an approximately 211% spatial increment for the same zone corresponding to the static landslide susceptibility map that excluded the seismic factor. The trend (significant areal increments for the high and very high landslide hazard zones) remains the same in all scenario earthquakes. Based on the results, the study concludes that seismicity becomes the main landslide causative factor for moderate to great earthquakes. Thus, it is recommended to include earthquake parameters for a more pragmatic evaluation of the landslide hazard in seismically active mountain belts.

Adapting sudden landslide identification product (SLIP) and detecting real-time increased precipitation (DRIP) algorithms to map rainfall-triggered landslides in Western Cameroon highlands (Central-Africa)

BackgroundNASA’s developers recently proposed the Sudden Landslide Identification Product (SLIP) and Detecting Real-Time Increased Precipitation (DRIP) algorithms. This double method uses Landsat 8 satellite images and daily rainfall data for a real-time mapping of this geohazard. This study adapts the processing to face the issues of data quality and unavailability/gaps for the mapping of the recent landslide events in west-Cameroon’s highlands.MethodsThe SLIP algorithm is adapted, by integrating the inverse Normalized Difference Vegetation Index (NDVI) to assess the soil bareness, the Modified Normalized Multi-Band Drought Index (MNMDI) combined with the hydrothermal index to assess soil moisture, and the slope inclination to map the recent landslide. Further, the DRIP algorithm uses the mean daily rainfall to assess the thresholds corresponding to the recent landslide events. Their probability density function (PDF) curves are superimposed and their intersections are used to propose sets of dichotomous variables before (1948–2018) and after the 28 October 2019 landslide event. In addition, a survival analysis is performed to correlate landslide occurrence to rainfall, with the first known event in Cameroon as starting point, and using the Cox model.ResultsFrom the SLIP model, the Landslide Hazard Zonation (LHZ) map gives an overall accuracy of 96%. Further, the DRIP model states that 6/9 ranges of probability are rainfall-triggered landslides at 99.99%, between June and October, while 3/9 ranges show only 4.88% of risk for the same interval. Finally, the survival probability for a known site is up to 0.68 for the best value and between 0.38 and 0.1 for the lowest value through time.ConclusionsThe proposed approach is an alternative based on data (un)availability, completed by the site’s lifetime analysis for a more flexibility in observation and prediction thresholding.

Landslide hazard zonation mapping using frequency ratio and relative effect models in Katteri macro watershed Nilgiris district, Tamilnadu

Present analysis is endeavored in Kattery macro watershed, Nilgiris District, Tamil Nadu, Republic of India wherever a serious landslide happened. totally different thematic maps relating landslide hazard studies were established from the toposheets and Remote Sensing satellite symbolisms utilizing Geographical system (GIS). Landslide hazard zonation map of Kattery macro watershed was ready by distribution correct weights and ranks for numerous themes. The north eastern and south-western part of Kattery macro watershed is additional susceptible to landslides and also the south-eastern part is a smaller amount vulnerable.

GIS-Based Landslide Hazard Evaluation and Zonation of Kg. Chas, Kuala Betis, Gua Musang, Kelantan

This research entitled GIS-Based Landslide Hazard Zonation and Evaluation of Kg. Chas, Kuala Betis, Gua Musang, Kelantan. The study area is located in Kuala Betis, Gua Musang, Kelantan with the area covered is 25 km2. The aim of this research is to evaluate the landslide causative factors and to produce the landslide hazard zonation map with scale of 1:25000. The method used in generating the landslide hazard zonation map is by using the Geographical Information System (GIS) which is using the Weighted Overlay Method (WOM). The parameters that triggered the occurrence of landslide were analyzed and overlaid in order to generate the landslide hazard zonation map. Digital Elevation Model (DEM) data were used to extract the parameters. Normalized Difference Vegetation Index (NDVI) methods were used to identify the changes of the vegetation and to locate the locations of the past landslides in the study area. The results showed that the landslide hazard zonation map were divided into 5 classes. Class 1 is no hazard, class 2 is low hazard, class 3 is medium hazard, class 4 is high hazard and class 5 is the highest hazard. Based on the landslide hazard zonation map, the study area is covered with a low hazard of landslide and the probability of landslide to occur is low.

Remote Sensing and GIS Based Potential Landslide Hazard Zonation in Ambo Woreda: Central Ethiopia

Landslide hazard is becoming a serious problem in many parts of the world because of its frequent occurrence and related effects it is causing to human and properties. Areas of high altitude and steep slopes were susceptible to landslide hazards depending on their soil type, geology, land use/ land cover, proximity to road and streams, aspects, seismic level and ground water level variation. Even though there are problems related to landslide hazards in the region where Ambo woreda is located, there was significant landslide related scientific studies conducted in the area. The current study was aimed to prepare landslide hazard zonation map for Ambo Woreda based on landslide hazard causal factors including spatial rainfall distribution, local geology, slope, elevation, aspect, soil type, LULC, distance from stream and land slide inventory data based on Geographical Information System and remote sensing techniques. As a result 921 polygons covered an area of 32.9km 2 (3.43%) of the total study area was found with past landslide hazards. Past landslide hazard areas were studied to investigate the contribution of each landslide causing factors and to map the potential landslide hazard zones of Ambo woreda. Consequently the study area was categorized in to four levels of Potential Landslide Hazard Zones termed as very high, high, moderate, low and very low. The total area of about 959.7km 2 , was classified as 14.7%, 53.28%, 23.43%, 4.99% and 3.6% among the very high, high, moderate, low and very low potential landslide hazard zones respectively. The presence of very high and high potential landslide hazard levels in wider area of Ambo woreda can be used as a warning message for local planners and the community to urgently plan for the reduction of potential landslide disaster risk reduction using various practices such as intensive soil and water conservation works and enhancing landslide disaster preparedness activities. Keywords: Landslide Hazard, Landslide hazard zonation, Potential landslide hazard DOI: 10.7176/JEES/10-2-03 Publication date: February 29 th 2020

Evaluation of landslide hazard and its impacts on hilly environment of the Nilgiris District - a geospatial approach

Landslide Hazard Zonation (LSH) maps play a key role in landuse planning particularly in landslide prone areas. LSH mapping is globally accepted one for analyzing the area for landslide susceptibility. Different approaches were followed by many researchers in India to prepare landslide hazard zonation mapping depending upon their need and requirement. The Nilgiris district in Western Ghats of India is one of the severe to high landslide hazard prone areas of India. Many agencies have carried out research on LSH mapping for the Nilgiris district with different scales. A systematic study of inventory and zonation was 122carried out in 1980’s by government agencies. However there is no proper updation or documentation on landslides after 1980’s in the district The purpose of this paper is to review the existing landslide-related studies in the district of The Nilgiris and review the district’s existing landslide hazard map with updated information. Landslide hazard maps in The Nilgiris were compiled in the GIS platform from various authenticated sources. Data on landslides from 1824 to 2014 were collected and a spatial database on landslides was created. A detailed inventory was analyzed and used for revision of the district’s landslide hazard impact on the 2009 landslides.. Based on the landslide inventory and densely populated areas and repeated landslides at the same locations, the most landslide hazard areas were identified.

Landslide Hazard Mapping: GIS Based Susceptibility Assessment of Leoutikhola Watershed, Dhankuta, Nepal

This article examines the landslide hazard mapping in Leoutikhola watershed of Dhankuta district, eastern hills of Nepal. The hills are regarded as one of the most vulnerable areas in the world. The area is prone to different types of natural hazards such as landslide, debris flow, gully erosion, mass wasting, and flooding. Various studies pointed out biophysical and socioeconomic factors are more responsible to landslide hazards in the hill-slope environment. This paper argues that the rainfall intensity, unscientific methods of cultivation and lack of environment friendly developmental activities in steep slope are some of the major driving factors to landslide in the Leoutikhola watershed area. Leoutikhola watershed area has been suffering from different types of natural hazards such as landslide, debris flow, gully erosion, mass wasting and flooding. Field verification and satellite imageries are the major sources for the information to analyze. Due to its fragile and very weak geological condition, geomorphic hazard is considered more common than other types of hazards which lose massive lives and property in the study area. The field observation and local people perception indicate a large amount of budget required to mitigate natural hazards in this area especially for landslide. In this context, this paper attempts to portray the landslide hazard zonation and susceptibility mapping correlated with various factors. For this purpose, bivariate statistical index and Geographic Information System (GIS) and Remote Sensing (RS) tools are used to calculate weighted values. The overall parameters indicate that in the series (-4.2 to 4.58) of five different hazard zones like very low, low, moderate, high and very high. The paper concludes that hazard determination calculated values indicate to 4.2 to -2.09, -2.09 to -1.0, -1.0 to-0.05, -0.05 to 1.24 and 1.24 to 4.58 respectively in the range of quartile series.

Multi-criteria evaluation for landslide hazard zonation by integrating remote sensing, GIS and field data in North Kashmir Himalayas, J&K, India

Landslides are one of the major natural hazards that are experienced in hilly terrains all over the world and Himalayas are no exception to this. Though primarily attributed to natural causes, landslides are increasing in frequency and magnitude due to anthropogenic disturbances. This has resulted in enormous damage to both life and property. Hence, identification of landslide prone areas is essential for safer strategic planning of future developmental activities. A landslide hazard zonation (LHZ) map is generated by multi-criteria evaluation (MCE) of various responsible factors like slope, drainage, land use and land cover, lithology, soil and aspect which are weighted on the basis of their relative contribution to the occurrence of landslides. These weights are normalized such that the sum of normalized weights is equal to unity. The study area is divided into five zones based on the deciles of the normalized weights. The results reveal that 40% of the area falls under high LHZ which needs immediate engineering and agronomic measures. The MCE model presented in this study could be utilized for other mountainous regions in general and Himalayas in particular.