Geological, hydrological and atmospheric vicissitudes lead to calamitous destruction of flora and fauna, artificial constructions and fatalities resulting in socio economic disruption . Disaster events triggered by nature are inexorable but the rate of fatalities can be abridged by creating awareness among the people (Luu et al. 2017). Frequent occurrence of disasters events are recorded lately due to the incongruous enhancement accomplishments implemented by human life without considering Earth natural system (Ahmad 2007). Over 1 billion of people’s life are critically affected by natural disasters during the past 2 decades due to the deficiency of possessions, framework and preparedness systems (Watson et al. 2007). Changes occurring in earth’s atmosphere and modification of topography due to human activities results in various natural and manmade disasters (Suresh and Yarrakula 2018a, 2019). Landslides are one among the various disasters that results in fatalities and loss of infrastructure and economy (Mata-Lima et al. 2013).
Among various natural disasters experienced with in the Indian extent, one of the foremost hydrogeological hazardous event that distress major portion of India is Landslides (Kapur 2005). Landslides are one of the most epoch-making hazards that have an impact on numerous locations of the subcontinent mainly during monsoon season (Senthilkumar et al. 2017). Landslides are a natural process of earth’s life cycle that hits the mountainous regions frequently during monsoon period. Landslides are failure of land mass down the slope affecting landscapes intimidating human life, Flora, Fauna and non-natural structures under unpredictable climatic and lithological conditions (Shirani and Pasandi 2019).
Being a natural disaster existing in mountainous provinces, landslides distresses communal and economic development, specifically in emerging provinces (Suresh and Yarrakula 2018b). Himalayan range in the northern and north-eastern of India and Western Ghats and Eastern Ghats in the southern part of India are highly prone to landslide events resulting in casualties and economical loss (Stephen 2012). Varying topography along Himalayas and Western Ghats in India hold an astonishing historical catastrophic landslide events over decades (Kumar and Annadurai 2013). Rainfall triggered landslide hit Guwahati on 18th September 1948 resulting in over 500 casualties and reported that an entire village has been destroyed by the landslide (Mandal and Mondal 2018).
In 1968, Darjeeling experienced heavy precipitation of about 1000 mm resulting in 91 landslides across a highway stretch of 60 km resulting in death of over 1000 human life (Pal et al. 2016). Series of landslides hit Mapla village in Uttarakhand from 11th August, 1998 for a period of 7 days wiping out the entire locality resulting in over 380 causalities (Paul et al. 2000). Kedarnath in Uttarakhand experienced landslide triggered by floods on 16th June 2013 which is reported to have over 5700 casualties and is recorded as a devastating landslide event in the history of landslides in India (Manish et al. 2013). In Western Ghats of India, landslides occurrence has increased over decades resulting in increase in the rate of casualties and damage to properties in the Nilgiris, Idukki District, Wayanad District, Kodagu District and Western parts of Pune district (Kumar et al. 2017). Malin landslide triggered due to heavy rainfall hit along the Western Ghats on 30th July 2014 resulted in killing over 151 people and near 100 where found missing post disaster (Sarvade et al. 2014).
Saklespur is a hill station located along the Western Ghats at a mean seal level of about 956 m, which is a tourist attraction spot well known for coffee, cardamom, pepper and areca plantations. Located along the Western Ghats, Saklespur is prone to landslides during the monsoon season that starts in June and ends at September. With lesser landslides events recorded compared to Madikeri, Nilgiris and Munnar along the Western Ghats, the location failed to grasp the attention of the researchers. Frequent landslides recorded in Saklespur has led to the damage of crop fields and for the villagers to migrate to rehabilitation camps. Figure 1 represents the location of the study area considered in the present study.
Influential factors and methodology from literature:
Recent studies have proven the ability of remote sensing and GIS in site suitability analysis with the aid of various spatial information. Introduction of Analytic Hierarchy Process (AHP) paves way for the decision makers in utilising the spatial datasets wisely in updating process of the hazard zonation maps (Chandio et al. 2013). Study on mapping landslide susceptibility zones was carried out using AHP and Fuzzy logic over Izeh Basin of Iran. Results from the study concluded that over 53% of the historical landslide event are recorded in the very high vulnerable zone proving that the methodology can be adopted for landslide studies (Feizizadeh et al. 2014). Nilgiris is one the landslide prone regions and a study over the Nilgiris using AHP and spatial data confirmed that nearly 90% of the landslide events recorded fall under hazardous zone (Suresh and Yarrakula 2018b). Thanh and De Smedt (2012) developed a landslide susceptibility map for Luoi district, Thus Thien Hue Province, Vietnam using remote sensing and GIS techniques. Analytic Hierarchy Process also used in various analysis like Precipitation (Vaishnavi et al 2017) and in studies of categorising the factors of precipitation (Vaishnavi et al 2020). AHP based multi-criteria decision making techniques is adopted using various thematic layers such as slope, land use / land cover, geomorphology, lineament density, lithology, elevation, weather, distance from drainage and precipitation for the identification of landslide susceptibility zones. As a result from the study a landslide susceptibility map for Luoi district is developed with four classes such as low, moderate, high and very high zones respectively (Thanh and De Smedt 2012).
Investigation of disasters using remote sensing techniques paved way for periodical monitoring and instant response during various disastrous events in both regional and global scale. Availability of various open access datasets and open source software’s helps in intensive investigation and analyse disaster events. There are several influential factors suggested by various authors Landslide Susceptibility mapping (LSM). Some of them are based on Fuzzy inference systems for ranking of suggested parameters. Mamdani Fuzzy interface system in Matlab is one of the method to derive Landslide Susceptibility Zone , using various topographical, geological and environmental inputs such as Altitude, lithology, slope gradient, curvature, NDVI, SPI and the model takes 351 data points as reference points of landslide assessment (Akgun et al 2012). Fuzzy member functions, for the purpose of pairwise ranking of Hazard susceptibility criteria, Analytical hierarchical processing system and list of criteria used in the study are Slope, Land use and Land Cover, Aspect, Distance to stream, Lithology, Distance to roads, Drainage density, Distance to fault and precipitation (Feizizadeh et al 2014).
Multicriteria Decision making system like Analytical Hierarchical Processing(AHP) and OWA (Overlay weighted analysis) are also used to do uncertainty analysis of LMS with parameters called Aspect, Distance to road, elevation and distance to stream, distance to fault, slope, land use, precipitation lithology (Bakhtiar et al 2013) and some other influential parameters were analysed (Saha et al 2002). On following these literature and with respect to the availability of data, nine of the parameters where selected area for the study. In Karnataka region, Migmatites and granodiorite, charnockite and very few areas of metabasalt and tuff about of lithology of Sakelspura. The study categorized Sakelespur under good and very good ground water potential zones and slope is also categorized under moderate to high and undulated terrain of Saklespur (Basavarajappa et al 2015).
Landslides are a natural process of earth’s life cycle that hits the mountainous regions frequently during monsoon period. Landslides are failure of land mass down the slope affecting landscapes intimidating human life, Flora, Fauna and non-natural structures under unpredictable climatic and lithological conditions (Shirani and Pasandi 2019). Lithology plays a major role in identification of landslide hazard zonation regions as the structure of the rocks and its parameters are directly related to the landslides. Geology is utilised as a major layer for landslide vulnerability analysis and for the present study the geology layer of 1:50000 scale is obtained from Geological Survey of India. Geology Map of Saklespur is composed of several minerals is shown in Figure 2a and they are classified into five divisions on following the flow of previous literature (Basavarajappa et al 2015) from very low to very high based on the percentage area is taken for the study. Rainfall is a primary catalyst for landslides as most of the landslide in India are triggered by rainfall during the monsoon season. INSAT 3D HEM Rainfall data is collected from MOSDAC website for the period of 1st June 2019 to 31st August 2019 and the average of the datasets are calculated and utilised in the present study. Rainfall data utilised in the present study is shown in Figure 2b.
Topography of a region plays a major role in landslide occurrence as regions that are flat never experience landslide whereas the varying topography subjected to the external parameters such as rainfall (Vaishnavi et al 2019) results in triggering landslides. Shuttle Radar Topography Mission Digital Elevation Model (SRTM DEM) of the study area is obtained from USGS earth explorer at a spatial resolution of 30m is shown in Figure 3a. SRTM DEM obtained is utilised in obtaining the slope angle of the region as shown in Figure 3b.
Slope angle is one of the primary factors to be considered in landslide hazard zonation mapping which is directly proportional to landslides. Slope angle integrated with the input parameters such as rainfall and geological parameters can aid in understanding and characterising the landslide events in updating the vulnerable zones. Aspect for the study area is developed using SRTM DEM as shown in Figure 4b and is also considered as an instability factor based on the slope face during rainfall, sunlight and blowing winds which directly influence the distribution of vegetation, evapotranspiration, thickness of soil and degree of saturation of water. Exhaustive investigation of the surface translations over the landslide prone region guides the government officials and researchers to serve the localities (Martha et al. 2017).
Surveyors experienced various challenges in monitoring and assessment of landslides using traditional surveying techniques such as tape and chain with arrows, pegs and ranging rods, plane table, etc. (Selvi 2012). Inaccuracy of results lead to the introduction of dumpy level, theodolite and total station in the field of surveying are time-consuming operations, which required technical manpower (Visakh et al. 2016). Introduction of space-based surveying helps surveyors to overcome the hurdles and monitor periodically (Geethapriya et al. 2018). Technological development over past decades encourages researchers understand landslide characteristics considering both geological and geomorphological parameters (Suresh et al. 2018).
Spatial distribution of land features and aspect are shown in Figure 4a and 4b where the land use categories directly influence the occurrence of landslides. Modifications to the natural features based on human requirements influence the landslides and one of the major human activities along the hilly regions that trigger landslides are deforestation. Land use/ land cover map for the study area is prepared with the aid of Sentinel 2 data with Bhuvan land cover map as reference. Roads are another artificially created parameter that trigger landslides. Roads are constructed along the slope of the hills to enable the movement of vehicles and supply the goods to the people located in the hill stations. Extraction and cutting of the slopes for the construction of roads results in loss of satiability along the slopes due to the vibration created by the flow of vehicles resulting in slope failure. Considering the scenario, a buffer zone is created based on the distance from the roads as show in Figure 5a for the preparation of hazard zonation map.
Streams play a major role in maintaining the slope stability by increasing the water level in the soil that results in slope instability due to erosion. Density of the stream defines the movement of water into the soil, higher the density of streams will have higher erosion leading to slope failure. In the present study drainage are obtained using DEM and the drainage density map is developed by using inverse distance weighting method as shown in Figure 5b.
Lineaments are linear feature in landscape that represents the underlying geological structure such as faults, folds, etc. Lineament density is prepared based on the density of lineaments using IDW method as shown in Figure 6. Lineaments are based on the geological aspects and more the lineament density in a region the possibility of occurrence of landslides are high. In the present the study, the layers collected are analysed and mapped using QGIS 3.10 LTR version for the identification of Landslide hazard zonation (LHZ) regions. Based on the previous research works, discussed in the literature section, these influential parameters are categorized into five, Very High, High, Medium, Low and Very Low. Percentage area of those five categories of influential parameters of the particular study area boundary are considered.