Assessing landslide vulnerability in Kohima city, Nagaland: A geospatial approach

Kohima located in the Eastern Himalaya of Northeast India experience numerous landslides and soil creeps annually. Landslides, the resultant of various interactions i.e., geological, geomorphologic, meteorological factors etc., caused immense loss economically and environmentally. Kohima city experiences the torrential amount of rainfall which further aggravate landslide hazard. This paper implores the use of high-resolution satellite data for deciphering landslide vulnerability mapping through remote sensing and GIS technique. Factors such as land use and land cover, lithology, lineament, drainage, road, aspect and slope were used as thematic input layers for landslide vulnerability mapping. The bivariate statistical method particularly Information Value method was used to extract the information from the landslide and the various controlling factors to generate the landslide vulnerability map. Validation of the landslide vulnerability mapping using classification and R-index methods along with ground observation were used to create the final vulnerability map.

Gis-based Gully Erosion Susceptibility Modelling, Adapting Bivariate Statistical Method and Ahp Approach in Gombe Town and Environs Northeast Nigeria

Gully erosion is a major environmental problem in Gombe town, large area of land is becoming unsuitable for human settlement, hence the need for gully erosion susceptibility map of the study area.To generate gully inventory map, detailed field exercise was carried out, during this investigation one hundred gullies were identified and studied extensively within the study area of about 550 km2. In addition to the mapped gullies, Google EarthPro with high resolution imagery was used to locate the spatial extents of fifty (50) more gullies. Ten gully erosion predisposing factors were carefully selected considering the information obtained from literature, and multiple field survey of the study area, the factors include: elevation, slope angle, curvature, aspect, topographic wetness index (TWI),soil texture, geology, drainage buffer, road buffer and landuse.In this study, a GIS-based Frequency Ratio (FR) and Analytical Hierarchy process (AHP) models were employed to predict areas prone to gully erosion in Gombe town and environs.The result obtained from FR shows that drainage, soil texture and slope have highest correlation with gully occurrence, while AHP modelrevealed that drainage buffer, soil texture, geology have high correlation with the formation of gully. Gully erosion susceptibility maps (GESM) were produced and reclassified into very high, high, moderate and low zones.The overall accuracies of both models weretested by means of area under curve(AUC) values and gully density distribution. FR and AHP model have AUC values of 0.73 and 0.72 respectively, the outcome indicates that both models have high prediction accuracy. The gully erosion density distribution values revealed that gullies are concentrated in the very high susceptibility class and it decreases towards the low class, Therefore the GESM produced using these models in this study area is reliable and can be used for land management and future planning

Regional-scale landslide susceptibility mapping using the weights of evidence method: an example applied to linear infrastructure

Large landslides are common in the gently sloping clay plains of the Saint Lawrence Lowlands of eastern Canada. These tend to occur along rivers carved into the marine soils deposited in the former Champlain Sea, which occupied the area roughly 10 000 years ago. This paper presents a landslide susceptibility model, developed at the regional scale using a bivariate statistical method: the weights of evidence method. The analysis considers the association of existing large landslides in a portion of the study area with key terrain features, such as ground elevation, flow accumulation in adjacent streams, soil type, soil thickness, and land use. The resulting model identifies three different levels of susceptibility: low, low to moderate, and moderate to high. These descriptors are related statistically to the probability of encountering existing large landslides within 500 m, 1 or 2 km, respectively. The model is tested along primary railway corridors and isolates 8% of the total length for further consideration of landslide hazard. Reconnaissance level air photo survey results further reduce the length of corridor with elevated susceptibility to 2% of the total length, thus focusing the application of additional resources to a very small proportion of the total inventory.

Landslide hazard mapping in Nepal: case studies from Lothar Khola (central Nepal) and Syangja district (western Nepal)

The present paper attempts to evaluate the present status of hazard mapping in Nepal and describes the case studies of landslide hazard mapping of the Lothar Khola (central Nepal) and Syangja district (western Nepal) by two different methods: 1. The rating method proposed in the Mountain Risk Engineering (Deoja et al. 1991), and 2. Bivariate Statistical method developed by the Institute of Aerospace Survey and Earth Sciences (ITC). The Netherlands (Van Westen 1997). The first method is a manual one and used to make hazard map of the Lothar Khola watershed while the second one is GIS based and was utilized to produce hazard map of the Syangja district. Potentially unstable slopes were mainly found on the slopes ranging from 26-40°, residual soil cover, and in areas underlain by the slate and phyllite. Interestingly the slope movement is high in the areas covered by forest in comparison to the cultivated slopes.