The Gangtok subdivision in east Sikkim district was developed under different geographical, lithological, and historical conditions. This research aimed towards creating a landslide susceptibility zone with the help of two GIS models, namely AHP (analytical hierarchy process) and FRM (frequency ratio model), used for landslide susceptibility mapping and make a comparison in accordance with their outputs. Primary data like the landslide location was collected by using the GPS technique and BHUVAN landslide inventory, while, photographic data were collected from various satellite images and theme-based images from BHUVAN, ENVIS, and Earth Explorer. Other secondary data were collected from the Survey of India (SOI), National Bureau of Soil Survey, Geological Survey of India, NRSC, India, and land use planning (NBSS&LUP), Census of India and Indian Meteorological Department. Eleven thematic layers including landslide inventory, rainfall, lithology, geomorphology, slope, aspect, curvature, distance from lineament, distance from the road, distance from drainage, and land use/land cover, were considered for the FRM method and the AHP method. AHP map captures 80% of the active slides in the very high to the high susceptible zones in comparison to the 75% active slide capture by the FRM method in the very high to high susceptible zone. For validation and comparison of the model output, the receiver operating curve (ROC) was applied to 30% cases out of the 100% of total landslides (92 landslide locations were marked). AHP method was found out to be the best among the two models with a 98% accuracy level. The risk mapping was done by integrating exposure map with hazard map along with physical vulnerability map of the study area. Through risk mapping it is seen that the eastern section of the study area has the least risk but on the contrary, the western zone is the riskier zone for landslide hazard. There has been also an attempt to find out plausible methods for landslide disaster management and mitigation for the study area.

Morphometric analysis is the mathematical analysis of a watershed. Groundwater storage is directly related to the morphometry of a watershed. Remote sensing and GIS gives an opportunity for the scientific and empirical investigation towards groundwater potentiality. The utilization of RS/GIS for scientific investigation into ground water potentiality is quite innovative for the hilly state of Mizoram of India, which faces acute water shortage during the winter season. Vanvate Lui basin of Mizoram was thus chosen for the present study. It is an important source of water for a significant number of rural villages like Zote, Chhipphir, and Lungmovi. The present study analyzed the groundwater potentiality of Vanvate lui basin and undertook groundwater potentiality zonation of Vanvate lui basin using eTOPSIS model. eTOPSIS is an intregated knowledge-based multi-criteria decision-making model assimilating TOPSIS objective weighting method and Shannon Entropy. Areal, relief and linear morphometric aspects of Vanvate lui basin were extracted from ALOS PALSAR DEM for conducting MCDM. It was found that sub-basins 1, 6, 8 and 2 have high potentiality for groundwater storage. Similar, studies were also done on the Donor basin adjacent to the study area for model validation. After applying e-TOPSIS in the Donor basin, it was found that the result of the study matches the groundwater data of Donor basin as provided by the PHE department, Mizoram. The zones found to be under high potential of groundwater in the sub-basins 14, 9, 2, 11, 6 and 5 are the ones where the ground water depth is less than 70 meters as measured by the ground water department of Mizoram state. The present study will help the policymakers, village governance system, district development authorities and P.W.D of Mizoram to take proper steps towards developing the rural life quality, identifying suitable groundwater storage and ensuring proper steps towards watershed management. It is hoped that the research work will help in mitigating the water scarcity problem of the study area during the dry winter season.

Ecotourism is becoming more and more significant because it aids in environmental protection and maintaining the sustainable growth of a region. Mizoram is known for its potentially varied landscapes, which draw visitors from many nations and territories. The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) approach was used in this study to evaluate land suitability for ecotourism initiatives in Mizoram spatially. The study also focused on role weighting (subjective, objective, and intergraded) on the decision-making process. In this regard, the weightage of twelve ecotourism influencing factors was determined to integrate with the TOPSIS model and the Geographical Information System (GIS) environment. As a result, five hierarchical ecotourism zones, including very high to very low, have been classified using Jenks’s natural breaking classification. The model’s accuracy based on the area under the curve (AUC) and receiver operating characteristic (ROC) curve revealed that all models successfully predict potential ecotourism in the marginal hilly region. As a result, the intergrade weighting combined TOPSIS model showed that 25.18% of the study region has very highly suitable for ecotourism. The results of this study may be used as a foundation for assessing the feasibility of resources suitable for ecotourism development by government officials and planners.

The current study introduced Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to enhance landslide susceptibility. It determines the relative distance of each alternative from the ideal best and ideal worst value. The ArcGIS environment was used to prepare eleven landslide conditioning factors, while raster values were extracted for the decision matrix preparation. We utilized subjective expert judgment to create a weighted matrix that considers the roles of each conditioning component. In addition, a Euclidean distance was measured from each alternative to the ideal best and worst values. The relative closeness value (R_i) has been used to prepare the landslide susceptibility index by the inverse distance weighting (IDW) interpolation. Furthermore, the precision of the landslide susceptibility was justified by area under curve-receiver operating characteristic (AUC-ROC) which was 0.987. Hence, multi-criteria decision-making (MCDM) techniques like the TOPSIS method are very useful for natural hazard mapping.

Champhai, the rice bowl of Mizoram, is known for wet rice practices. Rapid urbanization and global climate change increased the demand for groundwater. Champhai city, being a hilly township in northeast India, is very difficult to identify the potential groundwater water availability. The present study aimed at groundwater potentiality zonation in Champhai town. For these purposes ten (10) factors from topographic, climatic, hydrological and other conditions were assigned weightage based on the AHP (analytical hierarchy process) technique. The aspect was given maximum weightage as the aspect working as the controlling factors of precipitation intensity, vegetation and soil type, while LULC (land use land cover) was assigned minimum weightage that unscientific human activities reduced infiltration rate. Subsequently, an addition of ten weighted rasters was performed for groundwater potentiality zonation. As a result, it was seen that the maximum part of the study area covered low potentiality zones (31.88%), whereas high and very high potential zone covered 14.73% and 5.08, respectively. A scientific validation technique, namely AUC (area under curve) value of 0.737, denoted a good classified groundwater water potentiality zone. Further, the single-layer sensitivity analysis highlighted that elevation, slope, aspect, infiltration number, distance to streams and rainfall had the maximum effective factors based on their effective weightage. The map removal sensitivity analysis highlighted that TWI (Topographic Wetness Index) and aspect had the maximum influence on the model. However, in a hilly environment like Champhai, the output of the current study will work as a blueprint for planning and decision making.