The current study intended to geospatially analyze the potentiality and site suitability of geo-ecotourism in West Bengal, India. The state of West Bengal is a great platform for diverse tourism and has enormous potential to cultivate geo-ecotourism, as has come up in recent years. The current effort throws some valuable light on the possibility of turning the many geologically, geomorphologically and ecologically significant tourist spots of West Bengal into geo-ecotourism sites, aided with geospatial techniques. The study deals with the qualitative and quantitative investigation of the potentiality of the whole state by dividing it into several geo-ecotourism zones, based on its physiographic setting and Land Use Land Cover (LULC) features, using satellite image data. The application of geospatial technology combined with Remote Sensing (RS) and Geographic Information System (GIS) was employed for this geospatial analysis to portray the potential zones using cartographic and statistical techniques. Furthermore, nine criteria were selected to run the Analytic Hierarchy Process (AHP) method to determine the site suitability for geo-ecotourism. The present submission attempts to record the mapping and analysis of geo-ecotourism of West Bengal employing a secondary database, an expert’s opinions and primary observations, with the application of the AHP method and GIS. The outcomes of the study were found to be very significant, as they indicate a proviso for geo-ecotourism development in the state and will contribute to the formation of location-specific planning and the sustainable management of geo-ecotourism.

The world’s largest mangrove ecosystem Sundarbans lies in the southwestern part of the Ganges-Brahmaputra Delta. The health, function, and ecosystem services of the mangrove forest depend on the availability of freshwater flow within the deltaic system. The rivers, which used to feed the delta and nourish the mangrove ecosystem now stand disconnected from their upstream freshwater sources. The unavailability of freshwater restricts the growth of freshwater-loving mangroves and has the potential to affect the health of the existing mangroves limiting their ability to provide ecosystem services. Due to the high salinity, the natural reproduction of these valuable freshwater-loving floral species gradually got ceased. High salinity is considered a stress factor influencing the health, growth, productivity, and distribution of mangrove plants. In this circumstance, the main objective of the study is to monitor the spatiotemporal change of the mangrove ecosystem of Sundarbans in terms of species assemblage, floral diversity, biomass, canopy cover, forest health, etc. Remote sensing techniques and field measurements were used to perform an in-depth mangrove genus-level classification (Maximum Likelihood Classifier). To assess the plant species diversity, Shannon-Wiener Index was used in different plots of the Sundarbans to get an idea of the rich biodiversity of these coastal ecosystems. Different vegetation indices such as NDVI, OSAVI, SAVI, TDVI, etc. were estimated to assess the health of the mangrove forest. The biomass and carbon sequestration potential of the mangrove forest was assessed using field data and microwave remote sensing techniques. The result shows the declining trend of freshwater-loving mangroves from the central section of Sundarbans and an increasing trend of saline water-loving mangroves by replacing the others.

Floods, while contributing to soil fertility and agricultural productivity in low-lying deltaic areas and floodplain regions, remain one of the most destructive natural hazards, posing significant risks to human life, property, the economy, and the environment. The annual occurrence of floods in the lower Dwarkeswar River Basin highlights the critical need for flood risk assessment to support effective risk reduction policies. This research employs the analytical hierarchy process within a geographic information system environment to evaluate flood risk, with a focus on Ghatal CD Block in West Medinipur, West Bengal. By integrating flood hazard elements and vulnerability indicators, a comprehensive risk map is developed, delineating high-risk zones such as Ghatal, Erpala, and Mansuka, as well as low-risk areas like Birsingha, Sultanpur, and Dewanchak. In the present study, the flood hazard map was validated using AUC curve, achieving an accuracy of 75%, incorporating data from primary surveyed flood locations (n = 42) within the study area. These ground truth points played a crucial role in assessing the hazard map’s precision. The study extends beyond mere hazard identification, recognizing the importance of vulnerability assessment in understanding the holistic risk landscape. The findings indicate that 36% of the study area falls within high to very high-risk zones emphasizing the necessity of targeted interventions and mitigation strategies. Ultimately, this research contributes to advancing flood risk assessment methodologies and reinforces the importance of informed decision-making in mitigating the multifaceted challenges posed by floods, thereby enhancing disaster resilience and preparedness.

The Indian Sundarbans, a UNESCO world heritage site, is a unique mangrove landscape that supports millions of livelihoods and plays a crucial role in carbon sequestration. Carbon sequestration is a vital ecosystem service provided by nature. The study area under investigation has been formed through the Ganges river sedimentation, and the area is also part of the Holocene delta. Carbon sequestration, being identified as a critical regulating service, plays a significant role in attenuating the impact of climate change. Considering this fact, the study assesses carbon sequestration in the Sundarbans Biosphere Region (SBR), India, using a non-GIS-based InVEST model to estimate carbon values for 1990, 2000, 2010, and 2020, and projects future values for 2030, 2040, and 2050 by integrating land use changes with the Markov model. Carbon sequestration potential varies significantly across landscapes, with the maximum observed in mangrove forests (2828.97 metric tonnes) and the minimum in water bodies. Social carbon cost value is also calculated following IPCC guidelines. Temporal changes show a shifting distribution of high carbon values in the Sundarbans mangrove region. Application of spatial autocorrelation with Moran’s, I and hotspot analysis show a clustering of carbon-sequestered zones around the core mangrove areas and human-influenced cold spots in surrounding zones. The findings underscore the Sundarbans' vital role in carbon absorption and the need for sustainable management practices to maximise this ecosystem service for future carbon sequestration.