The rapid urbanization occurring globally has significantly intensified the challenges of waste management in densely populated metropolitan areas. A growing amount of waste has become a major concern for municipal authorities and local governments due to the limited availability of suitable land. Geospatial techniques, such as Geographic Information Systems (GISs) and remote sensing, combined with machine learning, play a crucial role in identifying suitable sites for urban waste management. These techniques assist planners in making well-informed decisions that strike a balance between environmental preservation and urban expansion by examining spatial data on land use, population density, and environmental concerns. Geospatial tools provide a data-driven basis for policy and urban planning, ensuring effective land use, reducing ecological hazards, and promoting sustainable urban growth for municipalities such as English Bazar and Old Malda. It can also pose serious threats to the environment, public health, and communities. Focusing on the English Bazar and Old Malda Municipalities in India, this paper examines the use of geospatial technologies to identify suitable sites for waste disposal. The research aims to address the complex processes of waste generation, collection, and disposal in urban environments. Using GIS and a Multi-Criteria Decision Analysis (MCDA) approach, the study employs the Analytic Hierarchy Process (AHP) alongside the Random Forest (RF) model and a machine learning (ML) technique to identify potential waste disposal sites within the English Bazar and Old Malda Municipalities in the Malda district. Eight key criteria were considered in the site selection process: land elevation; distances from surface water, roads, railways, and urban areas; groundwater depth; land use and land cover; and distance from sensitive and restricted areas. AHP analysis showed that 8%, 26%, and 27% of the sites were categorized as very highly suitable, moderately suitable, and unsuitable, respectively. Meanwhile, 38%, 17%, and 13% of the areas were classified as unsuitable, moderately suitable, and very highly suitable according to the RF model. The overall accuracy and Kappa coefficient indicated that the AHP method (overall capacity of 83.83% and Kappa coefficient of 0.7894) was slightly better than the RF model (overall capacity of 80.61% and Kappa coefficient of 0.7474) for site suitability analysis. This research underscores the broad relevance of geospatial technology in creating resilient and environmentally sustainable cities while offering valuable guidance on effectively allocating waste disposal sites. The findings provide crucial insights for urban planners and decision-makers, facilitating the identification of optimal locations for sustainable waste management in urban settings.

Food security is unquestionably crucial to society's well-being. The world is experiencing unprecedented global shocks; therefore, it is critical to protect the agri-food systems. This concept is broad and complex, with various interpretations around the globe. The problems of social equity, environmental sustainability, and food security are interconnected and are rarely best addressed separately. The failure to address the farming sector, particularly that of women farmers, is the basis of the current discussion. Creating sustainable food systems requires moving from an agriculture-centred to a food system policy and research framework. This will be fundamental to fostering the complex and holistic transformation necessary to achieve sustainable food systems, which is, in turn, a prerequisite to achieving sustainable food and nutrition security. Therefore, the current study aims to establish the link between women's empowerment and food security. The study used a systematic literature review approach based on secondary data available in relevant and contemporary literature. The findings showed the scarcity of research in areas of gender response to climate change and coping strategies and cultural biases against women.Moreover, most policies designed to improve and expand local communities’ capacity for adaptation are gender-neutral. Interdisciplinary research and innovation are likely to be the most effective methods for tackling food insecurity while considering its complex social, economic, and environmental components. The objective is to advance sustainable solutions. Therefore, in addition to academic thought, a focused approach to the issue is required; one must act following reality.

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.