Members’ Publication

Small and medium-sized businesses have the potential to make a significant contribution to Bangladesh's overall economic development, both in alleviating poverty and contributing to the country's GDP. The present study aims to investigate the causes and consequences of poverty, identify suitable small- and medium-sized industries, and select appropriate sites for the development of such industries, using Chatmohor in Pabna district as a case study. This study utilized descriptive statistics, multilinear regression, binary logistic regression, rank-based quotient, Analytical Hierarchy Approach and the Multi-criteria decision analysis method. PRA, FGD, and KII are also the instruments that were used in the process of primary data collection. The study shows 80% of respondents live below extreme poverty, with 37.5% never attending school and 5.2% reaching undergraduate level. With a less than 0.05 p-value, two factors, unemployment and unstable economic conditions found to be significant in affecting mental health. Using AHP, weights of 55.79%, 26.33%, 12.19%, and 5.69% were assigned to growth centres, Land Use Land Cover, rural markets, and slope, respectively. Using this weight Multi-criteria Decision analysis identified most of the suitable land for industry, such as right near the Chatmohor railway station, Shitllai Zaminadar house near Natore National Highway, and Mulgram. The study's findings indicated that agro-processing companies in the region are crucial to the local economy, as a wide variety of agricultural products are readily available. This study enables stakeholders to make informed decisions about industries, promoting economic prosperity, thereby contributing to sustainable growth and achieving the goal of poverty alleviation.

Coastal regions of the Global South, particularly rapidly urbanizing areas like Chattogram, Bangladesh, face significant ecological deterioration requiring long term geospatial assessment of ecosystem service value (ESV) dynamics. This study employed an integrated methodology combining random forest classification of Landsat imagery (2000 to 2020), the Patch-generating Land Use Simulation (PLUS) model for prediction (2040 and 2060), and the Geographical Detector Model (GDM) to analyze land use and land cover change drivers. Historical classifications demonstrated high accuracy with Kappa Coefficients ranging from 0.81 to 0.88. The PLUS model showed strong predictive robustness with low error metrics for waterbody (RMSE 0.08) and vegetation (RMSE 0.09). Findings reveal intense urbanization: settlement areas rose from 5.35% in 2000 to 25.07% in 2020. Under business-as-usual trajectories, settlements are projected to reach 33.65% by 2060, driving vegetation decline from 73.52 to 41.28%. This transformation correlates with a projected 43.85% decline in vegetation ESV. Although settlement ESV is projected to increase to $1397.75 million by 2060, this compensates for only three service indicators compared to 21 provided by vegetation. Analysis identified slope (Power of Determinant 0.512), proximity to railway (0.480), and Digital Elevation Model (0.390) as significant ESV drivers. Sensitivity analysis confirmed ESV reliability, and Monte Carlo simulations bounded overall ESV decline from $5206 million (2000) to $4821 million (2060). These results underscore critical trade-offs between urbanization and ecosystem services, demanding immediate policy revisions to implement mandatory green buffer zones along railway corridors and strict protection zoning for hills to achieve sustainable urban planning and ecosystem management.

This chapter examines the mismanagement of Common-Pool Resources (CPRs) in the Halti Beel area, focusing on environmental degradation, resource depletion, and conflicts. Employing Participatory Rural Appraisal (PRA) methodology, the research aims to assess current CPR extraction, engage the community, and empower locals for sustainable resource management. Various participatory tools such as social and resource mapping, transect walks, mobility mapping, dream mapping, and SWOT analysis are utilized to collect data and engage the community in resource management. The study examines conflicts within the Halti Beel community that stem from resource extraction. Using resource mapping and historical analysis, it uncovers contradictions among community members. It highlights Halti Beel’s ecological importance, emphasizing its diverse biodiversity, and addresses the challenges of managing shared resources, particularly land, water, and fisheries. The study reveals conflicts between farmers and fishermen, issues with land acquisition, wetland management, and implications of over-exploitation. Factors contributing to degradation include corruption, bird-killing, improper fishing methods, and a lack of employment opportunities. Recommendations include community engagement, negotiation, localized management, and better regulation implementation. Policy suggestions involve environmental and participatory governance and time-bound resource use agreements. The study underscores the importance of managing resource consumption for sustainable development, especially in addressing over-exploitation in developing countries like Bangladesh. It serves as a baseline for future conflict management efforts related to Common-Pool Resource degradation.

Medium-sized coastal cities in deltaic environments face unique urbanization challenges constrained by fluvial erosion and climate hazards, yet remain underexplored compared to major metropolitan regions. This study addresses this gap by quantifying the spatiotemporal interplay between urban expansion and population dynamics in Barishal, Bangladesh, a climate-vulnerable coastal city where physical constraints fundamentally shape growth patterns. Using Landsat 5 and 8 imageries with sensor-specific NDBI thresholding validated through Otsu and ROC methods, combined with gridded population data from WorldPop, this study analyzed urban development patterns from 2000 to 2020. Built-up area increased from 198.05 km² to 241.49 km², while population rose from 366,284 to 433,623, with classification accuracy exceeding 89.8% (Kappa > 0.80) across all periods. Land consumption ratio declined substantially between 2000 and 2010 during severe riverbank erosion episodes, with negative UE/GLCR ratios in 2005–2010 and 2015–2020 indicating densification patterns amid constrained horizontal growth. These findings reveal how environmental barriers drive alternative urban growth forms, informing critical policy needs for urban growth boundary controls, zoning overlays for erosion-vulnerable zones, and infrastructure resilience planning. This research provides evidence-based spatial and demographic essential for sustainable urban planning in hundreds of similarly constrained deltaic cities worldwide facing intensifying climate pressures.