Climate change impacts, the resulting spatiotemporal changes, and growing uncertainty exert pressure on city leaders and policy makers to create climate adaptive development strategies worldwide. This article introduces climate urbanism as a new development paradigm that advocates for a climate adaptive urban development process, safeguarding urban economics and infrastructure, and ensuring equitable implementation of related strategies. The objective of this article is to determine how far a climate vulnerable city in the Global South has progressed toward climate urbanism. The study employs Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines to develop a conceptual framework. Afterward, the analytical hierarchy process (AHP) and indexing are used to develop a multicriteria decision analysis (MCDA) method to assess the selected climate sensitive factors related to climate urbanism. Findings reveal that the city of Khulna’s climate urbanism index score is 0.36, which is extremely low and denotes subpar urban performance. ‘Climate Conscious Governance’ and ‘Climate Smart Infrastructure’ contribute little, while ‘Adaptive and Dynamic Urban Form’ and ‘Urban Ecosystem Services’ contribute even less. The binary logistic regression analysis reveals the significant indicators of (transformative) climate urbanism. The article provides a critical lens for stakeholders to evaluate climate urbanism and promote urban sustainability in the face of climate change.

Major cities of Bangladesh have been experiencing rapid urbanization and industrialization. These are incurring positive externalities to national economy at the expense of environmental degradation and deterioration of living environment. The ambivalent sequel of industrialization has made it necessary to study urban areas and monitor spatiotemporal changes to facilitate decision-making process regarding land use planning, resource distribution, priority setting for planning interventions. Thus, this study aims to classify land use land cover (LULC) of Narayanganj Sadar Upazila and detect spatiotemporal changes within the period of 2015 to 2020 using MLC algorithm based supervised classification method. To serve this purpose, sentinel-2 satellite imagery are used. The results derived from the study elicit an increase (24.14 acre) in industrial land in 2020 compared to 2015. Approximately 1,538-acres land transformed into built-up area in 2020. Decrease in vegetation (15.85%) and water body (7.65%) are also evident from the findings. The results of the study will be conducive to have an initial glimpse of the LULC changing trend in the study area due to rapid urbanization and thus, will be instrumental for performing further research.

This research intends to measure and characterize the level of rurality in the southwestern region of Bangladesh using an indexing approach from functional perspective. The findings of the study can be conducive for efficient decision making related to rural development policies and planning. Besides, operational delineation of administrative units, such as Unions and Wards, is essential for the formulation and effective implementation of evidence-based development initiatives. The study has utilized the latest available population census data published by Bangladesh Bureau of Statistics (BBS). The results reveal that Satkhira district exhibits a higher degree of rurality (RI = 4.23) compared to Khulna (RI = 3.58) and Bagerhat (RI = 4.14) districts. This variation among the three districts is ascribed to existing rural–urban disparities. The study underscores the primary influence of socio-economic factors on the rural–urban disparities, with a secondary role for demographic and infrastructural aspects. However, education's impact was notably limited in this context. Insights on intra-district disparities infer that Khulna district exhibits significantly greater rural–urban disparities than the other two. The study also highlights the clustering of non-rural areas along major rivers. This research will assist rural planners and policy makers in understanding the specific rural dynamics of the study area, essential for tailoring fit-to-context development strategies. Moreover, the study provides a basis for classifying the region into clusters to streamline development priorities and resource allocation. Furthermore, the article presents a transferable methodology for evaluating rurality and delineating rural regions in different contexts.