The transition from the Green Revolution to biomass-based energy in India is marked by ecological stress and institutional constraints. Punjab, a state pivotal to the food security of India, is confronting severe groundwater depletion and persistent stubble-burning challenges arising from increasingly compressed cropping cycles. Employing a mixed-methods framework, the study integrates Propensity Score Matching (PSM) for the estimation of income effects with Ethnographic Decision Modelling (EDM) to interrogate the socio-institutional logics underpinning ex-situ crop residue management (CRM) adoption. The PSM estimates indicate that adopters realize an income premium of INR 21,800 to 26,300 (USD 264 to 319) per hectare annually, with adoption mediated by access to extension services, institutional credit, asset ownership, and proximity to procurement centres. Ethnographic evidence further reveals that adopters prioritize timely field preparation, express dissatisfaction with in-situ alternatives, and value the presence of stubble collection facilities, while non-adopters report rigid sowing schedules, infrastructural deficits, and the normalization of burning as binding constraints. Survey responses indicate negligible divergence on broad policy instruments but pronounced differences on decentralized interventions. The viability of biomass management is contingent on local infrastructure, targeted incentives, and coordinated co-governance among the Union, state, and farmer unions, reconciling environmental objectives with social priorities.
This study provides a spatio-temporal analysis of urbanization and land-use efficiency in Assam, India (2000-2025) using Global Human Settlement Layer (GHSL) datasets. Evaluating SDG 11.3.1, we integrated the Land Consumption to Population Growth Rate (LCRPGR) with supplementary metrics: Achieved Population Density in Expansion Areas (AAPDEA) and Marginal Land Consumption per New Inhabitant (MLCNI). Findings reveal severe spatial heterogeneity and rising land-use inefficiency. Built-up areas expanded significantly - Kamrup Rural grew from 55.44 to 81.53 km2 -while population growth decelerated. Consequently, peripheral districts experienced uncoordinated sprawl. Goalpara's LCRPGR spiked from an efficient 0.76 (2000-2005) to a highly inefficient 5.37 (2020-2025). This sprawl is evidenced by precipitous density drops; Barpeta's AAPDEA plummeted from 78,650 to 12,170 persons/km2, and Goalpara's MLCNI reached an alarming 191 m2 per new resident. Conversely, the urban core, Kamrup Metropolitan, functioned efficiently, maintaining LCRPGR below 0.5 and consuming only 9 m2 of new land per added resident. These statistical disparities highlight a critical divergence between compact core development and fragmented peri-urban sprawl. To meet SDG 11.3 targets, this study emphasizes the urgent need for context-specific interventions, such as strict peri-urban growth boundaries, to halt inefficient land consumption
Regional development theory has long emphasized proximity, interaction, and territorial context, yet the built environment remains unevenly specified within its core conceptual frameworks. Traditions including industrial districts, clusters, regional innovation systems, learning regions, and entrepreneurial ecosystems all rely on spatial assumptions, but they often invoke broad territorial categories without adequately clarifying the material and institutional-spatial conditions through which economic interaction is organized. This paper argues for a more explicit treatment of the built environment within regional development theory. It develops an analytical framework organized around urban form, accessibility, land-use configuration, governance coordination, and the spatial organization of economic activity. The framework is used to examine Copenhagen and East London as analytically contrasting illustrative cases. The comparison shows that familiar regional development categories may refer to materially different spatial configurations: Copenhagen exhibits a more coordinated and distributed metropolitan structure, whereas East London is characterized by more selective concentration, redevelopment pressures, and fragmented governance. The paper contributes by positioning the built environment as a conditioning dimension of regional development rather than an external backdrop, and by offering a more precise basis for interpreting spatial variation across regional contexts.
The surface urban heat phenomenon and global warming share a mutual relationship, representing major environmental challenges of the 21st century. This study examines spatio-temporal variations of Surface Urban Heat Islands (SUHIs) in 16 major Iranian cities across different climatic regions to identify areas with intense surface warming and explore their relationship with urban characteristics. MODIS Land Surface Temperature (LST) data from 2001 to 2020 and Landsat-derived NDVI were used to assess vegetation cover. Temporal trends were quantified using the Mann - Kendall and linear regression methods, and Ward's hierarchical clustering classified cities based on SUHI intensity patterns. The results showed four and six main clusters during daytime and night-time, respectively. The Surface Urban Cool Island (UCI) effect dominated during the day, while SUHI prevailed at night. UCI mainly occurred in urban areas surrounded by barren lands in arid and semi-arid regions. LST trends confirmed UCI formation through decreasing daytime temperatures, while night-time SUHI exhibited higher temperatures at city centres. NDVI time-series analysis indicated minimal vegetation change during the 17-year period. Overall, the spatial pattern of LST across Iran is influenced by elevation, latitude, vegetation, and proximity to the sea under different climatic conditions.
