Land surface temperature and human thermal comfort responses to land use dynamics in Chittagong city of Bangladesh

Intense urbanization alters the microclimate and ecology of cities by converting naturally vegetated and permeable surfaces into impervious built-up surfaces. These artificial impermeable surfaces re-balance the surface energy budget by storing solar heat due to their higher thermal conductivity, and consequently, increase the Land Surface Temperature (LST). The higher LST affects the city dwellers' Human Thermal Comfort (HTC). To address these issues, unlike most prior research, we assess not only the influence of Land Use and Land Cover (LULC) alterations on summer LST but also on winter LST in Chittagong City of Bangladesh between 1993 and 2020 by using Remote Sensing (RS) and Geographic Information Systems (GIS). Additionally, the study evaluates the impact of LULC changes on the HTC during summer as LST substantially affects HTC in summer. The LULC analysis shows an increase in built-up area by 204% from bare lands, vegetated lands, lowlands, and water bodies between 1993 and 2020. In contrast, bare lands were converted from naturally vegetated surfaces, followed by lowlands and water bodies because of anthropogenic activities. The LSTs of Chittagong city, derived from remote sensing data, show a strong upward trend, with summer (winter) ranges of 20.62-34.07 degrees C (7.50-27.52 degrees C), 22.82-37.62 degrees C (14.92-29.32 degrees C), and 22.32-43.52 degrees C (17.08-31.83 degrees C) for 1993, 2007, and 2020, respectively. Between 1993 and 2020, the spatial mean winter and summer LSTs increased by 4.04 degrees C and 6.45 degrees C, respectively, or 0.15 degrees C and 0.24 degrees C per year. Chittagong had the highest mean LST in built-up areas for all the years. In addition, the study area's HTC gradually shifted to intense heat stress. The summer LST strongly correlated with normalized difference vegetation index (NDVI), normalized difference built-up index (NDBI) and normalized difference water index (NDWI) while winter LST exhibited poor correlation with these indices.