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Remote Sensing-Based Outdoor Thermal Comfort Assessment in Local Climate Zones in the Rural–Urban Continuum of eThekwini Municipality, South Africa
Remote Sensing-Based Outdoor Thermal Comfort Assessment in Local Climate Zones in the Rural–Urban Continuum of eThekwini Municipality, South Africa
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Remote Sensing-Based Outdoor Thermal Comfort Assessment in Local Climate Zones in the Rural–Urban Continuum of eThekwini Municipality, South Africa
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Remote Sensing-Based Outdoor Thermal Comfort Assessment in Local Climate Zones in the Rural–Urban Continuum of eThekwini Municipality, South Africa
Remote Sensing-Based Outdoor Thermal Comfort Assessment in Local Climate Zones in the Rural–Urban Continuum of eThekwini Municipality, South Africa

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Remote Sensing-Based Outdoor Thermal Comfort Assessment in Local Climate Zones in the Rural–Urban Continuum of eThekwini Municipality, South Africa
Remote Sensing-Based Outdoor Thermal Comfort Assessment in Local Climate Zones in the Rural–Urban Continuum of eThekwini Municipality, South Africa
Journal Article

Remote Sensing-Based Outdoor Thermal Comfort Assessment in Local Climate Zones in the Rural–Urban Continuum of eThekwini Municipality, South Africa

2023
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Overview
Due to the need to continuously monitor and understand the thermal environment and its socioeconomic implications, this study used remotely sensed data to analyze thermal comfort variation in LCZs, including along the rural to urban gradient of the eThekwini Municipality in KwaZulu-Natal province of South Africa. LCZs were mapped using multi-temporal and multi-spectral Landsat 8 and Landsat 9 data using the approach by World Urban Database and Access Portal Tools (WUDAPT), while thermal data were used to retrieve land surface temperatures (LSTs). Data for training classification of LCZs and accuracy assessment were digitized from GoogleEarth guided by knowledge gained and data collected during a field survey in March 2022 as well as pre-existing maps. LCZs were mapped using the random forest classifier in SAGA GIS software while a single channel algorithm based on band 10 was used to compute LST for different scenes. The LSTs were adjusted and further used to derive thermal comfort based on the Universal Thermal Comfort Index (UTCI) categories as an indicator for outdoor thermal comfort on the extremely low- and extremely high-temperature periods in the cool and hot seasons, respectively. LCZs were mapped with high accuracy (overall accuracy of 90.1% and kappa of 0.88) while inter-class separability was high (>1.5) for all LCZ pairs. Built-up LCZs dominate the eastern parts of the municipality, signifying the influence of the sea on development within the area. Average LST was coolest in the dense forest, open low-rise and water LCZs in the cool and hot seasons, respectively. The compact high-rise LCZ was the warmest in both the hot (36 °C) and the cool (23 °C) seasons. The sea sands were among coolest regions in both seasons due to their high water content, attributed to their high water table and close proximity to the ocean. There was no thermal stress during the cool season, while most areas recorded moderate to strong heat stress in the hot season. Some areas in the densely built-up LCZs recorded very strong heat stress in the hot season. The findings suggest that policies and strategies should enhance heat mitigation capacities in strong-heat-stress areas during the hot season. Municipal authorities and citizens must work together to build strategies to minimize temperature extremes and associated socioeconomic pressures. Urban development policies, plans and strategies should consider implications on the thermal environment as well as the value of conservation of LCZs with high-heat mitigation value such as dense forests and expansion of built-up LCZs with low-heat absorption levels such as open low-rise. The study was based mainly on remotely sensed temperatures with some ground data used to validate results, which may limit the assessment. Overall, the study provides insights towards achievement of global sustainable and climate-smart development targets.