Information from the abstract
Rapid urbanization has intensified the urban heat island (UHI) effect in Southeast Asian megacities, necessitating effective nature-based solutions. This study evaluates the cooling capacity of diverse green spaces in Khung Bang Kachao (KBK), Thailand, by integrating Google Earth Engine (GEE), field vegetation inventories, and temperature monitoring across 20 plots representing three types: rehabilitation forest, agroforestry, and urban areas. Results demonstrate that mean LST varied significantly across green space types: rehabilitation forests achieved the lowest mean LST (33.86 °C), followed by agroforestry (35.19 °C) and urban areas (40.77 °C). Structural parameters (tree density, crown cover, height, species composition, and NDVI) correlated negatively with LST, with NDVI exhibiting the strongest correlation (r = −0.74). Multivariable modeling revealed NDVI as the sole significant predictor of LST reduction at 10 m and 30 m resolutions, highlighting NDVI as a stronger driver of LST reduction than other structural parameters. In temporal analysis (2020–2024), rehabilitation forest cover contracted sharply from 31.94% to 12.02% due to agricultural conversion, corresponding to lower NDVI and higher LST, potentially exacerbating the localized UHI effect. Furthermore, a weak correlation between LST and air temperature underscores the influence of built environment heat factors. The final model included only Month and Light Intensity. While NDVI indicates LST, satellite-derived LST alone cannot reflect air temperature, requiring both environmental and physical factors in urban heat management.
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Related topics: Urban Heat Island Mitigation · Urban Green Space and Health · Plant Water Relations and Carbon Dynamics
Thai researcher and institutional participation
Chayanit Homsin · Wirongrong Duangjai · Sapit Diloksumpun · Jamroon Srichaichana · Montathip Sommeechai · Kasetsart University · Thaksin University
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