Quantifying urban cooling benefits with SDGSAT-1 nighttime light and thermal infrared data Long Ye(a,b), Tengfei Long(a,b)*, Weili Jiao(a,b),Elhadi Adam(c)
a)Aerospace Information Research Institute, Chinese Academy of Sciences (CAS), Beijing, China
b)University of Chinese Academy of Sciences, Beijing , China
* longtf[at]aircas.ac.cn
c)University of the Witwatersrand, Johannesburg 2050, South Africa
Abstract
Accelerating global urbanization and expanding impervious surfaces have intensified the Urban Heat Island (UHI) effect, posing significant challenges to urban livability and resident well-being. Leveraging the unique capability of China^s first Sustainable Development Science Satellite (SDGSAT-1) to acquire concurrent high-quality night-time Light (NTL) and thermal infrared (TIR) data, this study develops an innovative methodology for quantifying urban cooling benefits. We first construct a predictive model for Land Surface Temperature (LST) using a Random Forest (RF) model, with SDGSAT-1 NTL data (indicating human activity intensity) and Digital Elevation Model (DEM) data as key input features. Building upon this, we introduce the novel Cooling Benefit Index (CBI), defined as the difference between the RF-predicted LST and the actual LST derived from TIR data (CBI = Predicted LST - Actual LST). This index precisely quantifies the localized cooling capacity within urban areas. Empirical analyses across multiple representative cities demonstrate the method^s effectiveness in identifying and quantifying cooling benefits. Results show that maximum CBI values exceeding 2.2 Kelvin (K) are common, validating the index^s utility. Areas exhibiting high CBI values, indicating significant cooling benefits, are predominantly located at urban peripheries or in regions with substantial vegetation cover, effectively mitigating local UHI. Conversely, urban cores consistently display lower CBI values, reflecting pronounced UHI intensity and limited cooling potential. The spatially detailed CBI distribution maps accurately reveal the heterogeneous pattern of cooling benefits within cities. This research not only highlights the substantial potential of synergistic SDGSAT-1 NTL and TIR data for generating fine-scale urban thermal comfort maps and quantifying cooling efficiency, but also provides a robust scientific foundation and decision-making support for UHI mitigation strategies,
Keywords: Night-time light, Land surface temperature, Cooling benefit index (CBI), Sustainable Development Goal , Urban heat island
