Impacts of spatial explanatory variables on surface urban heat island intensity between urban and suburban regions in China

Abstract

ABSTRACTThe intensified thermal environment in suburban areas is raising wide concerns for human society and public health due to rapid urbanization. Although the satellite-derived surface urban heat island intensity (SUHII) is a commonly used indicator, it still needs to be determined the SUHII between urban and suburban areas due to the challenges in delineating their boundaries with changes. Thus, a comprehensive analysis of the spatial explanatory variables (SEVs) and SUHII among urban and suburban areas is highly needed. Here, using the long-term satellite observations, we analyzed the spatiotemporal patterns of SUHII in different temporal intervals (i.e. seasonal and diurnal) and the contribution of SEVs in urban and suburban areas. Our results indicate that SUHII shows predominantly increasing trend from 2012–2021 in cities of China. Despite the trends of SEVs (i.e. increasing/decreasing) being relatively consistent in both urban and suburban, the latter shows a higher proportion regarding the trends in various SEVs. Besides, the partial least squares regression (PLSR) model shows that the major contributors to SUHII in urban areas are landscape shape index (LSI), patch density (PD), and the digital elevation model (DEM), while in suburban areas, those critical SEVs are LSI, normalized difference built-up index (NDBI), and DEM. These findings can facilitate the sustainable design of urban planning in a nature-based solution.

Keywords

• Land surface temperature
• suburban areas
• urban landscape
• urban heat island
• time series