Simultaneous Analysis of Future Canopy and Surface Urban Heat Island Effects and Their Risks Under SSPs-RCPs Scenarios

Abstract

  The Urban Heat Island (UHI) phenomenon, characterized by higher temperatures in urban areas compared to surrounding rural areas, has been documented for over two centuries. Integral to the dynamics of urban socio-ecological systems, UHIs represent a prominent environmental repercussion of anthropogenic activities. As one of the most noticeable and concerning consequences of human activities within urban socio-ecological systems, UHIs significantly impact public health and economic development. This phenomenon serves as a quasi-experimental design, offering insights into the potential impacts of urbanization. Although previous studies have utilized remote sensing and ground monitoring technologies to observe UHIs globally and in various regions, little research has focused on the future patterns and risks of UHI intensity and its changes under socio-economic and climate change scenarios. In our study, we first quantified Beijing's UHI intensity at a 1km resolution using seamless near-surface air temperature and surface temperature data, 30 m land-cover data with a fine classification system (GLC_FCS30), and topographic information, employing the simplified urban extent algorithm. We then developed a predictive model for UHI intensity using the Extreme Gradient Boosting (XGBoost) algorithm, trained with 2020 data on land use types, landscape patterns, population, and topography. Finally, using the patch-generating land use simulation (PLUS) model, we simulated future land use in Beijing from 2020 to 2100 under four SSPs-RCPs scenarios (SSP 1-RCP 2.6, SSP2-RCP 4.5, SSP3-RCP 4.5, and SSP 4-RCP 6.0), and projected the corresponding UHI intensities. We also analyzed the potential risks of UHI by considering the level of population exposure. Our results indicate that, compared to the baseline level of 2020, Beijing's overall UHI level is expected to rise under any scenario, with a more significant increase in the area affected by UHIs, especially in the urban expansion scenario of SSP 4. Due to the considerable projected decline in China's future population, the number of people affected by UHI and the overall risk of UHI in Beijing shows a decreasing trend. However, the proportion of the population affected by higher degrees of UHI is gradually increasing. Our study not only identifies the characteristics of changes in UHI intensity and risk under different future scenarios but also provides insights for future urban planning and climate-economic goal setting by identifying key areas, thereby aiming to minimize the impact of localized climate change on urban residents.