Study on the Response Relationship between Urban Thermal Environment and Impervious surface distribution density at Multi-spatial Scale—Taking Beijing as an Example

Abstract

With the rapid development of urbanization, the natural landscape has been replaced by impermeable surfaces, which change the surface radiation, thermal characteristics and humidity of urban areas. Among these effects, urban heat island (UHI) is a phenomenon in which the atmosphere or surface temperature in an urban area tends to be higher than the surrounding environment. As the process of urbanization continues to accelerate, the UHI effect continues to intensify. Research and treatment of UHI effect play an important role in energy consumption, air quality, environmental health, etc. With the development of remote sensing technology, the impact of UHI is usually estimated based on thermal infrared remote sensing technology. Due to the convenient transportation and continuous coverage in urban areas, UHI has attracted more and more attention in recent decades. Land surface temperature (LST) derived from thermal infrared remote sensor is one of the most commonly used indicators in UHI analysis. An accurate representation of the temporal and spatial variation of UHI is a prerequisite for sustainable urban development. Therefore, studying the relationship between urban thermal environment and impervious surface is of great significance to further improve the quality of human settlements and control urban heat islands. In view of the insufficient research on the response law of urban thermal environment and the impervious surface distribution density (ISDD) in the past, this paper selected Beijing as a case study. Based on MODIS data, the average temperature difference between the urban construction area and the marginal area was calculated as the urban heat island intensity (UHII). In combination with the characteristics of UHII level, six typical regions with high expected value of UHII level were selected to study the response relationship between UHII level and ISDD. Finally, Landsat data was used to invert surface temperature to study the critical point and optimal scale of surface temperature response to ISDD in both urban construction areas and typical regions. The results showed that: (1) The frequency of occurrence of UHII levels, their variation degree during the day and night have a certain correlation with ISDD, and the variation characteristics of UHII under similar ISDD are similar. (2) The distribution characteristics of the surface mean temperature in urban construction areas and ISDD are obviously consistent. As the scale radius r increases, the response is more obvious. Besides, there are critical points for the response of the surface temperature to ISDD. The response of critical points gradually increases with the decrease of scale radius r. When the scale radius r=1000m, the ISDD reaches 60% and its influence tends to weaken; the critical points of r=500m, r=300m are 69% and 83%, respectively. (3) There are differences in the optimal scales of different typical regions. The optimal scale of Xierqi, Xisanqi, and Huilongguan is 150m, and that of Dongsi, Di’anmen, Xinjiekou and Qingqiao near the fourth ring is 60m. However, seasonal changes have little impact on the optimal scale. The optimal scale can measure the degree of fragmentation of impervious surface distribution in different regions and the single degree of surface type to some extent. This study can provide a reference for urban planning and urban heat island governance.