Abstract
Although many prior studies have found that landscape pattern significantly affects urban heat environment globally, the spatially heterogeneous in the cooling effects of landscape pattern remains poorly understood. In addition, most previous studies have only employed a single landscape metric separately, without holistic consideration of the composition and configuration of different landscapes. Taking one of the new “stove” cities in China-Fuzhou City, Fujian Province, as an example, we employed the principal component analysis (PCA) to synthesize a landscape pattern comprehensive index (LPCI) composed of the four common landscape metrics (i.e., aggregation index, AI; mean patch area, Area mn; largest patch index, LPI; and percentage of landscape, PLAND) of the three major land surfaces (i.e., water, vegetation, and impervious surface). Then, the local model (geographically weighted regression, GWR) was proposed to explore the spatially heterogeneous in the cooling effects of urban landscape. The results revealed that: (1) from 2000 to 2016, the land surface temperature (LST) increased by 4.262 °C, and the proportion of the urban heat island region showed an upward trend, while the urban-heat-island ratio index (URI) increased from 0.328 to 0.457; (2) the cooling effect of different land surfaces ranked from high to low was: water (29.69 °C), vegetation (38.56 °C), and impervious surface (41.82 °C); (3) compared with vegetation patches, water patches had a more obvious cooling effect on the surrounding environment, with the cooling distance within 60–90 m for the vegetation, while reaching 120–150 m for water body; (4) the proposed LPCI could explain more than 80% of the information for all of the landscape metrics for all of the landscape types, and presented a patchy distribution in the study area; (5) the GWR results revealed that the cooling effect of the landscape pattern varied spatially across the study area, indicating that the configuration of landscapes is more important in an urban center in alleviating urban heat environment than in an urban fringe area. The proposed approach provides a new understanding of the interaction between the landscape patterns and urban heat environments, providing a strong basis for landscape planning strategies for specific local sites.
Highlights
China’s urbanization rate had reached 60.60% by 2019 [1]
This study revealed the relationship between land surface temperature (LST) and urban landscape pattern, so we can use this as an entry point to provide an effective way to reduce the urban heat island effects (UHI) effect for urban landscape design
This paper proposed a comprehensive index (LPCI) to evaluate landscape pattern and employed geographically weighted regression (GWR) to explore spatially heterogeneous in the cooling effects of the landscape
Summary
Urbanization changes the structure of a city’s underlying surface [2], combining with the heat emission from human activities, which lead to the phenomenon of concern, that is the well-known urban heat island effects (UHI) [3,4]. The UHI was defined as the surface temperature of urban areas and is significantly higher than that of suburban areas [5]. The tremendous heat generated by urban motor vehicles and human activities exacerbates such phenomena. The UHI can aggravate air pollution [6], result in extremely bad weather conditions (e.g., strong winds and storms), and seriously affect both the physical and mental health of people [7,8,9], and the quality of life of urban residents [5,10,11]. The cooling effects of landscape on the UHI have become a global research hotspot [12,13,14] to explore technologies and strategies for urban planners to alleviate urban thermal environment
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