• "人居环境健康与GIS" •

### 植被与不透水面的降温和增温效率分析方法

1. 1. 福建师范大学地理科学学院,福州 350007
2. 福建师范大学地理研究所,福州 350007
• 收稿日期:2020-12-15 出版日期:2021-09-25 发布日期:2021-11-25
• 通讯作者: *张友水（1974— ）,男,安徽含山人,教授,主要研究方向为资源与环境遥感。E-mail: yzha5553@163.com
• 作者简介:李 玉（1995— ）,女,山西太原人,硕士生,主要研究方向为资源与环境遥感。E-mail: liyuedu@foxmail.com
• 基金资助:
福建省公益类科研院所专项(2019R1102);福建省自然科学基金项目(2018J01739)

### Cooling and Warming Efficiency of Vegetation and Impervious Surface

LI Yu1,2, ZHANG Youshui1,2,*()

1. 1. School of Geographical Sciences, Fujian Normal University, Fuzhou 350007, China
2. Institute of Geography, Fujian Normal University, Fuzhou 350007, China
• Received:2020-12-15 Online:2021-09-25 Published:2021-11-25
• Supported by:
Public Welfare Research Institutes of Fujian Province(2019R1102);Natural Science Foundation of Fujian Province(2018J01739)

Abstract:

Remote sensing based studies of urban thermal environment usually analyze the relationship among vegetation, impervious surface, and Land Surface Temperature (LST). Although the cooling effects of vegetation and warming effects of impervious surface have been widely recognized, quantitative studies on cooling and warming efficiencies are lacking. In this study, Land Surface Cooling Rate (LSCR) and Land Surface Warming Rate (LSWR) were used to quantify the cooling efficiency of vegetation and the warming efficiency of impervious surface, respectively. Taking the central urban area of Nanjing, Jiangsu Province in 2017 as the research area, Landsat 8 OLI remote sensing data of four dates were selected as the data source. Firstly, Linear Spectral Mixture Analysis (LSMA) was used to obtain Fractional Vegetation Coverage (FVC) and Impervious Surface Percentage (ISP). High-resolution Google earth images were used for precision verification. Then, with LST inversion results, the LSCR and LSWR of each season were calculated, and the influence of different LSTs on the LSCR and LSWR was analyzed. Finally, using a thresholding method, FVC and ISP were divided into four intervals of 0%~25%, 25%~50%, 50%~75% and 75%~100%. The LSCR and LSWR of each interval were calculated. On this basis, the changes of LSCR and LSWR of different intervals were analyzed. The results show that: (1) LST is positively correlated with the overall LSCR and LSWR. The cooling effect of vegetation and the warming effect of impervious layer are the strongest in summer, with LSCR being 5.6% and LSWR being 5.1%. (2) In summer, LSCR in every interval is positively correlated with FVC. When FVC is 75%~100%, LSCR reaches the maximum value of 7.5%. In addition, LSWR in every interval is negatively correlated with ISP in summer. When ISP is 75%~100%, LSWR reaches the minimum value of 2.4%. (3) In the future planning, the cooling effect of vegetation can best inhibit the warming effect of impervious surface when FVC is 0%~25% while ISP is 75%~100%, which is the best areal combination of vegetation and impermeable surface. The LSCR and LSWR analysis methods adopted in this study can select the best FVC and ISP intervals from the perspective of preventing the rise of surface temperature. Based on this, different cities can be compared with each other in the future. Considering the impacts of latitude, topography, climate, tree species, etc. on LSCR and LSWR, we can further explore the influencing factors and changing rules of LSCR and LSWR.