Land Surface Temperature Variation and Major Factors in Beijing, China Rongbo Xiao, Qihao Weng, Zhiyun Ouyang, Weifeng Li, Erich W. Schienke, and Zhaoming Zhang Abstract urban atmosphere, and is a primary factor in determining Land surface temperature (LST) is a significant parameter in surface radiation and energy exchange, the internal climate urban environmental analysis. Current research mainly of buildings, and human comfort in the cities (Voogt and focuses on the impact of land-use and land-cover (LULC) on Oke, 1998). The physical properties of various types of LST. Seldom has research examined LST variations based on urban surfaces, their color, the sky view factor, street the integration of biophysical and demographic variables, geometry, traffic loads, and anthropogenic activities are especially for a rapidly developing city such as Beijing, China. important factors that determine LSTs in the urban envi- This study combines the techniques of remote sensing and ronments (Chudnovsky et al., 2004). The LST of urban geographic information system (GIS) to detect the spatial surfaces correspond closely to the distribution of land-use variation of LST and determine its quantitative relationship and land-cover (LULC) characteristics (Lo et al., 1997; with several biophysical and demographic variables based on Weng, 2001 and 2003; Weng et al., 2004). Each compo- statistical modeling for the central area of Beijing. LST and nent surface in urban landscapes (e.g., lawn, parking lot, LULC data were retrieved from a Landsat Thematic Mapper road, building, cemetery, and garden) exhibits unique (TM) image. Building heights were delimited from the shadows radiative, thermal, moisture, and aerodynamic properties identified on a panchromatic SPOT image. The integration of and relates to their surrounding site environment (Oke, LULC and census data was further applied to retrieve grid- 1982). The myriad of these component surfaces and the based population density. Results indicate that the LST pattern spatial complexity when they are mosaicked create a was non-symmetrical and non-concentric with high tempera- limitless array of energy balance and microclimate sys- ture zones clustered towards the south of the central axis and tems (Oke, 1982). To study urban LSTs, some sophisticated within the fourth ring road. The percentage of forest, farm- numerical and physical models have been developed. land, and water per grid cell were found to be most significant These include energy balance models (Oke et al., 1999; factors, which can explain 71.3 percent of LST variance. Tong et al., 2005), laboratory models (Cendese and Monti, Principal component regression analysis shows that LST was 2003), three-dimensional simulations (Saitoh et al., 1996), positively correlated with the percentage of low density built- Gaussian models (Streutker, 2003), and other numerical up, high density built-up, extremely-high buildings, low simulations (Yang et al., 2003). Among these models and buildings per grid cell, and population density, but was simulations, energy balance models are by far the main negatively correlated with the percentage of forest, farmland, methods, but statistical analysis may play an important and water bodies per grid cell. The findings of this study can role in linking LST to related factors, especially at larger be applied as the theoretical basis for improving urban scales (Bottyán and Unger, 2003). Previous studies have planning for mitigating the effects of urban heat islands. focused primarily on biophysical and meteorological factors, such as built-up area and height (Bottyán and Unger, 2003), urban and street geometry (Eliasson, 1996), Introduction LULC (Dousset and Gourmelon, 2003), and vegetation Land surface temperature (LST) is an important parameter (Weng et al., 2004). A less number of studies, however, in study of urban thermal environment and behavior. have examined how population distribution influences LST modulates the air temperature of the lower layer of urban heat island (UHI) intensity, although it is apparently an indicator of anthropogenic heat emission (Fan and Sailor, 2005) and the intensity of human activities (Elvidge et al., 1997). Rongbo Xiao is with the National State Key Lab of Urban and Little research effort has been made to study the intra- Regional Ecology, Research Center for Eco-Environmental urban variations of LST and their related biophysical and Sciences, Chinese Academy of Sciences, Beijing, China socioeconomic variables within a city. The combination ([email protected]). of biophysical and socioeconomic data for urban studies Zhiyun Ouyang and Weifeng Li are with the National State has been hampered by the spatial unit problem, because Key Lab of Urban and Regional Ecology, Research Center for the relevant spatial units for biophysical processes are Eco-Environmental Sciences, Chinese Academy of Sciences, different from the spatial units for population and other Beijing, 100085 China. Qihao Weng is with the Department of Geography, Geology, and Anthropology, Indiana State University, Terre Haute, IN. Photogrammetric Engineering & Remote Sensing Erich W. Schienke is with the Department of Science and Vol. 74, No. 4, April 2008, pp. 451–461. Technology Studies, Rensselaer Polytechnic Institute, Troy, NY. 0099-1112/08/7404–0451/$3.00/0 Zhaoming Zhang is with the China Remote Sensing Satellite © 2008 American Society for Photogrammetry Ground Station, Chinese Academy of Sciences, Beijing, China. and Remote Sensing PHOTOGRAMMETRIC ENGINEERING & REMOTE SENSING April 2008 451 socioeconomic data (Yuan et al., 1997). Recent significant on LULC, LST, and building heights will be extracted from advances in the data and technological integration between remote sensing data. Grid based population density will remote sensing and GIS suggest that the integration is a then be computed by integrating LULC and census popula- powerful and effective tool in urban studies. Remote tion. Statistical analyses will explore how the LST variation sensing from airborne or satellite platforms cannot only to be a function of the biophysical and demographic provide thermal infrared data, but also LULC, building variables. This analysis would provide useful information height, and other urban biophysical variables. GIS technol- for designing measures to effectively mitigate the UHI ogy provides powerful capability for entering, analyzing, effects and thus improve the thermal environment of and displaying digital data from various sources and Beijing. formats. In order to gain a deeper insight into urban thermal behavior and climate, more research is needed to explore LST’s relationship with various biophysical and socioeconomic variables using an integrated remote Study Area sensing and GIS approach. Moreover, this integration may Beijing, one of the largest cities in the world, covers app- help serve to bridge the gap between scientific studies of roximately 16,800 km2 with a population of 13 million urban climate and their applications in planning and people. It is the political, cultural, and communication environmental management. center of China, and has a history of more than 3,000 Beijing, the capital of China, has experienced a rapid years as a city and more than 800 years as a capital city. urban expansion over the past two decades. Accelerated It has been selected as the site of 2008 Summer Olympic urban development and lack of appropriate planning Games. Over the past two decades, Beijing has undergone measures have created serious impacts on its thermal significant LULC changes characterized by accelerated environment. It is found that air temperature UHI effect urbanization. The development pattern is typically a in Beijing became more evident, where average daily air concentric expansion, which forms an obvious ring-shaped temperature in the urban area was 4.6°C higher than that pattern from the inner center to the outskirts. Our study in the suburban area (Song and Zhang, 2003). Existing area focuses within the fifth-ring road, where the majority UHI studies in Beijing have been focused primarily on the of built-up takes place. This area occupies 666.7 km2 temporal dynamics of air temperatures. Further analysis comprised by nine counties and 120 townships. Beijing of the spatial patterns of its LST and the contributing resides on a plain, with the elevation at approximately factors is urgently needed. In this study, we combine 100 m above mean sea level. It is located in the temperate remote sensing and GIS to analyze the spatial pattern of climatic zone, and has a mean annual temperature of LST and explore the factors that have contributed to the 12°C, and an average annual precipitation of 640 mm. LST variations. Considering the study area’s unique geo- The study area was divided into 1000 m ϫ 1000 m grids graphical setting and data availability, this study identifies (Figure 1) in order to compute grid-based population potential explanatory variables from LULC, building heights density and to conduct data integration for statistical distribution, and population density. The information analysis. Figure 1. Location of the study area. 452 April 2008 PHOTOGRAMMETRIC ENGINEERING & REMOTE SENSING Data and Methods The at-surface reflectivity was calculated with the following equation (Chavez, 1996): Data Used Five primary data sources were employed in this study: p(L Ϫ L )d2 r ϭ sat p (2) (a) Beijing 2000 census data by township, (b) a Landsat-5 TM surf E cosu T scene acquired on 31 August 2001, which