HR: 0800h
AN: B21A-0029    [Abstracts]
TI: A Volume Model for Urban Heat Island Based on Remote Sensing Imagery and Its Application: A Case Study in Beijing
AU: * Zhou, J
EM: zhouji@ires.cn
AF: State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Xinjiekouwai Street, Beijing, 100875, China
AU: * Zhou, J
EM: zhouji@ires.cn
AF: College of Resources Science and Technology, Beijing Normal University, Xinjiekouwai Street, Beijing, 100875, China
AU: Chen, Y H
EM: cyh@ires.cn
AF: State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Xinjiekouwai Street, Beijing, 100875, China
AU: Chen, Y H
EM: cyh@ires.cn
AF: College of Resources Science and Technology, Beijing Normal University, Xinjiekouwai Street, Beijing, 100875, China
AU: Li, J
EM: lijing@ires.cn
AF: State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Xinjiekouwai Street, Beijing, 100875, China
AU: Li, J
EM: lijing@ires.cn
AF: College of Resources Science and Technology, Beijing Normal University, Xinjiekouwai Street, Beijing, 100875, China
AU: Weng, Q H
EM: qhweng@gmail.com
AF: Department of Geography, Geology, and Anthropology, Indiana State University, Terre Haute, Indianapolis, IN 47809, United States
AB: Along with urbanization, urban heat island (UHI) has become one of the most serious urban problems, because of its impacts on the urban microclimate, air quality, energy consuming, public health and so on. With the advent of thermal remote sensing technology, remote observations of UHIs become the focus of urban remote sensing. While some progresses have been made by scientists, remote sensing study of UHI has been slow to advance qualitative description of thermal patterns and simple correlations. As a common indicator of UHI, magnitude is often used to describe the degree of UHI occurrence. In order to develop a more quantitative and more effective indicator for UHI dynamic monitoring at regional scale, deriving its spatial feature and facilitating the comparisons between different UHIs occur at different time or different areas based on remote sensing imageries, this paper proposes a new parameter named UHI volume to integrate UHI magnitude and extent effectively. After the subtraction of the rural contribution in the land surface temperature (LST) image, the isolated UHI signature is fitted using a least-squares Gaussian surface and then the UHI volume is calculated as a double integral of the UHI signature function over its footprint. This study investigates the applicability of this volume model based on examination of thirty EOS-Terra MODIS level 1B imageries of Beijing City, China, acquired between 2004~2006. These imageries include fifteen nighttime scenes, with their corresponding daytime scenes. Firstly, the resampled digital elevation model (DEM) data, the normalized difference vegetation index (NDVI) and the modified normalized difference water index (MNDWI) are used to extract the urban areas. Secondly, a simplified method is performed to retrieve the land surface temperature from MODIS channel 31 and channel 32. Thirdly, four transects at different directions including N-S, W-E, NW-SE and NE-SW are selected to detect the UHIs to ensure the application of the volume model is valid. The detections reveal that each of the UHI in Beijing City at different time has a single core and its spatial distribution is symmetrical as a whole, despite there are some small UHIs in the outskirts, so the volume model presented is appropriate for the UHI simulations. Results of the UHI simulations demonstrate that: (1)The correlation between the modeled UHI signatures and the corresponding true values is high, especially for the nocturnal UHIs. This fact indicates that the Gaussian fit and the volume model is valid for UHI simulation. (2)There is obvious UHI effect in both daytime and nighttime in the summer. In the spring, autumn and winter, there is UHI effect in the nighttime, while no UHI in the daytime; the UHI magnitude and volume shows that the diurnal UHI is intenser than the nocturnal UHI, and the difference of the volume between the diurnal and nocturnal UHIs seems to be stable. (3)Because of different dominant factors including natural and anthropogenic factors and their different influences, the changes of the nocturnal UHIs are complicated, especially the extents of UHIs. The UHI magnitude and volume shows that the nocturnal UHI effect is intensest in the winter, while weakest in the summer.
DE: 0426 Biosphere/atmosphere interactions (0315)
DE: 0480 Remote sensing
SC: Biogeosciences [B]
MN: 2007 Fall Meeting