The Study Of Urban Heat Island Effect Based On Remote Sensing Image Information Capacity

The continuous development of urbanization promotes unceasing enhancement of the urban heat island (UHI) effect, and then brings significant influence in urban climate, residents living and health. Since 1950s, the UHI effect has gradually become a hot research issue in the disciplines of meteorology, remote sensing science and technology, ecological environment and urban planning. Remote sensing monitoring method is the main method of urban thermal environment research, which is based on the advantages of continuity, integrity and real-time of data acquisition. Retrieving land surface temperature (LST) by remote sensing data is a key problem in the study of spatial heterogeneity and evolution of UHI effect.The municipal districts of Xi'an and Xianyang in Shaanxi province as the main study area, this research uses satellite remote sensing data to retrieve LST, extracts underlying surface factors (vegetation and impervious surface) which influence LST, and makes qualitative and quantitative analysis about the spatial and temporal pattern of UHI and the relationship between UHI and underlying surface factors. Besides, information capacity (IC) is firstly used to analyze the spatial pattern of UHI. Through the study, we found:(1) Landsat 5/Landsat 8 data as the data source, using mono-window algorithm for retrieving LST, this research analysed the relationship between the LST evolution and urban expansion during 20 years ranged from 1994 to 2014. The research shows that the UHI area is increasing and the distribution of UHI is expanding in the study area, the expanding scope mainly along the city center and continue to expand to the periphery, which is consiste with the urbanization of the study area.(2) There is a close correlation between LST and underlying surface types. Two key underlying surface factors (vegetation and impervious surface) affecting the intensity of UHI effect was selected to quantitatively reveal the relationship between the underlying surface and UHI effect. The research shows that UHI effect and vegetation was negatively correlated, and impervious surface showed a positive correlation with UHI.(3) The IC based on multi-dimensional histogram can be used to characterize the spatial complexity of the remote sensing image, and can be used to evaluate the pattern of UHI effect. The research shows that IC of LST and the IC of underlying surface factors have a positive correlation, further illustrate the change of the LST spatial pattern is consistent with the change of the underlying surface factor spatial pattern.