Analysis of land use/land cover change, population shift, and their effects on spatiotemporal patterns of urban heat islands in metropolitan Shanghai, China

Using time series Landsat TM/ETM+ imagery and demographic data of Shanghai for 1997 and 2008, the relationship between land use/land cover (LULC) change and population shift and their effects on the spatiotemporal patterns of urban heat islands (UHIs) were quantitatively examined using an integrated approach of remote sensing, geographical information systems (GIS), and statistical analysis. The results showed that this city has experienced unprecedented urban growth and sprawl during the study period. The developed land increased by 219.50%, approximately 72.52% of which was converted from former cropland (24.79%), fallow land (21.21%), forest and shrub (18.97%), bare land (6.62%), and water (0.93%). Furthermore, in combination with the detection of LULC change, an analysis of the spatially differential growth rates for developed land area and population size revealed an urban-suburban-exurban gradient pattern of population shifting, as evidenced by a sharp increase in developed land area within the middle sub-zones at the urban fringe and the exurban sub-zones beyond the outer traffic ring. Consequently, changes in LULC and population shifts resulted in significant variation in the spatiotemporal patterns of the UHIs due to the loss of water bodies and vegetated surfaces. In the foreseeable future, substantial population growth and urban expansion will continue, especially in the rapidly urbanizing suburban and exurban areas, and thus, the extent and magnitude of UHI effects will continue expanding as well. The relationships between land use, the UHI effect, and regional climate change require that the underlying mechanisms, patterns, and processes of land conversion as well as the response of urban climate should be addressed throughout official decision-making processes. Thus, the planners and decision-makers could fully evaluate the environmental consequences of different land development scenarios and therefore improve the scientific basis of future planning and regulations.