以快速城市化的典型地区广东省东莞市为例,利用Landsat卫星遥感数据、气象观测数据进行地表温度反演。从城市下垫面最基本的组成元素出发,对典型下垫面类型加以界定,采用NDVI阈值法提取水体-高植被区-建筑密集区的分布信息。通过对地表温度与典型下垫面信息的叠加分析,研究温室效应增强背景下典型下垫面温度的相对变化趋势。研究结果表明,在1988~2005年间,东莞市地表温度的高低顺序为:建筑密集区>高植被区>水体,建筑密集区与水体、高植被区的温度反差明显增大,而且建筑密集区与水体的温差大于建筑密集区与高植被区的温差。
As a typical rapid urbanization city, the thermal environment in Dongguan, Guangdong has changed much in the past 28 years because of the economy development, the population growth, the underlying surface change, and the greenhouse effect enhancement. Taking Dongguan as an example, the paper retrieves the land surface temperature using Mono-window Algorithm proposed by Qin Zhihao from Landsat/TM data, meteorological measurement data and basic geographical data. Based on the Vegetation-Impervious surface-Soil model which was proposed by Ridd in 1995 according to the basic elements of underlying surfaces in a city, it defines the typical underlying surfaces as water, high vegetation region and dense building region,and gets the distribution information of them from the threshold division of normalized difference vegetation index. It takes an overlay analysis between the typical underlying surface information and land surface temperature data. The result shows that this method can effectively get the temperature differences of typical underlying surfaces. From 1988 to 2005, the land surface temperature of dense building region is higher than that of vegetation and water in Dongguan. The distribution of high land surface temperature region is consistent with the distribution of dense building region, and the low is consistent with the vegetation and water. Under the background of global warming caused by enhanced greenhouse effect, the temperature difference of dense building region and water, as the same as the temperature difference of dense building region and high vegetation region, are apparently increased. The former is bigger than the latter.
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