摘要
城市热环境是城市生态环境的重要方面,它与城市气候、城市生态、城市灾害有着重要的联系。以北京、上海、广州三地为研究区,选取近10年MODIS的夜晚地表温度(LST)产品MOD11A2,分别采用质心迁移、景观格局指数、空间自相关方法研究京沪穗三地近10年的不同等级热力景观质心迁移演变、格局变迁和空间集聚特征。主要结论为:三地热力景观随郊区向市中心趋近,体现了由低温区、次中温区向中温区、次高温区、高温区过渡的趋势;三地的中温区所占比例最大,城市热力景观破碎度三地中上海市最高,5种热力景观比较,次中温区和高温区的破碎度最高;城市热力景观离散度三地中北京市最高,低温区和高温区的离散度较高。热环境空间自相关分析表明三地均以高温-高温区,低温-低温区集聚为主,北京、广州高温-高温区分布于南部,且集中成片分布,而上海市高温-高温区分布比较离散,相对较为复杂。从分布面积来说,10a中北京、上海表现为先减少后增加,而广州则持续减少。总体而言北京热环境恶化,而广州、上海热环境有所好转。
The urban thermal environment is an important element for the urban ecological environment, urban climate and urban disasters. This paper selected MOD11A2, the MODIS LST night data to study the thermal environment evolution in Beijing, Shanghai and Guangzhou, which are the three major cities of China in the past decade. Three methods have been applied in the paper, Landscape eentroid evolution, Landscape pattern index and spatial autocorrelation. Three main conclusions have been drawn as follows. Firstly the thermal landscape distributions in the three cities have moved from the suburb to the downtown. And the evolution trend of the thermal landscape is changed from the low temperature region, sub- middle temperature region to middle temperature region, sub-high temperature region and high temperature region. Secondly, among these five types of thermal landscape, the middle temperature region is the most prevalent. The urban thermal landscape fragmentation was highest in Shanghai among the three cities, and sub-middle and high temperature region has the highest fragmentation. The urban thermal landscape dispersion was highest in Beijing, and the dispersion of low and high temperature region was higher than the other types of thermal landscapes. Thirdly, thermal environment spatial autocorrelation analysis showed that the high-high temperature zones were adjacent, low-low temperature areas were adjacent, which are the main types in the temperature spatial agglomeration. And for Beijing and Guangzhou city, the high- high temperature zone located in the south of the city, the low-low temperature region located in the north. While, the spatial autocorrelation distribution of LST in Shanghai is more complicated. The distribution areas of high-high temperature varied among the three cities in the past decade. In Beijing, the distribution area increased shortly after decreasing, and in Guangzhou, the distribution area continued to decline, which preliminary reflects the heat island effect problem aggravated in Beijing, while weakened in Shanghai and Guangzhou. Through comparisons and analysis, the paper has provided a reference for urban planning and urban living environment improvements, but there are still some inadequacies to be further studied. Firstly, this study only selected the January night LST data in the three cities. Because the time factors, such as season, daytime and nocturne, will affect the urban heat environment pattern, the comprehensiveness of the thermal environment pattern changes need to be improved. In addition, the paper only selected the data in the period of three years, the evolution regulation of the urban thermal environment pattern is not precise. Secondly, the landscape of urban heat environment were impacted by many factors, including the pattern of landuse, urban surface construction, weather conditions, terrain, anthropogenic heat emissions factors and so on. The analysis between the urban heat environment and impact factors will help reveal the mechanism of urban heat environment and which will be studied further.
出处
《生态学报》
CAS
CSCD
北大核心
2013年第5期1545-1558,共14页
Acta Ecologica Sinica
基金
中国博士后科学基金(20110490447)
北京市博士后科研基金(49)
北京市教育委员会科技计划面上项目(KM201310028011)
973计划前期研究专项课题(2012CB723403)
关键词
城市热环境
热力景观格局
空间质心
景观格局指数
空间自相关
urban thermal environment
thermal landscape pattern
spatial centroid
landscape pattern index
spatial autocorrelation