• 研究报告 •

基于空间自相关的兰州市热环境

1. 1中国科学院国家科学图书馆兰州分馆/中国科学院资源环境科学信息中心， 兰州 730000； 2兰州大学资源环境学院， 兰州 730000）
• 出版日期:2014-04-10 发布日期:2014-04-10

Urban thermal environment pattern with spatial autocorrelation in Lanzhou.

WANG Peng-long1**, ZHANG Jian-ming2, LU Rong-fang2

1. (1Lanzhou Branch of the National Science Library/Scientific Information Center for Resources and Environment, Chinese Academy of Sciences, Lanzhou 730000, China; 2College of Earth and Environmental Sciences, Lanzhou University, Lanzhou 730000, China)
• Online:2014-04-10 Published:2014-04-10

Abstract: Based on the Landsat-8 OLI/TIRS image, atsatellite brightness temperature was retrieved, and the spatial and internal patterns of urban thermal environment were analyzed with spatial autocorrelation in Lanzhou, a valley flat typed City. The results showed that the high temperature spots were mainly focused on the areas with intensive industry, commerce and population. The Yellow River and the afforesting belts along both sides of the river formed a relatively low temperature channel across the urban areas. The spatial pattern of brightness temperature retrieved from TIRS band 10 could better differentiate high or low temperature spots than from TIRS band 11. Meanwhile, band10based brightness temperature of the same land use/cover type was more concentrated, hence, more helpful to analyze the urban thermal environment. The spatial pattern of brightness temperature in Lanzhou was of significant autocorrelation. The band10based brightness temperature pattern had better spatial dependence. Given the same resolution to the TIRS, 1 km sampling interval could be used to study the urban thermal environment pattern. Local spatial autocorrelation could characterize the internal pattern of urban thermal environment, and monitoring the abnormal value spots could provide a sound background to ecological planning.