安徽农业大学学报2016，Vol.43Issue(3)：474-480,7.DOI:10.13610/j.cnki.1672-352x.20160512.014
基于landsat8 oli数据的合肥市热岛时空特征分析
Landsat8 oli data-based analysis of spatial-temporal characteristics of heat island in Hefei
摘要
Abstract
Heat island defined as the temperature in a specific area is higher than the surrounding area is a peculiar environmental problem resulted from human civilization and development.To reveal the spatial temporal changes of the urban heat island in rapidly urbanizing areas,this study used oli data of landsat-8 in 2014 to retrieve surface temperature in Hefei using remote sensing algorithms.The distribution of heat island and its causes and the relationship between normalized difference building index,normalized difference vegetation index and heat island distribution,as well as the impact to heat island effect by urban underlying surface were analyzed.In addition,an ecological evaluation of the urban thermal field was conducted.The results showed that the heat island effect existed in Hefei year-around.The intensity of heat island effect was the strongest in summer with the highest temperature of about 57.86℃ and the weakest in spring and winter.Heat island areas were concentrated in villages,towns and bare areas in winter and in main urban areas in other seasons with a weak intensity.The heat island effect mainly appeared in impervious surface and bare areas,while the urban cold island appeared near water bodies.The urban heat island distribution had a negative correlation with the normalized difference vegetation index and had a positive correlation with the normalized difference building index.Improved radius method could better distinguish the urban built-up area.There was a significant difference between the built-up area and suburbs.关键词
landsat8 oli数据/地表温度/热岛分布/归一化建筑指数/合肥市Key words
landsat8 oli data/land surface temperature/distribution of heat island/normalized building index/Hefei city分类
资源环境引用本文复制引用
宋瑞祥,张庆国,孟庆岩,徐丽,施悯悯..基于landsat8 oli数据的合肥市热岛时空特征分析[J].安徽农业大学学报,2016,43(3):474-480,7.基金项目
国家自然科学基金项目“基于机载LiDAR数据的城市绿度空间指数模型研究”(41471310)资助. （41471310）
