Assessing the effects of land use spatial structure on urban heat islands using HJ-1B remote sensing imagery in Wuhan, China

被引:125
|
作者
Wu, Hao [1 ,2 ]
Ye, Lu-Ping [1 ]
Shi, Wen-Zhong [2 ]
Clarke, Keith C. [3 ]
机构
[1] Wuhan Univ Technol, Sch Resources & Environm Engn, Wuhan 430070, Peoples R China
[2] Hong Kong Polytech Univ, Dept Land Surveying & Geoinformat, Kowloon, Hong Kong, Peoples R China
[3] Univ Calif Santa Barbara, Dept Geog, Santa Barbara, CA 93106 USA
基金
中国国家自然科学基金; 中国博士后科学基金;
关键词
Urban heat island; Land use spatial structure; Vegetation indexes; Landscape metrics; Fractal analysis; HJ-1B; SURFACE TEMPERATURE RETRIEVAL; EMISSIVITY RETRIEVAL; LANDSCAPE PATTERN; FRACTAL ANALYSIS; COVER CHANGE; SATELLITE; VEGETATION; IMPACT; WATER; CITY;
D O I
10.1016/j.jag.2014.03.019
中图分类号
TP7 [遥感技术];
学科分类号
081102 ; 0816 ; 081602 ; 083002 ; 1404 ;
摘要
Urban heat islands (UHIs) have attracted attention around the world because they profoundly affect biological diversity and human life. Assessing the effects of the spatial structure of land use on UHIs is essential to better understanding and improving the ecological consequences of urbanization. This paper presents the radius fractal dimension to quantify the spatial variation of different land use types around the hot centers. By integrating remote sensing images from the newly launched HJ-1B satellite system, vegetation indexes, landscape metrics and fractal dimension, the effects of land use patterns on the urban thermal environment in Wuhan were comprehensively explored. The vegetation indexes and landscape metrics of the HJ-1B and other remote sensing satellites were compared and analyzed to validate the performance of the HJ-1B. The results have showed that land surface temperature (LST) is negatively related to only positive normalized difference vegetation index (NDVI) but to Fv across the entire range of values, which indicates that fractional vegetation (Fv) is an appropriate predictor of LST more than NDVI in forest areas. Furthermore, the mean LST is highly correlated with four class-based metrics and three landscape-based metrics, which suggests that the landscape composition and the spatial configuration both influence UHIs. All of them demonstrate that the HJ-1B satellite has a comparable capacity for UHI studies as other commonly used remote sensing satellites. The results of the fractal analysis show that the density of built-up areas sharply decreases from the hot centers to the edges of these areas, while the densities of water, forest and cropland increase. These relationships reveal that water, like forest and cropland, has a significant effect in mitigating UHIs in Wuhan due to its large spatial extent and homogeneous spatial distribution. These findings not only confirm the applicability and effectiveness of the HJ-1B satellite system for studying UHIs but also reveal the impacts of the spatial structure of land use on UHIs, which is helpful for improving the planning and management of the urban environment. (C) 2014 Elsevier B.V. All rights reserved.
引用
收藏
页码:67 / 78
页数:12
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