Analysis on Spatiotemporal Variation of Urban Impervious Surface and Its Influence on Urban Thermal Environment: Fuzhou City, China

被引:0
|
作者
Wang M. [1 ]
Xu H. [1 ]
Li X. [1 ]
Lin Z. [1 ]
Zhang B. [1 ]
Fu W. [1 ]
Tang F. [1 ]
机构
[1] College of Environment and Resources, Fujian Provincial Key Laboratory of Remote Sensing of Soil Erosion and Disaster Prevention, Fuzhou University, Fuzhou
来源
Yingyong Jichu yu Gongcheng Kexue Xuebao/Journal of Basic Science and Engineering | 2018年 / 26卷 / 06期
关键词
Fuzhou; Impervious surface; Remote sensing; Urban expansion; Urban thermal environment;
D O I
10.16058/j.issn.1005-0930.2018.06.015
中图分类号
学科分类号
摘要
The fast urban spatial expansion has led to the considerable substitution of natural vegetation-dominated land surfaces by impervious surface. Understanding of the role of impervious surface changes to urban thermal environments is of importance for mitigating severe urban heat island effect in cities of the world. Taking Fuzhou city in southeastern China as a case, this study examined the quantitative relationship of impervious surface with land surface temperature (LST).Two Landsat images of 1989 and 2014 were used to extract the information of impervious surface, vegetation and water and to retrieve LST from the images. The result shows that the impervious surface in Fuzhou's urban area has significantly increased by 161% during the study period, which was 54.29km 2 in 1989 but remarkably increased to 141.45km 2 in 2014.The regression analysis results showed a strong positive exponential relationship existing between the percent impervious surface and LST. This suggests that the areas with high impervious surface percentage will accelerate the raise of the LST much faster than the areas with low impervious surface percentage. Each decrement of 10% impervious surface cover with additional 10% green or water space could lower LST by up to 4.15 or 5.25℃, respectively. According to this regression analysis, the increase of impervious surface area and the decrease of vegetation and water coverage in Fuzhou urban area during the 25-study years have made a substantial LST rise by 16.54℃ in the area from 1989 to 2014. © 2018, The Editorial Board of Journal of Basic Science and Engineering. All right reserved.
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页码:1316 / 1326
页数:10
相关论文
共 31 条
  • [1] Weng Q.H., Remote sensing of impervious surfaces in the urban areas: Requirements, methods, and trends, Remote Sensing of Environment, 117, 2, pp. 34-49, (2012)
  • [2] Wu C., Murray A.T., Estimating impervious surface distribution by spectral mixture analysis, Remote Sensing of Environment, 84, 4, pp. 493-505, (2003)
  • [3] Bauer M.E., Loffelholz B.C., Wilson B., Estimating and Mapping Impervious Surface Area by Regression Analysis of Landsat Imagery, (2008)
  • [4] Xu H.Q., Analysis of impervious surface and its impact on urban heat environment using the normalized difference impervious surface index (NDISI), Photogrammetric Engineering & Remote Sensing, 76, 5, pp. 557-565, (2010)
  • [5] Zou C., Zhang Y., Huang H., Impacts of impervious surface area and landscape metrics on urban heat environment in Fuzhou City, China, Journal of Geo-information Science, 16, 3, pp. 490-498, (2014)
  • [6] Guo G., Wu Z., Liu X., Seasonal variations of urban heat environment and its relationship to impervious surface: A case study of guangzhou core urban area, Ecology and Environmental Sciences, 24, 2, pp. 270-277, (2015)
  • [7] Yuan F., Bauer M.E., Comparison of impervious surface area and normalized difference vegetation index as indicators of surface urban heat island effects in Landsat imagery, Remote Sensing of Environment, 106, 3, pp. 375-386, (2007)
  • [8] Roberts D.A., Quattrochi D.A., Hulley G.C., Et al., Synergies between VSWIR and TIR data for the urban environment: an evaluation of the potential for the Hyperspectral Infrared Imager (HyspIRI) Decadal Survey mission, Remote Sensing of Environment, 117, pp. 83-101, (2012)
  • [9] Xu H., Analysis on urban heat island effect based on the dynamics of urban surface biophysical descriptors, Acta Ecologica Sinca, 31, 14, pp. 3890-3901, (2011)
  • [10] Balcik F.B., Determining the impact of urban components on land surface temperature of Istanbul by using remote sensing indices, Environmental Monitoring and Assessment, 186, 2, pp. 859-872, (2014)