福州市城市不透水面景观指数与城市热环境关系分析

doi:10.3724/SP.J.1047.2014.00490

地球信息科学学报 ›› 2014, Vol. 16 ›› Issue (3): 490-498.doi: 10.3724/SP.J.1047.2014.00490

福州市城市不透水面景观指数与城市热环境关系分析

邹春城, 张友水, 黄欢欢

福建师范大学地理科学学院, 福州350007

收稿日期:2013-07-01 修回日期:2013-10-15 出版日期:2014-05-10 发布日期:2014-05-10
通讯作者: 张友水（1974- ），男，副教授，主要从事资源环境应用研究。E-mail：yzha5553@163.com E-mail:yzha5553@163.com
作者简介:邹春城（1988- ），男，硕士生，主要从事资源环境应用研究。E-mail：yzcc0123@163.com
基金资助:
福建省自然科学基金项目（2012J01164）。

Impacts of Impervious Surface Area and Landscape Metrics on Urban Heat Environment in Fuzhou City, China

ZOU Chuncheng, ZHANG Youshui, HUANG Huanhuan

College of Geographical Sciences, Fujian Normal University, Fuzhou 350007, China

Received:2013-07-01 Revised:2013-10-15 Online:2014-05-10 Published:2014-05-10

摘要/Abstract

摘要：

城市化致使城市环境问题的产生，城市热环境问题就是其中之一。本文从不透水面方面研究对城市热环境的影响。根据福州市1989年和2001年LandsatTM/ETM+遥感影像数据，利用线性光谱分解法提取两时相不透水面信息，并离散化分级为中低、中、中高、高密度区4个区域，分别计算这4个区域的地表温度（LST）、归一化植被指数（NDVI），并进行相关性分析；根据阈值法和范围法分别计算不透水面的PD、AI、LPI等景观指数，结果表明：两时段内不透水面的面积有所增加，在高密度区增加明显；不透水面与地表温度的呈正相关，相关系数分别为0.66和0.71；不透水面景观指数对FISA敏感，景观指数整体的变化趋势与地表温度的变化趋势相一致，FISA值越大，温度越高，且各斑块的形状越来越复杂，空间的连续性越强；聚集度越高，人类活动也越强。

关键词: 不透水面, 线性光谱分解, 景观指数, 地表温度, 福州市

Abstract:

With the economic development, urbanization has been accelerating in recent years in Fuzhou City, Fujian Province of China. Rapid change on land surface property and its patterns may lead to change of thermal properties in urban areas of Fuzhou City. One of the main impacts of rapid urbanization is the effect of urban thermal environment. Landscape patches in a region are different in size, shape and spatial arrangements, which contribute to the spatial heterogeneity of landscape and are linked to the distinct behaviour of urban thermal environments. Studies on landscape metrics extracted from discretized percent impervious surface area data are comparatively rare. This research, which investigated the relationship of landscape metrics and urban thermal environments in Fuzhou City, Fujian Province, China, is based on both the analysis of land surface temperature (LST) in relation to normalized difference vegetation index (NDVI), and the percent impervious surface area (FISA). Two Landsat TM/ETM+ images acquired on June 15 1989 and March 4, 2001 were used to estimate LST, NDVI, and impervious surface area (ISA). This was extracted by applying linear spectral mixture analysis. We analyzed the relationship between the above-mentioned components of urban ecosystem. Using threshold value method and range method to discretize percent ISA into different categories. Landscape metrics such as cohesion, AI, LPI, etc. are calculated based on different FISA categories. The result showed that there is a positive linear relationship between LST and impervious surface over the region. The correlation coefficient is .66(1989) and .71(2001). To find the relationship between landscape metrics and LST, we analyzed landscape metrics from three aspects: shape, area and structure. The study indicated that landscape metrics are sensitive to the variation of FISA and LST. Therefore, the integration of FISA and landscape metrics provided a feasible way to describe the spatial distribution and temporal variation in urban thermal patterns in a quantitative manner.

Key words: linear spectral mixture analysis, Fuzhou City, impervious surface area, landscape metrics, land surface temperature

邹春城, 张友水, 黄欢欢. 福州市城市不透水面景观指数与城市热环境关系分析[J]. 地球信息科学学报, 2014, 16(3): 490-498.DOI:10.3724/SP.J.1047.2014.00490

ZOU Chuncheng, ZHANG Youshui, HUANG Huanhuan. Impacts of Impervious Surface Area and Landscape Metrics on Urban Heat Environment in Fuzhou City, China[J]. , 2014, 16(3): 490-498.DOI:10.3724/SP.J.1047.2014.00490

参考文献

[1] 潘竟虎,刘春雨,李晓雪.基于混合光谱分解的兰州城市热岛与下垫面空间关系分析[J].遥感技术与应用，2009, 24(4):462-468.
[2] 林云杉,徐涵秋,周榕.城市不透水面及其与城市热岛的关系研究[J].遥感技术与应用,2007,22(1):14-19.
[3] 赵俊华.城市热岛的遥感研究[J].城市环境与城市生态, 1994,7(4):40-43.
[4] Carlson T N, Arthur S T. The impact of land use/land cover changes due to urbanization on surface microclimate and hydrology: A satellite perspective[J]. Global and Planetary Change, 2000,25(1):49-65.
[5] Ridd M K. Exploring AV-I-S (Vegetation-Impervious Surface-soil) model for urban ecosystem analysis through remote sensing: Comparative anatomy for cities[J]. International Journal of Remote Sensing, 1995,16(12):2165-2185.
[6] Wu C. Normalized spectral mixture analysis for monitoring urban composition using ETM+ imagery[J]. Remote Sensing of Environment,2004,93(4):480-492.
[7] 程熙,沈占锋,骆剑承,等.利用混合光谱分解与SVM估算不透水面覆盖率[J].遥感学报,2011,15(6):1228-1241.
[8] 黄聚聪,赵小锋,唐立娜,等.城市化进程中城市热岛景观格局演变的时空特征——以厦门市为例[J].生态学报, 2012,32(2):622-631.
[9] 孟丹,李小娟,宫辉力,等.北京地区热力景观格局及典型城市景观的热环境效应[J].生态学报,2010,30(13):3491-3500.
[10] Buyantuyev A, Wu J G, Gries C. Multiscale analysis of the urbanization pattern of the Phoenix metropolitan landscape of USA: Time, space and thematic resolution[J]. Landscape and Urban Planning, 2010(94):206-217.
[11] 张友水,韩春峰,伍雄昌,等.多时相遥感影像福州市热场与土地覆盖分析[J].资源科学,2011,33(5):950-957.
[12] Sobrino J A, Raissouni N, LI Z L. A comparative study of land surface emissivity retrieval from NOAA data[J]. Remote Sensing of Environment,2001,75(2):256-266.
[13] Brown L ,Chen J M, Leblanc S G. A shortwave infrared modification to the simple ratio for LAI retrieval in boreal forest: An image and model analysis[J]. Remote Sensing of Environment, 2000,71(1):16-25.
[14] 覃志豪, Zhang M H, Karnielia A, 等. 用陆地卫星TM6 数据演算地表温度的单窗算法[J]. 地理学报，2001,56 (4):456-466.
[15] 徐涵秋.一种快速提取不透水面的新型遥感指数[J].武汉大学学报,2008,33(11):1150-1153.
[16] 徐涵秋.利用改进的归一化差异水体指数(MNDWI)提取水体信息的研究[J].遥感学报,2005,9(5):589-595.
[17] 周存林,徐涵秋.福州城区不透水面的光谱混合分析与识别制图[J].中国图象图形学报,2007,12(5):875-881.
[18] Yue W Z, Wu C F. Urban impervious surface distribution estimation by spectral mixture analysis[J]. Journal of Remote Sensing,2007,11(6):914-922.
[19] 李彩丽,都金康,左天惠.基于高分辨率遥感影像的不透水面信息提取方法研究[J].遥感信息,2009(5):36-40.
[20] Roy H Y, Mark C. Quantifying landscape Structure: A review of landscape indices and their application to forested landscapes[J]. Progress in Physical Geography, 1996, 20(4):418-445.
[21] Liu H, Weng Q. Seasonal variations in the relationship between landscape pattern and land surface temperature in Indianapolis, USA[J]. Environmental Monitoring and Assessment, 2008(144):199-219.

福州市城市不透水面景观指数与城市热环境关系分析

Impacts of Impervious Surface Area and Landscape Metrics on Urban Heat Environment in Fuzhou City, China

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