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遥感技术与应用  2010, Vol. 25 Issue (1): 8-14    DOI: 10.11873/j.issn.1004-0323.2010.1.8
研究与应用     
基于TM影像的城市热岛效应监测与预测分析
盛辉,万红,崔建勇,郭鹏
中国石油大学(华东)地球资源与信息学院,山东 青岛266555
Urban Heat Island Effect Study and Pridiction Analysis Based on Landsat TM Data
SHENG Hui,WAN Hong,CUI Jian-yong,GUO Peng
College of Geo-resources and Information,China University of Petroleum (East China),Qingdao 266555,China
 全文: PDF(3520 KB)  
摘要:

近些年,随着城市建设的高速发展,热岛效应也越来越被人们所重视。采用1999年、2005年、2009年的TM遥感影像,分析了东营市的热岛效应时空演化规律并应用马尔科夫模型对其未来发展趋势进行了预测。研究发现:东营市热岛效应明显且稳定存在,热岛中心主要分布在西城区、东城区人口密度大以及工业区聚集的地方,植被和水体有减弱热岛效应的作用。随着城市的扩展,热岛区分布变广,呈现小而广的分布状态,且随着城市注重环境治理和注重绿化,未来10年东营市热岛效应有减弱的趋势,但是速度较慢。

关键词: 遥感/城市热岛效应Landsat亮温马尔科夫模型    
Abstract:

Recently,along with the fast\|developing urban construction,the urban heat effect (UHI) has caught great attention.Using the Landsat TM images which were obtained on 1999,2005 and 2009,the evolution of the urban heat island distribution in Dongying city are analyzed and future tendency of urban heat island are predicted,following the Markov Model in this paper.The result showed that the UHI in Dongying city was obvious and existed steadily,the centers of UHI present to the Xicheng district,Dongcheng district,which are all the densely inhabited district and industrial park gathering,vegetation and water have reduced the role of heat island effect with the developing of urban expanding,the distributing of heat island become wide ,besides the distributing show a small and wide.With the urban pay more attention to environmental governace and urban greening,the trend of Dongying heat island effect has weakened in the next decade,but the speed is slow.

Key words:  RS    Urban Heat Island Effect    Land sat    Brightness temperature    Markov model
收稿日期: 2009-03-24 出版日期: 2011-11-04
通讯作者: 盛辉 Email :Shenghui@mail.hdpu.edu.cn   
作者简介: 盛辉(1972-),男,副教授,博士研究生,主要从事摄影测量与遥感、GIS 方面的教学与研究工作。
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引用本文:

盛辉, 万红, 崔建勇, 郭鹏. 基于TM影像的城市热岛效应监测与预测分析[J]. 遥感技术与应用, 2010, 25(1): 8-14.

SHENG Hui, WAN Hong, CUI Jian-yong, GUO Peng. Urban Heat Island Effect Study and Pridiction Analysis Based on Landsat TM Data. Remote Sensing Technology and Application, 2010, 25(1): 8-14.

链接本文:

http://www.rsta.ac.cn/CN/10.11873/j.issn.1004-0323.2010.1.8        http://www.rsta.ac.cn/CN/Y2010/V25/I1/8

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