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基于TM的城市温度异常区分析
引用本文:黄妙芬,陈波,刘素红,程灿,彭睿.基于TM的城市温度异常区分析[J].国土资源遥感,2007,18(3):23-27.
作者姓名:黄妙芬  陈波  刘素红  程灿  彭睿
作者单位:1. 大连水产学院海洋工程学院,大连,116023
2. 北京师范大学地理学与遥感科学学院,北京,100875
基金项目:国家重点基础研究发展计划(973计划) , 国家自然科学基金 , 中国地质调查局资助项目
摘    要:利用实时探空数据和单窗算法对2004年7月6日北京市TM图像进行地表温度反演,根据反演结果,采用阈值法将北京城区地表温度空间分布分为植被正常温度区、水体正常温度区、水体高温区、裸地正常温度区、建筑物低温区、建筑物正常温度区、建筑物高温区、植被建筑物混合高温区和植被建筑物混合正常温度区等9种模式。在此基础上,对水体高温区、植被建筑物混合高温区、建筑物低温区和建筑物高温区等4种温度异常区进行了实地抽样调查,详细分析了这些温度异常区形成的原因。

关 键 词:TM  单窗算法  地表温度  阈值法  城市温度异常区
文章编号:1001-070X(2007)03-0023-05
收稿时间:2006-12-27
修稿时间:2006-12-272007-04-05

AN ANALYSIS OF THE CITY TEMPERATURE ABNORMAL  AREA BASED ON TM DATA
HUANG Miao-fen,CHEN Bo,LIU Su-hong,CHENG Can,PENG Rui.AN ANALYSIS OF THE CITY TEMPERATURE ABNORMAL  AREA BASED ON TM DATA[J].Remote Sensing for Land & Resources,2007,18(3):23-27.
Authors:HUANG Miao-fen  CHEN Bo  LIU Su-hong  CHENG Can  PENG Rui
Institution:1. School of Marine Engineering, Dalian Fisheries University, Dalian 116023, China; 2. School of Geography, Beijing Normal University, Beifing 100875, China
Abstract: Using Landsat 5 TM remotely sensed data and field calibration in Beijing performed on July 6, 2004, the authors detected the temperature distribution through the single-window algorithm and field validation. Nine patterns were recognized on the basis of the temperature data, namely, ①water body normal temperature area, ② water body abnormal temperature area, ③vegetation normal temperature area, ④vegetation and construction mixed normal temperature area, ⑤vegetation and construction mixed abnormal temperature area, ⑥construction low temperature area, ⑦construction normal temperature area, ⑧construction high abnormal temperature area, and ⑨ bare soil normal temperature area.  The abnormal areas were sampled and tested in situ in detail so as to extract the factors responsible for the abnormality.  A new way has thus been found to monitor the city environment and the living status.
Keywords:TM  Single -window algorithm  Surface temperature  Threshold value  City temperature abnormal area
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