基于TM的城市温度异常区分析  

AN ANALYSIS OF THE CITY TEMPERATURE ABNORMAL AREA BASED ON TM DATA

作　　者：黄妙芬[1] 陈波[2] 刘素红[2] 程灿[2] 彭睿[2] 

机构地区：[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

出　　处：《国土资源遥感》2007年第3期23-27,I0002,共6页Remote Sensing for Land & Resources

基　　金：国家重点基础研究发展规划项目"973计划"(G20000779);国家自然科学基金项目(40471094);中国地质调查项目"城市环境地球化学调查方法技术及污染影响机理研究(20032013004)"

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。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.

关 键 词：TM 单窗算法 地表温度 阈值法 城市温度异常区 

分 类 号：TP79[自动化与计算机技术—检测技术与自动化装置]