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北京城区2000—2014年地表温度反演及因素分析
引用本文:刘苏庆,陈建平,李诗.北京城区2000—2014年地表温度反演及因素分析[J].地质学刊,2019,43(3):499-505.
作者姓名:刘苏庆  陈建平  李诗
作者单位:中国地质大学(北京)地球科学与资源学院
基金项目:科技部深地资源勘查开采专项“深部成矿地质异常定量预测方法与模型”(2017YFC0601502)
摘    要:传统的城市温度监测方法周期长、效率低,而利用热红外遥感影像进行城区温度监测的方法具有准确、简便、实用等优点。基于Landsat TM、ETM+、OLI遥感影像数据,应用辐射传输方程法对北京城区(东城区、西城区、宣武区、崇文区、朝阳区、海淀区和丰台区7个区域)2000—2014年夏季地表温度的空间分布和时间变化进行分析及温度反演,结果显示,高温区分布有一定的规律,降雨情况、植被覆盖度的变化以及城区规划都是北京城区温度变化的重要影响因素。研究结果可为减缓北京的热岛效应提供依据。

关 键 词:ERDAS软件  地表温度反演  Landsat  TM、ETM+、OLI  影响因素  北京

Land surface temperature inversion and factor analysis in Beijing downtown, 2000-2014
Liu Suqing,Chen Jianping,Li Shi.Land surface temperature inversion and factor analysis in Beijing downtown, 2000-2014[J].Jiangsu Geology,2019,43(3):499-505.
Authors:Liu Suqing  Chen Jianping  Li Shi
Abstract:The traditional urban temperature monitoring method has the disadvantage of long period and low efficiency, while using thermal infrared remote sensing image for urban temperature monitoring is accurate, simple and practical. Based on Landsat TM, ETM+,OLI remote sensing image data, this paper used radiative transfer equation to analyze the spatial distribution, temporal variation, and temperature inversion of land surface temperature in Beijing city (including Dongcheng, Xicheng, Xuanwu, Chongwen, Chaoyang, Haidian and Fengtai 7 districts) in the summers of 2000-2014. The results show that there are certain regularities in the distribution of high temperature areas, and the change of rainfall, vegetation coverage and urban planning are all important factors influencing the temperature change in Beijing downtown. The results can provide a basis for the slowing of the heat island effect in Beijing.
Keywords:ERDAS software  land surface temperature inversion  Landsat TM  ETM+  OLI  influencing factor  Beijing
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