摘要
在利用决策树模型将城市复杂地表分为植被、建筑物、水体、裸土等4类进行地表比辐射率估算和利用MODIS近红外数据反演大气水分含量的基础上,采用Jim啨nez-Mu灳oz单通道算法进行了城市复杂地表TM温度的反演,并将反演结果与EOS MODIS地表温度产品进行了比较分析。结果表明:(1)基于地表信息分类提取后的地表比辐射率和MODIS反演的大气水汽含量得到的地表温度接近于实际状况;(2)反演结果与EOS MODIS地表温度产品对比发现Landsat TM的陆表温度均值和标准差高于EOS MODIS的陆表温度产品。
Material and the energy conversion process in urban region is changed for the disturbances coming from human being, which results in the local thermal feature abnormality and variation. As the key physical parameter in the balance between land surface and atmosphere, land surface temperature plays an important role and becomes one of the key factors and influences on the environmental temperature. Based on surface emissivity estimated from the urban complex surface divided into vegetation, buildings, water, and bare soil by decision tree model, and the total atmospheric water vapor content from MODIS, the land surface temperature was inversed from TM data with Jimenez - Munoz single - channel algorithm. Then EOS MODIS products and inversion results were compared. Results show that: (1) According to surface emissivity calculated by the classification of the surface and atmospheric water vapor content inversed from MODIS, the surface temperature is closer to the actual situation; (2) by compared the inversed result with EOS MODIS land surface temperature products, Landsat TM land surface temperature mean and standard deviation are all higher than those of the EOS MODIS land surface temperature products.
出处
《自然灾害学报》
CSCD
北大核心
2009年第5期113-118,共6页
Journal of Natural Disasters
基金
国家高技术研究发展计划(863计划)(2006AA12Z142-1)
国家自然科学基金(40701020
40771136
40701114)
北京市自然科学基金(8082015)
北京市科技计划项目(D08040600580801)
北京市优秀人才培养资助项目(20081D0503100254)
地理信息科学江苏省重点实验室开放基金资助项目联合资助
关键词
城市
复杂地表
温度反演
遥感
city
complex surface
temperature inversion
remote sensing