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Improvement of mono-window algorithm for land surface temperature retrieval integrated with subpixel mapping for Landsat imagery

  • Fudan University
  • East China Normal University

科研成果: 书/报告/会议事项章节会议稿件同行评审

摘要

Since a large proportion of pixels are often composed of mixed land cover types within remote sensing images, how to eliminate the impact of the error resulting from pixel mixing effect in the estimation of land surface emissivity on the accuracy of land surface temperature (LST) retrieval from remote sensing data is a key problem to resolve firstly in process of LST retrieval. Based on the local relationship between the thermal radiance of one pixel and that of its components satisfying the Planck's radiance function, in this paper, the mono-window algorithm was improved by integrating with mixed-pixel classification and sub-pixel mapping for Landsat imagery. Validation indicates that the improved mono-window algorithm is able to provide more accurate LST than the original algorithm for Landsat TM/ETM+ imagery. By applying the improved algorithm to the Landsat image of Shanghai, the result revealed the spatial heterogeneity characteristics of UHI effect in Shanghai city.

源语言英语
主期刊名4th International Workshop on Earth Observation and Remote Sensing Applications, EORSA 2016 - Proceedings
编辑Paolo Gamba, George Xian, Shunlin Liang, Qihao Weng, Jing Ming Chen, Shunlin Liang
出版商Institute of Electrical and Electronics Engineers Inc.
24-27
页数4
ISBN(电子版)9781509014798
DOI
出版状态已出版 - 25 8月 2016
已对外发布
活动4th International Workshop on Earth Observation and Remote Sensing Applications, EORSA 2016 - Guangzhou, 中国
期限: 4 7月 20166 7月 2016

出版系列

姓名4th International Workshop on Earth Observation and Remote Sensing Applications, EORSA 2016 - Proceedings

会议

会议4th International Workshop on Earth Observation and Remote Sensing Applications, EORSA 2016
国家/地区中国
Guangzhou
时期4/07/166/07/16

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