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

  • Xiaoyan Dai
  • , Zhongyang Guo*
  • , Chen Chen
  • *Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Scopus citations

Abstract

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.

Original languageEnglish
Title of host publication4th International Workshop on Earth Observation and Remote Sensing Applications, EORSA 2016 - Proceedings
EditorsPaolo Gamba, George Xian, Shunlin Liang, Qihao Weng, Jing Ming Chen, Shunlin Liang
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages24-27
Number of pages4
ISBN (Electronic)9781509014798
DOIs
StatePublished - 25 Aug 2016
Externally publishedYes
Event4th International Workshop on Earth Observation and Remote Sensing Applications, EORSA 2016 - Guangzhou, China
Duration: 4 Jul 20166 Jul 2016

Publication series

Name4th International Workshop on Earth Observation and Remote Sensing Applications, EORSA 2016 - Proceedings

Conference

Conference4th International Workshop on Earth Observation and Remote Sensing Applications, EORSA 2016
Country/TerritoryChina
CityGuangzhou
Period4/07/166/07/16

Keywords

  • Landsat imagery
  • land surface temperature
  • mono-window algorithm
  • remote sensing
  • sub-pixel mapping

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