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Journal of Geophysical Research Atmospheres
Article . 2009 . Peer-reviewed
License: Wiley Online Library User Agreement
Data sources: Crossref
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Improvements in land surface temperature retrieval from the Landsat series thermal band using water vapor and air temperature

Authors: Jordi Cristóbal; Juan C. Jiménez-Muñoz; José A. Sobrino; Miquel Ninyerola; Xavier Pons;

Improvements in land surface temperature retrieval from the Landsat series thermal band using water vapor and air temperature

Abstract

Land surface temperature (LST) is involved in many land surface processes such as evapotranspiration, net radiation, or air temperature modeling. In this paper we present an improved methodology to retrieve LST from Landsat 4 TM, Landsat 5 TM, and Landsat 7 ETM+ using four atmospheric databases covering different water vapor ranges (from 0 to 8 g cm−2) to build the LST retrieval models and using both water vapor and air temperature as input variables. We also compare this with LST retrievals using only water vapor or only air temperature, as well as with an existing LST retrieval algorithm. In order to validate the results, we have selected 77 Landsat images taken between 2002 and 2006 (Catalonia, northeast of the Iberian Peninsula) and two sources of water vapor (radiosounding data and remote sensing estimations) and air temperature (radiosounding data and air temperature modeling). The best results using radiosounding data are obtained when both air temperature and water vapor are present in the LST retrieval models with a mean RMSE of 0.9 K, followed by only water vapor models with a mean RMSE of 1.5 K and only air temperature models with a mean RMSE of 5.6 K. The results obtained using Terra Moderate Resolution Imaging Spectroradiometer (MODIS) Level 2 water vapor product and at‐satellite‐pass air temperature modeling as input data also show that this kind of input data offers best results, with a mean RMSE of 0.9 K, followed by water vapor models with a mean RMSE of 2.1 K and only air temperature models with a mean RMSE of 5.6 K. Similar errors when using radiosounding or modeled water vapor and air temperature as input data suggest the avoidance of radiosounding data to retrieve LST over extensive areas. Finally, when comparing the presented methodology with another methodology also using water vapor and air temperature as input data, the improvement is of more than 0.5 K.

Subjects by Vocabulary

Microsoft Academic Graph classification: Earth's energy budget Mean squared error Meteorology Evapotranspiration Remote sensing Atmospheric temperature Air temperature Environmental science Satellite Moderate-resolution imaging spectroradiometer Water vapor

Keywords

Atmospheric Science, Soil Science, Aquatic Science, Oceanography, Geochemistry and Petrology, Earth and Planetary Sciences (miscellaneous), Earth-Surface Processes, Water Science and Technology, Ecology, Paleontology, Forestry, Geophysics, Space and Planetary Science

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    107
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    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
  • citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    107
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
107
Top 10%
Top 10%
Top 10%
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