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Remote Sens. 2017, 9(6), 532; doi:10.3390/rs9060532

The Relationship between Urban Land Surface Material Fractions and Brightness Temperature Based on MESMA

1
Institute of Geophysics and Geomatics, China University of Geosciences, Wuhan 430074, China
2
Fujian Surveying and Mapping Institute, Fuzhou 350003, China
*
Author to whom correspondence should be addressed.
Academic Editors: Soe Myint and Prasad S. Thenkabail
Received: 12 March 2017 / Revised: 17 May 2017 / Accepted: 24 May 2017 / Published: 27 May 2017
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Abstract

The relationship between urban land surface material fractions (ULSMFs) and brightness temperature has long attracted attention in research on urban environments. In this paper, a multiple endmember spectral mixture analysis (MESMA) method was applied to extract vegetation-impervious surface-soil (V-I-S) fractions in each pixel, and the surface brightness temperature was derived by using the radiation in the upper atmosphere, on the basis of Landsat 8 images. Then, a clustering analysis, ternary triangular chart (TTC), and a multivariate statistical analysis were applied to ascertain the relationship between the fractions in each pixel and the land surface brightness temperature (LSBT). The hypsometric TTC, as well as the geographical distribution features of the LSBT, revealed that the changes in LSBT were associated with the high fractions of impervious surfaces (or vegetation), in addition to the temperature distribution differences across locations with varying land-cover types. The data fitting results showed that the comprehensive endmember fractions of V-I-S explained 98.6% of fluctuating LSBT, and the impervious surface fraction had a positive impact on the LSBT, whereas the fraction of vegetation had a negative impact on the LSBT. View Full-Text
Keywords: ternary triangular chart (TTC); sub-pixel unmixing; multiple endmember spectral mixture analysis (MESMA); Landsat 8; land surface brightness temperature (LSBT) ternary triangular chart (TTC); sub-pixel unmixing; multiple endmember spectral mixture analysis (MESMA); Landsat 8; land surface brightness temperature (LSBT)
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Chen, T.; Zhang, X.; Niu, R. The Relationship between Urban Land Surface Material Fractions and Brightness Temperature Based on MESMA. Remote Sens. 2017, 9, 532.

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