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Sensors 2017, 17(4), 744; doi:10.3390/s17040744

Downscaling Land Surface Temperature in Complex Regions by Using Multiple Scale Factors with Adaptive Thresholds

1
School of Earth Science and Engineering, Hohai University, 8 Buddha City West Road, Nanjing 210098, China
2
College of Natural Resources and Environment, Chizhou University, No.199 Muzhi Road, Chizhou 247000, China
*
Author to whom correspondence should be addressed.
Academic Editors: Changshan Wu and Shawn (Shixiong) Hu
Received: 5 January 2017 / Revised: 29 March 2017 / Accepted: 30 March 2017 / Published: 1 April 2017
View Full-Text   |   Download PDF [6080 KB, uploaded 1 April 2017]   |  

Abstract

Many downscaling algorithms have been proposed to address the issue of coarse-resolution land surface temperature (LST) derived from available satellite-borne sensors. However, few studies have focused on improving LST downscaling in urban areas with several mixed surface types. In this study, LST was downscaled by a multiple linear regression model between LST and multiple scale factors in mixed areas with three or four surface types. The correlation coefficients (CCs) between LST and the scale factors were used to assess the importance of the scale factors within a moving window. CC thresholds determined which factors participated in the fitting of the regression equation. The proposed downscaling approach, which involves an adaptive selection of the scale factors, was evaluated using the LST derived from four Landsat 8 thermal imageries of Nanjing City in different seasons. Results of the visual and quantitative analyses show that the proposed approach achieves relatively satisfactory downscaling results on 11 August, with coefficient of determination and root-mean-square error of 0.87 and 1.13 °C, respectively. Relative to other approaches, our approach shows the similar accuracy and the availability in all seasons. The best (worst) availability occurred in the region of vegetation (water). Thus, the approach is an efficient and reliable LST downscaling method. Future tasks include reliable LST downscaling in challenging regions and the application of our model in middle and low spatial resolutions. View Full-Text
Keywords: land surface temperature; downscaling; adaptive threshold; multi-scale factors land surface temperature; downscaling; adaptive threshold; multi-scale factors
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Yang, Y.; Li, X.; Pan, X.; Zhang, Y.; Cao, C. Downscaling Land Surface Temperature in Complex Regions by Using Multiple Scale Factors with Adaptive Thresholds. Sensors 2017, 17, 744.

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