A Combination of TsHARP and Thin Plate Spline Interpolation for Spatial Sharpening of Thermal Imagery

There have been many studies and much attention paid to spatial sharpening for thermal imagery. Among them, TsHARP, based on the good correlation between vegetation index and land surface temperature (LST), is regarded as a standard technique because of its operational simplicity and effectiveness....

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Main Authors: Xuehong Chen, Wentao Li, Jin Chen, Yuhan Rao, Yasushi Yamaguchi
Format: Article
Language:English
Published: MDPI AG 2014-03-01
Series:Remote Sensing
Subjects:
Online Access:http://www.mdpi.com/2072-4292/6/4/2845
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spelling doaj-eed93416fa17402793b0dab8d1b9110d2020-11-24T22:46:45ZengMDPI AGRemote Sensing2072-42922014-03-01642845286310.3390/rs6042845rs6042845A Combination of TsHARP and Thin Plate Spline Interpolation for Spatial Sharpening of Thermal ImageryXuehong Chen0Wentao Li1Jin Chen2Yuhan Rao3Yasushi Yamaguchi4State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing 100875, ChinaState Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing 100875, ChinaState Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing 100875, ChinaState Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing 100875, ChinaGraduate School of Environmental Studies, Nagoya University, Nagoya 464-8601, JapanThere have been many studies and much attention paid to spatial sharpening for thermal imagery. Among them, TsHARP, based on the good correlation between vegetation index and land surface temperature (LST), is regarded as a standard technique because of its operational simplicity and effectiveness. However, as LST is affected by other factors (e.g., soil moisture) in the areas with low vegetation cover, these areas cannot be well sharpened by TsHARP. Thin plate spline (TPS) is another popular downscaling technique for surface data. It has been shown to be accurate and robust for different datasets; however, it has not yet been attempted in thermal sharpening. This paper proposes to combine the TsHARP and TPS methods to enhance the advantages of each. The spatially explicit errors of these two methods were firstly estimated in theory, and then the results of TPS and TsHARP were combined with the estimation of their errors. The experiments performed across various landscapes and data showed that the proposed combined method performs more robustly and accurately than TsHARP.http://www.mdpi.com/2072-4292/6/4/2845thermal sharpeningland surface temperatureTsHARPthin plate splineerror estimation
collection DOAJ
language English
format Article
sources DOAJ
author Xuehong Chen
Wentao Li
Jin Chen
Yuhan Rao
Yasushi Yamaguchi
spellingShingle Xuehong Chen
Wentao Li
Jin Chen
Yuhan Rao
Yasushi Yamaguchi
A Combination of TsHARP and Thin Plate Spline Interpolation for Spatial Sharpening of Thermal Imagery
Remote Sensing
thermal sharpening
land surface temperature
TsHARP
thin plate spline
error estimation
author_facet Xuehong Chen
Wentao Li
Jin Chen
Yuhan Rao
Yasushi Yamaguchi
author_sort Xuehong Chen
title A Combination of TsHARP and Thin Plate Spline Interpolation for Spatial Sharpening of Thermal Imagery
title_short A Combination of TsHARP and Thin Plate Spline Interpolation for Spatial Sharpening of Thermal Imagery
title_full A Combination of TsHARP and Thin Plate Spline Interpolation for Spatial Sharpening of Thermal Imagery
title_fullStr A Combination of TsHARP and Thin Plate Spline Interpolation for Spatial Sharpening of Thermal Imagery
title_full_unstemmed A Combination of TsHARP and Thin Plate Spline Interpolation for Spatial Sharpening of Thermal Imagery
title_sort combination of tsharp and thin plate spline interpolation for spatial sharpening of thermal imagery
publisher MDPI AG
series Remote Sensing
issn 2072-4292
publishDate 2014-03-01
description There have been many studies and much attention paid to spatial sharpening for thermal imagery. Among them, TsHARP, based on the good correlation between vegetation index and land surface temperature (LST), is regarded as a standard technique because of its operational simplicity and effectiveness. However, as LST is affected by other factors (e.g., soil moisture) in the areas with low vegetation cover, these areas cannot be well sharpened by TsHARP. Thin plate spline (TPS) is another popular downscaling technique for surface data. It has been shown to be accurate and robust for different datasets; however, it has not yet been attempted in thermal sharpening. This paper proposes to combine the TsHARP and TPS methods to enhance the advantages of each. The spatially explicit errors of these two methods were firstly estimated in theory, and then the results of TPS and TsHARP were combined with the estimation of their errors. The experiments performed across various landscapes and data showed that the proposed combined method performs more robustly and accurately than TsHARP.
topic thermal sharpening
land surface temperature
TsHARP
thin plate spline
error estimation
url http://www.mdpi.com/2072-4292/6/4/2845
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