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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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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