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Remote Sens. 2019, 11(3), 336; https://doi.org/10.3390/rs11030336

An Effective Similar-Pixel Reconstruction of the High-Frequency Cloud-Covered Areas of Southwest China

1,2,3,*
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4
,
1,2,3
,
1,2,3
,
1,2,3
and
1,2,3
1
Research Base of Karst Eco-environments at Nanchuan in Chongqing, Ministry of Nature Resources, School of Geographical Sciences, Southwest University, Chongqing 400715, China
2
Chongqing Jinfo Mountain Field Scientific Observation and Research Station for Kaster Ecosystem, School of Geographical Sciences, Southwest University, Chongqing 400715, China
3
Chongqing Engineering Research Center for Remote Sensing Big Data Application, School of Geographical Sciences, Southwest University, Chongqing 400715, China
4
Heihe Remote Sensing Experimental Research Station, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, 320 Donggang West Road, Lanzhou 730000, China
*
Author to whom correspondence should be addressed.
Received: 22 January 2019 / Accepted: 6 February 2019 / Published: 8 February 2019
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Abstract

With advantages of multispatial resolutions, a high retrieval accuracy, and a high temporal resolution, the satellite-derived land surface temperature (LST) products are very important LST sources. However, the greatest barrier to their wide application is the invalid values produced by large quantities of cloudy pixels, especially for regions frequently swathed in clouds. In this study, an effective method based on the land energy balance theory and similar pixels (SP) method was developed to reconstruct the LSTs over cloudy pixels for the widely used MODIS LST (MOD11A1). The southwest region of China was selected as the study area, where extreme drought has frequently occurred in recent years in the context of global climate change and which commonly exhibits cloudy and foggy weather. The validation results compared with in situ LSTs showed that the reconstructed LSTs have an average error < 1.00 K (0.57 K at night and −0.14 K during the day) and an RMSE < 3.20 K (1.90 K at night and 3.16 K in the daytime). The experiment testing the SP interpolation indicated that the spatial structure of the LST has a greater effect on the SP performance than the size of the data-missing area, which benefits the LST reconstruction in the area frequently covered by large clouds. View Full-Text
Keywords: cloudy pixels; reconstruction; land surface temperature; MODIS; land energy balance cloudy pixels; reconstruction; land surface temperature; MODIS; land energy balance
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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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Yu, W.; Tan, J.; Ma, M.; Li, X.; She, X.; Song, Z. An Effective Similar-Pixel Reconstruction of the High-Frequency Cloud-Covered Areas of Southwest China. Remote Sens. 2019, 11, 336.

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