IGSNRR OpenIR
Retrievals of all-weather daytime air temperature from MODIS products
Zhu, Wenbin; Lu, Aifeng; Jia, Shaofeng1; Yan, Jiabao; Mahmood, Rashid
2017-02-01
Source PublicationREMOTE SENSING OF ENVIRONMENT
ISSN0034-4257
Volume189Pages:152-163
Corresponding AuthorJia, Shaofeng(jiasf@igsnrr.ac.cn)
AbstractIt is well known that remote sensing techniques hold the potential to explore the spatial estimation of air temperature (T-a) with fine spatial and temporal resolution across the world. However, because of the complex interaction of land-atmosphere systein and the contamination of cloud cover, the retrieval of daytime T-a exclusively from remote sensing data is still far from straight forward, especially under cloudy sky conditions. In this paper, we presented a simple parameterization scheme of daytime T-a under all-weather conditions entirely based on Moderate Resolution Imaging Spectroradiometer (MODIS) products. To evaluate its applicability, the scheme was demonstrated in two regions with totally different geomorphological and climatic conditions, the east part of the Qaidam Basin (EQB) in China and the Southern Great Plains (SGP) in the United States of America. The instantaneous T-a under clear sky conditions (T-a,T-clear) was determined as the average of near surface air temperature (T-a(s)) retrieved from MOD07_L2 product and land surface temperature (T-s) retrieved from MOD06_12 product. Then a regression model between T-a,T-clear and T-s was established, and the instantaneous Ta under cloudy sky conditions (T-a,T-cloudy) was estimated by applying the regression model to T-s retrieved under cloudy sky conditions. The results showed that the averaging parameterization scheme has significantly improved the accuracy of T-a,T-clear retrievals with MAE = 1.95 degrees C, RMSE = 2.50 degrees C, and B = 0.02 in the EQB, and MAE = 2.02 degrees C, RMSE = 2.56 degrees C, and B = 0.01 in the SGP. The T-a,T-cloudy estimates also showed good agreement with T-a observations in both regions with a correlation coefficient (r) higher than 0.91. The values of RMSE calculated for the EQB and SGP were 3.42 degrees C and 2.91 degrees C, respectively. The accuracy of both T-a,T-clear and T-a,T-cloudy estimates has reached a level comparable with other traditional statistical approaches that adopt ancillary T-a measurements as training dataset. Therefore, it is feasible to estimate daytime T-a under all-weather conditions entirely based on MODIS products. (C) 2016 Elsevier Inc. All rights reserved.
KeywordAir temperature Land surface temperature Atmospheric temperature profile Adiabatic lapse rate MODIS Remote sensing
DOI10.1016/j.rse.2016.11.011
WOS KeywordSOUTHERN GREAT-PLAINS ; REMOTE-SENSING DATA ; CLEAR-SKY DAYS ; SURFACE-TEMPERATURE ; DAILY MAXIMUM ; ENVIRONMENTAL VARIABLES ; SOIL-MOISTURE ; AVHRR DATA ; LST DATA ; EVAPOTRANSPIRATION
Indexed BySCI
Language英语
Funding ProjectNational Science and Technology Support Program of China[2012BAC09B05] ; National Natural Sciences Foundation of China[90302009]
Funding OrganizationNational Science and Technology Support Program of China ; National Natural Sciences Foundation of China
WOS Research AreaEnvironmental Sciences & Ecology ; Remote Sensing ; Imaging Science & Photographic Technology
WOS SubjectEnvironmental Sciences ; Remote Sensing ; Imaging Science & Photographic Technology
WOS IDWOS:000393005400012
PublisherELSEVIER SCIENCE INC
Citation statistics
Cited Times:22[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.igsnrr.ac.cn/handle/311030/64930
Collection中国科学院地理科学与资源研究所
Corresponding AuthorJia, Shaofeng
Affiliation1.Chinese Acad Sci, Key Lab Water Cycle & Related Land Surface Proc, Beijing 100101, Peoples R China
2.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China
Recommended Citation
GB/T 7714
Zhu, Wenbin,Lu, Aifeng,Jia, Shaofeng,et al. Retrievals of all-weather daytime air temperature from MODIS products[J]. REMOTE SENSING OF ENVIRONMENT,2017,189:152-163.
APA Zhu, Wenbin,Lu, Aifeng,Jia, Shaofeng,Yan, Jiabao,&Mahmood, Rashid.(2017).Retrievals of all-weather daytime air temperature from MODIS products.REMOTE SENSING OF ENVIRONMENT,189,152-163.
MLA Zhu, Wenbin,et al."Retrievals of all-weather daytime air temperature from MODIS products".REMOTE SENSING OF ENVIRONMENT 189(2017):152-163.
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