IGSNRR OpenIR
Net Surface Shortwave Radiation Retrieval Using Random Forest Method With MODIS/AQUA Data
Ying, Wangmin1,2; Wu, Hua1,2,3; Li, Zhao-Liang4,5
2019-07-01
Source PublicationIEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING
ISSN1939-1404
Volume12Issue:7Pages:2252-2259
Corresponding AuthorWu, Hua(wuhua@igsnrr.ac.cn)
AbstractThe net surface shortwave radiation (NSSR) at the Earth's surface drives evapotranspiration, photosynthesis, and other physical and biological processes. The primary objective of this study is to estimate NSSR in all sky conditions by using narrowband data of the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument onboard the AQUA satellite. The random forest (RF) machine learning method for retrieving NSSR was developed with MODerate resolution atmospheric TRANsmission model (MODTRAN 5) simulated data. The bias, root mean square error (RMSE), and R-2 for the training dataset of the model are 0.04 W m(-2), 2.03 W m(-2), and 1.00, respectively; for testing data, these values are 0.53 W m(-2), 5.50 W m(-2), and 1.00, respectively. Note that the proposed method is better than the traditional method (RMSE 7.29 W m(-2)) with MODTRAN data, and the sky conditions (clear and cloudy) do not need to be distinguished in the RF method. Seven in situ measurements of the Surface Radiation (SURFRAD) observation network were used to validate the estimated NSSR with MODIS/AQUA data using the proposed RF method, and the bias, RMSE, and R2 of the comparison are -8.4 W m(-2), 76.8 W m(-2), and 0.91, respectively. Approximately 70% of the absolute difference of all the samples is below 50 W m(-2). Considering its concise process and relatively improved accuracy, both in regard to model development and validation, it can be concluded that the retrieval of NSSR with RF will be an efficient and feasible method in the future.
KeywordMODerate resolution atmospheric TRANsmission model (MODTRAN) Moderate Resolution Imaging Spectroradiometer (MODIS)/AQUA net surface shortwave radiation random forest remote sensing
DOI10.1109/JSTARS.2019.2905584
WOS KeywordENERGY-BALANCE ; FLUX
Indexed BySCI
Language英语
Funding ProjectNational Key R&D Program of China[2018YFB0504800] ; Strategic Priority Research Program of the Chinese Academy of Sciences[XDA20030302] ; National Natural Science Foundation of China[41871267]
Funding OrganizationNational Key R&D Program of China ; Strategic Priority Research Program of the Chinese Academy of Sciences ; National Natural Science Foundation of China
WOS Research AreaEngineering ; Physical Geography ; Remote Sensing ; Imaging Science & Photographic Technology
WOS SubjectEngineering, Electrical & Electronic ; Geography, Physical ; Remote Sensing ; Imaging Science & Photographic Technology
WOS IDWOS:000480354800024
PublisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Citation statistics
Cited Times:1[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.igsnrr.ac.cn/handle/311030/68862
Collection中国科学院地理科学与资源研究所
Corresponding AuthorWu, Hua
Affiliation1.Chinese Acad Sci, IGSNRR, State Key Lab Resources & Environm Informat Syst, Beijing 100101, Peoples R China
2.UCAS, Beijing 100049, Peoples R China
3.Jiangsu Ctr Collaborat Innovat Geog Informat Reso, Nanjing 210023, Jiangsu, Peoples R China
4.Chinese Acad Agr Sci, Inst Agr Resources & Reg Planning, Minist Agr, Key Lab Agriinformat, Beijing 100081, Peoples R China
5.CNRS, UdS, ICube, F-67412 Illkirch Graffenstaden, France
Recommended Citation
GB/T 7714
Ying, Wangmin,Wu, Hua,Li, Zhao-Liang. Net Surface Shortwave Radiation Retrieval Using Random Forest Method With MODIS/AQUA Data[J]. IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING,2019,12(7):2252-2259.
APA Ying, Wangmin,Wu, Hua,&Li, Zhao-Liang.(2019).Net Surface Shortwave Radiation Retrieval Using Random Forest Method With MODIS/AQUA Data.IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING,12(7),2252-2259.
MLA Ying, Wangmin,et al."Net Surface Shortwave Radiation Retrieval Using Random Forest Method With MODIS/AQUA Data".IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING 12.7(2019):2252-2259.
Files in This Item:
There are no files associated with this item.
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Ying, Wangmin]'s Articles
[Wu, Hua]'s Articles
[Li, Zhao-Liang]'s Articles
Baidu academic
Similar articles in Baidu academic
[Ying, Wangmin]'s Articles
[Wu, Hua]'s Articles
[Li, Zhao-Liang]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Ying, Wangmin]'s Articles
[Wu, Hua]'s Articles
[Li, Zhao-Liang]'s Articles
Terms of Use
No data!
Social Bookmark/Share
All comments (0)
No comment.
 

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.