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A spatial downscaling approach for the SMAP passive surface soil moisture product using random forest regression
Zhao, Wei1; Sanchez, Nilda2; Lu, Hui3; Li, Ainong1
2018-08-01
Source PublicationJOURNAL OF HYDROLOGY
ISSN0022-1694
Volume563Pages:1009-1024
SubtypeArticle
Contribution Rank1
AbstractThe low-resolution characteristic of passive microwave surface soil moisture (SSM) products greatly limits their application in many fields at regional or local scale. Aiming to overcome this limitation, a random forest (RF)-based downscaling approach was proposed in this study to disaggregate the Soil Moisture Active and Passive (SMAP) SSM product with the synergistic use of the Optical/Thermal infrared (TIR) observations from the Moderate-Resolution Imaging Spectro-radiometer (MODIS) onboard the Terra and Aqua satellites. The Iberian Peninsula was selected as the study area during the period from 2015 to 2016. First, the performance of the RF-based approach in building the SSM relationship model with surface variables (surface temperature, vegetation index, leaf area index, albedo, water index, solar factor, and elevation) was compared with that resulting from a widely used polynomial-based relationship model. Good agreement was achieved for the RF-based method with a correlation coefficient (R) above 0.95 and a mean root-mean-square deviation (RMSD) of 0.009 m(3)/m(3). Next, four data combinations (AM + Terra, AM + Aqua, PM + Terra, and PM + Aqua) were generated according to the different overpass times of the SMAP and MODIS observations, and they were separately used to derive the spatially downscaled SSM with the proposed RF-based downscaling method. Validation was performed with the in situ measurements from the REMEDHUS network of the University of Salamanca in Spain. The results indicated that all combinations have similar good performances with an unbiased root-mean-square difference (ubRMSD) of 0.022 m(3)/m(3), and the downscaled SSM at 1-km spatial resolution presented better accuracy while showing higher spatial heterogeneity and more detailed temporal pattern. Finally, the temporal changing pattern of the downscaled SSM was assessed with the precipitation time series from eight meteorological stations in the study area, and the rainfall effect on the variation of SSM was well tracked from its temporal changes. Overall, this study suggests that the proposed RF-based downscaling method is able to capture the variation of SSM well, and it should be helpful to improve the resolution of passive microwave soil moisture data and facilitate their applications at small scales.
KeywordDownscaling SMAP MODIS Surface soil moisture Random forest Validation
DOI10.1016/j.jhydrol.2018.06.081
Indexed BySCI
WOS KeywordREMEDHUS NETWORK SPAIN ; IN-SITU OBSERVATIONS ; HIGH-RESOLUTION ; AMSR-E ; INITIAL ASSESSMENT ; TIBETAN PLATEAU ; UNITED-STATES ; SMOS ; TEMPERATURE ; RETRIEVALS
Language英语
Funding ProjectNational Natural Science Foundation of China[41771409] ; National Natural Science Foundation of China[41631180] ; National Key Research and Development Program of China[2016YFA0600103] ; Hundred Young Talents Program of the Institute of Mountain Hazards and Environment[SDSQB-2015-02] ; Youth Innovation Promotion Association CAS[2016333] ; 135 Strategic Program of the Institute of Mountain Hazards and Environment, CAS[SDS-135-1708] ; Spanish Ministry of Economy and Competitiveness[ESP2015-67549-C3-3-R] ; Spanish Ministry of Economy and Competitiveness[ESP2017-89463-C3-3-R] ; Castilla y Leon Region Government[SA007U16] ; European Regional Development Fund (ERDF)
WOS Research AreaEngineering ; Geology ; Water Resources
WOS SubjectEngineering, Civil ; Geosciences, Multidisciplinary ; Water Resources
WOS IDWOS:000441492700081
Funding OrganizationNational Natural Science Foundation of China ; National Key Research and Development Program of China ; Hundred Young Talents Program of the Institute of Mountain Hazards and Environment ; Youth Innovation Promotion Association CAS ; 135 Strategic Program of the Institute of Mountain Hazards and Environment, CAS ; Spanish Ministry of Economy and Competitiveness ; Castilla y Leon Region Government ; European Regional Development Fund (ERDF)
PublisherELSEVIER SCIENCE BV
Citation statistics
Cited Times:18[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.imde.ac.cn/handle/131551/23743
Collection数字山地与遥感应用中心
Corresponding AuthorLi, Ainong
Affiliation1.Chinese Acad Sci, Inst Mt Hazards & Environm, Chengdu 610041, Sichuan, Peoples R China;
2.Univ Salamanca, Inst Hispano Luso Invest Agr, CIALE, Duero 12, Salamanca 37185, Villamayor, Spain;
3.Tsinghua Univ, Dept Earth Syst Sci, Key Lab Earth Syst Modelling, Minist Educ, Beijing, Peoples R China
First Author Affilication中国科学院水利部成都山地灾害与环境研究所
Corresponding Author Affilication中国科学院水利部成都山地灾害与环境研究所
Recommended Citation
GB/T 7714
Zhao, Wei,Sanchez, Nilda,Lu, Hui,et al. A spatial downscaling approach for the SMAP passive surface soil moisture product using random forest regression[J]. JOURNAL OF HYDROLOGY,2018,563:1009-1024.
APA Zhao, Wei,Sanchez, Nilda,Lu, Hui,&Li, Ainong.(2018).A spatial downscaling approach for the SMAP passive surface soil moisture product using random forest regression.JOURNAL OF HYDROLOGY,563,1009-1024.
MLA Zhao, Wei,et al."A spatial downscaling approach for the SMAP passive surface soil moisture product using random forest regression".JOURNAL OF HYDROLOGY 563(2018):1009-1024.
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