A spatial downscaling approach for the SMAP passive surface soil moisture product using random forest regression

doi:10.1016/j.jhydrol.2018.06.081

CORC > 成都山地灾害与环境研究所 > 中国科学院水利部成都山地灾害与环境研究所 > 数字山地与遥感应用中心

	A spatial downscaling approach for the SMAP passive surface soil moisture product using random forest regression
	Zhao, Wei1 ; Sanchez, Nilda 2; Lu, Hui 3; Li, Ainong1
刊名	JOURNAL OF HYDROLOGY
	2018-08-01
卷号	563 页码:1009-1024
关键词	Downscaling SMAP MODIS Surface soil moisture Random forest Validation
ISSN号	0022-1694
DOI	10.1016/j.jhydrol.2018.06.081
通讯作者	Li, Ainong
产权排序	1
英文摘要	The 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.
电子版国际标准刊号	1879-2707
语种	英语
出版者	ELSEVIER SCIENCE BV
WOS记录号	WOS:000441492700081
内容类型	期刊论文
源URL	[http://ir.imde.ac.cn/handle/131551/23742]
专题	成都山地灾害与环境研究所_数字山地与遥感应用中心
通讯作者	Li, Ainong
作者单位	1.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
推荐引用方式 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.