A Downscaling Method for Improving the Spatial Resolution of AMSR-E Derived Soil Moisture Product Based on MSG-SEVIRI Data

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 Downscaling Method for Improving the Spatial Resolution of AMSR-E Derived Soil Moisture Product Based on MSG-SEVIRI Data
	Zhao, Wei; Li, Ainong
刊名	REMOTE SENSING
	2013-12-01
卷号	5 期号:12 页码:6790-6811
关键词	soil moisture AMSR-E SEVIRI downscaling
ISSN号	2072-4292
通讯作者	无
英文摘要	Soil moisture is a vital parameter in various land surface processes, and microwave remote sensing is widely used to estimate regional soil moisture. However, the application of the retrieved soil moisture data is restricted by its coarse spatial resolution. To overcome this weakness, many methods were proposed to downscale microwave soil moisture data. The traditional method is the microwave-optical/IR synergistic approach, in which land surface temperature (LST), vegetation index and surface albedo are key parameters. However, due to the uncertainty in absolute LST estimation, this approach is partly dependent on the accuracy of LST estimation. To eliminate the impacts of LST estimation, an improved downscaling method is proposed in this study to downscale Advanced Microwave Scanning Radiometer on the Earth Observing System (AMSR-E) Land Parameter Retrieval Model (LPRM) soil moisture product with visible and thermal data of Meteosat Second Generation (MSG)-Spinning Enhanced Visible and Infrared Imager (SEVIRI). Two temperature temporal variation parameters related to soil moisture, including mid-morning rising rate and daily maximum temperature time, are introduced in the proposed method to replace LST. The proposed method and the traditional method are both applied to the Iberian Peninsula area for July and August 2007. Comparison of the two results shows that the coefficient of determination (R-squared) has an average improvement of 0.08 and the root mean square error has a systematic decrease. The downscaled soil moisture by the proposed method was validated by REMEDHUS soil moisture network in the study area, and site specific validation gets poor correlation between the two datasets because of the low spatial representativeness of site measurement for one MSG-SEVIRI pixel. Although the comparisons at 15 km and network scale show an improvement over the site specific comparison, it is found that the downscaling method systematically degrades the accuracy in soil moisture data, with a R-squared of 0-0.4 and 0.218 for the downscaled data set against 0.7-0.8 and 0.571 for AMSR-E data at 15 km scale and the network scale respectively.
WOS标题词	Science & Technology ; Technology
类目[WOS]	Remote Sensing
研究领域[WOS]	Remote Sensing
关键词[WOS]	THERMAL-INFRARED DATA ; REGIONAL EVAPOTRANSPIRATION ; SURFACE-TEMPERATURE ; TEMPORAL EVOLUTION ; MODIS PRODUCTS ; SMAP MISSION ; VALIDATION ; RETRIEVAL ; BASIN ; DISAGGREGATION
收录类别	SCI
原文出处	http://www.mdpi.com/2072-4292/5/12/6790
语种	英语
WOS记录号	WOS:000330318900029
内容类型	期刊论文
源URL	[http://ir.imde.ac.cn/handle/131551/8323]
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
作者单位	Chinese Acad Sci, Inst Mt Hazards & Environm, Chengdu 610041, Peoples R China
推荐引用方式 GB/T 7714	Zhao, Wei,Li, Ainong. A Downscaling Method for Improving the Spatial Resolution of AMSR-E Derived Soil Moisture Product Based on MSG-SEVIRI Data[J]. REMOTE SENSING,2013,5(12):6790-6811.
APA	Zhao, Wei,&Li, Ainong.(2013).A Downscaling Method for Improving the Spatial Resolution of AMSR-E Derived Soil Moisture Product Based on MSG-SEVIRI Data.REMOTE SENSING,5(12),6790-6811.
MLA	Zhao, Wei,et al."A Downscaling Method for Improving the Spatial Resolution of AMSR-E Derived Soil Moisture Product Based on MSG-SEVIRI Data".REMOTE SENSING 5.12(2013):6790-6811.