Assessing a scheme of spatial-temporal thermal remote-sensing sharpening for estimating regional evapotranspiration

doi:10.1080/01431161.2018.1434326

	Assessing a scheme of spatial-temporal thermal remote-sensing sharpening for estimating regional evapotranspiration
	Liu, Kai 1; Su, Hongbo 2; Tian, Jing 1; Li, Xueke 3; Wang, Weimin 4; Yang, Lijun 4; Liang, Hong 4
刊名	INTERNATIONAL JOURNAL OF REMOTE SENSING
	2018
卷号	39 期号:10 页码:3111-3137
ISSN号	0143-1161
DOI	10.1080/01431161.2018.1434326
通讯作者	Tian, Jing(tianj.04b@igsnrr.ac.cn)
英文摘要	A high temporal frequency of high-resolution thermal data is required in regional evapotranspiration (ET) studies. In this article, a spatial-temporal thermal remote-sensing sharpening scheme, which can be used to perform temporally stable land surface temperature (LST) mapping with high spatial resolution and further facilitate the estimation of ET, is discussed in the context of the Soil Moisture Experiment of 2002. To demonstrate this scheme, relationships between LST and three remote-sensing parameters (normalized difference vegetation index (NDVI), fractional vegetation cover (FVC), and Bowen ratio) were first used in a thermal disaggregation procedure for retrieving LSTs at a 250-m scale. Then, the spatial and temporal adaptive reflectance fusion (STARFM) model was applied to the 250-m LSTs, producing LST data at a fine resolution of 60m and a fine temporal resolution of 1 day. Two remote-sensing-based energy balance models were then used to retrieve the ET at the Moderate Resolution Imaging Spectroradiometer overpass time respectively using 250- and 60-m LSTs. The results showed that the Bowen ratio-based LSTs were matched field observations better than did the LSTs obtained with the other two approaches (NDVI- and FVC-based) at the 250-m scale, and consequently produced 250-m ET mapping that better matched the observed tower-based values. When combined with the STARFM fusion model, the 250-m Bowen ratio-based LSTs produced more accurate time-series LSTs and ET at the 60-m scale. The Bowen ratio, which is more related to surface energy principles and the soil moisture variation, was effective in disaggregating LSTs and promoting the estimation of ET. Overall, sharpened LSTs using the combination of thermal disaggregation procedure and the STARFM fusion model could substantially improve remote-sensing-based ET estimates. Moreover, the STARFM model that can fuse LST from 250 to similar to 100m should be given more attention as long as the thermal disaggregation procedure that can disaggregate LST from 1000to 250m, provided that it contributed approximately 10.1% to further improving ET retrieval performance.
WOS关键词	LAND-SURFACE TEMPERATURE ; MONITORING DAILY EVAPOTRANSPIRATION ; ENERGY BALANCE METHOD ; MODIS DATA FUSION ; HEAT-FLUX ; TIME-SERIES ; MODEL ; RESOLUTION ; SCALE ; DISAGGREGATION
WOS研究方向	Remote Sensing ; Imaging Science & Photographic Technology
语种	英语
出版者	TAYLOR & FRANCIS LTD
WOS记录号	WOS:000427181200004
内容类型	期刊论文
源URL	[http://ir.igsnrr.ac.cn/handle/311030/57194]
专题	中国科学院地理科学与资源研究所
通讯作者	Tian, Jing
作者单位	1.Chinese Acad Sci, Inst Geog Sci & Nat Resources, Key Lab Water Cycle & Related Land Surface Proc, Beijing, Peoples R China 2.Florida Atlantic Univ, Dept Civil Environm & Geomat Engn, Boca Raton, FL 33431 USA 3.Univ Connecticut, Dept Geog, Mansfield, CT USA 4.Shenzhen Environm Monitoring Ctr, Shenzhen, Peoples R China
推荐引用方式 GB/T 7714	Liu, Kai,Su, Hongbo,Tian, Jing,et al. Assessing a scheme of spatial-temporal thermal remote-sensing sharpening for estimating regional evapotranspiration[J]. INTERNATIONAL JOURNAL OF REMOTE SENSING,2018,39(10):3111-3137.
APA	Liu, Kai.,Su, Hongbo.,Tian, Jing.,Li, Xueke.,Wang, Weimin.,...&Liang, Hong.(2018).Assessing a scheme of spatial-temporal thermal remote-sensing sharpening for estimating regional evapotranspiration.INTERNATIONAL JOURNAL OF REMOTE SENSING,39(10),3111-3137.
MLA	Liu, Kai,et al."Assessing a scheme of spatial-temporal thermal remote-sensing sharpening for estimating regional evapotranspiration".INTERNATIONAL JOURNAL OF REMOTE SENSING 39.10(2018):3111-3137.