Spatially Disaggregating Satellite Land Surface Temperature With a Nonlinear Model Across Agricultural Areas

doi:10.1029/2019JG005227

	Spatially Disaggregating Satellite Land Surface Temperature With a Nonlinear Model Across Agricultural Areas
	Liu, Kai 1; Wang, Shudong 2; Li, Xueke 3; Wu, Taixia 4,5
刊名	JOURNAL OF GEOPHYSICAL RESEARCH-BIOGEOSCIENCES
	2019-11-06
页码	20
ISSN号	2169-8953
DOI	10.1029/2019JG005227
通讯作者	Wang, Shudong(wangsd@radi.ac.cn)
英文摘要	Accurate remotely sensed land surface temperature (LST) is a promising tool for predicting surface evapotranspiration (ET). The spatial resolution of commonly existing daily satellite products (i.e., Moderate Resolution Imaging Spectroradiometer [MODIS] LST) is similar to 1 km, which remains relatively low for used in estimating ET. This paper developed a model that disaggregates similar to 1-km spatial resolution MODIS-derived LST data to fine spatial resolutions of 250 m. The proposed model was achieved by using a spatial and temporal nonlinear strategy that contains the predictor variables of the Bowen ratio, the photochemical reflectance index, and the normalized difference vegetation index. The proposed disaggregation model was assessed mainly at two agriculture sites, including the Heihe River Basin in China and the Walnut Creek Watershed in the United States, during the growing seasons. The assessment procedure was conducted at both the field scale and the image scale in terms of disaggregated LST and ET. The statistical results demonstrated that the proposed model produced 250-m LST and ET that matched better with the observed values and achieved more accurate LST and ET relative to other reference ones. Our study shows that surface moisture status and vegetation physiological dynamic are important factors in improving the LST disaggregation over the agriculture region. The results of this study have the potential to improve water resource management and sustainable water use.
资助项目	National Natural Science Foundation of China[41671362] ; Fundamental Research Funds for the Central Universities[2017B20514] ; Fundamental Research Funds for the Central Universities[2017B05114]
WOS关键词	INDUCED CHLOROPHYLL FLUORESCENCE ; WATER-STRESS DETECTION ; VEGETATION INDEX ; DAILY EVAPOTRANSPIRATION ; EDDY COVARIANCE ; REGIONAL-SCALE ; SOIL-MOISTURE ; MODIS ; RESOLUTION ; ENERGY
WOS研究方向	Environmental Sciences & Ecology ; Geology
语种	英语
出版者	AMER GEOPHYSICAL UNION
WOS记录号	WOS:000494590500001
资助机构	National Natural Science Foundation of China ; Fundamental Research Funds for the Central Universities
内容类型	期刊论文
源URL	[http://ir.igsnrr.ac.cn/handle/311030/131978]
专题	中国科学院地理科学与资源研究所
通讯作者	Wang, Shudong
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.Chinese Acad Sci, Inst Remote Sensing & Digital Earth, Beijing, Peoples R China 3.Univ Connecticut, Dept Geog, Storrs, CT USA 4.Hohai Univ, Minist Educ, Key Lab Integrated Regulat & Resource Dev Shallow, Nanjing, Jiangsu, Peoples R China 5.Hohai Univ, Earth Sci & Engn Sch, Nanjing, Jiangsu, Peoples R China
推荐引用方式 GB/T 7714	Liu, Kai,Wang, Shudong,Li, Xueke,et al. Spatially Disaggregating Satellite Land Surface Temperature With a Nonlinear Model Across Agricultural Areas[J]. JOURNAL OF GEOPHYSICAL RESEARCH-BIOGEOSCIENCES,2019:20.
APA	Liu, Kai,Wang, Shudong,Li, Xueke,&Wu, Taixia.(2019).Spatially Disaggregating Satellite Land Surface Temperature With a Nonlinear Model Across Agricultural Areas.JOURNAL OF GEOPHYSICAL RESEARCH-BIOGEOSCIENCES,20.
MLA	Liu, Kai,et al."Spatially Disaggregating Satellite Land Surface Temperature With a Nonlinear Model Across Agricultural Areas".JOURNAL OF GEOPHYSICAL RESEARCH-BIOGEOSCIENCES (2019):20.