Filling Gaps of Monthly Terra/MODIS Daytime Land Surface Temperature Using Discrete Cosine Transform Method

doi:10.3390/rs12030361

	Filling Gaps of Monthly Terra/MODIS Daytime Land Surface Temperature Using Discrete Cosine Transform Method
	Liu, Hengzi 1,4; Lu, Ning 1,2; Jiang, Hou 1,4; Qin, Jun 3; Yao, Ling 1,2
刊名	REMOTE SENSING
	2020-02-01
卷号	12 期号:3 页码:16
关键词	gaps filling land surface temperature discrete cosine transform penalized least square approach MODIS
DOI	10.3390/rs12030361
通讯作者	Lu, Ning(lvn@lreis.ac.cn)
英文摘要	Land surface temperature (LST) is a key parameter in geophysical fields. The Moderate Resolution Imaging Spectroradiometer (MODIS) onboard Terra provides an accurate LST dataset with global coverage and monthly series, but the monthly MODIS LST data are often obscured by clouds and other atmospheric disturbances and consequently exhibit significant data gaps at a global scale, resulting in a difficult interpretation of LST trends and climatological characteristics. In this paper, an effective and fast LST reconstruction method to fill data gaps in monthly MODIS LST is presented. The proposal combines the Discrete Cosine Transform (DCT) and the Penalized Least Square approach (PLS) together with the Generalized Cross-Validation (GCV) criterion. It depends only on the spatial high-frequency information from original LST estimates and allows a fast and automatic filling process without the help of any other ancillary data. To analyze its performance, the method is applied to fill data gaps on three continents with synthetic random missing values introduced as validation sets. The statistical evaluation shows that this method is capable of filling a large number of missing values in MODIS LST datasets with very high accuracy. In addition, the trend differences between the original LST and reconstructed LST have assessed the significance by computing 95% confidence intervals for a time series of trend differences is examined. Simulated experiments show that data gaps with large missing counts lead to significant differences in trend patterns and the patterns on validation sets are well estimated by this method, which confirms that the filling process of MODIS LST is necessary and favorable results can be produced for substantial data gaps by the DCT-PLS method.
资助项目	National Natural Science Foundation of China[41890854] ; National Natural Science Foundation of China[41971312] ; National Natural Science Foundation of China[41771380]
WOS关键词	MODIS ; RESOLUTION ; RETRIEVAL
WOS研究方向	Remote Sensing
语种	英语
出版者	MDPI
WOS记录号	WOS:000515393800020
资助机构	National Natural Science Foundation of China
内容类型	期刊论文
源URL	[http://ir.igsnrr.ac.cn/handle/311030/132575]
专题	中国科学院地理科学与资源研究所
通讯作者	Lu, Ning
作者单位	1.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing 100101, Peoples R China 2.Jiangsu Ctr Collaborat Innovat Geog Informat Reso, Nanjing 210023, Peoples R China 3.Chinese Acad Sci, Inst Tibetan Plateau Res, Key Lab Tibetan Environm Changes & Land Surface P, Beijing 100085, Peoples R China 4.Univ Chinese Acad Sci, Coll Resources & Environm, Beijing 100049, Peoples R China
推荐引用方式 GB/T 7714	Liu, Hengzi,Lu, Ning,Jiang, Hou,et al. Filling Gaps of Monthly Terra/MODIS Daytime Land Surface Temperature Using Discrete Cosine Transform Method[J]. REMOTE SENSING,2020,12(3):16.
APA	Liu, Hengzi,Lu, Ning,Jiang, Hou,Qin, Jun,&Yao, Ling.(2020).Filling Gaps of Monthly Terra/MODIS Daytime Land Surface Temperature Using Discrete Cosine Transform Method.REMOTE SENSING,12(3),16.
MLA	Liu, Hengzi,et al."Filling Gaps of Monthly Terra/MODIS Daytime Land Surface Temperature Using Discrete Cosine Transform Method".REMOTE SENSING 12.3(2020):16.