A robust method for reconstructing global MODIS EVI time series on the Google Earth Engine

doi:10.1016/j.isprsjprs.2019.06.014

	A robust method for reconstructing global MODIS EVI time series on the Google Earth Engine
	Kong, Dongdong 1; Zhang, Yongqiang 2; Gu, Xihui 3; Wang, Dagang 1
刊名	ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING
	2019-09-01
卷号	155 页码:13-24
关键词	Remote sensing vegetation index EVI Time series reconstruction Whittaker Google Earth Engine
ISSN号	0924-2716
DOI	10.1016/j.isprsjprs.2019.06.014
通讯作者	Zhang, Yongqiang(zhangyq@igsnrr.ac.cn)
英文摘要	Obtaining high quality remote sensing vegetation index that is not noticeably affected by abiotic factors is critical for agricultural, ecological, climate and hydrological studies. Here we developed a computationally efficient and well-performed denoising method for reconstructing remote sensing vegetation indices, namely wWHd (weighted Whittaker with dynamic parameter lambda in spatial). The single parameter lambda is automatically estimated for every pixel by a multiple linear regression. Weights updating and the inherit nature of Whittaker make Whittaker robust for contaminations. We applied the wWHd on the Google Earth Engine (GEE) platform for reconstructing 500 m resolution enhanced vegetation index (EVI) time series from moderate-resolution imaging spectroradiometer (MODIS) at global scale and for the period of 2000-2017. To demonstrate its robustness, wWHd was compared with four well-known denoising methods, i.e. Fourier-based approach (Fourier), Savitzky-Golay filter (SG), Asymmetric Gaussian (AG) and double logistic (DL) at 16,000 randomly selected sites. All approaches were evaluated using two indices at each site: (1) root mean square error (RMSE) between observed best quality EVI and gap-filled EVI series, and (2) roughness of gap-filled EVI series. Results show that wWHd has an RMSE (indicating fidelity) of similar to 0.032, which is similar to Fourier and SG at similar to 90% sampled sites, but outperforms (similar to 0.02 less in the RMSE) AG and DL at similar to 45% and similar to 25% sampled sites. Among the four, wWHd has the lowest (best) roughness of similar to 0.003. These performances demonstrate that wWHd balances fidelity and roughness well. Another advantage is that the wWHd is computationally more efficient than others, and is currently the only one denoising method deployed on the GEE. Our results suggest that it is promising to use the proposed wWHd method for processing remote sensing vegetation indices with high spatiotemporal resolution and the reconstructed EVI product should be widely used by global community.
资助项目	IGSNRR Supporting Fund[YJRCPT2019-101] ; National Key Research and Development Program of China[2018YFA0605603] ; National Natural Science Foundation of China[41501037] ; International Program for Ph.D. Candidates, Sun Yat-Sen University ; CAS Pioneer Hundred Talents Program
WOS关键词	LAND-SURFACE PHENOLOGY ; VEGETATION INDEX ; HARMONIC-ANALYSIS ; TIBETAN PLATEAU ; NDVI ; TEMPERATURE ; PERFORMANCE ; EXTRACTION ; REGRESSION ; CHINA
WOS研究方向	Physical Geography ; Geology ; Remote Sensing ; Imaging Science & Photographic Technology
语种	英语
出版者	ELSEVIER
WOS记录号	WOS:000482526600002
资助机构	IGSNRR Supporting Fund ; National Key Research and Development Program of China ; National Natural Science Foundation of China ; International Program for Ph.D. Candidates, Sun Yat-Sen University ; CAS Pioneer Hundred Talents Program
内容类型	期刊论文
源URL	[http://ir.igsnrr.ac.cn/handle/311030/69735]
专题	中国科学院地理科学与资源研究所
通讯作者	Zhang, Yongqiang
作者单位	1.Sun Yan Sen Univ, Sch Geog & Planning, Guangzhou 510275, Guangdong, Peoples R China 2.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Water Cycle & Related Land Surface Proc, Beijing 100101, Peoples R China 3.China Univ Geosci, Sch Environm Studies, Dept Atmospher Sci, Wuhan 430074, Hubei, Peoples R China
推荐引用方式 GB/T 7714	Kong, Dongdong,Zhang, Yongqiang,Gu, Xihui,et al. A robust method for reconstructing global MODIS EVI time series on the Google Earth Engine[J]. ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING,2019,155:13-24.
APA	Kong, Dongdong,Zhang, Yongqiang,Gu, Xihui,&Wang, Dagang.(2019).A robust method for reconstructing global MODIS EVI time series on the Google Earth Engine.ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING,155,13-24.
MLA	Kong, Dongdong,et al."A robust method for reconstructing global MODIS EVI time series on the Google Earth Engine".ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING 155(2019):13-24.