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Spring green-up phenology products derived from MODIS NDVI and EVI: Intercomparison, interpretation and validation using National Phenology Network and AmeriFlux observations
Peng, Dailiang1,2; Wu, Chaoyang3; Li, Cunjun4; Zhang, Xiaoyang5; Liu, Zhengjia6; Ye, Huichun1,2; Luo, Shezhou1; Liu, Xinjie1; Hug, Yong7; Fang, Bin8
2017-06-01
Source PublicationECOLOGICAL INDICATORS
ISSN1470-160X
Volume77Pages:323-336
Corresponding AuthorWu, Chaoyang(liefery@I63.com)
AbstractAdvances in the timing of spring green-up date are a typical response of vegetation global change. Longterm observations of plant phenology have been used to track vegetation response to climate change. Normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI) have been the most commonly used indicators in reconstructing spring green-up dates from remote sensing over the past several decades. The Moderate Resolution Imaging Spectroradiometer (MODIS) based phenology time series from NDVI and EVI with an enhanced TIMESAT algorithm are the two operational phenology products developed recently with sun-sensor geometry corrected reflectance. However, a comprehensive intercomparison and evaluation of these two spring green-up datasets using intensive ground observations have not been conducted, limiting their applications in regional interpretation of land surface phenology. Therefore, we used 455 ground observations from USA National Phenology Network (NPN) and 106 observations from 21 AmeriFlux sites to assess and validate the spring green-up dates for United States for 2000-2013. Our results indicate that the spring green-up dates from NDVI and EVI showed a good agreement in eastern United States, while substantial differences (70 days) were found in western and southern areas. Ground observations generally had a significant correlation (p < 0.01) with the two MODIS spring green-up dates, especially for deciduous broadleaf forests with root mean square error (RMSE) of 12 days and 16 days when compared with USA-NPN and AmeriFlux observations, respectively. Spring green-up dates from EVI overall showed a better relationship and a lower RMSE in reference to both USA-NPN and AmeriFlux observations than NDVI-based spring green-up dates. Our results highlight the importance of a rigorous validation of remote sensing products to better understand their limitations in operational applications. (C) 2017 Elsevier Ltd. All rights reserved.
KeywordPhenology Normalized difference vegetation index Enhanced vegetation index National Phenology Network AmeriFlux GPP
DOI10.1016/j.ecolind.2017.02.024
WOS KeywordLAND-SURFACE PHENOLOGY ; VEGETATION PHENOLOGY ; SATELLITE DATA ; TIME-SERIES ; INTERANNUAL VARIABILITY ; CLIMATE-CHANGE ; UNITED-STATES ; CARBON-BUDGET ; FOREST ; FLUXNET
Indexed BySCI
Language英语
Funding ProjectNational Key Research and Development Program of China[2016YFB0501501] ; National Natural Science Foundation of China[41571423] ; Youth Innovation Promotion Association, Chinese Academy of Sciences[Y4YR1300QM] ; SLRSS[16ZY-03] ; Strategic Priority Research Program (B) of the Chinese Academy of Sciences[XDB03030406]
Funding OrganizationNational Key Research and Development Program of China ; National Natural Science Foundation of China ; Youth Innovation Promotion Association, Chinese Academy of Sciences ; SLRSS ; Strategic Priority Research Program (B) of the Chinese Academy of Sciences
WOS Research AreaBiodiversity & Conservation ; Environmental Sciences & Ecology
WOS SubjectBiodiversity Conservation ; Environmental Sciences
WOS IDWOS:000406435800034
PublisherELSEVIER SCIENCE BV
Citation statistics
Cited Times:15[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.igsnrr.ac.cn/handle/311030/62543
Collection中国科学院地理科学与资源研究所
Corresponding AuthorWu, Chaoyang
Affiliation1.Chinese Acad Sci, Inst Remote Sensing & Digital Earth, Key Lab Digital Earth Sci, Beijing 100094, Peoples R China
2.Key Lab Earth Observat, Sanya 572029, Hainan, Peoples R China
3.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China
4.Beijing Res Ctr Informat Technol Agr, Beijing 100097, Peoples R China
5.South Dakota State Univ, Geospatial Sci Ctr Excellence, Brookings, SD 57007 USA
6.Chinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote Sensing Sci, Beijing, Peoples R China
7.Chongqing Inst Surveying & Planning Land Resource, Chongqing 400020, Peoples R China
8.Columbia Univ, Dept Earth & Environm Engn, New York, NY 10027 USA
Recommended Citation
GB/T 7714
Peng, Dailiang,Wu, Chaoyang,Li, Cunjun,et al. Spring green-up phenology products derived from MODIS NDVI and EVI: Intercomparison, interpretation and validation using National Phenology Network and AmeriFlux observations[J]. ECOLOGICAL INDICATORS,2017,77:323-336.
APA Peng, Dailiang.,Wu, Chaoyang.,Li, Cunjun.,Zhang, Xiaoyang.,Liu, Zhengjia.,...&Fang, Bin.(2017).Spring green-up phenology products derived from MODIS NDVI and EVI: Intercomparison, interpretation and validation using National Phenology Network and AmeriFlux observations.ECOLOGICAL INDICATORS,77,323-336.
MLA Peng, Dailiang,et al."Spring green-up phenology products derived from MODIS NDVI and EVI: Intercomparison, interpretation and validation using National Phenology Network and AmeriFlux observations".ECOLOGICAL INDICATORS 77(2017):323-336.
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