title: [Evaluation of remote sensing extraction methods for vegetation phenology based on flux tower net ecosystem carbon exchange data].
abstract: Taking the vegetation phenological metrics derived from the net ecosystem carbon exchange (NEE) data of 72 flux towers in North America as the references, a comprehensive evaluation was conducted on the three typical classes of remote sensing extraction methods (threshold method, moving average method, and function fitting method) for vegetation phenology from the aspects of feasibility and accuracy. The results showed that the local midpoint threshold method had the highest feasibility and accuracy for extracting vegetation phenology, followed by the first derivative method based on fitted Logistic function. The feasibility and accuracy of moving average method were determined by the moving window size. As for the MODJS 16 d composited time-series normalized difference vegetation index (NDVI), the moving average method had preferable performance when the window size was set as 15. The global threshold method performed quite poor in the feasibility and accuracy. Though the values of the phenological metrics extracted by the curvature change rate method based on fitted Logistic function and the corresponding ones derived from NEE data had greater differences, there existed a strong correlation between them, indicating that the vegetation phenological metrics extracted by the curvature change rate method could reflect the real temporal and spatial variations of vegetation phenology.
authors.affiliation: State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing, China. minjie_2009@163.com
authors.forename: Min-Jie
authors.initials: MJ
authors.lastname: Mou
authors.forename: Wen-Quan
authors.initials: WQ
authors.lastname: Zhu
authors.forename: Ling-Li
authors.initials: LL
authors.lastname: Wang
authors.forename: Ying-Jun
authors.initials: YJ
authors.lastname: Xu
authors.forename: Jian-Hong
authors.initials: JH
authors.lastname: Liu
mesh_terms: D002244:Carbon / Q000378:metabolism*; D057486:Carbon Cycle; D002980:Climate; D003247:Conservation of Natural Resources; D003625:Data Collection; D017753:Ecosystem; D004784:Environmental Monitoring / Q000379:methods*; D063245:Plant Development; D010944:Plants / Q000378:metabolism*; D058998:Remote Sensing Technology
chemical_list: D002244:Carbon