DOI: 10.1175/JCLI-D-11-00319.1
Scopus记录号: 2-s2.0-84871791989
论文题名: Robust identification of global greening phase patterns from remote sensing vegetation products
作者: Dahlke C. ; Loew A. ; Reick C.
刊名: Journal of Climate
ISSN: 8948755
出版年: 2012
卷: 25, 期: 23 起始页码: 8289
结束页码: 8307
语种: 英语
Scopus关键词: Analysis method
; Confidence levels
; Data sets
; Global greening
; Global scale
; Phase dynamics
; Phase patterns
; Photosynthetically active radiation
; Robust algorithm
; Robust identification
; Seasonal cycle
; Seasonality
; Spatiotemporal patterns
; Temporal and spatial dynamics
; Terrestrial biosphere
; Vegetation dynamics
; Vegetation greening
; Vegetation model
; Dynamics
; Time series
; Vegetation
; Remote sensing
; algorithm
; annual variation
; comparative study
; detection method
; identification method
; photosynthetically active radiation
; remote sensing
; seasonality
; time series analysis
; vegetation cover
英文摘要: The fraction of absorbed photosynthetically active radiation (fAPAR) is an essential diagnostic variable to investigate the temporal and spatial dynamics of the terrestrial biosphere. The present study provides a new method to assess global vegetation greening phase dynamics, derived from fAPAR time series from four different remote sensing products. A robust algorithm is developed to detect intra-annual greening phase patterns and derive seasonality patterns of vegetation dynamics at the global scale. The comparison of four independent remote sensing datasets shows significantly consistent global spatiotemporal patterns at the 95% confidence level. Regions where the remote sensing datasets show consistent results, as well as regions where at least one of the used remote sensing datasets deviates, can be identified. The derived global greening phase dataset and analysis method provides a solid framework for the evaluation of global vegetation models. © 2012 American Meteorological Society. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/52131
Appears in Collections: 气候变化事实与影响
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作者单位: Max Planck Institute for Meteorology, Hamburg, Germany
Recommended Citation:
Dahlke C.,Loew A.,Reick C.. Robust identification of global greening phase patterns from remote sensing vegetation products[J]. Journal of Climate,2012-01-01,25(23)