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Title: Quantifying climatic influence on vegetation time series
Other Titles: Detection of climate components based on Ensemble Empirical Mode Decomposition (EEMD) and local significance testing
Authors: Hawinkel, Pieter
Swinnen, Else
Van Orshoven, Jos
Verbist, Bruno
Muys, Bart
Issue Date: Jun-2014
Publisher: University of Granada
Host Document: Proceedings ITISE 2014 International work-conference on Time Series pages:747-758
Conference: ITISE 2014 International work-conference on Time Series location:Granada, Spain date:25-27 June 2014
Abstract: Vegetation monitoring by satellite sensors has delivered 30-year time series of vegetation cover images over large areas. Decomposition of a pixel’s Vegeta-tion Index (VI) time series reveals the underlying processes of vegetation cover change at various time scales. Ensemble Empirical Mode Decomposition (EEMD) is a data-adaptive technique to isolate the effects of non-stationary recurrent climatic variability. To recognize significant patterns in the detected components, we propose a local significance test. We tested the method’s accuracy and sensitivity on a set of synthetic time series that represent our knowledge of climatic phenomena and vegeta-tion dynamics. It was also demonstrated for a set of real VI time series over a study area in East and Central Africa.
ISBN: 978-84-15814-97-7
Publication status: published
KU Leuven publication type: IC
Appears in Collections:Division Forest, Nature and Landscape Research

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