Time Series Analysis of Noaa Avhrr Derived Vegetation Cover as a Means to Extract Proportions of Permanent and Seasonal Components at Pixel Level

The scope of this study was to find a simple and robust technique to analyze a 16 years time se-ries (totalling 576 decades) of NOAA-AVHRR derived Green Vegetation Fraction (GVF) for de-scribing the bio-physical properties of the observed vegetation canopy as a function of its compo-sition in terms of a seasonally changing vegetation component and a permanent vegetation com-ponent. The principal idea behind the analysis is to use a simple model of an annual vegetation growth cycle per pixel, which is fitted against the available time sequence of data, and interpret on one side the parameters of the fit and on the other side the residuals of the original versus the fitted data. For simplicity reasons this part is represented by a sinus curve with a fixed wavelength of one year. This model allows splitting of the timely resolved vegetation signal into two compo-nents in vegetation appearance. One represents a "permanent background" throughout the year, which is the off-set between the 0 level representing the absence of vegetation cover and the minimum of the modelled seasonal change. The second represents the difference between the maximum and the minimum vegetation cover modelled every year. This technique has been ap-plied to the entire Mediterranean region covered by a NOAA AVHRR time series. The derived pro-portions of permanent and seasonal vegetation components have been finally interpreted on the European CORINE land cover class ‘Olive grove’, assessing the variation of permanent and sea-sonal vegetation components as function of management intensity, leading to a distinction of dif-ferent olive grove management intensity classes within the limits of the CORINE class. The olive class has been chosen as test case because of its well known linkages between the evergreen component represented by the olive trees and the more or less pronounced presence of annual herbaceous understory.

WEISSTEINER Christof;  SOMMER Stefan;  STROBL Peter; 

2008-02-22

European Association of Remote Sensing Laboratories

JRC37881

1729-3782,   

http://www.eproceedings.org/,    http://www.eproceedings.org/static/vol07_1/07_1_weissteiner1.pdf,    https://publications.jrc.ec.europa.eu/repository/handle/JRC37881,