Abstract:
Satellite observations of the terrestrial biosphere cover a period of time sufficiently extended to allow reliable climatologies to be determined. The latter is particularly relevant for studies of vegetation response to climate variability. This chapter reviews work done by the authors since the late 80-s on the use of time series analysis techniques to extract concise information from extended time series of large area multispectral satellite data. Two basic methods have been used: the Fast Fourier Transform, especially in the earlier studies, and Harmonic Analysis in more recent work. Since our first study we have been relying on the global radiometric data collected by AVHRR and later on MODIS. The studies reviewed in this chapter have been preformed in different continents. The main applications documented by published results are: (a) identification and mapping of zones characterized by a similar response of terrestrial vegetation to environmental forcing; (b) determination and characterization of the response of terrestrial vegetation to climate variability over any period of time covered by available time series of satellite data; (c) early warning on anomalies in vegetation development of terrestrial vegetation using indicators of photosynthetic activity such as NDVI and fAPAR. These applications span a range of temporal and spatial scales, consistently with the nature of processes observed. We have shown, using data at low spatial and temporal resolutions, that at continental scale spatial patterns in vegetation types and their average pehenology are determined by climate, in particular dryness. The response of vegetation phenology to interannual climate variability required observations at significantly higher spatial and temporal resolutions. Finally, monitoring and early warning on drought related anomalies in vegetation development required observations at even higher spatial and temporal resolutions, while still covering large areas continuously.
