Evaluation of Avhrr Ndvi for Monitoring Intra-annual and Interannual Vegetation Dynamics in a Cloudy Environment (scotland, Uk)

Vegetation change detection has become increasingly important in understanding vegetation dynamics and its role in terrestrial and atmospheric systems. In the case of Scotland, there is a need to routinely monitor habitats which include native pine woodland, montane habitats, upland heathland and blanket bog (EC Habitats Directive). In northern temperate regions restricted and distinct growing seasons impart significant phenological changes in vegetation which are detectable in remotely sensed data. However, the high frequency of cloud cover in northern temperate climates presents a complicating factor in the use of remote sensing data for monitoring vegetation. High cloud probability means loss of data which makes it more difficult to compile and interpret time-series of data than would be the case in less cloudy areas. For this study satellite data of coarse spatial resolution and high temporal frequency from the NOAA/AVHRR sensor have been evaluated for their utility in monitoring interannual and intra-annual vegetation dynamics of semi-natural and agricultural vegetation types in Scotland. Weekly composited NDVI images for 1995 to 1998 were used in conjunction with digital maps of vegetation distribution to extract NDVI time-series. Temporal development curves of the NDVI values for various vegetation cover types were visually compared to observe the phenology and to detect changes in NDVI response between years. The weekly time-series approach proved to be useful for understanding seasonal dynamics and allowed for interannual comparisons despite the high cloud-cover rate. However, it has also become evident that pre-processing and accurate calibration of the AVHRR imagery is extremely important.