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Identifying Ecological Variability in Vegetation Dynamics Through Temporal Mixture Analysis

Large areas of forests, grasslands and agricultural land use are important contributors to the global carbon cycle and variations in the relative proportions of these biomes can have significant implications for climate change. Advances in time series analysis of multi-temporal satellite image sequences are important for these applications, particularly given international policies such as the Kyoto Protocol and the commitment to long-term terrestrial monitoring programs. In this study we use temporal mixture analysis (TMA) to assess regional-scale ecological change over an area of agriculture, grassland, and boreal forest in western North America. Interannual variations in vegetation dynamics are quantified by applying image-based temporal endmembers to NDVI products derived near the peak of the growing season from NOAA- AVHRR imagery over the 21-year period 1981 - 2001. Temporal fraction images provide comprehensive temporal information and display regional-scale patterns of spatial-temporal attributes of land cover change, with a sensitivity to climate events such as droughts.