Analysis of the global vegetation dynamic metrics using MODIS vegetation index and land cover

Climate change has important implications on the global distribution and dynamics of vegetation that, in turn, impacts the global carbon cycle. Irrespective of the forcings driving these changes, a characterization of global vegetation dynamics and the establishment of accurate metrics that can be linked to forcings are paramount to addressing questions related to climate change and its bearings on the terrestrial biosphere. Terrestrial ecosystems affect climate through a complex system of interactions among water, carbon and energy. An increase, or decrease in these fluxes forces new equilibrium states and feedbacks to the climate system, which in turn impacts the ecosystems. NDVI-based time series analysis of satellite imagery from the NOAA-AVHRR sensor, collected during the last two decades narrates an enhanced vegetation activity over key areas of the Earth (high and mid latitudes). Most of this increase in activities has been indirectly linked to an increase in the Earth's temperature and CO2 concentration. In this study we assessed the relationships between vegetation dynamic metrics and climate-ecosystem parameters: We analyzed 3 years of MODIS Vegetation Index (VI) data augmented by a global land cover map derived from the same sensor, and the GTOPO DEM data. Using a stratified spatial analysis, we assessed the role of the following characteristics on vegetation: Latitude: to isolate temperature regimes and seasonality, Elevation: to isolate land cover and precipitation distribution, Land cover: to isolate phonological characteristics. A combinatorial analysis using the above stratification was applied in successive orders to generate compound results. The results yielded coherent time series profiles depicting vegetation dynamics as it relates to elevation, latitude and land cover.