The long-term monitoring of vegetation cover in the Amazonian region of northern Brazil using NOAA-AVHRR data

Abstract

We have analysed monthly composites of normalized difference vegetation index (NDVI) calculated from NOAA's Advanced Very High Resolution Radiometer (AVHRR) for the Amazonian region of northern Brazil across a decade (August 1981 to June 1991) to ascertain if the dominant vegetation types could be differentiated,and to seek inter-annual climatic variation due to changing environmental conditions. The vegetation types observed included dense forest ( submontana and terras baixas ), open forest ( submontana and terras baixas ), transitional forest, seasonal forest ( caatinga ), and two types of savanna ( cerrado ). We found that monthly NDVI composites revealed seasonality in cerrado and especially in caatinga cover types, which can be used in their identification, whilst the phenology of other forest cover types varies little throughout the year. Additionally, yearly composite NDVI values showed a clear and significant reduction ( p 0.95) in dry years, such as those with El Nino Southern Oscillation events. These results indicate the potential use of multi-temporal NDVI data for the environmental characterization and identification of forest ecosystems. Our research found NDVI images from NOAA AVHRR offer a long-term data set that is unequalled for monitoring terrestrial land cover. However, these data have to be used with a degree of caution, especially in regards to atmospheric interference, such as cloud contamination and volcanic eruptions, and post-launch changes in calibration.