Samanta, A; Ganguly, S; Vermote, E; Nemani, RR; Myneni, RB (2012). Why Is Remote Sensing of Amazon Forest Greenness So Challenging?. EARTH INTERACTIONS, 16, 7.
The prevalence of clouds and aerosols and their impact on satellite-measured greenness levels of forests in southern and central Amazonia are explored in this article using 10 years of NASA Moderate Resolution Imaging Spectroradiometer (MODIS) greenness data: normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI). During the wet season (October-March), cloud contamination of greenness data is pervasive;nearly the entire region lacks uncorrupted observations. Even in the dry season (July-September), nearly 60%-66% of greenness data are corrupted, mainly because of biomass burning aerosol contamination. Under these conditions, spectrally varying residual atmospheric effects in surface reflectance data introduce artifacts into greenness indices; NDVI is known to artificially decrease, whereas EVI, given its formulation and use of blue channel surface reflectance data, shows artificial enhancement, which manifests as large patches of enhanced greenness. These issues render remote sensing of Amazon forest greenness a challenging task.