Why is Remote Sensing of Amazon Forest Greenness so Challenging?
Abstract
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 ten 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 to March) cloud contamination of greenness data is pervasive - nearly the entire region lacks uncorrupted observations. Even in the dry season (July to September), nearly 60-66% of greenness data are corrupted, mainly due to 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, while, 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.
- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2012
- Bibcode:
- 2012AGUFM.B41E0333S
- Keywords:
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- 0305 ATMOSPHERIC COMPOSITION AND STRUCTURE / Aerosols and particles;
- 0434 BIOGEOSCIENCES / Data sets;
- 0439 BIOGEOSCIENCES / Ecosystems;
- structure and dynamics;
- 0480 BIOGEOSCIENCES / Remote sensing