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dc.contributor.authorSamanta, Arindam
dc.contributor.authorGanguly, Sangram
dc.contributor.authorVermote, Eric
dc.contributor.authorNemani, Ramakrishna R.
dc.contributor.authorMyneni, Ranga B.
dc.date.accessioned2017-06-09T16:41:18Z
dc.date.available2017-06-09T16:41:18Z
dc.date.copyright2012/06/01
dc.date.issued2012
dc.identifier.otherams-72244.pdf
dc.identifier.urihttp://onlinelibrary.yabesh.ir/handle/yetl/4214226
dc.description.abstracthe 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.
dc.publisherAmerican Meteorological Society
dc.titleWhy Is Remote Sensing of Amazon Forest Greenness So Challenging?
dc.typeJournal Paper
dc.journal.volume16
dc.journal.issue7
dc.journal.titleEarth Interactions
dc.identifier.doi10.1175/2012EI440.1
dc.journal.fristpage1
dc.journal.lastpage14
dc.treeEarth Interactions:;2012:;volume( 016 ):;issue: 007
dc.contenttypeFulltext


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