Detection of forests using mid-IR reflectance: An application for aerosol studies

Journal Article · Sun May 01 04:00:00 EDT 1994 · IEEE Transactions on Geoscience and Remote Sensing (Institute of Electrical and Electronics Engineers); (United States)

DOI:https://doi.org/10.1109/36.297984· OSTI ID:7034365

Kaufman, Y J ^[1]; Remer, L A ^[2]

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1. National Aeronautics and Space Administration, Greenbelt, MD (United States). Goddard Space Flight Center
2. Science Systems and Applications Inc., Lanham, MD (United States)

The detection of dark, dense vegetation is an important step in the remote sensing of aerosol loading. Current methods that employ the red (0.64 [mu]m) and the near-IR (0.84 [mu]m) regions are unsatisfactory in that the presence of aerosols in the scene distorts the apparent reflectance in the visible and near-IR ranges of the spectrum. The mid-IR spectral region is also sensitive to vegetation due to the absorption of liquid water in the foliage, but is not sensitive to the presence of most aerosols (except for dust). Therefore, mid-IR channels on the AVHRR and EOS-MODIS (e.g., the 3.75 [mu]m or the 3.95 [mu]m channels) have a unique potential for the remote sensing of dark, dense vegetation, particularly in the presence of biomass burning smoke or industrial/urban haze. The reflective part of the 3.75 [mu]m channel ([rho][sub 3.75]) is applied to images of the AVHRR over the eastern US. This channel was found to be correlated to reflectance at 0.64 [mu]m ([rho][sub 0.64]), less sensitive to haze than the visible channel and superior to both the 0.64 [mu]m reflectance and the normalized difference vegetation index (NDVI) to determine forest pixels in an image. However, its application to monitor the seasonal evolution of vegetation is presently questionable. For the purpose of the remote sensing of aerosol over dark, dense vegetation, it is proposed that the dark, dense vegetation be determined from [rho][sub 3.75] < 0.025. These findings may have further implications for other specific applications of the remote sensing of vegetation in hazy atmospheres.

• OSTI ID: 7034365
• Journal Information: IEEE Transactions on Geoscience and Remote Sensing (Institute of Electrical and Electronics Engineers); (United States), Journal Name: IEEE Transactions on Geoscience and Remote Sensing (Institute of Electrical and Electronics Engineers); (United States) Vol. 32:3; ISSN 0196-2892; ISSN IGRSD2
• Country of Publication: United States
• Language: English

Related Subjects

54 ENVIRONMENTAL SCIENCES
540120 -- Environment
Atmospheric-- Chemicals Monitoring &amp; Transport-- (1990-)
58 GEOSCIENCES
580000* -- Geosciences
AEROSOLS
COLLOIDS
DISPERSIONS
ELECTROMAGNETIC RADIATION
FORESTS
GEOPHYSICAL SURVEYS
GROUND COVER
INFRARED RADIATION
INFRARED SURVEYS
INTERMEDIATE INFRARED RADIATION
RADIATIONS
REMOTE SENSING
RESEARCH PROGRAMS
SOLS
SURVEYS