First sentence of abstract: In this paper we discuss developed techniques to remotely assess the fraction of photosynthetically active radiation absorbed by green vegetation [fAPAR-GREEN=fAPAR*(green LAI/total LAI)], fractional green vegetation cover (FGVC), green leaf area index (GLAI) green leaf biomass (GLB) and net ecosystem carbon dioxide exchange (NEE) in crops

Gitelson, Anatoly A.

Rundquist, Donald C.

Viña, Andrés

English

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University of Nebraska - Lincoln DigitalCommons@University of Nebraska - Lincoln Papers in Natural Resources Natural Resources, School of 6-2005 Remote Estimation of Crop Health [ABSTRACT] Anatoly A. Gitelson University of Nebraska - Lincoln, agitelson2@unl.edu Andrés Viña Michigan State University, vina@msu.edu Donald C. Rundquist University of Nebraska - Lincoln, drundquist1@unl.edu Follow this and additional works at: https://digitalcommons.unl.edu/natrespapers  Part of the Natural Resources and Conservation Commons Gitelson, Anatoly A.; Viña, Andrés; and Rundquist, Donald C., "Remote Estimation of Crop Health [ABSTRACT]" (2005). Papers in Natural Resources. 245. https://digitalcommons.unl.edu/natrespapers/245 This Article is brought to you for free and open access by the Natural Resources, School of at DigitalCommons@University of Nebraska - Lincoln. It has been accepted for inclusion in Papers in Natural Resources by an authorized administrator of DigitalCommons@University of Nebraska - Lincoln. Remote Estimation of Crop HealthAnatoly Gitelson, Andres Vina,Donald RundquistUniversity of Nebraskagitelson@calmit.unl.eduIn this paper we discuss developed techniques to remotely assess the fraction of photosyntheticallyactive radiation absorbed by green vegetation [fAPAR-GREEN=fAPAR*(green LAI/total LAI)],fractional green vegetation cover (FGVC), green leaf area index (GLAI) green leaf biomass (GLB) andnet ecosystem carbon dioxide exchange (NEE) in crops. fAPAR-GREEN is one of the main playersused in the formulation of production efficiency models.  FGVC is used in radiative transfer models tocompute fAPAR, and is also required for calculating sensible heat fluxes.  GLAI pertains to the ratio ofgreen leaf surface area to ground surface area. Both GLAI and GLB are directly related to thephotosynthetic apparatus of the vegetation.  While all these biophysical characteristics areinterrelated, different techniques are required to estimate them remotely. We suggest to use the greenNDVI (with near infra-red, NIR, and green, around 550 nm) and the red-edge NDVI (with NIR and aband around 700 nm) to estimate fAPAR-GREEN in soybean and maize. For estimating FGVC, wesuggest the Visible Atmospherically Resistant Index (VARI). VARI uses only visible (the blue, red and either the green or the red edge) spectral bands. The index showed linear relationship with FGVC inwheat, maize and soybean providing the estimation of FGVC with an error of less than 10%. Toestimate GLAI and green leaf biomass, we developed a technique that uses reflectances in two spectral channels: NIR and either the green around 550 nm, or in the red-edge near 700 nm. The technique wastested in agricultural fields under irrigated and rainfed maize and soybean, and proved suitable for anaccurate estimation of GLAI and GLB in both crops.Abstract from 31st International Symposium on Remote Sensing of Environment (June 20-24, 2005, St. Petersburg, Russia)

Remote Estimation of Crop Health [ABSTRACT]

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University of Nebraska - Lincoln 
DigitalCommons@University of Nebraska - Lincoln 
Papers in Natural Resources Natural Resources, School of 
6-2005 
Remote Estimation of Crop Health [ABSTRACT] 
Anatoly A. Gitelson 
University of Nebraska - Lincoln, agitelson2@unl.edu 
Andrés Viña 
Michigan State University, vina@msu.edu 
Donald C. Rundquist 
University of Nebraska - Lincoln, drundquist1@unl.edu 
Follow this and additional works at: https://digitalcommons.unl.edu/natrespapers 
 Part of the Natural Resources and Conservation Commons 
Gitelson, Anatoly A.; Viña, Andrés; and Rundquist, Donald C., "Remote Estimation of Crop Health 
[ABSTRACT]" (2005). Papers in Natural Resources. 245. 
https://digitalcommons.unl.edu/natrespapers/245 
This Article is brought to you for free and open access by the Natural Resources, School of at 
DigitalCommons@University of Nebraska - Lincoln. It has been accepted for inclusion in Papers in Natural Resources 
by an authorized administrator of DigitalCommons@University of Nebraska - Lincoln. 
Remote Estimation of Crop Health
Anatoly Gitelson, Andres Vina,Donald Rundquist
University of Nebraska
gitelson@calmit.unl.edu
In this paper we discuss developed techniques to remotely assess the fraction of photosynthetically
active radiation absorbed by green vegetation [fAPAR-GREEN=fAPAR*(green LAI/total LAI)],
fractional green vegetation cover (FGVC), green leaf area index (GLAI) green leaf biomass (GLB) and
net ecosystem carbon dioxide exchange (NEE) in crops. fAPAR-GREEN is one of the main players
used in the formulation of production efficiency models.  FGVC is used in radiative transfer models to
compute fAPAR, and is also required for calculating sensible heat fluxes.  GLAI pertains to the ratio of
green leaf surface area to ground surface area. Both GLAI and GLB are directly related to the
photosynthetic apparatus of the vegetation.  While all these biophysical characteristics are
interrelated, different techniques are required to estimate them remotely. We suggest to use the green
NDVI (with near infra-red, NIR, and green, around 550 nm) and the red-edge NDVI (with NIR and a
band around 700 nm) to estimate fAPAR-GREEN in soybean and maize. For estimating FGVC, we
suggest the Visible Atmospherically Resistant Index (VARI). VARI uses only visible (the blue, red and
 either the green or the red edge) spectral bands. The index showed linear relationship with FGVC in
wheat, maize and soybean providing the estimation of FGVC with an error of less than 10%. To
estimate GLAI and green leaf biomass, we developed a technique that uses reflectances in two spectral
 channels: NIR and either the green around 550 nm, or in the red-edge near 700 nm. The technique was
tested in agricultural fields under irrigated and rainfed maize and soybean, and proved suitable for an
accurate estimation of GLAI and GLB in both crops.
Abstract from 31st International Symposium on Remote Sensing of Environment (June 20-24, 2005, St. Petersburg, Russia)


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Remote Estimation of Crop Health [ABSTRACT]

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