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Remote estimation of leaf area index and green leaf biomass in maize canopies

Anatoly A. GitelsonCenter for Advanced Land Management Information Technologies (CALMIT) University of Nebraska‐Lincoln Lincoln Nebraska USAAndrés ViñaCenter for Advanced Land Management Information Technologies (CALMIT) University of Nebraska‐Lincoln Lincoln Nebraska USATimothy J. ArkebauerDepartment of Agronomy University of Nebraska‐Lincoln Lincoln Nebraska USADonald C. RundquistCenter for Advanced Land Management Information Technologies (CALMIT) University of Nebraska‐Lincoln Lincoln Nebraska USAGalina KeydanCenter for Advanced Land Management Information Technologies (CALMIT) University of Nebraska‐Lincoln Lincoln Nebraska USABryan LeavittCenter for Advanced Land Management Information Technologies (CALMIT) University of Nebraska‐Lincoln Lincoln Nebraska USA
2003en
ABI

Аннотация

Leaf area index (LAI) is an important variable for climate modeling, estimates of primary production, agricultural yield forecasting, and many other diverse studies. Remote sensing provides a considerable potential for estimating LAI at local to regional and global scales. Several spectral vegetation indices have been proposed, but their capacity to estimate LAI is highly reduced at moderate‐to‐high LAI. In this paper, we propose a technique to estimate LAI and green leaf biomass remotely using reflectances in two spectral channels either in the green around 550 nm, or at the red edge near 700 nm, and in the NIR (beyond 750 nm). The technique was tested in agricultural fields under a maize canopy, and proved suitable for accurate estimation of LAI ranging from 0 to more than 6.

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