Paper
17 March 2003 Use of semi-empirical and radiative transfer models to estimate biophysical parameters in a sparse canopy forest
Mirco Boschetti, Roberto Colombo, Michele Meroni, Lorenzo Busetto, Cinzia Panigada, Pietro Alessandro Brivio, Carlo Maria Marino, John R. Miller
Author Affiliations +
Abstract
Knowledge of the characteristics of the vegetation cover is of great interest due to its role in the mass and energy exchanges at the surface/atmosphere interface (e.g. water and carbon cycles). This study is part of DARFEM experiments, EU-funded HySens project (DLR), designed to provide a better understanding of the capability of airborne hyperspectral and directional observations to retrieve biophysical vegetation parameters. Different airborne hyperspectral data were acquired in late June 2001 on the experimental site, a poplar plantation belonging to CARBOEUROFLUX network, located in Northern Italy. An intensive field campaign was accomplished during the aerial survey to collect vegetation parameters and radiometric measurements. Leaf area index (LAI) and vegetation fractional cover (Fc), were retrieved from remote sensing data by statistical relationships with ground measurements. A radiative transfer model was used in direct mode to simulate and analyse the canopy spectral signature changes for varying overstory LAI and different understory conditions. In order to minimize the influence of the extensive understory vegetation on the relationship between spectral Vegetation Index (VI) and LAI, an optical index exploiting short wave infrared (SWIR) was evaluated. A comparison of different VIs performance is presented and relative advantages and drawbacks of SWIR exploitation are discussed.
© (2003) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Mirco Boschetti, Roberto Colombo, Michele Meroni, Lorenzo Busetto, Cinzia Panigada, Pietro Alessandro Brivio, Carlo Maria Marino, and John R. Miller "Use of semi-empirical and radiative transfer models to estimate biophysical parameters in a sparse canopy forest", Proc. SPIE 4879, Remote Sensing for Agriculture, Ecosystems, and Hydrology IV, (17 March 2003); https://doi.org/10.1117/12.463081
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Cited by 3 scholarly publications.
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KEYWORDS
Vegetation

Short wave infrared radiation

Reflectivity

Sensors

Data modeling

Remote sensing

Ecosystems

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