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Abstract The causal relation between multispectral reflectance and green leaf area index (l.a.i.) has enabled the estimation of green leaf area index by the judicious use of remotely sensed multispectral reflectance measurements. In this paper three topics are discussed. First, the reflectance properties of a vegetation canopy and the problems of determining the form of the relation between green l.a.i. and red and near-infrared reflectance: these problems include variability in substrate and leaf reflectance and the geometry of the scene and sensor. Second, the methodologies currently employed for estimating green l.a.i.: these methodologies are based on the production of simple, complex or modelled calibration curves. Third , current research at the University of Sheffield: this includes not only studies with multispectral reflectance collected from aircraft-mounted sensors to estimate the green l.a.i. of heathlands and grasslands but also multispectral reflectance collected from satellites to map estimated green l.a.i. It is concluded that the main applications for this remote-sensing technique are within the fields of agricultural intelligence, agricultural m anagement and ecological research.
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Paul J. Curran (Mon,) studied this question.
synapsesocial.com/papers/6a16ffbbb13aec50ea6bbc8e — DOI: https://doi.org/10.1098/rsta.1983.0039
Paul J. Curran
University of Wolverhampton
Philosophical Transactions of the Royal Society of London Series A Mathematical and Physical Sciences
University of Sheffield
Google (United States)
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