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Proceedings Paper

Estimation of vegetation parameters by inversion of radiative-transfer models from multispectral imagery supported by ground control measurements
Author(s): Franz Kurz; Olaf Hellwich
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Paper Abstract

We propose a general framework to estimate vegetation parameters from multidimensional remote sensing data using physical models and a moderate amount of ground control data. This framework is exemplarily demonstrated for winter wheat fields imaged by the Daedalus multispectral scanner using physical radiative transfer models, like the SAIL and PROSPECT model, combined with a linear empirical model. Results show the invertibility of the model for leaf area index, chlorophyll content, dry matter, and water content. The attained accuracies of these parameters are compared to the amount of ground control data. The vegetation parameters estimated with help of the devised method are intended to be used to derive information about soil heterogeneities that are important for precision farming.

Paper Details

Date Published: 25 September 2001
PDF: 6 pages
Proc. SPIE 4548, Multispectral and Hyperspectral Image Acquisition and Processing, (25 September 2001); doi: 10.1117/12.441396
Show Author Affiliations
Franz Kurz, GSF-National Research Ctr. for Environment and Health (Germany)
Olaf Hellwich, Technische Univ. Muenchen (Germany)

Published in SPIE Proceedings Vol. 4548:
Multispectral and Hyperspectral Image Acquisition and Processing
Qingxi Tong; Yaoting Zhu; Zhenfu Zhu, Editor(s)

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