8 August 2003 Estimation of chlorophyll concentration in vegetation using global optimization approach
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Proceedings Volume 5072, Technologies, Systems, and Architectures for Transnational Defense II; (2003); doi: 10.1117/12.487756
Event: AeroSense 2003, 2003, Orlando, Florida, United States
Abstract
In this paper we consider the problem of estimating chlorophyll content in vegetation using an experimental optical method from noisy spectral data. It is shown that the quantitative analysis of the spectral curves for the reflection of plant leaves may be the basis for development of new methods for interpretation of the data obtained by the remote measurement of plants. A mathematical model of vegetation reflectance is proposed to estimate the chlorophyll content from spectral data. Estimates are defined as minimizers of penalized cost functionals with sequential quadratic programming (SQR) methods. An estimation is related to the local scoring procedure for the generalized additive model. A deviation measurement in risk analysis of vegetation is considered. The role of deviation and risk measures in optimization is analyzed. Experimental and simulation results are shown for different agricultural plants using a functional-parametric representation of spectral curves.
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Vitaliy Alexeevich Yatsenko, Svetlana M. Kochubey, Panos M. Pardalos, Lezhou Zhan, "Estimation of chlorophyll concentration in vegetation using global optimization approach", Proc. SPIE 5072, Technologies, Systems, and Architectures for Transnational Defense II, (8 August 2003); doi: 10.1117/12.487756; https://doi.org/10.1117/12.487756
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KEYWORDS
Vegetation

Reflectivity

Neurons

Data modeling

Mathematical modeling

Remote sensing

Agriculture

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