CONFERENCE PROCEEDINGS
Advanced Search
Home > Journals > J. Appl. Rem. Sens. > Volume 11 > Issue 2 > Article
Open Access
2 May 2017 In silico analysis of decomposed reflectances of C3 and C4 plants aiming at the effective assessment of crop needs
Gladimir V. G. Baranoski, Spencer Van Leeuwen, Tenn F. Chen
Author Affiliations +
Journal of Applied Remote Sensing, Vol. 11, Issue 2, 026012 (May 2017). https://doi.org/10.1117/1.JRS.11.026012
Abstract
By separating the surface and subsurface components of foliar hyperspectral signatures using polarization optics, it is possible to enhance the remote discrimination of different plant species and optimize the assessment of different factors associated with their health status. These initiatives, in turn, can lead to higher crop yield and lower environmental impact. It is important to consider, however, that the main varieties of crops, represented by C3 (e.g., soy) and C4 (e.g., maize) plants, have markedly distinct morphological characteristics. Accordingly, the influence of these characteristics on their interactions with impinging light may affect the selection of optimal probe wavelengths for specific applications making use of combined hyperspectral and polarization measurements. In this paper, we compare the sensitivity of the total (including surface and subsurface components) and subsurface reflectance responses of C3 and C4 plants to different spectral and geometrical light incidence conditions. This investigation is supported by measured biophysical data and predictive light transport simulations. The results of our comparisons indicate that the total and subsurface reflectance responses of C3 and C4 plants depict well-defined patterns of sensitivity for varying illumination conditions. We believe that these patterns should be considered in the design of high-fidelity crop discrimination and monitoring procedures.
CC BY: © The Authors. Published by SPIE under a Creative Commons Attribution 4.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.
Citation Download Citation
Gladimir V. G. Baranoski, Spencer Van Leeuwen, and Tenn F. Chen "In silico analysis of decomposed reflectances of C3 and C4 plants aiming at the effective assessment of crop needs," Journal of Applied Remote Sensing 11(2), 026012 (2 May 2017). https://doi.org/10.1117/1.JRS.11.026012
Received: 19 November 2016; Accepted: 17 April 2017; Published: 2 May 2017
JOURNAL ARTICLE
 13 PAGES
DOWNLOAD PAPER SAVE TO MY LIBRARY
GET CITATION
Lens.org Logo
CITATIONS
Cited by 1 scholarly publication.
Advertisement
Advertisement
KEYWORDS
Reflectivity
Data modeling
Multispectral imaging
Polarization
Visible radiation
Computer simulations
Interfaces
RELATED CONTENT
Subscribe to Digital Library
Receive Erratum Email Alert
Back to Top