Hyperspectral technologies are being increasingly employed in precision agriculture. 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 the crops’ health status such as chlorophyll levels and water content. These initiatives, in turn, can lead to higher crop yield and lower environmental impact through a more effective use of freshwater supplies and fertilizers (reducing the risk of nitrogen leaching). 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 work, we compare the sensitivity of the surface and subsurface reflectance responses of C₃ and C₄ plants to different spectral and geometrical light incidence conditions. In our comparisons, we also consider intra- species variability with respect to specimen characterization data. This investigation is supported by measured biophysical data and predictive light transport simulations. The results of our comparisons indicate that the surface and subsurface reflectance responses of C₃ and C₄ plants depict well-defined patterns of sensitivity to varying illumination conditions. We believe that these patterns should be considered in the design of new high-fidelity crop discrimination and monitoring procedures.

Date Published: 30 April 2016
PDF: 10 pages
Proc. SPIE 9880, Multispectral, Hyperspectral, and Ultraspectral Remote Sensing Technology, Techniques and Applications VI, 98800G (30 April 2016); doi: 10.1117/12.2223806

Published in SPIE Proceedings Vol. 9880:
Multispectral, Hyperspectral, and Ultraspectral Remote Sensing Technology, Techniques and Applications VI
Allen M. Larar; Prakash Chauhan; Makoto Suzuki; Jianyu Wang, Editor(s)