Optical spectral characterization of leaves for Quercus Resinosa and Magnolifolia species in two senescent states

R. C. Barragán; Marija Strojnik; Antonio Rodríguez-Rivas; G. Garcia Torales; Francisco Javier González

doi:10.1117/12.2321710

18 September 2018 Optical spectral characterization of leaves for Quercus Resinosa and Magnolifolia species in two senescent states

R. C. Barragán, Marija Strojnik, Antonio Rodríguez-Rivas, G. Garcia Torales, Francisco Javier González

Author Affiliations +

Proceedings Volume 10765, Infrared Remote Sensing and Instrumentation XXVI; 1076511 (2018) https://doi.org/10.1117/12.2321710
Event: SPIE Optical Engineering + Applications, 2018, San Diego, California, United States

Abstract

Study of vegetation by non-invasive methods is a relevant topic for the preservation of the forests, by mean the biochemical analysis of vegetation, the study of the plants and analysis of their behavior with external agents. These methods are based on the spectral signatures of leaves under different behavior conditions. This information can be used in remote sensing techniques for various application through the use of multispectral images or measurements of spectroradiometers. In this document, we examine the diffuse reflectance spectra of the leaves of tree species in two spectral ranges. The first region is enclosed from 0.4 μm to 2.5 μm which corresponds to the solar radiation. The second region covers from 2.5 μm to 20 μm. The study explains the change in the specific signatures of the leaves in relation to the internal decomposition of the foliar plate, due to dehydration of the leaf, the loss of chlorophyll, the production of anthocyanin, and the destruction of the cellular structure, considering two senescent states.

Citation Download Citation

R. C. Barragán, Marija Strojnik, Antonio Rodríguez-Rivas, G. Garcia Torales, and Francisco Javier González "Optical spectral characterization of leaves for Quercus Resinosa and Magnolifolia species in two senescent states", Proc. SPIE 10765, Infrared Remote Sensing and Instrumentation XXVI, 1076511 (18 September 2018); https://doi.org/10.1117/12.2321710

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