An Unmanned Aerial System (UAS) for concurrent measurements of solar-induced chlorophyll fluorescence and hyperspectral reflectance toward improving crop monitoring

Chang, Christine Y.; Zhou, Ruiqing; Kira, Oz; Marri, Samhita; Skovira, Joseph; Gu, Lianhong; Sun, Ying

doi:10.1016/j.agrformet.2020.108145

Title: An Unmanned Aerial System (UAS) for concurrent measurements of solar-induced chlorophyll fluorescence and hyperspectral reflectance toward improving crop monitoring

Journal Article · Thu Aug 20 00:00:00 EDT 2020 · Agricultural and Forest Meteorology

DOI:https://doi.org/10.1016/j.agrformet.2020.108145· OSTI ID:1659560

Chang, Christine Y. ^[1]; Zhou, Ruiqing ^[2];

^[1]; Marri, Samhita ^[3];

^[3]; Gu, Lianhong ^[4]; Sun, Ying ^[1]

Cornell Univ., Ithaca, NY (United States). School of Integrative Plant Science
Cornell Univ., Ithaca, NY (United States). School of Integrative Plant Science; Zhejiang Univ., Hangzhou (China). College of Biosystems Engineering and Food Science
Cornell Univ., Ithaca, NY (United States). Dept. of Electrical and Computer Engineering
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Environmental Sciences Division and Climate Change Inst.

Unmanned aerial system (UAS)-based remote sensing can provide high spatial- and temporal-resolution crop monitoring for precision management. Existing crop monitoring UAS primarily use conventional techniques such as multi-spectral broadband vegetation indices (VIs) to track canopy structure/biomass. Recently developed lightweight hyperspectral sensors can track crop physiology and performance via complementary signals such as solar-induced chlorophyll fluorescence (SIF) and photochemical reflectance index (PRI) that can be derived from hyperspectral reflectance. However, few existing UAS can acquire high-quality SIF and hyperspectral reflectance. Here, we designed a novel UAS that simultaneously captures far-red SIF and hyperspectral reflectance, using a single bifurcated fiber and motorized arm to measure downwelling and upwelling irradiance. The UAS was tested over (1) a heterogeneous corn field with spatially varying crop yield potential and (2) a set of soybean and corn plots under differing nutrient treatments. Our UAS can maintain stability under low-to-moderate winds (2–3 m/s) with <0.4 m geolocation accuracy, <0.1 m altitude drift, and <1.5° error of the fiber optic from nadir position during scanning. Weekly seasonal campaigns reveal that SIF outperforms conventional VIs such as the normalized difference vegetation index (NDVI) for distinguishing plots with different crop yield potential, especially after canopy closure when NDVI tends to saturate. The UAS can capture the diurnal dynamics of SIF and PRI for both corn and soybean. At the seasonal scale, SIF acquired from the UAS correlates well with that from a fixed SIF tower system (R² = 0.81), which measured the same target albeit with different footprints, demonstrating the capability of UAS in characterizing the seasonal progression of crop activity. In conclusion, our newly developed UAS provides high-quality SIF and hyperspectral reflectance, facilitating mechanistic understanding of the physiological control on photosynthesis dynamics. Our findings also imply that this UAS could enable extension of fixed tower-based systems to monitor multiple targets from diurnal to seasonal scales and improve monitoring of heterogeneous fields.

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Research Organization:: Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)

Sponsoring Organization:: USDOE Office of Science (SC), Biological and Environmental Research (BER); USDA; Chinese Scholarship Council; United States - Israel Binational Agricultural Research and Development (BARD) Fund

Grant/Contract Number:: AC05-00OR22725; 2018-67012-27985; 1014740; 201806320111; FI-576-18

OSTI ID:: 1659560

Journal Information:: Agricultural and Forest Meteorology, Vol. 294; ISSN 0168-1923

Publisher:: ElsevierCopyright Statement

Country of Publication:: United States

Language:: English

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Title: An Unmanned Aerial System (UAS) for concurrent measurements of solar-induced chlorophyll fluorescence and hyperspectral reflectance toward improving crop monitoring

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