Remote sensing techniques to monitor nitrogen-driven carbon dynamics in field corn

Lawrence A. Corp; Elizabeth M. Middleton; Petya K. Entcheva Campbell; K. Fred Huemmrich; Yen-Ben Cheng; Craig S. T. Daughtry

doi:10.1117/12.825508

20 August 2009 Remote sensing techniques to monitor nitrogen-driven carbon dynamics in field corn

Lawrence A. Corp, Elizabeth M. Middleton, Petya K. Entcheva Campbell, K. Fred Huemmrich, Yen-Ben Cheng, Craig S. T. Daughtry

Author Affiliations +

Proceedings Volume 7454, Remote Sensing and Modeling of Ecosystems for Sustainability VI; 745403 (2009) https://doi.org/10.1117/12.825508
Event: SPIE Optical Engineering + Applications, 2009, San Diego, California, United States

Abstract

Patterns of change in vegetation growth and condition are one of the primary indicators of the present and future ecological status of the globe. Nitrogen (N) is involved in photochemical processes and is one of the primary resources regulating plant growth. As a result, biological carbon (C) sequestration is driven by N availability. Large scale monitoring of photosynthetic processes are currently possible only with remote sensing systems that rely heavily on passive reflectance (R) information. Unlike R, fluorescence (F) emitted from chlorophyll is directly related to photochemical reactions and has been extensively used for the elucidation of the photosynthetic pathways. Recent advances in passive fluorescence instrumentation have made the remote acquisition of solar-induced fluorescence possible. The goal of this effort is to evaluate existing reflectance and emerging fluorescence methodologies for determining vegetation parameters related to photosynthetic function and carbon sequestration dynamics in plants. Field corn N treatment levels of 280, 140, 70, and 0 kg N / ha were sampled from an intensive test site for a multi-disciplinary project, Optimizing Production Inputs for Economic and Environmental Enhancement (OPE). Aircraft, near-ground, and leaf-level measurements were used to compare and contrast treatment effects within this experiment site assessed with both reflectance and fluorescence approaches. A number of spectral indices including the R derivative index D₇₃₀/D₇₀₅, the normalized difference of R₇₅₀ vs. R₇₀₅, and simple ratio R₈₀₀/R₇₅₀ differentiated three of the four N fertilization rates and yielded high correlations to three important carbon parameters: C:N, light use efficiency, and grain yield. These results advocate the application of hyperspectral sensors for remotely monitoring carbon cycle dynamics in terrestrial ecosystems.

Citation Download Citation

Lawrence A. Corp, Elizabeth M. Middleton, Petya K. Entcheva Campbell, K. Fred Huemmrich, Yen-Ben Cheng, and Craig S. T. Daughtry "Remote sensing techniques to monitor nitrogen-driven carbon dynamics in field corn", Proc. SPIE 7454, Remote Sensing and Modeling of Ecosystems for Sustainability VI, 745403 (20 August 2009); https://doi.org/10.1117/12.825508

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