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Proceedings Paper

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

Paper Details

Date Published: 20 August 2009
PDF: 11 pages
Proc. SPIE 7454, Remote Sensing and Modeling of Ecosystems for Sustainability VI, 745403 (20 August 2009); doi: 10.1117/12.825508
Show Author Affiliations
Lawrence A. Corp, Sigma Space Corp. (United States)
Elizabeth M. Middleton, NASA Goddard Space Flight Ctr. (United States)
Petya K. Entcheva Campbell, Univ. of Maryland, Baltimore County (United States)
K. Fred Huemmrich, Univ. of Maryland, Baltimore County (United States)
Yen-Ben Cheng, Earth Resources Technology Inc. (United States)
Craig S. T. Daughtry, U.S. Dept. of Agriculture (United States)

Published in SPIE Proceedings Vol. 7454:
Remote Sensing and Modeling of Ecosystems for Sustainability VI
Wei Gao; Thomas J. Jackson, Editor(s)

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