Spectral indices to monitor nitrogen-driven carbon uptake in field corn

Thumbnail Image

Files

043555_1.pdf (718.25 KB)

Links to Files

https://www.spiedigitallibrary.org/journals/journal-of-applied-remote-sensing/volume-4/issue-1/043555/Spectral-indices-to-monitor-nitrogen-driven-carbon-uptake-in-field/10.1117/1.3518455.short?SSO=1

Permanent Link

https://doi.org/10.1117/1.3518455
 http://hdl.handle.net/11603/28643

Collections

UMBC Joint Center for Earth Systems Technology (JCET)
UMBC Faculty Collection
UMBC Geography and Environmental Systems Department
UMBC GESTAR II

Author/Creator

Author/Creator ORCID

https://orcid.org/0000-0002-0505-4951
 https://orcid.org/0000-0003-4148-9108

Date

2010-11-01

Type of Work

journal articles
Text

Department

Program

Citation of Original Publication

Lawrence A. Corp, Elizabeth M. Middleton, Petya K. E. Campbell, Karl F. Huemmrich, Craig S. T. Daughtry, Andrew L. Russ, and Yen-Ben Cheng "Spectral indices to monitor nitrogen-driven carbon uptake in field corn," Journal of Applied Remote Sensing 4(1), 043555 (1 November 2010). https://doi.org/10.1117/1.3518455

Rights

This work was written as part of one of the author's official duties as an Employee of the United States Government and is therefore a work of the United States Government. In accordance with 17 U.S.C. 105, no copyright protection is available for such works under U.S. Law.
Public Domain Mark 1.0

Subjects

Abstract

Climate change is heavily impacted by changing vegetation cover and productivity with large scale monitoring of vegetation only possible with remote sensing techniques. The goal of this effort was to evaluate existing reflectance (R) spectroscopic methods for determining vegetation parameters related to photosynthetic function and carbon (C) dynamics in plants. Since nitrogen (N) is a key constituent of photosynthetic pigments and C fixing enzymes, biological C sequestration is regulated in part by N availability. Spectral R information was obtained from field corn grown at four N application rates (0, 70, 140, 280 kg N/ha). A hierarchy of spectral observations were obtained: leaf and canopy with a spectral radiometer; aircraft with the AISA sensor; and satellite with EO-1 Hyperion. A number of spectral R indices were calculated from these hyperspectral observations and compared to geo-located biophysical measures of plant growth and physiological condition. Top performing indices included the R derivative index D730/D705 and the normalized difference of R750 vs. R705 (ND705), both of which differentiated three of the four N fertilization rates at multiple observation levels and yielded high correlations to these carbon parameters: light use efficiency (LUE); C:N ratio; and crop grain yield. These results advocate the use of hyperspectral sensors for remotely monitoring carbon cycle dynamics in managed terrestrial ecosystems.