Remote estimation of nitrogen and chlorophyll contents in maize at leaf and canopy levels

Authors

Michael Schlemmer, Bayer Crop ScienceFollow
Anatoly A. Gitelson, University of Nebraska-LincolnFollow
James S. Schepers, USDA-ARS, Lincoln, NEFollow
Richard B. Ferguson, University of Nebraska-LincolnFollow
Y. Peng, University of Nebraska-LincolnFollow
J. Shanahan, DuPont Pioneer
Donald Rundquist, University of Nebraska-LincolnFollow

Date of this Version

12-2013

Citation

Published in International Journal of Applied Earth Observation and Geoinformation 25 (December 2013), pp. 47–54; doi: 10.1016/j.jag.2013.04.003

Comments

Copyright © 2013 Elsevier B.V. Used by permission.

Abstract

Leaf and canopy nitrogen (N) status relates strongly to leaf and canopy chlorophyll (Chl) content. Remote sensing is a tool that has the potential to assess N content at leaf, plant, field, regional and global scales. In this study, remote sensing techniques were applied to estimate N and Chl contents of irrigated maize (Zea mays L.) fertilized at five N rates. Leaf N and Chl contents were determined using the red-edge chlorophyll index with R2 of 0.74 and 0.94, respectively. Results showed that at the canopy level, Chl and N contents can be accurately retrieved using green and red-edge Chl indices using near infrared (780–800 nm) and either green (540–560 nm) or red-edge (730–750 nm) spectral bands. Spectral bands that were found optimal for Chl and N estimations coincide well with the red-edge band of the MSI sensor onboard the near future Sentinel-2 satellite. The coefficient of determination for the relationships between the red-edge chlorophyll index, simulated in Sentinel-2 bands, and Chl and N content was 0.90 and 0.87, respectively.