Remote Estimation of Net Ecosystem CO2 Exchange in Crops: Principles, Technique Calibration and Validation

Authors

Anatoly A. Gitelson, University of Nebraska at LincolnFollow
Andrés Viña, University of Nebraska - Lincoln
Shashi Verma, University of Nebraska - LincolnFollow
Donald C. Rundquist, University of Nebraska - LincolnFollow
Timothy J. Arkebauer, University of Nebraska - LincolnFollow
Galina P. Keydan, University of Nebraska - LincolnFollow
Bryan Leavitt, University of Nebraska-LincolnFollow
Veronica Ciganda, University of Nebraska-Lincoln
George G. Burba, University of Nebraska-LincolnFollow
Andrew E. Suyker, University of Nebraska - LincolnFollow

Document Type

Article

Date of this Version

2004

Comments

Published in Gitelson, Viña, Verma, Rundquist, Arkebauer, Keydan, Leavitt, Ciganda, Burba & Suyker in 2nd International Workshop on Remote Sensing of Vegetation Fluorescence (November 17-19, 2004, Montreal, Quebec, Canada). Copyright © 2004, European Space Commission.

Abstract

Accurate and synoptic estimation of spatially distributed CO2 fluxes is of great importance for regional and global studies of carbon balance. A technique solely based on remotely sensed data was developed and tested for estimating net ecosystem CO2 exchange (NEE) in maize and soybean. The model is based on the reflectance in two spectral channels: the near-infrared and either the green or red-edge around 700 nm. The technique provides accurate estimations of mid-day NEE in both crops under either rainfed or irrigated conditions, explaining more than 85% of NEE variation in maize and more than 81% in soybean, and shows great potential for remotely tracking crop NEE.