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Remote Sensing

Estimation of Carbon Dioxide Exchange
Anatoly Gitelson, Don Rundquist, Bryan Leavitt, Galina Keydan, Rick Perk, and Veronica Ciganda

Project Goal
Develop quantitative remote sensing techniques to estimate biophysical properties of crop
  • fraction of absorbed photosynthetically active radiation
  • green vegetation cover
  • green biomass
  • net ecosystem CO2 exchange (NEE)

Project Description
We are investigating the relationship between remotely measured reflectance (sun light reflected by crops) and tower-based measurements of CO2 fluxes. The project was carried out in three large production fields; each field was equipped with tower eddy covariance flux instrumentation and supporting meteorological sensors.

Spectral radiometric measurements were made in the visible and near infra-red spectral regions using two hyperspectral radiometers mounted on “Goliath”, an all-terrain sensor platform (Figure 1). To calculate reflected light, we measured simultaneously upwelling radiance and incident irradiance. From reflectance spectra we were able to retrieve such biophysical crop characteristics as biomass and greenness which are a proxy of crop photosynthetic activity and, thus, CO2 fluxes.

Figure 1. “Goliath”, an all-terrain sensor platform measuring sun light reflected by crop reflectance spectra in different stages of corn development.
We also acquired imagery by an AISA hyperspectral imaging system (Figure 2), with 35 spectral bands between 400 and 900 nm. Measurements were made from an altitude of ~1000 m, providing a spatial resolution of ~3 m/pixel. Output includes distribution of biomass (or greenness) and crop photosynthetic activity (or vigor).

Figure 2. CALMIT’s AISA Imaging Spectrometer is programmable from 1-286 spectral channels (430-900 nm).

Progress
We developed techniques for quantitative assessment of vegetation cover, biomass and CO2 fluxes (Figures 3 and 4) in irrigated and rainfed maize and soybean. The techniques allow us to make synoptic estimates of these important crop biophysical characteristics, to calculate carbon sequestered by crops, to detect early stages of crop stress and to predict yield in precision agriculture.

Figure 3. Carbon dioxide flux and its remote estimate (where  ρRed Edge is the light reflectance around 700 nm and  ρNIR is the near-infrared (NIR) reflectance (>750 nm).

Figure 4. Comparison of measured and predicted CO2 fluxes.

Date Irrigated Maize (Field 1) Irrigated Soybean (Field 2) Rainfed Soybean (Field 3)
June 21, 2002
June 27, 2002
July 12, 2002
July 15, 2002
September 7, 2002
September 17, 2002

Figure 5. Maps of Net Ecosystem Carbon Dioxide Exchange for irrigated maize and irrigated and rainfed soybean fields for the 2002 growing season. Data was developed from AISA hyperspectral imagery. The maps show how crop greenness and CO2 fluxes change with crop development and maize or soybean phenology. It also quantitatively shows how much higher maize CO2 fluxes are than soybean fluxes and it shows that rainfed soybean sequesters less carbon than irrigated soybean.

Figure 6. Mid-day tower-based measured NEE vs. estimated NEE for maize and soybean fields generated from six AISA hyperspectral images taken between June and September, 2002.

Staff
Anatoly Gitelson  Team Leader and Professor (SNRS & CALMIT)

Don Rundquist  Professor (SNRS) and CALMIT Director

Bryan Leavitt  Technician (CALMIT)

Galina Keydan  Programmer (CALMIT)

Rick Perk  Assistant Geoscientist (CALMIT)

Veronica Ciganda PhD Student (Agronomy and Horticulture & CALMIT)


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