Remote Detection of Biophysical Properties of Plant Canopies

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Remote Detection of Biophysical Properties of
Plant Canopies

• Andrés Viña
• CALMIT School of Natural Resource Sciences

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Introduction

• Plant canopies constitute a major element of the
  interface between the land surface and the
  atmosphere.
• Canopy properties such as Leaf Area Index (LAI),
  Absorbed Photosynthetic Active Radiation (APAR)
  and photosynthetic rates are very important
  components in diverse studies ranging from
  climate modeling to agricultural yield
  forecasting.

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Reflectance is the key!

• Reflectance spectra (rl) of plant canopies is a
  non-linear combination of the spectral
  characteristics of light absorbers in the canopy
  (e.g. pigments, water) and the spectral
  properties of the background (e.g. soil, litter).

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Inversion problem

• To estimate biophysical properties of vegetation
  from reflectance data, it is necessary to
• Find wavelengths (l) where canopy reflectance (r)
  is maximally sensitive to the amount and activity
  of light absorbers.
• Find appropriate response functions that describe
  the effects of canopy architecture.
• Remove the effects of the atmosphere.

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Vegetation Indices

• A vegetation index (VI) is a derivative of r with
  respect to l, which is a function of
• Chlorophyll content in leaves
• LAI - Leaf Area Index
• Background (e.g. soil) scattering
• A response function that describes the effect of
  canopy architecture

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Objectives

• To develop quantitative methods for remote
  estimation of canopy biophysical properties
• LAI
• Green biomass
• Photosynthetic activity (as measured by CO2 flux)
• To validate the techniques under different plant
  canopies, including cropland and forests.

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Study Area
Agricultural fields located at UNL-ARDC. Field 1
corresponds to irrigated continuous maize, field
2 to irrigated maize- soybean rotation and field
3 to rainfed maize-soybean rotation.
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Methods - Reflectance
Reflectance measure-ments were obtained using two
hyper-spectral radiometers (400-900 nm) mounted
on Goliath, an all-terrain sensor platform.
Data include GPS readings and video camera
imagery.
?? (L??/E??)
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Ancillary Data

• Canopy Carbon Flux (Eddy covariance tower)
• Soil Carbon Flux (Portable gas exchange
  equipment)
• Total Green Biomass (Destructive sampling)
• LAI (Destructive sampling using leaf area meters)

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Preliminary Results
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Vegetation Indices
Temporal change of NDVI, VARI (rGreen
rRed)/(rGreen rRed rBlue) and newly
developed indices (rNIR/rRedEdge)-1 and
(rNIR/rGreen)-1
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New Indices
Sensitivity of newly developed index
(rNIR/rRedEdge)-1 to hybrid and water stress
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Indices vs. LAI (Before Tasseling)
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New Index vs. Green Biomass
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What is behind the index ?
Photosynthesis !
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Canopy Mapping
AISA (Airplane mounted hyperspectral imaging
sensor) image July 15, 2002 Field 1
NDVI
(rNIR/rGreen)-1
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Conclusions and Further Research

• Close relationships were found between newly
  proposed vegetation indices and canopy
  biophysical properties (i.e. LAI, green biomass,
  canopy photosynthesis).
• These indices are indicative of the phenological
  stages of maize during the growing season.
• Work is underway to study the sensitivity of the
  indices to biophysical properties in other
  vegetation types (e.g. soybean canopies), as well
  as to validate the current results.

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Acknowledgements

• CALMITs Team
• Dr. Anatoly A. Gitelson
• Dr. Donald C. Rundquist
• Rick Perk
• Bryan Leavitt
• Galina Keydan
• Jeff Moon
• Jared Burkholder
• Ian Ratcliffe
• Giorgio DallOlmo

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Acknowledgements

• Dr. Arkebauers team (Soil Flux and Green
  Biomass)

• Dr. Vermas team (Canopy Flux)

Carbon Sequestration Program PIs Dr. Shashi
Verma and Dr. Kenneth Cassman