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Distinguishing N and P addition from the air using imaging spectroscopy. Alex Young

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Distinguishing N and P addition from the air using imaging spectroscopy. Alex Young

  1. 1. Distinguishing N and P addition from the air using imaging spectroscopy Alex Young, Anna Schweiger, Melany Fisk, & Ruth Yanai Twitter: @bearsofthemoss Airborne imaging spectroscopy & field studies
  2. 2. Oversold promises vs recent improvements Low resolution High resolution Spatial resolution Spectral resolution
  3. 3. NEON AOP 1. RGB photo ● 5 cm resolution 1. Hyperspectral data ● 450 wavelengths m-2 1. Lidar data ● 1-4 points m-2
  4. 4. Laliberte, Schweiger, Legendre 2019 - Partitioning plant spectral diversity into alpha and beta components
  5. 5. NEON AOP 1. RGB photo ● 5 cm resolution 1. Hyperspectral data ● 450 wavelengths m-2 1. Lidar data ● 1-4 points m-2
  6. 6. NEON AOP 1. RGB photo ● 5 cm resolution 1. Hyperspectral data ● 450 wavelengths m-2 1. Lidar data ● 1-4 points m-2
  7. 7. Results ●N and P addition changed reflectence where light is used for photosynthesis ●Basal area relationship ●N addition reduced reflectance ○ More chlorophyll, absorbed more light ● P addition increased reflectance ○ If you have thoughts, post in the chat!
  8. 8. When we told the model the treatment class (control, N, P, N+P) for 75% of the data (27 plots), on average we had 83% accuracy for predicting the other 25% (9 plots)
  9. 9. Field-measured resin-available N and P in soil align with clustering of tree-top spectra High soil N Low soil N Low soil P High soil P
  10. 10. ●Trees are signals of belowground function that can be easily observed remotely. ●Developing relationship of light reflectance and nutrient availability may build on our understanding of biogeochemistry. ●The NEON AOP could be brought to Hubbard Brook. Acknowledgements • NEON online tutorials & data availability • The MELNHE Project is funded by USDA NIFA (2019-67019-29464) and NSF (DEB-1637685) . For more information, please visit www.esf.edu/melnhe

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