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Distinguishing N and P addition from the air using imaging spectroscopy. Alex Young
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.
3. Oversold promises vs recent improvements
Low resolution
High resolution
Spatial resolution Spectral resolution
4. NEON AOP
1. RGB photo
โ 5 cm resolution
1. Hyperspectral data
โ 450 wavelengths m-2
1. Lidar data
โ 1-4 points m-2
6. NEON AOP
1. RGB photo
โ 5 cm resolution
1. Hyperspectral data
โ 450 wavelengths m-2
1. Lidar data
โ 1-4 points m-2
7. NEON AOP
1. RGB photo
โ 5 cm resolution
1. Hyperspectral data
โ 450 wavelengths m-2
1. Lidar data
โ 1-4 points m-2
8.
9. Results
โN and P addition changed reflectence
where light is used for photosynthesis
โBasal area relationship
โN addition reduced reflectance
โ More chlorophyll, absorbed more light
โ P addition increased reflectance
โ If you have thoughts, post in the chat!
10. 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)
11. 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
12. โTrees are signals of belowground function
that can be easily observed remotely.
โDeveloping relationship of light reflectance
and nutrient availability may build on our
understanding of biogeochemistry.
โThe NEON AOP could be brought to
Hubbard Brook.
Acknowledgements
โข NEON online tutorials & data availability
โข The MELNHE Project is funded by USDA NIFA (2019-67019-29464) and
NSF (DEB-1637685) . For more information, please visit
www.esf.edu/melnhe