This document summarizes research aiming to detect foliar nutrient status from aerial hyperspectral imagery. Hyperspectral data was collected via aircraft over forest plots with experimental nutrient additions. The research aims to 1) match individual tree crowns to their spectral properties in the imagery, 2) correlate foliar nutrition levels with spectral reflectance values, specifically a vegetation index called PRI. Challenges included obstructed canopy views and locating exact tree positions. Preliminary results show differences in PRI values between treatment and control plots. Future work will map additional stands and analyze full spectral profiles.

1. Detecting foliar nutrient
status from the sky:
Ground truthing NEON
spectra in MELNHE plots
Marissa Gabriel
Alexander Young, Ruth Yanai

2. Significance
Match individual
trees to their
spectral properties
Correlate foliar
nutrition remotely

3. Remote Sensing
Extent of
NEON Flight
Campaign
C2
C4
C9
C6
C7 C8
C3
C1
C5

4. Hyperspectral
Intensity of reflectance is affected
by chemical composition of
materials
Visible to Shortwave Infrared Imaging
Spectrometer
Captures reflectance of wavelengths

9. Vegetation Index
Calculated from the reflectance values
of multiple wavelengths for each
spatial unit
Could be correlated with foliar
chemistry associated with nutrient
addition

10. 530 nm 570 nm
Photochemical Reflective Index (PRI)
Photosynthetic light
use efficiency

11. Objective
Can differences induced
be detected remotely?
Identify specific tree
crowns
Match with spectral
profile

12. ● Obstructed view of
canopy
● Tree stem location not
indicative of crown
position
● Multiple stems
clumped
● Fallen or dead
● Inaccurate stake
positions
Challenges

13. Stem Map Aerial Image
Species
Ash
Basswood
Beech
Hemlock
Red maple
Sugar maple
Yellow birch

14. Stem Map Plotted Crowns

15. Aerial Image PRI

16. PRI vs Treatment

17. Map rest of
stands
Use full spectral
profile
Future Work