Monitoring Vegetation Health
Research Question
Can affordable “Plant Stress Glasses” (i.e., green-subtracting
filters) enable Forest Watch students to visualize and
quantify different levels of vegetation stress?
General Procedure
Simulate “Plant Stress Glasses” by placing comparable greensubtracting filter material over digital camera lens, followed
by comparison of digital output from camera and VIRIS
(Visible InfraRed Intelligent Spectrometer; GER2600).
Objective- Determine if minus green filter material
could enable students to visually detect vegetation
stress spectral properties.
•Use natural and induced vegetation stress to initiate spectral
reflectance changes in vegetation.
•Use VIRIS to quantify stress induced spectral reflectance changes.
•Use a commercially available digital camera, a photographic gray
scale, and minus green filter to quantify stress induced spectral
reflectance changes.
•Compare digital camera/filter spectral response to VIRIS spectral
response. Here we assume the VIRIS spectral response represents
‘truth’ or ‘spectral reality’, and the degree to which the digital
camera/filter reproduces the VIRIS spectral response is assumed to
be a direct indicator of its ability to represent ‘spectral reality’.
Methodology
•Use gradual stressors as treatments for plant foliage: 1) seasonal
(phenological) change, and 2) drying of cut foliage.
•Measure spectral reflectance properties simultaneously with the
VIRIS and with a digital camera outfitted with minus green filter
(theater gel).
Hypothesis 1: There is a statistically significant association between
the VIRIS and digital camera/filter measurements. Using VIRIS
($75,000.00 tool) to represent “spectral reality”, if the digital
camera/filter ($300.00 tool) can not sufficiently estimate “spectral
reality” then Hypothesis 1 is rejected.
Hypothesis 2: Vegetation determined to be stressed by the VIRIS
will also be determined to be stressed by the digital camera. If this
hypothesis is supported, then students can reliably use a digital
camera to estimate vegetation stress.
Methodology continued
Seasonal Vegetation Stress
Leaf collections were made every 1-2 weeks from mid-June through
mid-October; black birch, red maple, red oak, and white pine (5 sets
of leaves per species).
Leaves were photographed in the field under ambient lighting
conditions with a digital camera at nadir, and a digital gray card in
the field of view. Photos taken included no-filter, 1-layer filter, 2layer (double) filter, and filter glasses.
Leaves were placed in Zip-lock bags in cooler with blue-ice,
transported to UNH, and refrigerated until scanned with the VIRIS.
Samples were scanned with the VIRIS, and simultaneously digitally
photographed, including no-filter, 1-layer filter, 2-layer (double)
filter, and filter glasses. A digital gray card was in the field of view.
Methodology continued
Using the digital photo processing software developed by John
Pickle, blue and red channel radiance values were retrieved from
a polygon on the leaf.
Also using the software, the blue and red channel radiance
values were retrieved from a polygon on the graycard from a
location immediately adjacent to the leaf.
Graycards use materials that reflect 30% of the incident radiation
in all wavelengths.
Photo of a red
maple leaf-stack
with gray scale in
the picture
VIRIS
Camera 1
with filter
Light
Source
Camera 2
without filter
1 2 3
4
5
7
1 2 3
4
5
7
Spectral Data based on reflectance:
Dominant factors affecting leaf reflectance
Leaf pigments
Cell structure
Water content
50
Healthy
% Reflectance
40
30
Red Edge
Damaged
Lignin and
Tannins
Water absorption
Cellulose peak
20
10
0
400
900
Visible spectrum Near Infrared
(400-700 nm)
(700–1000 nm)
1400
Wavelength (nm)
1900
Short Wave Infrared
(1000-2500 nm)
2400
Spectral Indices Used
• Red Edge Inflection Point (REIP) – A measure
of the relative amount of chlorophyll, sensitive to
initial loss of chlorophyll (Rock, et al., 1988).
• Moisture Stress Index (MSI or TM 5/4) – A
measure of foliar moisture content using two IR
spectral bands (NIR and SWIR; Rock, et al.,
1986).
• Chlorophyll Minimum (Chlmin) – Percent
reflectance at center of red chlorophyll well,
indicative of major chlorophyll loss.
TM2
TM3
60
80
100
TM1
0
20
40
Filter Behavior
350 400 450 500 550 600 650 700 750 800 850 900 950 1000
Wavelength (nm)
Reference Panel No Filter
ref2x
ref1x
refgl
30
TM2
TM3
10
20
TM1
0
Gray Card Behavior
350 400 450 500 550 600 650 700 750 800 850 900 950 1000
Wavelength (nm)
Gray Card No Filter
gray2x
gray1x
Gray Card Glasses
730
720
710
700
REIP vs. Day
10Jun
1Jul
22Jul
12Aug
Date
reipbb
reipro
2Sep
23Sep
14Oct
reiprm
reipwp
REIP Summary:
Stable over entire period for White Pine (orange).
Stable over most of period for Red Oak (green); declining around late September.
Began to decline by late July and fell drastically in early September for both Black
Birch (blue) and Red Maple (red).
5.5
5
4.5
3.5
Increased gradually over time up until
late September for all species.
Chlmin vs. Day
4
chlbb/chlrm/chlro/chlwp
Chlorophyll minimum Summary:
17Jun
8Jul
29Jul
19Aug
9Sep
30Sep
Date
20
15
10
White pine (orange) showed no dramatic
changes in chlmin.
Chlmin vs. Day
5
chlbb/chlrm/chlro/chlwp
By mid-October, Black Birch (blue) and
Red Maple (red) exhibited dramatic
increase, while Red Oak (green)
increased a only slightly.
chlrm
chlwp
25
chlbb
chlro
10Jun
1Jul
22Jul
12Aug
Date
chlbb
chlro
2Sep
chlrm
chlwp
23Sep
14Oct
Pairwise Comparisons (correlations) between BLUE spectral
reflectance acquired from Field Images, Lab Images, and VIRIS data.
Black Birch
r
Field Image/Lab Image
-0.40
Field Image/VIRIS
0.12
Lab Image/VIRIS
0.20
Field Image/VIRIS
-0.28
Lab Image/VIRIS
0.02
Field Image/VIRIS
-0.51
Lab Image/VIRIS
-0.45
Red Maple
r
Field Image/Lab Image
-0.03
Red Oak
r
Field Image/Lab Image
0.03
Pairwise Comparisons (correlations; r) between RED spectral
reflectance acquired from Field Images, Lab Images, and VIRIS data.
Black Birch
r
Field Image/Lab Image
0.70*
Field Image/VIRIS
0.90***
Lab Image/VIRIS
0.73*
Field Image/VIRIS
0.91***
Lab Image/VIRIS
0.68*
Field Image/VIRIS
-0.11
Lab Image/VIRIS
-0.32
Red Maple
r
Field Image/Lab Image
0.76*
Red Oak
r
Field Image/Lab Image
0.42
*p<0.05, **p<0.01, ***p<0.001
Summary of Lab and Field Image
comparisons with VIRIS
•Blue channel is highly variable and shows no correlation
between camera/filter images and VIRIS measurements.
•Red channel shows much stronger correlation between
camera/filter images and VIRIS measurements. However,
this finding on applies to Black Birch, and Red Maple. In
Red Oak, the red channel information from the images and
VIRIS were unrelated.
•Calibrated reflectances from the red channel of a digital
camera outfitted with a green-subtracting filter shows
greatest potential for assessing chlorophyll status, because
its values are strongly associated with VIRIS measurements
from the red region. This may not be the case, however, in
all species.
How well associated are camera blue and red features
with VIRIS REIP and Chlmin?
Blue Lab Image
REIP
Black Birch
0.09
-0.17
Red Lab Image
REIP
Black Birch
-0.59
Field Image
Field Image
-0.86**
Red Maple
-0.25
0.09
Red Maple
-0.35
-0.70*
Red Oak
0.25
0.21
Red Oak
0.11
0.25
Lab Image
Field Image
0.74*
0.90***
*p<0.05, **p<0.01, ***p<0.001
Blue
Chlmin
Black Birch
Lab Image
Field Image
0.08
0.18
Chlmin
Black Birch
Red Maple
-0.05
-0.11
Red Maple
0.69*
0.92***
Red Oak
-0.22
-0.30
Red Oak
-0.08
-0.32
Red
Summary of comparisons between camera/filter reflectance
values and VIRIS REIP and Chlmin indices.
•There were no pairwise comparisons between the blue reflectance values
from the lab or field images and the VIRIS indices REIP and Chlmin that
was statistically significant. This suggests the blue channel holds no
predictive value for estimating REIP or Chlmin values.
•Red information from images taken in the field showed good predictive
potential for estimating REIP and especially good for Chlmin values in
Black Birch and Red Maple, but not in Red Oak.
•Red information from images taken in the lab showed good predictive
potential for estimating Chlmin, but not REIP in Black Birch and Red
Maple. Again, Red Oak Chlmin and REIP were not able to be predicted.
• These findings suggest that camera/filter images acquired under similar
or consistent lighting conditions may be useful in discerning “Plant Stress”,
but those taken under field conditions may be far superior.
The Drying Experiment
• Stack of Norway Maple and Red Oak
Leaves Placed on Scale (to determine
weight/water loss;
• VIRIS Spectral Scan and Photos (with and
without filters) taken every 15 minutes;
• Change-over-time characterized for both the
spectral (VIRIS) properties and the filter
brightness values in the blue and red
spectral regions.
725
71.5
Leaf Drying Stress- Norway Maple
715
710
70.5
REIP
Mass (g)
71
720
Mass vs. Time
70
705
REIP vs. Time
100
150
Time (min)
200
250
0
50
100
150
Time (min)
200
250
200
250
.76
50
.85
0
TM5/4 vs. Time
.66
.68
.7
TM5o4
.83
.82
.81
NDVI
.72
.84
.74
NDVI vs. Time
0
50
100
150
Time (min)
200
250
0
50
100
150
Time (min)
Summary of findings from Norway
Maple Drying Experiment
•With drying, the expected results were observed in
measurements of decreasing mass and increasing moisture
stress index.
•Unexpected results were observed in the form of substantial
blue-shifts of the REIP during drying.
•The digital camera/filter data and VIRIS measurements were
in close agreement, suggesting that the minus green filter
material can be useful for detecting drying stress over
relatively short time frames.
.825
REIP vs. Time
200
Time (min)
300
400
0
100
200
Time (min)
300
400
300
400
6.4
.68
100
710
.82
NDVI vs. Time
0
Chlmin vs. Time
6.2
6
5.8
.6
.62
.64
Chlorophyll Minimum Reflectance
.66
TM 5/4 vs. Time
5.6
.58
TM 5/4
720
715
.83
NDVI
REIP (nm)
.835
725
.84
730
.845
Leaf Drying Stress- Red Oak (no mass measurements)
0
100
200
Time (min)
300
400
0
100
200
Time (min)
Summary of results from Red Oak leaf drying experiments
•Unlike Norway Maple, Red Oak demonstrated a resistance to
changing spectral properties for the first 4 hours (250min).
After 4 hours, there was more marked changes in NDVI, REIP,
Chlmin, and the blue and red reflectance measurements. The
MSI indicated water loss was occurring steadily from the onset
of drying.
•The camera with filter, was not able to reliable discern changes
in blue and red reflectance throughout the drying experiment.
As in the seasonal results, it appears that the camera and filter
photography does not permit vegetation health assessment of
drying Red Oak leaves.
Overall Summary of Results
The VIRIS produced data consistent with vegetation
stress for leaves undergoing seasonal change as well as
experimental drying.
In Black Birch and Red Maple, the digital camera/filter
data produced data in close agreement with the VIRIS
data. Thus the digital cameral/minus green filter has
potential as an inexpensive, and accessible tool for
students to estimate vegetation stress.
Digital camera/filter blue channel data provided no
information value for estimating stress under any
circumstance, while red showed very good
correspondence with VIRIS measurements.
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