precision agriculture in cotton: definition of the optimal imaging resolution required for purple...
TRANSCRIPT
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Precision agriculture in cotton:Definition of the optimal imaging
resolution required for purple nutsedge
detection
Tal Miller, Liraz Cohen, Eldar Peleg, Matan Gilad and Anat Stein
Western Galilee Regional Highschool
Hanan EizenbergDepartment of Weed Research,
Newe Ya’ar Research Center, Agricultural Research Organization (ARO)
The 2nd International Conference of Novel and Sustainable Weed Management in Arid and Semi-
Arid Agro EcosystemsSeptember 6th-10th , Santorini, Greece
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Introduction• Purple nutsedge is a troublesome weed, causing
severe damage in cotton
• Weeds may compete on resources such as water,
light, space, nutrients etc.
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The effect of purple nutsedge infestation on cotton biomass
y = -0.2008x + 41.577
R2 = 0.908
0
5
10
15
20
25
30
35
0 50 100 150 200
משקל יבש של עשבי גומא הפקעים )גרם(
ם(ר
)גה
תנכו
החי
מצ
ל ש
ש ב
ל ישק
מ
Purple nutsedge biomass (g m-2)
Cott
on
bio
mass
(g m
-2)
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Precision agriculture approach
• Precision agriculture, specifically, site specific
weed management is a modern approach for
reducing herbicide rates
• This could be achieved by spraying herbicides only
on weed patches based on the detection of the
spatial distribution of weeds (and not on the entire
field)
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50% savings
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50% savings
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66% savings
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• Weeds are easily detected visually because they
are green plants on brown soil
• Several indexes were developed for this purpose
How can we detect weeds grown in the
field?
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Normalized Difference Vegetation index (NDVI)
)()(
redNIRredNIR
NDVI
• NIR = Reflection in Near Infra Red (770hm)
• Red = Reflection in Red (660hm)
• It was reported in the literature that NDVI is highly
correlated to vegetative growth, nitrogen and
chlorophyll levels
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NDVI image by NASA
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NDVI of wheat field pre planting
savings 50%
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Wheat field pre planting
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When NIR channel is not available, NGRDI index may be used:
)()(
redGreenredGreen
NGRDI
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• The main goal of this study was to determine the
optimal resolution required for the detection of purple
nutsedge in cotton
Research objectives
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Specific objectives were:
• Detecting purple nutsedge
on bare soil (inter rows)
using NGRDI index
• Defining the threshold
resolution for purple
nutsedge detection
Research objectives (cont.)
High resolution RGB image
(0.05 x 0.05 m per pixel)
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Hypothesis
We hypothesize that NGRDI values, greater than
bare soil NGRDI (~0.01) represent vegetative
growth,
in our case purple nutsedge infestation
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• Experiments were performed in a commercial cotton
field in the Jesreel Valley, Northern Israel
• Aerial images were captured at the same day of data
collection
• Image resolution was 0.05 x 0.05 m per pixel
• Twenty-five plots were randomly selected for data
collection
Materials & Methods
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Materials & Methods (cont.)
• Weed coverage (%) was visually estimated
• Purple nutsedge shoots were counted
• Plot locations were marked using a differential GPS
(dGPS – sub-meter)
• Data were imported into a Geographical Information
Software (GIS) software for advance analysis
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Results
10m
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Data processing
• Originally pixel size was 0.05 x 0.05 m
• Computing values of RGB channels
• Reducing the resolution by increasing the size of the
pixels
• Re-computing values for the merged pixels by using
the average value
0.45 m
1.70 m
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Imaging
GIS
Observations
Fixing imageMarking location by
dGPS
Increasing pixel size
Validation
Determining threshold value
No Yes
Creating multi-layer map
Choosing plots
Color channels analysis
Computing NGRDI index
Is index value higher than ground value?
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Relations between pixel size and NGRDI index
0 1000 2000 3000 4000
NG
RD
I
0.000
0.005
0.010
0.015
0.020
0.025
0.030
0.035
Pixel size (cm2)
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Conclusions
• The threshold resolution for purple nutsedge
detection from an aerial RGB image is 0.5 X 0.5
m per pixel (using NGRDI index)
• Although NIR imaging is separating better weed
from soil, using RGB channels (NGRDI index) is
much cheaper and available for weed detection
• Weed coverage that causes damage to cotton
could be detected with a resolution of 0.5 x 0.5
m per pixel
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Acknowledgment
• EWRS for supporting my trip
• Anat Stein for her assistance and motivation
• Research team in the Newe Ya’ar Research Center,
Department of Weed Research
• Dr. Yafit Cohen, Sensing, Information and
Mechanization Engineering, ARO
• Jimmie Ipen, field crops action, Alonim
• Shay Mey-tal, Agam LTD
• The school, for support and resources
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Thank you for your attention!