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Noxious Weed Identification with UAVs
Kathryn Hooge HomNatural Resources Management and
Agricultural and Biosystems Engineering
Outline
• Data collection– UAVs– Sensors
• Analysis– Spectral signature classification– Imagery classification
Research Goals
• Develop computer algorithms that will identify noxious weeds in imagery based on spectral signatures
• Help move field forward in accurately identifying noxious weeds using small UAVs and multispectral sensors
• Identify noxious weeds based on flowers and leaves
Unmanned Aerial Vehicles (UAV)
• Used in mapping and surveying• Attached camera collects imagery of land
and plants
DJI S1000 Trimble UX5
UAVs Used in Research
• DJI Phantom 3 & 4– RGB camera– Multispectral camera
• DJI Matrice 100– Multispectral camera
DJI Phantom
DJI Matrice 100
Sensors Used in Research
• RGB camera• Sentera Quad Multispectral
– 6 Bands: RGB, Red, Red Edge, NIR• SlantRange Multispectral
– 4 Bands: Green, Red, Red Edge, NIR• OceanView Spectrometer
– Collected spectral range400-1000 nm
SlantRangecamera
SenteraQuad
Spectral Signatures
• Spectral signatures: reflectance of material along electromagnetic spectrum
• Collected in visible and near infrared ranges
0
20
40
60
80
100
400 500 598 693 786 875 961
Ref
lect
ance
(%)
Wavelength (nm)
Spectral Signatures
VegetationSoil
Visible Near infrared
False color composite
Flowers
Leaves
Surroundingplants & litter
-2
-1
0
1
2
3
400 500 598 693 786 875 961
Wavelengths (nm)
Spectral SignaturesLythrum flowers
Lythrum leaves
Leafy spurge bracts
Leafy spurge leaves
Grass
Soil
• Purple loosestrife and leafy spurge have different spectral signatures from other plants and soil
• Software separates signatures in imagery
Spectral Signatures
Flowers
Leaves
Surroundingplants & litter
Data Collection Overview
• Collected at 3 different locations• Collected before and during
flowering• Altitude: 10 m• Image resolution: 5 mm• Area: about 1-2 acres
Purple loosestrife collection
Imagery Collection
Mosaic of imagery collected
Spectral Signatures Collection
-2
-1
0
1
2
3
400 500 598 693 786 875 961Wavelengths (nm)
Spectral Signatures
Lythrum flowers
Lythrum leaves
Leafy spurgebractsLeafy spurgeleavesGrass
Soil
Spectral Signatures Classification
• Partial Least Squares Regression: Shows how accurately a model can identify spectral signatures of a specific material
-3
-2
-1
0
1
2
400 500 598 693 786 875 961Wavelengths (nm)
Spectral Signatures
Lythrum leaves
Backgroundplants
Purple Loosestrife vs. Surroundings
-3-2.5
-2-1.5
-1-0.5
00.5
11.5
400 500 598 693 786 875 961Wavelengths (nm)
Spectral SignaturesLythrumflowersLythrum leaves
BackgroundplantsBackground
Cal Val
Reference Y (C3(1), Factor-7)
1 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9 2
Pre
dict
ed Y
(C3(
1), F
acto
r-7)
0.8
1
1.2
1.4
1.6
1.8
2
2.2
2.4
2.6
Predicted vs. Reference
Slope Offset RMSE R-Square
0.9538831 0.0692825 0.1073726 0.9538834
0.9221948 0.1132392 0.1537211 0.9066977
Slope Offset RMSE R-Square
0.9538831 0.0692825 0.1073726 0.9538834
0.9221948 0.1132392 0.1537211 0.9066977
Calibration
Validation
Factors
Factor-0 Factor-1 Factor-2 Factor-3 Factor-4 Factor-5 Factor-6 Factor-7
Y-v
aria
nce
0
10
20
30
40
50
60
70
80
90
100Explained Variance
Lythrum leaves Background plants
Factor-1 (35%, 72%)
-25 -20 -15 -10 -5 0 5 10 15 20 25 30 35
Fact
or-2
(6%
, 12%
)
-15
-10
-5
0
5
10
15
20Scores
-2.5-2
-1.5-1
-0.50
0.51
1.5
400 500 598 693 786 875 961Wavelengths (nm)
Spectral Signatures
Lythrum leaves
Backgroundplants
Purple Loosestrife Leaves vs. Surroundings
Spurge bracts Spurge leaves Grass
Spurge background Spurge litter Soil
Factor-6 (2%, 5%)
-9 -8 -7 -6 -5 -4 -3 -2 -1 0 1 2 3 4 5 6 7 8 9
Fact
or-2
(20%
, 6%
)
-15
-10
-5
0
5
10
15
20Scores
Reference Y (C3(1), Factor-7)
1 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9 2
Pre
dict
ed Y
(C3(
1), F
acto
r-7)
0.4
0.6
0.8
1
1.2
1.4
1.6
1.8
2
2.2
2.4
2.6
Predicted vs. Reference
Slope Offset RMSE R-Square
0.8080685 0.3439813 0.1777487 0.8080698
0.7710731 0.4105308 0.2074618 0.7390063
Slope Offset RMSE R-Square
0.8080685 0.3439813 0.1777487 0.8080698
0.7710731 0.4105308 0.2074618 0.7390063
Calibration
Validation
Factors
Factor-0 Factor-1 Factor-2 Factor-3 Factor-4 Factor-5 Factor-6 Factor-7
Y-v
aria
nce
0
5
10
15
20
25
30
35
40
45
50
55
60
65
70
75
80
85Explained Variance
-2.5-2
-1.5-1
-0.50
0.51
1.52
2.5
400 500 598 693 786 875 961Wavelengths (nm)
Spectral SignaturesLeafy spurgebractsLeafy spurgeleavesGrass
Litter
SpurgebackgroundSoil
Leafy Spurge vs. Surroundings
Leafy Spurge Leaves vs. Surroundings
-2
-1
0
1
2
3
400 500 598 693 786 875 961Wavelengths (nm)
Spectral Signatures
Leafy spurgeleavesGrass
Partial Least Squares Results
• Predicted r2 values of weeds and surrounding plants range from 74% to 94%
• Indicates 74% to 94% of the difference in the spectral signatures is explained by the models
Imagery Classification
Leafy spurge bracts
Leafy spurge leaves
Leafy spurge bracts
Leafy spurge leaves
Leafy spurge bracts
Leafy spurge leaves
“False color” composite of green, red, and NIR bands
NIR Band (730 nm) imageRGB image
Spectral Angle Mapper (SAM)
• Requires reference spectra
• Compares reference spectra to unknown pixel
• Identifies appropriate class for each pixel
SAM Classification Results
False color composite Purple loosestrife flowers classified in red
SAM Classification Results
• Purple loosestrife flower results in red• Purple loosestrife leaf results in green
Summary
• Able to separate spectral signatures of leafy spurge and purple loosestrife from surrounding vegetation
• Using spectral data to identify these noxious weeds in imagery shows promise
Supplementary Material
Accuracy Check1 2 3
4 5 6
1
23
4
56
78
9
10
Imagery date: 6 September 2017
Mosaicked Imagery
26 May 2017Leafy spurge in rangeland
13 July 2017Purple loosestrife in field
