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

Thank you!

Kathryn Hooge Homk.hooge@ndsu.edu

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