Presentation on hyperspectral imagery uses in production agriculture.

1. Advanced
Reconnaissance
Corp.
Trends –Hyperspectral Imagery Advancing
Production Agriculture

2. Contact Information
Nate J. Taylor,
Director Commercial Business Development, Marketing & Sales
• 15 years project management/product development
experience
• Chevron
• John Deere
• ZedX
• GeoVantage
ntaylor@advrecon.com +1 (814) 441-1867
http://advrecon.com
Facebook, Vimeo
@natejtaylor
@advrec
2

3. Ag Technology Evolution
1980
1990
1995
2000
2010
Today
Technology
Traditional
Equipment
Pusedo GIS
Yield Monitors
Real GIS
Application Control
Machine Display
Machine Guidance
Implement Guidance
Crop Models
Tracking
Machine Steering
GPS Positioning
Lightbar Guidance
Remote Sensing
Sensing Technologies
GPS Augmentation
Telemetry
Hitch Technologies
Automation
Display Technologies
Video/Vision
Technologies
Positioning Systems
Autonomous
Operation
Swarms
Data analysis
Self Calibrating Equipment
Rule Based Decision
3

4. Shortening the Cycle
Remote
Sensing
2015
2018
AgVu
4

5. Advanced Reconnaissance Corp. at a Glance
Agriculture
Sustainability
Military
ARC Produces and Operates the Most Advanced—Yet Least Complex--
Hyperspectral Imaging Systems in the World --- For Rapid Information to Users
Crops of Interest
IED Indicators
Crop Health /
Maturity
Stressed Vegetation 5

6. ARC’S TECHNOLOGY
• Visible / near infrared
& thermal
• 151 spectral bands
• Uses full spectrum of
information
6

7. Introduction to AgVu
Applicability to Quantifying Crop Stress
• Crop Stress has traditionally been difficult to automatically quantify for
remote sensing. Why?
 Many things effect multispectral signatures similarly
 Plant signatures can be different at different locations
 Plant signatures change over time (as vegetation matures)
 Disease is initially subtle in the plant signature
• AgVu
 Hyperspectral imaging based content
 Has 50x the information content as NDVI or multispectral
 False colors separate information from different diseases, pests, etc
7

8. 1
0.45
to
0.52
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.40
0.47
0.53
0.59
0.64
0.71
0.78
0.99
1.15
1.30
1.45
1.62
1.87
2.17
longitud de onda (micrones)
reflectancia
Visible Reflected infrared
Near infrared Short wave infrared
Leaf pigments Leaf cell structure Water content
Region of
Spectrum
Wavelength (microns)
Reflectance
2
0.52
to
0.60
3
0.63
to
0.69
5
1.55
to
1.75
7
2.08
to
2.35
TODAY’S MULTISPECTRAL IMAGINGTODAY’S MULTISPECTRAL IMAGING
Image collectionImage collection
4
0.79
to
0.90
8

9. • Current analysis based
on only 4 bands
• Data is normalized
• Variability Limited
• Ratio of 2 bands to
create NDVI
• Relative Index
Band 3 Band 1 Band 2 Band 4
TODAY’S MULTISPECTRAL IMAGINGTODAY’S MULTISPECTRAL IMAGING
Image analysisImage analysis
9

10. Detecting “The Shift”
Hundreds of narrow contiguous spectral bands
Data
•Yield
•Multispectral
•As Applied
Information
•Hyperspectral
Knowledge
•Agronomic
•Quality
Decisions
•Variety
Selection
•Storage
•Many more
The Knowledge Gap
Barrier
ARC’s analysis breaks “the agriculture
knowledge gap barrier”
Hyperspectral Imagery
10

11. Hyperspectral Imaging in Real-World
PlantType(s)
Real-World
Agronomics
i
1
i
2
i
3
i
4
Cause Real
Signature Differences
i
5
AgVu Decodes the Signature into
Stable Information Levels
i
6
i
7
Difficult to Separate
using the Signature
11

12. The ARC Difference
The Information Layers are Accessed
By “Flipping Different Switches” in the Software
Layer 2 Shows
Crop Health
Layer 1 Shows
Crop Type
Layer 3 Shows
Crop Cultivars
12

13. MORE INFORMATION, BETTER DECISIONSMORE INFORMATION, BETTER DECISIONS
13
4 bands: What do you see?4 bands: What do you see?

14. 7 bands: What do you see?7 bands: What do you see?
14
MORE INFORMATION, BETTER DECISIONSMORE INFORMATION, BETTER DECISIONS

15. 15
151 bands: What do you see?151 bands: What do you see?
MORE INFORMATION, BETTER DECISIONS

16. Decisions are only as good as the amount of information available
True Color NDVI AgVu
50X as much information
means subtle issues are
evident earlier
MORE INFORMATION, BETTER DECISIONS
16

17. Soybeans
What Hybrid is Planted?
Crop Varieties
Crop Growth Inhibitors
Waterway - grass
Farmstead
Terraces
Grass Waterway
Farmstead
Line
Oldfenceline
Corn - 2 Hybrids
Alternate 16 rows
Corn - different hybrid
Beans
RR
STS
Conventional
Corn
Soybeans
Different
Varieties
Var I
Var II
Var III
Var IV
Var 3
Var 2
Var 3
Var 4
Corn - different hybrid
CRP - (10 year reserve)
grass with areas mowed (dark)
for thistle control
30 in row soybeans
Corn
Roundup Ready
STS
Conventional
Var 2
Var 1
Var 1
Var 2
Var 4
MORE INFORMATION, BETTER DECISIONS
17

18. ThermalTrue Color AgVu
Two spotted spider
mite infestation
It provides crop information to growers, earlier and more timely than any other way
ARC’s AgVu™ Shows Early Signs of Insects in Strawberry Fields
MORE INFORMATION, BETTER DECISIONS
18

19. Around 10am, Day 1 Around 12pm, Day 2
REPEATABLE ACCURACY
19

20. Wrap Up
• ARC alone has the capability to automatically process
hyperspectral data
 Rapid turn around of actionable information creating institutional
knowledge
 Enables low cost identification of a variety of crop stresses
• ARC’s AgVu service enables decision agriculture by bridging the
“knowledge gap barrier.”
 Agronomists and agriculturalists can leverage their knowledge
• ARC’s algorithm can detect soil minerals, pest/disease
infestation, crop health and more
 Specific and quantifiable information directly from imagery
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21. Backup

22. Detecting “The Shift”