Date post: | 08-Jul-2015 |
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Data & Analytics |
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AERIAL IMAGERYSERVICE OVERVIEW
PRECISE INFORMATION ADVANCING PRECISION AGRICULTURE
Current Market Sectors
• Agriculture: Information for crop analysis
• Defense: IED detection/counter narcotics
Near-Term Additional Markets
• Geology
• Natural recourses
• Environmental assessment
• Forestry
• Aquaculture/mariculture
Current Market Sectors
• Agriculture: Information for crop analysis
• Defense: IED detection/counter narcotics
Near-Term Additional Markets
• Geology
• Natural recourses
• Environmental assessment
• Forestry
• Aquaculture/mariculture
2
ARC’S TECHNOLOGY• Visible / near infrared
& thermal• 151 spectral bands• Uses full spectrum of
information
Why Hyperspectral
4
Imagery Today - Multispectral
5
10.45to
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)
refle
ctan
cia
Visible Reflected infrared
Near infrared Short waveinfrared
Leafpigments
Leaf cellstructure
Watercontent
Region ofSpectrum
Wavelength (microns)
Refle
ctan
ce
20.52To
0.60
30.63To
0.69
40.79To
0.90
51.55to
1.75
72.08To
2.35
• 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
Collection to Analysis
Hyperspectral Imagery “The Next Generation”
6
In real life, plants are much more complicated,and every soil difference or farming decision
shows up in the spectral details
100s of bands in hyperspectral images show more detailby splitting the spectrum into smaller pieces than multispectral
Every color in the AgVu imageshows real information:• Crop Health• Effect of Nitrogen/ Sulfur• Invasive Species• From 151 Spectral Bands
The Next Generation is Now
Collection to Analysis
We pick this up
7
4 bands: What do you see?4 bands: What do you see?MORE INFORMATION, BETTER DECISIONSMORE INFORMATION, BETTER DECISIONS
8
7 bands: What do you see?7 bands: What do you see?MORE INFORMATION, BETTER DECISIONSMORE INFORMATION, BETTER DECISIONS
9
151 bands: What do you see?151 bands: What do you see?MORE INFORMATION, BETTER DECISIONS
10
How the Techniques CompareMultispectral
NDVI RGB
11
The most subtle distinctions arepicked out over the entirevegetative region—allowing imagesto show farmers crop health andstress earlier than ever before
How the Techniques CompareHyperspectral Imaging—How to See It Early
More Information, Better Decisions
12
ARC’s hyperspectral sensor removes this limitationDecisions are limited by the amount of information available
True Color NDVI AgVu
50X as much information meanssubtle issues are evident earlier
More Information, Better Decisions
13
SoybeansSoybeans
What Hybrid is Planted?
Crop Varieties Crop Growth Inhibitors
Waterway - grass
Farmstead
Terraces
Grass Waterway
Farmstead
Line
Old
fe
nce
lin
eOl
d
fenc
e
line
Corn - 2 HybridsAlternate 16 rows
Corn - different hybrid
Beans
RR
STS
Conventional
CornSoybeans
DifferentVarietiesDifferentVarieties
Var IVar IVar IIVar IIVar IIIVar IIIVar IVVar IV
Var 3Var 3
Var 2Var 2 Var 3Var 3
Var 4Var 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 2Var 2
Var 1Var 1
Var 1Var 1
Var 2Var 2
Var 4Var 4
Efficient Monitoring
14
June 25 July 10 Aug 14 Sep 11 Sep 25
AgVu identifies weed pressure early in the season, saving the grower lost crop andlost yield by allowing them to treat the problem early.
Provides information for improving yields, reducing costs, and increasing sales
Operations
15
How We Schedule
“Charter” flights• Customer monitors for growth stages• Increased infrastructure• Loss of efficiency• Scheduling harder for customers
“Commercial” flights• Automatic monitoring of growth stages• Less infrastructure• High efficiency• Scheduling easy for customers
0
100
Cumulative Temperature/GDDs
Tass
elin
g
Har
vest
Cro
p G
row
th S
tatu
s (%
)
Bare soil
V5-V10FertilityRequirements
Pre-senescenceYield predictions
Example Timing of Imagery Capture
Emer
genc
e
16
OrderSubmission
OrderValidation
MissionPlanning
FlightScheduling
Flight PlanDelivery
1 2 3 4 5
Customer providedshp files
Online interface Chose acquisition
window Imagery
specifications
Validate shp files Validate all customer
information
Operations plans Determine Regions
of Interest (ROI)
CompileOperations/flightplans
Provide flight plansand timing of flights
Ensure pilotavailability
Raw ImagesCaptured
ImageDelivery
QA/QCImage
ProcessingCustomer
Access
69 8 710
Via web interface Export/Import to
precision ag software
True Color Analysis map (AgVu) Push to web interface
Check forinconsistencies
Shadows Reprocess
ARC process viaproprietary algorithm
Mosaic andorthorectification
Clipped to boundary
Data sent fromfield site to ARCserver
24 hours 24 hours
7 Day Flight Range
48 Hours12 hours
Back Office Work Flow
17
Order Entry to Delivery