geospatial platforms: enabling disruptive business models from
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Geospatial Platforms: Enabling Disruptive Business Models from Space
North Bethesda, MD| WorldView-2
The data deluge
Rome, Italy | WorldView-2
90% of the world’s data created in the last 2 years
✔
✔
✔
✔ ✔
most of which is location enabled
500,000,000 Tweets EVERY DAY
0 50 100 150 200 250 300
DigitalGlobe Collection
DigitalGlobe Production
Skybox (24-sat)
Blacksky Global (60-sat)
PlanetLabs (150-sat)
Airbus Pleiades (2-sat)
TBytes/day
Satellites collect a LOT of data
0 50 100 150 200 250 300
DigitalGlobe Collection
DigitalGlobe Production
Skybox (24-sat)
Blacksky Global (60-sat)
PlanetLabs (150-sat)
Airbus Pleiades (2-sat)
TBytes/day
Satellites collect a LOT of data
Satellites collect a LOT of data
0 50 100 150 200 250 300
DigitalGlobe Collection
DigitalGlobe Production
Skybox (24-sat)
Blacksky Global (60-sat)
PlanetLabs (150-sat)
Airbus Pleiades (2-sat)
TBytes/day
High resolution drives large data volumes
Landsat 8 15m GSD
Average scene size
0.5 GB
©Landsat/USGS
Planet Labs Doves 3-5m GSD
Equivalent size
16 GB
Planet Labs/Creative Commons License
WorldView 3 0.3m GSD
Equivalent size
941 GB
1900x size of Landsat8
60x size of PlanetLabs
The data management challenge
1 Byte
DGI 1999-2016
80 PB IT Department
Data
X 160,000
(32X world fleet)
The data management challenge
1 Byte
DGI 1999-2016
80 PB IT Department
Data
X 160,000
(32X world fleet)
Managing the data deluge
Palm Jumeira, United Arab Emirates | WorldView-2
Public clouds are enablers
Cloud characteristic Customer benefit
Store data once in the cloud Avoids massive cost to replicate storage
Move computation to the data Avoids network bottlenecks
Provision compute elasticly Avoids paying for idle compute
Enjoy scale economics Leverage top-tier buying power
Swim in the same ocean Enables rapid ecosystem development
Algorithms are enablers
• Requires large amounts of compute
• Requires large training sets
Deep learning excels at pattern recognition
Crowdsourcing is an enabler
• Machines are scalable but still stupid
• People are smarter but more expensive
• Crowd + machine marries the best of both
• Crowd trains machine
• Crowd QAs machine
The emergence of platforms
Rio de Janeiro, Brazil | WorldView-2
Traditional vs Platform Business Models
Traditional
Platform
Producer Consumer
Data GBDX Platform
Algorithms Extracted
Information
DigitalGlobe’s GBDX is such a platform
80 PB ++
Algorithm Developers
(sellers)
“Application” Developers
(buyer)
More algorithms attract more application developers
More application developers attract more algorithm developers
GBDX is in use today
GBDX supports a wide range of algorithms
Removes the effects of the
atmospheric to allow for consistent
imagery suitable for machine
learning applications
e.g., aircraft density vs time around the globe
It has a developer-friendly API
and a growing ecosystem
Including a partnership between DigitalGlobe, TAQNIA & KACST
40X/day 80 cm resolution
Solving Customer Problems
San Francisco, CA | GBDX Car Counts
Identifying where people live in the developing world
…and how to connect them
Enabling consumer retail analytics
Other data sets
Opportunistic imagery over tens of thousands of retail locations
“Secret Sauce” model
Car Detection Algorithm
+3%
Building large scale geospatial databases
… using WV-3 SWIR data to identify roof types
What next?
San Francisco, CA | WorldView-3 high off nadir image | Superbowl Sunday, 2016
Ecosystems breed innovation
Large scale problem solving
Planet-scale “macroscope”