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”