"Using Satellites to Extract Insights on the Ground," a Presentation from Orbital Insight

Copyright © 2017 Orbital Insight 1

Using Satellites to Extract Insights

on the Ground

Dr. Boris Babenko, Orbital Insight

May 2017


• Founded in 2013

• Our mission: to understand socio-economic trends on a global scale,

using aerial imagery

• Our technology: deep learning and computer vision + data science

• Our partners: Airbus, DigitalGlobe, Planet, ImageSat, MDA Corporation,

Urthecast, USGS Landsat

• Our customers: >70 asset management firms, several U.S. government

agencies, 2 global nonprofits

About Orbital Insight


Background: Why Space Now?


• Building and launching a satellite is

cheaper than ever before

• Artificial intelligence has made great

advances

• Satellite imagery: a previously untapped

resource outside of government

The Perfect Combination

Image Credit: NASA


• In a few years, you’d need every person in New York City to spend all

day, every day, looking at photos in order to have humans lay eyes on

each satellite image being generated daily.

Why Do We Need Artificial Intelligence?

Image Credit: matheuslotero, Flickr, CC Attribution license


Satellites: Not One-Size-Fits-All


• Bigger satellites

• More expensive to make & launch (~5,000 lb),

so fewer in orbit

• As a result, less frequent imagery

• Higher resolution photos (e.g., 0.5 m)

• Smaller satellites (nanosats, cubesats, etc.)

• Less expensive to make & launch (~10 lb), so

more in orbit

• As a result, more frequent imagery

• Lower resolution photos (e.g., 3 m)

Size, Frequency and Detail

Photo Credit: DigitalGlobe

Photo Credit: Planet


What Can We Measure?


• Convolutional neural network

trained to detect cars in 0.5 m

imagery – cars are only a few

pixels in size

• Track hundreds of retail chains,

malls, etc.

• Parking lot traffic correlates

with sales

Retail Sales Forecasting

Photo Credit: Orbital Insight/satellite imagery: DigitalGlobe


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CMG Stock Price CMG Indexed Traffic

Street consensus estimates fail to pickup ongoing slowdown in traffic, stock corrects -40% after six-month dislocation

Orbital Insight uncovers a slowdown in traffic, missed by consensus

Stock declines -20% after nine-month

dislocation from traffic patterns

Stock declines -45% to more closely correlate to the 12 month deterioration in traffic

Orbital Insight observes traffic peak in early 2015, stock continues to deviate from underlying deterioration in traffic

Orbital Insight uncovers deterioration in traffic, dislocation from Wall Street expectations.

Helping Uncover Dislocations to Street

Expectations


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JCP stock price performance mirrors traffic after three year

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Uncovering Early Short Opportunities


What else can be done with a car detector?

Nanjing, China

• Detect cars across an entire city

• Proxy for: urban development,

population, income, gasoline

demand


• Estimating how much oil

is in each tank

• Tracking 20,000+ tanks

worldwide

Tracking worldwide crude oil inventory

Photo Credit: Orbital Insight/satellite imagery: DigitalGlobe, Planet

0.5 m imagery 3 m imagery


Tracking worldwide crude oil inventory


Previously knownFound by Orbital Insight

• Ran CNN across all China to find

unknown oil tank farms

Building a complete catalog of tanks


• Never enough data

• Trade-off between spatial resolution and temporal frequency

• Clouds

• Can’t count cars if they’re covered by clouds

• Cloud computing

• Computational resources seem infinite and inexpensive… until you start using GPUs

• Recruiting engineers (we’re hiring!)

Challenges

Photo Credit: Orbital Insight/satellite imagery: DigitalGlobe, Planet, USGS


Future Possibilities


Railcar storage Landuse classification

Iron ore stockpiles Aircraft monitoring Heavy industry

Photo Credit: Orbital Insight/satellite imagery: DigitalGlobe, Planet, USGS

Other applications


• More verticals

• Infrastructure and asset monitoring

• Agriculture

• Integrating more data

• More satellite imagery

• Beyond optical: SAR

• Beyond satellites: UAV/Drone imagery

• Beyond imagery: AIS, other GIS datasets

Where We Go From Here


• The Science Behind the Signal: Tracking Unknown Oil Tanks Around

the World, Orbital Insight’s blog

• From the Macroscope: Home Improvement Stores End 2015 With

a Whimper, Orbital Insight’s blog

• Leveraging Commercial Applications to Help the World Bank

Map Poverty, Orbital Insight’s blog

• “Agricultural Crop Health Analysis” in Deep Learning Use Cases for

Computer Vision, by Tractica, Embedded Vision Alliance website

Resources

https://medium.com/from-the-macroscope/the-science-behind-the-signal-tracking-unknown-oil-tanks-around-the-world-9fc917e25795#.et70n576d

https://medium.com/from-the-macroscope/from-the-macroscope-home-improvement-stores-end-2015-with-a-whimper-bd5ead2f685d#.ozhcvg4o0

https://medium.com/from-the-macroscope/leveraging-commercial-applications-to-help-the-world-bank-map-poverty-79bca51814ee#.8badr2md7

http://www.embedded-vision.com/academy/WP-DLCV-16 Tractica.pdf

"Using Satellites to Extract Insights on the Ground," a Presentation from Orbital Insight

Technology