Presentation on applications of AI in the geospatial domain at the Fourth Edition of AI in Practice (6th November 2019, Startup Village, Amsterdam, The Netherlands) Erik Van Der Zee, Enterprise Architect, Geodan

1. Applications of AI in the
Geospatial Domain
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Erik van der Zee
Geospatial Enterprise Architect (Geodan)
AI in Practice | Startup Village Amsterdam
Amsterdam | 6th November 2019

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Erik van der Zee
Geospatial Enterprise Architect (Geodan)
@erikvanderzee erik.van.der.zee@geodan.nl +31 6 10099691

3. Contents
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1. The Geospatial Data Explosion
2. About Geospatial Algorithms
3. Applying of AI to Geospatial

4. The Geospatial Data Explosion
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The Geospatial Data Explosion
Causes of geospatial data explosion
• More geospatial data creators (humans, + smart things “IoT”, drones, satellites, etc.)
• New geo data types (e.g. lidar point clouds, 360 panoramic pictures, CCTV, dashcams, bodycams, drones, etc.)
• Higher spatial resolution (megapixel → gigapixel cameras, high resolution scanners)
• Higher temporal (real-time) resolutions (image snapshots → continuous HR video)
• Higher spectral resolutions (“bands”) (multi-spectral → hyper-spectral “data cubes”)
• Derived data (information products, spatio-temporal model output e.g. weather and climate models)

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The Geospatial Data Explosion
Real-time geo-enabled sensor data streams

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The Geospatial Data Explosion
Remote sensing satellites (EU Sentinel, Worldview, etc. ) → Petabytes of data

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The Geospatial Data Explosion
Hyperspectral Data (“Data Cubes”) captured by planes, drones, cars
• From Multispectral
• To Hyperspectral

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The Geospatial Data Explosion
Near real-time remote sensing imagery of each place on earth (200+ Planet Satellites)
• xxx

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The Geospatial Data Explosion
GIGApixel Photos and Videos (360gigapixels.com)

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The Geospatial Data Explosion
Thermographic Aerial Photos

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The Geospatial Data Explosion
Panoramic (360°) Pictures and Videos

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UC 3 - Surveillance Cameras
Cameras everywhere… (body cams, dash cams, surveillance cams, etc.)

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The Geospatial Data Explosion
OpenStreetCam (open dash cam data)

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The Geospatial Data Explosion
Generation of Lidar Pointclouds (from air by planes, drones, cars, smartphones, etc.)(1/2)

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The Geospatial Data Explosion
Generation of Lidar Pointclouds (from air by planes, drones, cars, smartphones, etc.)(2/2)

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The Geospatial Data Explosion
Location Enabled Social Media Content (georeferenced images, videos, tweets, etc.)

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The Geospatial Data Explosion
Real-Time predictive model and simulation output

19. About Geospatial Algorithms
A VERY brief introduction…
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Geospatial
The power of location
• All physical objects have a location in space and time (“XYZT”)
• There are spatial relationships between objects
• To know the location and status (by using sensors) of objects at any moment in time can be used to optimize
business processes
• Example 1 knowing the real-time positions of package pick-up and delivery vehicles and the positions of orders
and cancellations can be used to do real-time planning and on the fly re-planning
• Example 2 knowing the real-time fill % of recycle containers (with sensors) in the city can be used to optimize
collection routes

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Spatial Relationships
Relationships between geospatial objects (cross, disjoint, inside, overlap, …)

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Spatial Relationships
Real-time spatial operators and geometry processors (e.g. geofencing)
Real-Time Spatial Operators
• Inside, Outside, Enter, Exit
• Intersect, Disjoint, Touches, Contains, Crosses, Equals, Overlaps, Within
Real-Time Geometry Processors
• Buffer, Simplifier, Projector, Union, Difference, Cutter, Convex Hull

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Georeferencing Pictures/Video
Georeferencing objects in panoramic pictures by combining image recognition with point clouds
Source: velodynelidar.com

24. Geospatial AI
Using AI to handle the geospatial data tsunami
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Geospatial Data Overload
AI to the resque…
• … Petabytes of BIG geospatial hyperspectral remote sensing data
• … Billions of sensor measurements from smart objects (IoT)
• … Needs to be analysed in real-time
• It is simply impossible for humans to analyse it all…
• AI to the rescue!

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Geospatial AI
Handling the geospatial data flow using AI

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Machine Learning and Deep Learning
Classification – Object Detection - Segmentation

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Some Use Cases for Geospatial AI
Sheet voor alleen tekst, verdeeld over twee kolommen
1. UC 1 – Decision Making in Smart City Scenarios (real-time analytics of sensor event streams and subsequent taking
of spatial actions (Geospatial IoT)
2. UC 2 – Automation of mapping (spatial object recognition and extraction, e.g. traffic signs, zebra crossings, etc.)
3. UC 3 – Surveillance cameras spatial object recognition (car license plate) or subject recognition (persons face)
4. UC 4 - Change detection in remote sensing and aerial photography data (PlanetLabs, Google Earth Engine)

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UC 1
Decision Making in
Smart City Scenarios
Real-time analytics of sensor event
streams and subsequent initiation of
spatio-temporal actions + predictions

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UC 1 – Decision Making in Smart City Scenarios
Sensing – Analysis – Actuating (Geospatial IoT)
Sensing
Analysis and
Prediction
Act(uat)ing
raw events meaningful
events
Sensing Actuating (tasking)

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UC 1 - Decision Making in Smart City Scenarios
Geo-enabled sensor data streams
• If This (and This and This and…) Then That (and That and That and…)

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UC 1 - Decision Making in Smart City Scenarios
Recognition of events (e.g. accidents) based on activity clusters of sensor events or social
media events → Location + content text/images

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UC 1 - Decision Making in Smart City Scenarios
Location Intelligence Use Cases

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UC 2
Automation of Mapping
Spatial object recognition and
extraction, e.g. traffic signs, zebra
crossings, etc.

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UC 2 – Automation of Mapping
Automated Land Use Classification

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UC 2 – Automation of Mapping
Detecting swimming pools

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UC 2 – Automation of Mapping
Detecting roads

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UC 2 – Automation of Mapping
Detecting zebra crossings

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UC 2 – Automation of Mapping
Detecting traffic signs

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UC 2 – Automation of Mapping
Road Feature Detection → Automated digitization

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UC 2 – Automation of Mapping
Road Feature Detection and GeoTagging with Deep Learning

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UC 2 – Automation of Mapping
Creating points of interest based on 360 panoramic pictures + text recognition
• Xxx

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UC 3
Surveillance Cameras
Spatial object (car license plate) or
subject (persons face) recognition in
surveillance cameras

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UC 3 - Surveillance Cameras
Automated Number Plate Recognition (ANPR) cameras → Locations of cars in space and time

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UC 3 - Surveillance Cameras
Spatial object (e.g. car license plate) recognition in surveillance cameras

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UC 3 - Surveillance Cameras
Surveillance Cameras (static and moving) capturing high-resolution footage

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UC 3 - Surveillance Cameras
OpenStreetCam (open dash cam data)

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UC 3 – Surveillance Cameras
Scanautos (parkeerbeheer) → Can also be used for garbage detection → Cleaning tasks

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UC 3 - Surveillance Cameras
Spatial subject (e.g. person clothes / walk) recognition in surveillance cameras

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UC 3 - Surveillance Cameras
Spatial subject (e.g. person face) recognition in surveillance cameras

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UC 4
Change detection
Change detection in remote sensing
and aerial photography data
(PlanetLabs, Google Earth Engine)

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Change Detection
Object change detection (Planet Labs)

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Change Detection
Object change detection (Planet Labs)

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Change Detection
Land Cover change detection (Munich airport)

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September 17, 2016November 10, 2019November 11, 2019
Change Detection
Area changes and moving objects

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Change Detection
Area changes (construction)
February 12, 2016July 19, 2016October 6, 2016

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Change Detection
Change of business (opened, closed, moved) based on Streetview or social media images

58. End of Presentation
… Q&A Time!
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59. President Kennedylaan 1
1079 MB Amsterdam
020-5711 311
Buitenhaven 27-A
5211 TP ‘s Hertogenbosch
073 – 6925 151
Contact
Vestiging Amsterdam Vestiging Den Bosch
info@geodan.nl
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60. Colophon
Title Applications of AI in the Geospatial Domain
Publication Geodan (www.geodan.nl)
Author Erik van der Zee (Geospatial Enterprise Architect)
Date 06-11-2019
Version 1.0
Status Final
Information Erik van der Zee
Email erik.van.der.zee@geodan.nl
Phone +31 (0)6 10099691
Twitter @erikvanderzee
Geodan
President Kennedylaan 1
1079MB Amsterdam The Netherlands
Phone 020 5711311
Twitter @GeodanNL
Youtube GeodanNL channel

61. Applications of AI in the
Geospatial Domain
61
Erik van der Zee
Geospatial Enterprise Architect (Geodan)
Amsterdam | 6th November 2019