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(2015/09) Drone Imagery Economics

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Some thoughts on Drone Imagery Economics and general Drone Economics. What the cheap drones, appropriate algorithms, cheap Cloud Computing and lots of OpenSource resources such as drone OSes and open drone hardware designes mean to the mapping industry at large.

Published in: Data & Analytics
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(2015/09) Drone Imagery Economics

  1. 1. Drone Imagery Economics Martin Scholl @zeit_geist m@martin-scholl.com
  2. 2. Mapping Cost will be zero.
  3. 3. Maps will be made for humans machines.
  4. 4. • Started by Stephen Mather on Apr 2014 • self-described as “an Open Source Toolkit for Processing Drone Imagery” • 31 contributors • installation takes 10m on EC2 • dead easy usage: ./run.pl in images directory
  5. 5. Open-
 Drone-
 Map Point Cloud Ortho- photo. … (Textured) Digital Surface Model
  6. 6. • OpenDroneMap makes drone imagery data processing as easy as running a single command • ~80pics take 1h10m on a 16-core EC2 machine • but: several steps are quadratic in runtime
 in # images and resolution • performance improvements underway • Where to host drone Orthophotos?
  7. 7. • OpenAerialMap is infrastructure for a “simple open way to host and provide access to imagery”* • Re-Initiated by HOT in 2015; grant from Humanitarian Innovation Fund • “supporting humanitarian organizations involved in emergency preparedness and response activities”** * https://github.com/hotosm/OpenAerialMap ** https://docs.google.com/document/d/ 1Cyj3x4MWzif3avAviELNaRThKhBdDoAA0sy38kwyH_g/edit
  8. 8. http://beta.openaerialmap.org/
  9. 9. http://beta.openaerialmap.org/ 0. Search & Filter
  10. 10. http://beta.openaerialmap.org/ 1. Select Area 0. Search & Filter
  11. 11. http://beta.openaerialmap.org/ 1. Select Area 2. Download
 Orthoimages0. Search & Filter
  12. 12. OpenAerialMap • OpenSource Project & Infrastructure • Solves rapid sharing of imagery data for
 humanitarian purposes • Clever data federation architecture by separating indexing from data storage leveraging
 Object Storage (Amazon S3) • mostly satellite images & some drone imagery • 1.1k images indexed yet
  13. 13. A Bigger Picture • OpenDroneMap: free drone image processing • OpenAerialMap: free 2D image hosting, etc. • OpenTerrain: free terrain model hosting, etc. • ArduPilot: free flight control & automation • DIY Drones, OpenUAV, et. al.: free UAV blueprints
  14. 14. Drone Imagery Economics
  15. 15. Drone Imagery Economics 101 w/ OpenDroneMap • Drone w/ 4K camera: $1000 range • Storing 250 high-res images: $0.01 / month
 (Google Cloud Storage) • Processing those images: 2h or ~$0.40
 (AWS EC2 c4.x4large spot instances) • 4k Camera @ 1cm resolution & 50% overlap:
 250 pictures cover 0.2km2
  16. 16. 5 times a day, 1 drone surveying 0.2km2 Per Day Per Month Per Year Drone* $0.92 $27.78 $333 Data Storage $0.05 $1.50 $117 Data Processing $2.00 $60.00 $720 Covered Area 1km2 30km2 360km2 Total Cost ~$3 $90 $1170 * 3y amortization
  17. 17. 5 times a day, 1 drone surveying 0.2km2 Per Day Per Month Per Year Drone* $0.92 $27.78 $333 Data Storage $0.05 $1.50 $117 Data Processing $2.00 $60.00 $720 Covered Area 1km2 30km2 360km2 Total Cost ~$3 $90 $1170 * 3y amortization Friedrichshain- Kreuzberg: 20.16km2
  18. 18. 3D Mapping Berlin* Refresh Rate Year Month Week Day # Drones 3 30 128 892 Monthly Cost $270 $2.700 ~$12.000 ~$80.000 * Berlin: 892 km2; Drone month: $90 / 30km2
  19. 19. … even more numbers Quadrocopter Airplane Landsat 8 Acquisition $1.000 $300.000 $850.000.000 Operations $600 $150.000 (pilot + …) $30.000.000 Amortization 3 years 15 years 30 years Per Year $900 ~$170.000 ~$60.000.000 http://robohub.org/price-wars-counting-the-cost-of-drones-planes-and-satellites/ http://spacenews.com/40841nasa-official-a-landsat-8-clone-would-cost-more-than-650-million/
  20. 20. $19
  21. 21. $19 space for iPhone
 baseboard
  22. 22. Some Consequences • Trade very accurate, highly-priced gear with
 super-inexpensive smartphone-scale chips • $100 autonomous drones mapping cost approaches $0, becomes a “Big Data’esk game” • Data Acquisition Cost < Total Derivable Value • Guiding questions: how stale may imagery data be? What else can we do with it?
  23. 23. Historic Mapping Shift? • Maps used to be power tools of the world,
 for humans, by humans. • Machine Vision for Autonomous Systems has different maps needs • Maps will be built for autonomous systems,
 human-scale map only a side-effect
  24. 24. Open Questions • At some point, drone manufacturers will truly 
 leverage smartphone market economics • When will the first company deliver the autonomous
 $100 drone with 8K+ video? • How will legislation react to this? • How will 100MP+ camera chips on $1000 drones change the quality in the data collection game? • OMG Privacy??
  25. 25. Summary • Drones are quite cheap already. Economics works. • Historic power shift in maps and maps’ users. • Mapping cost will approach $0. • 3D maps: machines & robots the primary user.
  26. 26. Thank you
  27. 27. Megapixels 0 4 8 12 16 2012 2013 2014 2015 iPhone Samsung Galaxy Smartphone Cameras
  28. 28. Moore’s Law • 2x transistor count every 1.5y • translated into equiv speed up every generation • Now Moore’s law works in “opposite direction” • same performance, half the size every 1.5y • 8 Core CPUs w/ less than 4Watt power draw • Drones will become smaller & cheaper 
 keeping the overall performance level

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