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Processing Rasters from Satellites, Drones, & More

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Part of Integrating Data Ecosystems with FME

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Processing Rasters from Satellites, Drones, & More

  1. 1. PROCESSING RASTERS FROM SATELLITES, DRONES, & MORE
  2. 2. Why do we care about rasters? Rasters are essential for background maps, spatial analytics, and visualizing data over time.
  3. 3. BRINGING RASTERS INTO YOUR WORKFLOWS ● Landsat 8 ● Sentinel 2 ● Planet ● Earth on AWS ● 54 new GDAL-based formats ● GDAL Generic Raster Reader ● GDAL VRT Raster Reader ● PDF Reader (also 2D & text data) Remote Sensing Sources New in FME 2018 ● Drones/UAVs ● Sensors Other Sources
  4. 4. Automation is key.
  5. 5. Top Raster Transformers Anything is possible for rasters in FME! safe.com/transformers
  6. 6. first Get data from Planet and other sources Read imagery and vector layers. Process Mosaic rasters, style vector data, combine, tile. Output as .png Store raster tiles in the cloud. Make available everywhere to anyone. third Automate Do this whenever new images become available. last DEMO: UP-TO-DATE HYBRID BASEMAP second
  7. 7. Check it live
  8. 8. HOW ABOUT MILLIONS OF TILES? WAIT A MINUTE...
  9. 9. first Get images Read Planet imagery of California wildfires. Process Store Save to local or cloud storage. third Analyze Make tools for visual and analytical change comparison. last DEMO: MONITOR AND ANALYZE CHANGE DAILY Derive new products like NIR, NDVI, NDWI. second
  10. 10. Check it live
  11. 11. first Get images from Planet Collect images for a selected timeframe. Process Clip to extents of desired area. Add video to map Prepare HTML output with LeafletJS. MAKE A GEOREFERENCED SATELLITE VIDEO third lastsecond Output as .mp4 Integrate with FFmpeg and output a video.
  12. 12. Scenario: NATURAL HAZARD WORKFLOWS Photo by C. Hitchcock
  13. 13. NATURAL HAZARDS: CHALLENGES ● Diverse data types needed. ○ Vector and raster ○ Open and proprietary ○ Spatial and non-spatial ● Limited IT infrastructure. Need to make data accessible. ● Urgency! Disasters mean short timelines. ● Need to automate processing and distribution.
  14. 14. KEY WORKFLOWS ● Impact assessment. ○ population and transportation ○ identify critical infrastructure ○ hazard sources and extents ● Data integration. ● Risk, probability, scenarios, time. ● UAV surveys, automation.
  15. 15. DEMO Vancouver Flood Hazard Risk Assessment
  16. 16. Bonus: Flood Notifications FME Knowledge Center Tutorial: http://fme.ly/flood
  17. 17. EXAMPLE: SEARCH AND RESCUE UAVs 1. Build route for UAV. 2. UAV flies autonomously and collects data. 3. Post-process – geolocate, assemble results into photomosaic.
  18. 18. Automated route generation SEARCH GRID GENERATION Automated image geolocation
  19. 19. UAVs FOR DAMAGE ASSESSMENT ● UAVs are easy and safe to deploy. ● Rapidly assess impact to people and infrastructure. ● Data guides the level of response. Story: Renato Salvaleon develops UAV systems at Southern Co, supported by FME Server automation. safe.com/uav UAV storm damage assessment by Southern Co.
  20. 20. MEETING NATURAL HAZARD CHALLENGES ● Diverse data types needed. ○ Vector and raster ○ Open and proprietary ○ Spatial and non-spatial ● Limited IT infrastructure. Need to make data accessible. ● Urgency! Disasters mean short timelines. ● Need to automate data processing and distribution. Rapid prototyping
  21. 21. Automation is key.
  22. 22. RESOURCES ● San Francisco Transit demo: http://fme.ly/sftransit ● Blog - earthquake notifications: http://fme.ly/earthquake ● Christchurch earthquake story: http://fme.ly/christchurch ● Flood notification tutorial: http://fme.ly/flood ● Risk analyzer by con terra: georiskanalyzer.com ● Blog - get started with drones: http://fme.ly/drones ● FME Server for Fort McMurray wildfire: http://fme.ly/atco ● Search “remote sensing” or “UAV” on safe.com
  23. 23. Q&A

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