Rasters are not Monsters - GeoMTL 2019
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There are more and more earth observation data available as Open Data (e.g. Landsat, Sentinel). With the current growth, it's important to make sure providers and users use the right format to store the data to enable fast and cheap access, processing, analysis of it.
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Rasters are not Monsters - GeoMTL 2019
- 1. Rasters are not Monsters A Cloud Optimized GeoTIFF’s story GéoMTL - Nov. 13, 2019.
- 2. Introductions Vincent Sarago Geospatial developer @_VincentS_ vincentsarago vincent@developmentseed.org
- 3. More Data
- 4. The Industry ● Earth Observation industry is growing ● Government are not the only one build and launching satellite
- 5. Lighter and Smaller ● Cheap to launch ● Faster iteration ● Increase temporal resolution
- 6. Data on the Cloud ● Cloud providers store the data for free https://registry.opendata.aws https://developers.google.com/earth-engine/datasets/catalog/
- 7. Cloud Optimized GeoTIFF - aka COG
- 8. Definition metadata overview 3 … overview 2 overview 1 Raw overview 3 overview 2 overview 1 Raw tile 1 tile n « A cloud optimized GeoTIFF is a regular GeoTIFF file, aimed at being hosted on a HTTP file server, whose internal organization is friendly for consumption by clients issuing HTTP GET range request ("bytes: start_offset-end_offset" HTTP header). » https://github.com/cogeotiff/cog-spec/blob/master/spec.md
- 9. Features ● Metadata header ● Internal tiling ● Internal overviews Raw 2x 4x 8x 16x
- 10. Data ● Most of satellite providers now offer COG as default format
- 11. Usages
- 12. Storage and fast access Reduce data transfer (compression + Range Request) Fast preview (with overviews)
- 13. Dynamic Tiling Create Web Map tiles from COG Allow user interaction with RAW data Ease ML processing ❤️ + =
- 14. Mosaic mosaicJSON specification Spatial and temporal representation of a set of COG https://github.com/developmentseed/mosaicjson-spec
- 15. Mosaic Pixel selection on the fly Made for dynamic tiling First Last Lowest Highest
- 16. Tools
- 17. Create and Validate $ pip instal rio-cogeo $ rio cogeo create my_file.tif my_cog.tif $ rio cogeo validate my_cog.tif https://github.com/cogeotiff/rio-cogeo
- 18. Visualize QGIS support COG creation/reading rio-viz python (rasterio) module https://github.com/developmentseed/rio-viz
- 19. Read $ pip instal rio-tiler $ rio cogeo validate my_cog.tif https://github.com/cogeotiff/rio-tiler
- 20. Mosaic $ pip instal git+http://github.com/developmentseed/cogeo-mosaic $ cat list_cog.txt | cogeo-mosaic create - -o mos.json https://github.com/developmentseed/cogeo-mosaic
- 21. At Scale Serverless stack to create COG https://github.com/developmentseed/cogeo-watchbot https://github.com/developmentseed/cogeo-watchbot-light Serverless stack to create tiles https://github.com/vincentsarago/lambda-tiler
- 22. Demo
- 25. ABoVe: 31 Bands = 31 Years
Notas del editor
- Bonjour Aujourd’hui je vais vous parler d’un sujet qui pourrait parait `boring` mais qui est pourtant très important lorsque l’on parle de traitement, d’analyse et de partage de donnée raster. Le titre original était: Creation, distribution et analyse des données raster, comment choisir le bon format ?
- Mon nom est Vincent Sarago, je suis developer geospatial senior chez DevelopmentSeed. DevelopmentSeed est une compagnie basée a Washington qui oeuvre auprès des organisme public ou privé afin de les aidées a traiter, analyser et partager les données geospatial. OSM, Machine Learning, Street level imagery, Architecture (Cumulus), Front end …
- L’industrie de l’observation de la Terre connait une croissance sans précédente depuis les 5 dernières année.
- TIFF crée en 1988 GeoTIFF crée en 1995 Mostly maintained by Evan Rouault et Frank Warmerdam since TIFF stay a simple format (in comparison to JPEG2000)