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 8TAMEN
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UID:pretalx-foss4g-2024-workshop-TNYSY9@talks.staging.osgeo.org
DTSTART;TZID=-03:20241203T090000
DTEND;TZID=-03:20241203T130000
DESCRIPTION:Ever wonder what GDAL is doing under the hood when you read a G
 eoTIFF file? Doubly so when the file is a Cloud-optimized GeoTIFF (COG) on
  a remote server somewhere? Have you been wondering what this new GeoZarr 
 thing is all about and how it actually works? Then there's the whole Kerch
 unk/VirtualiZarr indexing to get cloud-native access for non-cloud-native 
 data formats\, what's that about?\n\nCloud-native geospatial is all the ra
 ge these days\, and for good reason. As file sizes grow\, layer counts inc
 rease\, and analytical methods become more complex\, the traditional downl
 oad-to-the-desktop approach is quickly becoming untenable for many applica
 tions. It's no surprise then that users are turning to cloud-based tools s
 uch as Dask to scale out their analyses\, or that traditional tooling is a
 dopting new ways of finding and accessing data from cloud-based sources. B
 ut as we transition away from opening whole files to now grabbing ranges o
 f bytes off remote servers it seems all the more important to understand e
 xactly how cloud native data formats actually store data and what tools ar
 e doing to access it.\n\nThis workshop aims to dig into how cloud-native g
 eospatial data formats are enabling new operational paradigms\, with a par
 ticular focus on raster data formats. We'll start on the surface by survey
 ing the current cloud-native geospatial landscape to gain an understanding
  of why cloud native is important and how it is being used\, including:\n\
 n* the core tenets of cloud-native geospatial formats\n* cloud-native data
  formats for both raster and non-raster geospatial data\n* SpatioTemporal 
 Asset Catalogs (STAC) and how STAC is used for raster data discovery and a
 ccess\n* high-level tooling like odc-stac that can leverage STAC and Dask 
 to scale processing of cloud-native data\n\nThen we'll get hands-on and go
  deep to build up an in-depth understanding of how cloud native raster for
 mats work. We'll examine the COG format and read a COG from a cloud source
  by hand using just Python\, selectively extracting data from the image wi
 thout any geospatial dependencies. We'll repeat the same exercise for geos
 patial data in Zarr format to see how that compares to our experience with
  COGs. Lastly we'll turn our attention to Kerchunk/VirtualiZarr to see how
  these technologies might allow us to optimize data access for non-cloud-n
 ative formats.
DTSTAMP:20260504T102740Z
LOCATION:Room Ilha de Marajó (E Block)
SUMMARY:Deep Dive into Cloud-Native Geospatial Raster Formats - Jarrett Kei
 fer
URL:https://talks.staging.osgeo.org/foss4g-2024-workshop/talk/TNYSY9/
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