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UID:pretalx-foss4g-2024-GM9HZN@talks.staging.osgeo.org
DTSTART;TZID=-03:20241205T160000
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DESCRIPTION:Visualizing and analyzing large-scale geospatial datasets\, suc
 h as Overture Maps' comprehensive global dataset containing more than 3 bi
 llion features grows more challenging as these datasets continue to expand
  in size and scale. This presentation introduces Lonboard\, a cutting-edge
  open-source Python library designed to address this challenge by enabling
  fast\, interactive geospatial vector data visualization within Jupyter no
 tebooks.\n\nLonboard's exceptional performance and ease of use stem from i
 ts innovative architecture\, built on four key technologies: deck.gl for G
 PU-accelerated rendering\, GeoArrow for efficient in-memory representation
 \, GeoParquet for optimized file storage\, and anywidget for seamless Jupy
 ter integration. This powerful combination allows Lonboard to move data fr
 om Python to JavaScript and then to the GPU with unprecedented efficiency.
 \n\nUnlike existing solutions that rely on slower GeoJSON encoding\, Lonbo
 ard employs a fully binary pipeline. It leverages GeoPandas as the primary
  user interface\, internally managing conversions to GeoArrow and GeoParqu
 et for efficient data transport and rendering. This approach not only acce
 lerates data processing but also significantly reduces the data size trans
 ferred to the browser.\n\nWe will demonstrate Lonboard's capabilities usin
 g Overture Maps data\, which is provided in GeoParquet format as monthly r
 eleases. This showcase will highlight how Lonboard's simple interface allo
 ws researchers and data scientists to effortlessly visualize and interact 
 with cloud-native\, optimized geospatial data at a global scale.
DTSTAMP:20260520T142448Z
LOCATION:Room V
SUMMARY:Visualizing Overture Maps Data with Lonboard in a Jupyter Notebook 
 - Vitor George\, Jennings Anderson
URL:https://talks.staging.osgeo.org/foss4g-2024/talk/GM9HZN/
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