BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//pretalx//talks.staging.osgeo.org//foss4g-2022//talk//VPDKN7
BEGIN:VTIMEZONE
TZID:CET
BEGIN:STANDARD
DTSTART:20001029T040000
RRULE:FREQ=YEARLY;BYDAY=-1SU;BYMONTH=10
TZNAME:CET
TZOFFSETFROM:+0200
TZOFFSETTO:+0100
END:STANDARD
BEGIN:DAYLIGHT
DTSTART:20000326T030000
RRULE:FREQ=YEARLY;BYDAY=-1SU;BYMONTH=3
TZNAME:CEST
TZOFFSETFROM:+0100
TZOFFSETTO:+0200
END:DAYLIGHT
END:VTIMEZONE
BEGIN:VEVENT
UID:pretalx-foss4g-2022-VPDKN7@talks.staging.osgeo.org
DTSTART;TZID=CET:20220824T161500
DTEND;TZID=CET:20220824T164500
DESCRIPTION:Point cloud data are an important component of geospatial data 
 workflows\, but software and formats to manage it often have compromises t
 hat work against efficient storage and processing of data. While commonly 
 seen characterizing topographic information in LiDAR applications\, point 
 cloud data are an important driver of change detection applications in SAR
  workflows and provide important raw data to bring the physical world to t
 he augmented one through handset capture on devices like the iPhone 12+. C
 OPC.io is an open specification by Hobu\, Inc. for organizing point cloud 
 data in LAZ that allows it to be streamable over HTTP\, selectable for res
 olution or spatial window\, and adaptable to existing point cloud workflow
 s in a backward compatible way. We will discuss the design choices and evo
 lution of COPC\, demonstrate its use in PDAL and QGIS scenarios\, and show
  how COPC can be used in the cloud for management of massive point cloud c
 ollections.
DTSTAMP:20260403T190454Z
LOCATION:Auditorium
SUMMARY:Cloud Optimized Point Cloud: Compressed\, Geospatial\, Lossless and
  Compatible Data Organization for Analysis Ready Point Cloud Data - Howard
  Butler
URL:https://talks.staging.osgeo.org/foss4g-2022/talk/VPDKN7/
END:VEVENT
END:VCALENDAR