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UID:pretalx-foss4g-2022-GPC8U8@talks.staging.osgeo.org
DTSTART;TZID=CET:20220824T161500
DTEND;TZID=CET:20220824T164500
DESCRIPTION:Although in use for about 10 years in various Esri products and
  services\, the LERC (Limited Error Raster Compression) raster compression
  algorithm has only just recently made its way into the free and open-sour
 ce GIS scene by its inclusion in GDAL (3.3).\n\nLERC can perform both loss
 less and lossy raster data compression. To achieve its impressive compress
 ion ratios and speed LERC employs two major basic tricks:\n- The raster is
  processed and compressed in small two-dimensional blocks\, taking advanta
 ge of spatial autocorrelation (neighboring values usually being more alike
  than others).\n- The raster values are quantized (absolute values are rep
 laced by differences between neighbors) and bitstuffed to minimize the num
 ber of bits required to store them\, this is especially useful for high bi
 t depth data.\n\nFor lossy compression LERC will follow a user-configurabl
 e maximum error threshold (the "limited error" in its name). Want to compr
 ess your DEM and allow up to one centimeter of error? No problemo!\n\nLERC
  is patented by Esri but thanks to the choice of the permissive Apache Lic
 ense it is freely usable by anyone.\n\nThe talk will try explain the algor
 ithm on a basic level\, understandable by non-experts\, and show its perfo
 rmance with some examples.
DTSTAMP:20260403T204308Z
LOCATION:Room Limonaia
SUMMARY:LERC\, an innovative compression algorithm for raster data - Johann
 es Kröger
URL:https://talks.staging.osgeo.org/foss4g-2022/talk/GPC8U8/
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