gdal org

No longer here. Find us at @[email protected]
GDAL is a translator library for raster and vector geospatial data formats.

[gdal org @GdalOrg]

By the way, we've moved away from this platform as everybody should, right? Find us at https://t.co/oRAvoYktLo

[Joe Morrison @mouthofmorrison]

Just sent another $300+ to OSGeo! Reminder: all proceeds go to support the maintainers of GDAL! And it’s not just shirts - we’ve got hoodies too.

https://t.co/hSG0tgk89g

[gdal org @GdalOrg]

GDAL 3.7.1 is released: https://t.co/CDqpL99saS

[@[email protected] @howardbutler]

@blaynechard from @LandInfoNZ did a bunch of useful research to show that NZ would have no problem using @Esri's LERC compression and @cogeotiff (available in recent @GdalOrg) to store and stream their raster elevation content. Visit https://t.co/i61EkmpzUS to learn more.

[gdal org @GdalOrg]

#GDAL 3.7.0 is released: https://t.co/pf2krSc7Ma . It includes JSON output for ogrinfo, TileDB vector support, reading of FileGeodatabase raster datasets, @sozip (Seek optimized ZIP) read/write support and many other enhancements and fixes.

[gdal org @GdalOrg]

A GDAL 3.7.0 release candidate is now available for your testing: https://t.co/3VghBsR2A0. Lots of exciting new stuff !

[gdal org @GdalOrg]

#GDAL 3.6.4 is released: https://t.co/aAk0inWeJ1

[gdal org @GdalOrg]

If you use GDAL with Conda, see https://t.co/cT1qh2SrE2 for instructions to upgrade your existing environment to recent GDAL builds that now use libjpeg-turbo

[@[email protected] @howardbutler]

@EvenRouault posted a nice summary of the work he has done for the @GdalOrg sponsorship program to the mailing list https://t.co/sW4A8UJql6 Thank you so much to the sponsors for supporting such high impact activities that benefit everyone using GDAL. https://t.co/cBgz0hSWwJ

[gdal org @GdalOrg]

Due to https://t.co/EaQH9Uhl2m recent move, GDAL Docker images are migrated to https://t.co/zcdB4M26cB{:tagname} : https://t.co/rjdAuBuH1l

[gdal org @GdalOrg]

GDAL 3.6.3 is released: https://t.co/mjLyHTEWzq

[gdal org @GdalOrg]

#GDAL 3.6.3 RC1 bug fix release available for your testing: https://t.co/yGhmhJCvcH

[gdal org @GdalOrg]

Thanks to Kikitte Lee for contributing a new raster->vector polygonizer algorithm, that is up to 10 times faster in some cases: https://t.co/9uhBHrOHr9

[gdal org @GdalOrg]

@pwramsey @postholer Given that @flatgeobuf (at least the GDAL implementation) reorders records to be in the order of the packed Hilbert R-Tree, you would end up rewriting the whole file when changing/appending to it, whatever the location of the index

[gdal org @GdalOrg]

Not yet adopted, but we are already mentioned as a reference implementation!

[Open Geospatial: OGC @opengeospatial]

Seeking public comment on FlatGeobuf becoming an OGC Community Standard. FlatGeobuf is a performant binary encoding for geographic data that works well as a “cloud native” lossless format for vector data #OGCPubCom https://t.co/ZchbJgOUVl

[gdal org @GdalOrg]

All that made possible by us. And practicality of working directly from #shizzle will increase again when @sozipOrg reaches your GDAL build

[ShapefiIe (@[email protected]) @shapefiIe]

Did you know, #geopandas can read and write directly to and from zipped #shapefiles, a.k.a #shizzle files (.shz). #gischat

https://t.co/9Ss3C7zLGQ​

https://t.co/Y9Ylh3tUgJ​

H/t https://t.co/96keRo5tnT

[gdal org @GdalOrg]

@abitmore @floodbase @STACspec @pangeo_data Thanks, and remember to contribute to the projects in your capacity so they remain healthy and striving!

[sozip @sozipOrg]

Try me now on @condaforge with @qgis !
conda create --name sozip_test
conda activate sozip_test
conda install -c gdal-master gdal
conda install -c conda-forge qgis
And with a @GeoPackage1 file:
sozip -j https://t.co/HNKduZK9Bl /path/to/in.gpkg
qgis https://t.co/HNKduZK9Bl

[gdal org @GdalOrg]

Thanks to @hobu, our master builds are now available back on Conda on the "gdal-master" channel. All details at https://t.co/ujibZqak5o. Using bleeding edge GDAL has never been so easy

[gdal org @GdalOrg]

There are limits to our good will that some have "precisely" exceeded :-) And our abstraction model doesn't necessarily capture all specialized data models.

[Postholer - GIS Resources @postholer]

@berttemme Core issue from the article, "..but nothing fit our particular needs. So like Google, we embarked upon creating our own specification..", like everyone else.

Should a spatial format reach critical mass, standard or not, the great homogenizer @GdalOrg will handle it.