# \[ANN\] GeoIO.jl - Load/save geospatial data in Julia

**URL:** <https://discourse.julialang.org/t/ann-geoio-jl-load-save-geospatial-data-in-julia/106031>\
**Category:** Package Announcements\
**Tags:** package, announcement, data, geo, io\
**Created:** [November 10, 2023, 12:00pm UTC](https://discourse.julialang.org/t/ann-geoio-jl-load-save-geospatial-data-in-julia/106031 "2023-11-10T12:00:35Z")\
**Posts on this page:** 1\
**Showing post:** 10

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**Author:** ![juliohm](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/juliohm/32/215266_2.png) [@juliohm](https://discourse.julialang.org/u/juliohm)\
**Post date:** [August 8, 2024, 10:03pm UTC](https://discourse.julialang.org/t/ann-geoio-jl-load-save-geospatial-data-in-julia/106031/10 "2024-08-08T22:03:58Z")

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Cross-posting a concrete example:

> [@\[ANN\] GeoStats.jl - Geospatial Data Science and Geostatistical Modeling in Julia](https://discourse.julialang.org/t/ann-geostats-jl/101054/17):
>
> A few tweaks here and there, and we are now able to visualize moderately large “raster” data stored in GeoTIFF files with any CRS in native Julia. To illustrate the feature, consider the following example with data from the NaturalEarth project: using GeoStats using GeoIO import GLMakie as Mke # https://www.naturalearthdata.com/downloads/50m-raster-data/50m-gray-earth raster = GeoIO.load("GRAY\_50M\_SR\_OB.tif") |\> Coerce(Continuous) # upscale for 3D mesh visualization coarse = raster |\> Upsca…

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