[ANN] GeoStats.jl - Geospatial Data Science and Geostatistical Modeling in Julia

[juliohm]

Quick update:

We are now using uv texture mapping in Makie.jl to visualize “rasters”, which gives an additional 2.5x speedup. If you need this speed, please update your environment.

[maxfreu]

If you want faster upsampling, look into NNlib. The julia native bilinear upsampling there is parallelized for cpu and gpu and supports 1, 2 & 3D data and is as fast as it can probably get.

[juliohm]

Relevant update:

[ANN] GeoArtifacts.jl

GeoArtifacts.jl v1.1 This release comes with a complete refactor of the internals to benefit from the various repairs of geometries implemented in GeoIO.jl. The NaturalEarth submodule is very comprehensive now, allowing users to download all sorts of datasets with clean syntax. Below is an example where we create a 3D visualization with a “raster” of the Earth, country borders, airports and water ports: using GeoStats using GeoArtifacts import GLMakie as Mke # download artifacts from natura…

[juliohm]

GeoStats.jl v0.66

Refactored Slice transform and other minor fixes:

"Raster" syntax in GeoStats.jl

Given that most people in the geo community are not aware of the “raster” syntax in GeoStats.jl, I collect a few examples here to facilitate the transition. This post may become part of the official project documentation in the future. The “raster” model A “raster” is nothing more than a Julia array that is georeferenced over a geospatial grid. The “raster” model is popular in the scientific community for two main reasons: it provides convenient syntax to access grid elements within “rectan…

[juliohm]

Two job opportunities:

Geospatial Software Development at Arpeggeo®

Description We are seeking a highly skilled and motivated Software Engineer to join our team, focusing on the development of cutting-edge geospatial software solutions. The ideal candidate will have strong expertise in GIS (Geographic Information Systems) technology and demonstrate a passion for solving complex geospatial problems through software development. This role involves working on a variety of projects that require a deep understanding of geospatial data, mapping technologies, and softw…

Arpeggeo + Algora: funding contributors of the GeoStats.jl framework

At Arpeggeo® we are starting an experimental initiative to attract more contributors to the Julia community. In partnership with algora.io, we are introducing open-source bounties to the GeoStats.jl framework. If you are a freelancer, or just want to make some extra cash besides your main job, look for open issues with the Bounty label on the JuliaEarth organization on GitHub. Here is a first easy one to get used to the Algora workflow: The Algora founders gave us a 1 month trial to see if …

[GeodeticR]

I’m finishing a Masters in Geophysics that is in the geospatial realm (my research is in geodesy). Maybe by the end of my degree I’ll qualify as for being “proficient in high-performance programming languages” because as of now, I’m firmly between novice and adequate. lol

Good luck with the search!

[juliohm]

GeoStats.jl v0.68

New discretization and refinement methods, and various other small improvements and fixes.

• New MaxLengthDiscretization to discretize geometries into subgeometries of maximum length. This is used in viz of geodesic geometries.

  Example

  If you create a Segment from two points with LatLon coordinates, and call viz you will see it is “curved”. Below you can see this with random segments:

  segs = rand(Segment, 100, crs=LatLon)
  
  viz(segs)
  

  
  Works for various other geometries of course, including all geometries with parametric dimension 1 (e.g. Rings of polygons).

• The TriRefinement now supports a predicate function for adaptive refinement. For instance, you can refine all elements with area greater than a given threshold TriRefinement(e -> area(e) > 1km^2).

• The georef function now supports a lenunit option besides the crs to specify the length units of some CRS from raw unitless columns.

• All Grid subtypes now support CRS (e.g., RectilinearGrid, StructuredGrid, RegularGrid, CartesianGrid). The CartesianGrid is now an alias to a RegularGrid with Cartesian CRS. If you need to convert back and forth between LatLon and Projected coordinates, prefer RegularGrid in your workflows.

We are seeing more and more articles in applied sciences citing the software. Thank you

[juliohm]

GeoStats.jl v0.71

This release introduces transiogram functions, which measure the transition probability between categorical values at any given distance along any given direction. Transiograms are used to simulate Markov processes in more than one dimension (e.g. space).

Various models are implemented, including the MatrixExponentialTransiogram model by Carle et al and the PiecewiseLinearTransiogram model by Li et al.

Below is an example where transition probabilities are estimated for 4 categorical values DebrisFlow, Floodplain, Overbank and Channel along the vertical direction.

Another function that was introduced recently is eachvertex, which can be used to iterate over the vertices of a polytope (polygon, segment, etc.) or mesh (e.g. grid) without memory allocation:

for v1 in eachvertex(g1)
  for v2 in eachvertex(g2)
    ...
  end
end

Various other performance optimizations related to eachvertex were implemented to speed things up and reduce the memory usage of specific algorithms.