By: Júlio Hoffimann

Re-posted from: https://juliohm.github.io/science/geodatascience/

Geospatial Data Science with Julia
presents a fresh approach to data science with
geospatial data and the Julia programming language.
It contains best practices for writting clean, readable
and performant code in geoscientific applications
involving sophisticated representations of the (sub)surface
of the Earth such as unstructured meshes made of 2D and
3D geometries.

By reading this book, you will:

1. Get a broader perspective on geospatial data
2. Learn advanced geostatistical algorithms
3. Reproduce practical open source examples

Most importantly, you will learn a set of geospatial features
that is much richer than the
simple features
implemented in traditional geographic information systems (GIS).

If you would like to support the book,
consider starring it on GitHub:
https://github.com/JuliaEarth/geospatial-data-science-with-julia

By: Júlio Hoffimann

Re-posted from: https://juliohm.github.io/science/hilbert-kriging/

How to interpolate objects in Hilbert spaces?

In this tutorial, we illustrate the concept with
a practical application in climate sciences.

By: Júlio Hoffimann

Re-posted from: https://juliohm.github.io/science/geostats-foss4g-workshop/

FOSS4G is the largest international
conference on geospatial open source software. I invite
everyone to participate in the GeoStats.jl workshop therein.

We will cover the basics of the Julia programming language
and the powerful stack we are building for advanced geostatistics.
You can find more details
here.