geostatistics

Curated from repositories that make our lives as geoscientists, hackers and data wranglers easier or just more awesome

Kriging Toolkit for Python

Well-documented Python demonstrations for spatial data analytics, geostatistical and machine learning to support my courses.

GSTools - A geostatistical toolbox: random fields, variogram estimation, covariance models, kriging and much more

An extensible framework for high-performance geostatistics in Julia

GeostatsPy Python package for spatial data analytics and geostatistics. Mostly a reimplementation of GSLIB, Geostatistical Library (Deutsch and Journel, 1992) in Python. Geostatistics in a Python package. I hope this resources is helpful, Prof. Michael Pyrcz

Geostatistical variogram estimation expansion in the scipy style

Fast, memory-efficient 3D spline interpolation and global kriging, via RBF (radial basis function) interpolation.

Geostatistics in Python

A set of numerical demonstrations in Excel to assist with teaching / learning concepts in probability, statistics, spatial data analytics and geostatistics. I hope these resources are helpful, Prof. Michael Pyrcz

Analysis of digital elevation models (DEMs)

GeoStats.jl tutorials

These are python notebooks accompanying Lessons available at GeostatisticsLessons.com

Fast image quilting simulation solver for the GeoStats.jl framework

Use SGeMS (Stanford Geostatistical Modeling Software) within Python.

A flexible MPS framework

GammaRay: a graphical interface to GSLib and other geomodeling algorithms.

The STK is a (not so) Small Toolbox for Kriging. Its primary focus is on the interpolation/regression technique known as kriging, which is very closely related to Splines and Radial Basis Functions, and can be interpreted as a non-parametric Bayesian method using a Gaussian Process (GP) prior.

Turing patterns simulation solver for the GeoStats.jl framework

A High Performance Unified Framework for Geostatistics on Manycore Systems.