Tutorial: GSTools, a toolbox for geostatistical modeling in Python
Channel: Software Underground
Date: 2022-04-25

Sebastian Müller

Things you need:
- Repository: https://github.com/GeoStat-Examples/gstools-transform22-tutorial
- Website: https://geostat-framework.org/
- Slack channel: #t22-mon-gstools (visit https://softwareunderground.org/slack to join)

Geostatistics as a subfield of statistics accounts for the spatial correlations encountered in many applications of e.g. Earth Sciences. Valuable information can be extracted from these correlations, also helping to address the often encountered burden of data scarcity. Despite the value of additional data, the use of geostatistics still falls short of its potential. This problem is often connected to the lack of user-friendly software hampering the use and application of geostatistics. We therefore present GSTools, a Python-based software suite for solving a wide range of geostatistical problems. We chose Python due to its unique balance between usability, flexibility, and efficiency and due to its adoption in the scientific community. GSTools provides methods for generating random fields, it can perform kriging and variogram estimation and much more. We demonstrate its abilities by virtue of a series of example application detailing their use.

Timestamps:
0:00:00 Start of live stream
1:34 Sebastian Müller presentation
2:40 GeoStat Framework
4:00 GSTools
9:00 GSTools Repository Tutorial
11:28 Installation
13:27 Citation
14:15 Introduction
22:37 Estimating and Fitting Variograms
26:14 The Covariance Model
53:01 Random Fields
1:11:25 Break
1:18:52 Variogram Estimation
1:39:50 Kriging
1:54:00 Conditioned Fields