Preprints
https://doi.org/10.5194/egusphere-2022-1224
https://doi.org/10.5194/egusphere-2022-1224
18 Nov 2022
 | 18 Nov 2022

GStatSim V1.0: a Python package for geostatistical interpolation and simulation

Emma Johanne MacKie, Michael Field, Lijing Wang, Zhen Yin, Nathan Schoedl, Matthew Hibbs, and Allan Zhang

Abstract. The interpolation of geospatial phenomena is a common problem in Earth sciences applications that can be addressed with geostatistics, where spatial correlations are used to constrain interpolations. In certain applications, it can be particularly useful to perform geostatistical simulation, which is used to generate multiple non-unique realizations that reproduce the variability of measurements and are constrained by observations. Despite the broad utility of this approach, there are few open-access geostatistical simulation software. To address this accessibility issue, we present GStatSim, a Python package for performing geostatistical interpolation and simulation. GStatSim is distinct from previous geostatistics tools in that it emphasizes accessibility for non-experts, geostatistical simulation, and applicability to remote sensing data sets. It includes tools for performing non-stationary simulations and interpolations with secondary constraints. This package is accompanied by a Jupyter Book with user tutorials and background information on different interpolation methods. These resources are intended to significantly lower the technological barrier to using geostatistics and encourage the use of geostatistics in a wider range of applications. We demonstrate the different functionalities of this tool for the interpolation of subglacial topography measurements in Greenland.

Emma Johanne MacKie et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2022-1224', Mirko Mälicke, 07 Jan 2023
  • RC2: 'Comment on egusphere-2022-1224', Joseph MacGregor, 10 Feb 2023

Emma Johanne MacKie et al.

Emma Johanne MacKie et al.

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Short summary
Earth scientists often have to fill in spatial gaps in measurements. This gap-filling or interpolation can be accomplished with geostatistical methods, where the statistical relationships between measurements are used to inform how these gaps should be filled. Despite the broad utility of these methods, there are few freely available geostatistics software. We present GStatSim, a Python package for performing different geostatistical interpolation methods.