Publication Details |
| Category | Text Publication |
| Reference Category | Journals |
| DOI | 10.5194/gmd-15-3161-2022 |
Licence  |
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| Title (Primary) | GSTools v1.3: a toolbox for geostatistical modelling in Python |
| Author | Müller, S.
; Schüler, L.; Zech, A.; Heße, F. |
| Source Titel | Geoscientific Model Development |
| Year | 2022 |
| Department | CHS |
| Volume | 15 |
| Issue | 7 |
| Page From | 3161 |
| Page To | 3182 |
| Language | englisch |
| Topic | T5 Future Landscapes |
| Data and Software links | https://doi.org/10.5281/zenodo.4891875 https://doi.org/10.5281/zenodo.5159578 https://doi.org/10.5281/zenodo.5159658 https://doi.org/10.5281/zenodo.5159728 |
| Abstract | Geostatistics as a subfield of statistics accounts for the spatial
correlations encountered in many applications of, for example, 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,
variogram estimation and much more. We demonstrate its abilities by
virtue of a series of example applications detailing their use. |
| Persistent UFZ Identifier | https://www.ufz.de/index.php?en=20939&ufzPublicationIdentifier=26076 |
| Müller, S., Schüler, L., Zech, A., Heße, F. (2022): GSTools v1.3: a toolbox for geostatistical modelling in Python Geosci. Model Dev. 15 (7), 3161 - 3182 10.5194/gmd-15-3161-2022 |
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