Data and scripts underlying the publication: Global search inversion for electromagnetic induction data using layered models
doi:10.4121/04ee8881-c4be-4c37-acbc-ca16efdf638d.v1
The doi above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future.
For a link that will always point to the latest version, please use
doi: 10.4121/04ee8881-c4be-4c37-acbc-ca16efdf638d
doi: 10.4121/04ee8881-c4be-4c37-acbc-ca16efdf638d
Datacite citation style:
Carrizo Mascarell, Maria; Werthmüller, dieter; Slob, Evert (2024): Data and scripts underlying the publication: Global search inversion for electromagnetic induction data using layered models. Version 1. 4TU.ResearchData. software. https://doi.org/10.4121/04ee8881-c4be-4c37-acbc-ca16efdf638d.v1
Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite
Software
CC BY 4.0
The repository contains Python scripts to calculate lookup tables using semi-analytic and low induction number approximation forward models of frequency domain electromagnetic induction measurements of 2-layered electrical conductivity earth models. Additionaly, the repository holds field data acquired using a DUALEM842s instrument. Finally, Jupyter Notebooks scripts to display the results.
history
- 2024-10-10 first online, published, posted
publisher
4TU.ResearchData
format
python
associated peer-reviewed publication
Global search inversion for electromagnetic induction data using layered models
code hosting project url
https://github.com/mariacarrizo/NSG2023-EMinversion/
funding
- Rijksdienst voor Ondernemend Nederland (RVO) project WarmingUP (project number TEUE819001)
organizations
TU Delft, Faculty of Civil Engineering and Geosciences, Department of Geoscience and Engineering
DATA
To access the source code, use the following command:
git clone https://data.4tu.nl/v3/datasets/92494f17-c1aa-4c07-b79e-7ae08c3da4ed.git "NSG2023-EMinversion"
