There are 0 repository under sedimentology topic.
Lithology and stratigraphic logs for wells or outcrop.
Basin and Landscape Dynamics model
python port of the USGS bedforms software tool
Badlands workshop & examples
Repository of upcoming abstract submission deadlines for geoscience conferences
Docker image for badlands
a paleocurrent plotter for plotting a histogram and a rose diagram out of paleocurrent direction values given in azimuth degrees
The code snippets and repositories are for generating embedded markov model to establish facies changes in the stratigraphic succession
Lithology identification of point clouds from geological outcrops.
Estimate Age-Depth Models and Transform Data
CarboCATLite model by Peter Burgess
Python scripts for analyzing data extracted from TESCAN Integrated Mineral Analyzer (TIMA)
Plot equal-area Rose diagrams of palaeocurrent indicators. Input as a spreadsheet. Plot different types of indicators (e.g. ripples, flutes, imbrication) on the same graph, stacked or overlain.
Shiny app visualizing the effects of carbonate stratigraphy on trait evolution
Repository of classification of sedimentary structures using CNN and transfer learning.
SedSettle is a program for performing grain size analysis with a settling tube.
A simple 2D module containing example to illustrate some hierarchical geological concepts
Tools to analyse XRF Corescan data from sediment cores
Identification of sedimentary structures using CNN and transfer learning.
Open Educational Resource (OER): creating an evidence-based facies model based on modern Bahamas
Code repository for the paper "Stochastic 3D Modelling of Discrete Sediment Bodies for Geotechnical Applications" by G.H. Erharter, F. Tschuchnigg and G. Poscher
Code for "Identification of the Mode of Evolution in Incomplete Carbonate Successions"
Preservation of Orbital Forcing in Incomplete Carbonate Successions
Shiny app visualizing the effects of sedimentary condensation
A package to support sediment source fingerprinting studies: characterising your dataset, selecting tracers (three-step method), modelling source contribution (BMM) and assessing the quality of modelling predictions using virtual mixtures (support BMM and MixSIAR).
Lithofacies and temporal variation predict composition of Siluro-Devonian vertebrate, invertebrate, and plant communities