liminfoStereonet Reference
Free reference guide: Stereonet Reference
About Stereonet Reference
The Stereonet Reference is a specialized guide for structural geologists covering the fundamentals and advanced techniques of stereographic projection. It includes six categories: Basics (strike/dip, dip direction, trend/plunge, rotation, Fisher statistics, field measurement conventions), Projections (Schmidt equal-area and Wulff equal-angle nets), Plotting methods (great circles, poles, contour diagrams, rose diagrams, small circles), Structural Analysis (beta and pi diagrams, eigenvector analysis, fold axis determination, joint analysis, fault kinematic analysis), and Software tools.
Each entry provides clear explanations of geological concepts with practical notation examples, conversion formulas, and interpretation guidelines. For instance, the strike/dip entry explains both right-hand rule and dip-direction conventions, the contour diagram entry covers Kamb and Fisher statistical methods, and the fault analysis entry details P-T axis and Bingham stress tensor estimation. This makes the reference useful for both classroom learning and field application.
The software section includes ready-to-use Python code examples for mplstereonet (Matplotlib-based stereonet plotting), covering great circle and pole plotting, density contouring, and mean vector calculation. It also documents Allmendinger Stereonet 11 and InnStereo open-source tools. Whether you are analyzing joint sets from field measurements, determining fold axes from bedding data, or preparing publication-quality stereographic projections, this reference provides the essential formulas and workflows.
Key Features
- Complete strike/dip and dip-direction/dip notation systems with conversion formulas and right-hand rule explanation
- Schmidt (equal-area) and Wulff (equal-angle) projection methods with guidance on when to use each
- Great circle, pole, contour diagram, and rose diagram plotting techniques with interpretation guidelines
- Fold axis determination using beta diagrams, pi diagrams, and eigenvector analysis methods
- Fault kinematic analysis including slickenline measurement, P-T axis analysis, and Bingham stress tensor
- Ready-to-use mplstereonet Python code examples for plotting and statistical analysis
- Fisher statistics reference including kappa concentration parameter and alpha-95 confidence cone
- Field measurement conventions covering Brunton compass usage and data recording notation
Frequently Asked Questions
What is a stereonet used for in structural geology?
A stereonet is a tool for projecting three-dimensional orientation data (planes and lines) onto a two-dimensional circular diagram. Structural geologists use it to visualize and analyze bedding attitudes, joint sets, fold geometries, fault planes, and lineations. The lower-hemisphere projection is standard in geology, allowing patterns in orientation data to be recognized and quantified.
What is the difference between Schmidt net and Wulff net?
The Schmidt net (equal-area or Lambert projection) preserves area proportions, making it ideal for density contouring and statistical analysis of pole distributions. The Wulff net (equal-angle or stereographic projection) preserves angular relationships, making it better for measuring angles between planes and lines. Structural geology predominantly uses the Schmidt net for data analysis.
How do I convert strike/dip to dip direction/dip notation?
For right-hand rule notation, dip direction equals strike + 90 degrees. For example, a plane with strike N30E/45SE (or 030/45SE) has dip direction 120 and dip 45, written as 120/45 in dip direction/dip notation. The dip direction/dip format is internationally more common because it is unambiguous without specifying a dip direction quadrant.
How do I determine a fold axis from stereonet data?
Two main methods exist: the Beta diagram plots great circles of bedding planes, and their intersection point gives the fold axis. The Pi diagram plots poles of bedding planes; these poles fall on a great circle whose own pole is the fold axis (pi axis). The Pi method is generally more precise for cylindrical folds. Eigenvector analysis of the orientation tensor provides a quantitative alternative.
What is Fisher statistics in the context of orientation data?
Fisher statistics is a probability distribution for directional data on a sphere. The kappa (k) parameter measures concentration: larger k means tighter clustering. Alpha-95 is the half-angle of the 95% confidence cone around the mean direction. R is the resultant vector magnitude. These statistics quantify how well-clustered your orientation measurements are and are essential for reporting mean directions.
How does the Kamb contouring method work?
Kamb contouring calculates the density of poles at each point on the stereonet based on a counting circle whose size is determined by sample size to achieve a specified level of statistical significance. Unlike simple percentage contouring, Kamb contouring accounts for the expected distribution under randomness, making density maxima more meaningful. Results are typically displayed as color-coded contour maps.
What Python libraries can I use for stereonet plotting?
The mplstereonet library is the most popular Python package for stereonet work. It integrates with Matplotlib and provides functions for plotting great circles (ax.plane), poles (ax.pole), lines (ax.line), density contours (ax.density_contourf), and calculating mean vectors (find_mean_vector). InnStereo is another open-source Python alternative with a GTK+ GUI.
What is P-T axis analysis for fault data?
P-T axis analysis determines the compression (P) and tension (T) axes from fault plane and slickenline (striation) data. For each fault, the P axis bisects the acute angle between the fault plane and auxiliary plane on the side of movement, while T bisects the obtuse angle. Combining P-T axes from multiple faults enables estimation of the paleostress field using Bingham distribution analysis.