In [2]:
import numpy as np
import matplotlib.pyplot as plt
%matplotlib inline
from IPython.display import Image
import pandas as pd
from numpy import random

Lecture 20:

  • We will work with directional data using rose diagrams and stereonets

Directions

Earth science is filled with directional data. Glacial striations, bedding planes, fault orientations, and geomagnetic field vectors are all forms of directional data. Dealing with directional data is quite different than other kinds of data, like lists of numbers, and we need special plots. Unless all the directions are in a single plane, if is often useful to project something that is inherently 3D onto a 2D plot.

To get started, we will consider directions in the horizontal plane, which are already 2D (no vertical component). Examples would be current directions in ancient rivers, or the direction of wind on the surface of the Earth.

One early fascination in Earth Science was the evidence for past glaciations. There are many clues to past glaciations (moraines, eskers, U-shaped valleys, etc.), but one that stands out as an interesting example of directional data is glacial striations. As glaciers flow over the surface of the Earth, they scratch it, making what are known as striations. When the ice melts back (as it is doing very rapidly), the striations remain as clues to their past movements.

In [3]:
Image(filename='Figures/glacier.jpg')
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