Data Structures Appropriate to Introductory Geoscience.
Random measurements from a population or replicates on a specific sample are often also referred to as univariate data. Learn more here
One-dimensional spatial data and bivariate data. Temperature vs depth (in ocean, boreholes, or the atmosphere), elevation cross-sections, solar insolation vs latitude, etc. are all examples of one-dimensional spatial data. An example of bivariate data is temperature vs salinity for ocean water. Both types of data are easily visualized using x-y scatter plots. Learn more here
One-dimensional time series. Examples include tides (ocean and solid earth), seismic signals, temperature, pressure, elevation, solar irradiance, etc. as functions of time. This type of data is easily visualized using x-y scatter plots.Learn more here
Spatial Contour Plots are extremely common throughout the geosciences. Contour plots are very useful for visualizing and interpreting large data collected on a two-dimensional grid network. Examples of such data sets include elevation, surface air temperature, ocean salinity, atmospheric water content, or vegetation type.Learn more here
Two dimensional times series are best visualized by HovMoller plots in which the absicca (x-axis) is the time and the ordinate (y-axis) some spatial variable like latitude, height, or depth, and the measured quantity identified by isopleths or color contours.Learn more here