Discover How We Make Maps from Data Points
Interpolation is used in many fields, from photography to geology to GIS and remote sensing.
How Do We Get a Continuous Map from Discrete Data Points?
Much of the data that we have looked at in the Seagrass Adventure were created using interpolation. Interpolation is a method in which the value of data points in unsampled areas is estimated using measurements from nearby sampled areas. Scientists use this technique because there is never enough time or money to measure every point in the area of interest.
Interpolation is based on Tobler’s Law of Geography, which states that “everything is related to everything else, but near things are more related than distant things.” In other words, points closer together in space are more likely to have similar characteristics than points that are farther apart. This is called ‘spatial autocorrelation.’
Putting It Into Practice
Now that we know what interpolation is, let’s put it into practice. If we want to estimate the water quality of the Bay, we can use multiple stations set up around the Bay. At each station we can collect measurements, such as chlorophyll a and total nitrogen. Then, the data from each station were inputted into a computer algorithm to estimate the values of the areas in between the points. This way, we could use only a handful of stations to learn about the entire Bay.
There are many different computer algorithms used to interpolate data points. Scientists choose between different algorithms based on the type of data and how the data will be used. Depending on which one you use, the final map can look different (see maps below).
Try It At Home
Here’s an activity that you can do at home:
Put 3-5 M&Ms in a petri dish or low clear dish with water in it. Watch the colors merge. Did you notice how “data” from one point spread out into the surrounding area and merged with other “data” points? This is a similar to what scientists do when they interpolate discrete data. If you have the time, empty the dish and try it again using several different arrangements of color and position. What do you see?