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<title>mapschool: Interpolation: a free introduction to geo</title>
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<h1><a href='./'>mapschool: Interpolation</a></h1>
<p>a free introduction to geo.</p>
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<p>Whereas aggregation takes lots of data and distills it into something simpler to analyze and visualize, interpolation 'fills in the blanks' between values. Interpolation is often used for datasets like elevation, where you have raster data values that records the height of every inch of a mountain, but there are a few places missing from the data - what programmers call <code>null</code> values.</p>
<p>Interpolation looks at the values around the 'blanks' and assumes that the missing values are basically similar to what's around them - a missing pixel at the top of a mountain will be assumed to be pretty high, while one in a valley is assumed to be low.</p>
<p>There are many ways to interpolate point data:</p>
<ul>
<li><strong>Heatmaps</strong> assign each point a weight and represent density of point values in "hotter" colors.</li>
<li><strong>Contour lines</strong> take point sample data and draw lines around them that represent a continuous estimated value. Elevation maps often use this technique.</li>
<li>A <strong>TIN</strong> (Triangulated Irregular Network) draws triangles between points that can be used to visualize terrains.</li>
<li><strong>Voronoi diagrams</strong> take a set of points and turn them into polygons of all of the area around them.</li>
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