Creating contours with meaningful values from point data

Question

I recently obtained a CSV containing the locations of all recorded bicycle accidents in Boston over the past few years. As an avid cyclist, I'd like to create a simple contour map that draws attention to the intersections with the greatest accident densities to share with friends, colleagues, and city officials.

Using the Heatmap QGIS plugin and GDAL's contour tool, I created an aesthetically pleasing contour map, but my concern is that the numerical values are not easily digestible, largely because the heatmap plugin computes density using KDE, rather than point density.

I'd like to create contours that reflect the number of crashes within 400m of a given point. (So for example, any point within the highest "elevation" contours is within 400m of at least 8 crashes, while any point within the lowest "elevation is within 400m of at least 1 crash.) Is this possible? Or is there another, better way to visualize point densities using contours?

If it's any help, I generated my heatmap with a radius of 400m, a decay of 0, and X and Y values of 10 (so each cell is 10m x 10m). I converted the heatmap into contours using an elevation value of 1.

Answer 1

For representation along roads, it is better to use line features. You can split your road at an arbitrary size, then use a spatial join to compute the number of accidents. You then simply use a color scale to represent the density of accidents per road segment or unit road length.