How to visualize large volume of geospatial data

How to visualize large volume of geospatial data

A common problem developers and UX designers face when dealing with geospatial data is visualizing huge volumes of data. I have personally worked on some projects that required rendering millions of data points on a map.

In this guide, I’ll walk you through some of the techniques that I’ve discovered while dealing with huge datasets. Here are some solutions you might find useful:

1> Use GPU rendering
-> Frontend development has progressed a lot in recent years, and one of the big improvements is the advent of WebGL. WebGL allows you to render your browser’s content on the GPU instead of the CPU. This allows you to leverage the power of the GPU and create very performant applications even if you have to render millions of data point

You can manually setup your website to use WebGL, but that is a lot of work. So I recommend using tools like VisGL and Deck.gl to make the development process much easier and smoother.

2> Data filtering
-> Now this is more of a UX decision than a coding decision. If you’re unable to load all the data at once, consider adding filters to your web-views, so that the user can filter the data in various ways like: time, geography, type, etc. This will decrease the amount of data in a single instance and should help with rendering

3> Data Clustering
-> Also more of a UX decision, see if it makes more sense to cluster the data, instead of showing the whole dataset at once
 

4> Pre-process The Data On The Server
-> Sometimes you may have some pre-processing in place, where you might have to sort the data before rendering the data. Generally, it makes sense to do this processing on the frontend code, but since this pre-processing process shares memory with the rendering process, this could affect the rendering speed and performance. In this case, you could try doing this pre-processing on your server code, so that your frontend can solely focus on the rendering process