Deck.GL: High-Performance Visuals for Complex Geospatial Data
In my last post, we explored how MapLibre handles thousands of points using the GPU. But what if you want to go beyond circles and icons? What if you need 3D arcs, heatmaps, or custom animations that move with the wind? Deck.GL might be your answer.

Deck.GL is a high-performance, WebGL-powered visualization framework designed to handle massive datasets. But before we dive into the "how-to," we need to understand how it plays with others.

The "Tracing Paper" Concept

If a map application is a plain white sheet of paper, the basemap (like MapLibre or Mapbox) is the drawing—the mountains, the oceans, and the city streets. Deck.GL is like a sheet of magical tracing paper placed on top. It allows you to draw complex animations, 3D structures, or heatmaps that appear to float perfectly over the world below.

How It Works: Choosing Your Mode

When you integrate Deck.GL with a mapping engine, you have two primary ways to do it. Each has its own strengths.

The Overlaid Mode (The Performance Specialist)

This is the default mode where Deck.GL creates a completely separate canvas on top of the basemap.

Why use it: It’s incredibly fast. Because it doesn’t have to wait for the map’s own rendering cycle, it maintains high frame rates even if the basemap starts to lag.
The Trade-off: Since it’s a separate layer on top, you cannot "sandwich" Deck.GL layers behind map labels or buildings. You might also notice a very slight "drift" or lag between the map and the data when moving quickly.

ref: Base Maps Overlaid explanation (https://deck.gl/docs/get-started/using-with-map#overlaid)

The Interleaved Mode (The Visual Perfectionist)

In this mode, Deck.GL shares the same WebGL "brain" (context) as the mapping engine. It is treated as a custom layer within the map's own stack.

Why use it: It offers perfect synchronization. You can insert a Deck.GL layer underneath map labels or icons, making the data feel like a native part of the map. No drifting, no lag.
The Trade-off: Because they share the same resources, a very heavy Deck.GL layer can "choke" the map’s performance, leading to a stuttery experience if not managed carefully.

ref: Base Maps Interleaved explanation (https://deck.gl/docs/get-started/using-with-map#interleaved)

Layers in Action: Real-World Examples

Once your setup is ready, you can explore the Layer Catalog to find the right tool for your data. In my recent projects, I have worked closely with three specific layers to bring complex data to life.

1. BitmapLayer

The BitmapLayer is used to render an image (a bitmap) onto specified boundaries on the map. You provide the image data—whether it is a URL string, a texture, or an actual image object—and define the geographic "bounds" where it should appear. This is incredibly useful for accurate data overlays, and you can even use rendering options to customize the colors of the image at runtime.

2. ScatterplotLayer and PathLayer

Deck.GL really shows its power when you combine multiple layers. In a storm-tracking project, I used:

ScatterplotLayer: To paint a series of points representing "snapshots" of storm history data.
PathLayer: To connect those snapshots and visualize the storm's trajectory.

But the standard PathLayer can only show so much. Since Deck.GL lives inside a WebGL context, and we can use GLSL (a high-level, C-like language for graphics) to write custom shaders that enhance the layer's capabilities.

By adding custom GLSL code to the PathLayer, I was able to create an animated line that displays the direction and sequence of the storm. This "spiced things up" by providing vital information—the direction and flow of the storm—that a simple static line simply could not communicate.

Conclusion: Your Turn to Build

The examples I have shared today are just the tip of the iceberg. Deck.GL offers a massive playground for anyone looking to push the boundaries of what a map can do. Whether you are visualizing urban traffic flows, global flight paths, or complex environmental shifts, the power to create something truly impactful is in your hands.

I encourage you to dive into the official document, experiment with different combinations, and see how you can transform raw data into a compelling story. The world of geospatial data is vast; it is time to start building something powerful.

Read more:
https://deck.gl/

https://luma.gl/docs

https://en.wikipedia.org/wiki/OpenGL_Shading_Language

DeckGL - high performance map visualization tool