Density Analysis

Aino enables you to explore spatial patterns in your data through density analysis, allowing you to understand where certain features or events are most concentrated on a map.

There are two main types of density analysis you can create in Aino:

1. Raster Heatmap (continuous surface visualization)

2. H3 Grid Density Map (hexagonal grid-based aggregation)

Raster Heatmaps

What Is a Raster Heatmap?

A raster heatmap visualizes data intensity across an area using color gradients. Each pixel on the map represents a value — for example, building density, temperature, or event frequency — mapped to a specific color. This method produces a smooth, continuous surface, ideal for showing gradual spatial changes.

How to Create a Raster Heatmap

You can easily create a heatmap using Aino’s AI Assistant.

Example prompts:

Build a raster heatmap of building density in Helsinki.

Visualize Bars in Manhattan as a heatmap

We recommend to use / to select the layer you want to style

Results appear as a changed data style for the selected data layer.

Adjusting Heatmap Style

• Click on the Heatmap dataset icon in the sidebar.

• Use the style panel to manually adjust:

  • Color gradients

  • Opacity

  • Radius and intensity

For more information about customizing visual styles, see the Data Visualization section of the documentation.

H3 Grid Density Analysis

What Is an H3 Grid?

H3, developed by Uber, is a hexagonal hierarchical spatial indexing system. It divides the Earth into a grid of hexagonal cells, each with a unique H3 ID. This allows you to aggregate or analyze data (like counts or averages) within each hex cell — instead of using raster pixels or irregular polygons.

What Does H3 Density Analysis Mean?

An H3 Density Map shows how many data points or features fall inside each hexagon.

Common examples:

• Counting the number of bars or restaurants in each neighborhood

• Summing population or incidents per cell

• Calculating average air pollution levels per area

How to Build an H3 Density Map

Use the AI Assistant to generate your H3 grid visualization.

Example prompt:

Build an H3 density map for bars in Manhattan.

Aino will process your dataset, group features into H3 hexagons, and visualize the density per cell. The result will be presented as a new dataset.

Adjusting H3 Grid Style

After the map is created:

1. Click on the H3 dataset icon.

1. Modify the color scale, labels, or legend appearance.

For more information about customizing visual styles, see the Data Visualization section of the documentation.

💡 Tips

• Use Raster Heatmaps for smooth, continuous data (e.g., population density, temperature).

• Use H3 Grids for discrete or event-based data (e.g., location of buildings, incidents, or services).

• Combine both layers to compare continuous vs. discrete density patterns.