Hierarchical population clustering: regions merge by attraction strength (population/distance⁴) – cities cluster first, continents last [OC]

**Data source:** Gridded Population of the World (GPW v4, SEDAC), 15 arc-minute resolution (~70,000 populated cells)

**Method:** Hierarchical clustering algorithm. Regions merge based on mutual attraction = (pop₁ × pop₂) / distance⁴. The algorithm iteratively merges the

pair with highest attraction until all regions connect.

**Visualization:** Each line shows a merge event. Color indicates merge order – early merges (neighborhoods, dense urban areas) start in black/navy/blue,

transitioning through the color spectrum to yellow/red for late merges (intercontinental connections).

**Related project:** https://jspenc4.github.io – 3D terrain visualizations of global population distribution

**Tools:** Java (clustering algorithm)