Spatial Clustering
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About
Spatial clustering is a core method in geospatial analysis for identifying how points, people, places, or events are distributed across space. Instead of treating data as isolated observations, clustering helps us detect patterns, revealing where concentrations or groupings occur — and just as importantly, where they do not.
Clustering allows us to transform large sets of point data into meaningful spatial insights that can guide research, decision-making, and planning.
Objectives
- Understand the concept of spatial clustering
- Learn how to prepare point data for clustering
- Apply K-Means, Hierarchical Clustering, and DBSCAN in Python
- Visualize clustering results on simple scatterplots and maps
| Type | Module |
|---|---|
| Level | Expert |
| Length | 1 hour |
| Earnable |
Completion of Spatial Clustering
|
| Topics |
geospatial geospatial data data processing Community: Spatial Turn |
Instructor
Chimdia Primus Kabuo
11 modules
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