TechnicalGIS

#Clustering

2 posts

Tutorial Python

DBSCAN and HDBSCAN spatial clustering in Python: finding Glasgow's dining districts

Cluster GPS and point-of-interest data in Python with DBSCAN and HDBSCAN: use the haversine metric on latitude and longitude or plain metres on a projected grid, choose eps with a k-distance plot, handle variable density with HDBSCAN, draw convex and concave hull polygons, treat noise properly, read silhouette and DBCV with care, and scale up with a BallTree. Uses 3,950 real Overture Maps restaurants, cafés and bars in Glasgow.

Intermediate 17 min read

Tutorial Python

Geodemographic classification in Python: k-means on Census 2021 Output Areas, and SKATER and max-p regionalisation

Build a small geodemographic classification of Cardiff's 1,115 Census 2021 Output Areas in Python: choose and transform variables from Nomis bulk tables, standardise them, check correlations, choose k for k-means with the elbow, silhouette and stability across seeds, profile and cautiously name the clusters with index scores and radar charts, compare the result with the official 2021/2 OAC, test the MAUP at LSOA level, and contrast it with contiguous regions from spopt's SKATER and max-p.

Intermediate 17 min read