This dataset supplements the scientific article by Pierri-Daunt and Siedentop (2025), which introduces a classification system for 18 cities in Latin America and the Caribbean (LAC), encompassing a total of 253 municipalities. It provides the dataset used for the classification, along with the cluster numbers assigned to each group.

The dataset combines various socioeconomic, demographic, and spatial characteristics of built-up areas at two scales of analysis: the city–regional scale (Data.city.origin.3HC.csv) and the municipal scale (Data.munic.orig.3HC.csv). Its purpose is to classify, compare, and identify cities and municipalities with similar typological features.

A complete description of the methodology and data sources can be found in README.txt and dataset_description_sources_information_PIerriDaunt_ISFULAC.pdf.

We identified three primary categories. City scale: Cluster 1 (saturated and well-serviced cities); Cluster 2 (vulnerabilized and dense cities); Cluster 3 (low-service and fragmented cities); Municipal scale: Cluster 1 (central, infilling, dense and well-serviced municipalities); Cluster 2 (building up at the edge and vulnerabilized); Cluster 3 (expanding, marginalized and low-density).

This dataset supplements the scientific article by Pierri-Daunt and Siedentop (2025), accepted on November 5, 2024, for publication in the Applied Geography journal. This work was funded by the Swiss National Science Foundation through the Postdoc Mobility grant P500PS_206567, acquired and managed by Ana Beatriz Pierri Daunt