In this paper, we introduce a new spatially constrained clustering problem called the max-p-regions problem. It involves the clustering of a set of geographic areas into the maximum number of homogeneous regions such that the value of a spatially extensive regional attribute is above a prede- fined threshold value. We formulate the max-p-regions problem as a mixed integer programming (MIP) problem, and propose a heuristic solution.
Infraestructura pública y precios de vivienda: Una aplicación de regresión geográficamente ponderada en el contexto de precios hedónicos.
Python library with spatially constrained clustering algorithms
Interactive tool for visualizing the interindustry dynamics in Colombian economy.
RiSE-group enters the top 25% of RePEc's ranking of research in Economics and related fields in Colombia
Professor Ye is assistant professor at the School of Earth, Environment, and Society (Bowling Green State University).
Professor Sastré is the Director of Spatial-SEALab and full time Professor and Researcher of Spatial Econometrics at the Centro de Investigaciones Socioeconómicas, CISE, Universidad Autónoma de Coahuila.
The subdirector of prospective planning of Medellin City mentioned RiSE group in Tecnova
