Density based geospatial clustering: Methods, Applications and Future Directions

Abstract

The emergence of the novel corona virus disease (COVID-19) since 2019 has been a cause of significant concern for people throughout the world. While tremendous effort has been put in to it by healthcare facilities, both public and private, it would not be a stretch to state that the resources allotted were not enough to handle the floods of covid and the non-covid patients at the same time. As the entire world was under lockdown, it was considerably tougher for people to move around. This meant getting check-ups for covid was fairly tough. Thus, building up many hospital camps around a city became important. In this article, the locations of different healthcare institutions and residential flats in and around the city of Bhubaneswar were analysed. Clusters were generated out of highly dense regions utilising a number of unsupervised learning density based clustering techniques and the best model was picked among them. Folium leaflet maps in Python were used to show the clusters created from the best performing clustering method. This would allow us to collect crucial information identifying areas in severe need of medical attention. Thus, resources can be divided evenly among the population with the information acquired.