This repo is part of a collaboration between the University of Trento's teachers M. Napolitano, D. Giuliani and Transform Transport for the course of Geospatial Analysis.
In this project, I attempt several analyses - mainly clustering and a simple spatial autoregression - to analyze the heat distribution and its relationship with the urban surroundings in a downtown neighbourhood in Milan.
For a complete list of modules utilized in this repository, please check "requirements.txt". This whole project was implemented on pyhton 3.8, using mostly sci-kit, pandas, geopandas and numpy, and
You can find the report here. At the time of writing, no indication or recommendation was explicit for this project from teachers, but only from Transform Transport. I was the only student who decided to take up the opportunity; although I loved the geospatial analysis course, this was an incredibly difficult challenge given it is my very first geospatial project, which could explain the underperforming models.