Detection and Analysis of Unused Properties: Real Estate Analytics for the city of Padova

The issue of unused properties causes significant challenges in urban environments, affecting economic growth, social equity and sustainable development. This study focuses on the city of Padova, where, despite a high demand for housing, a considerable number of properties remain vacant or underutilized. The research aims to quantify the extent of this problem in the city and identify key factors contributing to property usage. By working with a comprehensive database provided by the Municipality of Padova, including Population and Land Registry data, the study implements various data cleaning and preparation techniques to create a reliable and accurate dataset. A binary classification model is then employed to categorize properties as used or unused, with water consumption data utilized as the primary indicator of usage. The findings of this study provide valuable insights for urban policy makers, highlighting the necessity of specific strategies to encourage the utilization of unused properties in order to address the housing issue in Padova. The methodologies and results presented in this dissertation aim to be used as a model for similar studies in other cities facing analogous challenges.