The research project aims at building a new methodological framework to delineate, characterize and compare the geographic features of perceived neighborhoods and regions within a city.
The identified gap and research aim lead to the main objectives of this project:
- to develop a map-based survey application that collects dwellers’ perceptions of different regions of the city;
- to apply state-of-the-art spatial analysis and machine learning methods for generating regions from primary (survey) and secondary (geotagged user generated content) sources of data;
- to assess the outputs using sociodemographic variables, features of the urban settings and official administrative boundaries.
The main challenge of our approach is to effectively design a framework that enables the generation and visual representation of regions while considering the specific nature of each data source. Nonetheless, the research team members have conducted high-quality research in the areas of urban intelligence; geographic information systems and science; smart cities; social media analysis; as well as spatial statistics, modeling and analysis.