Teacher: Giovanna Venuti
Supervisor: Ing. Gianluca Murdaca – MindEarth
Description: The project aims to analyze multi-temporal geospatial data related to urban expansion and identify recurring morphological patterns of urban growth through clustering techniques. The student will work on features extracted from binary raster maps of built-up areas at different time steps, with the objective of grouping areas showing similar growth behaviors, such as infill, edge expansion, fragmentation, or densification.
Difficult level: Medium
Requirements: Python, basic GIS and raster data analysis, basic machine learning