Teacher: Giovanna Venuti
Supervisor: Ing. Gianluca Murdaca – MindEarth
Description: The goal of this project is to design and generate a geospatial dataset in GeoZarr format according to the emerging GeoZarr specifications. The student will study the current conventions, identify the required metadata and structure for georeferenced multidimensional raster data, and implement a prototype workflow to convert an existing internal dataset into a valid GeoZarr representation. The project will also assess practical aspects such as metadata organization, coordinate reference system encoding, chunking strategy, multiscale support, and compatibility with available tools and validators. The final deliverable will include a working example GeoZarr dataset, documentation of the adopted design choices, and an evaluation of the format’s suitability for the company’s geospatial data infrastructure.
Difficult level: Medium
Requirements: Basic knowledge of Python, raster data, multidimensional arrays, and geospatial metadata. Familiarity with Zarr, cloud-native formats, and geospatial standards is beneficial. Knowledge of STAC or OGC-related specifications is a plus but not mandatory.