This PhD course is part of the thematic path "Technologies, Techniques and Methodologies for Sustainable Development" of the PhD programme in Urban and Regional Development. Advanced geospatial data management functionalities require adopting and exploiting adequate data formats. The shapefile format is a de facto standard for vector geospatial data. Still, it has several limitations that, in an advanced environment, become unacceptable: shapefile limitations include physical aspects (e.g. file size, supported data types, attribute names, single geometry type per file, no raster storage, unknown character set, etc.) and functional ones (e.g. multi-editing and data integrity rules not easily implementable, complex data sharing due to its multi-file format, etc.) The main purpose of this PhD course is to: - describe geodatabase data formats and highlight how the adoption of such formats overcomes most of the shapefile limitations; - discuss the main geodatabase formats, both Open Source and commercial, highlighting the respective strong and weak points; - practice with the design, population, maintenance, and exploitation of geodatabases while working on real data. The course aims to provide the students with the expertise required to effectively handle, organize and manage (geo)spatial data, including both vector and raster datasets. Specifically, the students will be able to: - critically analyze the data model of the selected data; - select the proper geodatabase format depending on the project requirements; - correctly import the data in the adopted geodatabase format in a GIS environment. To develop the aforementioned expertise, the students will learn the fundamentals of databases with spatial extension and how to implement and handle them in both OS (QGIS) and COTS (ESRI) solutions, including advanced functionalities.

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The course topics are grouped into lectures and software exercises. The fundamentals of each subject are introduced with lectures and then applied to real datasets using two GIS software, namely QGIS and ESRI ArcGIS Pro. A course module will be in the form of Team-Based Learning (innovative teaching according to the guidelines of the University's Teaching Lab). The teaching program includes the following topics: - fundamentals of GIS (including coordinate and reference systems) and open data, with a focus on OpenStreetMap (4 h); - geodatabase fundamentals: overcoming shapefile limitations, improving data sharing (hosting vector and raster data in a single container), enabling multi-editing functions and increasing performance. An introductory overview of geodatabase solutions (DBMS with spatial extensions like PostgreSQL + PostGIS, OS solutions like OGC GeoPackage, commercial solutions like Geodatabase ESRI) (2 h); - GeoPackage and its exploitation in OS (QGIS) and commercial (ArcGIS Pro) software (2 h); - Geodatabase (ESRI) as GIS environment in commercial software, which allows the implementation and exploitation of "advanced" analysis models (e.g. subtypes, domains, networks, raster image mosaics, management of complex relationships, transport network datasets, etc. ) (4 h); - operational examples based on Open Data (8 h).

In presenza

Presentazione orale - Sviluppo di project work in team

P.D.1-1 - Gennaio