Course aims at introducing advanced concepts in spatio-temporal data management, geovisualizazion and cartography, and spatial modeling, through a review of underlying theory and hands-on applications design and development.

Applications in such different fields as environmental and groundwater protection/remediation and natural resources vulnerability resources assessment should provide relevant background to understand the role of geospatial sciences and GIS in supporting policy making processes.

The course builds upon the foundation concepts in GIScience, providing an in-depth review of theory behind key building blocks of a geographic information system, namely spatio-temporal data management, cartography/geovisualization and spatial data analysis. Hands-on examples are worked through to provide practical evidence of design and implementation issues, using state-of-the-art open source tools, and discuss relevance in supporting and guiding policy making processes.

Program details:

• Spatio-temporal data management theory: general principles, relational data base (normalization, tables, relationships, views), basic SQL language and SQL spatial extensions;
• Spatial databases architectures: ESRI geodatabase architecture and data models, PostgreSQL/PostGIS and Oracle. Similarities and differences, advantages and shortcomings (technical, licensing, organizational);
• Hands-on tutorial on PostgreSQL/PostGIS multi-user concurrent database and how to integrate with different clients for different users: pgAdmin III, desktop GISs (proprietary ArcGIS and OS QuantumGIS), statistical and geostatistical analysis tools (R);
• Case study: design and development of a hydrogeological and environmental monitoring database, using PostgreSQL/PostGIS;
• Spatio-temporal data visualisation and cartography in Quantum GIS and ArcGIS;
• Spatial modeling with GIS: introduction to modeling, spatial statistics and geostatistics (variogram analysis and kriging), cartographic modeling and map algebra, advanced deterministic modeling. Examples in environmental vulnerability assessment supporting policy making, optimal sites selection;
• Brief overview of key concepts, relevance and options in automating and programming geospatial solutions: the examples of Python and ArcPy in ArcGIS, Model Builder, R programming language for data analysis and visualization.
• Design and architecture of Spatial Decision Support Systems: different coupling strategies (from loose to tight), integration and flexibility. Advanced case studies in groundwater hydrology, addressing resources availability in water scarse regions and agriculture-water-energy nexus, and groundwater protection/remediation in environmental contaminated sites.

The teaching material prepared by the lecturer in addition to recommended textbooks (such as for instance slides, lecture notes, exercises, bibliography) and communications from the lecturer specific to the course can be found inside the Moodle platform › blended.uniurb.it