Geospatial Data Management
A.Y. 2021/2022
Learning objectives
The course aims at providing key concepts for the understanding of geospatial and mobility data, as well as the basic competences for the management of such information through spatial and spatio-temporal databases.
Expected learning outcomes
Students are expected to be able to utilize and integrate georeferenced data from heterogeneous sources. Moreover, students will be able to organize and query geospatial and mobility data using both a spatial DBMS and a GIS platform, and, in addition, to use a few analytical functions.
Lesson period: First semester
Assessment methods: Esame
Assessment result: voto verbalizzato in trentesimi
Single course
This course cannot be attended as a single course. Please check our list of single courses to find the ones available for enrolment.
Course syllabus and organization
Single session
Responsible
Lesson period
First semester
The course will be provided on-line and sychronously. The communication platform is Zoom. The content of the program does not change, but the lab activity will be reduced. The examination form does not change.
Course syllabus
The course is organized in two parts.
Part I: introduction to the basic notions on spatial coordinate systems, OGC SImple Feature model for the representation of spatial data in vector format, the PostGIS spatial database and the QGIS platform.
Parte II: introduction ot the models for the representation of spatial trajectories:; introduction to spatial data analysis with focus on clustering methods applied to spatial data and segmentation techniques applied to trajectories
Part I: introduction to the basic notions on spatial coordinate systems, OGC SImple Feature model for the representation of spatial data in vector format, the PostGIS spatial database and the QGIS platform.
Parte II: introduction ot the models for the representation of spatial trajectories:; introduction to spatial data analysis with focus on clustering methods applied to spatial data and segmentation techniques applied to trajectories
Prerequisites for admission
Basics in data management
Teaching methods
Frontal lessons, exercises on PC, seminar on research topics
Teaching Resources
Slides, textbook: PostGIS in Action, Manning Editor
Assessment methods and Criteria
Oral test plus project
ING-INF/05 - INFORMATION PROCESSING SYSTEMS - University credits: 6
Lessons: 48 hours
Professor:
Damiani Maria Luisa
Professor(s)