HB370 Data Management (3ECTS)

1 Spatial data modelling, collection, and storage

2 Spatial data processing and visualization with Python and GeoPandas (with hands-on)

3 Advanced geo-programming with Python (with hands-on)

4 Spatial DBMS, Spatial query Languages (with hands-on)

5 Spatial data analysis and visualization with GIS (with hands-on)

6 Open standards in the Geospatial domains

- Spatial interoperability, why open standards, OGC

- WMS/WFS/WCS, GML, metadata

- Spatial data infrastructures (SDI)

- The EU INSPIRE

1. To be able to create the required data types, part of a standard exchange format and

to configure systems for secure storage, transfer and backup of survey data.

2. To be able to identify potential data quality issues and apply data cleaning or

transformation techniques to assess, accept and reject data.

3. To be able to apply spatial data processing methods to create digital terrain models

or gridded surfaces and contouring. 4. To explain the concepts of Spatial Data

Infrastructures (SDIs); raster and vector data models; open geospatial standards

(WMS/WFS/WCS/GML) and metadata.

5. To be able to use file types that support the exchange of (hydrographic) data to

transfer data between acquisition, database and GIS environments.

6. To be able to manage and query spatial data in a spatial database (i.e., PostGIS)

7. To be able to use Python to analyze, processing, and visualize spatial (hydrographic)

data.

8. To be able to use GIS software (i.e., QGIS) to analyse, processing, and visualize spatial (hydrographic) data.

• Evaluation form

Written examination with open questions and programming exercises.

Assignments – permanent evaluation of the practical exercises