Analysis and visualization of spatial data in GIS 2800-OG-EN-AVOSD

The most important issues covered in the course:
1. Spatial socio-economic data resources (data, geoservices/geoportals)
2. Spatial analysis of socio-economic data part 1: Selected elements of vector analysis, network analysis and spatial statistics.
3. Spatial analysis of socio-economic data part 2: Selected elements of raster analysis.
4. Spatial analysis of socio-economic data part 3: Selected advanced methods of spatial analysis.
5. Spatial Data Modeling.
6. Analysis and Visualization of Environmental Data.
7. Digital Terrain Model (DTM) and Digital Surface Model (DSM)
8. Spatial analysis based on elevation data.
9. GIS 3D.
10. Visualization of space in 3D.

Total student workload

Contact hours with teacher (35 hrs): - participation in laboratory – 30 hrs - consultations – 5 hrs Self-study hours (65 hrs): - reading literature – 10 hrs - preparation for laboratory – 25 hrs - projects preparation – 30 hrs (15+15) Altogether: 100 hrs (4 ECTS)

Learning outcomes - knowledge

W1: Student knows the basic concepts of modeling and visualization (2D and 3D) of spatial data. W2: Student knows the basic sources of elevation and socio-economic data. W3: Student knows the contemporary trends and directions of development of GIS technology.

Learning outcomes - skills

U1: Student is able to select the correct methodological approach in spatial data analysis at intermediate and advanced levels. U2: Student skillfully acquires and processes elevation data and socio-economic data from various sources. U3: Student is able to operate GIS software at a level that allows independent performance of spatial analyses on Digital Terrain Models and socio-economic data. U4: Student is able to prepare a 2D/3D visualization of a terrain fragment in GIS software.

Learning outcomes - social competencies

K1: Student understands the need for lifelong learning, sees the need to constantly expand knowledge and improve professional competences. K2: Student is able to determine the priorities for the implementation of a specific task. K3: Student understands the importance of responsibility (including professional responsibility) for independently prepared analyses and visualizations.

Teaching methods

Exploratory teaching methods: - exercise; - laboratory; - project.

Type of course

elective course

Prerequisites

Knowledge of ArcGIS and QGIS software will be helpful but not required.

Course coordinators

Radosław Golba
Agnieszka Pilarska

Assessment criteria

A student will receive a positive grade for the course if they meet the following conditions:
- attendance at classes (minimum 80% of classes) (W1, W2, W3, U1, U2, U3, U4, K1, K2, K3);
- all project works completed correctly and passed on time (W1, W2, W3, U1, U2, U3, U4, K1, K2, K3).

There will be two main projects to be made for assessment: one from the socio-economic part and the other from the environmental and visualization part.

Additional information

Additional information (registration calendar, class conductors, localization and schedules of classes), might be available in the USOSweb system:

Description of 2800-OG-EN-AVOSD in USOSweb