Geographic information systems in discovering and describing our world 2800-OG-EN-GISID

1. Introduction to GIS software covering both, open-source and commercial types
2. Spatial data characteristics, differences between raster and vector data and examples of their applications.
3. Integration and interaction of raster and vector data.
4. Spatial analyses on vector and raster datasets.
5. Digital Elevation Models (DEMs) – creation, interpolation, ready-to-use data sets, filtering techniques, visualization.
6. Spatial analyses based on DEMs, examples of modeling processes and phenomena.
7. Remote sensing data (satellite and aerial) – acquisition, processing and use in geographic research.
8. Application of basic methods for spatial data visualization.

Total student workload

Contact hours with teacher: - participation in classes – 30 hours - consultations – 6 hours - writing test – 4 hours Self-study hours: - preparation for classes – 10 hours - making projects – 30 hours - preparation for test – 20 hours Altogether: 100 hours (4 ECTS)

Learning outcomes - knowledge

W1: Student understands operations and issues of collecting, processing and visualizing data in Geographic Information Systems (GIS) software. W2: Student understands phenomena and processes occurring in geographic space and has the knowledge necessary to explain and interpret them. W3: Student knows methods used in geographical research. W4: Student has knowledge of the possibilities and limitations of GIS software, including both, open-source and commercial types.

Learning outcomes - skills

U1: Student is skilled in using GIS software, including both, open-source and commercial types. U2: Student is able to search, evaluate and use spatial data. U3: Student is able to select and apply specific GIS tools in solving given research problems and interpret the results correctly.

Learning outcomes - social competencies

K1: Student understands the importance of digital analysis methods, processing and visualization of spatial data in present-day earth sciences. K2: Student understands the issues associated with computer data analysis. K3: Student can interact in a group, taking different roles in it.

Teaching methods

laboratory, practical, project work

Exploratory teaching methods

- laboratory
- project work
- practical

Type of course

elective course

Prerequisites

Basic geographic knowledge and practical computer skills. Communicative English.

Course coordinators

Marcin Nowak

Assessment criteria

Assessment methods:
1. practical test – types of questions: short answer, matching, multiple choice – W1, W3, W4, U1
2. projects – W4
3. presence (min. 85%) and activity in the classes.

Criteria of test assessment:
- grade 2,0 – below 50%,
- grade 3,0 – 50-59%,
- grade 3,5 – 60-69%,
- grade 4,0 – 70-79%,
- grade 4,5 – 80-89%,
- grade 5,0 – 90% and more.

Practical placement

None.

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-GISID in USOSweb