Home
Student Pages
Undergraduate course

Practical Skills in Remote Sensing and Spatial analysis

  • ECTS credits10
  • Teaching semesterSpring
  • Course codeGEOV316
  • Number of semesters1
  • LanguageEnglish
  • Resources

Main content

ECTS Credits

10 ECTS

Level of Study

Master

Teaching semester

Spring

Place of Instruction

Bergen

Objectives and Content

The aim of the course is to enable the student to understand the theory behind RS analyses and to complete practical RS based applications, using a range of sensors and methodologies.

This course introduces a selection of methods and analytical skills that can be used in practical applications within Earth Observation and Spatial Analysis. The course will cover a variety of topics that can be applied both for further studies and for future career prospects.

The course will focus on the theoretical foundations related to the preprocessing, analysis and post-analysis of remote sensing imagery, as well as the fundamental differences between different remote sensing platforms and sensors.

The course will cover topics such as land cover classification, change detection, photogrammetry and topographic analysis, and Radar Remote Sensing. Data such as aerial photos, digital elevation models, multispectral and SAR satellite imagery will be processed and manipulated during computer practicals.

Learning Outcomes

A student who has completed the course should have the following learning outcomes: 

Knowledge

The candidate can:

  • Describe and discuss a set of methods to analyse, interpret and assess remotely sensed imagery
  • Define and explain the key concepts and terminologies used in remote sensing
  • Describe how the electromagnetic spectrum interacts with the terrestrial environment
  • List key platforms and sensors and their characteristics
  • Identify and explain common processing pathways used in remote sensing
  • Describe and quantify error sources within remote sensing analyses

Skills

The candidate can:

  • Plan, manage and complete a remote sensing based study
  • Acquire remote sensing data and assess the suitability for analysis
  • Interpret remote sensing and GIS products and understand their metadata
  • Choose appropriate methods/algorithms and apply such methods/algorithms to analyse optical, radar, and topographic data
  • Automate the processing of spatial data using model builder and scripting
  • Interpret, assess and discuss results of image analyses

General competence

The candidate:

  • Can critically assess and draw on literature on remote sensing and GIS
  • Has sufficient knowledge and skills to conduct his/her own GIS and remote sensing investigations
  • Can work independently on a selection of proprietary and open-source software

Required Previous Knowledge

GEOV205 or similar

Credit Reduction due to Course Overlap

10 credit overlap with GEO316

Teaching and learning methods

The course will be held over a three-week period, which will consist of morning lectures/seminars and afternoon computer practicals. Lectures/seminars will introduce the theoretical aspects; computer labs provide the hands-on experience with a range of software, both open source and proprietary. After the teaching is over the students will work for approximately two weeks on their own assignments as well as a group report. The assignments will be assessed through a poster presentation and a short oral exam. The group reports will be presented infront of the cohort and will feature peer-assessment.

Compulsory Assignments and Attendance

Group presentation

Forms of Assessment

Portfolio assessment

  • Portfolio assessment: The portfolio contains a group assignment and a poster presentation
  • Presentation: The oral poster presentation may adjust the final grade.

All parts of the assessment must be passed in the same semester. 

Examination Support Material

None

Grading Scale

Ved sensur vert karakterskalaen A-F nytta. Graden A er best mogleg karakter, medan F er stryk.

Assessment Semester

Assessment in teaching semester

Contact

Exam information

  • Type of assessment: Mappevurdering med poster presentasjon

    Submission deadline
    10.02.2022, 15:00
    Withdrawal deadline
    01.05.2022
    • Exam part: Mappevurdering

      Examination system
      Inspera
      Digital exam
    • Exam part: Presentasjon