Application deadline

Type of course

Master course for biology students - principally aimed at MSc-students specializing in Northern Populations and Ecosystems. In addition to the Campus based teaching, BIO-3111 offer an alternative web based, distance eLearning solution.

The course is available as a singular course.

Admission requirements

Local admission , application code 9371  - Master`s level singular course.

Admission requires a Bachelor`s degree (180 ECTS) or equivalent qualification, with a major in biology of minimum 80 ECTS.

Recommended prerequisites: Students should have some familiarity with geographic information systems (GIS), basic statistics and general knowledge of practical use of computers.

Course content

Objectives of the course

Knowledge:

• The meaning and importance of datum and projections in spatial data
• The physical background for remote sensing emphasizing the properties of electromagnetic radiation
• Principles of global navigation satellite systems (GNSS), its importance in gathering spatial reference data and integration in GIS
• Different remote sensing platforms (Drones/UAV and space borne satellites), active (radar and LIDAR) and passive (visible, infrared, thermal) sensors and application of multi- and hyperspectral data
• Understand the nature of raster data and basis of image processing (restoration, enhancement, transformation) 
• Background of image analyzing techniques (time serial and change detection), classification (supervised, unsupervised) and spatial interpolation and regression

Skills/ Learning outcome:

• How to find, download, store and implement remote sensing data in GIS
• Create informative and visual attractive maps by combining basis topographical data and thematic data layers from open access web based services 
• Extract and analyze information by selective query in tabular data and visualize it in maps 
• Determine land cover or other earth features by means of different classification methods  
• Application of different image processing techniques to improve the visibility and information content of raster data 
• Create new data layers by Boolean query in raster data and combine them in multi-criteria suitability mapping 
• Application of different image processing techniques to improve the visibility and information content of raster data
• Create informative and visual attractive maps by combining basis topographical data and thematic data layers
• Determine land cover or other earth features by means of different classification methods 
• Extract and analyze information by selective query in tabular data and visualize it in maps
• Create new data layers by Boolean query in raster data and combine them in multi-criteria suitability mapping
• Application of spatial multivariate analysis such as principle component analysis (PCA) for noise removal, data redundancy and change detection
• Apply regression techniques to analyze spatial relationships and heterogeneity
• Do simple Python scripting in order to understand how to be more efficient and productive within a GIS

General competence:

• Understand the importance and usefulness of GIS and remote sensing as tools for solving practical environmental problems, presenting thematic data and as a management system for spatial data
• Independent complete a practical GIS project using remote sensing data, image processing and analyzing techniques and present the results in a written report

Language of instruction and examination

Teaching methods

Information to incoming exchange students

This course is open for inbound exchange student who meets the admission requirements. Please see the "Admission requirements" section.

Do you have questions about this module? Please check the following website to contact the course coordinator for exchange students at the faculty: https://en.uit.no/education/art?p_document_id=510412