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.

The course will be held over a two-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.

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

Restricted to the following study programmes:

MASV-GEOG Masterprogram i geografi

MASV-MEHA Master's Programme in Geographies of Sustainable Development

MASV-PHYG Master's Programme in Physical Geography

INTL-SV/PSYK/MN/MED/JUS/HF/KMD International students at all UiB faculties

Interested students from other programmes and exchange students are welcome to contact the Department of Geography (Studieveileder.geog@uib.no).

Portfolio assessment and oral poster presentation.

• Portfolio assessment: The portfolio contains a group assignment (25%) and a poster presentation (75%)
• Presentation: The oral poster presentation may adjust the grade

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