Practical Skills in Remote Sensing and Spatial analysis

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.

On completion of the course the student should have the following learning outcomes defined in terms of knowledge, skills and general competence:

Knowledge

The student

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

Skills

The student

• can plan, manage and complete a remote sensing based study
• can acquire remote sensing data and assess the suitability for analysis
• can interpret remote sensing and GIS products and understand their metadata
• can choose appropriate methods/algorithms and apply such methods/algorithms to analyse optical, radar, and topographic data
• can automate the processing of spatial data using model builder and scripting
• can interpret, assess and discuss results of image analyses

General competence

The student

• 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