Aims and Fit of Module

This module will give students the opportunity to apply the key remote sensing principles and techniques that are used in environmental science in practical situations such as those used in spatial ecology, and environmental management.

Learning outcomes

A. demonstrate an understanding of the basics of remote sensing and image processing techniques.

B. comprehend common image classification methods


C. assess the accuracy of image processing results


D. demonstrate an understand the advanced image analysis skills, such as time series analysis, image fusion and hyperspectral analysis


E. select and apply a range of remote sensing techniques to examine environmental science problems

Method of teaching and learning

Lectures will introduce students to core remote sensing concepts. Practical skills will be developed through a series of well documented practical computer sessions, guided by lecturers. Each lab session carries a small summative mark as part of the Lab Portfolio (15%), providing students with direct credit for their hands-on work and ensuring timely engagement with practical exercises.

Skills reinforcement and personal development will be via independent work. The practical exercises take longer than the time span of the practical session and there is a requirement for further work before and after the lecturer-led session.

The module culminates in an Integrated Practical Report in which students apply both foundational and advanced remote sensing techniques to a single environmental research question, and a Live Demonstration & Viva in which each student demonstrates their ENVI workflow and answers structured questions to verify the authenticity and depth of their understanding.