Module Information

Module Identifier
Module Title
Skills in Remote Sensing
Academic Year
Semester 2
Other Staff

Course Delivery

Delivery Type Delivery length / details
Lecture 5 x 2 Hour Lectures
Practical 11 x 2 Hour Practicals


Assessment Type Assessment length / details Proportion
Semester Assessment Coursework. fieldwork report based on analysis of remote sensing data (3000 words)   50%
Semester Exam 3 hours practical-based examination  50%
Supplementary Assessment Resubmission of failed assignment  50%
Supplementary Exam 3 Hours   Supplementary Exam  To be scheduled in F4, due to nature of computers used for exam.  50%

Learning Outcomes

On successful completion of this module students should be able to:

  1. Identify, for particular applications, the most appropriate remote sensing datasets.
  2. Independently using remote sensing software for the analysis of multispectral, hyperspectral, lidar and radar data.
  3. Implement approaches to the derivation of products from remote sensing data (e.g., vegetation indices and digital elevation models).
  4. Undertake field studies to support the interpretation and analysis of remote sensing data.
  5. Be able to apply an object oriented classification of remote sensing imagery

Brief description

The module is intended to provide students with a background in advanced processing and analysis of a range of remote sensing data for applications in physical geography, biology, computer science and physics. The module also includes a field visit within the local area, during which insight into the interpretation of remote sensing data acquired by a range of sensors will be obtained.


  1. Object-orientated image analysis and classification
  2. Techniques for change detection between datasets
  3. Hyperspectral data analysis
  4. Laser scanning
  5. Radar data anaylsis
  6. Thermal remote sensing data analysis

Module Skills

Skills Type Skills details
Application of Number Problem solving assignment
Communication Skills report writing and submission of a discussion paper. Discussion groups within the Blackboard teaching and learning environment
Improving own Learning and Performance Library and web-based referencing; literature review and discussions with scientists
Information Technology Use of commercial and open sources software for practical applications. Specific skills in programming and statistical analysis.
Personal Development and Career planning Awareness of scientific literature, functionality of software and programming. Provision of advice and information for careers.
Problem solving Image classification through programming and development of skills in remote sensing data interpretation; awareness of scientific literature and future directions for research.
Research skills Basic strategies relating to remote sensing data sources and acquisition strategies, data integration and processing within the framework of a GIS and effective analysis and interpretation of remote sensing data, field data collection to support interpretation of remote sensing data. Reviewing literature.
Subject Specific Skills As above
Team work Fieldwork will be undertaken in groups who will be involved in decisions relating to data collection and image analysis and interpretation


This module is at CQFW Level 7