Undergraduate prospectus

Course Information

Introduction to Remote Sensing

Module summary

Module code: GEOL1008
Level: 7
Credits: 15
School: Engineering and Science
Department: Pharm, Chemical and Envi Science
Module Coordinator(s): Meredith Williams

Specification

Aims

The aim of this course is to introduce the students to the concepts and principles behind remote sensing and the characteristics of remotely sensed data, their collection, processing, and display. This course also aims to introduce basic image processing techniques through ‘hands‐on’ experience. This course explores the theories and techniques behind Earth Observation (EO) and remote sensing data acquisition.

The course also provides a theoretical introduction to a wide variety of remote sensing platforms and sensors. Students receive practical experience in dealing with a varied range of remotely sensed data using ERDAS Imagine, one of the most common commercial image processing packages. This course develops the basic concepts of image processing, which are dealt with in greater detail in the course GEOL 1009 ‘Advanced Image Processing’.

Learning outcomes

On successful completion of this course a student will be able to:

1 Critically reflect on the physics of electromagnetic spectrum and their importance in Earth Observation, specifically in the use of Visible, Infrared and Microwave remote sensing.
2 Critically evaluate the roles and limitations of satellite, aerial & terrestrial remotely sensed imagery in a variety of contexts.
3 Demonstrate a critical awareness of the hardware and software requirements for the interpretation of modern imagery data.
4 Critically analyse airborne photogrammetric data sets.

Indicative content

• The nature of the electromagnetic spectrum, the laws of radiation and physical principles of remote sensing.
• Interaction of radiation with the atmosphere and Earth surface.
• Introduction to remote sensing platforms and sensors; data capture and data types.
• Basic image pre-processing: noise & artefact removal, radiometric correction, atmospheric correction, geometric correction.
• Simple visual and numerical enhancement techniques for digital imagery; such as contrast stretching, convolution filtering, and hard classifiers.
• The theory of filter construction in the spatial and spectral domains; to include smoothing filters, edge enhancement filters and directional filters, Fourier filtering, and the problem of artefacts.
• Image histogram manipulation through linear and non-linear transforms.
• Visible to thermal infrared wavelength imaging.
• The basic principles of microwave remote sensing and RADAR.
• Photo-interpretation of aerial photographs, and analogue photogrammetric techniques.

Teaching and learning activity

A combination of lecture based teaching and lab based learning methods are employed to provide students with the necessary knowledge and opportunities to achieve the learning outcomes.
Lectures 50% of contact
Practical Work 50% of contact

Assessment

Method of summative assessment: Coursework 1
Nature of FORMATIVE assessment supporting student learning: Practical 1 formatively assessed.
Outcomes assessed:3,4
Grading Mode (e.g. pass/ fail; %): %
Weighting % :50%
Passmark: 50%
Word Length: 7 x <500 pro-forma
Outline Details:All eight of the compulsory 2 hours computing practicals will have a short answer sheet, for submission within one week of the practical. Practicals 2-8 will be assessed, and a combined score assigned at the end of the course.

Method of summative assessment: Exam
Outcomes assessed:1,2,3,4
Grading Mode (e.g. pass/ fail; %): %
Weighting % :50%
Passmark:50%
Word Length: n/a
Outline Details:3 hours exam. Students answer 1 compulsory essay, plus an additional 2 questions out of 5, related to the topics covered in the lectures and practicals.

Method of summative assessment:Poster
Outcomes assessed:1,2,
Grading Mode (e.g. pass/ fail; %): %
Weighting % :0
Passmark:0
Word Length:n/a
Outline Details: Conference-style poster presentation & short talk introducing the poster.