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2020/21 Taught Postgraduate Module Catalogue

JUSO5261M Remote Sensing for Earth Observation (WUN)

15 creditsClass Size: 50

Module manager: Booker Ogutu

Taught: 1 Oct to 31 Jan, 1 Oct to 31 Jan (Adv pre 2223) View Timetable

Year running 2020/21

This module is not approved as an Elective

Module summary

Given the growing importance of remotely sensed imagery to GIS, it is important for someone to have at least some basic understanding of the field of remote sensing. This module will provide an introduction to the principles behind the acquisition and utilization of remotely sensed airborne and spaceborne images for the study of natural and human landscapes. Further, image processing techniques to analyse and interpret information from remotely sensed data for understanding environmental will be emphasized.


On completion of the module students should be able to:
1. introduce RS as an important enabling tool for earth surface research problems and applications;
2. examine the basics of RS and the main satellite/sensor systems that are in use;
3. provide practical experiences of image processing (PC-based) and interpretation.

Learning outcomes
1. Define and explain the key concepts and terminology used in remote sensing.
2. List and discuss the advantageous features of remote sensing for the study of the Earth's environment.
3. Describe the electromagnetic spectrum and appreciate some of the fundamental physical properties of radiation and their suitability for use in remote sensing.
4. Summarise and discuss the interactions of radiation in visible to microwave wavelengths with the terrestrial environment, and with vegetation, soils and water in particular.
5. Describe the properties of some major remote sensing systems.
6. Explain how thematic maps may be derived from remotely sensed data.
7. Appreciate some of the ways remote sensing may be used in the study of the Earth's environment.

Skills outcomes
Students will be able to:
1. Critically analyse literature on remote sensing
2. Analyse and interpret remotely sensed data
3. Conduct computer based analyses of remotely sensed data in an appropriate and safe manner
4. Use appropriate techniques to produce clear products such as thematic maps
5. Pursue knowledge in an ordered way
6. Produce structured and succinct written reports on complex topics
7. Use computational skills in the analysis of spatial data


Introduction to Remote Sensing
Electromagnetic Radiation and the Electromagnetic Spectrum
Energy Interactions with the Atmosphere and the Earth's surface
EMR interactions with the Earth's surface
Sensor Technology
Major Remote Sensing systems
Introduction to Image Processing Part I
Introduction to Image Processing Part II
Estimating Earth Surface Properties Using
Image classification Unsupervised
Image classification-Supervised
Landcover mapping and accuracy
Application of remote sensing in environmental management
Application of remote sensing in natural disaster management
Application of remote sensing in climate change studies
Practical exercise
Image enhancement Part I (Image display, Contrast stretching)
Image enhancement Part II (filtering techniques)
Vegetation index
Image Classification Unsupervised
Image Classification Supervised
Change detection studies

Teaching methods

Delivery typeNumberLength hoursStudent hours
Email/Phone Tutorial301.0030.00
Private study hours120.00
Total Contact hours30.00
Total hours (100hr per 10 credits)150.00

Private study

To read papers: 80 hours
To complete the assessments: 40 hours

Opportunities for Formative Feedback

Through email communication and online discussion room.

Methods of assessment

Assessment typeNotes% of formal assessment
PracticalPractical reports of 1,500 words each30.00
PracticalPractical reports of 1,500 words each30.00
Report1 project report of 1,500 words40.00
Total percentage (Assessment Coursework)100.00

Normally resits will be assessed by the same methodology as the first attempt, unless otherwise stated

Reading list

There is no reading list for this module

Last updated: 29/04/2022 15:32:21


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