SATELLITE REMOTE SENSING - 2019/0
Module code: EEEM033
Module Overview
Expected prior learning: None specifically advised.
Module purpose: Earth and planetary observation with remote sensing data is playing a key role in the present understanding of natural phenomena, prevention of disasters, resources monitoring, comprehension of origins of life.
Through a series of lectures, seminars, open discussions and “thinking breaks” in class, the module aims to give an introduction to the scientific principles of remote sensing – both passive and active – as carried out by spacecraft. Remote sensing is discussed in terms of instrumentation, missions, products and applications.
IMPORTANT: The Second assessment pattern (100% Weighting for Written Exam) is only applicable to the MSc Short Course Students.
Module provider
Electrical and Electronic Engineering
Module Leader
GUIDA Raffaella (Elec Elec En)
Number of Credits: 15
ECTS Credits: 7.5
Framework: FHEQ Level 7
Module cap (Maximum number of students): 90
Overall student workload
Workshop Hours: 3
Independent Learning Hours: 114
Lecture Hours: 31
Laboratory Hours: 2
Module Availability
Semester 1
Prerequisites / Co-requisites
None.
Module content
Indicative content includes the following.
Section 1 - INTERACTIONS, SENSORS & PLATFORMS
Introduction to Remote Sensing: Radiometry, Electromagnetic Spectrum, Radiant and Spectral quantities, Blackbodies, Planck law, Stefan-Boltzmann law, Wien displacement law.
Energy Interactions: Physics of interactions, interactions in the atmosphere (influence factors, mechanisms, effects), interactions at the Earth’s surface (the energy balance, different kinds of reflectors). Mechanisms of reflection, transmission, absorbance, scattering (Rayleigh, Mie, Non-selective).
Data acquisition and interpretation: Data acquisition, data analysis, reference data, calibration.
Sensors and Platforms: Active and Passive systems, Spatial Resolution, Spectral Resolution, Swath Width, Coverage (Along-track scanner, Across-track scanner), Nadir, Signal to Noise Ratio (SNR), Payload design (Factors and Limitations), Orbits (Apogee and Perigee, Eccentricity, Orbital Period and Speed, Ascending and Descending Node, Inclination, Shape and Altitude, Geostationary Earth Orbits, Sun-Synchronous Orbits). Examples of some missions: LANDSAT program, SPOT program, NOAA program.
Section 2 - RADAR REMOTE SENSING
Radar Remote Sensing: Viewing geometry, Antenna Beam. Signal properties in Time Domain (Continuous wave CW and Pulsed wave PW) and Frequency domains, (Spectrum for CW and PW). Linear Frequency Modulation. Range and Doppler discrimination. Geometric distortions (Foreshortening, Layover, Shadow). Real Aperture Radar (RAR), Radar Equation (Bistatic and Monostatic), Swath width, Range resolution, Azimuth resolution, Signal Fading (speckle).
Synthetic Aperture Radar (SAR): Synthetic-Array approach, Doppler-Synthesis approach, lower and upper bounds for PRF. Configurations: stripmap, spotlight, hybrid, scansar. SAR Missions and Applications. SAR Interferometry. SAR Polarimetry. Scatterometer: basic principles. Altimeter: basic principles. Examples of SAR missions: NovaSAR-S mission (invited speaker from SSTL Ltd.)
Section 3 - DATA QUALITY & IMAGE PROCESSING
Image Processing: Image rectification and restoration (Geometric correction, Radiometric correction, Noise removal); Image enhancement (Contrast manipulation, Spatial feature manipulation, Multi-image manipulation). Image classification (supervised and unsupervised), classifiers. Data merging: principles.
Assessment pattern
Assessment type | Unit of assessment | Weighting |
---|---|---|
Coursework | ASSIGNMENT | 20 |
Examination | EXAMINATION - 2HRS | 80 |
Alternative Assessment
Students failing a unit of assessment resit the assessment in its original format.
Assessment Strategy
The assessment strategy for this module is designed to provide students with the opportunity to demonstrate the following:
- a basic knowledge of remote sensing principles and instrumentation and a good understanding of the interactions of radiation with the earth’s surface and atmosphere, assessed through coursework and examination;
- a good understanding of Synthetic Aperture Radar principles and applications, assessed through coursework and examination;
- a good capability of analysing end-users requirements for specific remote sensing application and converting them in technical specifications for the design of remote sensing instrumentation, assessed through coursework;
- a good knowledge of basic image processing and interpretation skills of remote sensing products, assessed through examination.
Thus, the summative assessment for this module consists of the following.
· 2 hours closed book examination.
- Satellite Remote Sensing Application: an assignment involving the image processing and analysis for a given application of Earth Observation, the application of theoretical concepts to verify satellite image parameters and the suggestion of a technical solution to address specific end-users requirements. The coursework is set in week 2 and deadline falls in week 7.
These deadlines are indicative. For confirmation of exact date and time, please check the Departmental assessment calendar issued to you.
Formative assessment and feedback
For the module, students will receive formative assessment/feedback in the following ways.
During lectures, by question and answer sessions and discussions
During tutorial classes
By means of unassessed tutorial problem sheets (with answers/model solutions)
During meetings with the module coordinator
By means of unassessed review of the coursework at intermediate steps.
Via the marking of coursework
Module aims
- introduce the student to remote sensing principles, the physical interactions of radiation with atmosphere and Earth's features;
- introduce the student to the processing of remotely sensed data and the development of applications for Earth's resources management and monitoring.
Learning outcomes
Attributes Developed | ||
1 | Have a good understanding of the interactions of radiation with the earth's surface and atmosphere and be able to use this knowledge to approach the design of new sensors and address specific problems | KC |
2 | Have a good knowledge of remote sensing instrumentation, and radar in particular | KC |
3 | Have a good understanding and basic interpretation skills of remote sensing products | KC |
4 | Be capable of analysing the requirements for some relevant application in remote sensing | CP |
Attributes Developed
C - Cognitive/analytical
K - Subject knowledge
T - Transferable skills
P - Professional/Practical skills
Methods of Teaching / Learning
The learning and teaching strategy is designed to achieve the following aims:
- communicate knowledge and information about satellite sensors and applications to a wide audience through lectures;
- engage students in the analysis of end-users applications requirements and their conversion in technical specifications for satellite sensors design through exercises in class;
- verify students. Understanding, and give feedback through open discussions in class and tutorials.
Learning and teaching methods include the following:
2.5 hour lectures x 10 week
1 hour tutorial x 1 week
2 hour lab x 1 week
0.5 hour class discussion x 10 week
3 hour workshop x 1 week
114 hour independent study
Indicated Lecture Hours (which may also include seminars, tutorials, workshops and other contact time) are approximate and may include in-class tests where one or more of these are an assessment on the module. In-class tests are scheduled/organised separately to taught content and will be published on to student personal timetables, where they apply to taken modules, as soon as they are finalised by central administration. This will usually be after the initial publication of the teaching timetable for the relevant semester.
Reading list
https://readinglists.surrey.ac.uk
Upon accessing the reading list, please search for the module using the module code: EEEM033
Programmes this module appears in
Programme | Semester | Classification | Qualifying conditions |
---|---|---|---|
Space Engineering MSc | 1 | Optional | A weighted aggregate mark of 50% is required to pass the module |
Electronic Engineering with Space Systems MEng | 1 | Optional | A weighted aggregate mark of 50% is required to pass the module |
Computer Vision, Robotics and Machine Learning MSc | 1 | Optional | A weighted aggregate mark of 50% is required to pass the module |
Electronic Engineering with Computer Systems MEng | 1 | Optional | A weighted aggregate mark of 50% is required to pass the module |
Electronic Engineering MEng | 1 | Optional | A weighted aggregate mark of 50% is required to pass the module |
Electronic Engineering MSc | 1 | Optional | A weighted aggregate mark of 50% is required to pass the module |
Electronic Engineering (EuroMasters) MSc | 1 | Optional | A weighted aggregate mark of 50% is required to pass the module |
Electronic Engineering with Communications MEng | 1 | Optional | A weighted aggregate mark of 50% is required to pass the module |
Electronic Engineering with Audio-Visual Systems MEng | 1 | Optional | A weighted aggregate mark of 50% is required to pass the module |
Please note that the information detailed within this record is accurate at the time of publishing and may be subject to change. This record contains information for the most up to date version of the programme / module for the 2019/0 academic year.