SATELLITE REMOTE SENSING - 2018/9

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 R Dr (Elec Elec En)

Number of Credits: 15

ECTS Credits: 7.5

Framework: FHEQ Level 7

JACs code: H643

Module cap (Maximum number of students): N/A

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 30
Examination EXAMINATION - 2HRS 70

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 Report: an assignment involving a literature survey on a given application for Earth Observation, the identification of current technological constraints and the suggestion of a technical solution to address present drawbacks. 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

Overall student workload

Lecture Hours: 31

Laboratory Hours: 2

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


3 hour tutorials x 1 week


0.5 hour class discussion x 10 week







 

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

Reading list for SATELLITE REMOTE SENSING : http://aspire.surrey.ac.uk/modules/eeem033

Programmes this module appears in

Programme Semester Classification Qualifying conditions
Computer Vision, Robotics and Machine Learning (EuroMasters) MSc 1 Optional A weighted aggregate mark of 50% is required to pass the module
Computer Vision, Robotics and Machine Learning (EuroMasters) MSc 1 Optional Each unit of assessment must be passed at 50% to pass the module
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
Communication 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 with Computer Systems MEng 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 MSc 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
Space 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 2018/9 academic year.