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DEGREE REGULATIONS & PROGRAMMES OF STUDY 2018/2019

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DRPS : Course Catalogue : School of Geosciences : Postgraduate Courses (School of GeoSciences)

Postgraduate Course: Near-ground Earth Observations: new platforms and sensors (PGGE11215)

Course Outline
SchoolSchool of Geosciences CollegeCollege of Science and Engineering
Credit level (Normal year taken)SCQF Level 11 (Postgraduate) AvailabilityNot available to visiting students
SCQF Credits10 ECTS Credits5
SummaryThe course aims to provide an introduction to cutting edge natural and built environment monitoring and spatial sampling platforms (small fixed-and rotary-wing unmanned aerial vehicles (sUAVs) weighing « 20kg) and the latest instruments (RGB, multispectral and thermal cameras, fixed point and imaging spectrometers, and laser ranging systems). Advanced GIS and EO analytical methods for both commercial and scientific applications will be introduced. This course will build on the Fundamentals of Remote Sensing course and complement the Hyperspectral Remote Sensing MSc course currently taught in the MSc in EO and GM and MSc in GIS programmes.
Course description Lecture 1: Introduction to the course and to the practicals assessed assignment
Lecture 2: Control and navigation systems for near-ground EO platforms.
Lecture 3: Earth observation sampling strategies near-ground EO platforms
Practical: Set 1st Practical assignment and begin 1st practical


Lecture 4: Basics of photogrammetry;
Tutorial 1: Photogrammetry and camera calibration
1st Practical Assignment to be submitted


Lecture 5: Introduction to optical remote sensing (multispectral, hyperspectral and thermal) from near-ground EO platforms
Tutorial 2: Use of structure from motion software to build 3-D models
Practical: Structure from Motion practical
1st Practical returned with informative feedback


Lecture: 6. Introduction to ranging and Lidar from near-ground platforms
Tutorial 3: Use of LIDAR point cloud visualization software
Practical: Introduction to ranging and Lidar from near-ground platforms


Lecture: 7 Case study: a scientific problem that could only be addressed through the use of sUAVs
Practical: Continue to work on Assessed Assignment
Entry Requirements (not applicable to Visiting Students)
Pre-requisites Co-requisites
Prohibited Combinations Other requirements None
Course Delivery Information
Not being delivered
Learning Outcomes
On completion of this course, the student will be able to:
  1. understand the advantages and disadvantages of fixed- and rotary-wing platforms, the use of sUAV mounted inertial measurement units (IMU) and GPS logging systems, and the H&S and regulatory framework for operation
  2. engage with photogrammetric techniques e.g. sUAVs, camera inherent distortions and how to correct them, and to use topographical mapping 3-D image generation and point-tracking software; multispectral, Lidar, and thermal imaging from sUAVs methods of observation, and post processing and analysis of high spatial resolution imagery.
  3. locate, read and summarise relevant literature, from both traditional and electronic media, to extend your understanding of the topic. Develop reasoned arguments, firmly grounded in the available literature
  4. take responsibility for their own learning through reading, practical work and the preparation of assignments, and reflect upon your learning experience. Plan and write assignments, within the specified time limits
Reading List
Anderson, K. and Gaston, K. (2013) Lightweight unmanned aerial vehicles will revolutionize spatial ecology. Frontiers in Ecology and the Environment 11: 138-146.
Berni, J. Zarco-Tejada, P., Suárez, L. and Fereres, E. (2009) Thermal and Narrowband Multispectral Remote Sensing for Vegetation Monitoring From an Unmanned Aerial Vehicle. IEEE Transaction on Geosciences and Remote Sensing. 47, 3, 722 - 738.
Colomina, I and Molina, P. (2014) Unmanned aerial systems for photogrammetry and remote sensing: A review. ISPRS Journal of Photogrammetry and Remote Sensing 92, 79-97.
Hardin. P. and Jensen, R. (2011). Unmanned Aerial Vehicles in Environmental Remote Sensing: Challenges and Opportunities, GIScience & Remote Sensing, 48:1, 99-111.
Kuenzer, C. and Dech, S. (eds) (2012) Thermal Infrared remote sensing: sensors, methods and applications. Springer DOI 10.1007/978-94-007-6639-6. Particularly Chapters 1 and 4.
Milton, E.J., 1987. Principles of field spectroscopy. International Journal of Remote Sensing, 8, 1807-1827. Milton, E.J., Schaepman, M., Anderson, K., Kneubuhler, M. and Fox, N. (2009). Progress in field spectroscopy. Remote Sensing of Environment, 113, S92-S109.
Schaepman-Strub, G., Schaepman, M.E., Painter, T.H., Dangel, S. and Martonchik, J.V. (2006). Reflectance quantities in optical remote sensing-definitions and case studies. Remote Sensing of Environment, 103, 27-42.
Whitehead, K., and Hugenholtz, C.H. (2014). Remote sensing of the environment with small unmanned aircraft systems (UASs), part 1: a review of progress and challenges. J. Unmanned Veh. Syst. 2. 86-102. Whitehead, K., and Hugenholtz, C.H. (2014). Remote sensing of the environment with small unmanned aircraft systems (UASs), part 1: a review of progress and challenges. J. Unmanned Veh. Syst. 2. 69-85. Watts, A., Ambrosia, V, and Hinkley, E. (2012). Unmanned Aircraft Systems in Remote Sensing and Scientific Research: Classification and Considerations of Use. Remote Sensing 2012, 4, 1671-1692.
Additional Information
Graduate Attributes and Skills Students will acquire and develop the following transferable skills:
* Ability to consider and evaluate the advantages and disadvantages of sUAV platform types and the constraints these place on data acquisition, quality and fitness for purpose. Planning skills for data acquisition and sampling strategies and understand how these influence the utility of data acquired for different purposes.
* Understanding of high spatial resolution EO data and how it can be quality assessed and analysed.
* Ability to write a detailed technical report presenting a near-ground EO campaign including, platform selection and instrument, flight planning and sampling strategies, data analysis and findings.
KeywordsNot entered
Contacts
Course organiserDr Alasdair MacArthur
Tel: (0131 6)50 5926
Email: Alasdair.MacArthur@ed.ac.uk
Course secretaryMrs Karolina Galera
Tel: (0131 6)50 2572
Email: k.galera@ed.ac.uk
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