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The University of Southampton
Courses

SOES6017 Introductory Remote Sensing of the Ocean

Module Overview

This course aims to provide a broad introduction at Masters level to the ways in which remote sensing of the oceans, mainly from satellites but also from autonomous underwater vehicles, is applied in oceanography. Whether you have a special interest in this particular aspect of oceanography, or you are simply taking the course to round out your knowledge, you should be able to learn from this course in several different ways, as summarised in the learning outcomes.

Aims and Objectives

Learning Outcomes

Learning Outcomes

Having successfully completed this module you will be able to:

  • Acquire a new Perspective: grasp what is special about the view of the ocean provided from remote sensing to enhance your knowledge of the ocean.
  • Methodology: understand the main methods of ocean remote sensing and the ocean properties that can be measured.
  • Importance in Ocean Science: discover some of the specific ways in which remote sensing data make unique contributions to ocean science.
  • Wider Applications: find out how ocean remote sensing data are being applied for the benefit of human activity in the ocean.

Syllabus

1. Basic principles: Introductory lectures on remote sensing methods, coupled with a practical introduction to image processing with self paced introductory tutorials to become familiar with using Matlab for satellite data. 2. Sea surface temperature: Method of sea surface temperature remote sensing, studies of ocean eddies and fronts, monitoring of global temperature patterns. 3. Ocean colour: Measuring chlorophyll and suspended sediment concentration from water colour as detected from satellites, studies of phytoplankton blooms. 4. Imaging Radar: How satellite radars "see" the ocean to study ocean topography, winds, rain and salinity globally. 5. Sea Ice: studying Arctic and Antarctic ice by synergy between different types of data. 6. Autonomous underwater vehicles: unique view of ocean physics and biogeochemistry, new frontier in ocean remote sensing 7. Lecture material is reinforced by online videos which go deeper into particular aspects of remote sensing and computer practicals using remote sensing data. Students will learn the use of Matlab for analysing satellite images.

Learning and Teaching

Teaching and learning methods

Formal Lectures: will provide an introduction to the theory underlying remote sensing methods used in oceanography. Each lecture systematically covers the main concepts and topics by the use of PowerPoint presentations. The lecturer's own experience in these fields is incorporated. Appropriate references to parts of course textbooks and introductory journal references are provided at each lecture. The lectures will focus on the practical applications of satellite data to ocean science topics. Lectures will include discussion points and peer instruction. Practicals: Interactive computer-based practical work with image data, including tutorials and instruction in Matlab. Online videos: provide more in-depth technical information on satellite data, which students can use to deepen their understanding of remote sensing topics specific to their assessments. A wide range of support can be provided for those students who have further or specific learning and teaching needs.

TypeHours
Tutorial63
Independent Study87
Total study time150

Assessment

Summative

MethodPercentage contribution
Assignment 30%
Essay 70%

Costs

Costs associated with this module

Students are responsible for meeting the cost of essential textbooks, and of producing such essays, assignments, laboratory reports and dissertations as are required to fulfil the academic requirements for each programme of study.

In addition to this, students registered for this module typically also have to pay for:

Other

There are no additional costs associated with this module.

Please also ensure you read the section on additional costs in the University’s Fees, Charges and Expenses Regulations in the University Calendar available at www.calendar.soton.ac.uk.

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