Ocean Colour and Sea Surface Temperature

Code:

EGEO4025

Acronym:

EGEO4025

Keywords
Classification	Keyword
OFICIAL	Surveying Engineering

Instance: 2020/2021 - 2S

Active?	No
Responsible unit:	Department of Geosciences, Environment and Spatial Plannings
Course/CS Responsible:	Master in Remote Sensing

Cycles of Study/Courses

Acronym	No. of Students	Study Plan	Curricular Years	Credits UCN	Credits ECTS	Contact hours	Total Time
M:DR	0	The study plan from 2018	1	-	3	21	81

Teaching language

Suitable for English-speaking students

Objectives

This course aims to provide an introduction at Master’s level to the ways in which Remote Sensing (RS) is used in Natural Science to understand, detect and quantify environmental variables inferred from the colour and surface temperature of the Ocean.

It is intended that students acquire knowledge of:

- the properties of the Ocean that can be measured from Remote Sensing (DR) sensors;

- the main methodologies used to quantify the environmental variables inferred from these properties;

- DR sensors that, operating in the Visible/Infrared (Vis/IR), allow the quantification of the environmental variables inferred from the above-mentioned properties;

- basic image processing techniques for manipulation and evaluation of Ocean Color (OC) and Sea Surface Temperature (SST) data, preferably using Open Source Software;

- OC/SST products publicly available on the internet;

- data analysis synergy for scientific and educational contexts.

Learning outcomes and competences

The learning outcomes of this unit are:

- Understand the advantages and specificities of using Visible/Infrared (Vis/IR) sensors on board RS satellites to enhance the knowledge of the Ocean;

- Acquire knowledge on the Ocean properties that can be measured from Vis/IR RS and understand the main methods and statistical techniques used to quantify environmental variables inferred from these properties;

- Understand basic image processing techniques to manipulate/evaluate Ocean Colour (OC) and sea surface temperature (SST) data using preferably Free/Open Source Software;

- Acquire basic skills to handle Vis/IR RS images in scientific and educational contexts and acquire information on OC/SST products freely available on the internet.

Working method

Presencial

Pre-requirements (prior knowledge) and co-requirements (common knowledge)

Prerequisites:
Fundaments of Remote Sensing
Digital Image Processing

Program

1. Visible Remote Sensing

1.1 Ocean Colour Remote Sensing: introduction; optical properties and classification of natural waters; reflection and refraction at the surface; scattering and absorption of light underwater; optical constituents of the ocean and their estimation; satellite sensors for ocean colour and their applications in natural science; calibration and validation of ocean colour; ocean colour web services and products.

1.2 Ocean Colour Remote Sensing – Applications: practical sessions.

1. Infrared Remote Sensing

2.1 Remote Sensing of sea surface temperature: introduction, thermal emission and atmospheric absorption; sea surface temperature retrieval; thermal skin layer – skin and bulk SST; surface films and their effect; infrared sensors for ocean sea surface temperature; calibration and validation of sea surface temperature; sea surface temperature web services and products.

2.2 Sea Surface Temperature – Applications: practical sessions.

Mandatory literature

Ian S. Robinson; Measuring the oceans from space. ISBN: 3-540-42647-7
I. S. Robinson; Satellite oceanography. ISBN: 0-471-95424-1
Mobley, C., Boss, E., Roesler, C.; Ocean Optics , http://www.oceanopticsbook.info/view/introduction/overview, 2017. ISBN: Web Book
Pozdnyakov, D.V. and H. Grassl; Colour of Inland and Coastal Waters: a methodology for its interpretation, Chichester: Springer-Praxis. ISBN: 978-3-540-00200-0
International Ocean-Colour Coordinating Group; IOCCG Report Number 7: Why Ocean Colour? The Societal Benefits of Ocean-Colour Technology, Platt, T., N. Hoepffner, V. Stuart, and C. Brown (eds), 2008 (Available online: http://ioccg.org/what-we-do/ioccg-publications/ioccg-reports/)

Complementary Bibliography

Igor V. Cherny; Passive microwave remote sensing of oceans. ISBN: 0-471-97170-7
Motoyoshi, ed. lit. Ikeda; Oceanographic applications of remote sensing. ISBN: 0-8493-4525-1
Richards J.A. Jia X.; Remote Sensing Digital Image Analysis

Teaching methods and learning activities

Theoretical classes are mainly based on Power Point presentations that are available on the site of the course. In the practical sessions, exercises covering all sections of the courseare solved through computational projects using Remote Sensing software.

Overall, the adopted teaching methods are consistent with CU objectives. The most relevant literature is used and with the teacher’s support, students can develop new and specific knowledge in Remote Sensing and its integration in other subjects.

Software

QGIS
SNAP

Evaluation Type

Distributed evaluation with final exam

Assessment Components

designation	Weight (%)
Exame	70,00
Trabalho escrito	30,00
Total:	100,00

Amount of time allocated to each course unit

designation	Time (hours)
Estudo autónomo	21,00
Frequência das aulas	21,00
Trabalho de investigação	14,00
Trabalho escrito	25,00
Total:	81,00

Eligibility for exams

The attendance in the tutorial classes is compulsory according to the University of Porto rules.

Calculation formula of final grade

Assessment is based on the final written exam (FE) and on the discussion of the report of an individual (CP) computational project developed by the student. Final grade (FG) is:

FG= 0.7xFE+0.3xCP

Special assessment (TE, DA, ...)

The University of Porto rules are obeyed.

Classification improvement

The University of Porto rules are obeyed.