Satellite Earth Observation

Code:

EGEO2001

Acronym:

EGEO2001

Level:

200

Keywords
Classification	Keyword
OFICIAL	Surveying Engineering

Instance: 2023/2024 - 1S

Active?	No
Responsible unit:	Department of Geosciences, Environment and Spatial Plannings
Course/CS Responsible:	Bachelor in Chemistry

Cycles of Study/Courses

Acronym	No. of Students	Study Plan	Curricular Years	Credits UCN	Credits ECTS	Contact hours	Total Time
L:B	0	Official Study Plan	3	-	6	48	162
L:CC	0	study plan from 2021/22	2	-	6	48	162
			3
L:F	0	Official Study Plan	2	-	6	48	162
L:G	0	study plan from 2017/18	2	-	6	48	162
			3
L:M	0	Official Study Plan	2	-	6	48	162
			3
L:Q	0	study plan from 2016/17	3	-	6	48	162

Teaching language

Portuguese

Objectives

In this Unit it is planned to introduce the essentials of Earth Observation recurring to electromagnetic radiation interacting with the surface of the Earth. The electromagnetic spectrum should cover different wavebands, from visible light to microwaves, and the Unit is intended as a prelude to other unit denominated “Remote Sensing” in the third year. Focus will be given to remote sensing of water and ocean surfaces and the atmosphere, by using mainly passive sensors.

It is required that the students:

1) Understand the potential of Earth Observation through Earth orbiting satellites, as well as its limitations. Address and comprehend the orbit characteristics of the mostly common used remote sensing satellites.

2) Acquire fundamental knowledge about techniques and methods to observe the surface of the Earth by measuring electromagnetic radiation.

3) Learn basic principles of remote sensing digital image analysis.

4) Become aware of the vast satellite data sets that are available, as well as their processing levels and products available online. The students should be able to recognize which products and processing levels are most adequate to the solution of an Earth Observation problem.

5) Be capable to use and understand satellite data, and prepared to acquire further knowledge in more advanced units in the course, such as the Unit “Remote Sensing”.

Learning outcomes and competences

The students should have been exposed to methods of structured computer programming before, with approval in at least one U.C..

Working method

Presencial

Program

1) Satellite orbits for Earth Observation: Kepler and Newton laws; the two-body problem, effects of the Earth’s oblateness and other actions that constrain Low Earth Orbits; orbital elements and the state vector; coordinate transformation; transformation between geocentric equatorial and inertial frame of reference; Earth referencial.

2) The electromagnetic Radiation (EM) in Earth Observation by satellite: black body, atmosphere and surface. Diffusion and absorption in the atmosphere and the ocean.

3) Multispectral sensors in the visible wavebands and infrared: ocean color and Sea Surface Temperature (SST); vegetation indexes;

4) Basic notions of digital image processing: image enhancement, image histograms and geophysical parameters retrieved from satellite measurements; image filters.

Mandatory literature

Ian S. Robinson; Discovering the Ocean from Space (The unique applications of satellite oceanography), 2010. ISBN: 978-3-540-24430-1
Jensen John R.; Remote Sensing of the Environment: An Earth Resource Perspective., Upper Saddle River, NJ: Prentice-Hall, 2007. ISBN: 0-13-188950-8.

Complementary Bibliography

Martin Seelye; An introduction to ocean remote sensing. ISBN: 0-521-80280-6
Richards, J.A., Jia, X.; Remote Sensing Digital Image Analysis - An Introduction, Springer-Verlag, 2000
Gonzalez, R.C., Woods, R.E.; Digital Image Processing, Addison-Wesley, 2008

Teaching methods and learning activities

The theoretical Lectures are presented with aid to power point, and the most relevant aspects of the technique used in Earth Observation by satellite are explained in simple terms with examples. The concepts are introduced step by step with projects that are developed in the laboratory sessions (TPs). These projects address the practical application of digital image processing, which must include reading the original files available as products by Space Agencies (such as NASA, ESA, etc.). The students are motivated to write computer code and perform simple operations to observe satellite data in various ways and forms, in order to gain insight for image data interpretation. The evaluation of the knowledge gained by students is continuous and gradual, being made during the computer projects in every TP session. There is also a written test or/and exam to assess more general and theoretical concepts addressed in the theoretical Lectures. 

Software

MATLAB

keywords

Natural sciences > Environmental science > Global change > Climate change
Technological sciences > Technology > Marine technology > Remote sensing: satelliteborne sensors, airborne
Technological sciences > Technology > Remote sensing

Evaluation Type

Distributed evaluation without final exam

Assessment Components

designation	Weight (%)
Participação presencial	10,00
Trabalho laboratorial	40,00
Trabalho prático ou de projeto	50,00
Total:	100,00

Amount of time allocated to each course unit

designation	Time (hours)
Trabalho laboratorial	9,00
Total:	9,00

Eligibility for exams

The students must submit at least two computer code assignments to solve proposed projects in remote sensing applications and using digital image processing techniques. In addition there is a computational project at the end of the semester to evaluate theoretical concepts about remote sensing techniques. 
A course project will be proposed to be handed in by the end of the semester.

Calculation formula of final grade

Evaluation requires two components: 1) Weekly computer programming in MATLAB (1/2); 2) Computer project at the end of semester (1/2); 

NF=0.5*NP + 0.4*TL + 0.1*PP

NF = Nota Final de Frequência
NP = Nota de Projeto
TL = Média da avaliação dos Trabalhos Laboratoriais
PP = Componente presencial

Examinations or Special Assignments

NA

Internship work/project

NA

Special assessment (TE, DA, ...)

Computer assignments + computer course projet in MATLAB.

Classification improvement

By taking an exame.