Remote Sensing

Code:

EGEO3003

Acronym:

EGEO3003

Level:

300

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
			3
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

Suitable for English-speaking students

Objectives

This curricular unit aims to complement the knowledge acquired in the unit ”Observação da Terra por satellite”, focusing on Remote Sensing (RS) using microwave sensors (in particular active sensors) and digital image processing for a representative set of RS applications.

Learning outcomes and competences

It is expected that tudents:

1) Are aware of the enormous potential of remote sensing techniques in the observation of the earth's surface.

2) Have consolidated their knowledge about the techniques used in Remote Sensing in the various bands of the electromagnetic spectrum.

3) Know the vast variety of available satellite data and are able to identify the most appropriate to solve a given problem.

4) Are able to correctly identify and use the appropriate tools for processing and analyzing data collected by satellites, aerial or unmanned autonomous vehicles(image and non-image)..

5) Are able to use satellite data to solve problems in various areas of geosciences and Engineering

Working method

Presencial

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

Students should have attended the unit  Satellite Earth Observation (EGEO2004). A student for whom this is the first Remote Sensing course, will be advised to also attend some of the introductory lectures of a basic Remote Sensing course

Program

1. Digital Image Processing: digital image concept, histograms, filters geometric corrections, calibration, and classification.

2. Multispectral sensors in the Visible and infrared regions of the EM spectrum. High spatial resolution sensors and hyperspectral sensors.

3. Microwave Remote sensing: sensors and measurement techniques.

4. Active sensors: radar altimetry, SAR (land and ocean applications).

5. Remote Sensing Applications

6. Remote Sensing data processing software: SNAP.

Mandatory literature

Jensen John R.; Remote sensing of the environment. ISBN: 0-13-489733-1
Lillesand Thomas M.; Remote sensing and image interpretation. ISBN: 978-0-470-05245-7
Richards, J.A., Jia, X; Remote Sensing Digital Image Analysis - An Introduction, Springer-Verlag, Fifth Edition, 2013 (Available online via Springer)

Complementary Bibliography

Gonzalez, R.C., Woods, R.E.; Digital Image Processing, Addison-Wesley, 2008
Lee-Lueng, ed. lit. Fu; Satellite altimetry and earth sciences. ISBN: 0-12-269545-3
Ian S. Robinson; Measuring the oceans from space. ISBN: 3-540-42647-7

Teaching methods and learning activities

Theoretical classes are mainly based on Power Point presentations.

In the Practical classes, a set of exercises is proposed, aiming to apply and consolidate the knowledge acquired in the theoretical classes. The functionalities of one or two Remote Sensing  (RS) processing tools are presented. A set of practical exercises are proposed, for solution in the computer, using specific RS processing software.

 

Software

SNAP
Surfer
Matlab

Evaluation Type

Evaluation with final exam

Assessment Components

designation	Weight (%)
Exame	100,00
Total:	100,00

Amount of time allocated to each course unit

designation	Time (hours)
Estudo autónomo	64,00
Frequência das aulas	56,00
Trabalho laboratorial	42,00
Total:	162,00

Eligibility for exams

Attendance of theoretical classes is not compulsory. The students might fail if they miss a number of practical classes that exceeds the number predicted in the University rules

Calculation formula of final grade

Type of evaluation: distributed with final exam.
The exam has two components: Theoretical (T) and Practical (P), the second one executed in the computer.

Evaluation formula: CF=T *0.5 + P*0.5.

Examinations or Special Assignments

NA

Internship work/project

NA

Special assessment (TE, DA, ...)

The assessment method is the same as for regular

Classification improvement

The students can use the methods predicted in the general University rules for mark improvement.