The curricular unit targets the fundamentals of remote sensing, the main Earth Observation satellite and satellite image processing methods. The final goal is that the student after completion of the unit will be able, in an autonomous way, to design and implement a project to produce information (e.g. thematic cartography) based on satellite images and classification algorithms.
Mário Sílvio Rochinha de Andrade Caetano
Weekly - Available soon
Total - Available soon
Portuguese. If there are Erasmus students, classes will be taught in English
There are no specific course prerequisites.
Caetano, M., and H. Costa, 2019. Remote Sensing Practicals, [e-book].
Jensen, J.R., 2016. Introductory Digital Image Processing: a Remote Sensing Perspective, 4a Ed. Glenview : Pearson https://ebookcentral.proquest.com/lib/novaims/detail.action?docID=5831484
CCRS, Canadian Centre for Remote Sensing, 2007. Fundamentals of Remote Sensing , [Online].
Jensen, J.R., 2013. Remote sensing of the environment: an earth resource perspective, 2a Edic¿a¿o. NewJersey: Prentice Hall.
Remote sensing of land use and land cover: principles and applications / ed. by Chandra P. Giri . - Boca Raton : CRC, 2012 . - 425 p . - (Series in Remote Sensing Applications)
9781420070743. ACESSO NOVA: https://doi.org/10.1201/b11964
The course has lectures and laboratory sessions. In the lectures, the instructor uses slides to illustrate the theory. The laboratory sessions consists on the use of a image processing software for deriving a thematic map based on spectral and/or temporal pattern analysis. The course also includes seminars to discuss the socioeconomic benefits of remote sensing.
The professor promotes an active and collaborative learning based on real world problem solving
- Test (individual) - 30%;
- Practical Project - 45%. Group project to solve a real problem by using satellite images and an image software chosen by the group. The problem has to be defined by the group. (Presentation and Report);
- Essay - 25% - The group can choose between two types of essay: (1) socio-economic benefits of remote sensing within a specific theme selected by the students from a list provided by the Professor, or (2) research and development trends in remote sensing (Presentation and Report)
Both Practical project and essay should be done in a collaborative way by students organised in groups. The composition of the groups for the practical project and essay should be the same. No individual projects or essays are accepted.
- Test: November 25
- Essay: December 14 (till noon, i.e. 12 hours in 24-hour clock)
- Practical Project: December 16 (till noon, i.e. 12 hours in 24-hour clock)
- Minimum grade in each component - 8
- Projects not delivered within deadline are not considered
- Projects not delivered through platform TurnItin are not considered
The Curricular Unit has the following Learning Units (LU):
- LU 1 Introduction to remote sensing and to the course
- LU 2 Remote sensing principles
- LU 3 Characteristics of Earth observation satellites and sensors
- LU 4 Exploratory analysis
- LU 5 Image pre-processing
- LU 6 Band transformations
- LU 7 Image information extraction (image classification)
- LU 8 Multi-temporal image analysis
- LU 9 Error analysis in thematic maps
- LU 10 Socioeconomic benefits of remote sensing
- LU 11 Practical exercises on satellite image processing
- LU 12 Real world problem solving based on satellite image processing
Programs where the course is taught:
- Specialization in Knowledge Management and Business Intelligence
- Specialization in Information Systems and Technologies Management
- Specialization in Marketing Intelligence
- Specialization in Knowledge Management and Business Intelligence – Working Hours Format
- Specialization in Information Systems and Technologies Management - Working Hours Format
- Specialization in Marketing Intelligence - Working Hours Format
- Master degree program in Geospatial Technologies
- Master of Geographic Information Systems and Science
- PostGraduate in Smart Cities
- PostGraduate in Geographic Information Systems and Science