Remote Sensing


On successful completion of the course students are expected to be able to (i.e. learning outcomes):

  1. Describe the principles of remote sensing
  2. Develop in an autonomous way a project to produce information based on satellite image classification
  3. Describe and evaluate the social economic benefits of remote sensing

General characterization





Responsible teacher

Mário Sílvio Rochinha de Andrade Caetano


Weekly - Available soon

Total - Available soon

Teaching language

Portuguese. If there are Erasmus students, classes will be taught in English


There are no specific course prerequisites.


Caetano, M., 2018. Teoria de Deteção Remota, [e-book]. Instituto Superior de Estatística e Gestão da Informação, Universidade Nova de Lisboa.; Caetano, M., 2012. Prática de Deteção Remota, [e-book]. Instituto Superior de Estatística e Gestão da Informação, Universidade Nova de Lisboa. ; Jensen, John R., 2000, Remote sensing of the environment: an earth resource perspective. New Jersey: Prentice Hall.; CCRS, Canadian Centre for Remote Sensing, 2007. Fundamentals of Remote Sensing , [Online]. Disponível em Access date: Feb 13, 2013; 0

Teaching method

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

Evaluation method

The professor in one of the first classes will discuss with the student the evaluation method to be applied in this course. As a starting point for the discussion it is proposed:

  • Test (individual) - 30%.
  • Project presentation and report  - 40%. The goal is the production of a land cover map using a satellite image within a image processing software. A project proposal has to be discussed with the professor.
  • Participation in classes ? 30%. Besides participation in classes thus evaluation component includes an individual presentation on socio-economic benefits of remote sensing within a specific theme selected by the student from a list provided by the Professor. 

In the first class the students agreed to implement the following weights: test (25%), project (45%), participation (10%) and presentation on socioeconomic benefits of remote sensing (20%). This last presentation should be done in group. .

In the second moment or any other moment of evaluation, the components of evaluation are exactly the same (except that participation in class is added to socio economic benefits presentation) and all projects have to be individual and have to be different from the ones presented during the semester (if existing).

Subject matter

  1. Introduction to remote sensing and to the course
  2. Remote sensing principles
  3. Remote sensing and the internet
  4. Characteristics of Earth observation satellites and sensors
  5. Exploratory analysis
  6. Introduction to Image information extraction
  7. Socioeconomic benefits of remote sensing
  8. Practical exercises on satellite image processing
  9. Real world problem solving based on satellite image processing