Geographical Information Technologies I

Name: Geographical Information Technologies I
Code: ERU2592L
Duration: 15 weeks/156 hours
Scientific Area: Biosystems Engineering

Teaching languages: Portuguese
Languages of tutoring support: Portuguese
Regime de Frequência: Presencial


Geographic information technologies are currently highly useful for management, monitoring, decision making, mapping and planning at the local, regional and global levels.

Sustainable Development Goals

Learning Goals

Acquisition of fundamental concepts in GPS, Geographical Information Systems and Remote Sensing. Understand the multiple applications attended by this technology and be familiar with the capacity to integrate space data in different formats. Develop practical competences in handling this type of equipments, in the digital classification of satellite images and it's connection with the geographical data bases. Develop the capacity to structure spatial data bases as models of the reality. Learn the spatial analysis functions that a SIG provides, in the perspective to support decision making. Create competences in the use of structured query languages and algebra of maps. Understand the radiometric natural surfaces behaviour, namely through the respective spectral signatures. To understand the importance of new technologies in the development of modern societies.


1.1) satellites triangulation ; 1.2) measurement of distances; 1.3) to assure exact time; 1.4) satellites position; 1.5) errors correction; 1.6) why do we need differential GNSS (DGNSS)?; 1.7) how does the differential GNSS works?; 1.8) where can we get differential correction?; 1.9) Other forms of working with DGPS; 1.10) GPS positioning types; 1.11) GPS applications; 1.12) practical works with GNSS (NAV, DGNSS and DGNSS RTK).
2.1) structuring spatial data bases, as reality models; 2.2) data models (A-raster and B-vectorial); 2.3) relevant aspects in the different data models; 2.4) Structured query languages; 2.5) Maps algebra.
3) remember the fundamental laws of the electromagnetic radiation. Vegetation Indexes (NDVI); 3.7) digital
classification images (principal components analysis, supervised and unsupervised classification)

Teaching Methods

Remote work: Introduction to the fundamental theoretical concepts through made available resources, in Moodle (lessons, several texts, PowerPoint presentations, Internet pages, etc). Students work will be guided to reach specific objectives. They will also develop collaborative work in Moodle.
Work in classroom: The practical competences will be acquired in the classroom. Will be given to the students individual practical work at home, after developing certain practical competences in the classroom. A work group will integrate the acquired knowledge given in the curricular unit.
Evaluation: 40% for the theoretical component and 60% the practical component