Geographic Information Systems


a) Dominate the specific vocabulary of Geographic Information Science and Systems
b) Know the main components of Geographic Information Systems (GIS)
c) Know the application domain of GIS
d) Understand the basics of Geographic Information
e) Identify application opportunities for GIS
f) Create data structures for analysis of spatial problems
g) Develop spatial analysis methodologies
h) Apply spatial analysis processes using technological platforms

General characterization





Responsible teacher

Rui Pedro de Sousa Pereira Monteiro Julião


Weekly - 4

Total - 168

Teaching language



Available soon


Burrough, P. & Mcdonnell, R. (1998). Principles of Geographical Information Systems (2nd ed.). Oxford, UK: Oxford Univ Press.

Julião, R.P. (2001). Tecnologias de Informação Geográfica e Ciência Regional: Contributos Metodológicos para a Definição de Modelos de Apoio à Decisão em Desenvolvimento Regional. Lisboa: UNL.

Longley, P., Goodchild, M., Maguire, D. & Rhind, D. (2005). Geographical Information Systems and Science (2nd ed.). Nova Iorque, NY: John Wiley & Sons.

Matos, J.L. (2008). Fundamentos de Informação Geográfica (5ª ed.). Lisboa: LIDEL.

Sutton, T., Dassau, O. & Sutton, M. (2009). A Gentle Introduction to GIS. Eastern Cape, ZA: Department of Land Affairs.

Teaching method

Teaching is done through expositive and participative classes, including exploitation of texts, presentations, handling technological platforms and group work.

Evaluation method

Evaluation method - Conducting a presentation in class (just for knowledge verification)(0%), Participation in a work group with report(35%), Reading a set of selected texts, whose contents, together with the material of classes (theoretical and practical), shall be assessed through a written test(65%)

Subject matter

1) Introduction
2) Fundamentals of Geographic Information Science and Systems
2.1. Background and Definitions
2.2. Applications and Users
2.3. Data Models
2.4. Implementation
3) Geographic Information Systems Development
3.1. Operational Models
3.2. Data Structuring and Acquisition
3.3. Data Validation and Integration
3.4. Data Exploration
3.5. Data Dissemination
4) Project