Universidade Nova de Lisboa

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Instituto Superior de Estatística e Gestão de Informação

Geographical Information Systems and Modelling

Code

42246

Academic unit

Instituto Superior de Estatística e Gestão de Informação

Credits

7,5

Teacher in charge

Pedro da Costa Brito Cabral

Weekly hours

0

Teaching language

Portuguese. In case there are any Erasmus students the class will be in English

Objectives

Numeric modelling of spatial processes, with emphasis on environmental modelling, is of major importance for many professionals in the field of geographic information systems. Models assist the comprehension of physical processes in the transport, accumulation and degradation of pollutants and materials, as well as the forecasting of future situations and scenarios. Although focussing on the environment, the methods and approaches presented have a wide application, e.g. in the areas of traffic, demography and public health. Developing an efficient model is not an easy task. Most processes show complex relationships within the time and space framework, usually requiring large amounts of data from different sources. Implementing a model, usually supported by a programming language, can become a difficult task for GIS professionals, which may limit the capacity to use it effectively. The implementation of a model implies the need to associate it with a GIS, for which several strategies can be applied. This unit has three main goals: (i) to provide a framework of useful concepts and approaches for the formulation of a spatial model; (ii) to present different operational methods to design and implement a spatial model; (iii) to discuss strategies to integrate a spatial model within a GIS environment.

Subject matter

The course in Modelling and GIS has five components: (i) Module 1: Modelling Fundamentals, which aims to introduce concepts of the mathematical modelling of spatial processes, with an emphasis on system dynamics. (ii) Module 2: Map Algebra, which is usually incorporated in any commercial GIS software. Conditional operators are presented as those most used in many GIS fields. (iii) Module 3: Statistical Modelling, which is supported by linear and non-linear regression models, derived from observational datasets. Geostatistics is presented as the statistical method to deal with the spatial nature of data and to characterize the spatial behaviour of variables and estimate unknown values. (iv) Module 4: Dynamic Modelling, which, by integrating the time component, is supported by mathematical functions inspired by physical processes occurring in nature, rather than empirical relationships from datasets. (v) Module 5: Model Implementation, which includes issues like programming and the advantages and limitations of different strategies to couple a model with commercial GIS packages.

Bibliography

GIS, Spatial Analysis, and Modeling, Eds. by Michael Batty, David Maguire, Michael Goodchild, Esri Press (2005)
Goovaerts P. (1997). Geostatistics for Natural Resources Evaluation. Oxford University Press, Inc, New York, USA
Isaaks E.H., Srivastava R.M. (1989). An Introduction to Applied Geostatistics. Oxford University Press, Inc, New York, USA
Soares A. (2000). Geoestatística para as Ciências da Terra e do Ambiente. Instituto Superior de Tecnico, IST Press. Lisboa, Portugal

Teaching method

The learning method has two main formats: (1) Teacher support, namely through online sessions to present and discuss the course content and continuous contact by email with each of the students. (2) Individual student work, supported by individual exercises, some compulsory, during the whole course period. Besides the continuous work based on the two formats, a GIS model project is also developed during the course, under the teacher's supervision. This process includes the design and formulation of a spatial model, data collection, implementation of the model, operation and validation. The project focuses on subjects related to the students' preferences, whether connected with a professional interest or not. This learning component is essential for individual in-depth development and the consolidation of practice in the formulation and implementation of a spatial model within a GIS environment. Individual initiative, creativity and self-confidence are values to be developed by this component.

Evaluation method

The evaluation method includes five components, with different weights for the final mark:
- A final project (55%)
- An examination (30%)
- 1 exercise (15%)
- Virtual Camous: bonus of 1.25% for each completed course (max.2)
- Progression exams (5% penalty for each exam that is not concluded)

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