GIS-ANN scenario building model of alternative futures. A contribution for a spatial decision support system

Wed 10 October 2018

Mill Lane Lecture Rooms

Cities in general and more particular urban coastal areas are nowadays, a conflict prone-habitat of competing visions and contrasting interests. Local governments and citizens of such areas are permanently tempted to break under the pressure of different stakeholders. More and better information are the key to a sustainable and successful decision making. Geospatial technologies, geocomputation and geographical modelling advances and widespread brought power for those who must govern, decide and live on those areas. The empowerment of people passes by given them access to information and knowledge. The knowledge of knowing what’s going on and more important a glimpse of how future (a part of it, at least) could be based on competing visions, so people can compare them and be in advantage to negotiate trade-offs. The underlying rationale of this communication is to show and demonstrate, based on real case study of a Portuguese fragile ecosystem coastal urban area (Trafaria at Lisbon metropolitan area), the potentialities of Geographic Information Systems (GIS) and Artificial Neural Networks (ANN) as powerful support tools for decision-makers and citizens has the provide answers for assuring a balanced management of the coastal area on the one hand and to solve existent land cover conflicts and avoid future discord, on the other. Our GIS-ANN model it allows people to identify the driving forces of changes and their relative importance as well it can spatialize/mapping alternative futures of a multitude of scenarios so we can understand how they are distributed, clustered or spread over territory.



Paulo Morgado is a Geographer and GIScientist. He holds a PhD in Geocomputation applied to Regional and Urban Planning. He is currently an Assistant Professor at the University of Lisbon where he lectures and coordinates the subjects of: Geographical Modeling, GIS Project, Geographic Modeling and Complex Urban Systems. Paulo is also coordinator of the GeoModLab (Laboratory of Remote Sensing, analysis and geographical modeling), a member of the Scientific Committee of Institute of Geography and Spatial Planning of the University of Lisbon, and reviewer for several international journals. He’s also coordinated the Geographical modelling tasks of several scientific projects, both national and international, and he’s provided advisory services to public and private companies, on spatial data analysis and data management. His research areas are centered to Theoretical and Quantitative Geography, e.g GISc, Geocomputation, Complex Networks and Graph Theory, Artificial Neural Networks, Cellular Automata and Multi-Agent Systems. More recently, he’s focused on Smart Cities, Smart Grown and Sustainable Cities. You can follow Paulo’s work here: Http://orcid.org/0000-0002-3220-4943.

Cost: free