In this paper we introduce a method for potential use in strategic environmental assessment (SEA) which integrates knowledge and tools of Collective Intelligence, Complexity Theory and Geoprospective, via the implementation of a technological Group-Spatial Decision Support System (GSDSS), usable for scenario building for infrastructure project planning. It operates on the basis of interdisciplinary consensus of a multidisciplinary group of experts, without strict dependency on a spatial analysis based on a single cognitive stance, using existing historical data. The method is used in a study case on planning of onshore wind energy in Mexico, which has been developed through a collaborative Geoweb application, and is functioning in a distributed and asynchronous real-time way, so-called Geospatial System of Collective Intelligence (SIGIC). The significance of this research lies in demonstrating the feasibility of a collective intelligence analysis aimed at proposing spatial locations in an energy transition context within an SEA framework.

Introducing a group spatial decision support system for use in strategic environmental assessment of onshore wind farm development in Mexico

Di Zio, Simone
2019

Abstract

In this paper we introduce a method for potential use in strategic environmental assessment (SEA) which integrates knowledge and tools of Collective Intelligence, Complexity Theory and Geoprospective, via the implementation of a technological Group-Spatial Decision Support System (GSDSS), usable for scenario building for infrastructure project planning. It operates on the basis of interdisciplinary consensus of a multidisciplinary group of experts, without strict dependency on a spatial analysis based on a single cognitive stance, using existing historical data. The method is used in a study case on planning of onshore wind energy in Mexico, which has been developed through a collaborative Geoweb application, and is functioning in a distributed and asynchronous real-time way, so-called Geospatial System of Collective Intelligence (SIGIC). The significance of this research lies in demonstrating the feasibility of a collective intelligence analysis aimed at proposing spatial locations in an energy transition context within an SEA framework.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11564/700041
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