Jorge Gil

City Induction: A Model for Formulating, Generating, and Evaluating Urban Designs

Urban planning and design have a considerable impact on the economic performance of cities and on the quality of life of the population. Efficiency at this level is hampered by the lack of integrated instruments for formulating, generating, and evaluating urban plans. This chapter describes the theoretical foundations of a research project, called City Induction, aimed at the creation of a model for the development of such an instrument, departing from existing theories, which are integrated through a discursive grammar. The proposed model is composed of three sub-models: (1) a model for formulating urban programs from the analysis and interpretation of the context, based on Alexanders pattern language; (2) a model for generating urban plans that match the program, based on Stinys shape and description grammars; and (3) a model for evaluating urban plans, that can be used for analyzing, comparing and ranking alternative solutions, departing from Hilliers space syntax. A common urban space ontology guarantees the syntactic and semantic interoperability among the three sub-models. This ontology will be used to structure and codify information into a Geographic Information System (GIS), which will be the kernel for the computer implementation of the larger model. A CAD system is used to construct 3D models from contextual information stored in the GIS. In short, following Stiny and Marchs design machines concept, the goal is to create an urban design machine that is able to produce flexible urban plans at the site planning level.

Building a Multimodal Urban Network Model Using OpenStreetMap Data for the Analysis of Sustainable Accessibility

This chapter presents the process of building a multimodal urban network model using Volunteered Geographic Information (VGI) and in particular OpenStreetMap (OSM). The spatial data model design adopts a level of simplification that is adequate to OSM data availability and quality, and suitable to the measurement of the sustainable accessibility of urban neighborhoods and city-regions. The urban network model connects a private transport system (i.e. pedestrian, bicycle, car), a public transport system (i.e. rail, metro, tram and bus) and a land use system (i.e. building land use units). Various algorithmic procedures have been developed to produce the network model, supporting the reproducibility of the process and addressing the challenges of using OSM data for this purpose. While OSM demonstrates great potential for urban analysis, thanks to the detail of its attributes and its open and universal coverage, there is still some way to go to provide the data quality and consistency required for detailed operational urban models.

Introducing Spatial Variability to the Impact Significance Assessment

The concept of Circular Economy has gained momentum during the last decade. Yet unsustainable circular systems can also create unintended social, economic and environmental damage. Sustainability is highly dependent on a system’s geographical context, such as location of resources, cultural acceptance, economic, environmental and transport geography. While in some cases an impact of the proposed change may be considered equally significant under all circumstances (e.g. increase of carbon emissions as a main contributor to the global climate change), many impacts may change both their direction and the extent of significance dependent on their context (e.g. land consumption may be positively evaluated if applied to abandoned territories or negatively if a forest needs to be sacrificed). The geographical context, (i.e. its sensitivity, vulnerability or potential) is commonly assessed by Spatial Decision Support Systems. However, currently those systems typically do not perform an actual impact assessment as impact characteristics stay constant regardless of location. Likewise, relevant Impact Assessment methods, although gradually becoming more spatial, assume their context as invariable. As a consequence, impact significance so far is also a spatially unvarying concept. However, current technological developments allow to rapidly record, analyse and visualise spatial data. This article introduces the concept of spatially varying impact significance assessment, by reviewing its current definitions in literature, and analysing to what extent the concept is applied in existing assessment methods. It concludes with a formulation of spatially varying impact significance assessment for innovation in the field of impact assessment.