Nuno Montenegro

A Land Use Planning Ontology: LBCS

Abstract: Urban planning has a considerable impact on the economic performance of cities and on the quality of life of their populations. Efficiency at this level has been hampered by the lack of integrated tools to adequately describe urban space in order to formulate appropriate design solutions. This paper describes an ontology called LBCS-OWL2 specifically developed to overcome this flaw, based on the Land Based Classification Standards (LBCS), a comprehensive and detailed land use standard to describe the different dimensions of urban space. The goal is to provide semantic and computer-readable land use descriptions of geo-referenced spatial data. This will help to make programming strategies available to those involved in the urban development process. There are several advantages to transferring a land use standard to an OWL2 land use ontology: it is modular, it can be shared and reused, it can be extended and data consistency maintained, and it is ready for integration, thereby supporting the interoperability of different urban planning applications. This standard is used as a basic structure for the “City Information Modelling” (CIM) model developed within a larger research project called City Induction, which aims to develop a tool for urban planning and design.

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.

Urbanmetrics: An Algorithmic-(Para)Metric Methodology for Analysis and Optimization of Urban Configurations

This chapter describes and evaluates the implementation of Urbanmetrics, a computational planning support methodology based on a set of algorithmic-parametric tools, developed to measure and optimize urban configurations through metrics related to principles derived from Transit Oriented Development (TOD)—an urban development model that advocates walkable, compact and mixed-use neighborhoods, centered around transport stations. More specifically, Urbanmetrics is used to analyze and improve urban configurations according to TOD principles such as transit acessibility, walkability, diversity and density. Urbanmetrics allows one to consider simultaneously physical metrics (e.g., distance), topological measures (e.g., connectivity and integration), and mathematical operations (e.g., algebraic, geometric) as fitness functions in optimization processes, to achieve improved solutions for urban arrangements within TOD scope. A principle-index-tool triad supports Urbanmetrics. That is, for each addressed principle, there is one or more corresponding indexes to measure and optimize the performance of a given area, accordingly to TOD criteria.