Feature Recognition and Clustering for Urban Modelling – Exploration and Analysis in GIS and CAD

In urban planning exploration and analysis assist the generation, measurement, interpretation and management of the modelled urban environments. This frequently involves categorisation of model elements and identification of element types. Such designation of elements can be achieved through attribution (e.g. ‘tagging’ or ‘layering’) or direct selection by model users. However, for large, complex models the number and arrangement of elements makes these approaches impractical in terms of time/effort and accuracy. This is particularly true of models which include substantial numbers of elements representing existing urban fabric, rather than only newly generated elements (which might be automatically attributed during the generation process). We present methods for identification and categorisation of model elements in models of existing and proposed urban agglomerations. We also suggest how these methods can enable exploration of models, discovery of identities and relationships not otherwise obvious, and acquisition of insights to the models’ structure and contents which are not captured, and may even be obscured, by manual selection or automated pre-attribution

Integrating User and Usage Information in a Design Environment

We describe research exploring and demonstrating the use of large-scale data gathering and processing to inform the activities of architectural and urban designers. We apply this research to public spaces in urban housing estates. The aim is to understand the current use patterns and usability of these spaces, and to adaptively redesign them according to the insights gained from these findings. Another aim of the research is to obtain scientific knowledge regarding the production and use of user-data-based design support systems which promote and enhance the capability of (digital) design aids, such as building- and urban-scale models, to act as ‘learning devices’ giving designers better insights to the nature of the design situations they are asked to address, as well as insights on design space definition and exploration. We adopt a multimodal data collection strategy, consisting of participatory workshops for residents and users, person-based crowdsourcing, location-based crowd sensing, and statistical demographics data

Convex- and Solid-Void Models for Analysis and Classification of Public Spaces

In this paper a semiautomated morphological classification of urban space is addressed systematically by sorting through the volumetric shapes of public spaces represented as 3-dimensional convex and solid voids. The motivation of this approach comes from a frequent criticism of space syntax methods for lacking information on how buildings and terrain morphology influence the perception and use of public spaces in general and streets in particular. To solve this problem information on how façades relate with streets and especially information about the facades’ height should be considered essential to produce a richer and more accurate morphological analysis of street canyons and other open spaces. Parametric modelling of convex voids broadens the hitherto known concept of two-dimensional convex spaces considering surrounding facades’ height and topography as important inputs for volumetric representation of urban space. The method explores the analytic potentials of ‘convex voids’ and ‘solid voids’ in describing characteristics of open public spaces such as containment, openness, enclosure, and perceived enclosure, and using these metrics to analyse and classify urban open spaces

Feature recognition and clustering for urban modelling

In urban planning exploration and analysis assist the generation, measurement, interpretation and management of the modelled urban environments. This frequently involves categorisation of model elements and identification of element types. Such designation of elements can be achieved through attribution (e.g. ‘tagging’ or ‘layering’) or direct selection by model users. However, for large, complex models the number and arrangement of elements makes these approaches impractical in terms of time/effort and accuracy. This is particularly true of models which include substantial numbers of elements representing existing urban fabric, rather than only newly generated elements (which might be automatically attributed during the generation process). We present methods for identification and categorisation of model elements in models of existing and proposed urban agglomerations. We also suggest how these methods can enable exploration of models, discovery of identities and relationships not otherwise obvious, and acquisition of insights to the models’ structure and contents which are not captured, and may even be obscured, by manual selection or automated pre-attribution.Architectural Engineering +TechnologyArchitecture and The Built Environmen

Energy-oriented design tools for collaboration in the cloud

Emerging from the challenge to reduce energy consumption in buildings is the need for energy simulation to be used more effectively to support integrated decision making in early design. As a critical response to a Green Star case study, we present DEEPA, a parametric modeling framework that enables architects and engineers to work at the same semantic level to generate shared models for energy simulation. A cloud-based toolkit provides web and data services for parametric design software that automate the process of simulating and tracking design alternatives, by linking building geometry more directly to analysis inputs. Data, semantics, models and simulation results can be shared on the fly. This allows the complex relationships between architecture, building services and energy consumption to be explored in an integrated manner, and decisions to be made collaboratively

CO2 and temperature effects on morphological and physiological traits affecting risk of drought-induced mortality

Despite a wealth of eco-physiological assessments of plant response to extreme drought, few studies have addressed the interactive effects of global change factors on traits driving mortality. To understand the interaction between hydraulic and carbon metabolic traits influencing tree mortality, which may be independently influenced by atmospheric [CO2] and temperature, we grew Eucalyptus sideroxylon A. Cunn. ex Woolls from seed in a full-factorial [CO2] (280, 400 and 640 μmol mol−1, Cp, Ca and Ce, respectively) and temperature (ambient and ambient +4 °C, Ta and Te, respectively) experiment. Prior to drought, growth across treatment combinations resulted in significant variation in physiological and morphological traits, including photosynthesis (Asat), respiration (Rd), stomatal conductance, carbohydrate storage, biomass and leaf area (LA). Ce increased Asat, LA and leaf carbohydrate concentration compared with Ca, while Cp generated the opposite response; Te reduced Rd. However, upon imposition of drought, Te hastened mortality (9 days sooner compared with Ta), while Ce significantly exacerbated drought stress when combined with Te. Across treatments, earlier time-to-mortality was mainly associated with lower (more negative) leaf water potential (Ψl) during the initial drought phase, along with higher water loss across the first 3 weeks of water limitation. Among many variables, Ψl was more important than carbon status in predicting time-to-mortality across treatments, yet leaf starch was associated with residual variation within treatments. These results highlight the need to carefully consider the integration, interaction and hierarchy of traits contributing to mortality, along with their responses to environmental drivers. Both morphological traits, which influence soil resource extraction, and physiological traits, which affect water-for-carbon exchange to the atmosphere, must be considered to adequately predict plant response to drought. Researchers have struggled with assessing the relative importance of hydraulic and carbon metabolic traits in determining mortality, yet an integrated trait, time-dependent framework provides considerable insight into the risk of death from drought for trees

Interdisciplinary knowledge modelling for free-form design - An educational experiment

The recent advances in digital design media and digital fabrication processes have introduced formal and procedural effects on the conception and production of architecture. In order to bridge the individual concepts and processes of multiple design disciplines, intensive cross-disciplinary communication and information exchange starting from the very early stages of design is necessary. A web-based database for design learning and design teaching named BLIP is introduced. In this framework, cross-disciplinary domain knowledge becomes explicit to be taught and transferred in Free-Form Design research and education. BLIP proposes a conceptual map through which the user can construct structured representations of concepts and their relationships. These concepts are high-level abstractions of formal, structural and production related concepts in Free-Form design development. BLIP is used for formalizing, organizing and representing conceptual maps of the three domains and facilitates information and knowledge sharing in collaborative conceptual design in context. The paper introduces the application together with its application in two educational design experiments