Urban identity through quantifiable spatial attributes: Coherence and dispersion of local identity through the comparative analysis of building block plans

The present analysis investigates whether and to what degree quantifiable spatial attributes, as expressed in plan representations, can capture elements related to the experience of spatial identity. Spatial identity is viewed as a constantly rearranging system of relations between discrete singularities. It is proposed that the structure of this system is perceived, inter alia, through its reflection in patterns of variable associations amongst constant spatial features. The examination of such patterns could thus reveal aspects of spatial identity in terms of degrees of differentiation and identification between discrete spatial unities. By combining different methods of shape and spatial analysis it is attempted to quantify spatial attributes, predominantly derived from plans, in order to illustrate patterns of interrelations between spaces through an objective automated process. Variability of methods aims at multileveled spatial descriptions, based on features related to scalar, geometrical and topological attributes of plans. The analysis focuses on the scale of the urban block as the basic modular unit for the formation of urban configurations and the issue of spatial identity is perceived through consistency and differentiation within and amongst urban neighbourhoods. The abstract representation of spatial units enables the investigation of the structure of relations, from which urban identity emerges, based on generic spatial attributes, detached from specific expressions of architectural style

Visualisation techniques for users and designers of layout algorithms

Visualisation systems consisting of a set of components through which data and interaction commands flow have been explored by a number of researchers. Such hybrid and multistage algorithms can be used to reduce overall computation time, and to provide views of the data that show intermediate results and the outputs of complementary algorithms. In this paper we present work on expanding the range and variety of such components, with two new techniques for analysing and controlling the performance of visualisation processes. While the techniques presented are quite different, they are unified within HIVE: a visualisation system based upon a data-flow model and visual programming. Embodied within this system is a framework for weaving together our visualisation components to better afford insight into data and also deepen understanding of the process of the data's visualisation. We describe the new components and offer short case studies of their application. We demonstrate that both analysts and visualisation designers can benefit from a rich set of components and integrated tools for profiling performance

Spectral Clustering and Integration: The Inner Dynamics of Computational Geometry and Spatial Morphology

Deviating from common evaluation strategies of spatial networks that are realised through numerical comparison of single floating-point numbers such as global and local space syntax measures (centralities, connectivity, etc.) we aim to present a new computational methodology for creating detailed topo-geometric encodings of spaces that encapsulate some of the fundamental ideas about spatial morphology by Hillier (Space is the Machine: A Configurational Theory of Architecture, London, UK, Space Syntax, 2007 [1]). In most cases, space syntax measures try to capture a particular quality of the space for comparison but they lose much of the detail of the spatial topo-geometry and morphology by mainly aggregating graph path traversals and not retaining any other information. This research explores the use of weighted graph spectra, in a composite form, for the purpose of characterising the spatial structure as a whole. The new methodology focuses on the three primary space syntax graph modelling concepts, ‘angular’, ‘metric’ and ‘topological’, from the point of view of the resulting spatial geometries and develops new computational innovations in order to map spatial penetration of local neighbourhood spectra in different scales, dimensions and built environment densities in a continues way. The result is a new composite vector of high dimensionality that can be easily measured against others for detailed comparison. The proposed methodology is then demonstrated with the complete road-network dataset of Great Britain. The main dataset together with subsets is then used in a series of unsupervised machine learning analyses, including clustering and a form of Euclidian ‘spectral integration’

The Network Analysis of Urban Streets: A Primal Approach

The network metaphor in the analysis of urban and territorial cases has a long tradition especially in transportation/land-use planning and economic geography. More recently, urban design has brought its contribution by means of the "space syntax" methodology. All these approaches, though under different terms like accessibility, proximity, integration,connectivity, cost or effort, focus on the idea that some places (or streets) are more important than others because they are more central. The study of centrality in complex systems,however, originated in other scientific areas, namely in structural sociology, well before its use in urban studies; moreover, as a structural property of the system, centrality has never been extensively investigated metrically in geographic networks as it has been topologically in a wide range of other relational networks like social, biological or technological. After two previous works on some structural properties of the dual and primal graph representations of urban street networks (Porta et al. cond-mat/0411241; Crucitti et al. physics/0504163), in this paper we provide an in-depth investigation of centrality in the primal approach as compared to the dual one, with a special focus on potentials for urban design.Comment: 19 page, 4 figures. Paper related to the paper "The Network Analysis of Urban Streets: A Dual Approach" cond-mat/041124

Identifying Potential Indicators of Neighbourhood Solar Access in Urban Planning

Solar access describes the capacity of urban spaces to receive sunlight and daylight. Rapid urbanization and unbridled densification pose a threat to sustainable solar access, reducing the penetration of sunlight and daylight into cities. To effectively assess solar access at such an early design stage, at the urban planning level, it is critical that evaluation metrics are simple and reliable. This paper examines a cross section of solar metrics, from simple to more complex ones, to find potential solar performance indicators for urban planning evaluations. The metric datasets were created based on iterations of homogeneous neighbourhood designs, based on the three commonest typologies in the Swedish context: courtyard, slab, and tower. The results were validated using case studies sampled from districts of Malmö. The findings indicate that simple geometrical and latitudinal metrics may be suitable for assessing the solar access of urban designs due to high correlation with built density. Potential performance indicators aimed at indoor and outdoor evaluation of daylighting (VSC, SVF) and sunlighting (ASH_F, RD_G) in urban planning stages were suggested. Possible methods of applying the provided metric database into assessments were proposed. Future work should find evidence-based thresholds for the metric values to establish performance benchmarks

Solar access indicators for urban planning

Solar access describes the amount and distribution of sunlight in living environments. Access to sunlight is crucial for the health and sustainability of cities. It is vital for people and vegetation, and for energy production and conservation. The amount of sunlight entering the city space is restricted by the urban layout, as buildings obstruct solar access by shading each other and the surroundings. Scarcity of land and growing urbanisation drive the densification of cities. As cities are built taller and tighter, less sunlight can reach the urban fabric. This problem becomes especially critical for higher latitudes. Urban planners receive development directives that often stipulate higher densification of new and existing areas. Presently, some solar access aspects (daylighting and sunlighting) are legislated and evaluated at the late stages of building design, when it is often too late to change basic urban layout features to increase solar access. Thus, the urban planning level appears to be the appropriate design stage for solar access interventions. Having so many urban design objectives to deal with at this planning level, urban planners need simple methods to effectively introduce discussion of solar access into the design process. This thesis aims to contribute to this goal by investigating relevant metrics to identify suitable performance indicators for the purposes of solar access evaluation.In the first phase, a literature review was conducted to identify existing solar access metrics. The metrics were analysed and arranged into a metric taxonomy. The ways in which assessment metrics are typically formulated were also investigated, which led to structuring of the metric formulation principles. These guidelines may help analysts to select or formulate suitable metrics for specific design evaluations. In the next phase, the metrics that were identified from the literature review were further examined through correlation studies and statistical methods, including regression models. The study was conducted on neighbourhood models, typical for the Swedish context, including both generic design iterations and case studies. The relationships between metrics and urban density were investigated. The analysis identified four potential metrics (1. VSC, 2. SVF, 3. ASH_F, 4. RD_G) which can help assess solar access at the urban planning phase. They adhere to four design objectives for solar access, recognised as: 1) daylighting indoors, 2) daylighting outdoors, 3) sunlighting indoors, and 4) sunlighting outdoors. These metrics are well-correlated with urban density and with other metrics, yet remain relatively simple. Finally, two assessment methods that use and apply the identified performance indicators were suggested. Both models require the analyst to input the urban density and choose a target metric. Then, using the metric datasets created in this thesis, the assessment models return either 1) urban design proposals for a given development plot or 2) expected value ranges for a given metric to position the proposed design in reference to the previously simulated cases. The first method leaves less creative space for the planners, while the second method gives only reference values for estimation of the potential to improve a design. Future work should aim to focus on establishing metric thresholds, i.e., performance benchmarks, as this would further develop workflows for solar access evaluations. Evidence-based research is required to establish recommended solar access levels for the complex network of wellbeing and energy objectives