Measuring urban form : overcoming terminological inconsistencies for a quantitative and comprehensive morphologic analysis of cities

Unprecedented urbanisation processes characterise the Great Acceleration, urging urban researchers to make sense of data analysis in support of evidence-based and large-scale deci- sion-making. Urban morphologists are no exception since the impact of urban form on funda- mental natural and social patterns (equity, prosperity and resource consumption’s efficiency) is now fully acknowledged. However, urban morphology is still far from offering a comprehensive and reliable framework for quantitative analysis. Despite remarkable progress since its emergence in the late 1950s, the discipline still exhibits significant terminological inconsistencies with regards to the definition of the fundamental components of urban form, which prevents the establishment of objective models for measuring it. In this article, we present a study of existing methods for measuring urban form, with a focus on terminological inconsistencies, and propose a systematic and comprehensive framework to classify urban form characters, where ‘urban form character’ stands for a characteristic (or feature) of one kind of urban form that distinguishes it from another kind. In particular, we introduce the Index of Elements that allows for a univocal and non-interpretive description of urban form characters. Based on such Index of Elements, we develop a systematic classification of urban form according to six categories (dimension, shape, spatial distribution, intensity, connectivity and diversity) and three conceptual scales (small, medium, large) based on two definitions of scale (extent and grain). This framework is then applied to identify and organise the urban form characters adopted in available literature to date. The resulting classification of urban form characters reveals clear gaps in existing research, in particular, in relation to the spatial distribution and diversity characters. The proposed framework reduces the current inconsistencies of urban morphology research, paving the way to enhanced methods of urban form systematic and quantitative analysis at a global scale

Towards a quantitative approach to morphological regions in GIS

The urban landscape is the result of a cumulative, historical stratification process, in which urban entities acquire formal and physical aspects that reflect the cultural and social functioning codes of the precedent periods in the city's formative process. Within this perspective, the concept of Morphological Regions and the method of Morphological Regionalisation, stand out as very important contributions to the study of the historico-geographical structure of the urban landscape. Central to that method, is the understanding of the way in which urban landscapes are structured: the existence of unitary areas which comprise an individualized combination of the three basic form complexes – namely the town plan, the building fabric and the land and building utilization — delimited by their degree of internal morphological similarity. However, from a methodological point of view, the identification of such areas (or morphological regions) remains based on qualitative visual analysis and on the personal expertise of the analyst. We propose to address the method of morphological regionalisation from a quantitative perspective, based on typological descriptions of urban form components derived by algorithmic means. The paper identifies and addresses the underlying premises of the method of regionalisation, arguing that its qualitative procedures can be translated into quantitative and objective parameters, through multi-variable geometric descriptions of urban form in GIS and through statistical clustering techniques. We attempt to contribute to the construction of a more robust method of morphological regionalisation, supported by a systematic and quantitative approach, applicable to large-scale comparative analysis of contemporary urban forms, which often elude previous historical typologies

Automatic generation of building information models from digitized plans

This paper proposes a new approach to creating Building Information (BIM) models of existing buildings from digitized images. This automatic approach is based on three main steps. The first involves extracting the useful information automatically from rasterized plans by using image processing techniques that include segmentation, filtering, dilation, erosion, and contour detection. This information feeds the knowledge base of an expert system for BIM model generation. In the second step, using the knowledge base of the expert system, the information required to inform the BIM model can be deduced. The range of information thus obtainable can be extended beyond the examples given. The paper concludes with a discussion of the final stage: the automatic generation of an Industry Foundation Classes (IFC) information model with all the desired geometric, physical and technical information. This can be accomplished by using one of the available open-source application program interfaces (APIs). This stage is currently work-in-progress and will be the subject of a future publication

A Supervised Approach to Delineate Built-Up Areas for Monitoring and Analysis of Settlements

Monitoring urban growth and measuring urban sprawl is essential for improving urban planning and development. In this paper, we introduce a supervised approach for the delineation of urban areas using commonly available topographic data and commercial GIS software. The method uses a supervised parameter optimization approach along with buffer-based quality measuring method. The approach was developed, tested and evaluated in terms of possible usage in monitoring built-up areas in spatial science at a very fine-grained level. Results show that built-up area boundaries can be delineated automatically with higher quality compared to the settlement boundaries actually used. The approach has been applied to 166 settlement bodies in Germany. The study shows a very efficient way of extracting settlement boundaries from topographic data and maps and contributes to the quantification and monitoring of urban sprawl. Moreover, the findings from this study can potentially guide policy makers and urban planners from other countries

Morphological tessellation as a way of partitioning space : improving consistency in urban morphology at the plot scale

Urban Morphometrics (UMM) is an expanding area of urban studies that aims at representing and measuring objectively the physical form of cities to support evidence-based research. An essential step in its development is the identification of a suitable spatial unit of analysis, where suitability is determined by its degree of reliability, universality, accessibility and significance in capturing essential urban form patterns. In Urban Morphology such unit is found in the plot, a fundamental component in the morphogenetic of urban settlements. However, the plot is a conceptually and analytically ambiguous concept and a kind of spatial information often unavailable or inconsistently represented across geographies, issues that limit its reliability and universality and hence its suitability for Urban Morphometric applications. This calls for alternative methods of deriving a spatial unit able to convey reliable plot-scale information, possibly comparable with that provided by plots. This paper presents Morphological Tessellation (MT), an objectively and universally applicable method that derives a spatial unit named Morphological Cell (MC) from widely available data on building footprint only and tests its informational value as proxy data in capturing plot-scale spatial properties of urban form. Using the city of Zurich (CH) as case study we compare MT to the cadastral layer on a selection of morphometric characters capturing different geometrical and configurational properties of urban form, to test the degree of informational similarity between MT and cadastral plots. Findings suggest that MT can be considered an efficient informational proxy for cadastral plots for many of the tested morphometric characters, that there are kinds of plot-scale information only plots can provide, as well as kinds only morphological tessellation can provide. Overall, there appears to be clear scope for application of MT as fundamental spatial unit of analysis in Urban Morphometrics, opening the way to large-scale urban morphometric analysis

Classifying Building Usages: A Machine Learning Approach on Building Extractions

This paper considers methods to infer building usage from the geographic and geometric spatial distribution of building extractions. Focusing on Knox County, TN, a Random Forest (RF) and Support Vector Machine (SVM) were used to classify a polygonized building map developed from a Convolutional Neural Network (CNN) based upon remote sensing imagery. The resulting classification metrics of nine building usages are then compared to the RF and SVM building usage classification of Knox County’s LiDAR building footprints and CNN building extractions with removal of false positives. It is shown that the raw CNN building extractions have acceptable building usage classification accuracies. This result is a useful addition to our understanding of building usage because the best remote sensing data (LiDAR building footprints) are not always accessible and completing tedious editing work (CNN building extractions with removal of false positives) is not feasible. Using the methods developed here, the effect of increasing CNN building detection training data for Knox County for testing on Knox County is also investigated. This case study assists in the process of examining if training a model on all Knox County CNN building detections can classify building usages in the similar urban-rural geographic location of Hamilton County, TN. ArcMap and R programming are utilized in gathering the data to conduct the machine learning algorithms while the building usage is defined by CoreLogic Parcel Land - Use codes

Geographical characterisation of British urban form and function using the spatial signatures framework

The spatial arrangement of the building blocks that make up cities matters to understand the rules directing their dynamics. Our study outlines the development of the national open-source classification of space according to its form and function into a single typology. We create a bespoke granular spatial unit, the enclosed tessellation, and measure characters capturing its form and function within a relevant spatial context. Using K-Means clustering of individual enclosed tessellation cells, we generate a classification of space for the whole of Great Britain. Contiguous enclosed tessellation cells belonging to the same class are merged forming spatial signature geometries and their typology. We identify 16 distinct types of spatial signatures stretching from wild countryside, through various kinds of suburbia to types denoting urban centres according to their regional importance. The open data product presented here has the potential to serve as boundary delineation for other researchers interested in urban environments and policymakers looking for a unique perspective on cities and their structure

Generalização cartográfica automatizada de toponímia de sistemas viários utilizando agentes

Orientadora : Profa. Dra. Luciene Stamato DelazariTese (doutorado) - Universidade Federal do Paraná, Setor de Ciências da Terra, Programa de Pós-Graduação em Ciências Geodésicas. Defesa: Curitiba, 21/08/2014Inclui referências : f. 131-136Resumo: A demanda de procedimentos que automatizem a generalização cartográfica é cada vez mais presente nos dias atuais, com a necessidade de apresentação dos mapas em dispositivos como os smartphones, que têm pequenas áreas de representação. Portanto é preciso tornar esse tipo de procedimento cada vez menos subjetivo e aprimorar os algoritmos já existentes, ou ainda propor novas soluções. Um dos elementos relevantes para o entendimento de uma região é a toponímia, que na maioria das vezes não é generalizada diretamente, pois são informações associadas às feições geográficas, que geralmente são o alvo da generalização. Porém, há casos em que existe espaço para representar os topônimos, mas os SIG utilizam das opções de colocação de etiquetas, ou fazem a eliminação do topônimo, mesmo quando poderia ser utilizada a abreviação. Nesta pesquisa os topônimos foram considerados feições geográficas e também como agentes. Estes atuam em um sistema multiagentes no qual tentam resolver seus conflitos de representação e armazenam e replicam as soluções encontradas para os demais agentes semelhantes. As amostras de dados utilizadas foram as regiões centrais dos municípios de Araucária, Curitiba e Florianópolis, contemplando, respectivamente, áreas com vias retas de baixa e alta hierarquia e ruas curvas. A partir destas, foram criadas tabelas para arquivar os atributos geométricos e semânticos dos topônimos e foram geradas imagens de mapas sem a toponímia. Estes foram processados por um aplicativo desenvolvido na Linguagem C, que resulta em imagens com a representação da toponímia generalizada. Ao considerar-se as escalas do mapeamento cadastral, o método utilizado apresenta vantagens a partir da escala 1:5000, na qual passa a representar mais informação acerca dos nomes das ruas das cidades. Em estudos futuros, pretende-se implementar este programa em um SIG. Palavras-chaves: generalização cartográfica, toponímia, agentes.Abstract: The need for processes to automated cartographic generalization are increasingly nowadays, mainly due to the need of map presentation in small devices, such as smartphones. Therefore it is necessary to make this procedure less and less subjective and improve the existing algorithms, or propose new solutions. One of the key elements for the understanding of a region is the place names. This, most of the times, is not directly generalized because it is information associated with the geographic features, which are usually the target of generalization. However, there are cases where there is space to represent the toponyms, but the GIS only make use of elimination or displacement, not exploiting other operator, such as abbreviation. This research considered the place names as geographical features as agents. These operate in a multi-agent system where they try to resolve their conflicts in the representation, storing and replicating the solutions for other similar agents. The samples used were the downtown regions of the municipalities of Araucaria, Curitiba and Florianópolis. From this, were created tables to store both the geometric and semantic attributes of place names and images of the maps without the place names. Those were then processed by a program developed in C language, which resulted in images with the representation of generalized toponymy. When considering the scales of cadastral mapping, the method developed has advantages from the scale 1:5000, which now represents more information about names of city streets, when comparing the same results obtained from a GIS software. In future studies, we intend to implement this program within a GIS. Keywords: cartographic generalization, toponymy, agent