Case Study of Spatial Pattern Description, Identification and Application Methodology

Abstract

In this case study the authors created and tested a configurable and expandable spatial patterns (SP) description, identification, and application methodology (SPDIAM) and an SP identification algorithm. SPDIAM allows urban planning and design (UPD) practitioners to describe SP in a computerized manner, identify SP automatically and then apply them in the UPD domain. SPDIAM is based on the space syntax (SS) method and normalized spatial and non-spatial measures and can be used with the statistical social, economic, and environmental indicators, which are related to the urban sustainability and spatial capital. The goal of the case study experiment was to proof a concept of SPDIAM and to identify the rules and the values of the measures used for the SP identification. For this City Layout SP was identified in the vector data of 12 European, North American, and African cities. The experiment results confirmed that SPDIAM is appropriate to describe SP and identify them automatically. The use of the normalized measures enables the comparison of different SP and reduces the degree of the subjectivity of the UPD solutions. SPDIAM no longer relies on statistical information but forms SP based on the probabilistic complex modelling of a city, which lets SPDIAM indicate possible directions of SP future transformation. SPDIAM uses the newly offered measures CENTER and URBAN COMPACTNESS INDEX to identify SP automatically and can add quantitative and qualitative improvement to the spatial network analysis tools in Geographic Information Systems.

SPDIAM: Methodology for Describing and Solving Spatial Problems in Territorial Planning

“…There were five spatial analysis methods-agent-based modelling, cellular automata, fractal analysis, space syntax, and SPDIAM that were compared using the qualitative descriptive method [24]. The features of the possible SP identification methods are compared focusing on three groups of criteria: (a) CSS modelling [11,23,[25][26][27][28][29], (b) method implementation [11,23,25,28], and (c) method application [23,[25][26][27][28]. Such method implementation aspects as source code, type of agent, coding language, API for model development, integrated development environment, operating system, or implementation platform [25] have not been compared, as currently there are too many different options that can be applied to each method, thus the implementation method alone does not bring enough added value to the method.…”

“…SPDIAM can be used in any of these fields as we can use the same steps to describe, identify, and apply different types of SP in various application fields. Only the principle of how to collect the input data that make up SP can differ, but the whole procedure is the same as described in [11].…”

“…And even more-SP when used together with simulation models can add additional value to CSS analysis. The oldest SP are urban models that nowadays can be defined as computer simulation models, combining theory, data, and algorithms, and which are classified into basic models (scale, analogue, conceptual); mathematical models (normative, probabilistic, optimizing) [9]; descriptive and analytical models [10]; and land-use-transportation models, that are used to predict demographic and economic measures of land-based activities [9,11].…”

“…SP description, identification, and application methodology (SPDIAM) [11] was developed for describing and detecting such spatial economic, social, and environmental phenomena and providing basic information technology (IT) artefacts that can be used for the development of the spatial structure (such as network or grid) analysis tools in Geographic Information System (GIS) [6]. SPDIAM allows urban planning and design (UPD) practitioners to describe SP in a computerized manner, identify SP automatically and apply them in the spatial planning and design domain.…”

“…SPDIAM allows urban planning and design (UPD) practitioners to describe SP in a computerized manner, identify SP automatically and apply them in the spatial planning and design domain. An SPDIAM data model [6,11] is based on the theory of CSS, spatial configuration and spatial capital concepts, space syntax method, and visibility graph analysis (VGA) [12]. It creates a computer model of space and quantifies its configuration which can be used to handle geographic and geometric data that are associated with attribute information, to perform spatial, mathematical, and statistical calculations.…”