Spatial reasoning as a syntactic method for programming socio-spatial parametric grammar for vertical residential buildings

Abstract

Integrating social constraints in computational models remains a challenge due to the difficulties in representing them algorithmically. Different methods, such as shape grammar and space syntax, consider the morphology of the overall form and its components. This research aims to find a mechanism for combining both methods for exploring spatial-formal features that affect the social life in vernacular houses in the Middle East and North Africa region. A developed model of 'spatial reasoning' analysis, embedded in Rhino/Grasshopper, offers an alternative method for extracting topological relations, understanding the social logic of spaces, and exploring the residents' behaviour by evaluating privacy, social interaction, and accessibility. The results of an analysis for vernacular houses and neighbourhoods were transformed into codes and parameters to be used for designing new vertical developments inspired from local traditions. The constructed grammar was used for developing a computational tool that generates alternatives which successfully achieved the principles of social sustainability.

The Implication of Spatial-Dispersion Theory in Housing Genotypes of Boushehri Historic and Contemporary Houses

“…In the next step, using the rotated component matrix table, the number of extracted categories and the concepts that de ne each of these factors could be discovered (Table 3). Consequently, the boundary commonalities in houses number 38,33,35,39,43,42,34,32,44,45,37,31,40,30,29,17 and 41 de ne the rst category. Houses number 28,26,22,27,20,18,19,16,23,25,24, and 21 are the second category, houses number 9, 5, 11, 15, 14, 1, 13, 3, 8, 7, 4 and 12 form the third category and houses 10 and 2 form the fourth category.…”

“…In Rhinoceros software and Grasshopper plugin, based on user input data, various spatial properties are accurately measured through mathematical algorithms and the effect of spatial con guration on the behavioral pattern of individuals is determined [26]. In recent years, studies investigated the syntax of residential spaces using this new method with the help of the Grasshopper plugin, which calculated the level of integration, control, choice, and entropy of spatial features such as privacy, spatial hierarchy, access, and order [27][28][29]. In this study, the typology of houses in the coastal city of Bushehr was discovered by combining the output of spatial analysis in Rhino and Depth Map, analysis of house structure, and factor analysis of the obtained data.…”

The implication of spatial-dispersion theory in housing genotypes of Boushehri historic and contemporary houses

“…In the next step, using the rotated component matrix table, the number of extracted categories and the concepts that define each of these factors could be discovered (Table 4). Consequently, the boundary commonalities in houses number 38,33,35,39,43,42,34,32,44,45,37,31,40,30,29,17 and 41 define the first category. Houses number 28,26,22,27,20,18,19,16,23,25,24, and 21 are the second category, houses number 9, 5, 11, 15, 14, 1, 13, 3, 8, 7, 4 and 12 form the third category and houses 10 and 2 form the fourth category.…”

“…In Rhinoceros software and Grasshopper plugin, based on user input data, various spatial properties are accurately measured through mathematical algorithms and the effect of spatial configuration on the behavioral pattern of individuals is determined [26]. In recent years, studies investigated the syntax of residential spaces using this new method with the help of the Grasshopper plugin, which calculated the level of integration, control, choice, and entropy of spatial features such as privacy, spatial hierarchy, access, and order [27][28][29]. In this study, the typology of houses in the coastal city of Bushehr was discovered by combining the output of spatial analysis in Rhino and Depth Map, analysis of house structure, and factor analysis of the obtained data.…”

Robust Attributed Adjacency Graph Extraction Using Floor Plan Images

“…Attributed adjacency graphs (also referred to as layout graphs/bubble diagrams/semantic building fingerprints in literature) can embed architectural information with multiple attributes, with nodes denoting different features of spaces and edges denoting various types of connections between spaces, which can be useful for numerous design tasks such as spatial analysis and reasoning (Al-Jokhadar & Jabi, 2020). Meanwhile, recent years have witnessed the surge of machine learning-based architectural design research (As et al, 2018).…”