Design of a spatial database to analyze the forms and responsiveness of an urban environment using an ontological approach

Abstract

This paper introduces a spatial database and ontology-enabled framework that models and operationalizes the relation between urban forms and their responsiveness to the needs of its user. The objective is to offer a framework that provides a practical implementation of the concept of responsive environment introduced by Bentley, Alcock, Murrain, McGlynn and Smith (1985) in order to provide enough reusability and flexibility to reflect different urban modeling viewpoints and conceptualizations. The developed system is organized in three modules: the first and second modules model the ontology of a responsive environment and the layout of an urban environment while the third module is a spatial database that supports further computational analysis of urban forms. We applied several spatial data metrics that analyze the structural properties of urban forms and the emerging opportunities as identified by the notion of responsive environments. The framework is experimented and applied to the district 12, region 4 of the city of Tehran in Iran. The modeling abstractions lead to the generation of several semantic bridge rules and map layers that reflect different levels of urban responsiveness. The emerging patterns are qualitatively evaluated and found to be correlated with inhabitants' own perception of an urban environment. The results show that the suggested framework can be applied to the analysis of the responsive environments of urban forms.

Evaluating the Impacts of Virtual Organization Absorption on the Quality of Urban Private Constructions; the System Dynamics Approach

“…Based on the study that provides an ontology model for the QCC of UPC in Iran (Moradi et al 2018) and according to many studies that focus on ontology-based systems and their advantages (Chung et al 2014;Niknam and Karshenas 2017;Rezgui et al 2011;Saba and Mohamed 2013;Silavi et al 2016;Staab and Studer 2013;Zhang and Issa 2011), this system is perceived here as a base model.…”

“…An ontology is a formal, explicit, and computer-understandable model, which describes the notions of a certain domain of interest (El-Gohary and El-Diraby 2009). In Fact, an ontology by identifying the terms, which constitute the intended concept, along with formulating their relations and axioms (Silavi et al 2016) provides a foundation, upon which VO could be constructed with rich capabilities in IM and knowledge extraction. As a result, scholars in different fields have used this approach to deal with their challenges (Iqbal et al 2013).…”

EFTG: Efficient and Flexible Top-K Geo-textual Publish/Subscribe

“…Spatial keyword query has been extensively studied in academia. Some research retrieves a set of geographical text objects based on Boolean matching [26] [27]. Other research is based on a scoring function with a federated spatial index (such as R-Tree, Quadtree) and a text index (such as a reverse file) [13] [28].…”

Projecting Pathways to Food–Energy–Water Systems Sustainability Through Ontology

“…Ontologies are also used to define indicators that relate to environmental, social, and economic variables and concepts such as efficiency, production, assessment, regulation, finance, industrial activity, monitoring, and ecology (e.g., Devuyst et al, 2001;Schwartz et al, 2002;Warhurst, 2002;Sikdar, 2003;Bebbington et al, 2007;Teece, 2007;Sala et al, 2015;UNSDG, 2015;Van de Kerk and Manuel, 2016;Geiger et al, 2017). They are built for environmental impact assessment (Garrido and Requena, 2011), sharing of expert knowledge in sustainability science (Kraines and Guo, 2011), environmental justice (Huang, 2015), decision management of urban water resources (Oliva-Felipe et al, 2017), structural properties of forms in an urban system (Silavi et al, 2016), flood risk assessment (Scheuer et al, 2013), built environment (Abanda et al, 2013;Chong and Wang, 2016), and environmental issues related to biological and biomedical sciences (ENVO, 2013;Buttigieg et al, 2013Buttigieg et al, , 2016. Previous semantic models emphasize on specific dimensions of the FEW systems in relation to sustainability (e.g., Kumazawa et al, 2009Kumazawa et al, , 2014Kumazawa et al, , 2017, FEW resources (e.g., Endo et al, 2015;Rao et al, 2016), Earth and environmental science (Raskin and Pan, 2005), hydrogeology (CUAHSI, 2008;Tripathy and Babaie, 2008), or urban environment (e.g., Vilches-Blázquez et al, 2007), and generally do not take an integrated, complex system approach to the nexus issues of the FEW networks in relation to various ecosystems.…”