A graph-based algorithm to define urban topology from unstructured geospatial data

Abstract

Interpretation and analysis of urban topology are particularly challenging tasks given the complex spatial pattern of the urban elements, and hence their automation is especially needed. In terms of the urban scene meaning, the starting point in this study is unstructured geospatial data, i.e. no prior knowledge of the geospatial entities is assumed. The aim of translating these data into more meaningful homogeneous regions can be achieved by detecting geographic features within the initial random collection of geospatial objects, and then by grouping them according to their spatial arrangement. The techniques applied to achieve this are those of graph theory applied to urban topology analysis within GIS environment. The role of graph theory in such a task and pre-processing of raw geospatial data were object of another previously published paper; this manuscript focuses primarily on the description of the procedure: "containmentfirst search" (CFS) -based on the well known breadth-first search algorithm for graph traversal, CFS analyzes and interprets the geospatial object arrangements in terms of the extension of the standard notion of the topological relation of adjacency to that of containment, what is defined within this research as "polygon-ring containment". LiDAR data were used as an example scenario for development purposes; in order to test the system proposed as a whole, further tests will entail the use of real world LiDAR datasets with different technical characteristics as well as photogrammetric datasets.

Ontology-Based Classification of Building Types Detected from Airborne Laser Scanning Data

“…Such challenges include occlusions caused by trees, shadowing [11], or confusion between buildings, roads, and bare soil [12]. Furthermore, descriptive information (features) derived from ALS data might be further used to extract -higher-level geographic information‖ [13], including building types. Unfortunately, only few studies have focused on evaluating the potential of ALS data for classifying the buildings into various classes [10,14].…”

Software Systems Approach to Multi-Scale GIS-BIM Utility Infrastructure Network Integration and Resource Flow Simulation

“…Future work could attempt to verify that this method can be extended to networks of other types of resources, such as gas and water supply and waste water. Further to its suitability for modelling and processing urban topologies [26,27], a graph database enables intuitive, human-readable concept models of systems to be reflected in the database structure, which results in a schema that is easier to interpret. There is no need to predefine the database schema since new nodes, relationships, and properties can be added on-the-fly; this flexibility is powerful for a utility resource network model that must integrate data from diverse and dynamic data sources.…”

“…A graph database was selected as they have been found to be efficient for storing and querying topologically connected data [24,25]. Furthermore, it has been proposed that graph theory and graph models are suitable for understanding urban topologies [26] and integrating models of urban data [27], and that graph databases can be used for the detection of spatial-semantic changes in CityGML documents [28]. The sub-networks derived from each data source are integrated into a single network by executing Neo4j Cypher queries that run 'merge' clauses on building nodes with matching identifiers across the CityGML and IFC files, and JSON stream.…”

Use of graph theory to study connectivity and regionalisation of the Polish urban network

“…They were used in network and settlement system research conducted by Rozenblat and Pumain (2006) as well as Rozenblat and Tissandier (2007). Furthermore, methodological works that combine classic graph theory with GIS tools have also emerged (de Almeida et al, 2013; Gil, 2014; Jażdżewska, 2008; Lin et al, 2013; Morgado & Costa, 2011; Natapov et al, 2013; Zdanowska et al, 2020).…”