Citation

Sehra SS, Singh J, Sehra SK, Rai HS. Spat. Inf. Res. 2023; 31(2): 135-144.

Copyright

(Copyright © 2023, Korean Spatial Information Society, Publisher Holtzbrinck Springer Nature Publishing Group)

DOI

10.1007/s41324-022-00480-3

PMID

unavailable

Abstract

OpenStreetMap (OSM) offers an under-explored crowdsourced geospatial data useful to urban street network researchers for assessing the geometrical properties of spatial data. Urban street network analysis can provide the assessment of spatial dataset through these properties. The lack of a suitable evaluation framework renders problem for its potential users to evaluate the geometrical properties of the data. To overcome this difficulty, the capability of processing toolbox of QGIS has been extended by developing processing scripts using Python. These scripts were further used as components in the graphical modeler. The parameters such as degree centrality, average path length, closeness centrality, betweenness centrality, clustering coefficient, and inter-network indicators are developed to provide insights to the overall nature of the spatial data. For performing the empirical analysis, OSM dataset of five biggest cities of state of Punjab (India) have been analyzed and compared temporally. The results presented the internal geometrical feature's evaluation of street network in temporal comparison of OSM dataset and its credibility. This study provided the basis for reproducible research by developing components for open source software QGIS. The developed model can be used to asses the geometrical properties assessment by the town planners to identify the prominent nodes, edges and their relationships in the datasets.

Language: en

Keywords

OpenStreetMap; QGIS; Urban street network