A Novel Method for Extracting and Analyzing the Geometry Properties of the Shortest Pedestrian Paths Focusing on Open Geospatial Data

Author:

Hosseini Reza1ORCID,Tong Daoqin2,Lim Samsung34ORCID,Sun Qian Chayn5,Sohn Gunho6ORCID,Gidófalvi Gyözö7ORCID,Alimohammadi Abbas8,Seyedabrishami Seyedehsan9ORCID

Affiliation:

1. Independent Researcher, Tehran 14117-13116, Iran

2. School of Geographical Sciences and Urban Planning, Arizona State University, Tempe, AZ 85287-5302, USA

3. School of Civil and Environmental Engineering, University of New South Wales, Sydney 2052, Australia

4. Biosecurity Program, Kirby Institute, University of New South Wales, Sydney 2052, Australia

5. Department of Geospatial Science, School of Science, RMIT University, Melbourne 3001, Australia

6. Department of Earth and Space Science & Engineering, Lassonde School of Engineering, York University, 4700 Keele St., Toronto, ON M3J 1P3, Canada

7. Division of Geoinformatics, Department of Urban Planning and Environment, KTH Royal Institute of Technology, 11428 Stockholm, Sweden

8. Department of Geospatial Information Systems, Faculty of Geodesy and Geomatics Engineering, K. N. Toosi University of Technology, Tehran 19967-15433, Iran

9. Department of Transportation Planning and Engineering, Faculty of Civil and Environmental Engineering, Tarbiat Modares University, Tehran 14117-13116, Iran

Abstract

Unlike car navigation, where almost all vehicles can traverse every route, one route might not be optimal or even suitable for all pedestrians. Route geometry information, including tortuosity, twists and turns along roads, junctions, and road slopes, among others, matters a great deal for specific types of pedestrians, particularly those with limited mobility, such as wheelchair users and older adults. Offering practical routing services to these users requires that pedestrian navigation systems provide further information on route geometry. Therefore, this article proposes a novel method for extracting and analyzing the geometry properties of the shortest pedestrian paths, with a focus on open geospatial data across four aspects: (a) similarity, (b) route curviness, (c) road turns and intersections, and (d) road gradients. Deriving from the Hausdorff distance, a metric called the “dissimilarity ratio” was developed, allowing us to determine whether pairs of routes show any tendencies to be similar to each other. Using the “sinuosity index”, a segment-based technique quantified the route curviness based on the number and degree of the road turns along the route. Moreover, relying upon open elevation data, the road gradients were extracted to identify routes offering smoother motion and better accessibility. Lastly, the road turns and intersections were investigated as pedestrian convenience and safety indicators. A local government area of Greater Sydney in Australia was chosen as the case study. The analysis was implemented on OpenStreetMap (OSM) shortest pedestrian paths against Google Maps as a benchmark for real-world commercial applications. The similarity analysis indicated that over 90% of OSM routes were identical or roughly similar to Google Maps. In addition, while Spearman’s rank correlation showed a direct relationship between route curviness and route length, rS(758) = 0.92, p < 0.001, OSM, on average, witnessed more tortuous routes and, consequently, shorter straight roads between turns. However, OSM routes could be more suitable for pedestrians when the frequency of intersections and road slopes are at the center of attention. Finally, the devised metrics in this study, including the dissimilarity ratio and sinuosity index, showed their practicability in translating raw values into meaningful indicators.

Publisher

MDPI AG

Subject

Earth and Planetary Sciences (miscellaneous),Computers in Earth Sciences,Geography, Planning and Development

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