Surface roughness from large-scale laser scanning point clouds for urban accessibility analysis
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Autor:in (Körperschaft)
Publikationsdatum
2026
Typ der Arbeit
Studiengang
Sammlung
Typ
01A - Beitrag in wissenschaftlicher Zeitschrift
Herausgeber:innen
Herausgeber:in (Körperschaft)
Betreuer:in
Übergeordnetes Werk
Smart Cities
Themenheft
DOI der Originalpublikation
Link
Zugehörige Forschungsdaten
Reihe / Serie
Reihennummer
Jahrgang / Band
9
Ausgabe / Nummer
9
Seiten / Dauer
146
Patentnummer
Verlag / Herausgebende Institution
MDPI
Verlagsort / Veranstaltungsort
Auflage
Version
Programmiersprache
Abtretungsempfänger:in
Praxispartner:in/Auftraggeber:in
Zusammenfassung
Surface macrotexture is of major interest for barrier-free routing, particularly for wheelchair travellers, because it relates to the functional properties of pavements, such as loss of energy through tyre-rolling resistance or vibrational discomfort. These functional properties are difficult to assess. The measurement and characterization of pavement macrotexture, therefore, is a promising approach to support safe route choice for wheelchair travellers and to provide comparative quality criteria for inclusive urban infrastructure management and planning. We use 3D point clouds from terrestrial laser scanning (TLS) and suggest a set of surface roughness parameters tailored to assess the accessibility of urban pavements at the micro-level. We explore the sensitivity of the parameters to point cloud resampling and apply them to a real-world dataset with eleven different pavements. In spite of value variation related to scanning distance and coverage, our results indicate that combining median-based versions of Average Roughness and Simulated Texture Depth together with parameters tailored to quantify the depth and proportion of joints and the roughness of the contact area facilitates the grouping and comparison of surfaces regarding barrier-free mobility. The results of this work will be integrated into a framework for accessibility analysis and barrier-free routing.
Schlagwörter
Fachgebiet (DDC)
Veranstaltung
Startdatum der Ausstellung
Enddatum der Ausstellung
Startdatum der Konferenz
Enddatum der Konferenz
Datum der letzten Prüfung
ISBN
ISSN
2624-6511
Sprache
Englisch
Während FHNW Zugehörigkeit erstellt
Ja
Zukunftsfelder FHNW
Publikationsstatus
Veröffentlicht
Begutachtung
peer-reviewed
Open Access-Status
Gold
Lizenz
Zitation
Hollenstein, D., Ammann, M., Grimm, D., & Bleisch, S. (2026). Surface roughness from large-scale laser scanning point clouds for urban accessibility analysis. Smart Cities, 9(9), 146. https://doi.org/10.3390/smartcities9090146