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UID:pretalx-foss4g-europe-2025-DQYFQC@talks.staging.osgeo.org
DTSTART;TZID=CET:20250717T143000
DTEND;TZID=CET:20250717T150000
DESCRIPTION:In a time where geospatial information is key to provide contex
 t to the world we live in\, accurate\, realistic\, and complete maps are a
  first-hand necessity. Crowdsourced maps provide a fast\, reliable\, and a
 ffordable way to obtain global geospatial information. Points of interest 
 (POI)\, street networks\, landscape data\, and even 3D models are among th
 e information that can be extracted from crowdsourced platforms. In the ge
 ospatial community\, a project that has dominated the crowdsourced map sce
 ne for its reasonable accuracy\, and extense community\, is OpenStreetMap 
 (OSM). \n\nAs OSM has historically been car-centric\, deriving realistic a
 nd good-quality pedestrian and cycling networks poses a complex task. Vari
 ous initiatives to improve the quality and amount of pedestrian and cyclin
 g data has appeared over the years\, specially for big urban centres in hi
 gh-income countries. Yet\, inconsistencies are still present\, as the qual
 ity of the data in crowdsourced projects varies from one place to another.
  Those inconsistencies create a dissociation of the street network with th
 e reality.\n\nBuilding pedestrian networks is increasingly difficult\, as 
 walking offers such freedom of movement. While normally in high-income soc
 ieties there are multiple rules and regulations for pedestrians\, low and 
 middle income countries do not follow such rigurosity. Thus\, streets that
  are normally not considered “walkable” in certain places\, are realis
 tically used for pedestrian movement\, even without the required infrastru
 cture. Another limitation is the level of detail\, as big cities normally 
 have very high map detail –including features such as separately-mapped 
 sidewalks and crossroads–\, while some other cities only have basic\, ca
 r-centric\, traffic networks that do not offer information about pedestria
 n capabilities. The situation is less drastic for cycling networks\, as no
 rmally cycling can be performed over the traffic network. However\, more a
 ccurate maps would allow the creation of safer and better maps for cyclist
 s.\n\nIn this work\, we propose and test a methodology for producing reali
 stic pedestrian\, cycling\, and traffic street networks extracted from Ope
 nStreetMap. The methodology is composed of a generalised set of filters an
 d post-processing methods to produce realistic and usable pedestrian\, cyc
 ling\, and traffic street networks from anywhere in the world. By realisti
 c\, we mean that the networks should be as close to reality as possible\, 
 while usability is related to the fact that they should allow functional a
 spects such as routing. To extract the raw networks we used the OSMnx libr
 ary. Filtering and post-processing is then applied to each raw network for
  further refinement.\n\nFor pedestrian networks\, a filter was designed to
  retrieve all traffic\, pedestrian\, and cycling street segments that are 
 potentially pedestrian. As a generalisation\, each street is considered pe
 destrian at first\, and then\, based on certain elimination criteria\, non
 -walkable street segments are eliminated. Elimination criteria includes ce
 rtain types of streets (e.g.\, motorways)\, streets and paths that are non
 -accessible\, cycleways that do not allow pedestrians\, and streets that h
 ave separately-mapped sidewalks. Particular attention was paid to streets 
 with separately mapped sidewalks\, as they provided an important source of
  inconsistencies. Separately mapped sidewalks provide granularity when map
 ping pedestrian networks\, as it states a clear separation between the geo
 metry of the main road and the geometry of the sidewalk. However\, inconsi
 stencies arise when the street segment does not specify that it has a sepa
 rately mapped sidewalk. The main issue with this kind of inconsistency is 
 the duplication of street segments\, increasing the size and complexity of
  an already complex network\, affecting real distances\, pedestrian routes
 \, and the calculation of indices based on the network topology. To overco
 me this\, a novel algorithm was implemented to eliminate streets with sepa
 rately mapped sidewalks based on spatial and angular proximity\, i.e.\, th
 at both a sidewalk and a street segment are close\, and their compass angl
 e is similar. As an example\, the processing of the pedestrian street netw
 ork of Mostar\, Bosnia and Herzegovina\, resulted in a network of 5.354 ed
 ges\, instead of the original 50.068 edges without elimination\, posing a 
 significant reduction. One special remark is that pedestrian street networ
 ks are represented as undirected graphs\, meaning that every segment can b
 e traversed in any direction.\n\nFor cycling street networks\, a filter wa
 s designed to exclude all non-bikeable segments\, as well as segments that
  clearly specify that cycling is not permitted. Cycling poses less challen
 ges than pedestrian street networks\, as regulations for bicycles are norm
 ally more strict\, and bicycles normally can use the traffic street networ
 k. Thus\, the cycling network is built on the assumption that bicycles can
  circulate on any street of the traffic network\, and elimination is made 
 based on attributes. Additionally\, as cycle networks are similar to traff
 ic\, direction is important. This means that cycling networks are represen
 ted as directed graphs.\n\nFor completeness\, the methodology for extracti
 ng traffic networks is provided. As OSM is already car-centric\, building 
 realistic and usable traffic networks is not a complex task. Nonetheless\,
  special care must be taken towards street direction\, as the direction in
  which traffic can flow is important for traffic. Ergo\, traffic street ne
 tworks are represented also as directed graphs.\n\nAn additional advantage
  of this methodology is that it can be used to spot inconsistencies on the
  various street networks of OSM\, aiding in collaborative mapping efforts.
  The paper will provide examples on how this methodology can be used to id
 entify duplicated streets and sidewalks\, and disconnected street segments
 . \n\nTo conclude\, street networks provide valuable information about hum
 an mobility and urban dynamics. Its analysis is fundamental for understand
 ing cities and settlements. Having realistic\, usable\, and open-sourced s
 treet network models is then a necessity to analyse\, plan\, and implement
  measures for sustainable and resilient cities. This work proposes a novel
  methodology to extract pedestrian\, cycling\, and traffic street networks
  that considers not only functionality\, but also real world scenarios.
DTSTAMP:20260527T222700Z
LOCATION:PA01 (Quarticle)
SUMMARY:Extracting realistic pedestrian\, cycling\, and traffic street netw
 orks from OpenStreetMap - Juan Pablo Duque Ordoñez
URL:https://talks.staging.osgeo.org/foss4g-europe-2025/talk/DQYFQC/
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