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Vol. 1 No. 2 (2020)

Articles

Generation and Enrichment of Pedestrian Maps with Vertical Shadows in Urban Environments from Mobile Laser Scanning Data

https://doi.org/10.38094/jastt14114

Published 2020-12-31

  • Jesus Balado Frias
    • ,
  • Lucía Díaz-Vilariño
    • ,
  • Ernesto Frías
    • ,
  • Elena González

Jesus Balado Frias
Delft University of Technology, Faculty of Architecture and the Built Environment, GIS Technology Section. 2628 BL Delft, The Netherlands

Lucía Díaz-Vilariño
Universidade de Vigo, CINTECX, GeoTECH group. 36310 Vigo, España

Ernesto Frías
Universidade de Vigo, CINTECX, GeoTECH group. 36310 Vigo, España

Elena González
Universidade de Vigo, CINTECX, GeoTECH group. 36310 Vigo, España

Abstract

Cities are becoming more pedestrian-friendly, reducing traffic and promoting physical activity and walking. However, prolonged exposure to the sun can cause sunburn and skin problems, so minimizing exposure to the sun while travelling is especially relevant at certain latitudes and in the summer months. This paper proposes a method for modelling urban contours and generating pedestrian maps with the location of shaded areas and accessibility barriers. The proposed method uses as input data a point cloud of an urban environment acquired with Mobile Laser Scanning. First, the input point cloud is segmented in ground points, obstacle points, and points causing shadows. Then, the three segmented point clouds are rasterized and the corresponded images are combined to obtain the navigable ground and the shaded areas. Finally, from the navigable ground, a navigation map is generated for pedestrians. To check the usefulness of this navigation map, a pathfinding algorithm is applied. The results show a correct generation of the navigable ground, and routes prioritizing the trajectory by shadow areas. Depending on the weighting between sun and shaded areas, the routes obtained show differences in distance travelled and sun exposure. The proposed method is sensitive to the existence of obstacles and noise in the point clouds.

Keywords

point clouds, physical accessibility, people with disabilities, wheelchair, navigation, sun exposure

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References

  1. U. Kozan, S.S. Uzunoglu, The Importance of Pedestrianization in Cities- Assessment of Pedestrianized Streets in Nicosia Walled City, European Journal of Sustainable Development. 9 (2020) 589. https://doi.org/10.14207/ejsd.2020.v9n2p589.
  2. K. Pogacar, P. Senk, Alternative approaches and tools for the transformation of streescapes: Direct physical interventions and different modes of participation, Prostor. 26 (2018).
  3. R.L. Church, J.R. Marston, Measuring Accessibility for People with a Disability, Geographical Analysis. 35 (2003) 83–96. https://doi.org/10.1111/j.1538-4632.2003.tb01102.x.
  4. A. Zamanian, C. Hardiman, Electromagnetic radiation and human health: A review of sources and effects, High Frequency Electronics. 4 (2005) 16–26.
  5. S.N. Byrne, How much sunlight is enough?, Photochemical & Photobiological Sciences. 13 (2014) 840–852.
  6. A. Rodrigues, F.F. Sniehotta, V. Araujo-Soares, Are Interventions to Promote Sun-Protective Behaviors in Recreational and Tourist Settings Effective? A Systematic Review with Meta-analysis and Moderator Analysis, Annals of Behavioral Medicine. 45 (2012) 224–238. https://doi.org/10.1007/s12160-012-9444-8.
  7. A. Serna, B. Marcotegui, Urban accessibility diagnosis from mobile laser scanning data, ISPRS Journal of Photogrammetry and Remote Sensing. 84 (2013) 23–32. https://doi.org/10.1016/j.isprsjprs.2013.07.001.
  8. J. Balado, L. Diaz-Vilariño, P. Arias, H. González-Jorge, Automatic classification of urban ground elements from mobile laser scanning data, Automation in Construction. 86 (2018) 226–239. https://doi.org/10.1016/j.autcon.2017.09.004.
  9. K. Ishikawa, D. Kubo, Y. Amano, Curb Detection and Accessibility Evaluation from Low-Density Mobile Mapping Point Cloud Data, International Journal of Automation Technology. 12 (2018) 376–385.
  10. J. Balado, L. Diaz-Vilarino, P. Arias, I. Garrido, Point Clouds To Indoor / Outdoor Accessibility Diagnosis, ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences; ISPRS Geospatial Week 2017. IV-2/W4 (2017) 18–22. https://doi.org/doi.org/10.5194/isprs-annals-IV-2-W4-287-2017.
  11. L. Diaz-Vilarino, P. Boguslawski, K. Khoshelham, H. Lorenzo, L. Mahdjoubi, Indoor navigation from point clouds: 3D modelling and obstacle detection, The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. XLI-B4 (2016) 275–281. https://doi.org/10.5194/isprsarchives-XLI-B4-275-2016.
  12. T. Maruyama, S. Kanai, H. Date, M. Tada, Simulation-Based Evaluation of Ease of Wayfinding Using Digital Human and As-Is Environment Models, ISPRS International Journal of Geo-Information . 6 (2017). https://doi.org/10.3390/ijgi6090267.
  13. T. Maruyama, S. Kanai, H. Date, M. Tada, Motion-capture-based walking simulation of digital human adapted to laser-scanned 3D as-is environments for accessibility evaluation, Journal of Computational Design and Engineering. 3 (2016) 250–265. https://doi.org/https://doi.org/10.1016/j.jcde.2016.03.001.
  14. G. Lopez-Pazos, J. Balado, L. Diaz-Vilarino, P. Arias, M. Scaioni, Pedestrian pathfinding in urban environments: Preliminary results, in: ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Kyiv, Ukraine, 2017: pp. 4–6. https://doi.org/doi.org/10.5194/isprs-annals-IV-5-W1-35-2017.
  15. J. Balado, L. Diaz-Vilarino, P. Arias, H. Lorenzo, Point clouds for direct pedestrian pathfinding in urban environments, ISPRS Journal of Photogrammetry and Remote Sensing. 148 (2019) 184–196. https://doi.org/10.1016/j.isprsjprs.2019.01.004.
  16. M. Soilan, B. Riveiro, P. Linares, M. Padin-Beltran, Automatic Parametrization and Shadow Analysis of Roofs in Urban Areas from ALS Point Clouds with Solar Energy Purposes, ISPRS International Journal of Geo-Information . 7 (2018). https://doi.org/10.3390/ijgi7080301.
  17. Y. Ye, H. Chen, C. Zhang, X. Hao, Z. Zhang, SARPNET: Shape attention regional proposal network for liDAR-based 3D object detection, Neurocomputing. 379 (2020) 53–63. https://doi.org/https://doi.org/10.1016/j.neucom.2019.09.086.
  18. M. Engelcke, D. Rao, D.Z. Wang, C.H. Tong, I. Posner, Vote3Deep: Fast object detection in 3D point clouds using efficient convolutional neural networks, in: 2017 IEEE International Conference on Robotics and Automation (ICRA), 2017: pp. 1355–1361. https://doi.org/10.1109/ICRA.2017.7989161.
  19. G. Pang, U. Neumann, 3D point cloud object detection with multi-view convolutional neural network, in: 2016 23rd International Conference on Pattern Recognition (ICPR), 2016: pp. 585–590. https://doi.org/10.1109/ICPR.2016.7899697.
  20. ISO, ISO-21542 Building construction — Accessibility and usability of the built environment, ISO International Organization for Standardization. (2011).
  21. P.H.S. Torr, A. Zisserman, MLESAC: A New Robust Estimator with Application to Estimating Image Geometry, Computer Vision and Image Understanding. 78 (2000) 138–156. https://doi.org/10.1006/cviu.1999.0832.
  22. M. Weinmann, B. Jutzi, S. Hinz, C. Mallet, Semantic point cloud interpretation based on optimal neighborhoods, relevant features and efficient classifiers, ISPRS Journal of Photogrammetry and Remote Sensing. 105 (2015) (2015) 286–304. https://doi.org/10.1016/j.isprsjprs.2015.01.016.
  23. M. Soilán, L. Truong-Hong, B. Riveiro, D. Laefer, Automatic extraction of road features in urban environments using dense ALS data, International Journal of Applied Earth Observation and Geoinformation. 64 (2018) 226–236. https://doi.org/https://doi.org/10.1016/j.jag.2017.09.010.
  24. N. Izzati, H. Shamsudin, nurdiyana abdul razak, U. Yusof, mohd nor akmal Khalid, A Cellular Automata and Navigation Graph Framework in Simulating Crowd Behaviour at Bus Terminal Platform, 2015.
  25. I. Puente, H. Gonzalez-Jorge, J. Martinez-Sanchez, P. Arias, Review of mobile mapping and surveying technologies, Measurement: Journal of the International Measurement Confederation. 46 (2013) 2127–2145. https://doi.org/10.1016/j.measurement.2013.03.006.
  26. V.T. Ngoc Nha, S. Djahel, J. Murphy, A Comparative Study of Vehicles’ Routing Algorithms for Route Planning in Smart Cities, Vehicular Traffic Management for Smart Cities (VTM), First International Workshop on IEEE. (2012) 1–6. https://doi.org/10.1109/VTM.2012.6398701.

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