Time, Spatial, and Descriptive Features of Pedestrian Tracks on Set of Visualizations

The aim of the paper is to elaborate on and evaluate a multiperspective cartographic visualization of the spatial behavior of pedestrians in urban space. The detailed objective is to indicate the level of usefulness of the proposed visualization methods for analyzing and interpreting the following features: track shape (trajectory geometry), topographical truth, track length, track visibility, walking time, motivation for getting to the finish point, walking speed, stops, spatial context (spatial surroundings, street names, and so on), and trajectory similarity. Each of the elaborated visualization presents spatial data from a different perspective and visually strengthens other aspects of the behavior of participants of the experiment. Recording the movement of participants by means of global positioning system (GPS) receivers was the first method used in the research, with the other one being a questionnaire that made it possible to determine what kind of motivation pedestrians had when selecting a track leading to the finish point. The results demonstrate different levels of usefulness of the six presented visualizations for reading selected features of the spatial behavior of pedestrians.

[1]  Beata Medyńska-Gulij,et al.  Graphically supported evaluation of mapping techniques used in presenting spatial accessibility , 2018, Cartography and Geographic Information Science.

[2]  Gerhard Tröster,et al.  Crowdsourced pedestrian map construction for short-term city-scale events , 2014, Urb-IoT.

[3]  Siegfried Reich,et al.  Why GPS makes distances bigger than they are , 2015, Int. J. Geogr. Inf. Sci..

[4]  Beata Medyńska-Gulij,et al.  Graphic Design and Button Placement for Mobile Map Applications , 2020 .

[5]  Helena Mitasova,et al.  Visualization of Pedestrian Density Dynamics Using Data Extracted from Public Webcams , 2019, ISPRS Int. J. Geo Inf..

[6]  Paweł Cybulski,et al.  Effectiveness of Dynamic Point Symbols in Quantitative Mapping , 2018, The Cartographic Journal.

[7]  Richard W. Olshavsky,et al.  Cognitive Maps and Spatial Behavior Of Consumers , 2010 .

[8]  Stefano Spaccapietra,et al.  Semantic trajectories modeling and analysis , 2013, CSUR.

[9]  Robert Lloyd,et al.  Cognitive Maps: Encoding and Decoding Information , 1989 .

[10]  Frank Dickmann,et al.  City Maps Versus Map-Based Navigation Systems – An Empirical Approach to Building Mental Representations , 2012 .

[11]  Pawel Cybulski,et al.  Cartographic Redundancy in Reducing Change Blindness in Detecting Extreme Values in Spatio-Temporal Maps , 2018, ISPRS Int. J. Geo Inf..

[12]  Tymoteusz Horbinski,et al.  Geovisualisation as a process of creating complementary visualisations: static two-dimensional, surface three-dimensional, and interactive , 2017 .

[13]  Lukasz Wielebski,et al.  Complexity Level of People Gathering Presentation on an Animated Map - Objective Effectiveness Versus Expert Opinion , 2020, ISPRS Int. J. Geo Inf..

[14]  Bettina Speckmann,et al.  Analysis and visualisation of movement: an interdisciplinary review , 2015, Movement Ecology.

[15]  Gennady L. Andrienko,et al.  Visual analytics of movement: An overview of methods, tools and procedures , 2013, Inf. Vis..

[16]  Gerta Köster,et al.  Can we learn where people go? , 2018, ArXiv.

[17]  Beata Medyńska-Gulij,et al.  Spatio-temporal dependencies between hospital beds, physicians and health expenditure using visual variables and data classification in statistical table , 2016 .

[18]  Stefan van der Spek,et al.  Classifying pedestrian movement behaviour from GPS trajectories using visualization and clustering , 2014, Ann. GIS.

[19]  Frank Dickmann,et al.  Mehrperspektivische Visualisierung von Informationen zum räumlichen Freizeitverhalten — Ein Smartphone-gestützter Ansatz zur Kartographie von Tourismusrouten , 2015, KN - Journal of Cartography and Geographic Information.

[20]  John Morrall,et al.  Analysis of factors affecting the choice of route of pedestrians , 1985 .

[21]  Morris S. Schwartz,et al.  Problems in Participant Observation , 1955, American Journal of Sociology.

[22]  Salmiah Abdul Hamid,et al.  Walking in the City of Signs: Tracking Pedestrians in Glasgow , 2014 .

[23]  Jarke J. van Wijk,et al.  Eurographics/ Ieee-vgtc Symposium on Visualization 2009 Visualization of Vessel Movements , 2022 .

[24]  Feng Qi,et al.  Trajectory data analyses for pedestrian space-time activity study. , 2013, Journal of visualized experiments : JoVE.

[25]  Dm Biadgilgn,et al.  Assessing the Cartographic Visualization of Moving Objects , 2011 .