Identification of central urban attractions based on GPS tracking data and network analysis
Article Sidebar
Main Article Content
Abstract
This study introduces a useful methodology to identify central urban tourism attractions based on the combination of GPS tracking data and the Network Analysis of visited attractions derived from GPS data. Identifying central attractions becomes critical for city managers when it comes to planning urban facilities, managing municipal resources, locating new attractions or capturing all the potential returns. The first step of the proposed methodology is the detection of visited attractions based on GPS tracking data analysis. Then from this GPS data set a network of visited attractions is built in order to carry out a network analysis. The empirical study is performed for the city of Bilbao, a tourism destination made famous by the Guggenheim Museum. Surprisingly, our methodology leads to unexpected results: while social media content (e.g. TripAdvisor) and experts (tourism agents) point to the Guggenheim as the main tourism asset, in fact it turns out to be the Old Town the most visited place in Bilbao according to real spatial behavior detected by our method. This methodological approach can be valuable for performing decisions that are more accurate and better policies concerning urban planning and management.
Downloads
Article Details
References
Abedi, N., Bhaskar, A., & Chung, E. (2014). Tracking spatio-temporal movement of human in terms of space utilization using Media-Access-Control address data. Applied Geography, 51, 72–81. https://doi.org/10.1016/j.apgeog.2014.04.001
Aranburu, I., Plaza, B., & Esteban, M. (2016). Sustainable Cultural Tourism in Urban Destinations: Does Space Matter? Sustainability, 8(8), 699. https://doi.org/10.3390/su8080699
Ashbrook, D., & Starner, T. (2003). Using GPS to learn significant locations and predict movement across multiple users. Personal and Ubiquitous Computing, 7(5), 275–286. https://doi.org/10.1007/s00779-003-0240-0
Axhausen, K. W., Schonfelder, S., Wolf, J., Oliveira, M., & Samaga, U. (2003). Eighty weeks of GPS traces: Approaches to enriching trip information. In The 83rd Transportation Research Board Meeting (pp. 1870–1876). Washington, DC.
Barthélemy, M. (2011). Spatial networks. Physics Reports, 499(1–3), 1–101. https://doi.org/10.1016/j.physrep.2010.11.002
Bastian, M., Heymann, S., & Jacomy, M. (2009). Gephi: An Open Source Software for Exploring and Manipulating Networks. Retrieved from http://www.aaai.org/ocs/index.php/ICWSM/09/paper/view/154
Bohte, W., & Maat, K. (2009). Deriving and validating trip purposes and travel modes for multi-day GPS-based travel surveys: A large-scale application in the Netherlands. Transportation Research Part C: Emerging Technologies, 17(3), 285–297. https://doi.org/10.1016/j.trc.2008.11.004
Capello, R., & Perucca, G. (2017). Cultural Capital and Local Development Nexus: Does the Local Environment Matter? In Socioeconomic Environmental Policies and Evaluations in Regional Science (pp. 103–124). Springer. https://doi.org/10.1007/978-981-10-0099-7_6
Cheng, J., Karambelkar, B., & Xie, Y. (2017). Leaflet: Create Interactive Web Maps with the JavaScript “Leaflet” Library. R package version 1.1.0. Retrieved from https://cran.r-project.org/package=leaflet
CICtourGUNE. (2011). Centro de Investigación Cooperativa en Turismo. Spain.
Demšar, U., Špatenková, O., & Virrantaus, K. (2008). Identifying Critical Locations in a Spatial Network with Graph Theory. Transactions in GIS, 12(1), 61–82. https://doi.org/10.1111/j.1467-9671.2008.01086.x
Dietvorst, A., & Ashworth, G. (1995). Tourist behaviour and the importance of time-space analysis. In Tourism and spatial transformations. (pp. 163–181). CAB International.
Esteban, M. (1999). Bilbao, luces y sombras del titanio: el proceso de regeneración del Bilbao metropolitano. Servicio Editorial de la Universidad del País Vasco.
Freeman, L. C. (1978). Centrality in social networks conceptual clarification. Social Networks, 1(3), 215–239. https://doi.org/10.1016/0378-8733(78)90021-7
Freytag, T. (2002). Tourism in Heidelberg: getting a picture of the city and its visitors. In City tourism 2002: Proceedings of European Cities Tourism's International Conference in Vienna, Austria, 2002 (pp. 211–219). Springer-Verlag Wien.
Fu, Z., Tian, Z., Xu, Y., & Qiao, C. (2016). A Two-Step Clustering Approach to Extract Locations from Individual GPS Trajectory Data. ISPRS International Journal of Geo-Information, 5(10), 166. https://doi.org/10.3390/ijgi5100166
Galí Espelt, N., & Donaire Benito, J. A. (2018). First-time versus repeat visitors’ behavior patterns: a GPS analysis. Boletín de La Asociación de Geógrafos Españoles, (78), 2711. https://doi.org/10.21138/bage.2711
García-Palomares, J. C., Gutiérrez, J., & Mínguez, C. (2015). Identification of tourist hot spots based on social networks: A comparative analysis of European metropolises using photo-sharing services and GIS. Applied Geography, 63, 408–417. https://doi.org/10.1016/j.apgeog.2015.08.002
Gobierno Vasco. (2012). Open Data Euskadi. Retrieved from http://opendata.euskadi.eus
Gospodini, A. (2001). Urban Design , Urban Space Morphology , Urban Tourism : An Emerging New Paradigm Concerning. European Planning Studies, 9(7), 925–934. https://doi.org/10.1080/0965431012007984
Grinberger, A. Y., Shoval, N., & McKercher, B. (2014). Typologies of tourists’ time–space consumption: a new approach using GPS data and GIS tools. Tourism Geographies, 16(1), 105–123. https://doi.org/10.1080/14616688.2013.869249
Gschwender, A., Munizaga, M., & Simonetti, C. (2016). Using smart card and GPS data for policy and planning: The case of Transantiago. Research in Transportation Economics, 59, 242–249. https://doi.org/10.1016/j.retrec.2016.05.004
Hall, C. M., & Ram, Y. (2019). Measuring the relationship between tourism and walkability? Walk Score and English tourist attractions. Journal of Sustainable Tourism, 27(2), 223–240. https://doi.org/10.1080/09669582.2017.1404607
Hartman, G. W. (1950). The Central Business District - A Study in Urban Geography. Economic Geography, 26(4), 237. https://doi.org/10.2307/141260
Hasan, S., Schneider, C. M., Ukkusuri, S. V, & González, M. C. (2013). Spatiotemporal Patterns of Urban Human Mobility. Journal of Statistical Physics, 151(1–2), 304–318. https://doi.org/10.1007/s10955-012-0645-0
Hawelka, B., Sitko, I., Beinat, E., Sobolevsky, S., Kazakopoulos, P., & Ratti, C. (2014). Geo-located Twitter as proxy for global mobility patterns. Cartography and Geographic Information Science, 41(3), 260–271. https://doi.org/10.1080/15230406.2014.890072
Jayasinghe, A., Sano, K., & Rattanaporn, K. (2017). Application for developing countries: Estimating trip attraction in urban zones based on centrality. Journal of Traffic and Transportation Engineering (English Edition), 4(5), 464–476.
Kaplan, E. D. (1996). Understanding GPS: Principles and Applications. Artech House.
Karambelkar, B., & Zheng, B. (2017). Extra Functionality for “leaflet” Package. Retrieved from https://cran.r-project.org/package=leaflet.extras
Kladou, S., & Mavragani, E. (2015). Assessing destination image: An online marketing approach and the case of TripAdvisor. Journal of Destination Marketing & Management, 4(3), 187–193. https://doi.org/10.1016/j.jdmm.2015.04.003
Kourtit, K., Nijkamp, P., & Partridge, M. D. (2013). The New Urban World. European Planning Studies, 21(3), 285–290. https://doi.org/10.1080/09654313.2012.716242
Lau, G., & McKercher, B. (2006). Understanding tourist movement patterns in a destination: A GIS approach. Tourism and Hospitality Research, 7(1), 39–49. https://doi.org/10.1057/palgrave.thr.6050027
Le-Klähn, D.-T. (2016). Sustainable Tourist Mobility: Implications for Urban Destination Management. In Sustainable Mobility in Metropolitan Regions (pp. 55–63). Wiesbaden: Springer Fachmedien Wiesbaden. https://doi.org/10.1007/978-3-658-14428-9_4
Leung, X. Y., Wang, F., Wu, B., Bai, B., Stahura, K. A., & Xie, Z. (2012). A Social Network Analysis of Overseas Tourist Movement Patterns in Beijing: the Impact of the Olympic Games. International Journal of Tourism Research, 14(5), 469–484. https://doi.org/10.1002/jtr.876
Lew, A., & McKercher, B. (2006). Modeling Tourist Movements. A Local Destination Analysis. Annals of Tourism Research, 33(2), 403–423. https://doi.org/10.1016/j.annals.2005.12.002
Liu, B., Huang, S. S., & Fu, H. (2017). An application of network analysis on tourist attractions: The case of Xinjiang, China. Tourism Management, 58, 132–141. https://doi.org/10.1016/j.tourman.2016.10.009
Mazimpaka, J. D., & Timpf, S. (2015). Exploring the Potential of Combining Taxi GPS and Flickr Data for Discovering Functional Regions. In AGILE 2015 (pp. 3–18). Springer. https://doi.org/10.1007/978-3-319-16787-9_1
Mckercher, B., & Lau, G. (2008). Movement Patterns of Tourists within a Destination. Tourism Geographies, 10(3), 355–374. https://doi.org/10.1080/14616680802236352
McKercher, B., Shoval, N., Ng, E., & Birenboim, A. (2012). First and Repeat Visitor Behaviour: GPS Tracking and GIS Analysis in Hong Kong. Tourism Geographies, 14(1), 147–161. https://doi.org/10.1080/14616688.2011.598542
Modsching, M., Kramer, R., Hagen, K. Ten, & Gretzel, U. (2008). Using Location-based Tracking Data to Analyze the Movements of City Tourists. Information Technology & Tourism, 10(1), 31–42. https://doi.org/10.3727/109830508785059011
Montoliu, R., Blom, J., & Gatica-Perez, D. (2013). Discovering places of interest in everyday life from smartphone data. Multimedia Tools and Applications, 62(1), 179–207. https://doi.org/10.1007/s11042-011-0982-z
Murakami, E., & Wagner, D. P. (1999). Can using global positioning system (GPS) improve trip reporting? Transportation Research Part C: Emerging Technologies, 7(2), 149–165.
Page, S. (2004). Transport and tourism. In A companion to tourism. Blackwell Publishing, Malden, Mass.
Pearce, D. G. (1988). Tourist time-budget. Annals of Tourism Research, 15(1), 106–121.
Peng, X., & Huang, Z. (2017). A Novel Popular Tourist Attraction Discovering Approach Based on Geo-Tagged Social Media Big Data. ISPRS International Journal of Geo-Information, 6(7), 216. https://doi.org/10.3390/ijgi6070216
Plaza, B., & Haarich, S. N. (2009). Museums for urban regeneration? Exploring conditions for their effectiveness. Journal of Urban Regeneration and Renewal, 2(3), 259–271. Retrieved from https://www.ingentaconnect.com/content/hsp/jurr/2009/00000002/00000003/art00006
Quiroga, C. A., & Bullock, D. (1998). Travel time studies with global positioning and geographic information systems: an integrated methodology. Transportation Research Part C: Emerging Technologies, 6(1), 101–127.
Ratti, C., Sobolevsky, S., Calabrese, F., Andris, C., Reades, J., Martino, M.,…Strogatz, S. H. (2010). Redrawing the Map of Great Britain from a Network of Human Interactions. PLoS ONE, 5(12), e14248. https://doi.org/10.1371/journal.pone.0014248
Richards, G. (2010). Increasing the Attractiveness of Places Through Cultural Resources. Tourism Culture & Communication, 10(1), 47–58. https://doi.org/10.3727/109830410X12629765735678
Richards, G. (2011). Creativity and tourism. Annals of Tourism Research, 38(4), 1225–1253. https://doi.org/10.1016/j.annals.2011.07.008
Richards, G. (2014). Creativity and tourism in the city. Current Issues in Tourism, 17(2), 119–144. https://doi.org/10.1080/13683500.2013.783794
Ruhnau, B. (2000). Eigenvector-centrality—a node-centrality? Social Networks, 22(4), 357–365. https://doi.org/10.1016/S0378-8733(00)00031-9
Sacco, P., Ferilli, G., & Blessi, G. T. (2014). Understanding culture-led local development: A critique of alternative theoretical explanations. Urban Studies, 51(13), 2806–2821.
Schönfelder, S., Axhausen, K. W., Antille, N., & Bierlaire, M. (2002). Exploring the Potentials of Automatically Collected GPS Data for Travel Behaviour Analysis: A Swedish Data Source. Arbeitsberichte Verkehrs-Und Raumplanung, 124.
Schuessler, N., & Axhausen, K. W. (2009). Identifying trips and activities and their characteristics from GPS raw data without further information. Transportation Research Record: Journal of the Transportation Research Board., 2105, 1–28.
Scott, J. P. (2000). Social Network Analysis: A Handbook. SAGE Publications. Retrieved from https://uk.sagepub.com/en-gb/eur/the-sage-handbook-of-social-network-analysis/book232753
Shaw, G., Agarwal, S., & Bull, P. (2000). Tourism consumption and tourist behaviour: A British perspective. Tourism Geographies, 2(3), 264–289. https://doi.org/10.1080/14616680050082526
Shen, L., & Stopher, P. R. (2014). Review of GPS Travel Survey and GPS Data-Processing Methods. Transport Reviews, 34(3), 316–334.https://doi.org/10.1080/01441647.2014.903530
Shoval, N., & Isaacson, M. (2009). Tourist Mobility and Advanced Tracking Technologies. Routledge Advances in Tourism series.
Shoval, N., McKercher, B., Ng, E., & Birenboim, A. (2011). Hotel location and tourist activity in cities. Annals of Tourism Research, 38(4), 1594–1612. https://doi.org/10.1016/j.annals.2011.02.007
Silberberg, T. (1995). Cultural Tourism and Business Opportunities for Museums and Heritage Sites. Tourism Management, 16(5), 361–365. https://doi.org/10.1016/0261-5177(95)00039-Q
Soh, H., Lim, S., Zhang, T., Fu, X., Lee, G. K. K., Hung, T. G. G., … Wong, L. (2010). Weighted complex network analysis of travel routes on the Singapore public transportation system. Physica A: Statistical Mechanics and Its Applications, 389(24), 5852–5863. https://doi.org/10.1016/j.physa.2010.08.015
Stienmetz, J. L., & Fesenmaier, D. R. (2015). Estimating value in Baltimore, Maryland: An attractions network analysis. Tourism Management, 50, 238–252. https://doi.org/10.1016/j.tourman.2015.01.031
Stopher, P., Jiang, Q., & FitzGerald, C. (2005). Processing GPS data from travel surveys. In 2nd International Colloqium on the behavioural foundations of integrated land-use and transportation models: frameworks, models and applications (pp. 1–21). Toronto.
Taczanowska, K., González, L.-M., Garcia-Massó, X., Muhar, A., Brandenburg, C., & Toca-Herrera, J.-L. (2014). Evaluating the structure and use of hiking trails in recreational areas using a mixed GPS tracking and graph theory approach. Applied Geography, 55, 184–192. https://doi.org/10.1016/j.apgeog.2014.09.011
Tchetchik, a., Fleischer, A., & Shoval, N. (2009). Segmentation of Visitors to a Heritage Site Using High-resolution Time-space Data. Journal of Travel Research, 48(2), 216–229. https://doi.org/10.1177/0047287509332307
Throsby, D. (2017). Culturally sustainable development: theoretical concept or practical policy instrument? International Journal of Cultural Policy, 23(2), 133–147.
Timmermans, H., Arentze, T., & Joh, C.-H. (2002). Analysing space-time behaviour: new approaches to old problems. Progress in Human Geography, 26(2), 175–190. https://doi.org/10.1191/0309132502ph363ra
Urtasun, A., & Gutiérrez, I. (2006). Tourism agglomeration and its impact on social welfare: An empirical approach to the Spanish case. Tourism Management, 27(5), 901–912.
Wang, D., Pedreschi, D., Song, C., Giannotti, F., & Barabasi, A.-L. (2011). Human mobility, social ties, and link prediction. In Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining - KDD ’11 (p. 1100). New York, New York, USA: ACM Press. https://doi.org/10.1145/2020408.2020581
Wolf, J., Guensler, R., & Bachman, W. (2001). Elimination of the travel diary: Experiment to derive trip purpose from global positioning system travel data. Transportation Research Record: Journal of the Transportation Research Board, 1768(1), 125–134.
Xiang, L., Gao, M., & Wu, T. (2016). Extracting Stops from Noisy Trajectories: A Sequence Oriented Clustering Approach. ISPRS International Journal of Geo-Information, 5(3), 29. https://doi.org/10.3390/ijgi5030029
Yu, W., Ai, T., & Shao, S. (2015). The analysis and delimitation of Central Business District using network kernel density estimation. Journal of Transport Geography, 45, 32–47.
Yuan, J., Zheng, Y., & Xie, X. (2012). Discovering regions of different functions in a city using human mobility and POIs. In Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining (pp. 186–194). New York, USA: ACM Press. https://doi.org/10.1145/2339530.2339561
Zhong, C., Schläpfer, M., Müller Arisona, S., Batty, M., Ratti, C., & Schmitt, G. (2017). Revealing centrality in the spatial structure of cities from human activity patterns. Urban Studies, 54(2), 437–455. https://doi.org/10.1177/0042098015601599
Zornoza Gallego, C., & Salom Carrasco, J. (2018). Geolocalized Tweets for assessing daily mobility: methodology to analyse and detect homelocation in the urban area of Valencia. Boletín de La Asociación de Geógrafos Españoles, (79). https://doi.org/10.21138/bage.2464