Abstract
The paper deals with evaluation of the quality of public service infrastructure in the city of Kronstadt, the historical part of Saint-Petersburg agglomeration. Public services are considered as FMCG, cultural and recreational venues people use in everyday life. We consider the quality of public services through a set of objective (availability, accessibility, variability) and subjective (users perception) indicators. We measure the quality of public service infrastructure based on the data from open digital sources, such as Technical Passports of Houses from Open Data of Saint-Petersburg Platform, Google Maps, Google Places, and validate usability of services based on a sociological survey. We illustrate our analysis with maps which provide a detailed view on the localization, accessibility, variability of the service infrastructure. We conclude that public service infrastructure in Kronstadt does not address the needs of the dormitory areas which make up one third of all citizens of the city.
Keywords
- Public service infrastructure
- Mapping public services
- Quality of urban environment
- Online data
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References
Jacobs, J.: The Death and Life of Great American Cities. Random House, New York (1961)
Oldenburg, R.: The café as a third place. In: Tjora, A., Scambler, G. (eds.) Café Society, pp. 7–21. Palgrave Macmillan US, New York (2013). https://doi.org/10.1057/9781137275936_2
Montgomery, J.: The story of temple bar: creating Dublin’s cultural quarter. Plann. Pract. Res. 10(2), 135–172 (1995)
Speck, J.: Walkable City: How Downtown Can Save America, One Step at a Time. Farrar, Straus and Giroux, New York (2012)
Aksenov, K.E.: Evolution of the types of shopping and spatial organization of retail trade in the post-Soviet metropolis. Reg. Res. Russ. 6(4), 375–386 (2016). https://doi.org/10.1134/S2079970516040043
Axenov, K.: Retail, services and leisure. In: URBAN EURASIA. Cities in Transformation. DOM Publishers, Berlin (2017)
Rosenbaum, M.: Restorative servicescapes: restoring directed attention in third places. J. Serv. Manage. 20(2), 173–191 (2009)
Al-Barrak, L., Kanjo, E., Younis, E.M.G.: NeuroPlace: categorizing urban places according to mental states. PLoS ONE 12(9), e0183890 (2017)
Dunkel, A.: Visualizing the perceived environment using crowdsourced photo geodata. Landscape Urban Plann. 142, 173–186 (2015)
Jiang, S., Alves, A., Rodrigues, F., Ferreira, J., Pereira, F.C.: Mining point-of-interest data from social networks for urban land use classification and disaggregation. Comput. Environ. Urban Syst. 53, 36–46 (2015)
Boy, J.D., Uitermark, J.: How to study the city on instagram. PLoS ONE 11(6), e0158161 (2016)
Salesses, P., Schechtner, K., Hidalgo, C.A.: The collaborative image of the city: mapping the inequality of urban perception. PLoS ONE 8(7), e68400 (2013)
Agryzkov, T., Mart., P., Tortosa, L., Vicent, J.F.: Measuring urban activities using Foursquare data and network analysis: a case study of Murcia (Spain). Int. J. Geogr. Inf. Sci. 31(1), 1–22 (2016)
Cranshaw, J., Schwartz, R., Hong, J.I., Sadeh, N.: The livehoods project: utilizing social media to understand the dynamics of a city. In: International AAAI Conference on Weblogs and Social Media, p. 58 (2012)
Nenko, A., Koniukhov, A., Petrova, M.: Areas of habitation in the city: improving urban management based on check-in data and mental mapping. In: Chugunov, A., Misnikov, Y., Roshchin, E., Trutnev, D. (eds.) EGOSE 2018. CCIS, vol. 947, pp. 235–248. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-13283-5_18
Nenko, A., Konyukhov, A., Mityagin, S.: Urban data and spatial segregation: analysis of food services clusters in St. Petersburg, Russia. In: Shi, Y., Fu, H., Tian, Y., Krzhizhanovskaya, V.V., Lees, M.H., Dongarra, J., Sloot, P.M.A. (eds.) ICCS 2018. LNCS, vol. 10862, pp. 683–690. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-93713-7_65
Quercia, D., Saez, D.: Mining urban deprivation from Foursquare: implicit crowdsourcing of city land use. IEEE Pervasive Comput. 13(2), 30–36 (2014)
Roberts, H.V.: Using Twitter data in urban green space research: a case study and critical evaluation. Appl. Geogr. 81, 13–20 (2017)
Hamstead, Z.A., Fisher, D., Ilieva, R.T., Wood, S.A., McPhearson, T., Kremer, P.: Geolocated social media as a rapid indicator of park visitation and equitable park access. Comput. Environ. Urban Syst. 72, 38–50 (2018)
Lloyd, A., Cheshire, J.: Deriving retail centre locations and catchments from geo-tagged twitter data. Comput. Environ. Urban Syst. 61, 108–118 (2017)
Bentley, F., Cramer, H., Müller, J.: Beyond the bar: the places where location based services are used in the city. Pers. Ubiquit. Comput. 19(1), 217–223 (2015)
Kelly, J.M., Swindel, D.: Service quality variation across urban space: first steps toward a model of citizen satisfaction. J. Urban Aff. 24(3), 271–288 (2002)
Lee, M., Farzan, R., Butler, B.: This is not just a café: toward capturing the dynamics of urban places. In: The CityLab Workshop in 10th International AAAI Conference on Web and Social Media (ICWSM), pp. 20–25 (2016)
Kronstadt the City of Forts Project. https://www.кpoнштaдт.pф (https://xn-80aiqmelqc4c.xn-p1ai/). Accessed 01 Mar 2020
Open Data of Saint-Petersburg Platform, Technical Passports of Houses. https://data.gov.spb.ru/opendata/7840013199-passports_houses/?search_all=пacпopтa%20мнoгoквapтиpныx%20дoмoв. Accessed 01 Mar 2020
LiveInternet. https://www.liveinternet.ru/stat/ru/index.html. Accessed 01 Mar 2020
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Nenko, A., Belyakova, N., Koniukhov, A. (2020). Evaluating a City’s Public Service Infrastructure Based on Online Data. In: Alexandrov, D.A., Boukhanovsky, A.V., Chugunov, A.V., Kabanov, Y., Koltsova, O., Musabirov, I. (eds) Digital Transformation and Global Society. DTGS 2020. Communications in Computer and Information Science, vol 1242. Springer, Cham. https://doi.org/10.1007/978-3-030-65218-0_25
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DOI: https://doi.org/10.1007/978-3-030-65218-0_25
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