Ahtikoski, A., Tuulentie, S., Hallikainen, V., Nivala, V., Vatanen, E., Tyrväinen, L., & Salminen, H. (2011). Potential Trade-Offs Between Nature-Based Tourism and Forestry, a Case Study in Northern Finland. Forests, 2(4), 894–912. https://doi.org/10.3390/f2040894
Crossref
Google Scholar
Allison, P., Westphal, R., Beames, S., & Gibson, J. (2008). Nature first: Outdoor life the Friluftsliv way: Bob Henderson and Nils Vikander, 2007 Toronto, Canada, Natural Heritage Books Can. $32.99, US$26.99, £15.99, 321 pp. ISBN 978-1-897045-21-3 Available from: www. naturalheritagebooks.com. Journal of Adventure Education & Outdoor Learning, 8(2), 159–160. https://doi.org/10.1080/14729670802601766
Crossref
Google Scholar
Almendros-Jiménez, J. M., & Becerra-Terón, A. (2018). Analyzing the Tagging Quality of the Spanish OpenStreetMap. ISPRS International Journal of Geo-Information, 7(8), 323. https://doi.org/10.3390/ijgi7080323
Crossref
Google Scholar
Arsanjani, J., Zipf, A., Mooney, P., & Helbich, M. (2015). An Introduction to OpenStreetMap in Geographic Information Science: Experiences, Research, and Applications. In J. Jokar Arsanjani, A. Zipf, P. Mooney, & M. Helbich (Eds.), OpenStreetMap in GIScience. Lecture Notes in Geoinformation and Cartography (pp. 1–15). Springer International Publishing. https://doi.org/10.1007/978-3-319-14280-7_1
Crossref
Google Scholar
Bełej, M. (2021). Analysis of spatial distribution of touristic accommodation in Poland with the kernel density estimation of POIs. Acta Scientiarum Polonorum. Administratio Locorum, 20(3), 159–171. https://doi.org/10.31648/aspal.6818
Crossref
Google Scholar
Bergsgard, N. A., Bratland-Sanda, S., Giulianotti, R., & Tangen, J. O. (2019). Sport, outdoor life and the Nordic world: An introduction. Sport in Society, 22(4), 515–524. https://doi.org/10.1080/17430437.2017.1390 927
Crossref
Google Scholar
Boers, B., & Cottrell, S. (2007). Sustainable Tourism Infrastructure Planning: A GIS-Supported Approach. Tourism Geographies, 9(1), 1–21. https://doi.org/10.1080/14616680601092824
Crossref
Google Scholar
Brouder, P., & Eriksson, R. H. (2013). Tourism Evolution: On The Synergies Of Tourism Studies And Evolutionary Economic Geography. Annals of Tourism Research, 43, 370–389. https://doi.org/10.1016/j.annals.2013.07.001
Crossref
Google Scholar
Cellmer, R. (2023). Points of Interest and Housing Prices. Real Estate Management and Valuation, 31(1), 69–77.
Crossref
Google Scholar
Cerić, D. (2023). Przestrzenne cechy transgranicznej współpracy turystycznej w regionie Morza Bałtyc¬kiego [Spatial features of cross-border tourist cooperation in the Baltic Sea Region]. Przegląd Geograficzny, 95(1), 85–112. https://doi.org/10.7163/PrzG.2023.1.4
Crossref
Google Scholar
Chang, Y. (2024). The spatial distribution characteristics of functional formats in the historical city of Shaoxing based on POI data. In Urban Construction and Management Engineering IV. CRC Press.
Crossref
Google Scholar
Constantin, D.-L., & Reveiu, A. (2018). A spatial analysis of tourism infrastructure in Romania: Spotlight on accommodation and food service companies. Region, 5(1), 1–16.
Crossref
Google Scholar
Dong, R., Li, S., Zhang, Y., Zhang, N., Wang, T., Tan, X., & Fu, X. (2018). Analysis of urban environmental problems based on big data from the urban municipal supervision and management information system. Ecological Indicators, 94, 52–69.
Crossref
Google Scholar
Dudás, G., Vida, G., Kovalcsik, T., & Boros, L. (2017). A socio-economic analysis of Airbnb in New York City. Regional Statistics, 7(1), 135–151.
Crossref
Google Scholar
Encalada, L., Boavida-Portugal, I., Cardoso Ferreira, C., & Rocha, J. (2017). Identifying Tourist Places of Interest Based on Digital Imprints: Towards a Sustainable Smart City. Sustainability, 9(12), 2317. https://doi.org/10.3390/su9122317
Crossref
Google Scholar
Ervola, A., Mäntymaa, E., & Uusivuori, J. (2024). Public right of access to private land: Examples and considerations. Scandinavian Journal of Forest Research, 39(6), 287–297. https://doi.org/10.1080/02827581.2024.2410348
Crossref
Google Scholar
Fedorov, G., Druzhinin, A., Golubeva, E., Subetto, D., & Palmowski, T. (Eds.). (2020). Baltic Region – The Region of Cooperation. Springer International Publishing. https://doi.org/10.1007/978-3-030-14519-4
Crossref
Google Scholar
Feng, R., & Morrison, A. M. (2002). GIS Applications in Tourism and Hospitality Marketing: A Case in Brown County, Indiana. Anatolia, 13, 127–143. https://doi.org/10.1080/13032917.2002.9687129
Crossref
Google Scholar
Ganter, M., Toetzke, M., & Feuerriegel, S. (2022). Mining Points-of-Interest Data to Predict Urban Inequality: Evidence from Germany and France. Proceedings of the International AAAI Conference on Web and Social Media, 16, 216–227. https://doi.org/10.1609/ICWSM.V16I1.19286
Crossref
Google Scholar
Gänzle, S., & Kern, K. (2016). The European Union Strategy for the Baltic Sea Region. In S. Gänzle & K. Kern (Eds.), A ‘Macro-regional’ Europe in the Making (pp. 123–144). Palgrave Macmillan UK. https://doi.org/10.1007/978-1-137-50972-7_6
Crossref
Google Scholar
Hall, C. M., & Page, S. J. (2009). Progress in Tourism Management: From the geography of tourism to geographies of tourism – A review. Tourism Management, 30(1), 3–16. https://doi.org/10.1016/j.tourman.2008.05.014
Crossref
Google Scholar
Hijmans, R. J. (2024). raster: Geographic Data Analysis and Modeling. https://CRAN.R-project.org/package=raster
Google Scholar
Holden, A. (2004, June 1). Tourism Studies and the Social Sciences. Routledge. https://doi.org/10.4324/9780203502396
Crossref
Google Scholar
IBSR. (2025). Interreg Baltic Sea Region. https://interreg-baltic.eu/about/
Google Scholar
Jia, R., Khadka, A., & Kim, I. (2018). Traffic crash analysis with point-of-interest spatial clustering. Accident Analysis & Prevention, 121, 223–230. https://doi.org/10.1016/j.aap.2018.09.018
Crossref
Google Scholar
Joenniemi, P. (2010). The EU strategy for the Baltic region: Where are we now? Baltic Region, (2). https://doi.org/10.5922/2079-8555-2010-2-4
Crossref
Google Scholar
Kebza, M., Nováček, A., & Popjaková, D. (2019). Socio-economic disparities in the Baltic States: Analytical comparison and categorisation of the Regions. Geographia Polonica, 92(3), 289–307. https://doi.org/10.7163/GPol.0150
Crossref
Google Scholar
Kosov, Yu., & Gribanova, G. (2016). EU Strategy for the Baltic Sea Region: Challenges and Perspectives of International Cooperation. Baltic Region, 8(2), 33–44. https://doi.org/10.5922/2079-8555-2016-2-3
Crossref
Google Scholar
Kozłowska, M. (2016). Issues with classification and categorization of accommodation in Poland and in the EU. European Journal of Service Management, 19, 43–50. https://doi.org/10.18276/ejsm.2016.19-06
Crossref
Google Scholar
Kropinova, E. (2021). Transnational and Cross-Border Cooperation for Sustainable Tourism Development in the Baltic Sea Region. Sustainability, 13(4), 2111. https://doi.org/10.3390/su13042111
Crossref
Google Scholar
Kulawiak, A., Rachwał, T., & Smętkiewicz, K. (2018). The Impact of Infrastructure, Industrial and Housing Investments on the Development of Local Systems Based on the Example of the Uniejów Commune in the Łódź Voivodeship (Poland). Prace Komisji Geografii Przemysłu Polskiego Towarzystwa Geograficznego, 32(3), 69–97.
Crossref
Google Scholar
Leung, R., Vu, H. Q., & Rong, J. (2017). Understanding tourists’ photo sharing and visit pattern at non-first tier attractions via geotagged photos. Information Technology & Tourism, 17(1), 55–74. https://doi.org/10.1007/s40558-017-0078-3
Crossref
Google Scholar
Lim, K. H., Chan, J., Karunasekera, S., & Leckie, C. (2018). Tour Recommendation and Trip Planning Using Location-Based Social Media: A Survey. Knowledge and Information Systems, 60, 1247–1275. https://doi.org/10.1007/s10115-018-1297-4
Crossref
Google Scholar
Łonyszyn, P., & Terefenko, O. (2014). Creation of an alternative season based on sustainable tourism as an opportunity for Baltic Sea Region. Journal of Coastal Research, 70, 454–460. https://doi.org/10.2112/SI70- 077.1
Crossref
Google Scholar
Massicotte, P., & South, A. (2023). rnaturalearth: World Map Data from Natural Earth. https://CRAN.R-project.org/package=rnaturalearth
Google Scholar
Mezhevich, N., Kretinin, G., & Fedorov, G. (2016). Economic and Geographical Structure of the Baltic Sea region. Baltic Region, 8(3), 11–21. https://doi.org/10.5922/2079-8555-2016-3-1
Crossref
Google Scholar
Mondzech, J., & Sester, M. (2011). Quality Analysis of OpenStreetMap Data Based on Application Needs. Cartographica, 46(2), 115–125. https://doi.org/10.3138/carto.46.2.115
Crossref
Google Scholar
Napierała, T., Leśniewska-Napierała, K., & Cotella, G. (2022). Theoretical fundamentals of sustainable spatial planning of European tourism destinations. Contemporary Challenges of Spatial Planning in Tourism Destinations, 7–15.
Crossref
Google Scholar
Niu, H., & Silva, E. A. (2023). Understanding temporal and spatial patterns of urban activities across demographic groups through geotagged social media data. Computers, Environment and Urban Systems, 100, 101934. https://doi.org/10.1016/j.compenvurbsys.2022.101934
Crossref
Google Scholar
Nunna, T. S. P., & Banerjee, A. (2022). Understanding the impact of tourism on spatial growth for sustainable development of tourist destinations through the measure of land use efficiency. UŁ. https://www.ceeol.com/search/article-detail?id=1103857
Crossref
Google Scholar
OpenGovData. (2025). The 8 Principles of Open Government Data. https://opengovdata.org/
Google Scholar
Overpass Turbo. (2025). Overpass Turbo. OpenStreetMap. https://wiki.openstreetmap.org/wiki/Tag:tourism=guest_house
Google Scholar
Palmowski, T. (2021). The European Union Strategy for the Baltic Sea Region and accomplishments. Baltic Region, 13(1), 138–152. https://doi.org/10.5922/2079- 8555-2021-1-8
Crossref
Google Scholar
Pebesma, E. (2018). Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal, 10(1), 439–446. https://doi.org/10.32614/RJ-2018-009
Crossref
Google Scholar
Rodríguez Rangel, M. C., & Sánchez Rivero, M. (2020). Spatial Imbalance Between Tourist Supply and Demand: The Identification of Spatial Clusters in Extremadura, Spain. Sustainability, 12(4), 1651. https://doi.org/10.3390/su12041651
Crossref
Google Scholar
Roman, M., Roman, M., & Niedziółka, A. (2020). Spatial Diversity of Tourism in the Countries of the European Union. Sustainability, 12(7), 2713. https://doi.org/10.3390/su12072713
Crossref
Google Scholar
Rudihartmann. (1986). Tourism, seasonality and social change. Leisure Studies, 5(1), 25–33. https://doi.org/10.1080/02614368600390021
Crossref
Google Scholar
Rula, A., Maurino, A., & Batini, C. (2016). Data Quality Issues in Linked Open Data. In C. Batini & M. Scan¬napieco (Eds.), Data and Information Quality (pp. 87–112). Springer International Publishing. https://doi.org/10.1007/978-3-319-24106-7_4
Crossref
Google Scholar
Santamaria-Granados, L., Mendoza-Moreno, J. F., & Ramirez-Gonzalez, G. (2020). Tourist Recommender Systems Based on Emotion Recognition – A Scientometric Review. Future Internet, 13(1), 2. https://doi.org/10.3390/fi13010002
Crossref
Google Scholar
Seaton, A. (1994). Tourism: The state of the art. https://www.semantic scholar.org/paper/Tourism-%3A-the-state-of-the-art-Seaton/c78c3556ea0d1cc171e0fd1c9f624347124ea9b4
Google Scholar
Silverman, B. W. (1986). Density estimation for statistics and data analysis. Chapman and Hall.
Google Scholar
Spencer, J., & Angeles, G. (2007). Kernel density estimation as a technique for assessing availability of health services in Nicaragua. Health Services and Outcomes Research Methodology, 7(3), 145–157. https://doi.org/10.1007/s10742-007-0022-7
Crossref
Google Scholar
Taylor, K., Lim, K. H., & Chan, J. (2018). Travel itinerary recommendations with must-see points-of-interest. Companion Proceedings of the The Web Conference 2018, 1198–1205.
Crossref
Google Scholar
Tofan, G.-B., Mihalaca, A.-I., & Nitia, A. (2016). The spatial dynamic of the accommodation facility in Maramureș County in the last quarter of a century. GeoJournal of Tourism & Geosites, 18(2). https://search.ebscohost.com/login.aspx?direct=true&pro-file=ehost&scope=site&authtype=crawler&jrn¬l=20650817&AN=119923619&h=uB5KT1jzoiW-886laQc0PcKkYV0d9s9AKTzzG3%2B%2Fdsga6Q5E-De92ZIPr9pTC7BuZnYcU2TpwA1%2FXpDbxS0P¬42CQ%3D%3D&crl=c
Google Scholar
Tritt, R., & Piotrowski, K. (2025). Infrastruktura do birdwatchingu na obszarach jeziornych i podmokłych: Funkcje, typologia i reprezentacja w otwartych bazach danych przestrzennych (przykład OpenStreetMap) [Birdwatching Infrastructure in Lake and Wetland Areas: Functions, Typology, and Representation in Open Spatial Databases (The Case of OpenStreetMap)] (pp. 59–83). Bogucki Wydawnictwo Naukowe. https://doi.org/10.12657/978-83-7986-579-6-3
Crossref
Google Scholar
Vartašová, A., & Červená, K. (2025). Accommodation Tax In The City Of Košice: Initial Stage Of Research. Ekonomia i Prawo, 24(2), 135–160. https://doi.org/10.12775/EiP.2025.08
Crossref
Google Scholar
Vestal, B. E., Carlson, N. E., & Ghosh, D. (2021). Filtering spatial point patterns using kernel densities. Spatial Statistics, 41, 100487. https://doi.org/10.1016/j.spasta.2020.100487
Crossref
Google Scholar
Vetrò, A., Canova, L., Torchiano, M., Minotas, C. O., Iemma, R., & Morando, F. (2016). Open data quality measurement framework: Definition and application to Open Government Data. Government Information Quarterly, 33(2), 325–337. https://doi.org/10.1016/j.giq.2016.02.001
Crossref
Google Scholar
Wei, H., Ji, W., Li, L., Yang, Y., & Liu, M. (2025). Exploring the Equality and Determinants of Basic Educational Public Services from a Spatial Variation Perspective Using POI Data. ISPRS International Journal of Geo-Information, 14(2), 66. https://doi.org/10.3390/ijgi14020066
Crossref
Google Scholar
Wei, J., Zhong, Y., & Fan, J. (2022). Estimating the Spatial Heterogeneity and Seasonal Differences of the Contribution of Tourism Industry Activities to Night Light Index by POI. Sustainability, 14(2), 692. https://doi.org/10.3390/su14020692
Crossref
Google Scholar
Wickham, H. (2016). ggplot2: Elegant Graphics for Data Analysis. Springer-Verlag New York. https://ggplot2.tidyverse.org
Crossref
Google Scholar
Wickham, H., Averick, M., Bryan, J., Chang, W., McGo¬wan, L. D., François, R., Grolemund, G., Hayes, A., Henry, L., Hester, J., Kuhn, M., Pedersen, T. L., Mil¬ler, E., Bache, S. M., Müller, K., Ooms, J., Robinson, D., Seidel, D. P., Spinu, V., … Yutani, H. (2019). Welcome to the tidyverse. Journal of Open Source Software, 4(43), 1686. https://doi.org/10.21105/joss.01686
Crossref
Google Scholar
Wickham, H., François, R., Henry, L., Müller, K., & Vaughan, D. (2023). dplyr: A Grammar of Data Manipulation. https://CRAN.R-project.org/package=dplyr
Google Scholar
Wu, R., Wang, J., Zhang, D., & Wang, S. (2021). Identifying different types of urban land use dynamics using Point-of-interest (POI) and Random Forest algorithm: The case of Huizhou, China. Cities, 114, 103202. https://doi.org/10.1016/j.cities.2021.103202
Crossref
Google Scholar
Yu, W., & Ai, T. (2014). The visualization and analysis of urban facility pois using network kernel density estimation constrained by multi-factors. Boletim de Ciências Geodésicas, 20(4), Article 4. https://revistas.ufpr.br/bcg/article/view/38958
Crossref
Google Scholar
Zhao, M., & Liu, J. (2021). Study on Spatial Structure Characteristics of the Tourism and Leisure Industry. Sustainability, 13(23), 13117. https://doi.org/10.3390/su132313117
Crossref
Google Scholar
Zhu, L., Li, W., Guo, K., Shi, Y., & Zheng, Y. (2017). The Tourism-Specific Sentiment Vector Construction Based on Kernel Optimization Function. Procedia Computer Science, 5th International Conference on Information Technology and Quantitative Management, ITQM 2017, 122, 1162–1167. https://doi.org/10.1016/j.procs.2017.11.487
Crossref
Google Scholar
Žitkus, L. (2013). Integration Of The Baltic Region States: Driving Forces And Obstacles. European Integration Studies, (7), 143–149. http://dx.doi.org/10.5755/j01.eis.0.7.5021
Crossref
Google Scholar