Article

Using mobile phone data to measure and map visitation in Forest Promotional Complex ‘Sudety Zachodnie'
Wykorzystanie danych z telefonów komórkowych do pomiaru i mapowania wizyt w Leśnym Kompleksie Promocyjnym „Sudety Zachodnie”
MARIUSZ CIESIELSKI
Sylwan 166 (10):647-661, 2022
DOI: https://doi.org/10.26202/sylwan.2022071
Available online: 2023-03-03
Open Access (CC-BY)
big data • Forest Promotional Complex • human mobility • mobile phones • monitoring

Abstract
Due to the spatial distribution of forests and their area, there is currently no monitoring of society’s activities in forests on a large scale. However, the high level of interest of spending time in the forest, especially for recreational purposes, makes information about the spatial and temporal distribution of activities in forest areas important. This is especially true since introducing the concept of forests with increased social function in 2022. This forest category will include forests that are intensively used for recreational purposes, in the direct neighbourhood of recre− ation resorts and forests in zones A and B in health resorts. The information on the temporal and spatial distribution of social activities, including its intensity, seems to be an essential element for the correct identification of the aforementioned forest category. Taking the above into account, the aim of the study was to use the data generated by mobile phone users to: i) determine the number of people in forest areas in the Forest Promotional Complex ‘Sudety Zachodnie’ in different time perspectives and spatial scales (the entire area of analysis, forest range and grid); ii) determination of activity hotspots (decile 10=highest intensity); iii) defining the characteristics of visitors (gender, age and sports activity profile); iv) place of residence, divided into inhabitants of the counties within Dolnośląskie voivodeship, other voivodeships and foreign tourists. The main results indicate that in 2019, the research area (22.3 thousand hectares) was visited by over 370,000 unique visitors. The average monthly number of visitors to the research area was 30.8 thousand with the volume of visitors varying every month. The highest number of people was observed in July (48.3 thousand) and June (38.2 thousand), while the lowest was observed in May and November, 13.3 and 18.4 thousand, respectively. The study area was most frequently visited by people aged 30−44 (37%), followed by 45−59 (25%) and 20−29 (26%). Among the visitors, 56% were women whereas 44% were men. The analysis of the place of residence of forest visitors over the whole year showed that 46% of tourists lived in Dolnośląskie voivodeship, 40% in other voivodeships and 14% were foreign tourists. The most visited forest areas were located in the Szronowiec, Czerniawa, Kamieńczyk and Orle forest ranges. Data from mobile phones provided information about visits to forests in the Forest Promotional Complex ‘Sudety Zachodnie’. It should be stated that based on the existing literature that the use and specificity of data from mobile phones for visitors’ monitoring in forest areas can be a valuable source of information.

Literature
Act, 1991. Ustawa o lasach z dnia 28 września 1991 r. Dz.U. 1991 nr 101 poz. 444 (ze zmianami). Available from: https://isap.sejm.gov.pl/isap.nsf/DocDetails.xsp?id=wdu19911010444 [accessed: 10.01.2023].
Arnberger, A., 2006. Recreation use of urban forests: As inter-area comparison. Urban Forestry and Urban Greening, 4: 135-144. DOI: https://doi.org/10.1016/j.ufug.2006.01.004.
Bernetti, I., Chirici, G., Sacchelli, S., 2019. Big data and evaluation of cultural ecosystem services: An analysis based on geotagged photographs from social media in Tuscan forest (Italy). IForest – Biogeosciences and Forestry, 12 (1): 98-105. DOI: https://doi.org/10.3832/ifor2821-011 https://doi.org/10.3832/ifor2821-011.
Cessford, G., Muhar, A., 2003. Monitoring options for visitor numbers in national parks and natural areas. Journal for Nature Conservation, 11 (4): 240-250. DOI: https://doi.org/10.1078/1617-1381-00055.
Ciesielski, M., Stereńczak, K., 2021. Using Flickr data and selected environmental characteristics to analyse the temporal and spatial distribution of activities in forest areas. Forest Policy and Economics, 129: 102509. DOI: https://doi.org/10.1016/j.forpol.2021.102509.
Ciesielski, M., Stereńczak, K., Bałazy, R., 2019. Wykorzystanie danych społecznościowej informacji geograficznej do monitorowania ruchu w przestrzeni leśnej. Sylwan, 163 (1): 80-88. DOI: https://doi.org/10.26202/sylwan.2018107.
Dudek, T., 2017. Rekreacyjne użytkowanie lasu w bilansie rocznym nadleśnictwa a szacunkowa wartość rekreacyjnej funkcji lasów. Sylwan, 161 (9): 748-755. DOI: https://doi.org/10.26202/sylwan.2017081.
Ferster, C., Nelson, T., Laberee, K., Winters, M., 2021. Mapping bicycling exposure and safety risk using Strava Metro. Applied Geography, 127: 102388. DOI: https://doi.org/10.1016/j.apgeog.2021.102388.
Fisher, D.M., Wood, S.A., Roh, Y.H., Kim, C.K., 2019. The geographic spread and preferences of tourists revealed by user-generated information on Jeju Island, South Korea. Land, 8 (5): 73. DOI: https://doi.org/10.3390/land8050073.
Forest Policy, 1997. Polityka leśna państwa. Dokument przyjęty przez Radę Ministrów w dniu 22 kwietnia 1997 r. Ministerstwo Ochrony Środowiska Zasobów Naturalnych i Leśnictwa, Warszawa. Available from: https://www.katowice.lasy.gov.pl/c/document_library/get_file?uuid=506deebb-988d-4665-bcd9-148fcf66ee02&groupId=26676 [accessed: 10.01.2023].
Fox, N., August, T., Mancini, F., Parks, K.E., Eigenbrod, F., Bullock, J.M., Sutter, L., Graham, L.J., 2020. ‘Photosearcher’ package in R: An accessible and reproducible method for harvesting large datasets from Flickr. SoftwareX, 12: 100624. DOI: https://doi.org/10.1016/j.softx.2020.100624.
Ghermandi, A., Sinclair, M., 2019. Passive crowdsourcing of social media in environmental research: A systematic map. Global Environmental Change, 55: 36-47. DOI: https://doi.org/10.1016/j.gloenvcha.2019.02.003.
Gołos, P., 2013. Selected aspects of the forest recreational function in view of its users. Forest Research Papers, 74 (3): 257-272. DOI: https://doi.org/10.2478/frp-2013-0025.
Gołos, P., 2018. Społeczne i ekonomiczne aspekty pozaprodukcyjnych funkcji lasu i gospodarki leśnej – wyniki badania opinii społecznej. Prace Instytutu Badawczego Leśnictwa, Rozprawy i Monografie, 22: 1-326. Available from: https://depot.ceon.pl/handle/123456789/17069 [accessed: 10.01.2023].
Guan, C., Song, J., Keith, M., Akiyama, Y., Shibasaki, R., Sato, T., 2020. Delineating urban park catchment areas using mobile phone data: A case study of Tokyo. Computers, Environment and Urban Systems, 81: 101474. DOI: https://doi.org/10.1016/j.compenvurbsys.2020.101474.
Heikinheimo, V., Tenkanen, H., Bergroth, C., Järv, O., Hiippala, T., Toivonen, T., 2020. Understanding the use of urban green spaces from user-generated geographic information. Landscape and Urban Planning, 201: 103845. DOI: https://doi.org/10.1016/j.landurbplan.2020.103845.
Hołowiecka, B., Grzelak-Kostulska, E., 2013. Atrakcyjność turystyczna lasów w kontekście nowych tendencji i trendów w turystyce. Studia i Materiały Centrum Edukacji Przyrodniczo-Leśnej, 15: 37 (4): 111-117.
IUL, 2012. Instrukcja Urządzania Lasu. Część I. Warszawa: Centrum Informacyjne Lasów Państwowych, 287 pp.
Jalinik, M., 2016. Czynniki decydujące o rozwoju sylwanoturystyki na obszarach leśnych. In: S. Bakier, ed. Turystyka na obszarach przyrodniczo cennych. Hajnówka: Wyd. Zamiejscowy Wydział Leśny Politechniki Białostockiej w Hajnówce, pp. 54-64.
Jiang, S., Ferreira, J., Gonzalez, M.C., 2017. Activity-based human mobility patterns inferred from mobile phone data: A case study of Singapore. IEEE Transactions on Big Data, 3 (2): 208-219. DOI: https://doi.org/10.1109/TBDATA.2016.2631141.
Kienast, F., Degenhardt, B., Weilenmann, B., Wäger, Y., Buchecker, M., 2012. GIS-assisted mapping of landscape suitability for nearby recreation. Landscape and Urban Planning, 105: 385-399. DOI: https://doi.org/10.1016/j.landurbplan.2012.01.015.
Kim, Y.J., Lee, D.K., Kim, C.K., 2020. Spatial tradeoff between biodiversity and nature-based tourism: Considering mobile phone-driven visitation pattern. Global Ecology and Conservation, 21: e00899. DOI: https://doi.org/10.1016/j.gecco.2019.e00899.
Korpilo, S., Virtanen, T., Lehvävirta, S., 2017. Smartphone GPS tracking – Inexpensive and efficient data collection on recreational movement. Landscape and Urban Planning, 157: 608-617. DOI: https://doi.org/10.1016/j.landurbplan.2016.08.005.
Kubo, T., Uryu, S., Yamano, H., Tsuge, T., Yamakita, T., Shirayama, Y., 2020. Mobile phone network data reveal nationwide economic value of coastal tourism under climate change. Tourism Management, 77: 104010. DOI: https://doi.org/10.1016/j.tourman.2019.104010.
Kupfer, J.A., Li, Z., Ning, H., Huang, X., 2021. Using mobile device data to track the effects of the COVID-19 pandemic on spatiotemporal patterns of national park visitation. Sustainability, 13: 9366. DOI: https://doi.org/10.3390/su13169366.
Lupp, G., Kantelberg, V., Förster, B., Honert, C., Naumann, J., Markmann, T., Pauleit, S., 2021. Visitor counting and monitoring in forests using camera traps: A case study from Bavaria (Southern Germany). Land, 10 (7): 736. DOI: https://doi.org/10.3390/land10070736.
Meijels, E.W., de Bakker, M., Groote, P.D., Barske, R., 2014. Analysis hiker movement patterns using GPS data: Implications for park management. Computers, Environmental and Urban Systems, 47: 44-57. DOI: https://doi.org/10.1016/j.compenvurbsys.2013.07.005.
Merrill, N.H., Atkinson, S.F., Mulvaney, K.K., Mazzotta, M.J., Bousquin, J., 2020. Using data derived from cellular phone locations to estimate visitation to natural areas: An application to water recreation in New England, USA. PLOS ONE, 15 (4): e0231863. DOI: https://doi.org/10.1371/journal.pone.0231863.
Miyasaka, T., Oba, A., Akasaka, M., Tosuchiya, T., 2018. Sampling limitations in using tourists’ mobile phones for GPS-based visitor monitoring. Journal of Leisure Research, 49 (3-5): 298-310. DOI: https://doi.org/10.1080/00222216.2018.1542526.
Monz, C., Mitrovich, M., D’Antonio, A., Sisneros-Kidd, A., 2019. Using mobile device data to estimate visitation in parks and protected areas: an example from the nature reserve of orange county, California. Journal of Park and Recreation Administration, 37 (4). DOI: https://doi.org/10.18666/JPRA-2019-9899.
Novak, J., Ahas, R., Aasa, A., Silm, S., 2013. Application of mobile phone location data in mapping of commuting patterns and functional regionalization: A pilot study of Estonia. Journal of Maps, 9 (1): 10-15. DOI: https://doi.org/10.1080/17445647.2012.762331.
Orange, 2022. Article about Orange Lab. Avaible from: https://biuroprasowe.orange.pl/informacje-prasowe/ [accessed: 10.09.2022].
Owuor, I., Hochmair, H.H., 2020. An overview of social media apps and their potential role in geospatial research. ISPRS International Journal of Geo-Information, 9 (9): 526. DOI: https://doi.org/10.3390/ijgi9090526.
Pickering, C., Rossi, S. D., Hernando, A., Barros, A., 2018. Current knowledge and future research directions for the monitoring and management of visitors in recreational and protected areas. Journal of Outdoor Recreation and Tourism, 21: 10-18. DOI: https://doi.org/10.1016/j.jort.2017.11.002.
Pieńkos, K., Kikulski, J., 2005. Produkt sylwaturystyczny – możliwość jego tworzenia, atrakcyjność, potrzeba promocji. In: K. Pieńkos, ed. Konkurencyjność polskiego produktu turystycznego. Warszawa: WSE, pp. 199-207.
Rogowski, M., 2020. Monitoring System of tourist traffic (MSTT) for tourists monitoring in mid-mountain national park, SW Poland. Journal of Mountain Science, 17 (8): 2035-2047. DOI: https://doi.org/10.1007/s11629-019-5965-y.
Selectivv, 2018a. Gdzie w stolicy potrzebne są nowe linie metra? Sprawdziliśmy, jak Warszawiacy poruszają się po mieście. Available from: https://selectivv.com/gdzie-w-stolicy-nowe-linie-metra/ [accessed: 10.01.2023].
Selectivv, 2018b. Wakacje Polaków – co dane z mobile mówią o podróżach międzyregionalnych. Available from: https://selectivv.com/dane-mobile-o-podrozach-miedzyregionalnych/ [accessed: 10.01.2023].
Selectivv, 2020. Wpływ COVID-19 na letni wypoczynek Polaków. Gdzie Polacy pojechali na wakacje? Nasze badania. Available from: https://selectivv.com/wplyw-covid-19-gdzie-polacy-pojechali-na-wakacje/ [accessed: 10.01.2023].
Statistics Poland, 2022. Poland Statistics Database Avaible from: https://bdl.stat.gov.pl/bdl/start [accessed: 10.09.2022].
Taczanowska, K., Bielański, M., González, L.M., Garcia-Massó, X., Toca-Herrera, J., 2017. Analyzing spatial behavior of backcountry skiers in mountain protected areas combining GPS tracking and graph theory. Symmetry, 9 (12): 317. DOI: https://doi.org/10.3390/sym9120317.
Taczanowska, K., Latosińska, B., Czachs, C., Hibner, J., Muhar, A., Brandenburg, C., Rothert, M., 2018. Towards standards for quantification of recreational use in forest areas – indicators and data collection tools applied by the State Forests National Forest Holding, Poland. The 9th International Conference on Monitoring and Management of Visitors in Recreational and Protected Areas (MMV9), 29-31 August 2018, Bordeaux, France, Abstract Book 481-483. Available from https://mmv.boku.ac.at/refbase/files/taczanowska_karolina_latosinska-2018-indicators-forests-poland.pdf [accessed: 05.10.2022].
Teles da Mota, V., Pickering, C., 2020. Using social media to assess nature-based tourism: Current research and future trends. Journal of Outdoor Recreation and Tourism, 30: 100295. DOI: https://doi.org/10.1016/j.jort.2020.100295.
Tenkanen, H., Di Minin, E., Heikinheimo, V., Hausmann, A., Herbst, M., Kajala, L., Toivonen, T., 2017. Instagram, Flickr, or Twitter: Assessing the usability of social media data for visitor monitoring in protected areas. Scientific Reports, 7 (1): 17615. DOI: https://doi.org/10.1038/s41598-017-18007-4.
Toch, E., Lerner, B., Ben-Zion, E., Ben-Gal, I., 2019. Analyzing large-scale human mobility data: asurvey of machine learning methods and applications. Knowledge and Information Systems, 58 (3): 501-523. DOI: https://doi.org/10.1007/s10115-018-1186-x.
Wang, Z., He, S.Y., Leung, Y., 2018. Applying mobile phone data to travel behaviour research: A literature review. Travel Behaviour and Society, 11: 141-155. DOI: https://doi.org/10.1016/j.tbs.2017.02.005.
Wang, Y., Li, J., Zhao, X., Feng, G., Luo, X., 2020. Using mobile phone data for emergency management: A systematic literature review. Information Systems Frontiers, 22 (6): 1539-1559. DOI: https://doi.org/10.1007/s10796-020-10057-w.
Ważyński, B., 1997. Urządzanie i zagospodarowanie lasu dla potrzeb turystyki i rekreacji. Poznań: Wyd. Akademii Rolniczej w Poznaniu, 146 pp.
Willberg, E. S., Tenkanen, H., Poom, A., Salonen, M., Toivonen, T., 2021. Comparing spatial data sources for cycling studies – a review [Preprint]. SocArXiv. DOI: https://doi.org/10.31235/osf.io/ruy3j.
Xu, H., Zhao, J., 2022. Planning urban internal transport based on cell phone data. Applied Sciences, 12 (17): 8433. DOI: https://doi.org/10.3390/app12178433.
Zarządzenie, 2004. Zarządzenie nr 61 Dyrektora Generalnego Lasów Państwowych z dnia 14 października 2004 r. w spra-wie Leśnego Kompleksu Promocyjnego „Sudety Zachodnie”. Available from: https://www.lasy.gov.pl/pl/informacje/zamowienia-publiczne-zarzadzenia-decyzje/copy_of_zarzadzenia-i-decyzje-do-19-stycznia-2010-r/1981_2004/z61-2004 [accessed: 10.01.2023].
Zarządzenie, 2022. Zarządzenie nr 58 Dyrektora Generalnego Lasów Państwowych z dnia 5 lipca 2022 r. w sprawie wprowadzenia „Wytycznych do zagospodarowania lasów o zwiększonej funkcji społecznej na gruntach w zarządzie Lasów Państwowych”. Available from: https://www.gov.pl/web/dglp/zarzadzenia-i-decyzje [accessed: 10.01.2023].
ZHL, 2012. Zasady Hodowli Lasu. Warszawa: Centrum Informacyjne Lasów Państwowych, 72 pp.