Kamil Choromański

Abstract

The growing pressure from society on naturally valuable areas means that the entities managing these areas are obliged to implement sustainable development plans that, on the one hand, ensure the preservation of natural values, and on the other hand, meet the needs of local communities and tourists in relation to various forms of recreation. Choosing the optimal strategy for managing naturally valuable areas (e.g. zoning or channeling human traffic) and educating the public to minimize the impact on the ecosystem requires access to objective data. While knowledge about the natural resources of protected areas is extensive and constantly updated, and the dynamics of various processes are monitored, information about the societal mobility in natural areas is rare. In some Polish national parks, permanent traffic monitoring is also absent. An example of such a park is the Kampinos National Park (KPN), located near Poland’s largest city. It is estimated that around 1.5 million people visit the park every year.

Considering the estimated volume of recreational traffic in KPN and the lack of permanent on‑ground monitoring, this study decided utilized available data from the STRAVA portal, covering the period from 2019‑2023, to determine:

1. The spatial distribution of activities by STRAVA users, categorised by activity type: walking, running, and cycling.

2. The traffic volume outside of the linear facilities designated for this purpose by the Director of the National park (marked hiking and cycling trails).

All linear facilities (available and unavailable for tourist traffic) in the KPN area, as recorded in the OpenStreetMap (OSM) database, were analyzed. The data provided by STRAVA was analyzed in detail on an annual basis, broken down by type of activity(running, walking, cycling, electric bicycle). The analysis covered the years 2019‑2023. Maps showing the intensity of use of OSM segments were created, categorized into 10 deciles (deciles 1‑3 indicating low activity level, deciles 4‑6 medium activity level, deciles 7‑9 high activity level, and decile 10 the highest activity level). Daily activity density was also calculated for each basic field activity taking place outside the designated linear objects. Density was calculated using the following formula: Sum (number of activities x object length)/(sum (object lengths) x number of days in the analysis period).

The quantification of linear objects in terms of intensity of use showed that, regardless of activity type (walking, running, cycling), the most intensively used linear objects in the park are located in the eastern part bordering the capital, Warsaw. The highest level of activity (10th decile, i.e. the number of activities in the range 15061‑88305) were recorded on 839 linear objects, 4.9% of which were not open to traffic. Spatial patterns differed among cyclists, walkers and runners. Activities such as walking or running were registered by STRAVA users on 90.6% of the linear objects in the OSM database. No unavailable linear object was used at the highest activity level. Overall, the highest activity level (9481‑13080 activities) was recorded on only 57 linear objects. Cycling was recorded on 96.8% of all OSM linear objects entered into the OSM database. The highest activity (12541‑82275 activities) was recorded on 4.6% of them (37 linear objects). It is clear that STRAVA users in KPN recorded cycling activities much more frequently than walking or running.

This paper presents the possibility of using STRAVA data to map the spatial distribution of traffic on linear objects in KPN. An activity intensity map developed based on actual data on the use of individual facilities can be an important element in supporting decisions related to public access to the park. In the future, quantitative data should be complemented by qualitative research that completes the knowledge of the factors determining the selection of park areas for recreational purposes, the reasons for migration from designated facilities, and societal expectations regarding the development of the recreational park while considering nature conservation. Further work should also focus on creating a model that explains the relationship between STRAVA data volumes and actual use.

Keywords: monitoring, recreation, national park, Volunteered Geographic Information (VGI), running, cycling

Mariusz Ciesielski [m.ciesielski@ibles.waw.pl], Instytut Badawczy Leśnictwa, Zakład Geomatyki
Anna Kębłowska [akeblowska@kampinoski-pn.gov.pl], Kampinoski Park Narodowy
Szymon Jastrzębowski [s.jastrzebowski@ibles.waw.pl], Instytut Badawczy Leśnictwa, Zakład Hodowli Lasu i Genetyki Drzew Leśnych
Jacek Marek [jacekm.kpn@gmail.com], Kampinoski Kolektyw Przewodnicki „ZaPuszczeni”
Kamil Choromański [kamil.choromanski@pw.edu.pl], Politechnika Warszawska, Wydział Geodezji i Kartografii
Tomasz Związek [tzwiazek@twarda.pan.pl], Instytut Geografii i Przestrzennego Zagospodarowania im. Stanisława Leszczyckiego PAN

Citation

APA: Ciesielski, M., Kębłowska, A., Jastrzębowski, S., Marek, J., Choromański, K., & Związek, T. (2024). Analiza przestrzenna aktywności wybranych grup użytkowników Kampinoskiego Parku Narodowego w latach 2019‑2023 na podstawie danych STRAVA. Przegląd Geograficzny, 96(3), 325-349. https://doi.org/10.7163/PrzG.2024.3.2
MLA: Ciesielski, Mariusz, et al. "Analiza przestrzenna aktywności wybranych grup użytkowników Kampinoskiego Parku Narodowego w latach 2019‑2023 na podstawie danych STRAVA". Przegląd Geograficzny, vol. 96, no. 3, 2024, pp. 325-349. https://doi.org/10.7163/PrzG.2024.3.2
Chicago: Ciesielski, Mariusz, Kębłowska, Anna, Jastrzębowski, Szymon, Marek, Jacek, Choromański, Kamil, and Związek, Tomasz. "Analiza przestrzenna aktywności wybranych grup użytkowników Kampinoskiego Parku Narodowego w latach 2019‑2023 na podstawie danych STRAVA". Przegląd Geograficzny 96, no. 3 (2024): 325-349. https://doi.org/10.7163/PrzG.2024.3.2
Harvard: Ciesielski, M., Kębłowska, A., Jastrzębowski, S., Marek, J., Choromański, K., & Związek, T. 2024. "Analiza przestrzenna aktywności wybranych grup użytkowników Kampinoskiego Parku Narodowego w latach 2019‑2023 na podstawie danych STRAVA". Przegląd Geograficzny, vol. 96, no. 3, pp. 325-349. https://doi.org/10.7163/PrzG.2024.3.2