Background | Methods | Outputs | How to get involved | Who we are | Acknowledgements | Keen to read more? 

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Background

The City of Tshwane (CoT), located in the Gauteng Province of South Africa, currently has 19 nature reserves accessible to the public. These reserves function as green spaces where citizens engage in recreational activities, including walking, hiking, and trail running. Physical activity has numerous health benefits, including improved blood and heart circulation, improved fitness and subsequent muscle, bones, and joint strength and flexibility, improved cholesterol levels, weight loss, and improved blood pressure. While trails are delineated for some of the open spaces, none of the current nature reserve maps assign a difficulty level to any of their trails. And while some maps are accessible to the public (either available online at https://www.tshwane.gov.za/?page_id=1201), or given to citizens at entry to the relevant nature reserve, not all open spaces have maps of their boundaries, points of interest, and trails. This impacts how CoT citizens can make best use of these open spaces. For example, have you ever wondered how long and how much energy it takes for you to walk from A to B, such as your weekly walk through your local nature reserve? These days you can easily log your energy expenditure with, for example, a smartwatch, but what if you do not have access to one? Would it not be better if the map of your local nature reserve would show not only the path you wish to take, but also how far it is, how long it should take you to walk it, and how much energy you will expend when you do.

Methods

We are working on a project where we model the expected energy someone would expend when travelling across a surface, i.e., along a path or trail. Our study sites are any of the nature reserves of the CoT. In addition to calculating energy expenditure, we also calculate the average time someone would need to spend to finish a trail and the distance per trail. These parameters are modelled using various algorithms, such as the Modified Hiker function (adapted from Tobler’s Hiker function, see Márquez-Pérez et al., 2017), Epstein’s function (Epstein et al., 1987), and Pandolf’s metabolic rate function (Pandolf et al., 1977), within a Geographic Information System (GIS). Based on modelled results, a grading system adapted from Hugo (1999a, b) is applied to each trail. This grading system is based on e.g., difficulty, time spent, trail gradient, and expected energy expended per trail. Modelled results are verified via fieldwork through the use of Garmin Forerunner 55 and Samsung Galaxy Active2 smartwatches, as well as using Volunteered Geographic Information (VGI) obtained from an online survey (https://arcg.is/D1L950), which is accessible via a QR code; the code is indicated on posters erected throughout the open spaces of the CoT. 

Outputs

Ultimately, we will make maps and infographics available to the public that list the 1) trail distance, 2) average time you will need to walk a trail, 3) average energy expenditure (i.e., what do you need to consume to replace what you expend when walking a trail for females and males), and 4) trail difficulty. The maps will be available in hard copy (at the reserves), and online (via a dynamic online web map) that anyone can access. The idea is to provide more information to the City’s residents on each nature park and its trails. This addresses Sustainable Development Goal (SDG) 11, which aims to “make cities and human settlements inclusive, safe, resilient and sustainable”. Urban green spaces (or open spaces) are used by citizens for recreational purposes, including physical activity. Target 11.7 of this SDG furthermore aims to “provide universal access to safe, inclusive and accessible, green and public spaces, in particular for women and children, older persons and persons with disabilities”. SDG 11, thus, includes making urban spaces accessible and provision for their effective use. The results of this project contribute to better management and decision support for the green spaces of the CoT, in addition to a more informed public. This feeds directly into SDG 11 and Target 11.7, by making cities more sustainable and accessible to their citizens.

The beta map viewer for the project can be viewed here.

How to get involved

Would you like to take part in this study? Then complete our survey every time you go for a walk, hike, or run in any of the city's nature reserves. You can complete our survey here. The project has been passed by the Faculty of Natural and Agricultural Sciences Ethics Board (ethics number NAS160/2021); all answers will be dealt with confidentially and according to the Protection of Personal Information Act (POPI) (Act No. 4 of 2013).

Who we are 

Acknowledgements

The project would not be possible without support from the University of Pretoria via its Research and Development program. The support of the City of Tshwane in providing access to its nature reserves is further gratefully acknowledged, as is the support of Garmin, Garmin Health, and Fitrockr in supporting the project.

Keen to read more?

If this project interests you, have a look at the selected references below. You can also contact us for more information.

• Epstein, Y., Stroschein, L. A., Pandolf, K. B., 1987, Predicting metabolic cost of running with and without backpack loads, European Journal of Applied Physiology, 56, 495-500.
• Hugo, M. L., 1999a, A comprehensive approach towards the planning, grading and auditing of hiking trails as ecotourism products, Current Issues in Tourism, 2(2-3), 138-173.
• Hugo, M. L., 1999b, Energy equivalent as a measure of the difficulty rating of hiking trails, Tourism Geographies, 1(3), 358-373.
• Márquez-Pérez, J., Vallejo-Villalta, I., Álvarez-Francoso, J. I., 2017, Estimated travel time for walking trails in natural areas, Geografisk Tidsskrift-Danish Journal of Geography, 117(1), 53-62.
• Pandolf, K. B., Givoni, B. & Goldman, R.F. 1977. Predicting energy expenditure with loads while standing or walking very slowly,  Journal of Applied Physiology: Respiratory, Environmental and Exercise Physiology, 43(4), 577-581.