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Cited by 15Human Mobility and Location-Based AnalysisUrban Transport and AccessibilitySports Performance and Training

The DOI matches its Crossref record; 17 of the 17 references it cites were found in a registry or an index; 1 of the 29 sources its claims cite were checked for support.

Improved prediction of hiking speeds using a data driven approach

Open access
Wood, Andrew, Mackaness, William, Simpson, T. Ian, Armstrong, J. Douglas·2023·PLOS One
DOI 10.1371/journal.pone.0295848PMC PMC10727444
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Abstract

Hikers and hillwalkers typically use the gradient in the direction of travel (walking slope) as the main variable in established methods for predicting walking time (via the walking speed) along a route. Research into fell-running has suggested further variables which may improve speed algorithms in this context; the gradient of the terrain (hill slope) and the level of terrain obstruction. Recent improvements in data availability, as well as widespread use of GPS tracking now make it possible to explore these variables in a walking speed model at a sufficient scale to test statistical significance. We tested various established models used to predict walking speed against public GPS data from almost 88,000 km of UK walking / hiking tracks. Tracks were filtered to remove breaks and non-walking sections. A new generalised linear model (GLM) was then used to predict walking speeds. Key differences between the GLM and established rules were that the GLM considered the gradient of the terrain (hill slope) irrespective of walking slope, as well as the terrain type and level of terrain obstruction in off-road travel. All of these factors were shown to be highly significant, and this is supported by a lower root-mean-square-error compared to existing functions. We also observed an increase in RMSE between the GLM and established methods as hill slope increases, further supporting the importance of this variable.

Overview

AI snapshot

Written from the paper’s full text.

TL;DR

The paper builds a data-driven generalised linear model of hiking speed using almost 88,000 km of UK GPS tracks, adding hill slope and terrain obstruction to the usual walking-slope variables. The new model improves short-section speed predictions over Naismith, Tobler, and Campbell et al., though whole-route time errors remain similar across methods.

Key findings

  • The final GLM included walking slope, hill slope, and terrain obstruction/road type; all were highly significant, and the model had lower RMSE than existing functions: 1.10 vs 1.27 for Naismith, 1.24 for Tobler, and 1.26 for Campbell et al.
  • Average percentage error for individual 50 m sections was 23.68% for the new model, compared with 26.36% (Naismith), 26.17% (Tobler), and 25.33% (Campbell et al.); R² was 0.09 for the new model versus negative values for the existing methods.
  • Terrain obstruction mattered: a 10 cm vegetation cutoff for “heavy obstruction” could reduce walking speed by more than 0.5 km/h, and the paper states up to 0.6 km/h.
  • For complete routes, all models had an average percentage error of 13.5%–15.5%, suggesting section-level improvements did not translate into better whole-route time estimates.

Methods

  • GPS tracks were obtained from Hikr.org and OpenStreetMap for UK hikes, then filtered to remove breaks and non-walking sections. The final modelling dataset contained 7,636 GPS tracks from England and Wales, with over 1.4 million data points and almost 88,000 km of travel; each point represented at least 50 m of travel (mean 60.3 m).
  • Elevation and walking slope were calculated using Ordnance Survey Terrain 5 DTM; hill slope used the quadratic surface method. Road type was classified from OSM within a 50 m radius, and terrain obstruction was calculated from lidar DSM–DTM differences, with heavy obstruction defined as >10 cm.
  • The selected model was a GLM of the form v = exp(a + bφ + cθ + dθ²), where φ is hill slope and θ is walking slope, with terrain obstruction and road type as factors/interactions. Variables were tested with the Wald test, models compared using 10-fold cross-validation, and performance assessed with percentage error, MSE, RMSE, and R².

Limitations

  • The paper states that crowdsourced GPS data meant no control over data collection, so bias from group size, ability, composition, weather, and other individual factors could not be modelled; filtering choices had no ground truth, and obstruction was calculated crudely from height at each GPS point.
  • The paper also notes uncertainty in road classification due to GPS drift and map error, likely overclassification of tracks on roads, and reduced off-road data; data came only from “walkable” regions, with sparse data on steep slopes and no ability to determine obstruction levels that make walking impossible.
  • Evident from the text: the model’s R² is very low (0.09), and whole-route prediction errors were similar across all methods, indicating limited explanatory power for individual variation and route-level time prediction.

Model-written summary. Check it against the paper before relying on it.

Integrity signals

Registry

Crossref · 10.1371/journal.pone.0295848

Cites

17 of 17 references verified0 citation errors · 0 not checkable

Statistics

Nothing to recompute.

Verification

Claims the paper makes

1 of 29 cited sources checked · 1 supported · 0 flagged

  • Findingown data

    Within the Hikr dataset, some segments were clearly driving to or from the hike location based on observed speeds.

    “While the Hikr dataset consisted of tracks which were tagged as a walk or hike, within some of these there were segments where it was clear that the participant was driving to or from the hike location, based on the observed speeds.”
    Quote in the paperSubstantial claim
  • Findingown data

    Exploration of the lidar data showed a clear drop in walking speeds once the height of an obstruction was greater than 10 cm, beyond which the speed was relatively constant.

    “Exploration of the lidar data (see S5 File) showed that there was a clear drop in walking speeds once the height of an obstruction was greater than 10 cm, beyond which the speed was relatively constant.”
    Quote in the paperSubstantial claim
  • Findingown data

    Of the off-road data (~2,900 km, spread across over 1,200 tracks), over 2,000 km had lidar data available.

    “Of our off-road data (∼2,900 km, spread across over 1,200 tracks), over 2,000 km had lidar data available.”
    Quote in the paperNot a substantial claim
  • Findingown data

    Analysis showed that walking speeds in Scotland were at the extreme end of what is seen throughout the rest of the UK.

    “Furthermore, analysis showed that that walking speeds in Scotland were at the extreme end of what is seen throughout the rest of the UK (see S4 File).”
    Quote in the paperSubstantial claim
  • Findingown data

    Visual inspection of the tracks showed that a large number contained long breaks which could impact the accuracy of a walking speed model.

    “Visual inspection of the tracks showed that a large number contained long breaks which could impact the accuracy of a walking speed model.”
    Quote in the paperSubstantial claim
  • Probably not a substantial claim. 38
  • It may state two separate claims as one. 45
  • The quote only partly states this claim. 2

  • Probably not a substantial claim. The paper’s conclusions may not depend on it.

    Premisecitation

    Previous research has found that most walking takes place on low walking slopes.

    “Previous research has found that most walking takes place on low walking slopes [33], and this is evidenced by our data (∼98% of our data was from walking slopes of under 10 degrees).”
    Quote in the paperNot a substantial claim1 of 1 sources checked
    • cites [33] DR Proffitt, 1995, Perceiving geographical slant, Psychonomic Bulletin & Review source

  • It may state two separate claims as one.

    Findingown data

    The OSM data was not filtered by transport type and contained a large number of tracks clearly from faster modes of transport, with speeds implausible for a hiker.

    “The OSM data, on the other hand, was not filtered by transport type. There were a large number of tracks which were clearly from faster modes of transport, as their speed was implausible for a hiker.”
    Quote in the paperSubstantial claim

  • It may state two separate claims as one.

    Findingown data

    The final modelling dataset consisted of 7,636 GPS tracks from England and Wales, with over 1.4 million individual data points and almost 88,000 km of travel.

    “Our final modelling dataset consisted of 7,636 GPS tracks from England and Wales, with over 1.4 million individual data points and almost 88,000 km of travel.”
    • Also stated in: § Results · plain
      “This process included iterative data cleaning to remove erroneous or non-walking data and identify/remove breaks (e.g. Fig 2) to give us a final usable dataset containing 7,636 GPS tracks, with over 1.4 million individual data points and covering almost 88,000 km of travel in the U.K.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.

    Findingown data

    Each data point represents at least 50 m of travel, with a mean distance of 60.3 m.

    “Each data point represents at least 50 m of travel (with a mean distance of 60.3 m), and the breakdown of the data by slope angle and terrain type is shown in Table 1.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim. The paper’s conclusions may not depend on it.

    Findingown data

    Our data shows that approximately 98% of data was from walking slopes under 10 degrees.

    “Previous research has found that most walking takes place on low walking slopes [33], and this is evidenced by our data (∼98% of our data was from walking slopes of under 10 degrees).”
    Quote in the paperNot a substantial claim

  • It may state two separate claims as one.

    Findingnone given

    Lidar data at 2 m resolution covered large areas of England and Wales, but coverage was not complete.

    “We had access to lidar data at 2 m resolution covering large areas of England and Wales, but the coverage was not complete.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim. The paper’s conclusions may not depend on it.

    Findingown data

    The final values for a, b, c and d are given in Table 2 for each of the terrain obstruction levels and road types.

    “The final values for a, b, c and d are given in Table 2 for each of the terrain obstruction levels and road types.”
    Quote in the paperNot a substantial claim

  • It may state two separate claims as one.

    Findingown data

    The final model was a Generalised Linear Model (GLM), chosen as it was the simplest of those tested, with no evidence that a more complex model would be superior.

    “Cross-validation methods showed that there was very little difference in performance of the best models, therefore the final model was a Generalised Linear Model (GLM), which was chosen as it was the simplest of those tested (we had no evidence that a more complex model would be superior).”
    Quote in the paperSubstantial claim

  • It may state two separate claims as one.

    Findingown data

    The model presented here requires the same tuning as existing methods but provides a more accurate population average walking speed across a wide range of terrain and slope conditions.

    “The model presented here requires the same tuning as these existing methods but provides more a more accurate population average walking speed across a wide range of terrain and slope conditions.”
    Quote in the paperSubstantial claim

  • It may state two separate claims as one.

    Findingown data

    The new model does this better than existing models, evidenced by improved RMSE.

    “and does this better than existing models (evidenced by the improved RMSE).”
    Quote in the paperSubstantial claim

  • It may state two separate claims as one.

    Findingown data

    Existing algorithms perform quite well against the dataset but tend to overestimate ascent time, underestimate descent time, and most ignore terrain obstruction and hill slope.

    “We found that the existing algorithms perform quite well against the dataset but they tend to overestimate ascent time, underestimate descent time and most ignore terrain obstruction and hill slope”
    Quote in the paperSubstantial claim

  • It may state two separate claims as one.

    Findingown data

    For individual 50 m sections, the new model had lower RMSE and percentage error, and higher R squared, than existing models.

    “the predicted speeds for individual 50 m sections had a lower RMSE and percentage error, and a higher R squared value using our new model than in the existing ones.”
    Quote in the paperSubstantial claim

  • It may state two separate claims as one.

    Findingown data

    Naismith's rule consistently overestimates walking speeds when descending a slope, and underestimates speeds when climbing a slope.

    “Naismith’s rule consistently overestimates walking speeds when descending a slope, and underestimates speeds when climbing a slope.”
    Quote in the paperSubstantial claim

  • It may state two separate claims as one.

    Findingown data

    The method proved successful, and a clear difference in walking speeds between areas of light and heavy obstruction was observed.

    “While this did prove to be successful, and we observed a clear difference in walking speeds between areas of light and heavy obstruction (see S5 File)”
    Quote in the paperSubstantial claim

  • It may state two separate claims as one.

    Findingown data

    Naismith's rule and Tobler's hiking function consistently overestimate walking speed when traversing a slope, because they do not take into account the impact of hill slope on reducing walking speeds.

    “both Naismith’s rule and Tobler’s hiking function consistently overestimate the walking speed when traversing a slope, as they do not take into account the impact that the hill slope has on reducing walking speeds.”
    Quote in the paperSubstantial claim

  • It may state two separate claims as one.

    Findingown data

    The error in predictions of the new model increases as the hill slope increases, though the RMSE is generally lower than seen in existing models.

    “The error in predictions of our new model does increase as the hill slope increases, though the RMSE is generally lower than seen in the existing models.”
    Quote in the paperSubstantial claim

  • It may state two separate claims as one.

    Findingown data

    For Tobler's and Campbell et al.'s functions, the shape of the walking slope component is relatively similar to the new model, with the main distinction being the peak predicted speed on flat ground.

    “For both Tobler’s and Campbell et al.’s functions, the shape of the walking slope component is relatively similar to our new model, with the main distinction being the peak predicted speed on flat ground.”
    Quote in the paperNot a substantial claim

  • The quote only partly states this claim.

    Findingown data

    The authors used the data to derive a new model that takes into account walking slope, hill slope, and terrain obstruction.

    “We used the data to derive a new model that takes into account these variables.”
    Quote in the paperSubstantial claim

  • The quote only partly states this claim.

    Findingcitation

    The final GLM included all three variables suggested by Arnet: hill slope, walking slope, and terrain obstruction level.

    “This final GLM model included all three of the variables suggested by Arnet [12]: (1) v=exp(a+bφ+cθ+dθ²)”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [12] F Arnet, 2009, Arithmetical Route Analysis with examples of the long final courses of the World Orienteering Championships 2003 in Switzerland and 2005 in Japan, Scientific Journal of Orienteering

  • It may state two separate claims as one.

    Findingown data

    Within the flat and mild slope region, the new model consistently has a lower RMSE than existing functions and a mean residual error close to 0 km/h.

    “Within this region our model consistently has a lower RMSE than the existing functions, and a mean residual error close to 0 km/h.”
    Quote in the paperSubstantial claim

  • It may state two separate claims as one.

    Findingown data

    Both existing models consistently underestimate walking speeds when traversing a slope, unlike the new model which has a mean residual of less than 0.4 km/h on slopes of up to 35 degrees.

    “Both of these existing models also consistently underestimate walking speeds when traversing a slope, unlike our new model which has a mean residual of less than 0.4 km/h on slopes of up to 35 degrees.”
    Quote in the paperSubstantial claim

  • It may state two separate claims as one.

    Findingown data

    On the steepest hill slopes, the new model appears to perform less well than existing ones, though only 0.2% of off-road data occurred on a hill slope steeper than 40 degrees.

    “On the steepest hill slopes our model appears to perform less well than the existing ones, though only 0.2% of our off-road data occurred on a hill slope steeper than 40 degrees.”
    Quote in the paperNot a substantial claim

  • It may state two separate claims as one.

    Findingown data

    The model provides more accurate walking speeds than existing methods in all scenarios, and particularly in off-road regions.

    “We demonstrated that the model provides more accurate walking speeds than the existing methods in all scenarios, and particularly in off-road regions.”
    Quote in the paperSubstantial claim

  • It may state two separate claims as one.

    Findingown data

    Terrain obstruction and hill slope are significant factors.

    “both of which we found to be significant factors.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.

    Findingown data

    These tracks recorded a variety of transport methods and required significant filtering.

    “These tracks recorded a variety of transport methods and required significant filtering.”
    Quote in the paperNot a substantial claim

  • It may state two separate claims as one.

    Findingown data

    The new model does not suffer from the problems of Naismith's rule, with both a lower RMSE and lower absolute mean residual value across all walking slopes.

    “Our new model does not suffer from these problems, with both a lower RMSE and lower absolute mean residual value across all walking slopes.”
    Quote in the paperSubstantial claim

  • It may state two separate claims as one.

    Findingown data

    None of the existing functions account for the hill slope, which leads to large disparities when predicting walking speed for slope traversals.

    “None of the existing functions account for the hill slope, which leads to large disparities when predicting the walking speed for slope traversals.”
    Quote in the paperSubstantial claim

  • It may state two separate claims as one.

    Findingown data

    Data from tracks confirms that each of walking slope, hill slope, and terrain type or obstruction are significant factors in determining walking speeds.

    “Data from tracks confirms that each of the walking slope, the hill slope and the terrain type or obstruction are significant factors in determining walking speeds.”
    Quote in the paperSubstantial claim

  • It may state two separate claims as one.

    Findingown data

    The critical gradient for this model is between 14-16 degrees when walking uphill and -16 to -18 degrees when walking downhill, depending on road and obstruction conditions, which is in line with previous findings.

    “The critical gradient for this model is between 14—16 degrees when walking uphill and -16 − -18 degrees when walking downhill (depending on road and obstruction conditions), which is in line with previous findings.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim. The paper may give no reason why it holds.

    Premisenone given

    Traversing on a steep hill while maintaining constant elevation is more difficult than traversing flat ground.

    “Experience tells us that traversing on a steep hill (while maintaining constant elevation) is more difficult than traversing flat ground.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim. The paper’s conclusions may not depend on it.

    Premisecitation

    A factor of 0.6 is applied to Tobler's calculated speed for all off-road travel.

    “In a similar manner to Aitken’s correction, a factor of 0.6 is applied to the calculated speed for all off-road travel.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [7] W Tobler, 1993, Three Presentations on Geographical Analysis and Modelling, National Center for Geographic Information and Analysis Technical Report

  • Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.

    Premisecitation

    Wood and Schmidtlein took all three of Arnet's factors into account, applied Tobler's function to both hill slopes and walking slopes, and calculated terrain obstruction coefficients based on energy usage rather than walking speed.

    “Wood and Schmidtlein [13], took all three of Arnet’s factors into account, and looked at evacuating citizens in the event of a hurricane. They applied Tobler’s function to both the hill slopes and walking slopes, and calculated the terrain obstruction coefficients based on energy usage rather than walking speed (using [14]).”
    Quote in the paperNot a substantial claim0 of 2 sources checked
    • cites [13] NJ Wood, 2012, Anisotropic path modeling to assess pedestrian-evacuation potential from Cascadia-related tsunamis in the US Pacific Northwest, Natural Hazards source

      Checked before — its earlier verdict is held back until a new check runs.

    • cites [14] RG Soule, 1972, Terrain coefficients for energy cost prediction, Journal of Applied Physiology source

  • Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.

    Premisecitation

    Tobler's function gives a speed of 5 km/h on flat ground, with a maximum speed of 6 km/h on a mild descent around 3 degrees.

    “Like Naismith’s rule, this gives a speed of 5 km/h on flat ground, with a maximum speed of 6 km/h on a mild descent (around 3 degrees).”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [7] W Tobler, 1993, Three Presentations on Geographical Analysis and Modelling, National Center for Geographic Information and Analysis Technical Report

  • Probably not a substantial claim.

    Premisecitation

    Research into fell-running suggested that movement velocity may depend on obstruction, walking slope, and hill slope.

    “When exploring speeds of fell-runners, Arnet [12] suggested that movement velocity may be dependent on three factors: obstruction (with different factors applied depending on the kind of obstruction), ascent in the run direction (walking slope) and slope of the terrain (hill slope).”
    • Also stated in: § Abstract · hedged
      “Research into fell-running has suggested further variables which may improve speed algorithms in this context; the gradient of the terrain (hill slope) and the level of terrain obstruction.”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [12] F Arnet, 2009, Arithmetical Route Analysis with examples of the long final courses of the World Orienteering Championships 2003 in Switzerland and 2005 in Japan, Scientific Journal of Orienteering

  • Probably not a substantial claim. The paper may give no reason why it holds.

    Premisenone given

    All of the studies mentioned above utilised relatively small sample sizes.

    “All of the studies mentioned above utilised relatively small sample sizes.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim. The paper’s conclusions may not depend on it.

    Premisecitation

    Aitken introduced a reduced base movement speed of 4 km/h on surfaces which are not paths or roads.

    “This was later adjusted by Aitken [6], who introduced a reduced base movement speed of 4 km/h on surfaces which are not paths or roads.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [6] Aitken R. Wilderness areas in Scotland; 1977.

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  • Probably not a substantial claim. The paper may give no reason why it holds.

    Premisenone given

    High levels of terrain obstruction in off-road areas are much more difficult to walk through than empty fields.

    “Similarly, high levels of terrain obstruction in off-road areas (such as a thick gorse bush) are much more difficult to walk through than empty fields.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim. It may state two separate claims as one.

    Study design and conductreasoning

    All OSM track segments within Scotland were excluded from further processing, and Hikr tracks tagged as taking place in Scotland and fully taking place in Scotland were excluded.

    “All OSM track segments which took place within Scotland were excluded from further processing. Similarly Hikr tracks which were tagged as taking place in Scotland, and which fully took place in Scotland were excluded.”
    Quote in the paperSubstantial claim

  • It may state two separate claims as one.

    Premisecitation

    Both [8] and [16] looked solely at the effect of walking slope on speed and did not explore additional variables.

    “Finally, although these studies had the benefit of using large sample sizes, they both looked solely at the effect of the walking slope on speed, and did not explore additional variables.”
    Quote in the paperSubstantial claim0 of 2 sources checked
    • cites [8] MJ Campbell, 2022, Predicting the variability in pedestrian travel rates and times using crowdsourced GPS data, Computers, Environment and Urban Systems source
    • cites [16] MJ Campbell, 2019, Using crowdsourced fitness tracker data to model the relationship between slope and travel rates, Applied Geography source

  • Probably not a substantial claim. The paper’s conclusions may not depend on it.

    Premisecitation

    Naismith's rule calculates walking time as an hour for every three miles on the map, with an additional hour for every 2,000 feet of ascent.

    “an hour for every three miles on the map, with an additional hour for every 2,000 feet of ascent.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [5] WW Naismith, 1892, Cruach Ardran, Stobinian, and Ben More, Scottish Mountaineering Club Journal

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  • It may state two separate claims as one.

    Interpretationreasoning

    5 m/s (18 km/h) is much higher than the maximum predicted speeds from existing methods such as Naismith's rule, so it is likely some non-walking data remained in Campbell et al.'s data.

    “However, 5 m/s (18 km/h) is much higher than the maximum predicted speeds from existing methods (such as Naismith’s rule), so it is likely some non-walking data remained.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.

    Premisereasoning

    Naismith's rule approximates to a walking speed of 5 km/h with 10 minutes added for every 100 m of ascent.

    “This approximates to a walking speed of 5 km/h with 10 minutes added on for every 100 m of ascent.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim. It may state two separate claims as one.

    Premisenone given

    Tobler's function predicts a sharp peak in walking speed on mild descents, which may be unrealistic.

    “Tobler’s function avoids the issues seen in Naismith’s rule when descending slopes, but it predicts a sharp peak in walking speed on mild descents, which may be unrealistic.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim.

    Study design and conductreasoning

    A process to remove non-walking tracks and segments was created, using known Hikr walking segments to create filtering bounds of plausible walking speeds applied to the remainder of the dataset.

    “A process to remove these non-walking tracks and segments was created, whereby the known Hikr walking segments were used to create filtering bounds of plausible walking speeds, which could then be applied to the remainder of the dataset.”
    Quote in the paperSubstantial claim

  • It may state two separate claims as one.

    Premisecitation

    Campbell, Dennison, and Butler conducted a study using lidar data to explore the effects of ground roughness and vegetation density on firefighter evacuation speeds, but did not consider hill slope separately.

    “Campbell, Dennison, and Butler [15] conducted a study using lidar data to explore the effects of ground roughness and vegetation density on firefighter evacuation speeds, but they did not consider the hill slope separately.”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [15] MJ Campbell, 2017, A LiDAR-based analysis of the effects of slope, vegetation density, and ground surface roughness on travel rates for wildland firefighter escape route mapping, International Journal of Wildland Fire source

  • Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.

    Interpretationreasoning

    The model developed here does not seek to model individual effects and would still require tuning based on personal ability or conditions.

    “As with the existing methods, this model did not seek to model individual effects, and would still require tuning based on personal ability or conditions.”
    Quote in the paperNot a substantial claim
    • Rests on an assumption: Most individual effects cannot be modelled without considerable prior knowledge about the person who is planning a route.

  • Probably not a substantial claim.

    Premisecitation

    Campbell et al. attempted to overcome non-walking data in [8] by only considering data points with a speed between 0.2 m/s and 5 m/s.

    “Campbell et al. attempted to overcome this in [8] by only considering data points with a speed between 0.2 m/s and 5 m/s (and the resulting model is shown in Fig 1).”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [8] MJ Campbell, 2022, Predicting the variability in pedestrian travel rates and times using crowdsourced GPS data, Computers, Environment and Urban Systems source

  • It may state two separate claims as one.

    Premisereasoning

    Recent work [8,16] explored data-driven walking speed modelling, but crowdsourced data collection was not controlled, so the data could not be assumed to consist wholly of walking or hiking tracks.

    “This has been explored in recent work [8, 16], however the crowdsourced nature of these studies meant that data collection was not controlled, and thus that the data could not be assumed to consist wholly of walking or hiking tracks.”
    Quote in the paperSubstantial claim0 of 2 sources checked
    • cites [8] MJ Campbell, 2022, Predicting the variability in pedestrian travel rates and times using crowdsourced GPS data, Computers, Environment and Urban Systems source
    • cites [16] MJ Campbell, 2019, Using crowdsourced fitness tracker data to model the relationship between slope and travel rates, Applied Geography source

  • It may state two separate claims as one.

    Premisereasoning

    The rise in GPS tracking means a data-driven approach to modelling walking speed is now possible, providing access to GPS tracks from a wide variety of regions and terrains and enabling tracks to be broken into individual sections for higher spatio-temporal resolution.

    “However, the rise in use of global navigation satellite systems (GNSS), more frequently referred to as GPS tracking, means that a data-driven approach to modelling walking speed is now possible, which provides two main benefits. Firstly, it is possible to access GPS tracks from a wide variety of regions and terrains. Secondly, each track can easily be broken down into individual sections, enabling”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim.

    Study design and conductnone given

    Datapoints in the original GPS track under 50 m in length were merged together to minimise the effects of errors in the GPS location values.

    “Where the datapoints in the original GPS track were under 50 m in length, they were merged together to minimise the effects of errors in the GPS location values.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim. The paper’s conclusions may not depend on it.

    Premisecitation

    Tobler's hiking function is W=6*exp(-3.5|S+0.05|), where W is velocity in km/h and S is gradient of slope.

    “An alternative hiking function proposed by Tobler [7], has become more popular in recent research and other situations where speeds do not need to be calculated by hand: W=6*exp(-3.5|S+0.05|),”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [7] W Tobler, 1993, Three Presentations on Geographical Analysis and Modelling, National Center for Geographic Information and Analysis Technical Report

  • Probably not a substantial claim. It may be too vague to check against evidence. The paper’s conclusions may not depend on it.

    Study design and conductreasoning

    The choice of filtering methods will have had an impact on the dataset and subsequent model.

    “the choice of filtering methods will have had an impact on the dataset and subsequent model”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim. It may be too vague to check against evidence. The paper’s conclusions may not depend on it. The paper may give no reason why it holds. It may state two separate claims as one.

    Interpretationnone given

    Knowledge of how hill slope reduces walking speeds, or that 10 cm of vegetation can reduce walking speeds by up to 0.6 km/h, may affect route choices made when out on a walk.

    “Similarly, the knowledge of how the hill slope reduces walking speeds, or that just 10 cm of vegetation can reduce walking speeds by up to 0.6 km/h may well affect route choices made when out on a walk.”
    Quote in the paperNot a substantial claim

  • It may state two separate claims as one.

    Interpretationreasoning

    By providing improved walking speed predictions in off-road regions, the authors have enabled more accurate calculations of the fastest route to or from any given location, which could save minutes in an emergency situation.

    “By providing improved walking speed predictions in these off-road regions, we have enabled more accurate calculations of the fastest route to or from any given location, which could save minutes in an emergency situation where every second is important.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim. The paper’s conclusions may not depend on it.

    Interpretationreasoning

    The authors suspect they were likely overclassifying tracks on roads.

    “We suspect that we were likely overclassifying tracks on roads.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim. The paper’s conclusions may not depend on it.

    Interpretationreasoning

    It is unclear whether the lack of data on steeper regions is a result of steep slopes being relatively rare, or that they cannot be easily navigated, so hikers chose an alternate path.

    “it is unclear whether the lack of data on steeper regions is a result of steep slopes being relatively rare, or that they cannot be easily navigated, so hikers chose an alternate path.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim. The paper’s conclusions may not depend on it.

    Study design and conductreasoning

    Inaccuracies present within GPS data may have led to some erroneous obstruction measurements.

    “the inaccuracies present within GPS data may have led to some erroneous obstruction measurements”
    Quote in the paperNot a substantial claim

  • It may state two separate claims as one.

    Interpretationreasoning

    Naismith's rule and other existing functions are still a good rule of thumb to calculate route times as a whole, but time estimates for individual sections of a route will be less accurate than when using the new model.

    “The results here suggest that Naismith’s rule, and other existing functions, are still a good rule of thumb to calculate route times as a whole, but time estimates for individual sections of a route will be less accurate than when using the new model found here.”
    Quote in the paperSubstantial claim

  • It may state two separate claims as one.

    Interpretationown data

    The average error in the new model increases as the hill slope increases, due to limited volumes of data at high hill slopes.

    “We do see that the average error in our model increases as the hill slope increases, but we believe that this is due to limited volumes of data at high hill slopes”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim. The paper’s conclusions may not depend on it.

    Study design and conductreasoning

    Variables within the model were tested for significance using the Wald test, which accounts for correlation between points within the same track.

    “Variables within the model were tested for significance using the Wald test, which allows us to account for correlation between points within the same track (coeftest function within lmtest package in R).”
    Quote in the paperNot a substantial claim

  • It may state two separate claims as one.

    Interpretationreasoning

    The performance of Campbell et al's model improves as the hill slope increases, although this is suggested to be more due to it underestimating the speed on shallow slopes.

    “The performance of Campbell et al’s model improves as the hill slope increases, although we suggest this is more due to it underestimating the speed on shallow slopes.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim. The paper’s conclusions may not depend on it.

    Study design and conductnone given

    The methods used to filter the datasets were blinded to the outcome of the model generation.

    “The methods used to filter the datasets were blinded to the outcome of the model generation”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim. The paper’s conclusions may not depend on it.

    Interpretationnone given

    The low R-squared value is due to variability within the data.

    “The R-squared value is still very low, however we suggest that this is due to the variability within the data.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim. It may state two separate claims as one.

    Interpretationreasoning

    The choice of a GLM meant that the model was easy to interpret and simple to apply to future work.

    “This choice also meant that our model was both easy to interpret, and simple to apply to future work.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim. The paper may give no reason why it holds.

    Premisenone given

    Tobler's hiking function suggests that walking speed increases on mild descents up to a maximum of 6 km/h.

    “Tobler’s hiking function suggests that walking speed increases on mild descents up to a maximum of 6 km/h.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.

    Study design and conductnone given

    The authors had to make a number of assumptions regarding data filtering and processing including model selection, and other choices may give different results.

    “As described above we had to make a number of assumptions regarding data filtering and processing including model selection, and other choices may give different results.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim. It may state two separate claims as one.

    Study design and conductown data

    Not all terms had a significant effect on all variables; a model with all possible terms was created, and terms were removed one at a time in order of least significance until all remaining terms were significant to at least 95% confidence level using the Wald test.

    “Not all terms had a significant effect on all variables; we therefore created a model with all possible terms, and removed them one at a time (in order of least significance) until all remaining terms were significant to at least 95% confidence level (using Wald test).”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim. The paper may give no reason why it holds. It may state two separate claims as one.

    Premisenone given

    Widely used algorithms (e.g. Naismith's rule) for estimating walking/hiking speed are simple to understand, very easy to calculate but are based on limited observations.

    “Widely used algorithms (e.g. Naismith’s rule) for estimating walking/hiking speed are simple to understand, very easy to calculate but are based on limited observations.”
    Quote in the paperNot a substantial claim

  • It may state two separate claims as one.

    Interpretationnone given

    Under Naismith's rule, predicted ascent time will likely be overestimated and predicted descent time will be underestimated.

    “it is likely that (under Naismith’s rule) the predicted ascent time will be overestimated and the predicted descent time will be underestimated.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim. The paper’s conclusions may not depend on it.

    Study design and conductnone given

    The method of calculating terrain obstruction value was relatively crude, looking only at obstruction height at each GPS point.

    “Our method of calculating the terrain obstruction value was relatively crude, looking only at the obstruction height at each GPS point.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim.

    Study design and conductcitation

    Models which failed to predict the critical gradient occurring below 21 degrees were removed.

    “Furthermore, previous work [11, 29–31] has identified the existence of a critical gradient; the angle at which it is faster to zig-zag up a hill, rather than ascend directly. This occurs at a walking slope of around 15—21 degrees, so models which failed to predict the critical gradient occurring below 21 degrees were removed.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim.

    Study design and conductnone given

    10-fold cross-validation was used to compare the remaining model parameters, looking at R-squared values, root-mean-squared error (RMSE) and mean absolute error.

    “10-fold cross-validation was used to compare the remaining model parameters, looking at R-squared values, root-mean-squared error (RMSE) and mean absolute error.”
    Quote in the paperSubstantial claim
72 of 72

  • The authors state this as an assumption.

    Walking speed should be a decreasing function of the magnitude of slope for both hill and walking slope components, with some allowance for faster walking speeds on mild descents.

    “As it is more challenging to walk on steeper slopes, for both the hill and walking slope components we knew that the walking speed should be a decreasing function of the magnitude of slope (with some allowance for faster walking speeds on mild descents).”

  • The authors state this as an assumption.

    Models which failed to predict the expected slope-speed relationship were removed under the assumption that the data were overfitted.

    “Models which failed to predict this were removed under the assumption that the data were overfitted.”

  • The paper relies on this without support.

    Most individual effects cannot be modelled without considerable prior knowledge about the person who is planning a route.

    “Most of the individual effects cannot be modelled without considerable prior knowledge about the person who is planning a route.”

  • The paper relies on this without support.

    The volume of crowdsourced data causes most individual effects (group size, ability, composition, weather) to average out.

    “although we would expect the volume of data to cause most of these effects to average out”

  • The authors state this as an assumption.

    All crowdsourced data came from walkable regions by definition.

    “the use of crowdsourced data meant that all of our data came from ‘walkable’ regions by definition.”

  • The authors state this as an assumption.

    The data filtering and processing choices (including model selection) are appropriate.

    “we had to make a number of assumptions regarding data filtering and processing including model selection”
6 of 6

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Past work has accommodated off-path environments by lumping the vast diversity of landscape characteristics into a single multiplier or a small number of fixed multipliers specific to broad land cover categories.

    “Past work has accommodated off-path environments by lumping the vast diversity of landscape characteristics into a single multiplier3,6 or a small number of fixed multipliers specific to broad land cover categories7,22.”

    From A singular, broadly-applicable model for estimating on- and off-path walking travel rates using airborne lidar data (2024) · cites this paper as [7]

    The Materials and methods sections describe a small number of terrain categories—paved road, unpaved road and off-road, plus light and heavy obstruction—with factor variables in the walking-speed model. That supports the general point about simplifying varied terrain, but the categories are not broad land-cover categories, and road type also interacts with slope rather than being represented solely by fixed multipliers. The Introduction separately describes single off-road multipliers in earlier models. (LLM, conf=0.82)

    Experimental — accuracy not yet measured

  • GET v1 has not been updated or modified since its initial creation to account for changing landscape conditions and advancements in understanding of how landscape characteristics affect pedestrian movement.

    “Despite its wide use, GET v1 has not been updated or modified since its initial creation to account for changing landscape conditions (e.g., hospital locations, road networks, and land cover) and advancements in our understanding of how landscape characteristics affect pedestrian movement [33,36,37].”

    From Wildland firefighter estimated ground evacuation time modeling to support risk-informed decision-making (2024) · cites this paper as [37]

    The Introduction (page not provided) describes limitations in existing walking-speed methods, and the Discussion reports new findings about how slope, terrain type and obstruction affect walking speed. The paper does not identify GET v1 or say whether it has been updated since its creation, so it cannot support that central part of the claim or the examples of changing hospital locations and land cover. (LLM, conf=0.78)

    Experimental — accuracy not yet measured

  • Existing travel rate functions fail to sufficiently account for the vast diversity of landscape conditions that impede foot travel.

    “Although a number of existing travel rate functions exist, they fail to sufficiently account for the vast diversity of landscape conditions that impede foot travel3–11.”

    From A singular, broadly-applicable model for estimating on- and off-path walking travel rates using airborne lidar data (2024) · cites this paper as [7]

  • Travel time estimates reveal an important degree of variability that would be left unaccounted for if fixed multiplicative terms were used to universally estimate off-path, slope-based travel times.

    “Furthermore, our travel time estimates reveal an important degree of variability that would be left unaccounted for if fixed multiplicative terms were used to universally estimate off-path, slope-based travel times3,6,7.”

    From A singular, broadly-applicable model for estimating on- and off-path walking travel rates using airborne lidar data (2024) · cites this paper as [7]

  • The specific quantitative relationship between vegetation structure and travel rates has been explored only sparingly in the scientific literature.

    “The specific quantitative relationship between vegetation structure and travel rates has been explored only sparingly in the scientific literature [33,34,37,41].”

    From Wildland firefighter estimated ground evacuation time modeling to support risk-informed decision-making (2024) · cites this paper as [37]

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

Each contradiction between two passages listed here was confirmed by an independent check.

  • Claim of not using fixed filtering values conflicts with the algorithm

    Minor

    The discussion says fixed values were not used to classify breaks and non-walking tracks, but the stated filtering algorithm uses fixed speed, duration, and distance thresholds to remove them.

  • Conclusion claims improvement in all scenarios despite a reported exception

    Minor

    The conclusion says the new model gives more accurate walking speeds in all scenarios, but the results report that Campbell et al.'s function has a lower RMSE on the steepest walking slopes.

2 of 2

Citations

Cites

Flagged first, then by citations

Research works printed but not linked: 3

  1. WW Naismith, 1892, Cruach Ardran, Stobinian, and Ben More, Scottish Mountaineering Club Journal, 2
  2. W Tobler, 1993, Three Presentations on Geographical Analysis and Modelling, National Center for Geographic Information and Analysis Technical Report, 93
  3. F Arnet, 2009, Arithmetical Route Analysis with examples of the long final courses of the World Orienteering Championships 2003 in Switzerland and 2005 in Japan, Scientific Journal of Orienteering, 17, 3

Cited by

Sorted by citations

Related

Metadata

Authors
Wood, A., Mackaness, W., Simpson, T. I., & Armstrong, J. D.
Affiliations
University of Edinburgh (GB)
Corresponding author
Wood, Andrew
ORCID
Venue
PLOS One
Publisher
Public Library of Science (PLoS)
Published
2023-12-18
Volume
18
Issue
12
Pages
e0295848
ISSN
1932-6203 (ISSN-L)
DOI
10.1371/journal.pone.0295848
PMC
PMC10727444
OpenAlex
W4389889070
Cited by
15
References
16
Citations by year
2026: 5 · 2025: 7 · 2024: 3
FWCI
1.91
Type
journal article
Language
en
Open access
Licence
Locations
  • PLoS ONE (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • arXiv (Cornell University) (submittedVersion, cc-by)
  • RePEc: Research Papers in Economics (submittedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • Edinburgh Research Explorer (University of Edinburgh) (submittedVersion, cc-by)
  • arXiv (Cornell University) (cc-by)
Funders
UK Engineering and Physical Sciences Research Council (EP/R513209/1)
Topics
  • Social Sciences › Transportation › Human Mobility and Location-Based Analysis
  • Social Sciences › Transportation › Urban Transport and Accessibility
  • Health Sciences › Medicine › Orthopedics and Sports Medicine › Sports Performance and Training
Keywords
hillslopes, terrain slope, terrain type, GPS tracking data, generalized linear models
MeSH terms
Walking Speed, Algorithms, Biomechanical Phenomena, Running, Linear Models, Walking

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

A language model drew the claims from the paper on 2026-11-09, under version 3 of the claim definition (model deepseek-v4.1-flash, prompt extract-v3).

A second model labelled each claim on 2026-11-09 (model jev-1.13-20260917, definition revision gold-guideline-v0.2).

Cited sources are checked with a language model’s help (gpt-6-sol).

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

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