“Nothing because all the walking routes I have used were in good condition.”
3. Support physical activity and sustainable travel choices:
6.2 Whole Network Usage Estimate (WNUE) methodology
We used Sustrans’ NCN Whole Network Usage Estimate (NCN WNUE) methodology to estimate usage across the entire extent of the NWCN in 201949. This methodology uses data from monitored sections of the UK-wide NCN to make an estimate of usage on the unmonitored sections of the NWCN. It is based on the following premise:
Any sections of a network which share the same characteristics (which are known to affect walking and cycling levels) will see the same level of usage.
The sections below set out the methodology as applied to the UK-wide NCN and then detail the revisions used to apply the same method to the NWCN.
6.2.1 Determinants of usage on the NCN
Previous Sustrans research (2014) identified two characteristics as key determinants of usage on the NCN:
Population in proximity – levels of cycling tend to increase in line with the size of population living in close proximity to it;
Proportion of the population who cycle to work – levels of cycling on a route tend to be high when the proportion of the local population who cycle to work is also high.
Several other variables were included in the study, but the above two variables were shown to be the best predictors of usage and are therefore used to estimate usage on the NCN.
6.2.2 Categorising the NCN according to characteristics that determine usage
Using a geographic information system (GIS), we break down a map of the NCN network into sections of route ≤ 1km long, using natural break points such as junctions or changes in the infrastructure provision.
49 The methodology described here was used to estimate usage on the NWCN in 2019 only. For the baseline report, a different and incomparable methodology was used to estimate usage on the NWCN. Due to their incomparability, no comparisons will be made to the estimate produced in 2016. The methodology described here was also used to estimate 2019 usage on the NCN (UK-wide) and NCN in Scotland specifically.
Values for the two ‘usage-determining’ characteristics identified above were calculated for each (1km or less) route sections. These characteristics are assumed to remain constant for each section.
Population in proximity
This characteristic is quantified using a metric called ‘population gravity’. This accounts for both the size of the local population and its proximity to the section in question by applying a non-linear weighting (the square of the distance from the section). This means that the further a population centre is from the section of route, the less its impact on the population gravity score. This metric is calculated as follows:
The centre point of the route section is identified;
Concentric rings are drawn around this point at 1km intervals between 1 and 10km;
The statistical geographies (SGs) (DataZones for Scotland, LSOAs in England and Wales, SOAs in Northern Ireland) that fall into each concentric ring are identified using the point co-ordinates of the population weighted centroid (PWC) of the SG;
The population of each concentric ring is calculated by summing the populations of the SG that lie in each ring;
The population of each ring is then divided by the square of the distance of that ring from the centre point of the route section in question. The mid-point of each ring is used (i.e. the distance value used is 0.5km, 1.5km…9.5km);
The resulting ten values are then summed to give a single value for that section of route.
The calculation can be written as follows:
𝑃𝑜𝑝𝑢𝑙𝑎𝑡𝑖𝑜𝑛 𝑔𝑟𝑎𝑣𝑖𝑡𝑦 = ∑ 𝑥𝑖 (𝑖 − 0.5)2
10
𝑖=1
𝑊ℎ𝑒𝑟𝑒 𝑖 = 𝑡ℎ𝑒 𝑏𝑢𝑓𝑓𝑒𝑟𝑠 𝑝𝑙𝑎𝑐𝑒𝑑 𝑎𝑟𝑜𝑢𝑛𝑑 𝑒𝑎𝑐ℎ 𝑟𝑜𝑢𝑡𝑒 𝑐𝑒𝑛𝑡𝑟𝑒 𝑝𝑜𝑖𝑛𝑡 (𝑖𝑛 𝑘𝑚) 𝑎𝑛𝑑 𝑥 = 𝑡ℎ𝑒 𝑠𝑢𝑚 𝑜𝑓 𝑡ℎ𝑒 𝑝𝑜𝑝𝑢𝑙𝑎𝑡𝑖𝑜𝑛 𝑜𝑓 𝑡ℎ𝑒 𝑆𝐺 𝑡ℎ𝑎𝑡 𝑙𝑖𝑒 𝑤𝑖𝑡ℎ𝑖𝑛 𝑒𝑎𝑐ℎ 𝑏𝑢𝑓𝑓𝑒𝑟.
Level of cycling to work
We quantify this characteristic using data taken from the 2011 Census concerning the proportion of people within an SG who cycle to work. A non-linear weighting is again applied to account for the effect of distance from the section of route in question. It is calculated as follows:
The proportion of people cycling to work in each SG lying in each concentric ring (from the previous section) is identified;
The mean proportion of people cycling to work is calculated for each ring;
The resulting value for each ring is then divided by the square of the distance of that ring from the centre point of the route section in question. The mid-point of each ring is used (i.e. the distance value used is 0.5km, 1.5km…9.5km);
The resulting ten values are then summed to give a single value for that section of route.
The calculation can be written as follows:
𝐶𝑦𝑐𝑙𝑒 𝑡𝑜 𝑤𝑜𝑟𝑘 𝑔𝑟𝑎𝑣𝑖𝑡𝑦 = ∑ 𝑥̅𝑖 (𝑖 − 0.5)2
10
𝑖=1
𝑊ℎ𝑒𝑟𝑒 𝑖 = 𝑡ℎ𝑒 𝑏𝑢𝑓𝑓𝑒𝑟𝑠 𝑝𝑙𝑎𝑐𝑒𝑑 𝑎𝑟𝑜𝑢𝑛𝑑 𝑒𝑎𝑐ℎ 𝑟𝑜𝑢𝑡𝑒 𝑐𝑒𝑛𝑡𝑟𝑒 𝑝𝑜𝑖𝑛𝑡 (𝑖𝑛 𝑘𝑚) 𝑎𝑛𝑑 𝑥̅ = 𝑡ℎ𝑒 𝑚𝑒𝑎𝑛 𝑐𝑦𝑐𝑙𝑒 𝑡𝑜 𝑤𝑜𝑟𝑘 𝑝𝑟𝑜𝑝𝑜𝑟𝑡𝑖𝑜𝑛 𝑜𝑓 𝑡ℎ𝑒 𝑆𝐺 𝑡ℎ𝑎𝑡 𝑙𝑖𝑒 𝑤𝑖𝑡ℎ𝑖𝑛 𝑒𝑎𝑐ℎ 𝑏𝑢𝑓𝑓𝑒𝑟.
6.2.3 Cycling and pedestrian usage data on the NCN
We identified over 200 automatic cycle and pedestrian counters located on the traffic-free UK-wide NCN using GIS. Count data for 2019 was extracted and Annual Median Daily Totals (AMDT) calculated. These usage estimates are assigned to the ≤1km route section on which they were located.
Very few automatic counters are located on the on-road NCN so Department for Transport traffic count data50 are used instead. This dataset contains the location of all count points used in the National Road Traffic Estimates (NRTEs) since 2000, along with the classified road traffic counts for that location (including cycle counts). We downloaded the Average Annual Day Flow (AADF) data for all 201851 count locations on the UK-wide NCN. These usage estimates are assigned to the ≤1km route section on which the relevant count was located.
50 https://data.gov.uk/dataset/208c0e7b-353f-4e2d-8b7a-1a7118467acc/gb-road-traffic-counts
51 No 2019 data was available at the time of writing this report.
6.2.4 Estimating usage where there are no count data on the NCN
The previous steps result in a dataset of the UK-wide NCN, made up of sections ≤1km long.
Each section has a value assigned for the two characteristics (population gravity and cycle to work proportion gravity), and some sections have a daily usage figure taken from either an automatic counter or DfT’s categorised NRTE counts.
It is then straightforward to use a multivariate regression of the two characteristics on the available count data to produce an equation to estimate cycle usage on the unmonitored sections.52 Because of the different sources of count data, two regressions are conducted: one for the on road sections and another for the off road sections. Note the term on the left hand side of the two equations differs because different transformations were applied to the count data.
Off road usage
√𝑦 𝑖 = 𝑏 0 + 𝑏 1 𝑥 1𝑖 + 𝑏 2 𝑥 2𝑖 + 𝑒 𝑖
On road usage
𝑙𝑜𝑔 10 𝑦 𝑖 = 𝑏 0 + 𝑏 1 𝑥 1𝑖 + 𝑏 2 𝑥 2𝑖 + 𝑒 𝑖
Where:
𝑦 = 𝑡ℎ𝑒 𝑒𝑠𝑡𝑖𝑚𝑎𝑡𝑒𝑑 𝑑𝑎𝑖𝑙𝑦 𝑢𝑠𝑎𝑔𝑒 𝑥1= 𝑃𝑜𝑝𝑢𝑙𝑎𝑡𝑖𝑜𝑛 𝑔𝑟𝑎𝑣𝑖𝑡𝑦
𝑥2= 𝐶𝑦𝑐𝑙𝑒 𝑡𝑜 𝑤𝑜𝑟𝑘 𝑝𝑟𝑜𝑝𝑜𝑟𝑡𝑖𝑜𝑛 𝑔𝑟𝑎𝑣𝑖𝑡𝑦 𝑏1 𝑎𝑛𝑑 𝑏2= 𝑇ℎ𝑒 𝑟𝑒𝑔𝑟𝑒𝑠𝑠𝑖𝑜𝑛 𝑐𝑜𝑒𝑓𝑓𝑖𝑐𝑖𝑒𝑛𝑡𝑠 𝑒 = 𝑇ℎ𝑒 𝑒𝑟𝑟𝑜𝑟 𝑖𝑛 𝑡ℎ𝑒 𝑚𝑜𝑑𝑒𝑙
𝑖 = 𝑇ℎ𝑒 𝑠𝑒𝑐𝑡𝑖𝑜𝑛 𝑜𝑓 𝑟𝑜𝑢𝑡𝑒 𝑖𝑛 𝑞𝑢𝑒𝑠𝑡𝑖𝑜𝑛
To estimate a usage figure for pedestrians, one of two approaches are taken. If there is a pedestrian counter on the section, we use the actual usage figure. For any sections without pedestrian data, previous analysis of combined pedestrian and cycle counts by Sustrans has indicated that there are approximately 3.00 pedestrian trips per cycle trip. Pedestrian usage on the remaining sections (both on and off road) is therefore the cycle usage estimate (either actual or modelled) multiplied by 3.00. Note, it is assumed that there is no pedestrian usage on any on-road sections of the NCN.
52 Note, any sections where there are count data are assigned the actual usage figure rather than the estimated figure.
The resulting usage figures are actually density figures – it is the count of cycles and pedestrians that would be recorded at any point on the given section of route. It is not an estimate of the number of individual trips being made on that section.53
To estimate the number of trips, we divide the density figure by the average trip length on the NCN (2.42km for cycles, 1.1km for pedestrians – Sustrans (2014)). The sum of the resulting figure for each section is the daily usage estimate for the network. Multiplying this by 365 gives the total annual usage estimate.
6.2.5 Applying the NCN WNUE methodology to the NWCN
To estimate usage on the NWCN we use the same regression co-efficients that we use on the UK wide NCN. This is because there is substantial overlap between the two networks in Scotland and it is also important that the two usage estimates are compatible with each other.
However, there are some adjustments to the methodology that are required to make it applicable to the NWCN. Unless stated, the methods are otherwise identical.
A GIS shapefile of the entire extent of the NWCN network was created by merging shapefiles of the NCN in Scotland with those for Scotland’s Great Trails and Scotland’s Canal towpaths.
Boolean attributes (TRUE/FALSE) were assigned to each section of the route, specifying whether the section was walkable and/or cyclable (please see the following section for the detail of how this attribute was identified) and whether it was on-road or traffic-free. The entire network was then divided into sections ≤ 1km in length, using natural break points such as junctions, or where the network switched between on-road to traffic-free cycling provision, or the walkability and cyclability definition changed.
The two explanatory characteristics were calculated for the non-NCN sections of the NWCN using the same approach as detailed above.
The NCN WNUE regression co-efficients were then used to calculate a usage figure for each section on the network, including on the non-NCN sections. Any sections where there are count data are assigned the actual usage figure rather than the estimated figure. This includes any automatic counters or DfT count points on the non-NCN NWCN.
A number of on-road sections of the NWCN are deemed to be walkable, but the DfT counts do
53 As an example, consider a section of network that is 2 kilometres long. There are 10 people cycling on the path, and they will cycle the full length of the path once. If a count was conducted it would record 10 instances of people passing the count site, regardless of the location of the count on the path. This would give the usage density – 10 people per unit of distance. If kilometres are used as the unit of distance, this gives 10 people per kilometre, or 10 usage kilometres. Scaling this up to the 2km path gives 20 usage kilometres. Note, any unit of distance could be used, as long as the length of the path was reported in the same unit.
However, usage kilometres are not easily communicable measure of usage. To convert usage kilometres into the number of trips being made, they are divided by the average length of trip on the section. In this example, divide the 20 usage kilometres by the cycle length – 2km – to give a total of 10 trips, which is the right answer.
not include a pedestrian category so it is not possible to use actual data for these sections.
Pedestrian usage on these sections is estimated using the same approach to estimating pedestrian usage on the traffic-free sections where there are no data (i.e. by factoring the cycle usage figure on the same section).
The resulting density figures are then divided by the average trip length on the NCN. Assumed also relevant to the NWCN (2.42km for cycles, 1.1km for pedestrians – Sustrans (2014)). The sum of the resulting figure for each section is the daily usage estimate for the NWCN. This is then multiplied by 365 to give an annual usage estimate.
6.2.6 Walkability and cyclability of the NWCN
There is considerable overlap between the different networks making up the NWCN, all with different definitions for what makes their component routes walkable and/or cyclable. A hierarchy of decisions has therefore been followed to determine the walkability/cyclability of any route section:
Figure 65 Defining walkability and cyclability on the NWCN
Is it Scottish Canals?
Is it Scotland’s Great Trails?
Is it NCN?
All walkable and cyclable
All walkable;
cyclable according to
audit (see section 6.2.7)
Traffic-free = walkable +
cyclable
On-road = cyclable only Yes
No
No
Yes
Yes
Not on NWCN No
6.2.7 Cyclability of Scotland’s Great Trails
Cyclable sections of SGTs are:
Suitable for:
A person of any age who can cycle on varied terrain.
Road or mountain bikes, unassisted or e-bikes.
Length:
A section of trail is defined as being of 1km or more in length, starting from an access point.
Surface type:
On or off road where the surface could range from smooth tarmac to loose gravel, bare earth or grass.
There may be some natural small obstacles such as roots or rocks.
A short flight of 3 or 4 steps is acceptable, or a longer flight if a wheeling ramp is installed at the side.
It is acceptable to negotiate water bars but it shouldn’t be necessary to lift a bike over multiple cross drains, i.e. more than 1 or 2 per km.
Gradients, barriers and gaps:
Gradients are mostly up to moderate (5% to 12%) but could include short steep sections (slopes between 12% and 20% of up to 50m duration) where cyclists might need to get off and push.
Sections of route should be free from barriers - or where a barrier is in place (e.g. a stile or a gate), it should be possible to open the barrier and push a bike through, rather than have to lift a bike over it.
Any gaps, e.g. in fences or between bollards, should be greater than 1200m.
Please see the following figure for the walkability and cyclability of the NWCN as determined for the whole network usage estimate methodology.
Figure 66 Walkability and cyclability of Scotland’s NWCN, as determined for the purposes of the whole network usage estimate methodology