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Route craft ·11 June 2024 · 10 min read

How to find good roads in a place you've never ridden

The Moveee team

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Arriving somewhere new with a bike is one of cycling's better problems, and one of its easiest to get wrong. You have a week, a map full of roads you've never seen, and no idea which of them are quiet and beautiful and which are 60 km of lorries and crosswind.

The information to answer that is nearly all public, and most of it is readable in twenty minutes at a table. Here's what to look at, in what order, and how to sanity-check a route before you commit a whole day to it.

Read the map for gradient first

Before anything else, learn to read the terrain directly, because it tells you what the ride will feel like far better than a distance figure does. On a contour map, gradient is just arithmetic: the number of contour lines a road crosses in a given distance, multiplied by the contour interval.

Contours crossed per kilometre → gradient

Assuming a 20 m contour interval, the most common on European 1:25,000 and 1:50,000 mapping. Check the interval printed on your map — 10 m and 50 m intervals both exist and change every number here.

1× 2% Flat to gently rising. You'll barely change gear.
2× 4% A real but easy gradient. Sustainable all day.
3× 6% A proper climb. Most alpine passes average here.
4× 8% Hard. Sustained 8% needs gearing and pacing.
5× 10% Steep. Fine for 2 km, punishing for 10.
7× 14% Very steep — check this is a road, not a track.
WIDE SPACING = SHALLOW 1 km TIGHT SPACING = STEEP 1 km

One caveat worth knowing: the elevation data behind digital route planners is not exact. Global elevation models carry vertical errors on the order of metres, and error grows with slope — which is why the same climb can show three different totals in three different apps. Use them for shape and for relative comparison, not as a gospel number.

Reading roads before you ride them

Road classification is the most useful free signal there is. The pattern is remarkably consistent across countries: the quiet, well-surfaced, interesting roads are the smallest ones that still have a number.

Look for · Minor roads with numbers or names

Classified-but-small roads are usually sealed, maintained and quiet. The best riding in most countries lives here.

Look for · Roads that wiggle

A road that follows a contour or a river was built before bulldozers. It is almost always more pleasant than the straight one beside it.

Look for · Roads to somewhere small

A road ending at a hamlet, a chapel or a pass carries only the traffic that wants that destination.

Avoid · Trunk roads and primary routes

Fast, busy, often with no shoulder. Cycling injury risk is measurably higher on major streets than on quiet ones.

Avoid · Dashed lines and thin tracks

Could be a smooth forest road; could be a footpath with steps. Never chain more than one unknown per ride.

Avoid · Single crossings of rivers or motorways

If one bridge is the only link, check on imagery that it exists and is open to bikes before you rely on it.

The point about major roads isn't only comfort. A large case-crossover study of injured cyclists found that major streets without bike infrastructure carried substantially higher injury risk than quiet local streets and separated infrastructure — with downhill grades and rail tracks adding risk on top. In a place you don't know, the small road is usually the safer road as well as the nicer one.

Two cyclists riding together on a road through green fields
The road you want is almost always the small one that wiggles. It was built to follow the land, not to move freight.

Heatmaps: useful, and biased

Aggregated ride data — the glowing lines showing where cyclists actually go — is the fastest way to find the local favourites. Research comparing crowdsourced fitness-app ridership against manual bicycle counts found the patterns correlate well enough to be a reasonable proxy for overall cycling volumes, particularly in dense areas.

But it is a proxy, with a known lean. The people who upload rides are not a random sample of cyclists, and researchers building ridership models from this data have had to explicitly correct for that bias. Read a heatmap accordingly:

  • A bright line means "lots of people ride here", not "this is the best road". Popular commuting corridors light up for reasons that have nothing to do with a good Saturday.
  • A dark road is not automatically bad. It may simply be somewhere the app-using population doesn't live.
  • Look for the thin bright lines. A minor road glowing more brightly than the parallel main road is the strongest single signal in this whole article — locals are choosing it for a reason.
  • Check the direction of travel where you can. Some climbs are only ever ridden one way, and the reverse is genuinely unpleasant.

If you've ridden in the area before, Moveee's Explore map shows which roads you've already covered — which is mostly useful for the opposite purpose: finding the ones you haven't.

Local knowledge, without knowing any locals

  • Find a local club's routes. Almost every club publishes a weekend loop. It will be the best 80 km within reach of that town, refined over decades.
  • Look for a bike shop and read its route page. Shops that rent road or gravel bikes usually publish the routes they hand to customers, and those routes are chosen to not produce complaints.
  • Find the local cyclosportive. A published event route is a curated set of the best roads in the region with the traffic problems designed out.
  • Check the mountain pass and col databases. For anywhere hilly, these give gradient profiles, surface notes and seasonal closures.
  • Note when roads shut. High passes close for months. A road being on a map says nothing about whether it's open in April.

The sanity check before you commit

Six questions, five minutes, before the route leaves the planning tool. Almost every ruined day in an unfamiliar place fails one of them.

1
Does the elevation profile look plausible?

Sawtooth noise on a flat road means bad elevation data, not a hilly road. Real climbs appear as smooth, sustained ramps.

2
Have you checked the surface of every unknown section?

Satellite imagery, two minutes, section by section. This is the single highest-value check on this list.

3
Is there a shop or tap roughly every 40 km?

In a place you don't know, assume one of them is closed.

4
Does the route cross a trunk road anywhere awkward?

Look at the junction on imagery. A 300 m stretch of dual carriageway can ruin an otherwise perfect route.

5
Is there a bail-out at roughly the halfway point?

A valley road, a station, a bus. You are in unfamiliar terrain — give yourself an exit.

6
Does it climb in the first third and descend in the last?

Not a rule, but a good default when you don't know how the terrain will feel.

Drawing it yourself with the surface breakdown visible removes most of the remaining guesswork — the Route builder shows the paved-versus-unpaved split and the elevation profile while you draw, and exports a GPX at the end. If you'd rather start from something that already exists, the Route Engine will find routes that match the time you have and the kind of day you want. The general principles of a good loop are covered in how to build the perfect cycling route.

The first ride in a new place

Make it shorter than you want to. Two to three hours, out and back along the most promising valley, is the best reconnaissance there is — you learn the traffic culture, the surface quality, the signage and how the gradients actually feel, and you can turn round at any point. Everything you plan for the rest of the week will be better for it.

And accept that one route in five will be a dud. Somewhere in the middle there will be 8 km of grim main road that looked fine on the map. That's the cost of exploring unfamiliar terrain, and it's a low price for the other four.

Sources 5

Where this article summarises a study, the study itself is linked — not a write-up of it.

  1. 1 Haklay M How good is volunteered geographical information? A comparative study of OpenStreetMap and Ordnance Survey datasets · Environment and Planning B: Planning and Design · 2010
  2. 2 Jestico B, Nelson T, Winters M Mapping ridership using crowdsourced cycling data · Journal of Transport Geography · 2016
  3. 3 Roy A, Nelson TA, Fotheringham AS, Winters M Correcting bias in crowdsourced data to map bicycle ridership of all bicyclists · Urban Science · 2019
  4. 4 Teschke K, et al. Route infrastructure and the risk of injuries to bicyclists: a case-crossover study · American Journal of Public Health · 2012
  5. 5 Ghannadi MA, Alebooye S, Izadi M, Ghanadi A Vertical accuracy assessment of Copernicus DEM (case study: Tehran and Jam cities) · ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences · 2023
Put it into a route

Build a route that is actually worth riding

The Route Engine works from real surface and elevation data and favours quiet roads, so it finds the lanes a fastest-way-there app routes you straight past. Give it a distance and a direction and it does the rest.

Build a route

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