Checkout https://bikehopper.org for solid elevation, bike infrastructure and transit-aware routing around the Bay Area. Some friends and I built this about 5 years ago and continue to maintain it. We use 1m DTM elevation data for SF and 50m for rural areas. DTM is a must for elevation based routing in SF as there are so many sizable buildings, large trees the other models fail hard.
I've checked out a few bike mapping apps recently and one feature I found absolutely invaluable was grade indications like http://hillmapper.com (which unfortunately seems unmaintained.)
Google Maps elevation diagrams comparing the various selected routes are nice but they do not do a good job of highlighting extreme grades. I feel like you actually want to graph the change in elevation rather than the elevation itself.
Using a route I cycled the other day (near Mission Bernal Safeway to near Diamond Heights Safeway). I think the routing may overweight bike lanes too much. For instance it will go four blocks by shared street and bike lane to avoid the two blocks on Clipper between Sanchez and Castro which are not a bike lane.
On my heavy cargo e-bike I've found there is quite a non-linear difference as the grade increases. 12% and I'll work a bit but be fine. 22% (the route Google Maps sent me...) and I'll all but collapse after a block.
Hillmapper falling apart was one of the main reasons we prioritized getting good elevation data into our router. We include steepness indicators for steep blocks and an elevation overview of the full trip and have found that combo to serve us well.
Getting between those two Safeways is rough. Bikehopper fails, it suggests the harry street steps; a non-starter for most. I’ll try to fix it. I definitely agree that grade is non-linear. We use accelerating weighting for grade so a hill that is twice as steep is more than twice as “discouraged” by the routing engine.
For bike routing I think e-bikes need a separate profile from acoustic bikes. Hill matter less and stairs are totally out of the question (this is important for routing in and out of transit centers).
The specific route suggested varies a bit depending on where you move the starting point. Closer to Sanchez St it does a better (albeit not perfect) job than google maps.
I guess as a cyclist in SF I’m not necessarily looking for the routing to be perfect but I am looking to see the information that matters so I can understand how appropriate the suggested routing is.
Agree that e-bike and acoustic bike riders probably do have slightly different sets of preferences. A big one for me is that I’m ok with 4 way stops every block on slow streets on an e-bike but on an acoustic bike they’d drive me nuts.
Can you please consider expanding it to include Seattle? Or better yet Puget Sound area? 1m DTM elevation data is available here. We have many amazing bike trails, but also plenty of hills that must be avoided.
We’d like too! It’s an open source project that was never designed to scale beyond one regions (bay area, puget sound, NYC, etc…) our hope has always been been that folks in different regions would spin up their own copy. By keeping it regional the data and hardware requirements for running it are minimal. That said, we are working on a new routing engine that we hope can scale to support continent wide routing. Then we can manage running it for many metro’s. If you’re interested in self hosting for Seattle we are happy to help get it set up.
What are the system requirements for hosting it? I'm not sure I have the discretionary funds to host it for the general public - but it all depends on how heavy this is :)
We run it on a single coolify box from someone’s house. 6 core, 32GB ddr4 memory box. The actual routing query are compute intensive but only momentarily. More cores and memory means higher concurrency but we’ve never had an issue with load in the Bay Area with a few hundred users a week. We used to run it on a k8s cluster but we cut it down to save on power and infrastructure management overhead.
DSM includes buildings and trees. So the DSM from SRTM data makes market street in S.F. look like a series of very steep hills and valleys because some of the datapoints are street level while others are the roofs of skyscrapers. DTM removes the buildings resulting in a map much closer to what we think of from the ground.
It would be neat if it there were an option which added distance and elevation gain, but minimized the grade.
For example, a route from SOMA to Nob Hill can be made flatter by approaching from either the east or west. Technically the "flattest" as measured by elevation gain between the two is straight up Taylor from Market, but it's much nicer to bike to the top of Nob Hill by going out of the way (e.g. Polk → California, Embarcadero → Broadway, etc.)
I suspect that this would result in absurdly long routes. Imagine trying to go up a mountain while minimizing grade... you'd end up zig-zagging back and forth endlessly.
Unless you are on foot (and even then) the route needs to follow existing roads, you can only zig zag as much as existing roads do it not endlessly.
And almost any practical routing system will have a mechanism for tradeoffs of different aspects. Often there is a distance/time tradeoff which directly relates to speed on corresponding segments. But the tradeoff can also be in the form of "on average x seconds spent waiting green light in each intersection or time to stop before railroad crossing. So there is no reason for a system optimizing grade to completely ignore all other factors, it's just a question of weights and curves of each of them.
Isn’t that exactly how you build a trail up a mountainside? They are usually a series of switchbacks.
Most people on most bikes can only take so much grade before climbing becomes impossible. A maximum grade setting would be very helpful for that exact reason.
Oh, yeah, I interpreted the parent comment as "minimize the grade" but if it's instead "keep grade below threshold" (for reasonable thresholds) that would make more sense.
I feel like even if the distances are equal, it's faster to walk a bike up a steep grade and bike the rest flat than it is to bike up a moderate grade the whole way. This topic has probably been discussed somewhere else.
People can generally only output their max power for short durations. The output level they can sustain is generally much lower. I bet you could try to model higher limits for short distances, but what those should be could vary greatly depending on personal fitness.
I think that too favors walking the bike up the incline. Anyone able-bodied should be able to do it, some faster than others, but biking up an SF incline is more hit or miss, especially when considering different bikes.
My reasoning for the bike-hike being faster is that legs are designed for it. Legs are only inefficient on flatter ground because you have no equivalent of high gear (like extendible legs), so all that torque is going to waste.
It's not accurate. I mapped it from my house on Cabrillo St in the outer Richmond to 4th avenue and it says I need to climb 25th avenue then walk Geary instead of correctly telling me to use 23rd avenue that is completely flat.
ah, I think this is related to SF's "Slow Streets" program and a genuine bug in the parser.
Cabrillo is a Slow Street, and the parser read its "destination-only" tag as closed to pedestrians, so the tool couldn't see the street at all (and started you a block over?). fixed and deployed; your trip should now go Cabrillo → 23rd → Geary.
No, as someone who writes a cycle routing engine by hand, this stuff is endemic when dealing with the trifecta of complex traffic regulations, inconsistent mapping data, and user preferences.
Looking at the repository [1], there are very strong signs for this being LLM generated. The README.md just smells of LLM tells, and Claude Code is being listed as "contributor".
I agree that the tone the parent commenter used wasn't the nicest but unfortunately, factually he is correct.
Nice visualization. For proper turn by turn directions, Valhalla [1] could help. It has elevation support so this could theoretically be built with it[2], or you just send the shape of your flattest route and it annotates it with guidance.
There's a weird thing going on at 22nd and San Jose in the Mission, where it doesn't seem to understand that you can simply continue down 22nd, but instead takes a hook down San Jose before backtracking. I see some other weird discontinuities like this as I click around.
I have to say that the Claude UI has made many inexplicable decisions here, including (but not limited to) the mysterious color coding, the confusing continuous slider over a discrete set, and the weird positioning of the height labels in the altitude graph.
This is great. Since SF is mostly a grid, I used to use the heuristic of only choosing paths that wouldn't take me further from my destination, avoiding going downhill but choosing the shallower uphill climb if a choice is given.
Other than knowing the direction of my destination, it only used local information
This seems to have the same issue I saw with Google Maps where it directed me along 29th St from near Mission Bernal Safeway to Diamond Heights Safeway. This includes a 22.7% grade! It's much faster and easier (at least on my cargo e-bike) to take the longer way around up Clipper St (12% grade).
The bug seems to be apparent when you set the end point at Duncan & Diamond Heights Blvd and the start point directly north along Clipper.
This route seems to maybe save 1 ft of climbing but goes up a 23% grade.
I wonder how that would work here with horribly inaccurate elevation data. I often ride a specific flat straightaway and Strava and other tracking apps always show me pedaling up and down 20-meter pine trunks next to the bike path.
I was wanting something similar to see the fall leaves in the mountains of NC. I wanted to pick roads at the appropriate elevation, where they are in peak, but google maps isn't really geared for that.
When I used to ride around SF on an e-bike, I’d deliberately choose undulating routes so I could climb at max assist speed and then fly down the descents above max assist speed.
As a life-long city cyclist, with a fable for going fast while staying pedantically lawful, I found that my prefered routes are not about avoiding hills, but about:
1. The length of uninterrupted high quality bicycle ways (e.g. no traffic lights crossings etc.), a 2 km uninterrupted path beats a 1 km route with a ton of crossings and traffic lights
2. The quality of the bicycle path surface. I accept a slightly longer path if the road surface doesn't resemble a moon landscape
3. The potential for "chaos" (for a lack of better words) on that route. For example I will take a detour if it avoids going through areas with tourists and taxis, all of whom appear to be surprised by the concept of the bicycle on a bicycle path on a deep existential level.
Of course hills can play a role as well, but that may be more important in some cities than others.
Your net elevation change is just the difference in altitude between your starting point and your ending point. So yes, it’s independent of route, but that’s not what the term “climb” refers to. It’s not a net elevation change; it’s a cumulative elevation gain, because in bicycling and walking the in‑between parts burn energy. Human legs don’t have regenerative braking, so every time you gain a foot of altitude you don’t get those calories back when you lose a foot of altitude.
In addition, while the net elevation change is bounded by the delta, given the choices might be "go up this steep section" vs "go along this gentle incline", one route can be "flatter" between the same endpoints.
Checkout https://bikehopper.org for solid elevation, bike infrastructure and transit-aware routing around the Bay Area. Some friends and I built this about 5 years ago and continue to maintain it. We use 1m DTM elevation data for SF and 50m for rural areas. DTM is a must for elevation based routing in SF as there are so many sizable buildings, large trees the other models fail hard.
Very Cool. Thanks for making it!
I've checked out a few bike mapping apps recently and one feature I found absolutely invaluable was grade indications like http://hillmapper.com (which unfortunately seems unmaintained.)
Google Maps elevation diagrams comparing the various selected routes are nice but they do not do a good job of highlighting extreme grades. I feel like you actually want to graph the change in elevation rather than the elevation itself.
Using a route I cycled the other day (near Mission Bernal Safeway to near Diamond Heights Safeway). I think the routing may overweight bike lanes too much. For instance it will go four blocks by shared street and bike lane to avoid the two blocks on Clipper between Sanchez and Castro which are not a bike lane.
On my heavy cargo e-bike I've found there is quite a non-linear difference as the grade increases. 12% and I'll work a bit but be fine. 22% (the route Google Maps sent me...) and I'll all but collapse after a block.
Hillmapper falling apart was one of the main reasons we prioritized getting good elevation data into our router. We include steepness indicators for steep blocks and an elevation overview of the full trip and have found that combo to serve us well.
Getting between those two Safeways is rough. Bikehopper fails, it suggests the harry street steps; a non-starter for most. I’ll try to fix it. I definitely agree that grade is non-linear. We use accelerating weighting for grade so a hill that is twice as steep is more than twice as “discouraged” by the routing engine.
For bike routing I think e-bikes need a separate profile from acoustic bikes. Hill matter less and stairs are totally out of the question (this is important for routing in and out of transit centers).
The specific route suggested varies a bit depending on where you move the starting point. Closer to Sanchez St it does a better (albeit not perfect) job than google maps.
I guess as a cyclist in SF I’m not necessarily looking for the routing to be perfect but I am looking to see the information that matters so I can understand how appropriate the suggested routing is.
Agree that e-bike and acoustic bike riders probably do have slightly different sets of preferences. A big one for me is that I’m ok with 4 way stops every block on slow streets on an e-bike but on an acoustic bike they’d drive me nuts.
Can you please consider expanding it to include Seattle? Or better yet Puget Sound area? 1m DTM elevation data is available here. We have many amazing bike trails, but also plenty of hills that must be avoided.
We’d like too! It’s an open source project that was never designed to scale beyond one regions (bay area, puget sound, NYC, etc…) our hope has always been been that folks in different regions would spin up their own copy. By keeping it regional the data and hardware requirements for running it are minimal. That said, we are working on a new routing engine that we hope can scale to support continent wide routing. Then we can manage running it for many metro’s. If you’re interested in self hosting for Seattle we are happy to help get it set up.
What are the system requirements for hosting it? I'm not sure I have the discretionary funds to host it for the general public - but it all depends on how heavy this is :)
We run it on a single coolify box from someone’s house. 6 core, 32GB ddr4 memory box. The actual routing query are compute intensive but only momentarily. More cores and memory means higher concurrency but we’ve never had an issue with load in the Bay Area with a few hundred users a week. We used to run it on a k8s cluster but we cut it down to save on power and infrastructure management overhead.
What does it mean to “cut it down”? Not familiar with k8s personally and unsure if it’s a technical thing or you just stopped using k8s
Would a DSM not be preferable to a DTM? Or is that you reference with regards to large trees?
DSM includes buildings and trees. So the DSM from SRTM data makes market street in S.F. look like a series of very steep hills and valleys because some of the datapoints are street level while others are the roofs of skyscrapers. DTM removes the buildings resulting in a map much closer to what we think of from the ground.
It would be neat if it there were an option which added distance and elevation gain, but minimized the grade.
For example, a route from SOMA to Nob Hill can be made flatter by approaching from either the east or west. Technically the "flattest" as measured by elevation gain between the two is straight up Taylor from Market, but it's much nicer to bike to the top of Nob Hill by going out of the way (e.g. Polk → California, Embarcadero → Broadway, etc.)
I suspect that this would result in absurdly long routes. Imagine trying to go up a mountain while minimizing grade... you'd end up zig-zagging back and forth endlessly.
Unless you are on foot (and even then) the route needs to follow existing roads, you can only zig zag as much as existing roads do it not endlessly.
And almost any practical routing system will have a mechanism for tradeoffs of different aspects. Often there is a distance/time tradeoff which directly relates to speed on corresponding segments. But the tradeoff can also be in the form of "on average x seconds spent waiting green light in each intersection or time to stop before railroad crossing. So there is no reason for a system optimizing grade to completely ignore all other factors, it's just a question of weights and curves of each of them.
Isn’t that exactly how you build a trail up a mountainside? They are usually a series of switchbacks.
Most people on most bikes can only take so much grade before climbing becomes impossible. A maximum grade setting would be very helpful for that exact reason.
Oh, yeah, I interpreted the parent comment as "minimize the grade" but if it's instead "keep grade below threshold" (for reasonable thresholds) that would make more sense.
I feel like even if the distances are equal, it's faster to walk a bike up a steep grade and bike the rest flat than it is to bike up a moderate grade the whole way. This topic has probably been discussed somewhere else.
People can generally only output their max power for short durations. The output level they can sustain is generally much lower. I bet you could try to model higher limits for short distances, but what those should be could vary greatly depending on personal fitness.
I think that too favors walking the bike up the incline. Anyone able-bodied should be able to do it, some faster than others, but biking up an SF incline is more hit or miss, especially when considering different bikes.
My reasoning for the bike-hike being faster is that legs are designed for it. Legs are only inefficient on flatter ground because you have no equivalent of high gear (like extendible legs), so all that torque is going to waste.
But hike a bike is no fun, especially if trying not to sweat
It's not accurate. I mapped it from my house on Cabrillo St in the outer Richmond to 4th avenue and it says I need to climb 25th avenue then walk Geary instead of correctly telling me to use 23rd avenue that is completely flat.
I think this comes down to the DEM they are using. I think it would have come out better if they had used USGS 3DEP DTM at 25cm.
Edited: which apparently is hosted for free on AWS S3.
ah, I think this is related to SF's "Slow Streets" program and a genuine bug in the parser.
Cabrillo is a Slow Street, and the parser read its "destination-only" tag as closed to pedestrians, so the tool couldn't see the street at all (and started you a block over?). fixed and deployed; your trip should now go Cabrillo → 23rd → Geary.
“genuine bug in the parser” -> red flag for slop for those keeping track at home
No, as someone who writes a cycle routing engine by hand, this stuff is endemic when dealing with the trifecta of complex traffic regulations, inconsistent mapping data, and user preferences.
Looking at the repository [1], there are very strong signs for this being LLM generated. The README.md just smells of LLM tells, and Claude Code is being listed as "contributor".
I agree that the tone the parent commenter used wasn't the nicest but unfortunately, factually he is correct.
[1] https://github.com/almostimplemented/flattensf
No need to be a jerk.
Nice visualization. For proper turn by turn directions, Valhalla [1] could help. It has elevation support so this could theoretically be built with it[2], or you just send the shape of your flattest route and it annotates it with guidance.
[1]: https://github.com/valhalla/valhalla
[2]: Currently it only supports 30m resolution for elevation unfortunately
The wiggle!
(in honor of my old commute, which I miss)
https://flattensf.com/#t~-122.40850~37.77493~-122.50940~37.7...
If that's OpenStreetMap data, it is missing the required attribution.
There’s the attribution at the bottom-right corner.
There's a weird thing going on at 22nd and San Jose in the Mission, where it doesn't seem to understand that you can simply continue down 22nd, but instead takes a hook down San Jose before backtracking. I see some other weird discontinuities like this as I click around.
I have to say that the Claude UI has made many inexplicable decisions here, including (but not limited to) the mysterious color coding, the confusing continuous slider over a discrete set, and the weird positioning of the height labels in the altitude graph.
This is great. Since SF is mostly a grid, I used to use the heuristic of only choosing paths that wouldn't take me further from my destination, avoiding going downhill but choosing the shallower uphill climb if a choice is given.
Other than knowing the direction of my destination, it only used local information
This seems to have the same issue I saw with Google Maps where it directed me along 29th St from near Mission Bernal Safeway to Diamond Heights Safeway. This includes a 22.7% grade! It's much faster and easier (at least on my cargo e-bike) to take the longer way around up Clipper St (12% grade).
The bug seems to be apparent when you set the end point at Duncan & Diamond Heights Blvd and the start point directly north along Clipper.
This route seems to maybe save 1 ft of climbing but goes up a 23% grade.
https://flattensf.com/#t~-122.43968~37.74865~-122.44028~37.7...
Half a block up the street it takes the sensible route with only a 13% grade. (Between the two different starting points is 41ft of climbing.)
https://flattensf.com/#t~-122.44087~37.74864~-122.44028~37.7...
good point.. the slider trades distance against total climbing and nothing else. steepness is currently reported but not optimized.
seems like a worthy addition to the objective!
It's telling me to bike on Geary and Divisadero. No thank you I'd rather stay alive.
fair point! it just doesn't know about bike lanes yet, I’ll see about getting the SFMTA bikeway network map from DataSF.
I wonder how that would work here with horribly inaccurate elevation data. I often ride a specific flat straightaway and Strava and other tracking apps always show me pedaling up and down 20-meter pine trunks next to the bike path.
I was wanting something similar to see the fall leaves in the mountains of NC. I wanted to pick roads at the appropriate elevation, where they are in peak, but google maps isn't really geared for that.
Would love an option for the steepest route! I run a lot in SF and try to maximize vertical gain on my routes
Neat! Now find me some hills on my routes in Cambridgeshire, it's flat as a pancake out here
Absolutely love the live profile updating when you swipe from flatter to shorter.
Cool, I used to build this https://github.com/cheeaun/steepless (2014)
When I used to ride around SF on an e-bike, I’d deliberately choose undulating routes so I could climb at max assist speed and then fly down the descents above max assist speed.
someone should make flattendallas.com as a joke
> The slider runs along the whole trade-off between distance and climbing [...] Climbing is cumulative gain
Another mechanism might be a kind of user-defined cost-curve, where a gradual climb to 10 might be preferred over a steep climb to 8, etc.
You want OpenTripPlanner. Their triangle lets the user trade distance, climbing, and safe facilities.
https://github.com/opentripplanner/OpenTripPlanner
https://github.com/opentripplanner/OpenTripPlanner/blob/dev-...
You should consider adding drive as well, some of us have manual transmissions still, although the Bike mode returns pretty reasonable results.
Gradient Descent
As a life-long city cyclist, with a fable for going fast while staying pedantically lawful, I found that my prefered routes are not about avoiding hills, but about:
1. The length of uninterrupted high quality bicycle ways (e.g. no traffic lights crossings etc.), a 2 km uninterrupted path beats a 1 km route with a ton of crossings and traffic lights
2. The quality of the bicycle path surface. I accept a slightly longer path if the road surface doesn't resemble a moon landscape
3. The potential for "chaos" (for a lack of better words) on that route. For example I will take a detour if it avoids going through areas with tourists and taxis, all of whom appear to be surprised by the concept of the bicycle on a bicycle path on a deep existential level.
Of course hills can play a role as well, but that may be more important in some cities than others.
Sorry if this is a stupid question, but isn’t the climb independent of the route?
Your net elevation change is just the difference in altitude between your starting point and your ending point. So yes, it’s independent of route, but that’s not what the term “climb” refers to. It’s not a net elevation change; it’s a cumulative elevation gain, because in bicycling and walking the in‑between parts burn energy. Human legs don’t have regenerative braking, so every time you gain a foot of altitude you don’t get those calories back when you lose a foot of altitude.
Not if there are hills in between. But the delta between A and B is the best you can do, yes.
In addition, while the net elevation change is bounded by the delta, given the choices might be "go up this steep section" vs "go along this gentle incline", one route can be "flatter" between the same endpoints.
I love Trick Dog!
Cool! Any way to toggle on street names on the map?
Lausanne residents play the same game, but with elevators, metros, bridges, stairs and Lime bikes as additional game mechanics. :)
Doesn't Google Maps in bicycle mode already do this?
There are many constraints to satisfy, and avoiding hills is but one of them.
Most of us would take a hill with a protected bike lane over a flat 45mph.
Now do Houston (:->
It’s all just the wiggle lol
you could mathematically find the least bikeable city using this lol
Try downtown to somewhere in Bernal, say Progressive Grounds coffee house.
The flattest route is only 0.2 miles longer than the shortest, but goes from 200ft of climbing to 500ft of climbing, 12% max grade to 22% max grade.
Apple maps picks the shortest every fucking time.