Elevation gain variance
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Elevation gain variance
We rode the same trail today with a large variance between results.
Wahoo ELEMNT Bolt. 220 ft
Apple Watch 7. 385 ft
i expect a difference between devices but this seems rather large. At a quick glance the elevation map profiles appear similar. Anyone know if they use different algorithms?
Wahoo ELEMNT Bolt. 220 ft
Apple Watch 7. 385 ft
i expect a difference between devices but this seems rather large. At a quick glance the elevation map profiles appear similar. Anyone know if they use different algorithms?
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We rode the same trail today with a large variance between results.
Wahoo ELEMNT Bolt. 220 ft
Apple Watch 7. 385 ft
i expect a difference between devices but this seems rather large. At a quick glance the elevation map profiles appear similar. Anyone know if they use different algorithms?
Wahoo ELEMNT Bolt. 220 ft
Apple Watch 7. 385 ft
i expect a difference between devices but this seems rather large. At a quick glance the elevation map profiles appear similar. Anyone know if they use different algorithms?
1) the barometric altimeter
2) GPS altitude - essentially useless
3) elevation from maps by correlating GPS location
different software will absolutely use different methods to reconcile the variation between these three sources.
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both devices have a barometric altimeter and GPS. what apps/software are you using to view the results? many map based systems (e.g. strava) will correct the device altitude readings based on map data. said map data varies in quality greatly, so you have three different potential altitude sources:
1) the barometric altimeter
2) GPS altitude - essentially useless
3) elevation from maps by correlating GPS location
different software will absolutely use different methods to reconcile the variation between these three sources.
1) the barometric altimeter
2) GPS altitude - essentially useless
3) elevation from maps by correlating GPS location
different software will absolutely use different methods to reconcile the variation between these three sources.
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We rode the same trail today with a large variance between results.
Wahoo ELEMNT Bolt. 220 ft
Apple Watch 7. 385 ft
i expect a difference between devices but this seems rather large. At a quick glance the elevation map profiles appear similar. Anyone know if they use different algorithms?
Wahoo ELEMNT Bolt. 220 ft
Apple Watch 7. 385 ft
i expect a difference between devices but this seems rather large. At a quick glance the elevation map profiles appear similar. Anyone know if they use different algorithms?
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My personal rule of thumb has always been to mix-n-match using the best numbers. One gives more elevation, the other more miles, use them both and toss out the lower numbers.
I would guess that for the vast majority the numbers really don’t matter. If it helps to make you feel better about yourself, who cares.
I remember when our boss wanted everyone in our dept to participate in recording daily steps. We all got clip on pedometers. I’d clip it on and drive to work. I was breezing through each day until I noticed my drive registered around 4000 steps each way. Oh well, I guess I deserve some credit for fighting traffic for almost an hour to work and an hour back. There were no prizes, but 10,000 steps were never so easy.
John
I would guess that for the vast majority the numbers really don’t matter. If it helps to make you feel better about yourself, who cares.
I remember when our boss wanted everyone in our dept to participate in recording daily steps. We all got clip on pedometers. I’d clip it on and drive to work. I was breezing through each day until I noticed my drive registered around 4000 steps each way. Oh well, I guess I deserve some credit for fighting traffic for almost an hour to work and an hour back. There were no prizes, but 10,000 steps were never so easy.
John
Last edited by 70sSanO; 07-17-22 at 01:26 AM.
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I gave up on recording with my Garmin Vivoactive. Always gave me wildly inflated #'s compared to mapping software like ridewithgps.
I want accuracy not a pat on the back.
I want accuracy not a pat on the back.
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Lots of folks buying lots of electronics that are essentially random number generators and then spending their time trying to figure out why they make little sense. Unless you figure out how to calibrate/verify what these "instruments" (being generous in many cases) are indicating, there's no reason to assume they're offering useful data. They may be consistent within themselves (i.e. they have precision) and may be useful under that umbrella(only), but without verified accuracy they have little connection to reality..or other devices. Toss in the software that lays on top of all theses devices..yikes. (imho..as a retired chemist that is familiar with real instrumentation as well as gage R&R instrument capability analysis)
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Who cares which is correct? If they are consistent in their reporting, then you'll know which route has more climbing and descending in it.
I wouldn't expect two different devices to report elevation gain loss the same way. If we really got to talking about it I doubt that even we would agree what constitutes elevation gain or loss.
If I'm on a fairly level road that goes up and down a foot 20 times over the course of a mile do I count that as 20 feet of gain/loss? What if it's 5 feet 20 times in one mile?
I wouldn't expect two different devices to report elevation gain loss the same way. If we really got to talking about it I doubt that even we would agree what constitutes elevation gain or loss.
If I'm on a fairly level road that goes up and down a foot 20 times over the course of a mile do I count that as 20 feet of gain/loss? What if it's 5 feet 20 times in one mile?
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#10
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If I'm on a fairly level road that goes up and down a foot 20 times over the course of a mile do I count that as 20 feet of gain/loss?
Sure, as it's valid elevation gain/loss, but you'd never measure it accurately and, as you noted, it's not worth even considering.
What if it's 5 feet 20 times in one mile?
Then it's 100 feet, you'd still never measure it accurately.
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Where I see a big difference between map sources is between Google Maps and RWGPS. I’ll get, say a 49 mile route from the former and then plot in on tha latter. The former will show something like 2,500’. The latter has shown nearly 1,000’ more.
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Who cares which is correct? If they are consistent in their reporting, then you'll know which route has more climbing and descending in it.
I wouldn't expect two different devices to report elevation gain loss the same way. If we really got to talking about it I doubt that even we would agree what constitutes elevation gain or loss.
If I'm on a fairly level road that goes up and down a foot 20 times over the course of a mile do I count that as 20 feet of gain/loss? What if it's 5 feet 20 times in one mile?
I wouldn't expect two different devices to report elevation gain loss the same way. If we really got to talking about it I doubt that even we would agree what constitutes elevation gain or loss.
If I'm on a fairly level road that goes up and down a foot 20 times over the course of a mile do I count that as 20 feet of gain/loss? What if it's 5 feet 20 times in one mile?
if you really dig into it, it just gets worse. the underlying data that strava uses for elevation correction is not that great. i've compared it to known-good data (surveys and other directly-measured elevation datums) and it's pretty far off in places. 15 to 20 percent error in these stats is pretty regular, whatever the source.
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yep. different underlying terrain models, different degrees of precision in those models and the way they interpolate the "2D" points onto the underlying model... and then just the inherent problems of that methodology. it took RwGPS about 10 years to not register riding across the golden gate bridge as dropping 200' to sea level, and then abruptly climbing 200' back up. an extreme example, but 400 additional feet of climbing per round trip.
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yep. different underlying terrain models, different degrees of precision in those models and the way they interpolate the "2D" points onto the underlying model... and then just the inherent problems of that methodology. it took RwGPS about 10 years to not register riding across the golden gate bridge as dropping 200' to sea level, and then abruptly climbing 200' back up. an extreme example, but 400 additional feet of climbing per round trip.
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https://ridewithgps.com/help/advance...tten-elevation
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Precision is "repeatability"(in the science and engineering worlds). An instrument can be highly precise and yet be completely inaccurate at the same time. Accuracy is an instrument's ability to measure a correct or theoretically correct value. All measurements are estimates of some true value. A good estimate of a true value is an average of multiple measurements.
Maps or reported elevation estimates need to be accurate. With any luck, they were developed with accurate and precise instruments.
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My personal rule of thumb has always been to mix-n-match using the best numbers. One gives more elevation, the other more miles, use them both and toss out the lower numbers.
I would guess that for the vast majority the numbers really don’t matter. If it helps to make you feel better about yourself, who cares.
I remember when our boss wanted everyone in our dept to participate in recording daily steps. We all got clip on pedometers. I’d clip it on and drive to work. I was breezing through each day until I noticed my drive registered around 4000 steps each way. Oh well, I guess I deserve some credit for fighting traffic for almost an hour to work and an hour back. There were no prizes, but 10,000 steps were never so easy.
John
I would guess that for the vast majority the numbers really don’t matter. If it helps to make you feel better about yourself, who cares.
I remember when our boss wanted everyone in our dept to participate in recording daily steps. We all got clip on pedometers. I’d clip it on and drive to work. I was breezing through each day until I noticed my drive registered around 4000 steps each way. Oh well, I guess I deserve some credit for fighting traffic for almost an hour to work and an hour back. There were no prizes, but 10,000 steps were never so easy.
John
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Not to be too anal(or pedantic if the last word was aced), but when talking about accuracy and precision it's best to use specific/correct terms.
Precision is "repeatability"(in the science and engineering worlds). An instrument can be highly precise and yet be completely inaccurate at the same time. Accuracy is an instrument's ability to measure a correct or theoretically correct value. All measurements are estimates of some true value. A good estimate of a true value is an average of multiple measurements.
Maps or reported elevation estimates need to be accurate. With any luck, they were developed with accurate and precise instruments.
Precision is "repeatability"(in the science and engineering worlds). An instrument can be highly precise and yet be completely inaccurate at the same time. Accuracy is an instrument's ability to measure a correct or theoretically correct value. All measurements are estimates of some true value. A good estimate of a true value is an average of multiple measurements.
Maps or reported elevation estimates need to be accurate. With any luck, they were developed with accurate and precise instruments.
in addition to the lack of spatial resolution, when the data is generated by remote sensing (as it usually is) things like trees, buildings, etc can make the sampled point just completely inaccurate. combine that with the low resolution, possible inaccuracy of the placement of the road on the map, the user's GPS position on the map, which may or may not be snapped to the road... and it's actually surprising to me that they aren't off by even MORE!
here's an example of a couple block spin around my neighborhood. RwGPS terrain model thinks it's a 1.3 mile segment with 170 feet of climbing. it's actually 1.25 miles (no way to know if RwGPS knows that but is just rounding...) and 239 feet of climbing. the actual vertical gain is almost 41 percent more! i've seen errors like this all over the place, with both strava and RwGPS, but there aren't all that many places in the world that "good" data is easy to come by.
Last edited by mschwett; 07-17-22 at 02:47 PM.
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I have also found that the degree to which I round up is in direct proportion to my age.
So far I have not yet resorted to metric distances. However, I anticipate doing so sometime in the future.
I also think many non-cyclists will be more impressed with kilometers, it just sounds further.
John
Edit added: Or a metric half century.
Last edited by 70sSanO; 07-17-22 at 03:36 PM.
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...imprecise..while I get your meaning..imprecise, precise and precision are very different words. The latter, in science, is basically a reserved term/professional jargon that only involves measurement repeatability. Detail and "precision" have no relationship. What the non-science/engineering world does with these words, in their own environment, including Webster's Dictionary, is up to them.
As for for my initial comments.. the random number generation applies to watts..calories burned, watches counting steps...... The devices may be useful in terms of individual unit precision, comparing output to other's results or reality will have limited success.
As for for my initial comments.. the random number generation applies to watts..calories burned, watches counting steps...... The devices may be useful in terms of individual unit precision, comparing output to other's results or reality will have limited success.
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yes. you're correct. the issue with the terrain models is actually not so simple - they are precise in the sense of repeatability - if you project the same 2d coordinate onto the model you will of course always get exactly the same result. but the frequency of sampling of the underlying data is very poor, which makes it inaccurate in a way that could also be described as imprecise. not in the sense of repeatability but in the sense of "lacking exactness and accuracy of expression or detail." (per the definition of imprecise.)
in addition to the lack of spatial resolution, when the data is generated by remote sensing (as it usually is) things like trees, buildings, etc can make the sampled point just completely inaccurate. combine that with the low resolution, possible inaccuracy of the placement of the road on the map, the user's GPS position on the map, which may or may not be snapped to the road... and it's actually surprising to me that they aren't off by even MORE!
here's an example of a couple block spin around my neighborhood. RwGPS terrain model thinks it's a 1.3 mile segment with 170 feet of climbing. it's actually 1.25 miles (no way to know if RwGPS knows that but is just rounding...) and 239 feet of climbing. the actual vertical gain is almost 41 percent more! i've seen errors like this all over the place, with both strava and RwGPS, but there aren't all that many places in the world that "good" data is easy to come by.
in addition to the lack of spatial resolution, when the data is generated by remote sensing (as it usually is) things like trees, buildings, etc can make the sampled point just completely inaccurate. combine that with the low resolution, possible inaccuracy of the placement of the road on the map, the user's GPS position on the map, which may or may not be snapped to the road... and it's actually surprising to me that they aren't off by even MORE!
here's an example of a couple block spin around my neighborhood. RwGPS terrain model thinks it's a 1.3 mile segment with 170 feet of climbing. it's actually 1.25 miles (no way to know if RwGPS knows that but is just rounding...) and 239 feet of climbing. the actual vertical gain is almost 41 percent more! i've seen errors like this all over the place, with both strava and RwGPS, but there aren't all that many places in the world that "good" data is easy to come by.
When calculating vertical gain, the length of your ruler has a significant impact on the answer. Even if your elevation data are perfect.
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i’ve done it before by projecting the line onto the surface created by the contour data and the using a script to sum any positive differences between subsequent points on the line. the projection algorithm introduces vertices wherever there needs to be a kink last a certain degree of variance.
it’s worth noting that the contour data is itself created by interpolation from a (very, very large) number of points, so it’s not perfect either. but it’s within inches in most of the dozens of locations that i’ve spot checked it against surveys of actual pieces of property. data like this is very hard to come by at the scale needed for something like cycling.
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RWGPS introduced a "Flatten Elevation" tool a couple-few years back to eliminate the up and down spikes from tunneled hills and gorges. It's a premium feature. I haven't used it(not a premium acct), but the functionality is pretty straight forward. They have a demo of it on their site somewhere.
https://ridewithgps.com/help/advance...tten-elevation
https://ridewithgps.com/help/advance...tten-elevation
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https://ridewithgps.com/news/5657-br...a-improve?otu=
worth noting that the auto version doesn’t work for rides, just routes:
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My ignore list is up to 88..and continues it's slow growth.
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