Help - Method for Calculating Uncertain Elevations

There are many peaks where the summit elevation is not known precisely. For these cases, this web site stores the elevation as the highest surrounding contour line below the peak on the most detailed topographic map available, and we also store the contour interval. Even worse, a solid majority of key cols used to compute prominence are not surveyed to the nearest foot or meter, so the site stores the lowest full contour line elevation lying above a saddle as its elevation, plus the contour interval.

When creating a peak list based on elevations and/or prominences that are uncertain, there are four general ways to deal with the uncertainty. To illustrate this, imagine Peak X, located on a map with 40-foot contours, and having a summit elevation between 3960 and 4000 feet, and a key col for prominence between 2920 and 2960 feet.

  • Method 1 - “Clean”: No elevation or prominence from the partial contour intervals on either side is assigned. The argument is that since we don’t know anything about the ground inside the summit closed contour or at the saddle,  we should not assume there is any elevation without evidence. Peak X gets an elevation of 3960 feet, and a prominence of 3960 – 2960 = 1000 feet. We are 100% sure that the elevation and prominence are at least these numbers—nothing is overstated. However, the corollary is that these numbers are almost certainly understated.
  • Method 2 - “Average”: We split the difference between the contours at the summit and the saddle. The elevation of Peak X is set to 3980 (3960 + 20, which is half the contour interval), the key col is 2940 feet (2960 – 20), and the prominence is 1040 feet. This method is most likely to be closest to the real numbers, but the numbers will be overstated or understated in a random pattern.
  • Method 3 – “Optimistic”: We give the maximum possible elevation to both the peak and the saddle, based on the contour intervals. Peak X gets 4000 feet of elevation, and its key col gets a value of 2920 feet, and therefore it has an optimistic prominence of 1080 feet. We can state for sure that we are not understating the elevation and prominence of this peak, but it is almost certainly overstated. The main use of this method is when trying to list all peaks above a certain threshold—if you want to be sure you list every single peak that could possibly be at or over 4000 feet of elevation, then Peak X should be shown as a possibility.
  • Method 4 -“Interpolated”: Using this method, an attempt is made to determine the summit and key col elevations by the relative size and position of the contours. If Peak X has a tiny little contour, then it gets an elevation of 3961 feet. If it has a huge contour, bigger across than the interval of the surrounding ones, then it might be assigned 3999 feet. Similarly, if the two 2960 foot contours almost meet at the key col, that could be assigned a value of 2959 feet. Sometimes the Average method is called Interpolated, but my sense is that Interpolation demands some attempt to intelligently see where the value might lie on a spectrum, not just taking an average. Interpolated prominence is not used very much, since it is hard to manually calculate for thousands of peaks, and at the end of the day it is really just guesswork, even if the guesses are somewhat educated.

How This Works on has always used the Clean method for calculating elevations and prominences, and also for building lists. This is a personal preference on the part of webmaster, but it is shared by a number of other mountain data researchers. In cases where the usual threshold for a list is based on the Average method, the threshold is adjusted to make it a Clean list—for example, the Colorado lists on this site us a Clean prominence cutoff of 280 feet, roughly corresponding to the Average cutoff of 300 traditionally used.

Additionally, many lists on this site have “unranked peaks” that show summits that may also be considered, based on methods other than Clean. Elevation-based threshold lists (e.g. the Colorado 14ers, the New Hampshire 4000-footers) have a prominence threshold as well, and this site will always show all peaks above the elevation threshold, and rank just the ones above the prominence threshold. And prominence-based lists show “error range” peaks based on optimistic prominence as unranked peaks on the list.

And, finally, a feature of is that any list with elevations or prominences stored as a contour interval range now allows the user to select the method for displaying the list. At the top of the list will be three links for Clean, Average, and Optimistic methods, and clicking on one of them will re-calculate and re-order the list based on the selected method.

Using this feature may cause minor chaos in the list. Unranked peaks may become ranked, and the order may get all jumbled. Lists that have a fixed number of peaks (such as a “Top 100”) may wind up with more peaks than expected due to the uncertainly.

However, the formal definition and storage of the lists on will remain based on the Clean method, and that is the default for site users who can’t be bothered with all this minutiae. So Front-Runner List statistics, for example, are all based on the Clean version of the list, so a situation where different climbers pursue different versions of the same list is avoided.

A Final Note

Many peaks in the database have precise peak and saddle elevations. This is often the case in places where excellent surveying has been done that has fixed exact locations and elevations for all peaks and saddles. The other situation where this happens is the opposite--if elevations are based on a digital elevation model (DEM), such as the well-known worldwide SRTM database, the elevations are stored without any intervals. In this case, it does not mean the data is 100% accurate, just an approximation too rough to even have a guess as to the accurate interval.

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