An Efficient Algorithm for Computing Mountain Prominence in Almost Linear Time

Prominence is one of the most important measurements in topography and mountaineering. This paper describes an efficient, almost linear time algorithm for computing mountain prominence for all peaks on Earth using digital elevation models (DEMs). It builds on top of a classic algorithm and leverages the observation that only a few peaks have their prominence determined by a relatively distant other mountain. Thus, the classic algorithm can be adapted to memorize and use less information without the loss of correctness. The algorithm is demonstrated using 3 arcsecond real-life data from SRTM datasets. Its importance is underscored by the increasing accuracy of Earth mapping methods and the corresponding growth in the amount of data that must be processed to compute prominence.

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Published
2024-09-04
DOI
https://doi.org/10.1109/inista62901.2024.10683840
Primary Topic
Educational Technology and Assessment
Type
article
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article

An Efficient Algorithm for Computing Mountain Prominence in Almost Linear Time

Paul Diac, George Alex Dumitrescu
Educational Technology and Assessment
article

An Efficient Algorithm for Computing Mountain Prominence in Almost Linear Time

Paul Diac, George Alex Dumitrescu
article en

Abstract

Prominence is one of the most important measurements in topography and mountaineering. This paper describes an efficient, almost linear time algorithm for computing mountain prominence for all peaks on Earth using digital elevation models (DEMs). It builds on top of a classic algorithm and leverages the observation that only a few peaks have their prominence determined by a relatively distant other mountain. Thus, the classic algorithm can be adapted to memorize and use less information without the loss of correctness. The algorithm is demonstrated using 3 arcsecond real-life data from SRTM datasets. Its importance is underscored by the increasing accuracy of Earth mapping methods and the corresponding growth in the amount of data that must be processed to compute prominence.

Alexandru Ioan Cuza University (RO)
Climate action
Openalex Percentile: Top 75%
Educational Technology and Assessment
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