Track papers across labs, topics, and trends.
Search papers, labs, and topics across Lattice.
This paper introduces an efficient algorithm that computes mountain prominence for all peaks on Earth in almost linear time, leveraging digital elevation models (DEMs). By adapting a classic algorithm and utilizing the observation that only a few peaks depend on distant mountains for their prominence, the authors significantly reduce the amount of information needed without sacrificing accuracy. The algorithm's effectiveness is validated using real-life 3 arcsecond data from SRTM datasets, making it a crucial advancement in topographic analysis as mapping methods become increasingly precise.
A groundbreaking algorithm computes mountain prominence for all Earth’s peaks in almost linear time, revolutionizing topographic analysis.
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.