A Deep Learning Model for Identifying Mountain Summits in Digital Elevation Model Data

Analyzing Digital Elevation Model (DEM) data to identify and classify landforms is an important task, which can contribute to improve the availability and quality of public open source cartography and to develop novel applications for tourism and environment monitoring. In the literature, several heuristic algorithms are documented for identifying the features of mountain regions, most notably the coordinate of summits. All these algorithms depend on parameters, which are manually set. In this paper, we explore the use of Deep Learning methods to train a model capable of identifying mountain summits, which learns from a gold standard dataset containing the coordinates of peaks in a region. The model has been trained and tested with Switzerland DEM and peak data.