Analyzing digital 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 coordinates of summits, from input data set, such as the Digital Elevation Model (DEM) of the Earth. Choosing the method to use for mountain peaks detection depends on the requirements of the application at hand, but the decision is helped also by the availability of rigorous comparison among the different methods. In this paper, we propose an approach for such a comparison and present the results obtained evaluating the best known methods form the literature in an area of Switzerland.
Algorithms for mountain peaks discovery: A comparison
Torres R. N.;Milani F.;Fraternali P.
2019-01-01
Abstract
Analyzing digital 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 coordinates of summits, from input data set, such as the Digital Elevation Model (DEM) of the Earth. Choosing the method to use for mountain peaks detection depends on the requirements of the application at hand, but the decision is helped also by the availability of rigorous comparison among the different methods. In this paper, we propose an approach for such a comparison and present the results obtained evaluating the best known methods form the literature in an area of Switzerland.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
