1. bookVolume 54 (2022): Issue 1 (January 2022)
Journal Details
License
Format
Journal
eISSN
2450-6966
ISSN
0324-8321
First Published
30 Mar 2015
Publication timeframe
4 times per year
Languages
English
access type Open Access

Algorithm of automatic digital cartographic generalisation with the use of contractive self-mapping

Published Online: 05 Apr 2022
Volume & Issue: Volume 54 (2022) - Issue 1 (January 2022)
Page range: 1 - 10
Received: 27 Jan 2022
Accepted: 17 Mar 2022
Journal Details
License
Format
Journal
eISSN
2450-6966
ISSN
0324-8321
First Published
30 Mar 2015
Publication timeframe
4 times per year
Languages
English
Abstract

The research of modern cartography in the field of digital generalisation focuses on the development of such methods that would be fully automatic and give an unambiguously objective result. Devising them requires specific standards as well as unique and verifiable algorithms. In metric space, a proposal for such a method, based on contractive mapping, the Lipschitz and Cauchy conditions and the Banach theorem, using the Salishchev metric, was presented in the publication (Barańska et al., 2021). The method formulated there is dedicated to linear objects (polylines). The current work is a practical supplement to it. It presents the practical implementation of the algorithm for automatic and objective generalisation. The article describes an operational diagram of the subsequent stages of the proposed generalisation method. In the test example, a binary tree structure of an ordered polyline was created. It was simplified in two selected scales and its shape after generalisation was illustrated. The resulting polyline obtained by the fully automatic method was verified in terms of accuracy.

Keywords

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