Issue |
BIO Web Conf.
Volume 173, 2025
International Scientific Conference “Fundamental and Applied Scientific Research in the Development of Agriculture in the Far East” (AFE-2024)
|
|
---|---|---|
Article Number | 03025 | |
Number of page(s) | 12 | |
Section | Biology and Chemistry of Soil and Water | |
DOI | https://doi.org/10.1051/bioconf/202517303025 | |
Published online | 23 April 2025 |
Process of cartographic generalization in maps digitalization
1
TIIAME National Research University,
Tashkent,
100000, Uzbekistan
2
National University of Uzbekistan named after Mirzo Ulugbek,
Tashkent,
100174, Uzbekistan
3
Tashkent University of Architecture and Construction,
Tashkent,
100069, Uzbekistan
* Corresponding author: minashkina61@gmail.com
This article examines the results of a comparison of two methods of cartographic generalization when creating maps using the traditional method, i.e. “manually” and utilizing automated generalization techniques during computer-based map creation. Generalization is an essential characteristic of any map. Even the most detailed large-scale maps involve a degree of generalization, as representing every object with complete precision is impractical. This text explores the concept of automated cartographic generalization, highlighting its benefits and limitations, as well as the capabilities of computer technologies and specific software in the map-making process. Cartographic generalization creates certain accents and helps to show qualitatively new information on the map. Map compilation is the production of the original map, which involves creating a mathematical framework, incorporating content derived from cartographic materials with appropriate generalization, and finalizing the cartographic representation. The initial map compiler refers to the original map developed through this compilation process, on which the content elements are applied in accordance with the requirements of the editorial documents.
© The Authors, published by EDP Sciences, 2025
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.