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Recognition of group patterns in geological maps by building similarity networks

Sayidov, Azimjon; Weibel, Robert; Leyk, Stefan (2022). Recognition of group patterns in geological maps by building similarity networks. Geocarto International, 37(2):607-626.

Abstract

The recognition of structures is fundamental to map generalization, furnishing structural information that assists in choosing and parameterizing generalization operators. We specifically focus on the process of recognizing groups of small polygons in geological maps as a prerequisite to subsequent aggregation or typification operators. Proximity between polygons represents an essential criterion in identifying neighboring map objects. Here, network-based analysis is used for effective definition and refinement of candidate group members, applying criteria such as the distance between polygons, polygon size, shape, orientation, and feature attributes such as rock type. Starting off from the Delaunay triangulation of the polygon centroids, the global and local long edges, which initially define the network, are removed. The modified network is loaded with additional criteria, and edges are kept or removed based on the local similarities of the polygons they connect. This approach leads to more homogeneous, meaningful groups of polygon features in geological maps.

Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:07 Faculty of Science > Institute of Geography
06 Faculty of Arts > Zurich Center for Linguistics
Dewey Decimal Classification:910 Geography & travel
Scopus Subject Areas:Social Sciences & Humanities > Geography, Planning and Development
Physical Sciences > Water Science and Technology
Uncontrolled Keywords:Geography, Planning and Development, Water Science and Technology
Language:English
Date:17 January 2022
Deposited On:28 Apr 2020 10:13
Last Modified:23 Jan 2025 02:37
Publisher:Taylor & Francis
ISSN:1752-0762
OA Status:Closed
Publisher DOI:https://doi.org/10.1080/10106049.2020.1730449

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