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Article

Geological Map Generalization Driven by Size Constraints

Department of Geography, University of Zurich, Winterthurerstrasse 190, 8057 Zurich, Switzerland
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ISPRS Int. J. Geo-Inf. 2020, 9(4), 284; https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi9040284
Received: 14 February 2020 / Revised: 8 April 2020 / Accepted: 22 April 2020 / Published: 24 April 2020
(This article belongs to the Special Issue Map Generalization)
Geological maps are an important information source used in the support of activities relating to mining, earth resources, hazards, and environmental studies. Owing to the complexity of this particular map type, the process of geological map generalization has not been comprehensively addressed, and thus a complete automated system for geological map generalization is not yet available. In particular, while in other areas of map generalization constraint-based techniques have become the prevailing approach in the past two decades, generalization methods for geological maps have rarely adopted this approach. This paper seeks to fill this gap by presenting a methodology for the automation of geological map generalization that builds on size constraints (i.e., constraints that deal with the minimum area and distance relations in individual or pairs of map features). The methodology starts by modeling relevant size constraints and then uses a workflow consisting of generalization operators that respond to violations of size constraints (elimination/selection, enlargement, aggregation, and displacement) as well as algorithms to implement these operators. We show that the automation of geological map generalization is possible using constraint-based modeling, leading to improved process control compared to current approaches. However, we also show the limitations of an approach that is solely based on size constraints and identify extensions for a more complete workflow. View Full-Text
Keywords: geological maps; map generalization; constraint-based methods; size constraints; generalization operators geological maps; map generalization; constraint-based methods; size constraints; generalization operators
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MDPI and ACS Style

Sayidov, A.; Aliakbarian, M.; Weibel, R. Geological Map Generalization Driven by Size Constraints. ISPRS Int. J. Geo-Inf. 2020, 9, 284. https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi9040284

AMA Style

Sayidov A, Aliakbarian M, Weibel R. Geological Map Generalization Driven by Size Constraints. ISPRS International Journal of Geo-Information. 2020; 9(4):284. https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi9040284

Chicago/Turabian Style

Sayidov, Azimjon, Meysam Aliakbarian, and Robert Weibel. 2020. "Geological Map Generalization Driven by Size Constraints" ISPRS International Journal of Geo-Information 9, no. 4: 284. https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi9040284

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