Header

UZH-Logo

Maintenance Infos

Geological map generalization driven by size constraints


Sayidov, Azimjon; Aliakbarian, Meysam; Weibel, Robert (2020). Geological map generalization driven by size constraints. ISPRS International Journal of Geo-Information, 9(4):284.

Abstract

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.

Abstract

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.

Statistics

Citations

Dimensions.ai Metrics
1 citation in Web of Science®
2 citations in Scopus®
Google Scholar™

Altmetrics

Downloads

21 downloads since deposited on 28 Apr 2020
10 downloads since 12 months
Detailed statistics

Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:07 Faculty of Science > Institute of Geography
Dewey Decimal Classification:910 Geography & travel
Scopus Subject Areas:Social Sciences & Humanities > Geography, Planning and Development
Physical Sciences > Computers in Earth Sciences
Physical Sciences > Earth and Planetary Sciences (miscellaneous)
Language:English
Date:24 April 2020
Deposited On:28 Apr 2020 10:20
Last Modified:29 Jul 2020 15:05
Publisher:MDPI Publishing
ISSN:2220-9964
OA Status:Gold
Free access at:Publisher DOI. An embargo period may apply.
Publisher DOI:https://doi.org/10.3390/ijgi9040284

Download

Gold Open Access

Download PDF  'Geological map generalization driven by size constraints'.
Preview
Content: Published Version
Language: English
Filetype: PDF
Size: 5MB
View at publisher
Licence: Creative Commons: Attribution 4.0 International (CC BY 4.0)