On scalable DCEL overlay operations

Abstract The Doubly Connected Edge List (DCEL) is an edge-list structure widely used in spatial applications, primarily for planar topological and geometric computations. However, it is also applicable to various types of data, including 3D models and geographic data. An essential operation is the overlay operation , which combines the DCELs of two input polygon layers and can easily support spatial queries on polygons like the intersection, union, and difference between these layers. However, existing techniques for spatial overlay operations suffer from two main limitations. First, they fail to handle many large datasets practically used in real applications. Second, they cannot handle arbitrary spatial lines that practically form polygons, e.g., city blocks, but they are given as a set of scattered lines. This work proposes a distributed and scalable way to compute the overlay operation and its related supported queries. Our operations also support arbitrary spatial lines through a scalable polygonization process. We address the issues of efficiently distributing the lines and overlay operators and offer various optimizations that improve performance. Our experiments demonstrate that the proposed scalable solution can efficiently compute the overlay of large real datasets.

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Publication Details

Journal
GeoInformatica
Published
2025-04-23
DOI
https://doi.org/10.1007/s10707-025-00539-x
Primary Topic
Algorithms and Data Compression
Type
article
Field-Weighted Citation Impact
0.00

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article

On scalable DCEL overlay operations

Vassilis J. Tsotras, Amr Magdy, Laila Abdelhafeez, Goce Trajcevski et al.
GeoInformatica
Algorithms and Data Compression
article

On scalable DCEL overlay operations

Vassilis J. Tsotras, Amr Magdy, Laila Abdelhafeez, Goce Trajcevski, Andres Calderon-Romero
article en

Abstract

Abstract The Doubly Connected Edge List (DCEL) is an edge-list structure widely used in spatial applications, primarily for planar topological and geometric computations. However, it is also applicable to various types of data, including 3D models and geographic data. An essential operation is the overlay operation , which combines the DCELs of two input polygon layers and can easily support spatial queries on polygons like the intersection, union, and difference between these layers. However, existing techniques for spatial overlay operations suffer from two main limitations. First, they fail to handle many large datasets practically used in real applications. Second, they cannot handle arbitrary spatial lines that practically form polygons, e.g., city blocks, but they are given as a set of scattered lines. This work proposes a distributed and scalable way to compute the overlay operation and its related supported queries. Our operations also support arbitrary spatial lines through a scalable polygonization process. We address the issues of efficiently distributing the lines and overlay operators and offer various optimizations that improve performance. Our experiments demonstrate that the proposed scalable solution can efficiently compute the overlay of large real datasets.

GeoInformaticaVol. 29(3)
University of California, Riverside (US), Iowa State University (US), Pontificia Universidad Javeriana (CO)
Google
Openalex Percentile: Top 96%
Algorithms and Data Compression
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