Geometry, Topology and p-Adic Numbers in Geospatial Data Modelling, Management and Processing: Review and Future Approaches

Abstract. Geometry and topology are both central concepts in geospatial data modelling and management. While geometry is the central concept for computational geometry applications, e.g. to intersect surfaces and solids in 3D space, topology is helpful for many application classes starting from city modelling to subsurface modelling and indoor navigation. Furthermore, p-adic numbers are useful for describing hierarchical processes on topological models. In this paper we first shortly review geometry- and topology-based approaches used for geospatial applications. We then describe our approach on turning geometry “upside down” focusing on topology during the whole process of distributed geospatial computing, data modelling, data management, and simulation. Furthermore, the way to use p-adic numbers for the description of hierarchical processes on topological models is shown for the example of simulation and the idea of p-adic analysis in distributed simulations is presented in the context of topological city and building models. The approach opens new insights such as topological relationships, components, and efficiently studying of the approximate behaviour of processes in the built environment using distributed computational systems. Finally, exemplary applications are presented to underline the importance of this new approach.

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Publication Details

Journal
ISPRS annals of the photogrammetry, remote sensing and spatial information sciences
Published
2024-10-18
DOI
https://doi.org/10.5194/isprs-annals-x-4-2024-51-2024
Primary Topic
Data Management and Algorithms
Type
article
Field-Weighted Citation Impact
0.00

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article

Geometry, Topology and p-Adic Numbers in Geospatial Data Modelling, Management and Processing: Review and Future Approaches

Patrick Erik Bradley, Markus Jahn, Mulhim Al-Doori, Martin Breunig et al.
ISPRS annals of the photogrammetry, remote sensing and spatial information sciences
Data Management and Algorithms
article

Geometry, Topology and p-Adic Numbers in Geospatial Data Modelling, Management and Processing: Review and Future Approaches

Patrick Erik Bradley, Markus Jahn, Mulhim Al-Doori, Martin Breunig, Emmanuel Stefanakis, Paul Vincent Kuper
article en

Abstract

Abstract. Geometry and topology are both central concepts in geospatial data modelling and management. While geometry is the central concept for computational geometry applications, e.g. to intersect surfaces and solids in 3D space, topology is helpful for many application classes starting from city modelling to subsurface modelling and indoor navigation. Furthermore, p-adic numbers are useful for describing hierarchical processes on topological models. In this paper we first shortly review geometry- and topology-based approaches used for geospatial applications. We then describe our approach on turning geometry “upside down” focusing on topology during the whole process of distributed geospatial computing, data modelling, data management, and simulation. Furthermore, the way to use p-adic numbers for the description of hierarchical processes on topological models is shown for the example of simulation and the idea of p-adic analysis in distributed simulations is presented in the context of topological city and building models. The approach opens new insights such as topological relationships, components, and efficiently studying of the approximate behaviour of processes in the built environment using distributed computational systems. Finally, exemplary applications are presented to underline the importance of this new approach.

ISPRS annals of the photogrammetry, remote sensing and spatial information sciencesVol. X-4-2024
Karlsruhe Institute of Technology (DE), University of Calgary (CA), Ajman University (AE)
Deutsche Forschungsgemeinschaft
Sustainable cities and communities
Openalex Percentile: Top 80%
Data Management and Algorithms
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Geometry, Topology and p-Adic Numbers in Geospatial Data Modelling, Management and Processing: Review and Future Approaches — Patrick Erik Bradley, Markus Jahn, et al. · ISPRS annals of the photogrammetry, remote sensing and spatial information sciences (2024) | TGRS Research Map | TGRS