实现空间数字孪生:技术、挑战和未来研究方向

IF 2.1 4区 地球科学 Q3 IMAGING SCIENCE & PHOTOGRAPHIC TECHNOLOGY
Mohammed Eunus Ali, Muhammad Aamir Cheema, Tanzima Hashem, Anwaar Ulhaq, Muhammad Ali Babar
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引用次数: 0

摘要

数字孪生(DT)是物理对象或系统的虚拟复制品,用于监控、分析和优化其行为和特征。空间数字孪生(SDT)是数字孪生的一种特殊类型,它强调物理实体的地理空间方面,包含精确的位置和尺寸属性,以全面了解其空间环境。随着近年来空间技术的进步以及人工智能(AI)和机器学习(ML)等其他计算技术的突破,SDTs 的市场规模预计将上升到 250 亿美元,涵盖广泛的应用领域。现有研究大多集中在 DT 上,往往未能涉及构建 SDT 所必需的空间技术。目前对 SDT 的研究主要集中在分析其在不同应用领域的潜在影响和机遇。由于构建 SDT 是一个复杂的过程,需要多种空间计算技术,因此对于这一跨学科领域的从业人员和研究人员来说,要掌握 SDT 使能技术的基本细节并非易事。在本文中,我们首次以分层方法(从数据采集到可视化)系统分析了与构建 SDT 相关的各种空间技术。更具体地说,我们将 SDT 的技术堆栈分为五个不同的技术层:(i) 数据采集和处理;(ii) 数据集成、编目和元数据管理;(iii) 数据建模、数据库管理及大数据分析系统;(iv) 地理信息系统(GIS)软件、地图及应用程序接口;以及 (v) 可视化、查询、挖掘、模拟和预测等关键功能组件。此外,我们还讨论了如何有效利用人工智能/ML、区块链和云计算等现代技术来支持和增强 SDT。最后,我们确定了 SDTs 的一系列研究挑战和机遇。本著作明确区分了 SDT 与传统 DT,确定了 SDT 的独特应用,概述了 SDT 的基本技术组件,并提出了 SDT 的未来发展愿景和面临的挑战,是 SDT 研究人员和从业人员的重要资源。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Enabling Spatial Digital Twins: Technologies, Challenges, and Future Research Directions

Enabling Spatial Digital Twins: Technologies, Challenges, and Future Research Directions

A Digital Twin (DT) is a virtual replica of a physical object or system, created to monitor, analyze, and optimize its behavior and characteristics. A Spatial Digital Twin (SDT) is a specific type of digital twin that emphasizes the geospatial aspects of the physical entity, incorporating precise location and dimensional attributes for a comprehensive understanding of its spatial environment. With the recent advancement in spatial technologies and breakthroughs in other computing technologies such as Artificial Intelligence (AI) and Machine Learning (ML), the SDTs market is expected to rise to 25 billion, covering a wide range of applications. The majority of existing research focuses on DTs and often fails to address the necessary spatial technologies essential for constructing SDTs. The current body of research on SDTs primarily concentrates on analyzing their potential impact and opportunities within various application domains. As building an SDT is a complex process and requires a variety of spatial computing technologies, it is not straightforward for practitioners and researchers of this multi-disciplinary domain to grasp the underlying details of enabling technologies of the SDT. In this paper, we are the first to systematically analyze different spatial technologies relevant to building an SDT in a layered approach (starting from data acquisition to visualization). More specifically, we present the tech stack of SDTs into five distinct layers of technologies: (i) data acquisition and processing; (ii) data integration, cataloging, and metadata management; (iii) data modeling, database management & big data analytics systems; (iv) Geographic Information System (GIS) software, maps, & APIs; and (v) key functional components such as visualizing, querying, mining, simulation, and prediction. Moreover, we discuss how modern technologies such as AI/ML, blockchains, and cloud computing can be effectively utilized in enabling and enhancing SDTs. Finally, we identify a number of research challenges and opportunities in SDTs. This work serves as an important resource for SDT researchers and practitioners as it explicitly distinguishes SDTs from traditional DTs, identifies unique applications, outlines the essential technological components of SDTs, and presents a vision for their future development along with the challenges that lie ahead.

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来源期刊
CiteScore
8.20
自引率
2.40%
发文量
38
期刊介绍: PFG is an international scholarly journal covering the progress and application of photogrammetric methods, remote sensing technology and the interconnected field of geoinformation science. It places special editorial emphasis on the communication of new methodologies in data acquisition and new approaches to optimized processing and interpretation of all types of data which were acquired by photogrammetric methods, remote sensing, image processing and the computer-aided interpretation of such data in general. The journal hence addresses both researchers and students of these disciplines at academic institutions and universities as well as the downstream users in both the private sector and public administration. Founded in 1926 under the former name Bildmessung und Luftbildwesen, PFG is worldwide the oldest journal on photogrammetry. It is the official journal of the German Society for Photogrammetry, Remote Sensing and Geoinformation (DGPF).
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