Digital Twin Technology in Geospatial Science: Trends, Applications and Challenges (Data-Intensive Research)

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Digital Twin Technology in Geospatial Science: Trends, Applications and Challenges (Data-Intensive Research)

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  • 製本 Hardcover:ハードカバー版
  • 言語 ENG
  • 商品コード 9783032203106

Full Description

This book explores utilization of digital twin technology and geospatial science for the digital transformation of urban planning, environmental monitoring, infrastructure, and disaster response using a series of present tools of data collection and applications. It covers transformational impact of digital twins, from their origin to their real-time applications in various domains. It presents real-time case studies focusing on real-world outcomes while addressing the potential risks. It also covers challenging issues related to geospatial twin technology and its solutions to handle relevant challenges. This book comprises several chapters that provide an overview of basic concepts from historical background and architecture twin technology with geospatial data, highlighting its capabilities for modeling, simulation, and optimizing complex systems. It also investigates the technical and ethical barriers to the widespread adoption of digital twin technology in geospatial science. It is a valuable source for students, engineers, professionals, researchers as well as organizations.

Contents

Fundamentals and Architecture OF Digital Twins in the Context of Geospatial Data.- Emergent Technologies Driving Digital Twins for Geo Spatial Science.- Advancements in 3D Modeling and Visualization for GIS Digital Twins.- A Geo-Artificial Intelligence (AI) based Digital Twins: A Synergistic Approach to Spatial Data Science.- A digital simulation tool for Geospatial research metric evaluation.- Digital Twins in Geospatial Science for Urban planning and development.- GIS-based digital twins for Environmental Monitoring and Climate Change.- Infrastructure Management and Asset Tracking using Digital Twins for Geo-spatia science.- A Framework for Object Detection in Digital Twin-Driven Geospatial Systems.- Hypergraph Convolutional Refinement in Latent Space for Underwater Digital Twins.- An Artificial Intelligence based Early Crop Disease Detection for GIS Digital Twins.- The Role of Artificial Intelligence (AI) and Geographic Information Systems (GIS) in Powering Digital Twins for Digital Plant Pathology.- Digital Twins Revolutions-Are we ready for it?.

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