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Geographic Information Systems (GIS) operate across three levels of application, each representing an increasing degree of complexity: data management, analysis, and prediction. These levels reflect the expanding functionality and versatility of GIS technology in handling spatial data for diverse purposes.Data ManagementAt its foundational level, GIS serves as a tool for data management, enabling the input, storage, retrieval, and organization of spatial data. This level is often employed in...
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Geographic Information Systems (GIS) are tools for storing, analyzing, and displaying spatial data alongside related attributes. Unlike traditional information systems that address general queries, GIS incorporates spatial components, enabling users to answer "where" and "how far." For example, GIS can process housing data linked to geographic locations like zip codes, allowing insights into population density or housing distribution through thematic maps.GIS integrates technologies such as...
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Developing Campus Digital Twin Using Interactive Visual Analytics Approach.

Xinyue Ye1, Suphanut Jamonnak2, Shannon Van Zandt1

  • 1Department of Landscape Architecture and Urban Planning & Center for Geospatial Sciences, Applications and Technology, Texas A&M University, College Station, TX, 77840, USA.

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Summary
This summary is machine-generated.

This study presents a new visual analytics system to address challenges in implementing Digital Twins (DTs) for the built environment. The system uses enrollment data to simulate campus capacity, improving efficiency and decision-making.

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Area of Science:

  • Digitalization and Smart Cities
  • Built Environment Informatics
  • Spatial-Temporal Data Analysis

Background:

  • Digital Twins (DTs) offer significant potential for enhancing efficiency and decision-making in the built environment.
  • Current DT implementation faces challenges including cost, complexity, interoperability, and data integration.

Purpose of the Study:

  • To introduce a novel interactive visual analytics system designed to overcome common Digital Twin implementation hurdles.
  • To demonstrate the system's application in simulating class distribution and campus building capacity.

Main Methods:

  • Development of an interactive visual analytics system for Digital Twin applications.
  • Leveraging university enrollment data, transformed into a spatial-temporal format.
  • Case study analysis focusing on simulating class distribution and campus resource utilization.

Main Results:

  • The system effectively addresses challenges related to cost, complexity, and data integration in DT development.
  • Demonstrated adaptability and real-world applicability through a university campus case study.
  • Successful simulation of class distribution and building capacity, optimizing resource utilization.

Conclusions:

  • The developed visual analytics system provides a practical solution for implementing Digital Twins in the built environment.
  • The approach facilitates informed decision-making regarding spatial-temporal resource allocation and campus planning.
  • Highlights the potential of interactive visual analytics for advancing Digital Twin technology in urban and campus settings.