Graph theory applications for advanced geospatial modelling and decision-making

Geospatial sciences (GS) include a wide range of applications, from environmental monitoring to infrastructure development, as well as location-based analysis and services. Notably, graph theory algorithms have emerged as indispensable tools in GS because of their capability to model and analyse spa...

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Bibliographic Details
Published in:Applied geomatics 2024-12, Vol.16 (4), p.799-812
Main Authors: Ghosh, Surajit, Mallick, Archita, Chowdhury, Anuva, De Sarkar, Kounik, Mukherjee, Jayesh
Format: Article
Language:English
Subjects:
Disaster studies
Earth and Environmental Science
Environmental management
Environmental monitoring
Geographical Information Systems/Cartography
Geography
Geophysics/Geodesy
International organizations
Measurement Science and Instrumentation
Remote Sensing/Photogrammetry
Resource management
Review
Spatial analysis
Surveying
Sustainability
Sustainable development
Sustainable Development Goals
Theories
Urban planning
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Summary:Geospatial sciences (GS) include a wide range of applications, from environmental monitoring to infrastructure development, as well as location-based analysis and services. Notably, graph theory algorithms have emerged as indispensable tools in GS because of their capability to model and analyse spatial relationships efficiently. This article underscores the critical role of graph theory applications in addressing real-world geospatial challenges, emphasising their significance and potential for future innovations in advanced spatial analytics, including the digital twin concept. The analysis shows that researchers from 58 countries have contributed to exploring graph theory and its application over 37 years through more than 700 research articles. A comprehensive collection of case studies has been showcased to provide an overview of graph theory’s diverse and impactful applications in advanced geospatial research across various disciplines (transportation, urban planning, environmental management, ecology, disaster studies and many more) and their linkages to the United Nations Sustainable Development Goals (UN SDGs). Thus, the interdisciplinary nature of graph theory can foster an understanding of the association among different scientific domains for sustainable resource management and planning.
ISSN:1866-9298
1866-928X
DOI:10.1007/s12518-024-00586-3