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...
| Autores principales: | , , , , |
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| Formato: | Journal Article |
| Lenguaje: | Inglés |
| Publicado: |
Springer
2024
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| Materias: | |
| Acceso en línea: | https://hdl.handle.net/10568/158366 |
| _version_ | 1855520790394437632 |
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| author | Ghosh, Surajit Mallick, A. Chowdhury, A. De Sarkar, K. Mukherjee, J. |
| author_browse | Chowdhury, A. De Sarkar, K. Ghosh, Surajit Mallick, A. Mukherjee, J. |
| author_facet | Ghosh, Surajit Mallick, A. Chowdhury, A. De Sarkar, K. Mukherjee, J. |
| author_sort | Ghosh, Surajit |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | 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. |
| format | Journal Article |
| id | CGSpace158366 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2024 |
| publishDateRange | 2024 |
| publishDateSort | 2024 |
| publisher | Springer |
| publisherStr | Springer |
| record_format | dspace |
| spelling | CGSpace1583662025-10-26T12:54:41Z Graph theory applications for advanced geospatial modelling and decision-making Ghosh, Surajit Mallick, A. Chowdhury, A. De Sarkar, K. Mukherjee, J. spatial data modelling decision making algorithms geographical information systems sustainable development goals urban planning rural planning environmental management case studies 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. 2024-12 2024-10-31T21:25:11Z 2024-10-31T21:25:11Z Journal Article https://hdl.handle.net/10568/158366 en Limited Access Springer Ghosh, Surajit; Mallick, A.; Chowdhury, A.; De Sarkar, K.; Mukherjee, J. 2024. Graph theory applications for advanced geospatial modelling and decision-making. Applied Geomatics, 16(4):799-812. [doi: https://doi.org/10.1007/s12518-024-00586-3] |
| spellingShingle | spatial data modelling decision making algorithms geographical information systems sustainable development goals urban planning rural planning environmental management case studies Ghosh, Surajit Mallick, A. Chowdhury, A. De Sarkar, K. Mukherjee, J. Graph theory applications for advanced geospatial modelling and decision-making |
| title | Graph theory applications for advanced geospatial modelling and decision-making |
| title_full | Graph theory applications for advanced geospatial modelling and decision-making |
| title_fullStr | Graph theory applications for advanced geospatial modelling and decision-making |
| title_full_unstemmed | Graph theory applications for advanced geospatial modelling and decision-making |
| title_short | Graph theory applications for advanced geospatial modelling and decision-making |
| title_sort | graph theory applications for advanced geospatial modelling and decision making |
| topic | spatial data modelling decision making algorithms geographical information systems sustainable development goals urban planning rural planning environmental management case studies |
| url | https://hdl.handle.net/10568/158366 |
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