{"title":"图论在高级地理空间建模和决策中的应用","authors":"Surajit Ghosh, Archita Mallick, Anuva Chowdhury, Kounik De Sarkar, Jayesh Mukherjee","doi":"10.1007/s12518-024-00586-3","DOIUrl":null,"url":null,"abstract":"<div><p>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.</p></div>","PeriodicalId":46286,"journal":{"name":"Applied Geomatics","volume":"16 4","pages":"799 - 812"},"PeriodicalIF":2.3000,"publicationDate":"2024-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Graph theory applications for advanced geospatial modelling and decision-making\",\"authors\":\"Surajit Ghosh, Archita Mallick, Anuva Chowdhury, Kounik De Sarkar, Jayesh Mukherjee\",\"doi\":\"10.1007/s12518-024-00586-3\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>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.</p></div>\",\"PeriodicalId\":46286,\"journal\":{\"name\":\"Applied Geomatics\",\"volume\":\"16 4\",\"pages\":\"799 - 812\"},\"PeriodicalIF\":2.3000,\"publicationDate\":\"2024-09-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Applied Geomatics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://link.springer.com/article/10.1007/s12518-024-00586-3\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"REMOTE SENSING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Applied Geomatics","FirstCategoryId":"1085","ListUrlMain":"https://link.springer.com/article/10.1007/s12518-024-00586-3","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"REMOTE SENSING","Score":null,"Total":0}
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 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.
期刊介绍:
Applied Geomatics (AGMJ) is the official journal of SIFET the Italian Society of Photogrammetry and Topography and covers all aspects and information on scientific and technical advances in the geomatics sciences. The Journal publishes innovative contributions in geomatics applications ranging from the integration of instruments, methodologies and technologies and their use in the environmental sciences, engineering and other natural sciences.
The areas of interest include many research fields such as: remote sensing, close range and videometric photogrammetry, image analysis, digital mapping, land and geographic information systems, geographic information science, integrated geodesy, spatial data analysis, heritage recording; network adjustment and numerical processes. Furthermore, Applied Geomatics is open to articles from all areas of deformation measurements and analysis, structural engineering, mechanical engineering and all trends in earth and planetary survey science and space technology. The Journal also contains notices of conferences and international workshops, industry news, and information on new products. It provides a useful forum for professional and academic scientists involved in geomatics science and technology.
Information on Open Research Funding and Support may be found here: https://www.springernature.com/gp/open-research/institutional-agreements