Data Science for Geographic Information Systems
Fuente:
arXiv
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| Autores principales: | , , |
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| Formato: | Preprint |
| Publicado: |
2024
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| Materias: | |
| Acceso en línea: | |
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| _version_ | 1866912120648499200 |
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| author | Oliveira, Afonso Fachada, Nuno Matos-Carvalho, João P. |
| author_facet | Oliveira, Afonso Fachada, Nuno Matos-Carvalho, João P. |
| contents | The integration of data science into Geographic Information Systems (GIS) has facilitated the evolution of these tools into complete spatial analysis platforms. The adoption of machine learning and big data techniques has equipped these platforms with the capacity to handle larger amounts of increasingly complex data, transcending the limitations of more traditional approaches. This work traces the historical and technical evolution of data science and GIS as fields of study, highlighting the critical points of convergence between domains, and underlining the many sectors that rely on this integration. A GIS application is presented as a case study in the disaster management sector where we utilize aerial data from Tróia, Portugal, to emphasize the process of insight extraction from raw data. We conclude by outlining prospects for future research in integration of these fields in general, and the developed application in particular. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2404_03754 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Data Science for Geographic Information Systems Oliveira, Afonso Fachada, Nuno Matos-Carvalho, João P. Image and Video Processing Computer Vision and Pattern Recognition Geophysics I.2.10; I.4; I.5; J.2 The integration of data science into Geographic Information Systems (GIS) has facilitated the evolution of these tools into complete spatial analysis platforms. The adoption of machine learning and big data techniques has equipped these platforms with the capacity to handle larger amounts of increasingly complex data, transcending the limitations of more traditional approaches. This work traces the historical and technical evolution of data science and GIS as fields of study, highlighting the critical points of convergence between domains, and underlining the many sectors that rely on this integration. A GIS application is presented as a case study in the disaster management sector where we utilize aerial data from Tróia, Portugal, to emphasize the process of insight extraction from raw data. We conclude by outlining prospects for future research in integration of these fields in general, and the developed application in particular. |
| title | Data Science for Geographic Information Systems |
| topic | Image and Video Processing Computer Vision and Pattern Recognition Geophysics I.2.10; I.4; I.5; J.2 |
| url | https://arxiv.org/abs/2404.03754 |