Data Science for Geographic Information Systems
<|reference_start|>Data Science for Geographic Information Systems: 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 Tr\'oia, 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.<|reference_end|>
@article{oliveira2024data,
    title={Data Science for Geographic Information Systems},
    author={Afonso Oliveira, Nuno Fachada, Jo~ao P. Matos-Carvalho},
    journal={2024 8th International Young Engineers Forum on Electrical and
  Computer Engineering (YEF-ECE), 1-7, IEEE, 2024},
    year={2024},
    doi={10.1109/YEF-ECE62614.2024.10624902},
    archivePrefix={arXiv},
    eprint={2404.03754},
    primaryClass={eess.IV cs.CV physics.geo-ph}
}