Data Science for Geographic Information Systems

05/07/2024

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.

Autores da comunidade :

• 

  N

  Nuno Fachada

  ist145239

  Afiliações e fontes

  IST > LARSYS

  Laboratório de Robótica e Sistemas em Engenharia e Ciência

VoR - Versão publicada

IEEE

https://ieeexplore.ieee.org/document/10624902

2024 8th International Young Engineers Forum on Electrical and Computer Engineering (YEF-ECE)

Caparica, Portugal

05/07/2024

05/07/2024

1

7

979-8-3503-8764-3

10.1109/YEF-ECE62614.2024.10624902

computer-and-information-sciences - Ciências da Computação e da Informação

Palavras-chave

• Machine learning
• Disaster management
• Data science
• Big data
• Data mining
• Remote sensing
• Geographic information systems

eng - Inglês