The Impact of Data Science on Geography: A Review with Optimization Algorithms

Roberto de Oliveira Machado

2025

Abstract

We conducted a systematic review using the PRISMA methodology, analyzing 2,996 studies and synthesizing 41 to explore the evolution of data science and its integration into geography. Optimization algorithms were employed to enhance the efficiency and precision of literature selection. Our findings reveal that data science has evolved over five decades, facing challenges such as the integration of diverse spatial data and the increasing demand for advanced computational skills. In the field of geography, data science emphasizes interdisciplinary collaboration and methodological innovation. Techniques like large-scale spatial data analysis and predictive algorithms hold promise for applications in natural disaster management and transportation optimization, enabling faster and more effective responses. These advancements highlight data science’s pivotal role in solving complex spatial problems. This study contributes to the application of optimization algorithms in systematic reviews and underscores the necessity for deeper integration of data science into geography. Key contributions include identifying challenges in managing heterogeneous spatial data and promoting advanced analytical capabilities. The intersection of data science and geography leads to significant improvements in disaster management and transportation efficiency, fostering more sustainable and impactful environmental solutions.

Paper Citation

in Harvard Style

Machado R. (2025). The Impact of Data Science on Geography: A Review with Optimization Algorithms. In Proceedings of the 11th International Conference on Geographical Information Systems Theory, Applications and Management - Volume 1: GISTAM; ISBN 978-989-758-741-2, SciTePress, pages 219-230. DOI: 10.5220/0013464200003935

in Bibtex Style

@conference{gistam25,
author={Roberto Machado},
title={The Impact of Data Science on Geography: A Review with Optimization Algorithms},
booktitle={Proceedings of the 11th International Conference on Geographical Information Systems Theory, Applications and Management - Volume 1: GISTAM},
year={2025},
pages={219-230},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013464200003935},
isbn={978-989-758-741-2},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 11th International Conference on Geographical Information Systems Theory, Applications and Management - Volume 1: GISTAM
TI - The Impact of Data Science on Geography: A Review with Optimization Algorithms
SN - 978-989-758-741-2
AU - Machado R.
PY - 2025
SP - 219
EP - 230
DO - 10.5220/0013464200003935
PB - SciTePress