Integrating Satellite Images Segmentation and Electrical Infrastructure Data to Identify Possible Urban Irregularities in Power Grid

Álisson Alves, Álisson Alves, Luísa Souza, Luísa Souza, Luiz Cho-Luck, Raniere Lima, Carlos Augusto, Wesley Marinho, Wesley Marinho, Rafael Capuano, Bruno Costa, Marina Siqueira, Jesaías Silva, Raul Paradeda, Pablo Alsina

2025

Abstract

Managing urban expansion and its impact on electrical infrastructure presents significant challenges, necessitating innovative methodologies to address irregular settlements and commercial losses in the electricity sector. This paper proposes an approach integrating convolutional neural networks and geospatial data to detect urban areas lacking electrical infrastructure. High-resolution Google Earth images and low-resolution Landsat 8 data were processed using advanced semantic segmentation architectures, LinkNetB7 and D-LinkNet50, to analyze land use patterns. The segmentation outputs were combined with data from the Brazilian Geographic Database of the Distribution System to generate comprehensive maps of electrical infrastructure coverage. The study focused on the SBAU substation in Sabaŕ a, Minas Gerais, which demonstrated commercial losses of up to 47.5% in specific feeders. Results demonstrated the effectiveness of deep learning models in identifying mismatches between urban development and infrastructure coverage, highlighting areas with potential irregular connections. This study contributes to advancing artificial intelligence applications in urban energy management by providing a scalable framework for analyzing land use and electrical infrastructure.

Paper Citation

in Harvard Style

Alves Á., Souza L., Cho-Luck L., Lima R., Augusto C., Marinho W., Capuano R., Costa B., Siqueira M., Silva J., Paradeda R. and Alsina P. (2025). Integrating Satellite Images Segmentation and Electrical Infrastructure Data to Identify Possible Urban Irregularities in Power Grid. In Proceedings of the 27th International Conference on Enterprise Information Systems - Volume 1: ICEIS; ISBN 978-989-758-749-8, SciTePress, pages 929-936. DOI: 10.5220/0013437500003929

in Bibtex Style

@conference{iceis25,
author={Álisson Alves and Luísa Souza and Luiz Cho-Luck and Raniere Lima and Carlos Augusto and Wesley Marinho and Rafael Capuano and Bruno Costa and Marina Siqueira and Jesaías Silva and Raul Paradeda and Pablo Alsina},
title={Integrating Satellite Images Segmentation and Electrical Infrastructure Data to Identify Possible Urban Irregularities in Power Grid},
booktitle={Proceedings of the 27th International Conference on Enterprise Information Systems - Volume 1: ICEIS},
year={2025},
pages={929-936},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013437500003929},
isbn={978-989-758-749-8},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 27th International Conference on Enterprise Information Systems - Volume 1: ICEIS
TI - Integrating Satellite Images Segmentation and Electrical Infrastructure Data to Identify Possible Urban Irregularities in Power Grid
SN - 978-989-758-749-8
AU - Alves Á.
AU - Souza L.
AU - Cho-Luck L.
AU - Lima R.
AU - Augusto C.
AU - Marinho W.
AU - Capuano R.
AU - Costa B.
AU - Siqueira M.
AU - Silva J.
AU - Paradeda R.
AU - Alsina P.
PY - 2025
SP - 929
EP - 936
DO - 10.5220/0013437500003929
PB - SciTePress