EventsInternational Conference on Advanced Remote Sensing (ICARS 2025)
Published
This submission belongs to the session S2. Urban Remote Sensing of the event International Conference on Advanced Remote Sensing (ICARS 2025)
Published date
25 Mar, 2025
Academic Editor
author-avatarFabio Tosti
Citation
Elizabeth Rocha Souza, Vandré Soares Viegas, Urban Expansion Projections in Maricá—Rio de Janeiro-RJ: Modeling with Cellular Automata and Sentinel Images for 2030 and 2040, in Proceedings of International Conference on Advanced Remote Sensing (ICARS 2025), Barcelona, 26 March–28 March 2025, MDPI: Basel, Switzerland
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Urban Expansion Projections in Maricá—Rio de Janeiro-RJ: Modeling with Cellular Automata and Sentinel Images for 2030 and 2040

1. Department of Geography at the Federal University of Rio de Janeiro - UFRJ, Brazil
Abstract

The city of Maricá, located on the eastern coast of the state of Rio de Janeiro, has experienced significant population growth in recent decades, driven by economic and infrastructure factors. This study aimed to predict urban expansion for the decades of 2030 and 2040 using dynamic modeling with cellular automata and land use and cover generated from Sentinel orbital images. The objective is to assist in formulating planning and management strategies that balance growth and sustainability. The methodology involved image classification using the GEE platform and adjustments in static variables representative of change (terrain, transportation system, hydrography, and environmental protection units). After classification and validation through fuzzy analysis, future scenarios were generated for the years 2030 and 2040. The results indicate that the built-up area is expected to increase by over 40% by 2030 compared to 2019. The projection for 2040 suggests a continuation of this urban expansion, driven by factors such as oil exploration, infrastructure investments, and innovative social programs that attract new residents. It is concluded that the use of cellular automata and Sentinel images allows for a coherent simulation of urbanization trends and can guide sustainable urban planning actions, providing support for public management to minimize environmental impacts and promote balanced development.

Keywords
urban expansion
dynamic modeling
cellular automata
Sentinel satellite imagery
sustainable urban planning
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