Temporal analysis of recurrence of flooded areas in Porto Alegre using Landsat and Sentinel-1 images

Authors

DOI:

https://doi.org/10.5902/2179460X91599

Keywords:

Flooded areas, MNDWI, Porto Alegre

Abstract

This study uses the collection of Landsat images to analyze the recurrence of flooded areas in the Porto Alegre region, highlighting its entire temporal scale from 1984 to the present, analyzing the images with the highest index. Additionally, the use of Sentinel-1 data, despite its smaller temporal scale, is explored to complement the analysis of flooded areas. Using qualitative, quantitative and exploratory methodology, the research demonstrates that the joint use of technologies such as Landsat and Sentinel-1 significantly increases the potential for analysis and monitoring, providing a robust data set, which contributes to decision-making in the context of disaster mitigation and urban planning in vulnerable areas such as Porto Alegre.

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Author Biographies

Vinícius de Azevedo Silva, Universidade Estadual de Campinas (UNICAMP)

Professional Master's Degree in Water Resources Management and Regulation from the State University of Rio de Janeiro.

Rodrigo Bruno Zanin, Universidade do Estado de Mato Grosso

PhD in Cartographic Sciences from the São Paulo State University Júlio de Mesquita Filho.

André Luis Sotero Salustiano Martim, Universidade Estadual de Campinas (UNICAMP)

PhD in Civil Engineering from the State University of Campinas.

Cristiano Poleto, Universidade Federal do Rio Grande do Sul

PhD in Water Resources and Environmental Sanitation from the Federal University of Rio Grande do Sul.

Francisco Lledo dos Santos, Universidade do Estado de Mato Grosso

PhD in Electrical Engineering from the São Paulo State University Júlio de Mesquita Filho.

References

ALLASIA, D. G. et al. Decreasing flood risk perception in Porto Alegre – Brazil and its influence on water resource management decisions. Proceedings of the International Association of Hydrological Sciences, v. 370, p. 189–192, 11 jun. 2015. https://doi.org/10.5194/piahs-370-189-2015, 2015. Available at: https://piahs.copernicus.org/articles/370/189/2015/ Access on: Set 29, 2024.

ALTAFINI, D. C. B., CLAUDIO, A. U. Mapping urban flood-prone areas' spatial structure and their tendencies of change: a network study for Brazil's Porto Alegre Metropolitan Region. Cartographica 58 (4) , pp. 205-226. 2023. 10.3138/cart-2023-0003 Available at: https://orca.cardiff.ac.uk/id/eprint/167578/ Access on Set 30, 2024.

ANDRADE, A. B. S. Utilização dos índices NDWI e MNDWI na detecção de corpos hídricos em imagens Sentinel-2 na bacia hidrográfica do rio Traipu – Alagoas. 2019. 37 f. TCC (Graduação em Engenharia de Agrimensura) – Universidade Federal de Alagoas, Alagoas, 2019. Available at: https://www.repositorio.ufal.br/bitstream/riufal/6157/1/Utiliza%C3%A7%C3%A3o%20dos%20%C3%ADndices%20NDWI%20e%20MNDWI%20na%20detec%C3%A7%C3%A3o%20de%20corpos%20h%C3%ADdricos%20em%20imagens%20Sentinel-2%20na%20bacia%20hidrogr%C3%A1fica%20di%20rio%20traipu%20-%20Alagoas.pdf Access on: Set 23, 2024.

DECLARO, A.; KANAE, S. Enhancing Surface Water Monitoring through Multi-Satellite Data-Fusion of Landsat-8/9, Sentinel-2, and Sentinel-1 SAR. Remote Sens. 2024, 16, 3329. https://doi.org/10.3390/rs16173329 Available at: https://www.mdpi.com/2072-4292/16/17/3329 Access on: Set 24, 2024.

MADDAH, S.; MOJARADI, B.; ALIZADEH, H. Enhancing flood susceptibility modeling using integration of multi-source satellite imagery and multi-input convolutional neural network. Natural Hazards. 2024. Available at: https://link.springer.com/article/10.1007/s11069-024-06764-1 Access on: Set 24, 2024.

MEHMOOD, H.; CONWAY, C.; PERERA, D.; 2021. Mapping of Flood Areas Using Landsat with Google Earth Engine Cloud Platform. Atmosphere 2021, 12, 866. https://doi.org/10.3390/atmos12070866 Available at: https://www.mdpi.com/2073-4433/12/7/866 Access on: Aug 31, 2024.

MISSION ENDS FOR COPERNICUS SENTINEL-1B SATELLITE. 2022. Available at: https://www.esa.int/Applications/Observing_the_Earth/Copernicus/Sentinel-1/Mission_ends_for_Copernicus_Sentinel-1B_satellite Access on: Set 28, 2024.

MISSION ENDS FOR COPERNICUS SENTINEL-1B SATELLITE | COPERNICUS. 2022. Available at: https://www.copernicus.eu/en/news/news/mission-ends-copernicus-sentinel-1b-satellite Access on: Oct 2, 2024.

SEXTON, Chrissy. Historic flooding in Rio Grande do Sul. Available at: https://www.earth.com/image/historic-flooding-in-rio-grande-do sul/ . Access on: Set 29, 2024.

SILVEIRA, L. N. et al. Wide-swath satellite altimetry reveals the 2024 Porto Alegre extreme flood was intensified by backwater effect across choked river section. Authorea (Authorea), Jun 6, 2024. Available at: https://sciety.org/articles/activity/10.22541/au.171769020.08746753/v1 Access on: Set 28, 2024.

TUCCI, C. E. M. Inundações Urbanas. Porto Alegre: ABRH/RHAMA, 393 p. 2007.

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Published

2025-05-21

How to Cite

Silva, V. de A., Zanin, R. B., Martim, A. L. S. S., Poleto, C., & Santos, F. L. dos. (2025). Temporal analysis of recurrence of flooded areas in Porto Alegre using Landsat and Sentinel-1 images. Ciência E Natura, 47(esp. 2), e91599. https://doi.org/10.5902/2179460X91599

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