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Article

Development of Tools for Coastal Management in Google Earth Engine: Uncertainty Bathtub Model and Bruun Rule

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CESAM—Centre for Environmental and Marine Studies, Department of Geoscience, University of Aveiro, Campus de Santiago, 3810-193 Aveiro, Portugal
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CESAM—Centre for Environmental and Marine Studies, Department of Physics, University of Aveiro, Campus de Santiago, 3810-193 Aveiro, Portugal
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CIBIO-InBIO, Research Center in Biodioversity and Genetic Resources, University of Porto, Campus de Vairão, Rua Padre Armando Quintas, 4485-661 Vairão, Portugal
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Instituto Politécnico de Viana do Castelo, Rua Escola Industrial e Comercial Nun’Álvares, 4900-347 Viana do Castelo, Portugal
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CESAM—Centre for Environmental and Marine Studies, Department of Environment and Planning, University of Aveiro, Campus de Santiago, 3810-193 Aveiro, Portugal
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Author to whom correspondence should be addressed.
Academic Editor: Koreen Millard
Received: 12 February 2021 / Revised: 30 March 2021 / Accepted: 2 April 2021 / Published: 7 April 2021
Sea-level rise is a problem increasingly affecting coastal areas worldwide. The existence of free and open-source models to estimate the sea-level impact can contribute to improve coastal management. This study aims to develop and validate two different models to predict the sea-level rise impact supported by Google Earth Engine (GEE)—a cloud-based platform for planetary-scale environmental data analysis. The first model is a Bathtub Model based on the uncertainty of projections of the sea-level rise impact module of TerrSet—Geospatial Monitoring and Modeling System software. The validation process performed in the Rio Grande do Sul coastal plain (S Brazil) resulted in correlations from 0.75 to 1.00. The second model uses the Bruun rule formula implemented in GEE and can determine the coastline retreat of a profile by creatting a simple vector line from topo-bathymetric data. The model shows a very high correlation (0.97) with a classical Bruun rule study performed in the Aveiro coast (NW Portugal). Therefore, the achieved results disclose that the GEE platform is suitable to perform these analysis. The models developed have been openly shared, enabling the continuous improvement of the code by the scientific community. View Full-Text
Keywords: sea-level rise; geographical information system; open-ource software; modeling sea-level rise; geographical information system; open-ource software; modeling
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MDPI and ACS Style

Terres de Lima, L.; Fernández-Fernández, S.; Gonçalves, J.F.; Magalhães Filho, L.; Bernardes, C. Development of Tools for Coastal Management in Google Earth Engine: Uncertainty Bathtub Model and Bruun Rule. Remote Sens. 2021, 13, 1424. https://0-doi-org.brum.beds.ac.uk/10.3390/rs13081424

AMA Style

Terres de Lima L, Fernández-Fernández S, Gonçalves JF, Magalhães Filho L, Bernardes C. Development of Tools for Coastal Management in Google Earth Engine: Uncertainty Bathtub Model and Bruun Rule. Remote Sensing. 2021; 13(8):1424. https://0-doi-org.brum.beds.ac.uk/10.3390/rs13081424

Chicago/Turabian Style

Terres de Lima, Lucas, Sandra Fernández-Fernández, João F. Gonçalves, Luiz Magalhães Filho, and Cristina Bernardes. 2021. "Development of Tools for Coastal Management in Google Earth Engine: Uncertainty Bathtub Model and Bruun Rule" Remote Sensing 13, no. 8: 1424. https://0-doi-org.brum.beds.ac.uk/10.3390/rs13081424

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