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

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 su...

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Main Authors: Lucas Terres de Lima, Sandra Fernández-Fernández, João Francisco Gonçalves, Luiz Magalhães Filho, Cristina Bernardes
Format: Article
Language:English
Published: MDPI AG 2021-04-01
Series:Remote Sensing
Subjects:
Online Access:https://www.mdpi.com/2072-4292/13/8/1424
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spelling doaj-a4f27fe29d374cc198379541aadeb1f22021-04-07T23:04:07ZengMDPI AGRemote Sensing2072-42922021-04-01131424142410.3390/rs13081424Development of Tools for Coastal Management in Google Earth Engine: Uncertainty Bathtub Model and Bruun RuleLucas Terres de Lima0Sandra Fernández-Fernández1João Francisco Gonçalves2Luiz Magalhães Filho3Cristina Bernardes4CESAM—Centre for Environmental and Marine Studies, Department of Geoscience, University of Aveiro, Campus de Santiago, 3810-193 Aveiro, PortugalCESAM—Centre for Environmental and Marine Studies, Department of Physics, University of Aveiro, Campus de Santiago, 3810-193 Aveiro, PortugalCIBIO-InBIO, Research Center in Biodioversity and Genetic Resources, University of Porto, Campus de Vairão, Rua Padre Armando Quintas, 4485-661 Vairão, PortugalCESAM—Centre for Environmental and Marine Studies, Department of Environment and Planning, University of Aveiro, Campus de Santiago, 3810-193 Aveiro, PortugalCESAM—Centre for Environmental and Marine Studies, Department of Geoscience, University of Aveiro, Campus de Santiago, 3810-193 Aveiro, PortugalSea-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.https://www.mdpi.com/2072-4292/13/8/1424sea-level risegeographical information systemopen-ource softwaremodeling
collection DOAJ
language English
format Article
sources DOAJ
author Lucas Terres de Lima
Sandra Fernández-Fernández
João Francisco Gonçalves
Luiz Magalhães Filho
Cristina Bernardes
spellingShingle Lucas Terres de Lima
Sandra Fernández-Fernández
João Francisco Gonçalves
Luiz Magalhães Filho
Cristina Bernardes
Development of Tools for Coastal Management in Google Earth Engine: Uncertainty Bathtub Model and Bruun Rule
Remote Sensing
sea-level rise
geographical information system
open-ource software
modeling
author_facet Lucas Terres de Lima
Sandra Fernández-Fernández
João Francisco Gonçalves
Luiz Magalhães Filho
Cristina Bernardes
author_sort Lucas Terres de Lima
title Development of Tools for Coastal Management in Google Earth Engine: Uncertainty Bathtub Model and Bruun Rule
title_short Development of Tools for Coastal Management in Google Earth Engine: Uncertainty Bathtub Model and Bruun Rule
title_full Development of Tools for Coastal Management in Google Earth Engine: Uncertainty Bathtub Model and Bruun Rule
title_fullStr Development of Tools for Coastal Management in Google Earth Engine: Uncertainty Bathtub Model and Bruun Rule
title_full_unstemmed Development of Tools for Coastal Management in Google Earth Engine: Uncertainty Bathtub Model and Bruun Rule
title_sort development of tools for coastal management in google earth engine: uncertainty bathtub model and bruun rule
publisher MDPI AG
series Remote Sensing
issn 2072-4292
publishDate 2021-04-01
description 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.
topic sea-level rise
geographical information system
open-ource software
modeling
url https://www.mdpi.com/2072-4292/13/8/1424
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