Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

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

Lucas Terres de Lima
* ORCID logo ,
Sandra Fernández-Fernández
ORCID logo ,
João Francisco Gonçalves
,
Luiz Magalhães Filho
,
Cristina Bernardes
ORCID logo
Version 1 : Received: 12 February 2021 / Approved: 23 February 2021 / Online: 23 February 2021 (12:39:09 CET)

A peer-reviewed article of this Preprint also exists.

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. 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.

Abstract

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 better coastal man-agement. This study aims to develop and to 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 Bruun Rule formula implemented in GEE and is capable to determine the coastline retreat of a profile through the creation of a simple vector line from topo-bathymetric data. The model shows a very high cor-relation (0.97) with a classical Bruun Rule study performed in Aveiro coast (NW Portugal). The GEE platform seems to be an important tool for coastal management. The models developed have been openly shared, enabling the continuous improvement of the code by the scientific commu-nity.

Keywords

Sea-Level Rise; GIS; Open-Source Software; Modeling

Subject

Environmental and Earth Sciences, Atmospheric Science and Meteorology

Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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