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

Lima, Lucas Terres de; Fernández-Fernández, Sandra; Gonçalves, João; Filho, Luiz Magalhães; Bernardes, Cristina

doi:10.3390/rs13081424

Cited by 8 publications

(3 citation statements)

References 42 publications

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“…However, heterogeneity of sea-land mapping and coastline delineation methods and the difficult access to these tools by coastal managers usually restricts their use [24,35,36,40,62,63]. The potential of GEE has already been demonstrated in previous studies [37,38,60,64,65], and we used S2 images within GEE in order to ensure accuracy and robust performance, as well as a user-friendly and accessible tool for coastal managers.…”

Section: High Frequency Remote Sensing Data: S2 Gee and Ndwimentioning

confidence: 99%

“…This platform allows this information to be processed in the cloud in order to detect changes, map trends and quantify differences on the Earth's surface, and can develop applications for final users [32]. Some studies have been carried out using S2 and GEE platform in marine and coastal areas, including water quality studies [33,34], coastline evolution [35,36], coastal management [37], and wetland mapping [38], showing the potential of the Copernicus open data and the GEE open-source platform for coastal monitoring.…”

Section: Introductionmentioning

confidence: 99%

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Monitoring Sand Spit Variability Using Sentinel-2 and Google Earth Engine in a Mediterranean Estuary

Roca

Navarro

Sanabria³

et al. 2022

Remote Sensing

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Estuarine degradation is a major concern worldwide, and is rapidly increasing due to anthropogenic pressures. The Mediterranean Guadiaro estuary, located in San Roque (Cadiz, Spain), is an example of a highly modified estuary, showing severe negative effects of eutrophication episodes and beach erosion. The migration of its river mouth sand spit causes the closure of the estuary, resulting in serious water quality issues and flora and fauna mortality due to the lack of water renewal. With the aim of studying the Guadiaro estuary throughout a 4-year period (2017–2020), the Sentinel-2 A/B twin satellites of the Copernicus programme were used thanks to their 5-day and 10 m temporal and spatial resolution, respectively. Sea–land mapping was performed using the Normalized Difference Water Index (NDWI) in the Google Earth Engine (GEE) platform, selecting cloud-free Sentinel-2 Level 2A images and computing statistics. Results show a closure trend of the Guadiaro river mouth and no clear sand spit seasonal patterns. The study also reveals the potential of both Sentinel-2 and GEE for estuarine monitoring by means of an optimized processing workflow. This improvement will be useful for coastal management to ensure a continuous and detailed monitoring in the area, contributing to the development of early-warning tools, which can be helpful for supporting an ecosystem-based approach to coastal areas.

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Section: High Frequency Remote Sensing Data: S2 Gee and Ndwimentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Monitoring Sand Spit Variability Using Sentinel-2 and Google Earth Engine in a Mediterranean Estuary

Roca

Navarro

Sanabria³

et al. 2022

Remote Sensing

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“…Williamson et al [45] used GEE to develop the Coral Reef Stress Exposure Index (CRSEI), for remotely monitoring coral reef exposure to environmental stressors. de Lima et al [46] developed and validated two models for sea-level rise prediction using GEE. Li et al [47] developed an automated approach to perform bathymetry mapping using the Sentinel-2 surface reflectance dataset in GEE.…”

Section: Introductionmentioning

confidence: 99%

Development of a Google Earth Engine-Based Application for the Management of Shallow Coral Reefs Using Drone Imagery

et al. 2023

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The Caribbean is one of the world’s most vulnerable regions to the projected impacts of climate change, and changes in coral reef ecosystems have been studied over the last two decades. Lately, new technology-based methods using satellites and unmanned vehicles, among others have emerged as tools to aid the governance of these ecosystems by providing managers with high-quality data for decision-making processes. This paper addresses the development of a Google Earth Engine (GEE)-based application for use in the management processes of shallow coral reef ecosystems, using images acquired with Remotely Piloted Aircraft Systems (RPAS) known as drones, at the Old Providence McBean Lagoon National Natural Park; a Marine Protected Area (MPA) located northwest of Old Providence Island, Colombia. Image acquisition and processing, known as drone imagery, is first described for flights performed using an RTK multispectral drone at five different monitoring stations within the MPA. Then, the use of the GEE app is described and illustrated. The user executes four simple steps starting with the selection of the orthomosaics uploaded to GEE and obtaining the reef habitat classification for four categories: coral, macroalgae, sand, and rubble, at any of the five monitoring stations. Results show that these classes can be effectively mapped using different machine-learning (ML) algorithms available inside GEE, helping the manager obtain high-quality information about the reef. This remote-sensing application represents an easy-to-use tool for managers that can be integrated into modern ecosystem monitoring protocols, supporting effective reef governance within a digitized society with more demanding stakeholders.

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Flood vulnerability under sea level rise for a coastal community located in a backbarrier environment, Portugal

Croteau,

Pacheco,

Ferreira

2023

J Coast Conserv

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Sea level rise will be a major threat to coastal communities within the next century due to the intensity and severity of the floods it can cause. A new methodology considering water infiltration, slope, and hydraulic connectivity was developed to assess the potential inundation extension associated with different total water level and sea level rise scenarios on sandy coasts. This methodology was applied for the current conditions as well as 2050 and 2100 scenarios of storm surge and high tide levels with return periods of 1 year and 100 years. The study area is Culatra village, located on the lagoon side of a barrier island in southern Portugal. The effects of shoreline evolution after the construction of a harbor and associated beach nourishment were also evaluated within the inundation scenarios. The results show that, within the study area, total water level variations caused by sea level rise have a greater influence on the inundation extension than shoreline retreat. The village appears to be safe for the current and 2050 total water level scenarios with a 1-year return period but would be highly affected by 100-year return periods, especially from 2050 onwards. This novel approach represents an improvement on more common flood mapping methods such as the bathtub approach and can be easily applied to other backbarrier environments under sea level rise or facing coastal erosion.

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

Cited by 8 publications

References 42 publications

Monitoring Sand Spit Variability Using Sentinel-2 and Google Earth Engine in a Mediterranean Estuary

Monitoring Sand Spit Variability Using Sentinel-2 and Google Earth Engine in a Mediterranean Estuary

Development of a Google Earth Engine-Based Application for the Management of Shallow Coral Reefs Using Drone Imagery

Flood vulnerability under sea level rise for a coastal community located in a backbarrier environment, Portugal

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