Crowdsourcing for Sargassum Monitoring Along the Beaches in Quintana Roo

Arellano‐Verdejo, Javier; Lazcano-Hernandez, Hugo-Enrique

doi:10.1007/978-3-030-59872-3_4

Cited by 8 publications

(7 citation statements)

References 9 publications

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“…Maps are a fundamental tool for the study and visualization of phenomena with some spatial component; that is why they are applied in various areas of knowledge ( Baniata, Mahmood & Kertesz, 2021 ; Ma, Zhang & Huang, 2021 ). Concerning the study of Sargassum , there are studies ( Arellano-Verdejo & Lazcano-Hernandez, 2020 ; Arellano-Verdejo & Lazcano-Hernández, 2021 ), that present an approach to the generation of Sargassum maps on the beach. In their work, the authors offer a methodology for acquiring images based on Crowdsourcing, processing these images, and finally, creating maps that show the presence/absence of Sargassum .…”

Section: Methodsmentioning

confidence: 99%

“…However, given the spatial resolution of the MODIS images, accurate monitoring along the beach is not feasible. Another novel approach to coastal monitoring, and in particular to monitor Sargassum on the beach, is Collective View ( Arellano-Verdejo & Lazcano-Hernández, 2021 ), which maps the presence/absence of Sargassum after automatic classification of images uploaded by citizens through the scheme of Crowdsourcing ( Arellano-Verdejo & Lazcano-Hernandez, 2020 ). Although the proposal is innovative, the presence/absence maps provide limited information and do not facilitate decision-making.…”

Section: Introductionmentioning

confidence: 99%

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Use of semantic segmentation for mapping Sargassum on beaches

Arellano‐Verdejo

Santos-Romero²,

Lazcano-Hernandez

2022

PeerJ

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The unusual arrival of Sargassum on Caribbean beaches is an emerging problem that has generated numerous challenges. The monitoring, visualization, and estimation of Sargassum coverage on the beaches remain a constant complication. This study proposes a new mapping methodology to estimate Sargassum coverage on the beaches. Semantic segmentation of geotagged photographs allows the generation of accurate maps showing the percent coverage of Sargassum. The first dataset of segmented Sargassum images was built for this study and used to train the proposed model. The results demonstrate that the currently proposed method has an accuracy of 91%, improving on the results reported in the state-of-the-art method where data was also collected through a crowdsourcing scheme, in which only information on the presence and absence of Sargassum is displayed.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Use of semantic segmentation for mapping Sargassum on beaches

Arellano‐Verdejo

Santos-Romero²,

Lazcano-Hernandez

2022

PeerJ

Self Cite

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“…Some of these studies, projects and initiatives are further described in Supplementary File S3. Continuous and systematic records of the occurrence of the phenomenon at fine temporal (i.e., daily) and spatial (i.e., meters) scales Sargassum population dynamics [50] Citizen Science for in situ monitoring [51,52] Improvements in statal telecommunication infrastructure (i.e., widespread free internet access) and massive informative campaigns…”

Section: Monitoring Modeling and Early Warningmentioning

confidence: 99%

A Review of a Decade of Local Projects, Studies and Initiatives of Atypical Influxes of Pelagic Sargassum on Mexican Caribbean Coasts

et al. 2022

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This study collates and reviews the state of the art in the phenomenon of atypical pelagic Sargassum influxes in the coastline of the Mexican Caribbean, focusing on projects, studies and initiatives that have been conducted in the country for a decade. We integrated multisectoral and multidisciplinary knowledge and identified gaps and strengths in current knowledge. Initiatives and projects conducted in Mexico are numerous, diverse and valuable. However, interdisciplinary and transdisciplinary research and interinstitutional coordinated actions in the medium- and long-term are still lacking. Because of this, there is an imbalance of actions in different knowledge areas that prevents this phenomenon from being addressed in a comprehensive way. Furthermore, the funding opportunities for Sargassum research projects and other initiatives seem to respond to the events of massive influxes, without continuity or long-term planning. Attention is mainly focused on urban and touristic areas, so impacts to rural or uninhabited zones are unknown. This review represents a stepping-stone towards an integrated multisectoral effort to shift the perspective from Sargassum being a “national problem” to a “national resource,” considering and fully understanding the ecological importance of this macroalgae as a floating ecosystem and its potential as an economic resource once it massively arrives in Mexican coastal areas.

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“…However, the lack of metadata in the images makes this approach ineffective ( Uribe-Martnez et al, 2020 ). Other initiatives, inspired by the use of “Citizen Science” and “crowdsourcing”, have collected information on the arrival of the Sargassum to the coast ( Arellano-Verdejo & Lazcano-Hernandez, 2020 ). These initiatives have offered promising results as well as new challenges.…”

Section: Introductionmentioning

confidence: 99%

“…The term crowdsourcing was coined by Howe (2006) , to describe “the act of taking a job traditionally performed by a designated agent (usually an employee) and outsourcing it to an undefined, generally large group of people in the form of an open call” ( Howe, 2006 ). Several studies have demonstrated that Crowdsourcing is a useful methodology for collecting and managing data in different content areas, including: image classification, character recognition, genome annotation, document translation, protein folding, RNA structure design, algorithm development ( Good & Su, 2013 ), and Sargassum monitoring ( Arellano-Verdejo & Lazcano-Hernandez, 2020 ). For the successful implementation of crowdsourcing, it is advisable to use a platform to standardize and automatize the study processes.…”

Section: Introductionmentioning

confidence: 99%

Collective view: mapping Sargassum distribution along beaches

Arellano‐Verdejo

Lazcano-Hernandez

2021

PeerJ Computer Science

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The atypical arrival of pelagic Sargassum to the Mexican Caribbean beaches has caused considerable economic and ecological damage. Furthermore, it has raised new challenges for monitoring the coastlines. Historically, satellite remote-sensing has been used for Sargassum monitoring in the ocean; nonetheless, limitations in the temporal and spatial resolution of available satellite platforms do not allow for near real-time monitoring of this macro-algae on beaches. This study proposes an innovative approach for monitoring Sargassum on beaches using Crowdsourcing for imagery collection, deep learning for automatic classification, and geographic information systems for visualizing the results. We have coined this collaborative process “Collective View”. It offers a geotagged dataset of images illustrating the presence or absence of Sargassum on beaches located along the northern and eastern regions in the Yucatan Peninsula, in Mexico. This new dataset is the largest of its kind in surrounding areas. As part of the design process for Collective View, three convolutional neural networks (LeNet-5, AlexNet and VGG16) were modified and retrained to classify images, according to the presence or absence of Sargassum. Findings from this study revealed that AlexNet demonstrated the best performance, achieving a maximum recall of 94%. These results are good considering that the training was carried out using a relatively small set of unbalanced images. Finally, this study provides a first approach to mapping the Sargassum distribution along the beaches using the classified geotagged images and offers novel insight into how we can accurately map the arrival of algal blooms along the coastline.

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Crowdsourcing for Sargassum Monitoring Along the Beaches in Quintana Roo

Cited by 8 publications

References 9 publications

Use of semantic segmentation for mapping Sargassum on beaches

Use of semantic segmentation for mapping Sargassum on beaches

A Review of a Decade of Local Projects, Studies and Initiatives of Atypical Influxes of Pelagic Sargassum on Mexican Caribbean Coasts

Collective view: mapping Sargassum distribution along beaches

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