Collective view: mapping Sargassum distribution along beaches
Javier Arellano-Verdejo1, Hugo E Lazcano-Hernández2
1Department of Observation and Study of the Earth, Atmosphere and Ocean, El Colegio de la Frontera Sur, Chetumal, Quintana Roo, Mexico.
Peerj. Computer Science
|June 4, 2021
Summary
This study introduces "Collective View," a crowdsourced method using deep learning to monitor beach-based Sargassum seaweed. AlexNet achieved 94% recall, enabling accurate mapping of algal blooms.
Area of Science:
- Marine Biology
- Remote Sensing
- Computer Science
Background:
- Pelagic Sargassum influxes cause significant economic and ecological harm to Mexican Caribbean beaches.
- Existing satellite remote-sensing methods lack the necessary resolution for near real-time monitoring of Sargassum on coastlines.
Purpose of the Study:
- To develop an innovative approach for monitoring Sargassum on beaches using crowdsourcing, deep learning, and GIS.
- To create a comprehensive, geotagged dataset for Sargassum presence/absence on Yucatan Peninsula beaches.
Main Methods:
- Implemented a crowdsourcing platform for image collection.
- Utilized deep learning, specifically modified convolutional neural networks (LeNet-5, AlexNet, VGG16), for image classification.
- Employed geographic information systems (GIS) for result visualization.
Main Results:
- The developed
- Collective View
- " system generated the largest geotagged Sargassum image dataset for the region.
- AlexNet achieved the highest performance with a 94% recall rate in classifying Sargassum presence/absence.
- The study successfully mapped Sargassum distribution along beaches using classified geotagged images.
Conclusions:
- The
- Collective View
- " approach offers an effective solution for near real-time monitoring of beach-bound Sargassum.
- Deep learning models, particularly AlexNet, show high accuracy even with limited, unbalanced datasets.
- This methodology provides novel insights for accurately mapping coastal algal bloom arrivals.
Keywords:
Artificial intelligenceBeach monitoringConvolutional neural networksCrowd-mappingCrowdsourcingEcological applicationGISGeotagged imagesMore Related Videos
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