User stories

VPR Simon Stevin

Taking the next step: In-situ imaging data through the Video Plankton Recorder

LifeWatch RV Simon Stevin Long-term data monitoring

Zooplankton and phytoplankton are essential to coastal ecosystems, playing crucial roles in marine food webs. Environmental changes like climate change and pollution threaten these delicate communities, making monitoring crucial. The Video Plankton Recorder (VPR), integrated with LifeWatch infrastructure, helps researchers study biodiversity and ecosystem health in real-time aboard the RV Simon Stevin, contributing to key research in Belgian coastal waters. 

Anouk Ollevier

 "The LifeWatch sensors and processing pipelines have been instrumental in facilitating my PhD research, aiding in the validation of thousands of images."

Dr. Anouk Ollevier

Anouk, a PhD student jointly affiliated with VLIZ and Ghent University, is committed to assessing the use of the Video Plankton Recorder (VPR) in turbid coastal waters. Her research focuses on leveraging the VPR's potential to advance our understanding of plankton ecology and distribution.

Objectives

This research aims to study plankton ecology using imaging techniques, especially the Video Plankton Recorder (VPR), to observe plankton in their natural habitat. By improving methods to estimate fragile organisms like jellyfish, it enhances understanding of plankton abundance and distribution. The study focuses on the vertical migration patterns of marine life in the Belgian North Sea and explores plankton as bioindicators of ecosystem changes. It also evaluates the VPR's effectiveness in turbid waters, refining its use in marine biodiversity research and monitoring.

Methodology

VPR

An innovative sensor used for biodiversity measurements is the Video Plankton Recorder (VPR) which captures underwater images of plankton and marine particles while being towed behind a research vessel. The strength of this real-time technique is that particles are photographed in their natural environment and that additional sensors on the VPR simultaneously collect environmental measurements (e.g., seawater temperature, salinity, turbidity, pressure, ...). This data is stored together with measurements of the depicted particles (e.g. length, height, circularity…) and classification data (e.g., name of the particle that has been photographed). This yields an outstanding strong dataset important to both marine biologists and geologists.

Used components of the LifeWatch Infrastructure

Belgian LifeWatch Observatory

Since 2012, plankton samples are collected during multidisciplinary sampling campaigns onboard of the RV Simon Stevin, visiting nine nearshore stations with monthly frequency and an additional eight offshore stations on a seasonal basis in the BPNS. As part of the Belgian LifeWatch E-science infrastructure, users interested in biodiversity and ecosystem research will be able to visualize and use the plankton data, products and web services related to plankton indicator calculations. The use case described here, has its origin in the Belgian LifeWatch Observatory.

 

Data system

To cope and easily handle such large image datasets, both images and associated metadata are stored in BioSenseMongoDB, a NoSQL database. It is well-suited for storing image data due to its flexible and scalable document-based data model. It can handle large amounts of unstructured data, including binary image data, without the need to define a schema beforehand. Additionally, MongoDB's efficient storage and retrieval capabilities, as well as its built-in support for handling gridFS (a specification for storing and retrieving files that exceed the BSON-document size limit of 16 MB), make it an interesting choice for image data storage. The built in gridFS view is handy to look at the images directly. To date, 6.087.636 images were collected by the VPR and are stored in BioSenseMongoDB, each image associated with 28 fields containing sample-based information, 7 fields of image-associated data, 6 fields of classification data and 5 fields containing environmental-information.

In-house VPR python package and Symfony/PHP user interface (MongoDB Uploader Tool, MUT) were developed to allow scientists to easily upload raw data from the VLIZ archive to BioSenseMongoDB. Image recognition algorithms are then run on image data in BioSenseMongoDB, which will predict the taxonomic name for each image (which is important to scientists). Moreover, an in-house Graphical User Interface, the Plankton Validation Tool (PlaVa), was developed to validate collected image data, by directly querying and writing to the BioSenseMongoDB database. It allows to easily query the BioSenseMongoDB database and directly writes the new (manually assigned) validations to the database, without the need for coding or downloading the images locally. 

Finally, users can query BioSenseMongoDB and extract validated biodiversity data for downstream pipelines. Image information can be reviewed and managed for quality control and IT-developments. 

VPR data flow
Plankton

Output

Scientific outreach

Ollevier, A.; Mortelmans, J.; Vandegehuchte, M.; Develter, R.; De Troch, M.; Deneudt, K. (2022). A Video Plankton Recorder user guide: Lessons learned from in situ plankton imaging in shallow and turbid coastal waters in the Belgian part of the North Sea. J. Sea Res. 188: 102257. https://dx.doi.org/10.1016/j.seares.2022.102257

Hablützel, P.I.; Rombouts, I.; Dillen, N.; Lagaisse, R.; Mortelmans, J.; Ollevier, A.; Perneel, M.; Deneudt, K. (2021). Exploring new technologies for plankton observations and monitoring of ocean health, in: Kappel, E.S. et al. Frontiers in ocean observing: Documenting ecosystems, understanding environmental changes, forecasting hazards. Oceanography, Suppl. 34(4): pp. 20-25. https://dx.doi.org/10.5670/oceanog.2021.supplement.02-09

Ollevier, A. (2024). Through the lens of a Video Plankton Recorder: Optical imaging and insights into zooplankton ecology. VLIZ Theses, 1. PhD Thesis. Flanders Marine Institute (VLIZ)/Ghent University, Faculty of Sciences, Biology Department: Ostend/Ghent. x, 183 pp. Available at https://www.vliz.be/en/imis?module=ref&refid=381616

 

Contact

Useful links

  • Data explorer: Access and explore the acoustic fish detection data with the LifeWatch data explorer.

  • LifeWatch GitHub: Find the scripts and tutorials developed for the use of data of the LifeWatch Infrastructure.

Other stories