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LifeWatch observatory data: phytoplankton annotated trainingset by FlowCam imaging in the Belgian Part of the North Sea [LifeWatch observatory data: phytoplankton annotated trainingset by FlowCam imaging in the Belgian Part of the North Sea] Citation Decrop, W., Lagaisse, R., Jonas, M., Muyle, J., Amadei Martínez, L., & Deneudt, K. (2024). LifeWatch observatory data: phytoplankton annotated trainingset by FlowCam imaging in the Belgian Part of the North Sea (Versie v1). Zenodo. https://doi.org/10.5281/zenodo.10554845. https://marineinfo.org/id/dataset/8645 Contact: Availability:  This dataset is licensed under a Creative Commons Attribution 4.0 International License.Description The images were collected in the framework of the Belgian Lifewatch Research Infrastructure. During multidisciplinary campaigns, a number of fixed stations in the Belgian Part of the North Sea (BPNS) are visited on a monthly (onshore stations) or seasonal (offshore stations) basis. Samples are taken using a 55µm mesh size Apstein net and fixed in Lugol's iodine solution. In the lab, the samples are processed using a VS-4 FlowCAM model at 4X magnification targeting a particle size range of 55-300µm. The identification of the image data is done with the use of a CNN and followed by a manual validation step. Since May 2017, this dataset has provided micro- and phytoplankton observations, mainly covering diatoms, dinoflagellates and cilliates, for the Belgian Part of the North Sea (BPNS).
This dataset comprises a trainings datasplit of 337,613 images distributed across 95 classes, with each class containing a minimum of 100 and a maximum of 10,000 images. The goal of this dataset is to be able to facilitate model training, here we have organized the data into a standard split, with 80% allocated for training, 10% for validation, and another 10% for testing purposes. This dataset structure ensures a balanced representation and supports scientific rigor in subsequent analyses. moreTechnical detailsData preprocessingRaw FlowCam output data is fully processed using in-house datapipelines, the VisualSpreadsheet software is only used for data acquisition during the lab run of the sample. Raw images and binary images are never saved during the FlowCam run, we only work on the image collages saved at the end of the run. Single images are cut from these collages using each image coordinates width and height pulled from the .lst file using in-house python code. The background of the images is not removed. These images are then predicted and annotated in-house at VLIZ. Data splittingThe training dataset is 80% used for training, 10% for validation and 10% for prediction. Classes, labels and annotationsThe dataset comprises 337,613 images distributed across 95 classes, with each class containing a minimum of 100 and a maximum of 10,000 images. Taxonomic coverage of the dataset comprises mainly of diatoms, dinoflagellates and cilliates, but to a lesser extent also zooplankton and other protists. ParametersThe images are read using cv2.imread and the values are used as parameters. Data sourcesImages are collected during the monthly monitoring of phytoplankton communities in the Belgian Part of the North Sea during the LifeWatch multidisciplinary campaigns by FlowCam VS-4 benchmodel (Fluid Imaging Technologies, Yarmouth, Maine, U.S.A.). Data qualityAll images are predicted and subsequently manually validated to ensure the quality of the trainingset. Image resolutionThe size range imaged is 55-300µm. Images are acquired using a Sony XCD SC90 digital gray-scale camera. Images are during training of CNN resized to 100px by 100px. Spatial coverageThe data comes from a number of fixed stations in the Belgian Part of the North Sea (BPNS). Nine stations onshore are visited monthly:
Eight additional offshore stations are visited seasonally:
Temporal coverageThe monitoring was initiated in May 2017 and has been running continuously every month. Scope Themes: Biology > Plankton > Phytoplankton Keywords: Neural networks, Phytoplankton, ANE, Belgium, Bacillariophyceae, Ciliophora, Dictyochophyceae, Dinophyceae, Prymnesiophyceae Geographical coverage ANE, Belgium [Marine Regions] Temporal coverage 1 May 2017 - 23 January 2024 Taxonomic coverage Parameter Contributors Vlaams Instituut voor de Zee (VLIZ), more, data provider Related datasets Project URL Dataset status: In Progress Data type: Data Data origin: Research Release date: 2024-01-22 Metadatarecord created: 2024-09-23 Information last updated: 2024-09-24 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
