Lightframe On-sight Key species Investigation (LOKI)

Schulz, Jan; Barz, Kristina; Mengedoht, Dirk; Hanken, T.; Lilienthal, H.; Rieper, Norbert; Hoops, J.; Vogel, Kurt; Hirche, Hans-Jürgen

doi:10.1109/oceanse.2009.5278252

Cited by 6 publications

(6 citation statements)

References 14 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Zooglider , like other plankton imaging systems (Wiebe and Benfield 2003; Cowen and Guigand 2008; Schulz et al 2009; Picheral et al 2010), permits resolution of fine‐scale vertical distributions of small suspended particles, marine snow, Chl a , and mesozooplankton on the scale at which zooplankton interact with such particles. However, Zooglider has the advantage that it is completely autonomous and untethered to a surface vessel or fixed platform.…”

Section: Discussionmentioning

confidence: 99%

“…This difference is most likely due to systematic limitations of physical net collections. Net systems are unable to resolve the fine‐scale vertical distributions of marine snow and small particles within the water column, while Zooglider , like other imaging systems (Wiebe and Benfield 2003; Cowen and Guigand 2008; Schulz et al 2009; Picheral et al 2010), is capable of resolving such associations.…”

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

Zooglider‐measured association of zooplankton with the fine‐scale vertical prey field

Whitmore

Ohman

2021

Limnology & Oceanography

View full text Add to dashboard Cite

We use Zooglider, a low‐power optical zooplankton‐sensing glider, to test the covariability of the fine‐scale vertical distributions of six omnivorous zooplankton taxa with three different representations of their potential prey field: small suspended particles (equivalent circular diameter [ECD] between 0.25 and 0.45 mm), marine snow (ECD ≥ 0.45 mm), and chlorophyll a (Chl a), in the San Diego Trough. All three prey fields tend to be highly correlated from 100 m to the depth of the subsurface Chl a maximum layer (SCML), while correlations between the prey fields are weaker or nonexistent from the SCML to the surface. An index of spatial overlap (Local Index of Collocation) showed stronger overlap of zooplankton with marine snow or small particles than with Chl a in most cases. Moreover, generalized additive models revealed marine snow distributions or small particles as the primary explanatory variable, by percent deviance explained, for all zooplankton taxa tested. Chl a distributions were a secondary explanatory variable for four of the six taxa tested (small copepods, appendicularia‐Fritillaria, and both night and day large copepods), and an insignificant explanatory variable for the remaining two (appendicularia‐others and large protists). The distributions of suspended particles, during our year‐round study in the San Diego Trough, were more informative for explaining distributions of omnivorous zooplankton than Chl a alone.

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Zooglider‐measured association of zooplankton with the fine‐scale vertical prey field

Whitmore

Ohman

2021

Limnology & Oceanography

View full text Add to dashboard Cite

show abstract

“…Darkfield imagers generally have better resolution and contrast but less throughput, and they are more suitable for long-term high-frequency observations at fixed spots at the shore [24] or the sea floor [25]. They have also been deployed with mobile platforms including the profilers [26], [27] and the research vessels [28], [29].…”

Section: Introductionmentioning

confidence: 99%

Development of a Buoy-Borne Underwater Imaging System for In Situ Mesoplankton Monitoring of Coastal Waters

Chen

Yang

et al. 2022

IEEE J. Oceanic Eng.

View full text Add to dashboard Cite

This article reports the development of an underwater imaging system and its trial on a moored surface buoy for in situ plankton monitoring of coastal waters. The imager features shadowless white light illumination by an orthogonal lamellar lighting design, resulting in high-quality underwater darkfield color imaging of planktonic particles in the size range of ∼200 µm to 40 mm and effective reduction of zooplankton phototaxis. Through raft and buoy trials, 46 804 plankton and suspending particle images have been annotated through a human-machine mutually assisted effort into a data set with 90 categories. In the meanwhile, a deep learning model based on a triclassification VGGNet-11 and multiclassification ResNet-18 convolutional neuron networks in a two-staged hierarchy has also been trained and developed. The model has been applied with human supervision to semiautomatically analyze a total of 1 545 187 images obtained from a buoy trial for six months from late spring to early winter of 2020. The high temporal resolution results well documented the variation of the mesoplankton community structure in two time series of 38 days in summer and 54 days in autumn of the target sea region. In addition, the dominant species in the trial period and a zooplankton outbreak that had threatened the safety of the nearby nuclear power plants were quantitatively Manuscript

show abstract

“…As early as in the era of film photography, people tried to use underwater optical imaging for in situ observation of marine plankton (Ortner et al, 1979). With the maturity of solid-state lighting and digital camera technologies since the 1990s, a variety of underwater plankton imagers have been developed (Benfield et al, 1996;Cowen and Guigand, 2008;Schulz et al, 2009;Picheral et al, 2010;Bi et al, 2013;M. Rotermund and Samson, 2015;Gallager, 2019;Orenstein et al, 2020;Li et al, 2022), through which digital images of plankters are captured in natural seawaters.…”

mentioning

confidence: 99%

“…These features are beneficial for finer plankton taxonomy and quantification, especially favorable for biodiversity study (Lombard et al, 2019). Therefore, darkfield imaging has been adopted by many underwater plankton cameras (Benfield et al, 1996;Gorsky et al, 2000;Schulz et al, 2009;Gallager, 2019;Orenstein et al, 2020;Li et al, 2022). For example, the Imaging Plankton Probe (IPP) developed by (Li et al, 2022) is a darkfield plankton imager that supports long-time near-shore buoy deployment.…”

mentioning

confidence: 99%

Deep focus-extended darkfield imaging for in situ observation of marine plankton

Chen

et al. 2023

Front. Mar. Sci.

View full text Add to dashboard Cite

Darkfield imaging can achieve in situ observation of marine plankton with unique advantages of high-resolution, high-contrast and colorful imaging for plankton species identification, size measurement and abundance estimation. However, existing underwater darkfield imagers have very shallow depth-of-field, leading to inefficient seawater sampling for plankton observation. We develop a data-driven method that can algorithmically refocus planktonic objects in their defocused darkfield images, equivalently achieving focus-extension for their acquisition imagers. We devise a set of dual-channel imaging apparatus to quickly capture paired images of live plankton with different defocus degrees in seawater samples, simulating the settings as in in situ darkfield plankton imaging. Through a series of registration and preprocessing operations on the raw image pairs, a dataset consisting of 55 000 pairs of defocused-focused plankter images have been constructed with an accurate defocus distance label for each defocused image. We use the dataset to train an end-to-end deep convolution neural network named IsPlanktonFE, and testify its focus-extension performance through extensive experiments. The experimental results show that IsPlanktonFE has extended the depth-of-field of a 0.5× darkfield imaging system to ~7 times of its original value. Moreover, the model has exhibited good content and instrument generalizability, and considerable accuracy improvement for a pre-trained ResNet-18 network to classify defocused plankton images. This focus-extension technology is expected to greatly enhance the sampling throughput and efficiency for the future in situ marine plankton observation systems, and promote the wide applications of darkfield plankton imaging instruments in marine ecology research and aquatic environment monitoring programs.

show abstract

Lightframe On-sight Key species Investigation (LOKI)

Cited by 6 publications

References 14 publications

Zooglider‐measured association of zooplankton with the fine‐scale vertical prey field

Zooglider‐measured association of zooplankton with the fine‐scale vertical prey field

Development of a Buoy-Borne Underwater Imaging System for In Situ Mesoplankton Monitoring of Coastal Waters

Deep focus-extended darkfield imaging for in situ observation of marine plankton

Contact Info

Product

Resources

About