AIMC Topic: Oceans and Seas

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A Neural Network Model for K(λ) Retrieval and Application to Global Kpar Monitoring.

PloS one
Accurate estimation of diffuse attenuation coefficients in the visible wavelengths Kd(λ) from remotely sensed data is particularly challenging in global oceanic and coastal waters. The objectives of the present study are to evaluate the applicability...

A novel hybrid machine learning approach for accurate retrieval of ocean surface chlorophyll-a across oligotrophic to eutrophic waters.

Environmental research
Accurate assessment of chlorophyll a (Chla) concentration distribution and variations is significant for environmental monitoring and ecological research. However, the inversion of Chla in different optical types of water bodies can only be achieved ...

Evaluating marine environmental pollution using Fuzzy Analytic Hierarchy Process (FAHP): A comprehensive framework for sustainable coastal and oceanic management.

Marine pollution bulletin
Marine pollution poses a significant threat to ecosystems, biodiversity, and human health, necessitating a structured evaluation framework. This study applies the Fuzzy Analytic Hierarchy Process (FAHP) to prioritize five major marine pollution sourc...

Quantifying Area Back Scatter of Marine Organisms in the Arctic Ocean by Machine Learning-Based Post-Processing of Volume Back Scatter.

Sensors (Basel, Switzerland)
As the sea ice reduces in both extent and thickness and the Arctic Ocean opens, there is substantial interest in mapping the marine ecosystem in this remote and until now largely inaccessible ocean. We used the during surveys in the Central Arctic O...

Instantaneous photosynthetically available radiation models for ocean waters using neural networks.

Applied optics
Instantaneous photosynthetically available radiation (IPAR) at the ocean surface and its vertical profile below the surface play a critical role in models to calculate net primary productivity of marine phytoplankton. In this work, we report two IPAR...

The dynamic trophic architecture of open-ocean protist communities revealed through machine-guided metatranscriptomics.

Proceedings of the National Academy of Sciences of the United States of America
Intricate networks of single-celled eukaryotes (protists) dominate carbon flow in the ocean. Their growth, demise, and interactions with other microorganisms drive the fluxes of biogeochemical elements through marine ecosystems. Mixotrophic protists ...

Collaborating robots sample the primary production in the ocean.

Science robotics
Sampling genetic material from phytoplankton in open ocean eddies becomes more precise and efficient using a heterogeneous network of autonomous marine robots.

A system of coordinated autonomous robots for Lagrangian studies of microbes in the oceanic deep chlorophyll maximum.

Science robotics
The deep chlorophyll maximum (DCM) layer is an ecologically important feature of the open ocean. The DCM cannot be observed using aerial or satellite remote sensing; thus, in situ observations are essential. Further, understanding the responses of mi...

Mobile robotic platforms for the acoustic tracking of deep-sea demersal fishery resources.

Science robotics
Knowing the displacement capacity and mobility patterns of industrially exploited (i.e., fished) marine resources is key to establishing effective conservation management strategies in human-impacted marine ecosystems. Acquiring accurate behavioral i...