Abstract
The lander is an underwater observatory used to provide insights into physical and biological processes in the “Dr?bak sund”, Oslofjord. The primary aims of the lander deployment are to increase the focus on the Oslofjord and to monitor fish and currents at this location. Conceptualization, construction and deployment of the lander as well as data collection takes place in a collaboration among the Institute of Marine Research, dScience Center at University of Oslo and Kongsberg Discovery, within the larger context of the Frisk Oslofjord project. The data from this project are primarily aimed to be used for scientific research and dScience participates actively in the maintenance of the data collection and organization system and provides access to the data for researchers. In addition, data scientists and domain experts at dScience collect the data, build up and maintain pipelines for data processing and analysis. Some aspects of the results are visualized and communicated via the Insight Oslofjord app which is accessible to all students participating on any of the excursion boat trips in Oslofjord. Preliminary analyses show interesting results on fish activity (e.g. school formation), plankton vertical migration and aggregation, turbulence and mixing in the water column and short-term water mass changes.
Background
The Oslofjord is facing eutrophication, pollution, fishing and ship traffic, leading to problems causing increasing political and public awareness over the last years. The Frisk Oslofjord project (https://www.friskoslofjord.no/) aims to improve the understanding of the fjord ecosystem and processes. By communicating the environmental challenges to the public, the project attempts to amplify actions needed to improve the fjords environmental status. The Dr?bak lander is part of the state-of-the art instrumentation that is used to observe the fjord in its different parts. The lander records bottom water temperature, salinity and turbidity. Furthermore, It monitors currents and backscatter through the whole water column using active acoustics (ADCP and echosounder). A camera is used to observe fishes and other animals close to the lander (Figure 1).
Methodology
We organize and manage data storage and access for all data coming in from the lander. So far, ~3.8 TB have been collected. The data are automatically transferred to Educloud and further processed within an Educloud project. We provide access to the data to UiO scientists and students, e.g. for a digital twin project of the Oslofjord.
We have developed a multi-step processing pipeline that includes shell, python and matlab scripts. The pipeline starts with data management tasks and data conversion from proprietary raw data to netcdf. Furthermore, we have developed tools for postprocessing and data analysis, such as noise removal, identification of fish schools and individual fishes based on the echosounder data and target tracking for assessing swimming speeds of fishes and plankton. All the analysis steps and the automatic pipeline are built and running inside Educloud in collaboration with the IT Department at the University of Oslo.
Further exploratory data analyses include integration of backscatter metrics to assess fish and plankton densities and analysis of environmental parameters to identify temporal changes and events. Finally, the data are visualized and communicated through the Innsikt Oslofjord app (Figure 2).
Read article about the Lander here (In Norwegian).
