Real-time reporting of marine ecosystem metrics from active acoustic sensors
Marine autonomous vehicles (MAVs) carrying active acoustic sensors(echosounders) are being used for ecosystem research, but high data volumes are presenting challenges for data storage, processing and communication. One of the appeals of autonomous vehicles is directing them to regions of interest a...
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| Format: | Text |
| Language: | English |
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2020
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| Online Access: | http://nora.nerc.ac.uk/id/eprint/530054/ https://nora.nerc.ac.uk/id/eprint/530054/1/2020BlackwellREPhD-20201215.pdf |
| Summary: | Marine autonomous vehicles (MAVs) carrying active acoustic sensors(echosounders) are being used for ecosystem research, but high data volumes are presenting challenges for data storage, processing and communication. One of the appeals of autonomous vehicles is directing them to regions of interest and receiving data in real-time, but current satellite networks have insufficient bandwidth for real-time acoustic data transmission. We seek solutions using data compression or summarisation. We first explore the use of generic, lossless data compression algorithmsr(e.g. ZIP) and find that they do not deliver the necessary reduction in data size. We then convert acoustic data to echograms and examine the role of colour palettes in echogram interpretation, but image compression is still unsatisfactory. Using echosounder data from the Southern Ocean ecosystem at South Georgia, collected by research vessels (which are easier to work with and more readily available than MAV acoustic data), we compute acoustic summary metrics and assess their correlation to independent ecosystem indices. There is a strong correlation between abundance and traditional krill density estimates. |
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