Legacy Data: How Decades of Seabed Sampling Can Produce Robust Predictions and Versatile Products
Sediment maps developed from categorical data are widely applied to support marine spatial planning across various fields. However, deriving maps independently of sediment classification potentially improves our understanding of environmental gradients and reduces issues of harmonising data across j...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2019-04-01
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| Series: | Geosciences |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2076-3263/9/4/182 |
| _version_ | 1818579206553993216 |
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| author | Peter J Mitchell John Aldridge Markus Diesing |
| author_facet | Peter J Mitchell John Aldridge Markus Diesing |
| author_sort | Peter J Mitchell |
| collection | DOAJ |
| description | Sediment maps developed from categorical data are widely applied to support marine spatial planning across various fields. However, deriving maps independently of sediment classification potentially improves our understanding of environmental gradients and reduces issues of harmonising data across jurisdictional boundaries. As the groundtruth samples are often measured for the fractions of mud, sand and gravel, this data can be utilised more effectively to produce quantitative maps of sediment composition. Using harmonised data products from a range of sources including the European Marine Observation and Data Network (EMODnet), spatial predictions of these three sediment fractions were generated for the north-west European continental shelf using the random forest algorithm. Once modelled these sediment fraction maps were classified using a range of schemes to show the versatility of such an approach, and spatial accuracy maps were generated to support their interpretation. The maps produced in this study are to date the highest resolution quantitative sediment composition maps that have been produced for a study area of this extent and are likely to be of interest for a wide range of applications such as ecological and biophysical studies. |
| first_indexed | 2024-12-16T06:58:01Z |
| format | Article |
| id | doaj.art-2ab557f5e71841c1821bad4d7da9754d |
| institution | Directory Open Access Journal |
| issn | 2076-3263 |
| language | English |
| last_indexed | 2024-12-16T06:58:01Z |
| publishDate | 2019-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Geosciences |
| spelling | doaj.art-2ab557f5e71841c1821bad4d7da9754d2022-12-21T22:40:14ZengMDPI AGGeosciences2076-32632019-04-019418210.3390/geosciences9040182geosciences9040182Legacy Data: How Decades of Seabed Sampling Can Produce Robust Predictions and Versatile ProductsPeter J Mitchell0John Aldridge1Markus Diesing2Centre for Environment, Fisheries and Aquaculture Science (Cefas), Pakefield Road, Lowestoft NR33 0HT, UKCentre for Environment, Fisheries and Aquaculture Science (Cefas), Pakefield Road, Lowestoft NR33 0HT, UKGeological Survey of Norway (NGU), Postal Box 6315 Torgarden, 7491 Trondheim, NorwaySediment maps developed from categorical data are widely applied to support marine spatial planning across various fields. However, deriving maps independently of sediment classification potentially improves our understanding of environmental gradients and reduces issues of harmonising data across jurisdictional boundaries. As the groundtruth samples are often measured for the fractions of mud, sand and gravel, this data can be utilised more effectively to produce quantitative maps of sediment composition. Using harmonised data products from a range of sources including the European Marine Observation and Data Network (EMODnet), spatial predictions of these three sediment fractions were generated for the north-west European continental shelf using the random forest algorithm. Once modelled these sediment fraction maps were classified using a range of schemes to show the versatility of such an approach, and spatial accuracy maps were generated to support their interpretation. The maps produced in this study are to date the highest resolution quantitative sediment composition maps that have been produced for a study area of this extent and are likely to be of interest for a wide range of applications such as ecological and biophysical studies.https://www.mdpi.com/2076-3263/9/4/182Particle size analysisrandom forestaccuracyEuropean continental shelfmudsandgravel |
| spellingShingle | Peter J Mitchell John Aldridge Markus Diesing Legacy Data: How Decades of Seabed Sampling Can Produce Robust Predictions and Versatile Products Geosciences Particle size analysis random forest accuracy European continental shelf mud sand gravel |
| title | Legacy Data: How Decades of Seabed Sampling Can Produce Robust Predictions and Versatile Products |
| title_full | Legacy Data: How Decades of Seabed Sampling Can Produce Robust Predictions and Versatile Products |
| title_fullStr | Legacy Data: How Decades of Seabed Sampling Can Produce Robust Predictions and Versatile Products |
| title_full_unstemmed | Legacy Data: How Decades of Seabed Sampling Can Produce Robust Predictions and Versatile Products |
| title_short | Legacy Data: How Decades of Seabed Sampling Can Produce Robust Predictions and Versatile Products |
| title_sort | legacy data how decades of seabed sampling can produce robust predictions and versatile products |
| topic | Particle size analysis random forest accuracy European continental shelf mud sand gravel |
| url | https://www.mdpi.com/2076-3263/9/4/182 |
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