DPLUS0045 Anguilla Seabed Classification derived from Pleiades data - T1
Simplified seabed classification and habitat map created from remote sensing data as part of the Darwin Plus funded project "Mapping Anguilla's 'Blue Belt' Ecosystem Services". The project develops local capacity to undertake comprehensive marine resource assessments of Anguilla's 'Blue-Belt', delivering best practice guidance for combining satellite and acoustic surveys, to extend mapping into deeper waters for the first time. The complexity of this shapefile means that it can only be dowloaded as a binary file and is not available via WMS/WFS.
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Alternate title | AI004002 |
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Date | 2018-03-30 |
Date type | Creation: Date identifies when the resource was brought into existence |
Unique resource identifier | 79db82a6-f839-4309-8240-1231a5c8db47 |
Point of contact
Organisation name | Centre for Environment Fisheries and Aquaculture Science (CEFAS) |
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Electronic mail address | datamanager@cefas.co.uk |
Role | Owner: Party that owns the resource |
Descriptive keywords
GEMET - INSPIRE themes, version 1.0 | |
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GEMET - Concepts, version 4.1.3 |
habitat
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biotope
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Spatial representation type | Vector: Vector data is used to represent geographic data |
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Spatial resolution
Denominator | 1800 |
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Language | English |
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Topic category code |
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Reference System Information
Unique resource identifier | http://www.opengis.net/def/crs/EPSG/0/3857 |
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Hierarchy level | Dataset: Information applies to the dataset |
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Lineage
Statement | Seabed classification and habitat maps were created from the remote sensing data collected by the Pleiades 1A Sensor. The data was mapped using Object based image analysis, a two-step process which involves the segmentation and then classification of an image. Before segmentation and classification, the satellite data underwent several different corrections including, radiometric calibration, atmospheric correction, orthorectification, land and cloud masking, sun glint correction and depth correction. The satellite data was segmented using the multi-resolution segmentation algorithm within Trimble's eCognition software (v9.0.0). The objects produced during the segmentation were classified using a mixture of K-nearest neighbour, random forest and support vector machines classification algorithms. All three of these algorithms take the statistics from the training dataset, created from the ground truthing data, and classify the remaining objects based on statistically driven decisions. The simplified map was classified to the simpler habitat classification of Seagrass, Algae, Bare and Mosaic. Maps were validated against a subset of the groundtruthing stations which were left out of the classification. The simplified map achieved an overall accuracy of 72.3%. For publication to EMODnet, SAERI reprojected the vector using the EPSG:4326 - WGS 84 coordinate system, cleaned the vector in mapshaper.org (https://mapshaper.org/) to eliminate gaps and overlaps, and processed the attribute table to fit the specified data exchange format. All work was conducted in QGIS v3.28.4. unless otherwise specified. SAERI used the original GUI assigned by CEFAS as this map's UUID and created the GUI AI004002. Data originally downloaded from https://data.cefas.co.uk/view/19317 |
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Distribution format | ESRI Shapefile (Version: 1) GML (Version: 3.2.1) | ||||||||||||||||||||||||||||
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Transfer options
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File identifier | 79db82a6-f839-4309-8240-1231a5c8db47 | ||||||
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Metadata language | English | ||||||
Character set | UTF8: 8-bit variable size UCS Transfer Format, based on ISO/IEC 10646 | ||||||
Hierarchy level | Dataset: Information applies to the dataset | ||||||
Date stamp | 2023-10-30T12:15:30.527Z | ||||||
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Overviews
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Associated resources
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