ERDDAP > info > cidcoBenthicSubstrateAiGrossePointe

Grid DAP Data	Sub- set	Table DAP Data	Make A Graph	W M S	Source Data Files	Title	Sum- mary	FGDC, ISO, Metadata	Back- ground Info	RSS	E mail	Institution	Dataset ID
data			graph	M	files	Classification of Benthic Substrates by Artificial Intelligence on the St. Lawrence Shoreline - Grosse Pointe | Classification des substrats benthiques par intelligence artificielle sur le littoral du Saint-Laurent - Grosse Pointe		F   I   M	background			Interdisciplinary...	cidcoBenthicSubstrateAiGrossePointe

The Dataset's Variables and Attributes

Row Type	Variable Name	Attribute Name	Data Type	Value
attribute	NC_GLOBAL	cdm_data_type	String	Grid
attribute	NC_GLOBAL	comment	String	Do not use unsupervised model data for navigation purposes The original coordinate system of the dataset was NAD83 / UTM zone 19N (EPSG:26919). The data were then reprojected into the standard WGS84 coordinate system (EPSG:4326). The original coordinate systeme (EPSG:26919) was retained for the downloadable .tif georeferenced images associated with the dataset.
attribute	NC_GLOBAL	comment_fr	String	Ne pas utiliser à des fins de navigation et en particulier les données du modèle non supervisé. Le système de coordonnées d'origine des données était le système NAD83 / UTM zone 19N (EPSG:26919). Les données ont ensuite été reprojetées dans le système de coordonnées standard WGS84 (EPSG:4326). Le système de coordonnées d'origine (EPSG:26919) a cependant été conservé pour les images georeferencées téléchargeables .tif associées au jeu de données.
attribute	NC_GLOBAL	contributor_institution	String	CIDCO, CIDCO, Fisheries and Oceans Canada, CIDCO, CIDCO
attribute	NC_GLOBAL	contributor_name	String	Guillaume Labbé-Morissette, Patrick Charron-Morneau, Yanick Gendreau, Théau Leclercq, Dominic Ndeh Munang
attribute	NC_GLOBAL	contributor_role	String	owner, distributor, collaborator, metadata custodian, collaborator
attribute	NC_GLOBAL	Conventions	String	CF-1.10 COARDS ACDD-1.3
attribute	NC_GLOBAL	creator_name	String	Interdisciplinary Centre for the Development of Ocean Mapping
attribute	NC_GLOBAL	creator_name_fr	String	Centre Interdisciplinaire de Développement en Cartographie des Océans (CIDCO)
attribute	NC_GLOBAL	creator_type	String	institution
attribute	NC_GLOBAL	DOI	String	https://doi.org/10.26071/ogsl-66c132fc-b150
attribute	NC_GLOBAL	Easternmost_Easting	double	-68.3765
attribute	NC_GLOBAL	geospatial_lat_max	double	49.03369
attribute	NC_GLOBAL	geospatial_lat_min	double	49.02966
attribute	NC_GLOBAL	geospatial_lat_units	String	degrees_north
attribute	NC_GLOBAL	geospatial_lon_max	double	-68.3765
attribute	NC_GLOBAL	geospatial_lon_min	double	-68.38731
attribute	NC_GLOBAL	geospatial_lon_units	String	degrees_east
attribute	NC_GLOBAL	grid_mapping_epsg_code	String	EPSG:4326
attribute	NC_GLOBAL	grid_mapping_epsg_code_url	String	https://epsg.io/4326
attribute	NC_GLOBAL	grid_mapping_geographic_crs_name	String	WGS 84
attribute	NC_GLOBAL	grid_mapping_inverse_flattening	String	298.2572236
attribute	NC_GLOBAL	grid_mapping_name	String	latitude_longitude
attribute	NC_GLOBAL	grid_mapping_prime_meridian_name	String	Greenwich
attribute	NC_GLOBAL	grid_mapping_semi_major_axis	String	6378137
attribute	NC_GLOBAL	history	String	Data and metadata were standardized and then checked with the SLGO data validation tool. The data were converted from the NAD83 / UTM zone 19N coordinate system to the WGS84 coordinate system and transformed from a tabular to a gridded format
attribute	NC_GLOBAL	infoUrl	String	https://www.cidco.ca/
attribute	NC_GLOBAL	institution	String	Interdisciplinary Centre for the Development of Ocean Mapping
attribute	NC_GLOBAL	institution_fr	String	Centre Interdisciplinaire de Développement en Cartographie des Océans
attribute	NC_GLOBAL	instrument	String	Multibeam echosounder, Hydrins attitude sensor, Septentrio GNSS Receiver
attribute	NC_GLOBAL	instrument_0_description	String	MBES Reson Seabat 7125SV dual frequency (400 and 200 kHz)
attribute	NC_GLOBAL	instrument_0_identifier	String	https://vocab.nerc.ac.uk/collection/L22/current/TOOL0772/
attribute	NC_GLOBAL	instrument_0_name	String	Multibeam Echosounder
attribute	NC_GLOBAL	instrument_1_description	String	Navigation correction (roll, pitch, heading, heave)
attribute	NC_GLOBAL	instrument_1_identifier	String	https://vocab.nerc.ac.uk/collection/L22/current/TOOL0833/
attribute	NC_GLOBAL	instrument_1_name	String	Hydrins attitude sensor
attribute	NC_GLOBAL	instrument_2_description	String	GNSS (Global Navigation Satellite System) Receiver and Antenna using for positioning
attribute	NC_GLOBAL	instrument_2_identifier	String	https://vocab.nerc.ac.uk/collection/L05/current/301/
attribute	NC_GLOBAL	instrument_2_name	String	Septentrio GNSS Receiver
attribute	NC_GLOBAL	instrument_fr	String	Sondeur multifaisceaux, station inertielle Hydrins, recepteur GNSS Septentrio
attribute	NC_GLOBAL	keywords	String	artificial intelligence, benthic substrates classification, benthic substrates mapping, supervised machine learning, unsupervised machine learning
attribute	NC_GLOBAL	keywords_fr	String	cartographie des substrats benthiques, classification des substrats benthiques, apprentissage automatique supervisé, apprentissage automatique non supervisé, intelligence artificielle
attribute	NC_GLOBAL	keywords_vocabulary	String	GCMD Science Keywords
attribute	NC_GLOBAL	license	String	Creative Commons Attribution 4.0 International license CC-BY 4.0. Allows for open sharing and adaptation of the data provided that the original creator is attributed
attribute	NC_GLOBAL	licenseUrl	String	https://creativecommons.org/licenses/by/4.0/
attribute	NC_GLOBAL	location	String	Grosse Pointe
attribute	NC_GLOBAL	marine_region	String	St. Lawrence Estuary
attribute	NC_GLOBAL	marine_region_identifier	String	http://marineregions.org/mrgid/23554
attribute	NC_GLOBAL	mission_time_coverage_end	String	2019-10-18
attribute	NC_GLOBAL	mission_time_coverage_start	String	2018-10-15
attribute	NC_GLOBAL	non_gridded_data_url	String	https://waf-cc.prod.ogsl.ca/data/ckan/cidco/ca-cioos_66c132fc-b150-4b9e-92fb-b1c6f5cc30f9/benthic_substrate_ai/csv_non-gridded_normalised-data/
attribute	NC_GLOBAL	Northernmost_Northing	double	49.03369
attribute	NC_GLOBAL	platform	String	research vessel
attribute	NC_GLOBAL	platform_vocabulary	String	https://vocab.nerc.ac.uk/collection/L06/current/
attribute	NC_GLOBAL	publisher_email	String	info at ogsl.ca
attribute	NC_GLOBAL	publisher_name	String	St. Lawrence Global Observatory
attribute	NC_GLOBAL	publisher_name_fr	String	Observatoire global du Saint-Laurent
attribute	NC_GLOBAL	publisherID	String	https://ror.org/03wfagk22
attribute	NC_GLOBAL	related_datasets	String	https://erddap.ogsl.ca/erddap/griddap/cidcoBenthicSubstrateAiBaieDesAnglais.graph https://erddap.ogsl.ca/erddap/griddap/cidcoBenthicSubstrateAiFranquelin.graph https://erddap.ogsl.ca/erddap/griddap/cidcoBenthicSubstrateAiGodbout.graph https://erddap.ogsl.ca/erddap/griddap/cidcoBenthicSubstrateAiMarina.graph https://erddap.ogsl.ca/erddap/griddap/cidcoBenthicSubstrateAiManicouagan.graph https://erddap.ogsl.ca/erddap/griddap/cidcoBenthicSubstrateAiPointeParadis.graph https://erddap.ogsl.ca/erddap/griddap/cidcoBenthicSubstrateAiStLudger.graph
attribute	NC_GLOBAL	sourceUrl	String	(local files)
attribute	NC_GLOBAL	Southernmost_Northing	double	49.02966
attribute	NC_GLOBAL	standard_name_nerc_vocabulary	String	The NERC Vocabulary Server (NVS)
attribute	NC_GLOBAL	standard_name_other_vocabulary	String	dwc: Darwin Core List of Terms (v 2023-09); dcmi: Dublin Core Metadata Initiative Metadata Terms (v 2020-01)
attribute	NC_GLOBAL	standard_name_vocabulary	String	CF Standard Name Table v79
attribute	NC_GLOBAL	summary	String	The substrate classification data were generated with two machine learning models: (1) A first model trained with field truth data from Fisheries and Oceans Canada and using a gradient reinforcement method. (2) A second model trained without field truth data and based on a Gaussian mixture method. The aim of generating this data is to facilitate the classification of substrates for various fields (fishing, dredging, gas and oil) via artificial intelligence, and to make it more accessible because it is less expensive from an operational point of view.
attribute	NC_GLOBAL	summary_fr	String	Les données de classifications des substrats ont été générés avec deux modèles d'apprentissage automatique : (1) Un premier modèle entraîné avec des données de vérité terrain provenant de Pêches et Océans Canada et utilisant une méthode de renforcement du gradient. (2) Un deuxième modèle entraîné sans données de vérité terrain et s'appuyant sur une méthode de mélange gaussien. L'ambition de la génération de ces données est de faciliter la classification des substrats pour des domaines variés (la pêche, le dragage, gaz et pétrole) via l'intelligence artificielle, et la rendre plus accessible car moins couteux d'un point de vue opérationnel.
attribute	NC_GLOBAL	time_coverage_end	String	2018-10-19
attribute	NC_GLOBAL	time_coverage_start	String	2018-10-19
attribute	NC_GLOBAL	title	String	Classification of Benthic Substrates by Artificial Intelligence on the St. Lawrence Shoreline - Grosse Pointe | Classification des substrats benthiques par intelligence artificielle sur le littoral du Saint-Laurent - Grosse Pointe
attribute	NC_GLOBAL	Westernmost_Easting	double	-68.38731
dimension	time		double	nValues=1, onlyValue=2018-10-19
attribute	time	_CoordinateAxisType	String	Time
attribute	time	actual_range	double	1.5399072E9, 1.5399072E9
attribute	time	axis	String	T
attribute	time	coverage_content_type	String	coordinate
attribute	time	ioos_category	String	Time
attribute	time	long_name	String	Sampling Date
attribute	time	nerc_identifier	String	https://vocab.nerc.ac.uk/collection/P01/current/ADATAA01/
attribute	time	nerc_standard_name	String	Date
attribute	time	standard_name	String	time
attribute	time	time_origin	String	01-JAN-1970 00:00:00
attribute	time	time_precision	String	1970-01-01
attribute	time	units	String	seconds since 1970-01-01T00:00:00Z
dimension	latitude		float	nValues=447, evenlySpaced=false, averageSpacing=9.035874439462331E-6
attribute	latitude	_CoordinateAxisType	String	Lat
attribute	latitude	actual_range	float	49.02966, 49.03369
attribute	latitude	axis	String	Y
attribute	latitude	description	String	Latitude coordinates of sampling in decimal degree (degrees north)
attribute	latitude	ioos_category	String	Location
attribute	latitude	long_name	String	Latitude
attribute	latitude	nerc_identifier	String	https://vocab.nerc.ac.uk/collection/P07/current/CFSN0600/
attribute	latitude	standard_name	String	latitude
attribute	latitude	units	String	degrees_north
dimension	longitude		float	nValues=772, evenlySpaced=false, averageSpacing=1.402075226978784E-5
attribute	longitude	_CoordinateAxisType	String	Lon
attribute	longitude	actual_range	float	-68.38731, -68.3765
attribute	longitude	axis	String	X
attribute	longitude	description	String	Longitude coordinates of sampling in decimal degree (degrees east)
attribute	longitude	ioos_category	String	Location
attribute	longitude	long_name	String	Longitude
attribute	longitude	nerc_identifier	String	https://vocab.nerc.ac.uk/collection/P07/current/CFSN0554/
attribute	longitude	standard_name	String	longitude
attribute	longitude	units	String	degrees_east
variable	sea_floor_depth_below_sea_surface		float	time, latitude, longitude
attribute	sea_floor_depth_below_sea_surface	axis	String	Z
attribute	sea_floor_depth_below_sea_surface	cidco_georeferenced_map_epsg	String	NAD83 / UTM zone19N (EPSG:26919)
attribute	sea_floor_depth_below_sea_surface	cidco_georeferenced_map_url	String	https://waf-cc.prod.ogsl.ca/data/ckan/cidco/ca-cioos_66c132fc-b150-4b9e-92fb-b1c6f5cc30f9/benthic_substrate_ai/geotiff_map/bathymetry/03-04_georeferenced.tif
attribute	sea_floor_depth_below_sea_surface	colorBarMaximum	double	5.0
attribute	sea_floor_depth_below_sea_surface	colorBarMinimum	double	1.0
attribute	sea_floor_depth_below_sea_surface	colorBarPalette	String	ReverseRainbow
attribute	sea_floor_depth_below_sea_surface	ioos_category	String	Bathymetry
attribute	sea_floor_depth_below_sea_surface	long_name	String	Sea Floor Depth
attribute	sea_floor_depth_below_sea_surface	nerc_identifier	String	https://vocab.nerc.ac.uk/collection/P07/current/CFV13N17/
attribute	sea_floor_depth_below_sea_surface	positive	String	down
attribute	sea_floor_depth_below_sea_surface	standard_name	String	sea_floor_depth_below_sea_surface
attribute	sea_floor_depth_below_sea_surface	units	String	m
variable	boosting_class_id		float	time, latitude, longitude
attribute	boosting_class_id	cidco_georeferenced_map_epsg	String	NAD83 / UTM zone19N (EPSG:26919)
attribute	boosting_class_id	cidco_georeferenced_map_url	String	https://waf-cc.prod.ogsl.ca/data/ckan/cidco/ca-cioos_66c132fc-b150-4b9e-92fb-b1c6f5cc30f9/benthic_substrate_ai/geotiff_map/supervised_model/03-01_georeferenced.tif
attribute	boosting_class_id	colorBarContinuous	String	false
attribute	boosting_class_id	colorBarMaximum	double	5.5
attribute	boosting_class_id	colorBarMinimum	double	-0.5
attribute	boosting_class_id	colorBarNSections	int	6
attribute	boosting_class_id	colorBarPalette	String	Rainbow
attribute	boosting_class_id	description	String	Index of substrate classification according to supervised model : 0 - Block 1 - Cobble 2 - Gravel 3 - Bedrock 4 - Sand 5 - Sandy Mud
attribute	boosting_class_id	ioos_category	String	Other
attribute	boosting_class_id	long_name	String	Boosting Class ID
attribute	boosting_class_id	original_name	String	boosting class
attribute	boosting_class_id	units	String	unitless
variable	gmm_class_id		float	time, latitude, longitude
attribute	gmm_class_id	cidco_georeferenced_map_epsg	String	NAD83 / UTM zone19N (EPSG:26919)
attribute	gmm_class_id	cidco_georeferenced_map_url	String	https://waf-cc.prod.ogsl.ca/data/ckan/cidco/ca-cioos_66c132fc-b150-4b9e-92fb-b1c6f5cc30f9/benthic_substrate_ai/geotiff_map/unsupervised_model/03-02_georeferenced.tif
attribute	gmm_class_id	colorBarContinuous	String	false
attribute	gmm_class_id	colorBarMaximum	double	6.5
attribute	gmm_class_id	colorBarMinimum	double	-0.5
attribute	gmm_class_id	colorBarNSections	int	7
attribute	gmm_class_id	colorBarPalette	String	ReverseRainbow
attribute	gmm_class_id	description	String	Index of substrate classification according to unsupervised model : 0 - Fit the most with the supervised sand class 1 - Unknown class 2 - Fit the most with the supervised gravel class 3 - Unknown class 4 - Fit the most with the supervised block class 5 - Fit the most with the supervised cobble class 6 - Fit the most with the supervised bedrock class
attribute	gmm_class_id	ioos_category	String	Other
attribute	gmm_class_id	long_name	String	GMM Class ID
attribute	gmm_class_id	original_name	String	gmm class
attribute	gmm_class_id	units	String	unitless

The information in the table above is also available in other file formats (.csv, .htmlTable, .itx, .json, .jsonlCSV1, .jsonlCSV, .jsonlKVP, .mat, .nc, .nccsv, .tsv, .xhtml) via a RESTful web service.