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Dataset Title:	Classification of Benthic Substrates by Artificial Intelligence on the St. Lawrence Shoreline - Pointe Paradis \| Classification des substrats benthiques par intelligence artificielle sur le littoral du Saint-Laurent - Pointe Paradis
Institution:	Interdisciplinary Centre for the Development of Ocean Mapping (Dataset ID: cidcoBenthicSubstrateAiPointeParadis)
Information:	Summary \| License \| FGDC \| ISO 19115 \| Metadata \| Background \| Data Access Form \| Files

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Graph Type:
X Axis:
Y Axis:
Color:

Dimensions

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time (UTC)

specify just 1 value →

latitude (degrees_north)

longitude (degrees_east)

Graph Settings
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Minimum:	Maximum:	N Sections:
Draw land mask:
Y Axis Minimum:	Maximum:

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Things You Can Do With Your Graphs

Well, you can do anything you want with your graphs, of course. But some things you might not have considered are:

Web page authors can embed a graph of the latest data in a web page using HTML <img> tags.
Anyone can use ERDDAPs Slide Sorter to build a personal web page that displays graphs with the latest data (or other images or HTML content), each in its own, draggable slide.

The Dataset Attribute Structure (.das) for this Dataset

Attributes {
  time {
    String _CoordinateAxisType "Time";
    Float64 actual_range 1.5395616e+9, 1.5395616e+9;
    String axis "T";
    String coverage_content_type "coordinate";
    String ioos_category "Time";
    String long_name "Sampling Date";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/ADATAA01/";
    String nerc_standard_name "Date";
    String standard_name "time";
    String time_origin "01-JAN-1970 00:00:00";
    String time_precision "1970-01-01";
    String units "seconds since 1970-01-01T00:00:00Z";
  }
  latitude {
    String _CoordinateAxisType "Lat";
    Float32 actual_range 49.04646, 49.06824;
    String axis "Y";
    String description "Latitude coordinates of sampling in decimal degree (degrees north)";
    String ioos_category "Location";
    String long_name "Latitude";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P07/current/CFSN0600/";
    String standard_name "latitude";
    String units "degrees_north";
  }
  longitude {
    String _CoordinateAxisType "Lon";
    Float32 actual_range -68.22111, -68.19315;
    String axis "X";
    String description "Longitude coordinates of sampling in decimal degree (degrees east)";
    String ioos_category "Location";
    String long_name "Longitude";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P07/current/CFSN0554/";
    String standard_name "longitude";
    String units "degrees_east";
  }
  sea_floor_depth_below_sea_surface {
    String axis "Z";
    String cidco_georeferenced_map_epsg "NAD83 / UTM zone19N (EPSG:26919)";
    String cidco_georeferenced_map_url "https://waf-cc.prod.ogsl.ca/data/ckan/cidco/ca-cioos_66c132fc-b150-4b9e-92fb-b1c6f5cc30f9/benthic_substrate_ai/geotiff_map/bathymetry/01-04_georeferenced.tif";
    Float64 colorBarMaximum 47.0;
    Float64 colorBarMinimum 2.0;
    String colorBarPalette "ReverseRainbow";
    String ioos_category "Bathymetry";
    String long_name "Sea Floor Depth";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P07/current/CFV13N17/";
    String positive "down";
    String standard_name "sea_floor_depth_below_sea_surface";
    String units "m";
  }
  boosting_class_id {
    String cidco_georeferenced_map_epsg "NAD83 / UTM zone19N (EPSG:26919)";
    String cidco_georeferenced_map_url "https://waf-cc.prod.ogsl.ca/data/ckan/cidco/ca-cioos_66c132fc-b150-4b9e-92fb-b1c6f5cc30f9/benthic_substrate_ai/geotiff_map/supervised_model/01-01_georeferenced.tif";
    String colorBarContinuous "false";
    Float64 colorBarMaximum 5.5;
    Float64 colorBarMinimum -0.5;
    Int32 colorBarNSections 6;
    String colorBarPalette "Rainbow";
    String description 
"Index of substrate classification according to supervised model : 
            0 - Block
            1 - Cobble
            2 - Gravel
            3 - Bedrock
            4 - Sand
            5 - Sandy Mud";
    String ioos_category "Other";
    String long_name "Boosting Class ID";
    String original_name "boosting class";
    String units "unitless";
  }
  gmm_class_id {
    String cidco_georeferenced_map_epsg "NAD83 / UTM zone19N (EPSG:26919)";
    String cidco_georeferenced_map_url "https://waf-cc.prod.ogsl.ca/data/ckan/cidco/ca-cioos_66c132fc-b150-4b9e-92fb-b1c6f5cc30f9/benthic_substrate_ai/geotiff_map/unsupervised_model/01-02_georeferenced.tif";
    String colorBarContinuous "false";
    Float64 colorBarMaximum 6.5;
    Float64 colorBarMinimum -0.5;
    Int32 colorBarNSections 7;
    String colorBarPalette "ReverseRainbow";
    String description 
"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";
    String ioos_category "Other";
    String long_name "GMM Class ID";
    String original_name "gmm class";
    String units "unitless";
  }
  NC_GLOBAL {
    String cdm_data_type "Grid";
    String comment 
"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.";
    String comment_fr 
"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.";
    String contributor_institution "CIDCO, CIDCO, Fisheries and Oceans Canada, CIDCO, CIDCO";
    String contributor_name "Guillaume Labbé-Morissette, Patrick Charron-Morneau, Yanick Gendreau, Théau Leclercq, Dominic Ndeh Munang";
    String contributor_role "owner, distributor, collaborator, metadata custodian, collaborator";
    String Conventions "CF-1.10 COARDS ACDD-1.3";
    String creator_name "Interdisciplinary Centre for the Development of Ocean Mapping";
    String creator_name_fr "Centre Interdisciplinaire de Développement en Cartographie des Océans (CIDCO)";
    String creator_type "institution";
    String DOI "https://doi.org/10.26071/ogsl-66c132fc-b150";
    Float64 Easternmost_Easting -68.19315;
    Float64 geospatial_lat_max 49.06824;
    Float64 geospatial_lat_min 49.04646;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max -68.19315;
    Float64 geospatial_lon_min -68.22111;
    String geospatial_lon_units "degrees_east";
    String grid_mapping_epsg_code "EPSG:4326";
    String grid_mapping_epsg_code_url "https://epsg.io/4326";
    String grid_mapping_geographic_crs_name "WGS 84";
    String grid_mapping_inverse_flattening "298.2572236";
    String grid_mapping_name "latitude_longitude";
    String grid_mapping_prime_meridian_name "Greenwich";
    String grid_mapping_semi_major_axis "6378137";
    String history 
"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
2024-11-05T16:28:15Z (local files)
2024-11-05T16:28:15Z https://erddap.ogsl.ca/griddap/cidcoBenthicSubstrateAiPointeParadis.das";
    String infoUrl "https://www.cidco.ca/";
    String institution "Interdisciplinary Centre for the Development of Ocean Mapping";
    String institution_fr "Centre Interdisciplinaire de Développement en Cartographie des Océans";
    String instrument "Multibeam echosounder, Hydrins attitude sensor, Septentrio GNSS Receiver";
    String instrument_0_description "MBES Reson Seabat 7125SV dual frequency (400 and 200 kHz)";
    String instrument_0_identifier "https://vocab.nerc.ac.uk/collection/L22/current/TOOL0772/";
    String instrument_0_name "Multibeam Echosounder";
    String instrument_1_description "Navigation correction (roll, pitch, heading, heave)";
    String instrument_1_identifier "https://vocab.nerc.ac.uk/collection/L22/current/TOOL0833/";
    String instrument_1_name "Hydrins attitude sensor";
    String instrument_2_description "GNSS (Global Navigation Satellite System) Receiver and Antenna using for positioning";
    String instrument_2_identifier "https://vocab.nerc.ac.uk/collection/L05/current/301/";
    String instrument_2_name "Septentrio GNSS Receiver";
    String instrument_fr "Sondeur multifaisceaux, station inertielle Hydrins, recepteur GNSS Septentrio";
    String keywords "artificial intelligence, benthic substrates classification, benthic substrates mapping, supervised machine learning, unsupervised machine learning";
    String keywords_fr "cartographie des substrats benthiques, classification des substrats benthiques, apprentissage automatique supervisé, apprentissage automatique non supervisé, intelligence artificielle";
    String keywords_vocabulary "GCMD Science Keywords";
    String license "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";
    String licenseUrl "https://creativecommons.org/licenses/by/4.0/";
    String location "Pointe Paradis";
    String marine_region "St. Lawrence Estuary";
    String marine_region_identifier "http://marineregions.org/mrgid/23554";
    String mission_time_coverage_end "2019-10-18";
    String mission_time_coverage_start "2018-10-15";
    String non_gridded_data_url "https://waf-cc.prod.ogsl.ca/data/ckan/cidco/ca-cioos_66c132fc-b150-4b9e-92fb-b1c6f5cc30f9/benthic_substrate_ai/csv_non-gridded_normalised-data/";
    Float64 Northernmost_Northing 49.06824;
    String platform "research vessel";
    String platform_vocabulary "https://vocab.nerc.ac.uk/collection/L06/current/";
    String publisher_email "info@ogsl.ca";
    String publisher_name "St. Lawrence Global Observatory";
    String publisher_name_fr "Observatoire global du Saint-Laurent";
    String publisherID "https://ror.org/03wfagk22";
    String related_datasets 
"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/cidcoBenthicSubstrateAiGrossePointe.graph
        https://erddap.ogsl.ca/erddap/griddap/cidcoBenthicSubstrateAiMarina.graph
        https://erddap.ogsl.ca/erddap/griddap/cidcoBenthicSubstrateAiManicouagan.graph
        https://erddap.ogsl.ca/erddap/griddap/cidcoBenthicSubstrateAiStLudger.graph";
    String sourceUrl "(local files)";
    Float64 Southernmost_Northing 49.04646;
    String standard_name_nerc_vocabulary "The NERC Vocabulary Server (NVS)";
    String standard_name_other_vocabulary "dwc: Darwin Core List of Terms (v 2023-09); dcmi: Dublin Core Metadata Initiative Metadata Terms (v 2020-01)";
    String standard_name_vocabulary "CF Standard Name Table v79";
    String summary "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.";
    String summary_fr "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.";
    String time_coverage_end "2018-10-15";
    String time_coverage_start "2018-10-15";
    String title "Classification of Benthic Substrates by Artificial Intelligence on the St. Lawrence Shoreline - Pointe Paradis | Classification des substrats benthiques par intelligence artificielle sur le littoral du Saint-Laurent - Pointe Paradis";
    Float64 Westernmost_Easting -68.22111;
  }
}

Using griddap to Request Data and Graphs from Gridded Datasets

griddap lets you request a data subset, graph, or map from a gridded dataset (for example, sea surface temperature data from a satellite), via a specially formed URL. griddap uses the OPeNDAP (external link)

Data Access Protocol (DAP) (external link)

and its projection constraints (external link)

The URL specifies what you want: the dataset, a description of the graph or the subset of the data, and the file type for the response.

(easy) You can get data by using the dataset's Data Access Form. It makes the URL for you.
(easy) You can make a graph or map by using the dataset's Make A Graph form. It makes the URL for you.
(not hard) You can bypass the forms and get the data or make a graph or map by generating the URL by hand or with a computer program or script.

griddap request URLs must be in the form
https://coastwatch.pfeg.noaa.gov/erddap/griddap/datasetID.fileType{?query}
For example,
https://coastwatch.pfeg.noaa.gov/erddap/griddap/jplMURSST41.htmlTable?analysed_sst[(2002-06-01T09:00:00Z)][(-89.99):1000:(89.99)][(-179.99):1000:(180.0)]
Thus, the query is often a data variable name (e.g., analysed_sst), followed by [(start):stride:(stop)] (or a shorter variation of that) for each of the variable's dimensions (for example, [time][latitude][longitude]).

For details, see the griddap Documentation.