ERDDAP > griddap > Data Access Form

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 | Files | Make a graph

 

Dimensions	Start	Stride	Stop	Size	Spacing
time (Sampling Date, UTC)				1	(just one value)
latitude (degrees_north)				2421	9.0E-6 (uneven)
longitude (degrees_east)				2040	1.37126E-5 (uneven)

Grid Variables (which always also download all of the dimension variables)

sea_floor_depth_below_sea_surface (m)

boosting_class_id (unitless)

gmm_class_id (unitless)

File type: (more information) .asc - View OPeNDAP-style ISO-8859-1 comma-separated text. .csv - Download a ISO-8859-1 comma-separated text table (line 1: names; line 2: units; ISO 8601 times). .csvp - Download a ISO-8859-1 .csv file with line 1: name (units). Times are ISO 8601 strings. .csv0 - Download a ISO-8859-1 .csv file without column names or units. Times are ISO 8601 strings. .das - View the dataset's metadata via an ISO-8859-1 OPeNDAP Dataset Attribute Structure (DAS). .dds - View the dataset's structure via an ISO-8859-1 OPeNDAP Dataset Descriptor Structure (DDS). .dods - OPeNDAP clients use this to download the data in the DODS binary format. .esriAscii - Download an ISO-8859-1 ESRI ASCII file (latitude longitude data only; longitude must be all below or all above 180). .fgdc - View the dataset's UTF-8 FGDC .xml metadata. .graph - View a Make A Graph web page. .help - View a web page with a description of griddap. .html - View an OPeNDAP-style HTML Data Access Form. .htmlTable - View a UTF-8 .html web page with the data in a table. Times are ISO 8601 strings. .iso19115 - View the dataset's ISO 19115-2/19139 UTF-8 .xml metadata. .itx - Download an ISO-8859-1 Igor Text File. Each axis variable and each data variable becomes a wave. .json - View a table-like UTF-8 JSON file (missing value = 'null'; times are ISO 8601 strings). .jsonlCSV1 - View a UTF-8 JSON Lines CSV file with column names on line 1 (mv = 'null'; times are ISO 8601 strings). .jsonlCSV - View a UTF-8 JSON Lines CSV file without column names (mv = 'null'; times are ISO 8601 strings). .jsonlKVP - View a UTF-8 JSON Lines file with Key:Value pairs (missing value = 'null'; times are ISO 8601 strings). .mat - Download a MATLAB binary file. .nc - Download a NetCDF-3 binary file with COARDS/CF/ACDD metadata. .ncHeader - View the UTF-8 header (the metadata) for the NetCDF-3 .nc file. .ncml - View the dataset's structure and metadata as a UTF-8 NCML .xml file. .nccsv - Download a NetCDF-3-like 7-bit ASCII NCCSV .csv file with COARDS/CF/ACDD metadata. .nccsvMetadata - View the dataset's metadata as the top half of a 7-bit ASCII NCCSV .csv file. .ncoJson - Download a UTF-8 NCO lvl=2 JSON file with COARDS/CF/ACDD metadata. .odvTxt - Download time,latitude,longitude,otherVariables as an ODV Generic Spreadsheet File (.txt). .timeGaps - View a UTF-8 list of gaps in the time values which are larger than the median gap. .tsv - Download a ISO-8859-1 tab-separated text table (line 1: names; line 2: units; ISO 8601 times). .tsvp - Download a ISO-8859-1 .tsv file with line 1: name (units). Times are ISO 8601 strings. .tsv0 - Download a ISO-8859-1 .tsv file without column names or units. Times are ISO 8601 strings. .wav - Download a .wav audio file. All columns must be numeric and of the same type. .xhtml - View a UTF-8 XHTML (XML) file with the data in a table. Times are ISO 8601 strings. .geotif - View a grayscale GeoTIFF .tif file (for latitude longitude data; longitude must be all below or all above 180). .kml - View a Google Earth .kml file (for latitude, longitude data only). .smallPdf - View a small .pdf image file with a graph or map. .pdf - View a standard, medium-sized .pdf image file with a graph or map. .largePdf - View a large .pdf image file with a graph or map. .smallPng - View a small .png image file with a graph or map. .png - View a standard, medium-sized .png image file with a graph or map. .largePng - View a large .png image file with a graph or map. .transparentPng - View a .png image file (just the data, without axes, landmask, or legend).

(Documentation / Bypass this form)
 
Submit (Please be patient. It may take a while to get the data.)

 

---

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
2024-11-05T16:48:31Z (local files)
2024-11-05T16:48:31Z https://erddap.ogsl.ca/erddap/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 Data Access Protocol (DAP) and its projection constraints.

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.

 

---

ERDDAP, Version 2.24
Disclaimers | Privacy Policy | Contact