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Dataset Title:  Estimated sea surface temperature at 1 km spatial resolution - Mondrian
forest (20230711T100406Z)
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Institution:  UNIGE-DITEN   (Dataset ID: unige-diten_sea_surface_temperature_final_output_MondrianForest_20230711T100406)
Information:  Summary ? | License ? | FGDC | ISO 19115 | Metadata | Background (external link) | Files | Make a graph
 
Dimensions ? Start ? Stride ? Stop ?  Size ?    Spacing ?
 latitude (degrees_north) ?      257    -0.02 (even)
  < slider >
 longitude (degrees_east) ?      397    0.02010101 (uneven)
  < slider >
 
Grid Variables (which always also download all of the dimension variables) 
 estimated_sst ?

File type: (more information)

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


 

The Dataset Attribute Structure (.das) for this Dataset

Attributes {
  latitude {
    String _CoordinateAxisType "Lat";
    Float64 _FillValue NaN;
    Float64 actual_range 39.31000000000001, 44.43000000000001;
    String axis "Y";
    String ioos_category "Location";
    String long_name "Latitude";
    String source_name "y";
    String standard_name "latitude";
    String units "degrees_north";
  }
  longitude {
    String _CoordinateAxisType "Lon";
    Float64 _FillValue NaN;
    Float64 actual_range 2.53, 10.49;
    String axis "X";
    String ioos_category "Location";
    String long_name "Longitude";
    String source_name "x";
    String standard_name "longitude";
    String units "degrees_east";
  }
  estimated_sst {
    Float64 _FillValue NaN;
    String long_name "Estimated Sst";
    String name "estimated_sst";
  }
  NC_GLOBAL {
    String acquisition_frequence "Periodic acquisition following Sentinel-3 (daily to sub-daily) observation cycles, subject to cloud coverage.";
    String acquisition_methodology "Input data acquired through satellite remote sensing using Copernicus Sentinel-3 observations.";
    String acquisition_mode "Delayed-mode acquisition using archived Sentinel-3 satellite data.";
    String cdm_data_type "Grid";
    String contributors_email "michela.castellano@unige.it; francesco.massa@unige.it;  tiziana.ciuffardi@enea.it";
    String contributors_name "Castellano, Michela; Massa, Francesco; Ciuffardi, Tiziana";
    String contributors_orcid "0000-0001-6101-0112; 0000-0001-9632-4939; 0000-0003-2512-7991";
    String contributors_role "data provision of in-situ measurements of sea surface temperature, support about the use of in situ data and results interpretation; provision of in-situ measurements of sea surface temperature, support about the use of in situ data and results interpretation; provision of in-situ measurements of sea surface temperature, support about the use of in situ data and results interpretation";
    String Conventions "COARDS, CF-1.6, ACDD-1.3";
    String creator_email "Sebastiano.Serpico@unige.it; Gabriele.Moser@unige.it; abdul.basit@edu.unige.it";
    String creator_name "Serpico, Bruno Sebastiano; Moser, Gabriele; Basit, Abdul";
    String creator_orcid "0000-0001-9858-7230; 0000-0002-3796-2938; 0000-0002-0092-6853";
    String creator_type "person; person; person";
    String creator_url "https://www.iprslab.it/";
    String data_format_original "netCDF";
    String data_version "1";
    String documentation "https://s4raise.it/dssmare/distributed_monitoring/, https://s4raise.it/dssmare/satellite_monitoring/, https://raise-spoke3.s4raise.it/project01";
    Float64 Easternmost_Easting 10.49;
    Float64 geospatial_lat_max 44.43000000000001;
    Float64 geospatial_lat_min 39.31000000000001;
    Float64 geospatial_lat_resolution 0.01999999999999999;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max 10.49;
    Float64 geospatial_lon_min 2.53;
    String geospatial_lon_units "degrees_east";
    String grid_mapping_crs_wkt "GEOGCS[\"WGS 84\"]";
    String grid_mapping_geographic_crs_name "WGS 84";
    String grid_mapping_GeoTransform "3.02 0.02 0.0 44.42 0.0 -0.02";
    String grid_mapping_horizontal_datum_name "World Geodetic System 1984";
    String grid_mapping_inverse_flattening "298.257223563";
    String grid_mapping_longitude_of_prime_meridian "0.0";
    String grid_mapping_name "latitude_longitude";
    String grid_mapping_prime_meridian_name "Greenwich";
    String grid_mapping_reference_ellipsoid_name "WGS 84";
    String grid_mapping_semi_major_axis "6378137.0";
    String grid_mapping_semi_minor_axis "6356752.314245179";
    String grid_mapping_spatial_ref "GEOGCS[\"WGS 84\"]";
    String history 
"2026-04-03T05:50:47Z (local files)
2026-04-03T05:50:47Z https://erddap.s4raise.it/erddap/griddap/unige-diten_sea_surface_temperature_final_output_MondrianForest_20230711T100406.das";
    String infoUrl "https://www.raiseliguria.it/spoke-3/";
    String inspire "Oceanographic geographical features";
    String institution "UNIGE-DITEN";
    String institution_country "IT";
    String keywords "Copernicus Programme, Earth Science > Oceans > Ocean Temperature > Water Temperature (46206E8C-8Def-406F-9E62-Da4E74633A58), Earth Science Services > Models > Machine Learning Models (fe4392b0-13a9-43ff-bacc-f44a65aed4fa), Earth Science Services > Models > Machine Learning Models > Ensemble Models > Random Forest (A68048F4-181C-4C6C-9Bfa-9E4171E9F237), Instruments > Earth Remote Sensing Instruments (6015ef7b-f3bd-49e1-9193-cc23db566b69), Ligurian Sea, Machine Learning, Marine Environment, Mondrian Forest, Random Forest, Remote Sensing, Satellite Oceanography, Sea Surface Temperature, Sentinel-3, Space-based Platforms > Earth Observation Satellites (3466eed1-2fbb-49bf-ab0b-dc08731d502b), Thermal Infrared";
    String keywords_vocabulary "GCMD Science Keywords";
    String language "XML";
    String license "CC-BY 4.0";
    String maintainer "ETT S.p.A.";
    String naming_authority "RAISE";
    Float64 Northernmost_Northing 44.43000000000001;
    String owner "UNIGE-DITEN";
    String owner_url "https://diten.unige.it/";
    String project_code "RAISE";
    String project_id "ECS00000035";
    String project_name "Robotics and AI for Socio-economic Empowerment";
    String project_statement "RAISE: Robotics and AI for Socio-economic Empowerment is an innovation ecosystem funded by the Ministry of University and Research under the National Recovery and Resilience Plan (NRRP, Mission 4, Component 2, Investment 1.5)";
    String project_url "https://www.raiseliguria.it/";
    String publisher "ETT S.p.A.";
    String sensors "Sea and Land Surface Temperature Radiometer (SLSTR) onboard Sentinel-3";
    String source "Model-generated data produced using supervised Random Forest (RF) and Mondrian Forest (MF) machine learning models (version 1.0)";
    String sourceUrl "(local files)";
    Float64 Southernmost_Northing 39.31000000000001;
    String standard_name_vocabulary "CF Standard Name Table v70";
    String summary "The dataset consists of estimated sea surface temperature (SST) obtained as the output of a machine learning model. Thermal infrared data from the Sentinel-3 mission of the Copernicus programme of the European Union, together with in situ sea-truth temperature measurements provided by colleagues at UNIGE-DISTAV and ENEA, are used to train the model within a supervised machine learning framework";
    String theme_eu_data "http://publications.europa.eu/resource/authority/data-theme/ENVI";
    String theme_eurovoc "http://publications.europa.eu/resource/authority/eurovoc/100224";
    String title "Estimated sea surface temperature at 1 km spatial resolution - Mondrian forest (20230711T100406Z)";
    String visibility "public";
    Float64 Westernmost_Easting 2.53;
  }
}

 

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.

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.


 
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