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Dataset Title:  NAUTILOS - CS - low-cost drifters for marine litter coastal monitoring Subscribe RSS
Institution:  CNR-ISMAR   (Dataset ID: CS_Sea_Clenar_mini_drifter)
Range: longitude = 5.463168 to 10.631103°E, latitude = 42.833366 to 44.39942°N
Information:  Summary ? | License ? | FGDC | ISO 19115 | Metadata | Background (external link) | Subset | Data Access Form | Files
 
Graph Type:  ?
X Axis: 
Y Axis: 
Color: 
-1+1
 
Constraints ? Optional
Constraint #1 ?
Optional
Constraint #2 ?
       
       
       
       
       
 
Server-side Functions ?
 distinct() ?
? ("Hover here to see a list of options. Click on an option to select it.Hover here to see a list of options. Click on an option to select it.Hover here to see a list of options. Click on an option to select it.Hover here to see a list of options. Click on an option to select it.")
 
Graph Settings
Marker Type:   Size: 
Color: 
Color Bar:   Continuity:   Scale: 
   Minimum:   Maximum:   N Sections: 
Draw land mask: 
Y Axis Minimum:   Maximum:   
 
(Please be patient. It may take a while to get the data.)
 
Optional:
Then set the File Type: (File Type information)
and
or view the URL:
(Documentation / Bypass this form ? )
    Click on the map to specify a new center point. ?
Zoom: 
Time range:           -   +  
[The graph you specified. Please be patient.]

 

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:

The Dataset Attribute Structure (.das) for this Dataset

Attributes {
 s {
  mission {
    String long_name "mission";
  }
  ID {
    String long_name "drifter ID";
  }
  time {
    String _CoordinateAxisType "Time";
    String axis "T";
    String ioos_category "Time";
    String long_name "Time";
    String source_name "time";
    String standard_name "time";
    String time_origin "01-JAN-1970 00:00:00";
    String time_precision "1970-01-01T00:00Z";
    String units "seconds since 1970-01-01T00:00:00Z";
  }
  latitude {
    String _CoordinateAxisType "Lat";
    Float64 actual_range 42.833365, 44.39942;
    String axis "Y";
    Float64 colorBarMaximum 90.0;
    Float64 colorBarMinimum -90.0;
    String ioos_category "Location";
    String long_name "Latitude";
    String standard_name "latitude";
    String units "degrees_north";
  }
  longitude {
    String _CoordinateAxisType "Lon";
    Float64 actual_range 5.463168, 10.631103;
    String axis "X";
    Float64 colorBarMaximum 180.0;
    Float64 colorBarMinimum -180.0;
    String ioos_category "Location";
    String long_name "Longitude";
    String standard_name "longitude";
    String units "degrees_east";
  }
  drifter_type {
    String long_name "Drifter Type";
  }
  speed {
    Float32 actual_range 0.0, 63.07;
    String long_name "Speed";
    String units "km/h";
  }
  direction {
    Float32 actual_range 0.0, 359.5;
    Float64 colorBarMaximum 360.0;
    Float64 colorBarMinimum 0.0;
    String long_name "Direction";
    String units "degrees";
  }
  temp_surface {
    Float32 _FillValue NaN;
    Float32 actual_range 12.06, 42.12;
    String long_name "Temp Surface";
    String SDN "SDN:P01::TEMPPR01";
    String units "°C";
  }
  temp_air {
    Float32 _FillValue NaN;
    Float32 actual_range 11.81, 39.56;
    String long_name "Temp Air";
    String SDN "SDN:P01::CTMPZZ01";
    String units "°C";
  }
 }
  NC_GLOBAL {
    String cdm_data_type "Other";
    String citation "This dataset was founded by: European Union's Horizon 2020 research and innovation programme under grant agreement No. 101000825 (NAUTILOS) and ML-DAR ricerca libera-9999.521 RL2019 and ML-CSA ricerca libera -9999.826 RL2020 projects by INGV. This output reflects only the author's view and the European Union cannot be held responsible for any use that may be made of the information contained therein.";
    String Conventions "COARDS, CF-1.6, ACDD-1.3, NCCSV-1.1";
    String data_DOI "https://doi.org/10.3390/s23020935 https://doi.org/10.13127/misc/73";
    Float64 Easternmost_Easting 10.631103;
    String EDMERP_code "13720";
    String foundig_sources "European Union H2020 grant agreement No. 101000825 (NAUTILOS); ML-DAR ricerca libera-9999.521 RL2019 and ML-CSA ricerca libera -9999.826 RL2020 projects by INGV";
    String funding_ID "101000825";
    String funding_statement "This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No. 101000825 (NAUTILOS). This output reflects only the author's view and the European Union cannot be held responsible for any use that may be made of the information contained therein";
    Float64 geospatial_lat_max 44.39942;
    Float64 geospatial_lat_min 42.833365;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max 10.631103;
    Float64 geospatial_lon_min 5.463168;
    String geospatial_lon_units "degrees_east";
    String history 
"2024-04-15T18:18:43Z (local files)
2024-04-15T18:18:43Z https://erddap.emodnet-physics.eu/tabledap/CS_Sea_Clenar_mini_drifter.das";
    String infoUrl "http://www.ismar.cnr.it/";
    String institution "CNR-ISMAR";
    String keywords "air, direction, latitude, longitude, speed, surface, temp_air, temp_surface, temperature";
    String license "CC-BY 4.0";
    Float64 Northernmost_Northing 44.39942;
    String Project_DOI "https://doi.org/10.3030/101000825";
    String projects "NAUTILOS, RAISE Spoke 3, ML-CSA, ML-DAR";
    String sourceUrl "(local files)";
    Float64 Southernmost_Northing 42.833365;
    String standard_name_vocabulary "CF Standard Name Table v70";
    String subsetVariables "ID, mission, drifter_type";
    String summary "This project utilizes traditional marine litter to create drifters equipped with electronic devices for analyzing sea routes. The use of ordinary litter provides a realistic model for studying ocean currents, while also being cost-effective and easily assembled by makers, associations, and schools. The drifters feature solar panels for energy and transmit data via GSM. The project aims to enhance monitoring efforts and raise awareness about marine litter in alignment with the Marine Strategy Framework Directive. The drifters are equipped with self-sustaining solar panels and transmit data through the GSM network. The novelty lies in the specially created software that records data in case of signal loss and transmits it as soon as the signal returns.";
    String title "NAUTILOS - CS - low-cost drifters for marine litter coastal monitoring";
    Float64 Westernmost_Easting 5.463168;
  }
}

 

Using tabledap to Request Data and Graphs from Tabular Datasets

tabledap lets you request a data subset, a graph, or a map from a tabular dataset (for example, buoy data), via a specially formed URL. tabledap uses the OPeNDAP (external link) Data Access Protocol (DAP) (external link) and its selection 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.

Tabledap request URLs must be in the form
https://coastwatch.pfeg.noaa.gov/erddap/tabledap/datasetID.fileType{?query}
For example,
https://coastwatch.pfeg.noaa.gov/erddap/tabledap/pmelTaoDySst.htmlTable?longitude,latitude,time,station,wmo_platform_code,T_25&time>=2015-05-23T12:00:00Z&time<=2015-05-31T12:00:00Z
Thus, the query is often a comma-separated list of desired variable names, followed by a collection of constraints (e.g., variable<value), each preceded by '&' (which is interpreted as "AND").

For details, see the tabledap Documentation.


 
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