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Dataset Title:	Soft sediments by grain size (in mm)
Institution:	Rutgers University (Dataset ID: Soft_Sediments_Size)
Information:	Summary \| License \| FGDC \| ISO 19115 \| Metadata \| Background \| Data Access Form \| Files

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Graph Type:
X Axis:
Y Axis:
Color:

Dimensions

Start

Stop

latitude (degrees_north)

longitude (degrees_east)

Graph Settings
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:
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Click on the map to specify a new center point.

Zoom:

[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:

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 {
  latitude {
    UInt32 _ChunkSizes 2420;
    String _CoordinateAxisType "Lat";
    Float32 actual_range 31.44976, 46.85506;
    String axis "Y";
    String ioos_category "Location";
    String long_name "Latitude";
    String standard_name "latitude";
    String units "degrees_north";
  }
  longitude {
    UInt32 _ChunkSizes 2452;
    String _CoordinateAxisType "Lon";
    Float32 actual_range -78.55391, -62.94482;
    String axis "X";
    String ioos_category "Location";
    String long_name "Longitude";
    String standard_name "longitude";
    String units "degrees_east";
  }
  grainsize {
    Float32 _FillValue -999999.0;
    Float64 colorBarMaximum 5.0;
    Float64 colorBarMinimum 0.0;
    String ioos_category "Unknown";
    String long_name "Grain Size";
    String units "mm";
  }
  NC_GLOBAL {
    String cdm_data_type "Grid";
    String comment "This layer classifies soft-sediments based on their grain size. Source data include USGS usSeabed: Atlantic coast offshore surficial sediment data (Data series 118, version 1.0) and the USGS East Coast Sediment Texture Database (2005), Woods Hole Coastal and Marine Science Center. Point-based data were interpolated using krigging tools to create this layer. Resulting values were classified based on grain-size according to the Wentworth (1922) scale. This classification process resulted in the following classes: clay (< 0.002 mmm), silt (0.024 - 0.06), very fine sand (0.06 - 0.125 mm), fine sand (0.125 - 0.25 mm), medium sand (0.25 - 0.5 mm), coarse sand (0.5 - 1.0 mm), very coarse sand (1 - 2 mm), and Gravel/granule (> 2 mm). Finally, point data was interpolated using kriging to create the resulting raster layer. The spatial resolution of this layer is 500 meters.";
    String Conventions "CF-1.6, COARDS, ACDD-1.3";
    Float64 Easternmost_Easting -62.94482;
    Float64 geospatial_lat_max 46.85506;
    Float64 geospatial_lat_min 31.44976;
    Float64 geospatial_lat_resolution 0.0063684580405126085;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max -62.94482;
    Float64 geospatial_lon_min -78.55391;
    Float64 geospatial_lon_resolution 0.006368457772337822;
    String geospatial_lon_units "degrees_east";
    String history 
"Created by Eli Hunter (hunter@marine.rutgers.edu),20-Apr-2020 13:25:54
2025-02-21T14:35:03Z (local files)
2025-02-21T14:35:03Z https://nybsand.marine.rutgers.edu/griddap/Soft_Sediments_Size.das";
    String infoUrl "https://portal.midatlanticocean.org/data-catalog";
    String institution "Rutgers University";
    String keywords "data, grain, grainsize, sediments, size, soft";
    String license 
"The data may be used and redistributed for free but is not intended
for legal use, since it may contain inaccuracies. Neither the data
Contributor, ERD, NOAA, nor the United States Government, nor any
of their employees or contractors, makes any warranty, express or
implied, including warranties of merchantability and fitness for a
particular purpose, or assumes any legal liability for the accuracy,
completeness, or usefulness, of this information.";
    Float64 Northernmost_Northing 46.85506;
    String source "http://nature.org/namera/,NAMERA_Soft_sediments_2015_geotiff.zip,SoftSediments.tif";
    String sourceUrl "(local files)";
    Float64 Southernmost_Northing 31.44976;
    String standard_name_vocabulary "CF Standard Name Table v55";
    String summary "This dataset was created for the Northwest Atlantic Marine Ecoregional Assessment (NAMERA) in order to map soft sediments based on their grain size (in mm). This version (2) is an update of the original 2010 soft sediments layer using new data. THIS DATASET WAS NOT CREATED FOR NAVIGATIONAL PURPOSES AND AS SUCH SHOULD NOT BE USED FOR NAVIGATION.";
    String title "Soft sediments by grain size (in mm)";
    Float64 Westernmost_Easting -78.55391;
  }
}

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.