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Dataset Title:  [St. Joseph Bay UAV Urchin survey] - Green turtle density in St. Joseph Bay,
Florida, USA estimated by performing aerial surveys in 2016, 2017, and
2019 (RAPID: Species on the Move: Tropicalization of Western Atlantic Seagrass
Beds) Subscribe RSS
Institution:  BCO-DMO   (Dataset ID: bcodmo_dataset_986917_v1)
Information:  Summary ? | License ? | Metadata | Background (external link) | Data Access Form | Files
 
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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:

The Dataset Attribute Structure (.das) for this Dataset

Attributes {
 s {
  Flight_Date {
    String long_name "Flight_date";
    String units "unitless";
  }
  Survey {
    Int32 actual_range 1, 4;
    String long_name "Survey";
    String units "unitless";
  }
  prevpost {
    String long_name "Prevpost";
    String units "unitless";
  }
  flight {
    Int32 actual_range 1, 99;
    String long_name "Flight";
    String units "unitless";
  }
  Waypoint {
    String long_name "Waypoint";
    String units "unitless";
  }
  SG_transect1 {
    Int32 actual_range 1, 3;
    String long_name "Sg_transect1";
    String units "unitless";
  }
  SG_transect3 {
    Int32 actual_range 1, 3;
    String long_name "Sg_transect3";
    String units "unitless";
  }
  perc_vis_trans1 {
    Float32 actual_range 12.5, 67.5;
    String long_name "Perc_vis_trans1";
    String units "unitless";
  }
  perc_vis_trans3 {
    Float32 actual_range 12.5, 67.5;
    String long_name "Perc_vis_trans3";
    String units "unitless";
  }
  n_turtles_trans1 {
    Int32 actual_range 0, 18;
    String long_name "N_turtles_trans1";
    String units "unitless";
  }
  n_turtles_trans3 {
    Int32 actual_range 0, 8;
    String long_name "N_turtles_trans3";
    String units "unitless";
  }
  n {
    Int32 actual_range 0, 18;
    String long_name "N";
    String units "unitless";
  }
  n_SG {
    Float32 actual_range 0.0, 88.0;
    String long_name "N_sg";
    String units "unitless";
  }
  n_SG_AB {
    Float32 actual_range 0.0, 488.8889;
    String long_name "N_sg_ab";
    String units "unitless";
  }
  km_trans1 {
    Float32 actual_range 0.73, 1.31;
    String long_name "Km_trans1";
    String units "kilometers";
  }
  km_trans3 {
    Float32 actual_range 0.3, 0.95;
    String long_name "Km_trans3";
    String units "kilometers";
  }
  total_km {
    Float32 actual_range 1.21, 2.08;
    String long_name "Total_km";
    String units "kilometers";
  }
  km2_flight {
    Float32 actual_range 0.02547168, 0.04356768;
    String long_name "Km2_flight";
    String units "square kilometers";
  }
  Area_covered {
    Float32 actual_range 2.547168, 4.356768;
    String long_name "Area_covered";
    String units "hectares";
  }
  density {
    Float32 actual_range 0.0, 5.42697;
    String long_name "Density";
    String units "number per hectare";
  }
  density_SG {
    Float32 actual_range 0.0, 27.93324;
    String long_name "Density_sg";
    String units "number per hectare";
  }
  density_SG_AB {
    Float32 actual_range 0.0, 155.1847;
    String long_name "Density_sg_ab";
    String units "number per hectare";
  }
  abundance {
    Float32 actual_range 0.0, 10853.94;
    String long_name "Abundance";
    String units "number per hectare";
  }
  abundance_SG {
    Float32 actual_range 0.0, 55866.49;
    String long_name "Abundance_sg";
    String units "number per hectare";
  }
  abundance_SG_AB {
    Float32 actual_range 0.0, 310369.4;
    String long_name "Abundance_sg_ab";
    String units "number per hectare";
  }
 }
  NC_GLOBAL {
    String cdm_data_type "Other";
    String Conventions "COARDS, CF-1.6, ACDD-1.3";
    String creator_email "info@bco-dmo.org";
    String creator_name "BCO-DMO";
    String creator_url "https://www.bco-dmo.org/";
    String doi "10.26008/1912/bco-dmo.986917.1";
    String history 
"2026-01-09T09:08:02Z (local files)
2026-01-09T09:08:02Z https://erddap.bco-dmo.org/tabledap/bcodmo_dataset_986917_v1.das";
    String infoUrl "https://osprey.bco-dmo.org/dataset/986917";
    String institution "BCO-DMO";
    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.";
    String sourceUrl "(local files)";
    String summary "Green turtle (Chelonia mydas) density was estimated by performing aerial surveys with a DJI Phantom 3 Professional unmanned aerial vehicle (UAV). UAV systems have been found to provide an effective method for monitoring abundance when conducting daytime surveys of large marine organisms in coastal waters. Aerial surveys are an effective survey method for estimating sea turtle abundance because the method allows coverage of their extensive range. Because primary C. mydas foraging times are during the early morning and late afternoon throughout most of its range, transects were flown in the morning to enhance the reliability of estimates. Efforts were focused on the dense turtlegrass beds in the southern portion of the bay, as acoustic telemetry in St. Joseph Bay suggests that green turtles spend most of their time in this area. Aerial surveys were conducted over two surveys in 2019 during August and September and compared to surveys conducted previously in 2016 and 2017.";
    String title "[St. Joseph Bay UAV Urchin survey] - Green turtle density in St. Joseph Bay, Florida, USA estimated by performing aerial surveys in 2016, 2017, and 2019 (RAPID: Species on the Move: Tropicalization of Western Atlantic Seagrass Beds)";
  }
}

 

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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