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Hosted/us_canyon (FeatureServer)

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Service Description:

All Layers and Tables

Has Versioned Data: false

MaxRecordCount: 2000

Supported Query Formats: JSON

Supports Query Data Elements:

Layers: Description: This dataset was created utilizing an objective system to inventory locations and names of large submarine canyons on the United States OCS in the Atlantic, Pacific, and Arctic Oceans and the Gulf of Mexico. The objective system utilized bathymetric data for average and maximum width, length and average and maximum depth of canyons to select ‘large’ submarine canyons for inclusion in this study. For the purposes of this study, submarine canyons were defined as “steep-walled, sinuous valleys with V-shaped cross sections, axes sloping outwards as continuously as river-cut land canyons and relief comparable to even the largest of land canyons”. One of the challenging portions of the selection process was the identification of individual canyons. While some canyons are spatially isolated from others and visually distinctive using various bathymetric data sources, others are more difficult to distinguish individually because of their proximity and overlapping or nearly overlapping dendritic patterning, especially in their shallower extents. Fortunately, a recent paper (Harris et al. 2014[1]) provided an authoritative description of many of these major canyons and was the starting point for development of the methods used in this study to determine the canyon boundaries. However, to develop a more objective methodology for this study, the basis for choosing the boundaries was based on defensible, accepted methods. In summary, the methods included: 1) examination of bathymetric datasets across all regions; 2) utilization of a series of tools within the Esri hydrology analysis Basin toolkit to extract the approximate Harris thalweg to define stream orders from the resulting flow accumulation output; 3) association of seafloor slope with canyons by examining the bathymetric raster for its cumulative frequency distribution of the slope values in SAS (2016) using PROC UNIVARIATE to sequentially eliminate the flatter slopes; 4) establishment of buffer spatial extents utilizing the 4.6th(2 Standard Deviations [SD]) percentile to determine the steepest slopes.

Service Item Id: 7b85b0aecbb849d6a3c2a2bce35659df

Copyright Text: CSA Ocean Sciences Inc. (CSA), De Leo, F.C., and Ross, S.W. 2019. Large Submarine Canyons of the United States Outer Continental Shelf Atlas dataset. U.S. Dept. of the Interior, Bureau of Ocean Energy Management, Environmental Studies Program, Washington, DC, under Contract Number 140M0119F0009.

Spatial Reference: 102100  (3857)  LatestVCSWkid(0)


Initial Extent: Full Extent: Units: esriMeters

Document Info: Enable Z Defaults: true

Supports ApplyEdits With Global Ids: false

Supports Dynamic Layers: false

Child Resources:   Info   Relationships

Supported Operations:   Query   Query Contingent Values   Append   Get Estimates