Short Citation:
National Centers for Coastal Ocean Science, 2021: NOAA ESRI Grid - depth predictions bathymetry model in New York offshore planning area from Biogeography Branch, https://www.fisheries.noaa.gov/inport/item/38949.

Item Identification

Title: NOAA ESRI Grid - depth predictions bathymetry model in New York offshore planning area from Biogeography Branch
Short Name: New_York_Bathymetry_Model_Depth
Status: Completed
Publication Date: 2012-05
Abstract:

This dataset represents depth predictions from a bathymetric model developed for the New York offshore spatial planning area. The model also includes spatially-explicit uncertainty estimates represented in another raster dataset. The model used to derive depth estimates builds on previous predictive bathymetric modeling approaches in the region (e.g. Calder, 2006), provides a continuous gridded bathymetric surface, and allows users to view and explore spatial variation in the vertical accuracy of depth predictions. The spatial resolution of the model is identical to the National Oceanic and Atmospheric Administration's (NOAA) Coastal Relief Model (CRM; horizontal resolution approximately 83.8 m) in the study area and was built from the same database of hydrographic survey points.

Purpose:

These depth predictions were developed to be viewed along with model uncertainty estimates. Together depth predictions and uncertainty estimates were made to prioritize locations for new bathymetric surveys with high uncertainty and better understand the reliability of depth predictions and derived spatial layers (e.g., benthic habitats, positions of depth contours).

Notes:

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Keywords

Theme Keywords

Thesaurus Keyword
Geospatial Platform OceanCommunity
ISO 19115 Topic Category environment
ISO 19115 Topic Category oceans
NOS Data Explorer Topic Category Bathymetry/Topography
None bathymetry/topography
None depth
None environment
None New York
None prediction
None Seafloor
None spatial planning
None uncertainty

Temporal Keywords

Thesaurus Keyword
None Long-term average determined by input data

Spatial Keywords

Thesaurus Keyword
None Long Island
None Mid-Atlantic
None New York
None New York Bight
None New York Offshore Planing Area
None Northwest Atlantic Ocean

Physical Location

Organization: National Centers for Coastal Ocean Science
City: Silver Spring
State/Province: MD

Data Set Information

Data Set Scope Code: Data Set
Maintenance Frequency: None Planned
Data Presentation Form: raster digital data
Entity Attribute Overview:

Raster values correspond to estimates of depth below MLLW. Estimates are based on a bathymetric geostatistical model developed using NOS hydrographic surveys.

Entity Attribute Detail Citation:

For more information see Menza, C., B.P. Kinlan, D.S. Dorfman, M. Poti and C. Caldow (eds.). 2012. A Biogeographic Assessment of Seabirds, Deep Sea Corals and Ocean Habitats of the New York Bight: Science to Support Offshore Spatial Planning. NOAA Technical Memorandum NOS NCCOS 141. Silver Spring, MD. 224 pp.

Distribution Liability:

These data were prepared by an agency of the United States Government. Neither the United States Government nor any agency thereof, nor any of their employees, make any warranty, expressed or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed in this report, or represents that its use would not infringe privately owned rights. Reference therein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof. Any views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof. Although all data have been used by NOAA, no warranty, expressed or implied, is made by NOAA as to the accuracy of the data and/or related materials. The act of distribution shall not constitute any such warranty, and no responsibility is assumed by NOAA in the use of these data or related materials.

Data Set Credit: CCMA credits these people for deriving this dataset: M. Poti, B.P. Kinlan, and Menza, C.

Support Roles

Data Steward

CC ID: 452355
Date Effective From: 2012-05
Date Effective To:
Contact (Position): NCCOS Scientific Data Coordinator
Email Address: NCCOS.data@noaa.gov

Distributor

CC ID: 452357
Date Effective From: 2012-05
Date Effective To:
Contact (Position): NCCOS Scientific Data Coordinator
Email Address: NCCOS.data@noaa.gov

Metadata Contact

CC ID: 452358
Date Effective From: 2012-05
Date Effective To:
Contact (Position): NCCOS Scientific Data Coordinator
Email Address: NCCOS.data@noaa.gov

Point of Contact

CC ID: 452356
Date Effective From: 2012-05
Date Effective To:
Contact (Position): NCCOS Scientific Data Coordinator
Email Address: NCCOS.data@noaa.gov

Principal Investigator

CC ID: 452359
Date Effective From: 2012-05
Date Effective To:
Contact (Person): Menza, Charles
Address: 1305 East-West Hwy
Silver Spring, MD 20910
Email Address: Charles.menza@noaa.gov
Phone: 240-533-0372
Fax: 301-713-4388

Extents

Currentness Reference: 201205

Extent Group 1

Extent Group 1 / Geographic Area 1

CC ID: 452362
W° Bound: -75
E° Bound: -69
N° Bound: 42
S° Bound: 37

Extent Group 1 / Time Frame 1

CC ID: 452361
Time Frame Type: Discrete
Start: 2012-05

Spatial Information

Spatial Representation

Representations Used

Grid: Yes

Grid Representation 1

CC ID: 585230
Dimension Count: 3
Cell Geometry: Area
Transformation Parameters Available?: No

Axis Dimension 1

Dimension Type: Row
Size: 5975

Axis Dimension 2

Dimension Type: Column
Size: 5335

Axis Dimension 3

Dimension Type: Vertical
Size: 1

Access Information

Security Class: Unclassified
Data Access Procedure:

Contact Distributor for instructions on how to acquire dataset.;

Data Access Constraints:

Data not yet available online.

Data Use Constraints:

Please reference NOAA/NOS/NCCOS/CCMA/Biogeography Branch when utilizing these data in a report or peer reviewed publication. Additionally, knowledge of how this dataset has been of use and which organizations are utilizing it is of great benefit for ensuring this information continues to meet the needs of the management and research communities. Therefore, it is requested but not mandatory, that any user of this data supply this information to the Project Manager: Charles Menza (charles.menza@noaa.gov)

Distribution Information

Distribution 1

CC ID: 452363
Download URL: http://coastalscience.noaa.gov/projects/download.aspx?fpath=D%3a%5cWebsites%5cNCCOS%5cprojects-attachments%5c80%5cNY_assessment_data_package.zip
Distributor:
Description:

Offline Data

File Type: zip file

URLs

URL 1

CC ID: 452354
URL: http://coastalscience.noaa.gov/projects/detail?key=80
URL Type:
Online Resource

Activity Log

Activity Log 1

CC ID: 452384
Activity Date/Time: 2015-05-27
Description:

Date that the source FGDC record was last modified.

Activity Log 2

CC ID: 452383
Activity Date/Time: 2017-04-05
Description:

Converted from FGDC Content Standard for Digital Geospatial Metadata (version FGDC-STD-001-1998) using 'fgdc_to_inport_xml.pl' script. Contact Tyler Christensen (NOS) for details.

Activity Log 3

CC ID: 585228
Activity Date/Time: 2017-09-13
Description:

Partial upload of Spatial Info section only.

Activity Log 4

CC ID: 600501
Activity Date/Time: 2017-11-01
Description:

Replaced entire Lineage section to populate new Source Contribution field.

Activity Log 5

CC ID: 716582
Activity Date/Time: 2018-02-08
Description:

Partial upload of Positional Accuracy fields only.

Data Quality

Horizontal Positional Accuracy:

The accuracy of this raster depends on the source and resolution of the data samples. See the following report for more information horizontal positional accuracy: Menza, C., B.P. Kinlan, D.S. Dorfman, M. Poti and C. Caldow (eds.). 2012. A Biogeographic Assessment of Seabirds, Deep Sea Corals and Ocean Habitats of the New York Bight: Science to Support Offshore Spatial Planning. NOAA Technical Memorandum NOS NCCOS 141. Silver Spring, MD. 224 pp.

Vertical Positional Accuracy:

The accuracy of this surface depends on the source and resolution of the data samples. See the following report for more information: Menza, C., B.P. Kinlan, D.S. Dorfman, M. Poti and C. Caldow (eds.). 2012. A Biogeographic Assessment of Seabirds, Deep Sea Corals and Ocean Habitats of the New York Bight: Science to Support Offshore Spatial Planning. NOAA Technical Memorandum NOS NCCOS 141. Silver Spring, MD. 224 pp.

Completeness Report:

The following reference provides information on omissions, selection criteria, generalization, definitions used, and other rules used to derive the data set: Menza, C., B.P. Kinlan, D.S. Dorfman, M. Poti and C. Caldow (eds.). 2012. A Biogeographic Assessment of Seabirds, Deep Sea Corals and Ocean Habitats of the New York Bight: Science to Support Offshore Spatial Planning. NOAA Technical Memorandum NOS NCCOS 141. Silver Spring, MD. 224 pp.

Conceptual Consistency:

All users should independently analyze the dataset according to their own needs and standards to determine data usability.

Lineage

Sources

National Ocean Service (NOS) Hydrographic Survey Data

CC ID: 600502
Contact Name: Department of Commerce (DOC), National Oceanic and Atmospheric Administration (NOAA), National Ocean Service (NOS), National Centers for Coastal Ocean Science (NCCOS), Center for Coastal Monitoring and Assessment (CCMA), Biogeography Branch
Publish Date: 2011-04-21
Extent Type: Discrete
Extent Start Date/Time: 2011-04-21
Citation URL: http://www.ngdc.noaa.gov/mgg/bathymetry/hydro.html
Source Contribution:

Hydrographic survey data was used as input to a geostatistical model. This raster dataset is output from the geostatistical model. | Source Geospatial Form: vector digital data | Type of Source Media: online

Process Steps

Process Step 1

CC ID: 600503
Description:

A geostatistical modeling approach was used to predict a continuous, gridded bathymetric surface from scattered sounding points and to generate corresponding spatially-explicit uncertainty estimates. Geostatistical methods are based on the premise that neighboring samples are more similar than samples farther away (Tobler, 1970), a phenomenon known as spatial autocorrelation. Spatial autocorrelation was detected, quantified and modeled by semivariogram analysis, and used to make predictions at locations that have not been measured. See the following report for more information on this layer's lineage. Menza, C., B.P. Kinlan, D.S. Dorfman, M. Poti and C. Caldow (eds.). 2012. A Biogeographic Assessment of Seabirds, Deep Sea Corals and Ocean Habitats of the New York Bight: Science to Support Offshore Spatial Planning. NOAA Technical Memorandum NOS NCCOS 141. Silver Spring, MD. 224 pp.

Process Date/Time: 2012-05-01 00:00:00
Source: National Ocean Service (NOS) Hydrographic Survey Data

Child Items

Rubric scores updated every 15m

Rubric Score Type Title
Entity (ENT) Estimated Depth

Catalog Details

Catalog Item ID: 38949
Metadata Record Created By: Tyler Christensen
Metadata Record Created: 2017-04-05 12:50+0000
Metadata Record Last Modified By: SysAdmin InPortAdmin
Metadata Record Last Modified: 2019-06-04 13:14+0000
Metadata Record Published: 2018-02-08
Owner Org: NCCOS
Metadata Publication Status: Published Externally
Do Not Publish?: N
Metadata Next Review Date: 2019-02-09