Slide Menu
Search Help Show/Hide Menu
Short Citation:
National Centers for Coastal Ocean Science, 2022: NOAA ESRI Grid - seafloor hardbottom occurrence predictions model in New York offshore planning area from Biogeography Branch, https://www.fisheries.noaa.gov/inport/item/38952.

Item Identification

Title: NOAA ESRI Grid - seafloor hardbottom occurrence predictions model in New York offshore planning area from Biogeography Branch
Short Name: New_York_Hardbottom_Predictions
Status: Completed
Publication Date: 2012-05
Abstract:

This dataset represents hard bottom occurrence predictions from a spatial model developed for the New York offshore spatial planning area. This model builds upon the data compilation and analytical framework laid out by Greene et al. (2010). The model also provides a continuous gridded prediction surface representing the likelihood of hard bottom occurrence.

Purpose:

These hard bottom occurrence predictions were developed to identify critical habitat areas for benthic organisms (e.g., clams, corals, demersal fish), and plan of human activities such as selecting appropriate offshore construction sites, and planning sand/gravel mining operations.

Notes:

568

Keywords

Theme Keywords

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

Temporal Keywords

Thesaurus Keyword
UNCONTROLLED
None Long-term average determined by input data

Spatial Keywords

Thesaurus Keyword
UNCONTROLLED
None Long Island
None Mid-Atlantic
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:

The final map of the "hard bottom occurrence likelihood index" consisted of a logistic transformation of MaxEnt's raw output to produce a smooth index between 0 and 1 (this is the default output of the MaxEnt program). It is related to the probability of occurrence, but is not strictly a probability (Elith et al., 2011). It should be considered an index of the relative likelihood of hard bottom occurrence, rather than a strict measure of the probability of encountering hard bottom.

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 and B.P. Kinlan

Support Roles

Data Steward

CC ID: 452477
Date Effective From: 2012-05
Date Effective To:
Contact (Position): NCCOS Scientific Data Coordinator
Email Address: NCCOS.data@noaa.gov

Distributor

CC ID: 452479
Date Effective From: 2012-05
Date Effective To:
Contact (Position): NCCOS Scientific Data Coordinator
Email Address: NCCOS.data@noaa.gov

Metadata Contact

CC ID: 452480
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: 452478
Date Effective From: 2012-05
Date Effective To:
Contact (Position): NCCOS Scientific Data Coordinator
Email Address: NCCOS.data@noaa.gov

Principal Investigator

CC ID: 452481
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: 452484
W° Bound: -75
E° Bound: -69
N° Bound: 42
S° Bound: 37

Extent Group 1 / Time Frame 1

CC ID: 452483
Time Frame Type: Discrete
Start: 2012-05

Spatial Information

Spatial Representation

Representations Used

Grid: Yes

Grid Representation 1

CC ID: 585243
Dimension Count: 3
Cell Geometry: Area
Transformation Parameters Available?: No

Axis Dimension 1

Dimension Type: Row
Size: 443

Axis Dimension 2

Dimension Type: Column
Size: 496

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: 452485
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: 452476
URL: http://coastalscience.noaa.gov/projects/detail?key=80
URL Type:
Online Resource

Activity Log

Activity Log 1

CC ID: 452507
Activity Date/Time: 2015-05-27
Description:

Date that the source FGDC record was last modified.

Activity Log 2

CC ID: 452506
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: 585241
Activity Date/Time: 2017-09-13
Description:

Partial upload of Spatial Info section only.

Activity Log 4

CC ID: 600510
Activity Date/Time: 2017-11-01
Description:

Replaced entire Lineage section to populate new Source Contribution field.

Activity Log 5

CC ID: 716585
Activity Date/Time: 2018-02-08
Description:

Partial upload of Positional Accuracy fields only.

Data Quality

Horizontal Positional Accuracy:

The horizontal positional accuracy of this raster 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

Bottom Type Descriptions from Hydrographic Surveys database

CC ID: 600512
Contact Name: National Oceanic and Atmospheric Administration (NOAA)/National OceanService (NOS)U.S. Coast and Geodetic Survey
Publish Date: 2011-04-21
Extent Type: Discrete
Extent Start Date/Time: 2011-04-21
Source Contribution:

Surficial sediment survey data was used as input to a spatial model. | Source Geospatial Form: vector digital data | Type of Source Media: online

usSEABED Atlantic Coast Offshore Surficial Sediment Data Release

CC ID: 600513
Contact Name: Nature Conservancy (TNC)
Publish Date: 2011-04-21
Extent Type: Discrete
Extent Start Date/Time: 2011-04-21
Source Contribution:

Surficial sediment survey data was used as input to a spatial model. | Source Geospatial Form: vector digital data | Type of Source Media: online

usSEABED Atlantic Coast Offshore Surficial Sediment Data Release

CC ID: 600511
Contact Name: USGS
Publish Date: 2011-04-21
Extent Type: Discrete
Extent Start Date/Time: 2011-04-21
Source Contribution:

Surficial sediment survey data was used as input to a spatial model. | Source Geospatial Form: vector digital data | Type of Source Media: online

Process Steps

Process Step 1

CC ID: 600514
Description:

A maximum entropy (MaxEnt) model was used to predict the likelihood of hard bottom occurrence by combining the presence-only hard bottom point dataset with potential predictor variables (Phillips et al., 2006; Phillips and Dudik, 2008). This approach can be thought of as creating a "suitability map" for the presence of hard bottom patches, analogous to habitat suitability maps developed for organisms (Elith et al., 2011). A full description of the MaxEnt algorithm is beyond the scope of this document (see Elith et al., 2011). Briefly, MaxEnt produces an estimate of the relative likelihood of a feature's occurrence at each location in a specified grid, assuming that presences take on the most spatially random (uniform) distribution possible under the constraint that for each environmental predictor variable the expected value from the estimated distribution matches its observed mean (Elith et al., 2006; Phillips et al., 2006; Peterson et al., 2007). MaxEnt models are trained on a subset of the data and validated by testing predictions on remaining data. MaxEnt has been shown to perform well compared to other presence-only approaches (Elith et al., 2006; Phillips and Dudik, 2008), and is readily implemented using free, open-source software (Phillips et al., 2006, downloadable at http://www.cs.princeton.edu/~schapire/maxent/). 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: usSEABED Atlantic Coast Offshore Surficial Sediment Data Release

Child Items

Rubric scores updated every 15m

Rubric Score Type Title
Entity Hard Bottom Occurrence

Catalog Details

Catalog Item ID: 38952
GUID: gov.noaa.nmfs.inport:38952
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: 2022-08-09 17:11+0000
Metadata Record Published: 2018-02-08
Owner Org: NCCOS
Metadata Publication Status: Published Externally
Do Not Publish?: N
Metadata Last Review Date: 2018-02-08
Metadata Review Frequency: 1 Year
Metadata Next Review Date: 2019-02-08