gov.noaa.nmfs.inport:38954 eng UTF8 dataset National Centers for Coastal Ocean Science resourceProvider NCCOS Scientific Data Coordinator NCCOS.data@noaa.gov pointOfContact 2025-05-15T19:16:08 ISO 19115-2 Geographic Information - Metadata Part 2 Extensions for imagery and gridded data ISO 19115-2:2009(E) 3 row 943 column 843 vertical 1 area 0 NOAA ESRI Grid - predictions of relative uncertainty for sediment size in the New York offshore planning area by NOAA Biogeography Branch New_York_Mean_Grain_Size_Error 2012-05 publication NOAA/NMFS/EDM 38954 https://www.fisheries.noaa.gov/inport/item/38954 WWW:LINK-1.0-http--link Full Metadata Record View the complete metadata record on InPort for more information about this dataset. information Menza, Charles 240-533-0372 301-713-4388 1305 East-West Hwy Silver Spring MD 20910 Charles.menza@noaa.gov principalInvestigator https://coastalscience.noaa.gov/projects/detail?key=80 WWW:LINK-1.0-http--link Citation URL Online Resource download This dataset represents sediment size prediction uncertainty from a sediment spatial model developed for the New York offshore spatial planning area. The model also includes spatially-explicit mean grain size estimates represented in another raster dataset. The predictive model of mean grain size was developed building upon the data compilation and analytical framework laid out by Goff et al. (2008). Mapping seafloor features, including sediment characteristics and distribution, provides crucial information for a number of coastal and marine spatial planning applications. Seafloor maps can be used to help identify critical habitat areas for benthic organisms (e.g., clams, corals, demersal fish), select appropriate offshore construction sites, and plan sand/gravel mining operations. CCMA credits these people for deriving this dataset: M. Poti, B.P. Kinlan and C. Menza completed NCCOS Scientific Data Coordinator NCCOS.data@noaa.gov pointOfContact NCCOS Scientific Data Coordinator NCCOS.data@noaa.gov custodian notPlanned OceanCommunity theme Geospatial Platform Bathymetry/Topography theme NOS Data Explorer Topic Category New York Seafloor bathymetry/topography environment grain size prediction sediment spatial planning uncertainty theme Long-term average determined by input data temporal Long Island Mid-Atlantic New York Bight New York Offshore Planing Area Northwest Atlantic Ocean place DOC/NOAA/NOS/NCCOS > National Centers for Coastal Ocean Science, National Ocean Service, NOAA, U.S. Department of Commerce dataCentre Global Change Master Directory (GCMD) Data Center Keywords 2017-04-24 publication 8.5 Earth Science Data and Information System, Earth Science Projects Division, Goddard Space Flight Center (GSFC), National Aeronautics and Space Administration (NASA) https://forum.earthdata.nasa.gov/app.php/tag/GCMD%2BKeywords GCMD Keyword Forum Page Global Change Master Directory (GCMD). 2025. GCMD Keywords, Version 22. Greenbelt, MD: Earth Science Data and Information System, Earth Science Projects Division, Goddard Space Flight Center (GSFC), National Aeronautics and Space Administration (NASA). URL (GCMD Keyword Forum Page): https://forum.earthdata.nasa.gov/app.php/tag/GCMD+Keywords information custodian ny_spatialplan project InPort otherRestrictions Cite As: National Centers for Coastal Ocean Science, [Date of Access]: NOAA ESRI Grid - predictions of relative uncertainty for sediment size in the New York offshore planning area by NOAA Biogeography Branch [Data Date Range], https://www.fisheries.noaa.gov/inport/item/38954. NOAA provides no warranty, nor accepts any liability occurring from any incomplete, incorrect, or misleading data, or from any incorrect, incomplete, or misleading use of the data. It is the responsibility of the user to determine whether or not the data is suitable for the intended purpose. otherRestrictions Access Constraints: Data not yet available online. otherRestrictions 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) otherRestrictions 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. unclassified NOAA Data Management Plan (DMP) NOAA/NMFS/EDM 38954 https://www.fisheries.noaa.gov/inportserve/waf/noaa/nos/nccos/dmp/pdf/38954.pdf WWW:LINK-1.0-http--link NOAA Data Management Plan (DMP) NOAA Data Management Plan for this record on InPort. information crossReference grid eng; US environment oceans -75 -69 37 42 | Currentness: 201205 2012-05-01 false eng false Estimated mean grain size uncertainty 2017-04-17 publication zip file Zip NCCOS Scientific Data Coordinator NCCOS.data@noaa.gov distributor https://coastalscience.noaa.gov/projects/download.aspx?fpath=D%3a%5cWebsites%5cNCCOS%5cprojects-attachments%5c80%5cNY_assessment_data_package.zip WWW:LINK-1.0-http--link https://coastalscience.noaa.gov/projects/download.aspx?fpath=D%3a%5cWebsites%5cNCCOS%5cprojects-attachments%5c80%5cNY_assessment_data_package.zip Offline Data download dataset 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 on the horizontal 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. 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. A geostatistical modeling approach was used to predict a continuous, gridded sediment size prediction surface from scattered sediment smaple 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. 2012-05-01T00:00:00 Source Contribution: Sediment size data was used as input to a geostatistical model. | Source Geospatial Form: vector digital data | Type of Source Media: online Parsed and extracted database of mean sediment grain size 2011-04-21 publication Dr. John Goff, University of Texas at Austin 2011-04-21