Hydrographic survey data extracted from the NOAA-NOS CD do not have formal metadata; however, information on individual surveys can be obtained by the using GEOphysical DAta System (GEODAS) application provided on the NOAA-NOS CD to retrieve the survey headers. Among other things, the headers provide information such as survey date, source institution, original datum, depth distance units, sounding methods, and data processing methods.
The .XYZ files extracted from the NOAA-NOS Hydrographic Survey Data CD provided the longitude, latitude, and depth of individual bathymetric soundings. See Appendix C for the complete list of National Geophysical Data Center (NGDC) survey numbers and data files used to create the final data set. For additional information regarding the original data source refer to the documentation on the CD and the NOAA/NGDC website (<http://www.ngdc.noaa.gov/mgg/gdas/gd_sys.html>).
The original data was created as follows:
The 152 individual .XYZ files were extracted from the NOAA-NOS Hydrographic Survey Data CD using the GEODAS application, imported into Excel, given field headings, and then exported as .txt files. The .txt files were brought into ArcView and converted to shapefiles using the Add Event Theme and Convert to Shapefile commands. The 152 individual files were merged into a single shapefile and its data table exported as a .txt file. The .txt file was imported into Access in order to remove duplicate points (points with identical longitude, latitude and depth). The file was then brought back into ArcView, converted to a shapefile, and reprojected from decimal degrees to NAD83 UTM Zone 4.
Note that only points with identical coordinates and depths were deleted from the data set. A total of 301 duplicate points were deleted from the data set. Refer to Appendix D for a list of deleted records. Points that share identical coordinates, but have different depth measurements were left in the data set. Appendix E lists those records. Some of these data points are problematic because of either the large differences in depth, or because of the multitude of depths associated with a single data point.