Commercial Vessel Density October 2009-2010 AIS UTM17

Marine Cadastre Data Registry

Date that the source FGDC record was last modified.

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.

Partial upload of Positional Accuracy fields only.

2010 Automatic Identification System (AIS) vessel count data for UTM Zone17N which provided information regarding vessel counts derived from AIS data at 1 kilometer square grids. | Type of Source Media: electronic mail system

NATIONWIDE AUTOMATIC IDENTIFICATION SYSTEM | Type of Source Media: online

Source data derived from the raw AIS data processing is as follows:

The USCG maintains a network of AIS receivers that collects AIS messages from passing ships. These data are transmitted to USCG data center that compiles the data and provides data feeds to other government agencies. In accordance with the USCG COMDTINST 5230.80, the USCG provided OCS with a "Level A" data feed. Level A is unfiltered real-time data that is less than 96 hours from initial time of transmission. OCS has subscribed to this data since 2008. To limit data storage requirements the data feed was filtered by the USCG to only send one position message per ship per minute and all duplicate messages (i.e. ship broadcasts received by more than one NAIS station) were removed. This real time feed was archived at OCS. A specialized software NOAADATA.py (K. Schwehr. The noaadata-py Software Tool-set, v0.42, 2009. http://vislab-ccom.-unh.edu/schwehr/software/noaadata) is used to create daily files and and load the data into an Oracle Spatial database.

Despite receiving this filtered feed, a great deal of conditioning needs to take place to prepare this data to be analyzed. The AIS system was not intended or designed for subsequent analysis; however Calder and Schwehr ably proved, given the proper conditioning, AIS data can be used for traffic analysis. ( B. R. Calder., K. Schwehr. Traffic Analysis for the Calibration of Risk Assessment Methods. Proceedings: US Hydrographic Conference 2009, Norfolk, VA, 11-14 May 2009, http://www.thsoa.org/us09papers.htm) Based on their research, we filtered out AIS messages with non-unique user IDs and vessels with erroneous dimensions. We also separated messages by speed, separating those reporting a speed of less than 0.4 knots into a separate anchored table.

The accuracy and abundance of the AIS data support high resolution analysis specifically within port areas. This study however was interested in traffic patterns on a macro scale so patterns could be analyzed across the coastal waters of the Continental United States. To limit the processing time and the overall file size for each region a grid cell size of 1 kilometer was chosen.

For this dataset a transits is counted for every unique vessel intersecting a grid cell each day. Multiple trips into a grid cell on a given day by the same vessel are only counted as one transit. Instead of calculating transits based on the coordinates within the AIS message transit lines were created by connecting all the vessels reports each day. Traffic counts were then calculated by summing the number of lines within each cell. Although this dataset only contains the total traffic count "TRNSTS_TTL" the original dataset has transits by AIS vessel type and many other attributes as well. Processed from May - July 2012.

Further data development processing followed to obtain this feature class:

Acquire original source data and maintain a copy on the development tier, create geodatabase import the original shapefiles. Delete all feature will zero values and validate the feature classes' geometry (Data Management > Features > Repair Geometry). Acquire, create and update metadata from providers (as needed). Compressed data set into a zip file for ease of download.