The New York State Office of Parks, Recreation and Historic Preservation (OPRHP) oversees more than 250 state parks, historic sites, recreational trails, golf courses, boat launches and more, encompassing nearly 350,000 acres, that are visited by 74 million people annually. These facilities contribute to the economic vitality and quality of life of local communities and directly support New York’s tourism industry. Parks also provide a place for families and children to be active and exercise, promoting healthy lifestyles. The agency is responsible for the operation and stewardship of the state park system as well as advancing a statewide parks, historic preservation, and open space mission. The New York State Office of Parks, Recreation, and Historic Preservation operates marinas and boat launching sites across the state. For more information about boating in New York State parks, visit http://nysparks.com/recreation/boating/

This dataset contains the file of vehicle, snowmobile and boat registrations in NYS. Expired registrations are excluded. Records that have a scofflaw, revocation and/or suspension are included with indicators specifying this.

Overview

This dataset contains 74 images of aerial maritime photographs taken with via a Mavic Air 2 drone and 1,151 bounding boxes, consisting of docks, boats, lifts, jetskis, and cars. This is a multi class problem. This is an aerial object detection dataset. This is a maritime object detection dataset.

The drone was flown at 400 ft. No drones were harmed in the making of this dataset.

This dataset was collected and annotated by the Roboflow team, released with MIT license.

https://i.imgur.com/9ZYLQSO.jpg" alt="Image example">

Use Cases

• Identify number of boats on the water over a lake via quadcopter.
• Boat object detection dataset
• Aerial Object Detection proof of concept
• Identify if boat lifts have been taken out via a drone
• Identify cars with a UAV drone
• Find which lakes are inhabited and to which degree.
• Identify if visitors are visiting the lake house via quad copter.
• Proof of concept for UAV imagery project
• Proof of concept for maritime project
• Etc.

This dataset is a great starter dataset for building an aerial object detection model with your drone.

Getting Started

Fork or download this dataset and follow our How to train state of the art object detector YOLOv4 for more. Stay tuned for particular tutorials on how to teach your UAV drone how to see and comprable airplane imagery and airplane footage.

Annotation Guide

See here for how to use the CVAT annotation tool that was used to create this dataset.

About Roboflow

Roboflow makes managing, preprocessing, augmenting, and versioning datasets for computer vision seamless. :fa-spacer: Developers reduce 50% of their boilerplate code when using Roboflow's workflow, save training time, and increase model reproducibility. :fa-spacer:

Analysis of ‘Boat Launch Sites by State Parks or Marine Facility’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/ab17cc49-40ac-442e-95c2-522c8d793008 on 27 January 2022.

--- Dataset description provided by original source is as follows ---

The New York State Office of Parks, Recreation and Historic Preservation (OPRHP) oversees more than 250 state parks, historic sites, recreational trails, golf courses, boat launches and more, encompassing nearly 350,000 acres, that are visited by 74 million people annually. These facilities contribute to the economic vitality and quality of life of local communities and directly support New York’s tourism industry. Parks also provide a place for families and children to be active and exercise, promoting healthy lifestyles. The agency is responsible for the operation and stewardship of the state park system as well as advancing a statewide parks, historic preservation, and open space mission. The New York State Office of Parks, Recreation, and Historic Preservation operates marinas and boat launching sites across the state. For more information about boating in New York State parks, visit http://nysparks.com/recreation/boating/

--- Original source retains full ownership of the source dataset ---

This dataset is maintained by Wisconsin Department of Natural Resources. It is a compilation of public sites where boats can be legally launched into public waters in Wisconsin. It includes locations and data for both ramp and carry-in (canoe/kayak) launch sites throughout the state. These public launch sites are owned and maintained by State government (i.e. DNR, DOT, etc.) and local municipalities. All information for non-DNR boat access sites presented herein is not maintained by the DNR. No privately-owned sites are included in this database.This dataset is continually being updated and added to; this item displays the most current edits, however it may contain errors or omissions.

This dataset contains the file of vehicle, snowmobile and boat registrations in NYS. Registrations expired more than 2 years are excluded. Records that have a scofflaw, revocation and/or suspension are included with indicators specifying those kinds of records.

Boat Registrations by County/City at End of Calendar Year (1998–2023). Boat owners in Virginia must apply for a certificate of title at the same time an application is made for registration. You can begin the title and registration process online at GoOutdoorsVirginia.com or complete an application form available from most watercraft dealers or this website. Some online transactions may require physical proof of purchase to be mailed to the agency. The online process will indicate what and where documentation should be mailed.

An application for title and registration requires a detailed description of the watercraft that includes the make, length, model year, type of vessel, hull material, type of propulsion, and the twelve-character hull identification number; the make, horsepower and serial number of the motor if in excess of 25 horsepower; and the name and address of the lienholder, if any.

DMV now accepts the application for Boat Registration and Title with the previous title and appropriate fee. DMV will issue a 60-Day Temporary and forward the Boat Registration/Title documentation to DWR for processing. (DMV does not accept mail-in applications for Boat Registration and Titles).

The California Department of Boating and Waterways provided the California Department of Fish and Game Marine Region GIS Lab with a boating facilities GIS dataset. The GIS Lab manually selected coastal and marine related boat launch sites from the boating facilities dataset to create this dataset. Only the name field was used from the boating facilities dataset and the GIS Lab added and attributed the rest of the fields in the dataset. Positions were more accurately located with the aid of aerial imagery.Please note that this dataset was clipped and reprojected as part of the San Diego Ocean Planning Partnership, a collaborative pilot project between the California State Lands Commission and the Port of San Diego. For this dataset, a three nautical mile buffer of the preliminary planning boundary was used in order to capture sites in San Diego and Mission Bay as well as Oceanside Harbor. As with other data, anything included outside of the preliminary planning boundary is for informational purposes only. For more information about the Partnership, please visit: https://www.sdoceanplanning.org/

Survey participants plotted activity points using an interactive mapping tool.The 2012 Northeast Recreational Boater Survey was conducted by SeaPlan, the Northeast Regional Ocean Council (NROC), states’ coastal agencies, marine trade associations composed of many private industry representatives, and the First Coast Guard District. The methodology for the 2012 Northeast Recreational Boater Survey follows a protocol similar to the 2010 Massachusetts Survey with modifications based on the lessons learned and recommendations suggested in the Massachusetts Survey Final Report.The methodology consists of surveying a random sample of selected boat owners throughout the Northeast through a series of monthly online surveys. The surveying period lasted throughout the 2012 boating season (May 1 through October 31, 2012), which was identified by the advisory committee (consisting of NROC and representatives from the recreational boating industry).The project team decided to use a random sample survey approach because it successfully gathered statistically robust economic and spatial data on recreational boating activity by Massachusetts registered boaters during the 2010 boating season. This was also the only approach that would allow for the calculation of statistically robust economic impact estimates for both the states and the region, which was identified as a priority (along withspatial data) by both NROC and the boating industry.

This dataset can be used by coastal planners in ocean planning activities to develop a better understanding of how and where humans use the ocean in the Northeast to inform regional ocean planning and minimize ocean use conflicts. This effort also fulfilled a recommendation from the 2010 Massachusetts Survey to expand the survey’s geographic range to the Northeast Region, allowing for the capture of interstate traffic between states in the Northeast. Furthermore, this dataset can also be used by the boating industry to show the importance of recreational boating to the region and to inform business planning.

Supplemental Information; SURVEY SAMPLING METHODOLOGY - The sample for this survey came from seven databases, including the U.S. Coast Guard Documented Vessel Database and databases of state registered boaters from New York, Connecticut, Rhode Island, Massachusetts, New Hampshire, and Maine. Recreational boaters who owned vessels that met the following criteria were eligible for the survey: * Registration: Currently registered with a state in the Northeast and/or registered as a documented vessel with the U.S. Coast Guard, with a hailing port in the Northeast * Primary Use: Recreational use designation * Length: At least 10 feet in length * Saltwater (if specified; only Maine and New Hampshire required this information) * Location: Located in a “coastal county”. The survey team defined “coastal counties” as those that border saltwater, or those that were highlighted by state coastal planners as likely containing large amount of saltwater boating activity. Based on the 2010 Massachusetts Survey and budgetary considerations, the project team determined an overall sample size that would provide sufficient spatial and economic data for both each state, as well as the whole Northeast. Because of the, at times, large discrepancies between the number of eligible boats in some states, the team decided that certain states with fewer eligible boats should also have a supplemental sample of boats in addition to the pure random sample. To ensure the sample represented the total population of registered boats in the Northeast, the sampling method included considerations of state, geography and size class. Of the 373,766 boats eligible for the survey, the base of randomly sampled boats included 50,000 boats from across all six states. In addition to this base, the survey team sampled 17,772 boats as a supplemental sample, including: 1,772 boats of 26 feet in length or more from across all six states to increase the number of large boats in the sample, and 16,000 additional boats to ensure each state had enough responses for the statistical analysis. These included 10,000 boats from Maine, 2,500 boats from Rhode Island, 2,000 boats from New Hampshire and 1,500 boats from Connecticut. This resulted in a total of 67,772 boaters invited to participate in the study. Boater Recruitment and Response: In the survey invitation package, the survey team also sent invited boaters a questionnaire to verify eligibility to participate in the survey. Eligibility requirements consist of: boat is used in saltwater; boat is used for recreational purposes; and boaters have access to the internet with a working email address. 12,218 boaters responded to the invitation; however only 7,800 of these respondents were found to meet all of the above criteria. From this sample, 4,297 individual boaters completed at least one monthly survey. Surveying Process: The study consisted of six monthly surveys and one end of season survey. The online monthly surveys gathered spatial and economic data on recreational boating activity that occurred during the previous month. The online survey had two parts: 1) a survey with questions about general boating activity during the previous month, and the boater’s last trip of the month (specifically focusing on spending), and 2) a mapping application developed by Ecotrust where boaters plotted their boating route and identified any areas where they participated in activities, such as fishing, diving, wildlife viewing, swimming and relaxing at anchor. The end of season survey gathered a variety of information that could not be gathered in the monthly surveys. The end of season survey contained questions about yearly boating-related expenditures (e.g., dockage, storage, taxes, yearly maintenance), feedback on the survey itself, and general boating-related questions (e.g. whether boaters have taken a boating safety course). Density Analysis: The density analysis described in the following paragraphs was vetted by a technical advisory team consisting of representatives from the Massachusetts Office of Coastal Zone Management (MA CZM), NROC, Maine Coastal Program and Applied Science Associates (ASA) and was based on mapping and analysis protocols from the 2010 Massachusetts Survey. To develop the density layer, vessel routes were drawn in WGS 1984 in the Ecotrust mapping application and were imported into Excel, then ArcMap using a data frame in that coordinate system. Routes from the random sample were selected from that data layer, and the data layer was re-projected into two separate shapefiles, one in UTM 18 and one in UTM 19. A line density analysis using a 250 m square grid cell with a 675 m neighborhood was applied to each shapefile. The 675 m neighborhood was applied to account for inherent user error in the mapping tool. The line density analysis resulted in a raster grid for each UTM zone. Each raster was clipped by the boundaries of its UTM zone, re-projected into the North American Albers Equal Area Conic Projection, and the separate rasters were mosaicked together. At the boundary of the two raster grids there was a line of cells with no data value. This was a result of mosaicking rasters that originated in different coordinate systems. To approximate values in the blank cells, each blank cell was populated by a value from a focal statistics calculation. The focal statistics expression took the mean of all cells in a 4x4 neighborhood around each blank cell. The values were then converted to Z-scores using the raster calculator by taking the log of the density values, subtracting the mean value, and dividing the resulting value by the standard deviation of the value. This layer was clipped again using the NOAA medium resolution shoreline dataset. DATA PROCESSING Processing environment: ArcGIS 10.05, Windows 7 Ultimate SP5, Intel Xeon CPU Process Steps Description 1 Raw routes from mapping application imported into ArcMap 2 Routes from random sample selected using select by attributes query 3 Routes projected into two separate shapefiles (UTM Zones 18 & 19) 4 LINE DENSITY tool in spatial analyst applied to each shapefile using a 250 m square grid with a 675 m neighborhood 5 Resulting rasters clipped to their respective UTM Zones using the EXTRACT BY MASK tool 6 Rasters reprojected to North America Albers Equal Area Conic Projection, using PROJECT tool 7 MOSAIC tool used to merge rasters 8 Focal mean expression (4x4 neighborhood) used to approximate and fill cells with no data at the boundary between mosaicked rasters 9 Raster calculator used to calculated Z-scores ([(Ln(Value))-Mean]/Std. Deviation) 10 Raster clipped by NOAA Medium Resolution Shoreline data using EXTRACT BY POLYGON tool QUALITY PROCESS Attribute Accuracy: The lines used to generate the density grid were derived from a mapping tool used by boaters to reconstruct their boating routes. To ensure that boaters included their round-trip route the mapping applications would send the user an error message asking them to re-plot the route or the program would automatically return the route to the starting point. This application also restricted the scale at which users could draw their routes, reducing the amount of error that could occur from plotting routes at too small a scale. Clipping this layer with a regional ocean shapefile derived from the NOAA medium resolution shoreline dataset excluded route density resulting from routes drawn over land, in freshwater, or outside of northeastern waters. Logical Consistency: None Completeness: Only reported routes from the random sample were included. Routes from the supplemental sample were excluded from this analysis. Route density occurring over land, freshwater areas, or outside northeastern waters was excluded by the final geoprocessing step. Positional Accuracy: The positional accuracy of the routes is dependent on the individual reporting routes through the

Nearshore fisheries in the Main Hawaiian Islands encompass a diverse group of fishers using a wide array of gears and targeting many different species. Communities in Hawaii often rely on these fisheries for economic, social, and cultural services. However, the stress from overfishing can cause ecosystem degradation and long-term economic loss. This layer represents the average annual catch of reef fish by non-commercial boat-based line fishing methods. Average annual catch at the island scale from 2004-2013 was estimated from Marine Recreational Information Program (MRIP) combined fisher intercept and phone survey data (McCoy et al., 2018). These island-scale estimates were spatially distributed offshore using distance to boat harbors and launch ramps while accounting for marine protected areas (MPAs) and de facto MPAs (e.g., military danger zones) where access is restricted. A Gaussian decay function assumed the majority of the catch occurs within 10-20 km of each harbor. Additionally, the Ocean Tipping Points (OTP) project weighted boat harbors by the human population present within 30 km. This layer's spatial footprint aligns with the inshore commercial reporting blocks for commercial fish catch reporting to the State of Hawaii Department of Aquatic Resources (DAR). Point data for boat harbors and launch ramps were combined from two datasets available from the Hawaii Statewide GIS Program website (Harbors.shp and BoatingFacilities.shp) (http://planning.hawaii.gov/gis/download-gis-data/). Data were checked for quality to ensure only operational boat harbors and launch ramps were included and geographic positions were accurate. Anchorages, fishing piers, historic, and disused ramps/harbors were removed prior to analysis. Boat facility weighting factors were calculated based on total human population within 30 km of each boat harbor or ramp. Human population was mapped based on 2010 census data and LANDFIRE land use/land cover data using the USGS Dasymetric Mapping Tool to gain a more accurate representation of population distribution. A 30-km buffer was then created around each boating facility and a Zonal Statistics tool was used to sum the human population within each buffer. These population values were then used to assign weights to each boating facility in order to allocate a proportion of total island catch estimates to each boat harbor or ramp. These weights sum to 1 for each island. In order to allocate catch proportionally to each boat harbor/ramp, estimated annual catch at the island scale and the human population-based weighting factor were joined to the attribute table of each boating facility's cost allocation footprint and used in a Gaussian decay function with each distance surface. This decay function assumes the majority of catch occurs within 10-20 km of a harbor or ramp and declines more rapidly with increasing distance. Catch in full no-take MPAs were set to zero and other areas with restricted access were reduced according to expert input and local knowledge. Pixel values within each boating facility's footprint were then rescaled such that the sum in each footprint was equal to the respective boat facility's weighting factor times the MRIP catch estimate for that island in units of kg per pixel. Finally, all raster layers for each boat harbor/ramp were summed together. Final pixels values are in units of kg/ha such that the sum of all pixels for each island is equal to the estimates of average annual catch from McCoy et al. (2018). Units, pixel size, and grid alignment are consistent with all other OTP fishing layers so that they can be compared directly or added together for various uses.

This dynamic map service contains all state maintained ferry boats and ferry boat facilities located within the Commonwealth of Kentucky that are federally funded through the FHWA FAST (Fixing America's Surface Transportation) Act. For more information on the FAST program, please reference the US Department of Transportation's Federal Highway Administration page on FAST.

Dataset

The Man OverBoard Drone (MOBDrone) dataset is a large-scale collection of aerial footage images. It contains 126,170 frames extracted from 66 video clips gathered from one UAV flying at an altitude of 10 to 60 meters above the mean sea level. Images are manually annotated with more than 180K bounding boxes localizing objects belonging to 5 categories --- person, boat, lifebuoy, surfboard, wood. More than 113K of these bounding boxes belong to the person category and localize people in the water simulating the need to be rescued.

In this repository, we provide:

66 Full HD video clips (total size: 5.5 GB)

126,170 images extracted from the videos at a rate of 30 FPS (total size: 243 GB)

3 annotation files for the extracted images that follow the MS COCO data format (for more info see https://cocodataset.org/#format-data):

annotations_5_custom_classes.json: this file contains annotations concerning all five categories; please note that class ids do not correspond with the ones provided by the MS COCO standard since we account for two new classes not previously considered in the MS COCO dataset --- lifebuoy and wood

annotations_3_coco_classes.json: this file contains annotations concerning the three classes also accounted by the MS COCO dataset --- person, boat, surfboard. Class ids correspond with the ones provided by the MS COCO standard.

annotations_person_coco_classes.json: this file contains annotations concerning only the 'person' class. Class id corresponds to the one provided by the MS COCO standard.

The MOBDrone dataset is intended as a test data benchmark. However, for researchers interested in using our data also for training purposes, we provide training and test splits:

Test set: All the images whose filename starts with "DJI_0804" (total: 37,604 images)

Training set: All the images whose filename starts with "DJI_0915" (total: 88,568 images)

More details about data generation and the evaluation protocol can be found at our MOBDrone paper: https://arxiv.org/abs/2203.07973 The code to reproduce our results is available at this GitHub Repository: https://github.com/ciampluca/MOBDrone_eval See also http://aimh.isti.cnr.it/dataset/MOBDrone

Citing the MOBDrone

The MOBDrone is released under a Creative Commons Attribution license, so please cite the MOBDrone if it is used in your work in any form. Published academic papers should use the academic paper citation for our MOBDrone paper, where we evaluated several pre-trained state-of-the-art object detectors focusing on the detection of the overboard people

@inproceedings{MOBDrone2021, title={MOBDrone: a Drone Video Dataset for Man OverBoard Rescue}, author={Donato Cafarelli and Luca Ciampi and Lucia Vadicamo and Claudio Gennaro and Andrea Berton and Marco Paterni and Chiara Benvenuti and Mirko Passera and Fabrizio Falchi}, booktitle={ICIAP2021: 21th International Conference on Image Analysis and Processing}, year={2021} }

and this Zenodo Dataset

@dataset{donato_cafarelli_2022_5996890, author={Donato Cafarelli and Luca Ciampi and Lucia Vadicamo and Claudio Gennaro and Andrea Berton and Marco Paterni and Chiara Benvenuti and Mirko Passera and Fabrizio Falchi}, title = {{MOBDrone: a large-scale drone-view dataset for man overboard detection}}, month = feb, year = 2022, publisher = {Zenodo}, version = {1.0.0}, doi = {10.5281/zenodo.5996890}, url = {https://doi.org/10.5281/zenodo.5996890} }

Personal works, such as machine learning projects/blog posts, should provide a URL to the MOBDrone Zenodo page (https://doi.org/10.5281/zenodo.5996890), though a reference to our MOBDrone paper would also be appreciated.

Contact Information

If you would like further information about the MOBDrone or if you experience any issues downloading files, please contact us at mobdrone[at]isti.cnr.it

Acknowledgements

This work was partially supported by NAUSICAA - "NAUtical Safety by means of Integrated Computer-Assistance Appliances 4.0" project funded by the Tuscany region (CUP D44E20003410009). The data collection was carried out with the collaboration of the Fly&Sense Service of the CNR of Pisa - for the flight operations of remotely piloted aerial systems - and of the Institute of Clinical Physiology (IFC) of the CNR - for the water immersion operations.

European Production of Ships and Boats Building by Country, 2023 Discover more data with ReportLinker!

[Metadata] Locations of small boat harbors / boat ramps in the State of Hawaii as of 1994. Source: DLNR/DOBOR and Office of Planning/CZM, 1994. For more information, please see metadata at https://files.hawaii.gov/dbedt/op/gis/data/harbors_small_boat.pdf or contact Hawaii Statewide GIS Program, Office of Planning and Sustainable Development, State of Hawaii; PO Box 2359, Honolulu, Hi. 96804; (808) 587-2846; email: gis@hawaii.gov; Website: https://planning.hawaii.gov/gis.

This dataset contains the file of vehicle, snowmobile and boat registrations in NYS. Expired registrations are excluded. Records that have a scofflaw, revocation and/or suspension are included with indicators specifying this.

This dataset contains the file of vehicle, snowmobile and boat registrations in NYS. Expired registrations are excluded. Records that have a scofflaw, revocation and/or suspension are included with indicators specifying this.

This dataset contains the file of vehicle, snowmobile and boat registrations in NYS. Expired registrations are excluded. Records that have a scofflaw, revocation and/or suspension are included with indicators specifying this.

The proposed AIS dataset encompasses a substantial temporal span of 20 months, spanning from April 2021 to December 2022. This extensive coverage period empowers analysts to examine long-term trends and variations in vessel activities. Moreover, it facilitates researchers in comprehending the potential influence of external factors, including weather patterns, seasonal variations, and economic conditions, on vessel traffic and behavior within the Finnish waters.

This dataset encompasses an extensive array of data pertaining to vessel movements and activities encompassing seas, rivers, and lakes. Anticipated to be comprehensive in nature, the dataset encompasses a diverse range of ship types, such as cargo ships, tankers, fishing vessels, passenger ships, and various other categories.

The AIS dataset exhibits a prominent attribute in the form of its exceptional granularity with a total of 2 293 129 345 data points. The provision of such granular information proves can help analysts to comprehend vessel dynamics and operations within the Finnish waters. It enables the identification of patterns and anomalies in vessel behavior and facilitates an assessment of the potential environmental implications associated with maritime activities.

Please cite the following publication when using the dataset:

TBD

The publication is available at: TBD

A preprint version of the publication is available at TBD

csv file structure

YYYY-MM-DD-location.csv

This file contains the received AIS position reports. The structure of the logged parameters is the following: [timestamp, timestampExternal, mmsi, lon, lat, sog, cog, navStat, rot, posAcc, raim, heading]

timestamp I beleive this is the UTC second when the report was generated by the electronic position system (EPFS) (0-59, or 60 if time stamp is not available, which should also be the default value, or 61 if positioning system is in manual input mode, or 62 if electronic position fixing system operates in estimated (dead reckoning) mode, or 63 if the positioning system is inoperative).

timestampExternal The timestamp associated with the MQTT message received from www.digitraffic.fi. It is assumed this timestamp is the Epoch time corresponding to when the AIS message was received by digitraffic.fi.

mmsi MMSI number, Maritime Mobile Service Identity (MMSI) is a unique 9 digit number that is assigned to a (Digital Selective Calling) DSC radio or an AIS unit. Check https://en.wikipedia.org/wiki/Maritime_Mobile_Service_Identity

lon Longitude, Longitude in 1/10 000 min (+/-180 deg, East = positive (as per 2's complement), West = negative (as per 2's complement). 181= (6791AC0h) = not available = default)

lat Latitude, Latitude in 1/10 000 min (+/-90 deg, North = positive (as per 2's complement), South = negative (as per 2's complement). 91deg (3412140h) = not available = default)

sog Speed over ground in 1/10 knot steps (0-102.2 knots) 1 023 = not available, 1 022 = 102.2 knots or higher

cog Course over ground in 1/10 = (0-3599). 3600 (E10h) = not available = default. 3 601-4 095 should not be used

navStat Navigational status, 0 = under way using engine, 1 = at anchor, 2 = not under command, 3 = restricted maneuverability, 4 = constrained by her draught, 5 = moored, 6 = aground, 7 = engaged in fishing, 8 = under way sailing, 9 = reserved for future amendment of navigational status for ships carrying DG, HS, or MP, or IMO hazard or pollutant category C, high speed craft (HSC), 10 = reserved for future amendment of navigational status for ships carrying dangerous goods (DG), harmful substances (HS) or marine pollutants (MP), or IMO hazard or pollutant category A, wing in ground (WIG); 11 = power-driven vessel towing astern (regional use); 12 = power-driven vessel pushing ahead or towing alongside (regional use); 13 = reserved for future use, 14 = AIS-SART (active), MOB-AIS, EPIRB-AIS 15 = undefined = default (also used by AIS-SART, MOB-AIS and EPIRB-AIS under test)

rot ROTAIS Rate of turn

0 to +126 = turning right at up to 708 deg per min or higher

0 to -126 = turning left at up to 708 deg per min or higher

Values between 0 and 708 deg per min coded by ROTAIS = 4.733 SQRT(ROTsensor) degrees per min where ROTsensor is the Rate of Turn as input by an external Rate of Turn Indicator (TI). ROTAIS is rounded to the nearest integer value.

+127 = turning right at more than 5 deg per 30 s (No TI available)

-127 = turning left at more than 5 deg per 30 s (No TI available)

-128 (80 hex) indicates no turn information available (default).

ROT data should not be derived from COG information.

posAcc Position accuracy, The position accuracy (PA) flag should be determined in accordance with the table below:

1 = high (<= 10 m)

0 = low (> 10 m)

0 = default

See https://www.navcen.uscg.gov/?pageName=AISMessagesA#RAIM

raim RAIM-flag Receiver autonomous integrity monitoring (RAIM) flag of electronic position fixing device; 0 = RAIM not in use = default; 1 = RAIM in use. See Table https://www.navcen.uscg.gov/?pageName=AISMessagesA#RAIM

Check https://en.wikipedia.org/wiki/Receiver_autonomous_integrity_monitoring

heading True heading, Degrees (0-359) (511 indicates not available = default)

YYYY-MM-DD-metadata.csv

This file contains the received AIS metadata: the ship static and voyage related data. The structure of the logged parameters is the following: [timestamp, destination, mmsi, callSign, imo, shipType, draught, eta, posType, pointA, pointB, pointC, pointD, name]

timestamp The timestamp associated with the MQTT message received from www.digitraffic.fi. It is assumed this timestamp is the Epoch time corresponding to when the AIS message was received by digitraffic.fi.

destination Maximum 20 characters using 6-bit ASCII; @@@@@@@@@@@@@@@@@@@@ = not available For SAR aircraft, the use of this field may be decided by the responsible administration

mmsi MMSI number, Maritime Mobile Service Identity (MMSI) is a unique 9 digit number that is assigned to a (Digital Selective Calling) DSC radio or an AIS unit. Check https://en.wikipedia.org/wiki/Maritime_Mobile_Service_Identity

callSign 7?=?6 bit ASCII characters, @@@@@@@ = not available = default Craft associated with a parent vessel, should use “A” followed by the last 6 digits of the MMSI of the parent vessel. Examples of these craft include towed vessels, rescue boats, tenders, lifeboats and liferafts.

imo 0 = not available = default – Not applicable to SAR aircraft

0000000001-0000999999 not used

0001000000-0009999999 = valid IMO number;

0010000000-1073741823 = official flag state number.

Check: https://en.wikipedia.org/wiki/IMO_number

shipType

0 = not available or no ship = default

1-99 = as defined below

100-199 = reserved, for regional use

200-255 = reserved, for future use Not applicable to SAR aircraft

Check https://www.navcen.uscg.gov/pdf/AIS/AISGuide.pdf and https://www.navcen.uscg.gov/?pageName=AISMessagesAStatic

draught In 1/10 m, 255 = draught 25.5 m or greater, 0 = not available = default; in accordance with IMO Resolution A.851 Not applicable to SAR aircraft, should be set to 0

eta Estimated time of arrival; MMDDHHMM UTC

Bits 19-16: month; 1-12; 0 = not available = default

Bits 15-11: day; 1-31; 0 = not available = default

Bits 10-6: hour; 0-23; 24 = not available = default

Bits 5-0: minute; 0-59; 60 = not available = default

For SAR aircraft, the use of this field may be decided by the responsible administration

posType Type of electronic position fixing device

0 = undefined (default)

1 = GPS

2 = GLONASS

3 = combined GPS/GLONASS

4 = Loran-C

5 = Chayka

6 = integrated navigation system

7 = surveyed

8 = Galileo,

9-14 = not used

15 = internal GNSS

pointA Reference point for reported position.

Also indicates the dimension of ship (m). For SAR aircraft, the use of this field may be decided by the responsible administration. If used it should indicate the maximum dimensions of the craft. As default should A = B = C = D be set to “0”

Check: https://www.navcen.uscg.gov/?pageName=AISMessagesAStatic#_Reference_point_for

pointB See above

pointC See above

pointD See above

name Maximum 20 characters 6 bit ASCII "@@@@@@@@@@@@@@@@@@@@" = not available = default The Name should be as shown on the station radio license. For SAR aircraft, it should be set to “SAR AIRCRAFT NNNNNNN” where NNNNNNN equals the aircraft registration number.

This dataset contains Saudi Arabia Ships Arriving at Saudi Ports, by Country of Registration and port for 2008 - 2019. Data from General Authority for Statistics. Export API data for more datasets to advance energy economics research.We have used year converter to find the Gregorian yearhttp://www.menalib.de/index.php?id=97

Global Export of Yachts, Pleasure, Sports Vessels, Rowing Boats and Canoes by Country, 2023 Discover more data with ReportLinker!