The Methodology for Assessing the Impact of Offshore Wind Farms on Navigation, Based on the Automatic Identiﬁcation System Historical Data

: Mounting offshore renewable energy installations often involves extra risk regarding the safety of navigation, especially for areas with high trafﬁc intensity. The decision-makers planning such projects need to anticipate and plan appropriate solutions in order to manage navigation risks. This process is referred to as “environmental impact assessment”. In what way can these threats be reduced using the available Automatic Identiﬁcation System (AIS) tool? This paper presents a study of the concept for the methodology of an a posteriori vessel trafﬁc description in the form of quantitative and qualitative characteristics created based on a large set of historical AIS data (big data). The research was oriented primarily towards the practical application and veriﬁcation of the methodology used when assessing the impact of the planned Offshore Wind Farm (OWF) Baltic II on the safety of ships in Polish Marine Areas, and on the effectiveness of navigation, taking into account the existing shipping routes and customary and trafﬁc separation systems. The research results (e.g., a signiﬁcant distance of the Baltic II from the nearest customary shipping route equal to 3 Nm, a small number of vessels in its area in 2017 amounting to only 930) obtained on the basis of the annual AIS data set allowed for an unambiguous and reliable assessment of the impact of OWFs on shipping, thus conﬁrming the suitability of the methodology for MREI spatial planning.


Introduction
Poland, as a member of the European Union, is obliged to reduce greenhouse gas emissions. One of the flagship projects aimed at achieving the planned reduction of GHG emissions is using wind farms to replace the energy deficit resulting from the gradually closing coal-fired power plants. By 2030, Renewable Energy Sources are to replace 66.6% of coal. Therefore, they constitute the main measures for achieving the target imposed by the European Union.
Over the last 10 years, the share of wind farms in the generating of electric power in Poland has increased more than 6-fold [1]. In addition, the installed capacity has increased more than 5-fold during the period 2010-2020.
According to data from the Energy Regulatory Office, at the end of 2020, there were 1239 wind farms operating in the country, including 1111 with a capacity of less than 10 MW (89.7%) and 128 with a capacity greater than or equal to 10 MW. The amount of energy produced from wind sources is also systematically growing, and is being introduced into the Polish power system. In 2020, they produced 14,174 GW h of energy (compared to 13,903 GW h in 2019). Wind energy accounted for approx. 8.2% of the energy consumed in the country in 2019. According to the assumptions of the National Energy and Climate -0.45-2 nautical miles-acceptable, medium, and high risk; -2-3.5 nautical miles-acceptable, low risk; ->3.5 nautical miles-very low risk.
In turn, in 2014, the Pacific Northwest National Laboratory issued a report indicating that ships generally chose to leave a distance of 5 nautical miles from the OWF, and this was safe [18]. On the other hand, the UK NOREL working group assumes that a distance of 2 nautical miles should be kept between the OWF border and the shipping route [19,20]. However, decisions regarding this parameter are generally made on a case-by-case basis, taking into account the existing obstacles and dangers to navigate as well as the location and layout of routes.
The research presented in this article focuses on the previously missing aspect of the effective use of AIS in spatial planning, supporting the optimal location of marine renewable energy installations through analysis, and the description of ship traffic in the form of quantitative and qualitative characteristics specified for various types of ships, as well as their draft and length. The results were obtained as part of an expert assessment of the impact of the planned OWF Baltic II on the safety of ships in Polish Maritime Areas and the effectiveness of their navigation, taking into account the existing shipping routes, and customary and traffic separation schemes commissioned by Baltic Trade and Invest (BTI) [21]. Currently the OWF Baltic II is managed by RWE Renewables as the project owner. RWE is going to utilize the conclusions drawn from the expert opinion on the safety of ships in Polish Maritime Areas and the effectiveness of their navigation while implementing the project.
The novelty of the proposed methodology is that it allows for the simultaneous implementation of quantitative and qualitative analyses, both in a small area of the OWF, and on the nearby customary shipping routes or the established maritime traffic regulation system. To use this methodology, three following data sets are needed: -describing maritime traffic (data come from coastal AIS stations); -describing the boundaries of the OWF area along with buffers; -about the marine environment (data obtained from electronic navigational charts, authorized by national hydrographic offices, guaranteeing their quality, reliability and timeliness).
The appropriate joint processing of these data sets makes it possible to obtain information to decide on the location of the OWF. The comparison of the gathered information, obtained before and after the building of the OWF, allows us to assess its impact on shipping.
The first part of the article presents the location of the planned OWF Baltic II in relation to the AIS coastal station system, the research tools used, as well as the AIS data coding and processing methodology.
The main part contains the developed quantitative and qualitative characteristics of ship traffic generalized to the area of the central coast of the Polish Maritime Areas (PMA) [22], detailed for the area of the OWF Baltic II and covering the nearest shipping routes [23].
The final part, however, is an analysis of quantitative characteristics, taking into account, inter alia, the main traffic flows and the analysis of qualitative characteristics broken down into the type, length, and draft of the vessel. Based on this, generalized final conclusions have been drawn.

Materials and Methods
Polish law requires an examination of the impact of MREI on the safety of the environment and shipping [24]. The research used AIS data collected in the database of the polish coastal system AIS-PL in 2017 and made available by the Maritime Office in Gdynia [25][26][27]. The identification of the characteristics of the vessels was carried out on the basis of information on vessel traffic obtained as a result of the appropriate processing of data from the AIS system (proprietary software). It concerned the part of the Baltic Sea basin where the OWF Baltic II is planned (Figure 1). Polish law requires an examination of the impact of MREI on the safety of the e ronment and shipping [24]. The research used AIS data collected in the database of polish coastal system AIS-PL in 2017 and made available by the Maritime Office in G nia [25][26][27]. The identification of the characteristics of the vessels was carried out on basis of information on vessel traffic obtained as a result of the appropriate processin data from the AIS system (proprietary software). It concerned the part of the Baltic basin where the OWF Baltic II is planned (Figure 1).  Figure 1 shows the location of the OWF Baltic II in relation to the monitoring covered by the AIS coastal station system on the Polish coast. The shipping area aro the installation is within the operating range of the available shore stations, which p vides access to archival and current data on vessel traffic in the OWF Baltic II zone.

Analysis Tools
Information on the characteristics of the vessels maneuvering in the OWF area obtained as a result of processing "raw" AIS data. A specially prepared software ap cation, "Analyzer", was used for this purpose. The application was made in the C Builder 10.2.3 integrated application development environment [28], designed for Windows 10 operating system ( Figure 2).  Figure 1 shows the location of the OWF Baltic II in relation to the monitoring area covered by the AIS coastal station system on the Polish coast. The shipping area around the installation is within the operating range of the available shore stations, which provides access to archival and current data on vessel traffic in the OWF Baltic II zone.

Analysis Tools
Information on the characteristics of the vessels maneuvering in the OWF area was obtained as a result of processing "raw" AIS data. A specially prepared software application, "Analyzer", was used for this purpose. The application was made in the C++ Builder 10.2.3 integrated application development environment [28], designed for the Windows 10 operating system ( Figure 2).
Its basic functionalities allow for the processing of raw VDM/NEMA 0183 messages used for transmitting the entire content of the AIS message packet received via the VHF/RS 232C/RS 422 link into information useful for the quantitative and qualitative analysis of vessel traffic [29,30]. The information created in this way is made available in the form of a GRID file (for quantitative analysis) and a tabular file (for qualitative analysis). GRID files are in the form of a regular square grid. Each square was assigned a value corresponding to the number of ships "staying" in it during a given period of time, determined as a result of the analysis of the mutual positions of successive sections along which vessels move and sections delimiting individual GRID meshes ( Figure 3). Figure 3 shows a fragment of the GRID (its four meshes) and two trajectories of vessel movement, which were determined on the basis of the coordinates of the positions of the vessels tracked in the AIS system. Inside each mesh (square) there is a knot that is assigned a value determined as a result of the analysis of the mutual position of the successive sections along which the vessel moves and the sections delimiting the individual meshes of the GRID mesh. The value of the knot increases by one if the section on which the vessel is moving crosses any of the sections that make up the sides of the square bounding the knot mesh. A vessel that has increased its value in a node may increase it by one only when the next section of its trajectory is crossed by one of the sections forming the sides of the square bounding the other mesh. This avoids multiple impacts of the same vessel on the same node. This is particularly important in the case of messages with position coordinates (no. 1-3, 18), which can be transmitted with high frequency (as much as every 2 s) depending on the navigational status, speed, and maneuvering method [31]. The following are the relationships for determining the coordinates (X, Y) of the point of intersection of straight lines passing through points A(x 1 , y 1 ) and B(x 2 , y 2 ) forming the next segment of the ship's trajectory, and lines passing through the sides of the square of the mesh for each node of the GRID: The calculated coordinates of the point should fall on the analyzed square side-line, which means that the unit enters the mesh area, and the value of the knot should be increased by one. The format of the resulting GRID network saved into the output file is shown below [32,33]. Its basic functionalities allow for the processing of raw VDM/NEMA 0183 messages used for transmitting the entire content of the AIS message packet received via the VHF/RS 232C/RS 422 link into information useful for the quantitative and qualitative analysis of vessel traffic [29,30]. The information created in this way is made available in the form of a GRID file (for quantitative analysis) and a tabular file (for qualitative analysis). GRID files are in the form of a regular square grid. Each square was assigned a value corresponding to the number of ships "staying" in it during a given period of time, determined as a result of the analysis of the mutual positions of successive sections along which vessels move and sections delimiting individual GRID meshes ( Figure 3). Its basic functionalities allow for the processing of raw VDM/NEMA 0183 messages used for transmitting the entire content of the AIS message packet received via the VHF/RS 232C/RS 422 link into information useful for the quantitative and qualitative analysis of vessel traffic [29,30]. The information created in this way is made available in the form of a GRID file (for quantitative analysis) and a tabular file (for qualitative analysis). GRID files are in the form of a regular square grid. Each square was assigned a value corresponding to the number of ships "staying" in it during a given period of time, determined as a result of the analysis of the mutual positions of successive sections along which vessels move and sections delimiting individual GRID meshes ( Figure 3).  This file can be imported by applications such as Geographic Information Systems (GIS), including MapInfo and ArcGIS, and used subsequently in these applications to create maps with the distribution of the intensity of vessel traffic on a cartographic basis (e.g., in the Mercator mapping projection). The resulting table files can, in turn, be imported by applications with a spreadsheet functionality, e.g., Microsoft Excel, and then used to create qualitative statistics on vessel traffic. This file is created as a result of the appropriate processing of messages with static information about the ship, i.e., no. 5 and 24, into text form [31]. It contains a numerical list of ships divided into types consistent with ITU-R M.1371-5 (Table 1), based on the draft, length, and class of the AIS transponder used. Port tenders 54 Vessels with anti-pollution facilities or equipment 55 Law enforcement vessels This file can be imported by applications such as Geographic Information Systems (GIS), including MapInfo and ArcGIS, and used subsequently in these applications to create maps with the distribution of the intensity of vessel traffic on a cartographic basis (e.g., in the Mercator mapping projection). The resulting table files can, in turn, be imported by applications with a spreadsheet functionality, e.g., Microsoft Excel, and then used to create qualitative statistics on vessel traffic. This file is created as a result of the appropriate processing of messages with static information about the ship, i.e., no. 5 and 24, into text form [31]. It contains a numerical list of ships divided into types consistent with ITU-R M.1371-5 (Table 1), based on the draft, length, and class of the AIS transponder used. First digit (1) Second digit (1) First digit (1) Second digit (1) 1-Reserved for future use 0-All ships of this type -0-Fishing Software validation was carried out using the AIS transponder simulator and the real data about ships standing, entering and leaving ports (obtained from the Harbor Master's Offices). The simulation generated a list of messages sent by many ships traveling on the same route (with a given Cross Track Distance (XTD)), standing at anchorages and moored to a harbor wharf. The compliance of the quantitative and qualitative values obtained with the developed software was checked with the true and simulated values corresponding to them. The results of the fifty validation tests carried out confirm the correctness of the software's operation.

The Analysis Process
The analysis of vessel characteristics was based on the AIS-PL archive data collected in the NMSS (National Maritime Safety System) database in 2017. These data, in the form of an annual set of one-day files with a capacity of 39.6 GB (after unpacking), were made available by the Maritime Office in Gdynia.
On the basis of this set of files, using the original "Analyzer" software, 839322999 "raw" AIS messages were processed, and 64856, being incorrect, were rejected (including on the basis of the checksum), and then converted into GRID files and tabular files. Secondly, this allowed for the description of the movement of ships in the form of: quantitative characteristics-based on distributions of traffic intensity, made with the use of a GRID file with a mesh resolution of 2"; -qualitative characteristics-based on spreadsheets used in Microsoft Excel to build statistics broken down by ship type, draft, and length.
These characteristics constitute the source of information used to identify the vessels sailing in the studied water, which helped to determine the customary routes and enabled the prediction of vessel movement in the spatial planning supporting the optimal location of offshore renewable energy installations.

The Results of the Identification of the Characteristic Features of Ships in a Large Sea Area around the OWF (Central Coast of the Polish Maritime Areas-PMA)
After the AIS data had been processed with the use of proprietary software, a quantitative and qualitative analysis was performed for various types of vessels, among which passenger, cargo, special, and fishing vessels were selected, due to their increased traffic within the wind farm. In total, 3861 unique vessel types were registered, including 3281 (85%) with an AIS Class A transponder and 581 (15%) with a Class B transponder. The results are presented in graphical form below. Figure 4 and Table 2 shows the distribution of traffic intensity and the qualitative characteristics for all types of ships covering a large sea area surrounding OWF.   Table 2 shows the distribution of traffic intensity and the qualitative characteristics for all types of ships covering a large sea area surrounding OWF.         Figure 5 and Table 3 shows the distribution of traffic intensity and the qualitative characteristics for fishing vessels covering a large sea area surrounding OWF.  Table 3 shows the distribution of traffic intensity and the qualitative characteristics for fishing vessels covering a large sea area surrounding OWF. In total, 268 unique fishing vessels were registered, of which 237 (88.4%) had AIS Class A transponders and 31 (11.6%) had a Class B transponders.  In total, 268 unique fishing vessels were registered, of which 237 (88.4%) had AIS Class A transponders and 31 (11.6%) had a Class B transponders. Figure 6 and Table 4 shows the distribution of traffic intensity and the qualitative characteristics for passenger ships covering a large sea area surrounding OWF. In total, 268 unique fishing vessels were registered, of which 237 (88.4%) had AIS Class A transponders and 31 (11.6%) had a Class B transponders. undefined Quantitative distribution of unique ships by their length Figure 5. Distribution of the traffic intensity of fishing vessels covering a large sea area around the OWF (vessel type number: 30, AIS-PL 2017).

Quantitative and Qualitative Characteristics of Passenger Ships
In total, 268 unique fishing vessels were registered, of which 237 (88.4%) had AIS Class A transponders and 31 (11.6%) had a Class B transponders.  Figure 6 and Table 4 shows the distribution of traffic intensity and the qualitative characteristics for passenger ships covering a large sea area surrounding OWF.       Figure 7 shows the flow of traffic running through the center of the OWF. It was created by the Russian OMSKIY-133 vessel (MMSI no.: 273310900, length = 108.4 m, width = 15 m), which ran several times a month between the ports of the eastern and western Baltic coasts, i.e., Saint Petersburg, Riga, Kaliningrad, Klaipeda, Kunda, Ventspils, Svetliy and Szczecin, Police, Frederiksvaerk and Rostock.            In total, 2164 unique cargo ships were registered, of which 2108 (97.4%) had an AIS Class A transponder and 56 (2.6%) had a Class B transponder (Table 6 and Table 7 In total, 2164 unique cargo ships were registered, of which 2108 (97.4%) had an AIS Class A transponder and 56 (2.6%) had a Class B transponder (Tables 6 and 7).       Figure 8 presents an area involving the OWF and the measurement profiles of the nearest shipping routes adopted for the analysis.     Figure 9, Figure 10 and Table 8 shows the distribution of traffic intensity and the qualitative characteristics for all types ships in the OWF area plus a 2 Nm buffer.   Table 8 shows the distribution of traffic intensity and the qualitative characteristics for all types ships in the OWF area plus a 2 Nm buffer.  Figure 9, Figure 10 and Table 8 shows the distribution of traffic intensity and the qualitative characteristics for all types ships in the OWF area plus a 2 Nm buffer.    The results presented below were obtained from the Maritime Office in Gdynia ( Figure 11 and Figure 12).  Figure 10. Vessel traffic intensity of all types in the OWF area plus a 2 Nm buffer (1 mesh GRID).   The results presented below were obtained from the Maritime Office in Gdynia ( Figure 11 and Figure 12).

Qualitative Characteristics of the Measurement Cross NW (E) Route
In total, 433 unique ships of all types were registered on the measurement profile 1-1, including 426 (98.4%) with AIS class A transponders and 7 (1.6%) with class B transponders (Tables 9 and 10).

Qualitative Characteristics of the Measurement Cross NE (D) Route
In total, on the measurement profile 2-2, 232 unique ships of all types were registered, including 232 (100.0%) with AIS Class A transponders and 0 (0.0%) with Class B transponders (Tables 11 and 12).

Qualitative Characteristics of the Measuring Cross EW (I) Route
In total, on the profile 3-3, 1996 unique ships of all types were registered on the measurement profile, including 1952 (97.8%) with AIS class A transponders and 44 (2.2%) with class B transponders (Tables 13 and 14).

Qualitative Characteristics of the Measurement Section 1-1 of the Usual NW (E) Route
In total, 433 unique ships of all types were registered on the measurement profile 1-1, including 426 (98.4%) with AIS class A transponders and 7 (1.6%) with class B transponders (Table 9 and Table 10).     In total, on the measurement profile 2-2, 232 unique ships of all types were registered, including 232 (100.0%) with AIS Class A transponders and 0 (0.0%) with Class B transponders (Table 11 and Table 12) .  In total, on the measurement profile 2-2, 232 unique ships of all types were registered, including 232 (100.0%) with AIS Class A transponders and 0 (0.0%) with Class B transponders (Table 11 and Table 12) .   In total, on the 3 to 3 profile, 1996 unique ships of all types were registered on the measurement profile, including 1952 (97.8%) with AIS class A transponders and 44 (2.2%) with class B transponders (Table 13 and Table 14).  In total, on the 3 to 3 profile, 1996 unique ships of all types were registered on the measurement profile, including 1952 (97.8%) with AIS class A transponders and 44 (2.2%) with class B transponders (Table 13 and Table 14).

Quantitative Characteristics of Traffic
The analysis of AIS data with the use of the proprietary software shows that OWF Baltic II will be located at a considerable distance from the lines of the main ship traffic flows, which minimizes its impact on the navigation course in the PMA and the South Baltic Sea (Figure 3). However, when considering a large sea area around an OWF, three main streams of ship traffic can be distinguished, as follows ( Figure 8 For the safety of navigation, most important are the customary routes E and D, which are approximately 2-3 nautical miles away. Ship traffic on both these routes can be considered low compared to route I. Only 433 and 232 unique vessels exceeded the measurement profiles 1-1 and 2-2 in 2017. The maximum traffic intensity measured on both profiles in the 2" mesh areas of GRID was only 90 (profile 1-1) and 20 (profile 2-2) vessels in 2017.
In the OWF area alone (in a small area of analysis; Figure 8), there were 794 vessels in 2016 and 930 in 2017. The maximum traffic intensity in the main OWF axes (AA and BB measurement profiles Figure 9) amounted to approximately 18 vessels in 2017 (measured on both profiles in the areas of 2" GRID meshes). These results give the basis for the conclusion that the numbers and intensity of vessel traffic in the OWF Baltic II region are low, even compared to the adjacent waters, including those located on the eastern side and selected for offshore wind farms.

Quantitative Characteristics of Traffic
The analysis of AIS data with the use of the proprietary software shows that OWF Baltic II will be located at a considerable distance from the lines of the main ship traffic flows, which minimizes its impact on the navigation course in the PMA and the South Baltic Sea (Figure 3). However, when considering a large sea area around an OWF, three main streams of ship traffic can be distinguished, as follows ( Figure 8 For the safety of navigation, most important are the customary routes E and D, which are approximately 2-3 nautical miles away. Ship traffic on both these routes can be considered low compared to route I. Only 433 and 232 unique vessels exceeded the measurement profiles 1-1 and 2-2 in 2017. The maximum traffic intensity measured on both profiles in the 2" mesh areas of GRID was only 90 (profile 1-1) and 20 (profile 2-2) vessels in 2017.
In the OWF area alone (in a small area of analysis; Figure 8), there were 794 vessels in 2016 and 930 in 2017. The maximum traffic intensity in the main OWF axes (AA and BB measurement profiles Figure 9) amounted to approximately 18 vessels in 2017 (measured on both profiles in the areas of 2" GRID meshes). These results give the basis for the conclusion that the numbers and intensity of vessel traffic in the OWF Baltic II region are low, even compared to the adjacent waters, including those located on the eastern side and selected for offshore wind farms. The analysis of AIS data with the use of the proprietary software shows that OWF Baltic II will be located at a considerable distance from the lines of the main ship traffic flows, which minimizes its impact on the navigation course in the PMA and the South Baltic Sea. However, when considering a large sea area around an OWF, three main streams of ship traffic can be distinguished, as follows ( Figure 8 For the safety of navigation, most important are the customary routes E and D, which are approximately 2-3 nautical miles away. Ship traffic on both these routes can be considered low compared to route I. Only 433 and 232 unique vessels exceeded the measurement profiles 1-1 and 2-2 in 2017. The maximum traffic intensity measured on both profiles in the 2" mesh areas of GRID was only 90 (profile 1-1) and 20 (profile 2-2) vessels in 2017.
In the OWF area alone (in a small area of analysis; Figure 8), there were 794 vessels in 2016 and 930 in 2017. The maximum traffic intensity in the main OWF axes (AA and BB measurement profiles Figure 9) amounted to approximately 18 vessels in 2017 (measured on both profiles in the areas of 2" GRID meshes). These results give the basis for the conclusion that the numbers and intensity of vessel traffic in the OWF Baltic II region are low, even compared to the adjacent waters, including those located on the eastern side and selected for offshore wind farms.

Qualitative Characteristics of Traffic
When analyzing the movement of ships in the large body of water presented in Figure 4, it is clearly visible that cargo ships are dominant. Out of the total number of 3861 registered vessels of all types, there were as many as 2164 (56%) unique types. Ships with a draft of Energies 2021, 14, 6559 21 of 23 4-6 m (31%) and a length of 100-200 m (49%) prevailed. The vast majority of ships of this type use the "Ławica Słupska" Ship Traffic Separation System, so the planned OWF does not have a significant impact on their navigation (mainly due to their distance of about 11 Nm from the OWF).
Fishing vessels constitute the next group in terms of numbers (237). Their movement is concentrated in the area of Rynna Słupska and their approach tracks to the ports of Ustka and Łeba ( Figure 5). Vessels with a draft of 2-6 m (53%) and with a length of less than 50 m (84%) prevail. The movement of these ships in the area of the planned OWF can be considered low.
In total, 113 passenger vessels form another group. The greatest intensity of this type of vessel occurs on the Gdynia-Karlskrona route. Passenger and cargo ferries run regularly throughout the year. Most of them are vessels with a draft in the range of 4-8 m (66%) and a length of 100-200 m (52%). Vessels of this type pass the OWF on the south side, but at a distance greater than 2 Nm.
In the small scope of analysis covered by the OWF (Figure 8), there were 764 vessels in 2016 and 930 in 2017 (according to data authorized by the Maritime Office in Gdynia). In 2016, cargo vessels accounted for the largest share of 324 (40.9%), followed by vessels engaged in fishing, at 245 (30.9%), and finally there were 55 (7.3%) vessels with a navigational status as sailing.
It should be noted that the slightly higher number of cargo ships results from the fact that fragments of the E and D routes were included in the analyzed area. In 2017, 433 unique ships used route E (cargo 77.6%, tankers 12.7%, fishing 6.9%, passenger 1.8%, other 1.0%), and D route was used by 232 unique ships (cargo 60.3%, tankers 17.7%, fishing 13.4%, passenger 3.4%, other 5.2%). The vast majority of ships with a draft of 2-6 m (56%) and lengths between 200 and 300 m (39%) navigated along the E route. On the other hand, the ships traveling along the D route had a draft above 4 m (65%) and a length of more than 100 m (89%). The results from a small area covering the OWF region and the 1-1 and 2-2 measurement profiles are consistent with those from a previous analysis covering the central PMA coast. Both, however, prove that the planned Baltic II wind farm together with the accompanying infrastructure will not have a significant impact on the safety of ships in Polish Maritime Areas, or on the efficiency of their navigation, taking into account the existing shipping routes and traffic separation schemes.

Conclusions
The obtained research results confirm the hypothesis that it is possible to use historical AIS data during the implementation of the spatial planning process aimed at optimizing the location of marine renewable energy installations. After their appropriate processing, it is possible to obtain a description of vessel traffic in the form of quantitative characteristics, based on traffic intensity distributions, and qualitative characteristics, based on statistics broken down by ship type, draft, and length. These characteristics may, in turn, constitute a secondary source of information used to identify vessels sailing in the studied area. Thus, they can be used to determine the course of customary routes, the intensity of traffic, or the number of ships staying in a given water area in a given period of time.
The advantages of the proposed solution are as follows: the possibility of using the most reliable and qualitatively superior static and dynamic data regarding ships in the AIS for ship traffic analysis; -the automation of the process of developing quantitative and qualitative characteristics for any sea area and time period (including those obtained from satellite AIS); -the possibility of creating the course lines of customary shipping routes without the need to use marine navigation charts and nautical publications (e.g., with the division of ships into types, or with a specific draft or length).
The proposed methodology is used to obtain new information on shipping and the marine environment, supporting decision-making related to the planning of OWF locations. This is included in maps made up of three layers, i.e., ship streams generated on the basis of adequately processed AIS data, the boundary of the planned OWF area with buffers, and electronic navigational charts and statistical data specified for the various vessel types, draft and lengths. However, it should be emphasized that the final decision on the location of the OWF is made in an arbitrary manner. On the other hand, a comparison of the juxtaposed information obtained before and after building the OWF allows for only a final assessment of its impact on shipping.
The proposed solution is the effect of preliminary research, but based on the results, it can be concluded that this research is worth continuing, although it should be taken into account that the application of the proposed solution requires the collection and processing of very large AIS data sets. Therefore, future research could be focused on increasing the computational efficiency of the data processing process.