Supervision method and system for fishing operation behavior in marine ecological protection red line

Abstract

The invention provides a method and system for supervising fishing operation behaviors in a marine ecological protection red line, and the method comprises the steps: obtaining AIS data, and extracting key data from the AIS data; wherein the key data comprises MMSI, position, navigational speed, navigational direction and navigational time; sub-track segments are divided through MMSI; ship trajectory segmentation is carried out according to the sub-trajectory segments; based on ship trajectory segmentation, judging whether a fishing boat fishing behavior exists or not; if the fishing boat catching behavior exists, judging whether the period is a no-fishing period or not; if the ship is not in the no-fishing period, ship AIS data are fully utilized, an integrated judgment system of the track, the navigational speed, the navigational time and the like is established, under the navigational speed and navigational time limiting conditions, through track feature judgment based on a direction distribution algorithm, the ship with the marine trawl fishing behavior can be more accurately and rapidly positioned, and the positioning accuracy is improved. The efficiency of managing man-made activities on the sea in the marine ecological protection red line is improved, and functional departments can conveniently make management and control decisions in time.

Description

Technical Field

[0001] The present invention relates to the field of marine ecological environment technology, and in particular to a method and system for supervising fishing operations within the marine ecological protection red line. Background Art

[0002] The Automatic Identification System (AIS) is a shipborne broadcast response system that helps people understand the traffic conditions of ships in nearby waters. AIS data mainly includes ship dynamic information such as ship position, speed, and heading, as well as static attributes such as ship name, call sign, ship type, and captain entered by the crew, and ship identification information mainly based on the unique identification code MMSI.

[0003] The ship automatic identification system should maintain normal working condition to achieve collision avoidance between ships. The research on the maritime application of AIS data started late in China, mainly focusing on ship collision avoidance and submarine cable management. The analysis of ship samples is relatively rare, and the more mature ones are mainly focused on the judgment of fishing trajectories.

[0004] According to AIS data, the ship's trajectory and activity level are identified, the type and behavior of fishing vessels are judged, and the activity patterns of ships are reflected. The main analysis methods are data fusion and empirical rules, statistical results and machine learning methods: 1) Directly identify the ship's navigation, stay, anchoring and fishing behaviors through the frequent mining method of AIS trajectory data, and analyze the trajectory characteristics of AIS data of different voyages of ships. Among them, the fishing behavior of fishing vessels is judged by the staggered trajectory; 2) Based on the spatiotemporal registration of radar data and AIS data, according to the stop of ship AIS data acquisition, that is, the ship's AIS equipment may be turned off, it is indirectly judged that the ship has illegal fishing behavior.

[0005] The judgment of fishing boat behavior requires matching with radar data analysis, and cannot be judged only by AIS data. Data processing becomes more difficult, and the model computing capability is required to be high, which makes it difficult to implement the business operation of marine ecological protection red line supervision. Second, there are limitations in the use of AIS data. The behavior of ships is judged only by single trajectory data or historical voyage data mining. The analysis and utilization of characteristic information such as the real-time speed and direction of ships is insufficient, and the judgment results are not timely. Summary of the invention

[0006] In view of this, the purpose of the present invention is to provide a supervision method and system for fishing operations within the marine ecological protection red line, and propose management rules for fishing operations within the red line from the perspective of time and space, which greatly improves the pertinence and applicability of identifying abnormal fishing behaviors at sea; makes full use of ship AIS data to establish an integrated identification system of trajectory, speed, and flight time. Under the conditions of speed and flight time restrictions, through the trajectory feature judgment based on the directional distribution algorithm, it is possible to more accurately and quickly locate the trawling fishing vessels at sea, thereby improving the management efficiency of human activities at sea within the marine ecological protection red line, and facilitating the functional departments to make timely management and control decisions.

[0007] In a first aspect, an embodiment of the present invention provides a method for supervising fishing operations within a marine ecological protection red line, the method comprising:

[0008] Acquire AIS data, and extract key data from the AIS data; wherein the key data includes MMSI, position, speed, heading and sailing time;

[0009] Dividing sub-trajectory segments by the MMSI;

[0010] Segmenting the ship trajectory according to the sub-trajectory segments;

[0011] Based on the ship trajectory segmentation, determining whether there is fishing behavior by a fishing vessel;

[0012] If the fishing behavior described above exists, determine whether it is a closed fishing season;

[0013] If it is not a closed fishing season, then if the fishing vessel is fishing in the core protection area, general control area of ​​the nature reserve and other species distribution areas within the marine ecological protection red line, the vessel identity information is output;

[0014] Among them, the distribution areas of other species include coral reefs, seagrass beds, seaweed fields, oyster reefs, and rare and endangered species.

[0015] Further, based on the ship trajectory segmentation, judging whether there is fishing behavior of a fishing vessel includes:

[0016] During the detection cycle, the target tracks and speeds of all fishing vessels in the detection area are traversed;

[0017] Tracing the continuous trajectory of the target within one detection cycle time according to the target trajectory of all the fishing vessels;

[0018] When the speed and the sailing time are within the set range and the continuous trajectories are in the form of cross-overlapping, the fishing behavior of the fishing boat exists.

[0019] Furthermore, the judgment of cross-overlap is achieved in the following way:

[0020] Obtaining timestamps and geographic coordinates of trajectory points from the continuous trajectory;

[0021] Calculating the ship track direction distribution according to the timestamp of the track point and the geographic coordinates;

[0022] Calculating the position rotation angle according to the ship track direction distribution;

[0023] Calculate the standard deviation of the x-axis and the standard deviation of the y-axis according to the position rotation angle;

[0024] Calculating a ratio according to the standard deviation of the x-axis and the standard deviation of the y-axis;

[0025] When the ratio is within a first preset threshold range, there is a cross-overlap.

[0026] Further, dividing the sub-trace segments by the MMSI includes:

[0027] Intercept any area within the marine ecological protection red line and mark the area as the target waters;

[0028] If a plurality of points in the track appear continuously in the target water area, the track is marked as target water area data;

[0029] Obtain all tracks passing through the target water area;

[0030] Counting the number of track points in each track passing through the target water area;

[0031] When the number of trajectory points is less than a first value, the current trajectory is removed;

[0032] When the number of the trajectory points is greater than the first value, the navigation time is greater than the second value, and the navigation speed is within a second preset threshold range, the MMSI is divided into the sub-trajectory segments.

[0033] Further, based on the ship trajectory segmentation, judging whether there is fishing behavior of a fishing vessel includes:

[0034] Build a big data computing and storage framework;

[0035] Taking the key data as input parameter;

[0036] According to the predefined anomaly rules, multiple types of anomaly features are detected concurrently by using threshold comparison, spatial operation, feature matching and comparative analysis combined with multi-threading technology;

[0037] Determine the type of abnormal event based on the classification of abnormal trawling behavior;

[0038] Produce early warnings based on the abnormal event type and abnormal management requirements;

[0039] Outputting abnormal event detection results in an array format, wherein the abnormal event detection results include an ordered combination of current time, target location, target identifier, and abnormal event;

[0040] The presence of the fishing behavior by the fishing boat is determined based on the abnormal event detection result.

[0041] Further, calculating the position rotation angle according to the ship track direction distribution includes:

[0042] The position rotation angle is calculated according to the following formula:

[0043]

[0044] in, is the difference between the mean center and the x-coordinate, is the difference between the mean center and the y coordinate, θ is the position rotation angle, and the timestamp of the trajectory point is used as the element i of the sample, x i is the horizontal coordinate of the element i, y i is the ordinate of the element i.

[0045] Further, calculating the standard deviation of the x-axis and the standard deviation of the y-axis according to the position rotation angle includes:

[0046] The standard deviation of the x-axis and the standard deviation of the y-axis are calculated according to the following formula:

[0047]

[0048] Among them, σ x is the standard deviation of the x-axis, σ y is the standard deviation of the y-axis.

[0049] In a second aspect, an embodiment of the present invention provides a supervision system for fishing operations within the marine ecological protection red line, the system comprising:

[0050] An acquisition module, used to acquire AIS data and extract key data from the AIS data; wherein the key data includes MMSI, position, speed, heading and sailing time;

[0051] A division module, used for dividing sub-trace segments according to the MMSI;

[0052] A segmentation module, used for segmenting the ship track according to the sub-track segments;

[0053] A first judgment module is used to judge whether there is fishing behavior of a fishing vessel based on the ship trajectory segmentation;

[0054] The second judgment module is used to judge whether it is a fishing ban period when the fishing boat is fishing;

[0055] An output module is used to output the vessel identity information when the fishing vessel is fishing in the core protection area, general control area of ​​the nature reserve and other species distribution areas within the marine ecological protection red line when it is not a closed fishing period;

[0056] Among them, the distribution areas of other species include coral reefs, seagrass beds, seaweed fields, oyster reefs, and rare and endangered species.

[0057] In a third aspect, an embodiment of the present invention provides an electronic device, including a memory and a processor, wherein the memory stores a computer program executable on the processor, and the processor implements the method described above when executing the computer program.

[0058] In a fourth aspect, an embodiment of the present invention provides a computer-readable medium having a non-volatile program code executable by a processor, wherein the program code enables the processor to execute the method as described above.

[0059] The embodiment of the present invention provides a method and system for supervising fishing operations within the marine ecological protection red line, including: obtaining AIS data, extracting key data from the AIS data; wherein the key data includes MMSI, position, speed, heading and sailing time; dividing sub-trajectory segments by MMSI; segmenting the ship trajectory according to the sub-trajectory segments; judging whether there is fishing by fishing vessels based on the ship trajectory segmentation; if there is fishing by fishing vessels, judging whether it is a closed fishing period; if it is not a closed fishing period, judging whether there is fishing by fishing vessels in the core protection area, general control area of ​​the nature reserve and other species distribution areas within the marine ecological protection red line. The ship's identity information is output; among them, other species distribution areas include coral reefs, seagrass beds, seaweed fields, oyster reefs, rare and endangered species; from the perspective of time and space, the management rules of fishing behavior within the red line are proposed respectively, which greatly improves the pertinence and applicability of the identification of abnormal fishing behavior at sea; make full use of the ship's AIS data, establish an integrated discrimination system of trajectory, speed, and sailing time, and under the conditions of speed and sailing time restrictions, through the trajectory feature judgment based on the direction distribution algorithm, it can more accurately and quickly locate the trawling fishing vessels at sea, improve the management efficiency of human activities at sea within the marine ecological protection red line, and facilitate the functional departments to make timely management and control decisions.

[0060] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or understood by practicing the present invention. The purpose and other advantages of the present invention are realized and obtained by the structures particularly pointed out in the description, claims and drawings.

[0061] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, preferred embodiments are given below and described in detail with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0062] In order to more clearly illustrate the specific implementation methods of the present invention or the technical solutions in the prior art, the drawings required for use in the specific implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some implementation methods of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0063] Figure 1 A flow chart of a method for supervising fishing operations within the marine ecological protection red line provided in Example 1 of the present invention;

[0064] Figure 2 A schematic diagram of fishing boat trajectory characteristics provided in Example 1 of the present invention;

[0065] Figure 3 A schematic diagram of the location of a suspicious vessel provided in the first embodiment of the present invention;

[0066] Figure 4 A schematic diagram of the trajectory of a suspicious vessel provided in the first embodiment of the present invention;

[0067] Figure 5 Schematic diagram of the supervision system for fishing operations within the marine ecological protection red line provided in Example 2 of the present invention. DETAILED DESCRIPTION

[0068] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the accompanying drawings. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0069] This application implements the ecological protection red line system. Effective red line supervision measures are critical to protecting important marine ecosystems within the red line. Sea trawling is one of the important factors affecting the habitat of marine organisms. Through the collection and analysis of relevant technical documents, a method for determining sea trawling behavior based on AIS data within the marine ecological protection red line has not yet been formed.

[0070] This method is suitable for the identification of trawling fishing behavior at sea and within the marine ecological protection red line. It mainly uses the statistical discrimination of ship AIS data, combined with the analysis of basic knowledge of trawling fishing behavior, to explore the behavioral characteristics of trawling fishing vessels, combined with the control requirements of various types of marine ecological protection red lines, and provides a supervision method and system for fishing operations within the marine ecological protection red line.

[0071] To facilitate understanding of this embodiment, the embodiment of the present invention is described in detail below.

[0072] Embodiment 1:

[0073] Figure 1 A flow chart of a method for supervising fishing operations within the marine ecological protection red line provided in Example 1 of the present invention.

[0074] Reference Figure 1 , the method comprises the following steps:

[0075] Step S101, obtaining AIS data, and extracting key data from the AIS data; wherein the key data includes MMSI, position, speed, heading and sailing time;

[0076] Here, key data also includes longitude and latitude, ship type, and signal reception time, etc. First, quality control is performed on AIS data, incomplete and unreasonable data records are deleted, and MMSI (Maritime Mobile Service Identify) is extracted.

[0077] Step S102, dividing the sub-trajectory segments by MMSI;

[0078] Step S103, segmenting the ship trajectory according to the sub-trajectory segments;

[0079] Step S104, based on the ship trajectory segmentation, determine whether there is fishing behavior of a fishing boat; if there is fishing behavior of a fishing boat, execute step S105; if there is no fishing behavior of a fishing boat, end the process;

[0080] Step S105, determining whether it is a closed fishing season; if it is not a closed fishing season, executing step S106; if it is a closed fishing season, executing step S107;

[0081] Step S106, outputting the vessel identity information when there is fishing activity in the core protection area, general control area of ​​the nature reserve and other species distribution areas within the marine ecological protection red line; other species distribution areas include coral reefs, seagrass beds, seaweed beds, oyster reefs, rare and endangered species;

[0082] Step S107, directly output the ship identity information.

[0083] Specifically, based on the characteristics of fishing behavior of fishing vessels, trawling fishing behavior within the marine ecological protection red line is identified, mainly through the ship identity information, combined with the location, speed, heading, time and other information provided in the AIS data, to identify abnormal fishing vessel behavior within the marine ecological protection red line, that is, the fishing behavior of the ship at a certain time or area does not comply with navigation laws or management regulations. For example, according to relevant regulations, it is prohibited to engage in fishing activities during the closed fishing season, closed fishing areas, and nature reserves.

[0084] The ecological protection red line refers to areas within the ecological space that have special and important ecological functions and require mandatory and strict protection. It is the bottom line and lifeline for ensuring and maintaining national ecological security.

[0085] The marine ecological protection red line mainly includes mangroves, coral reefs, seagrass beds, coastal salt marshes, important estuaries, important tidal flats and shallow waters, distribution areas of rare and endangered species, and spawning grounds of important fishery resources. According to the red line management requirements, human development and utilization activities are not allowed in the red line core protection areas, and only limited human activities that do not cause damage to ecological functions are allowed in other areas.

[0086] Based on the impact of trawling activities on protected objects within the red line, combined with relevant regulations on national fishery fishing and marine ecological protection red line management, rules for trawling within the marine ecological protection red line are formulated in terms of time and space:

[0087] 1. Time rules: Vessels are prohibited from trawling within the red line during the fishing ban period.

[0088] 2. Spatial rules outside the closed fishing season:

[0089] 1) Vessels are prohibited from conducting trawling in the red line core protection area and the general control area of ​​the nature reserve;

[0090] 2) Trawling is prohibited in coral reefs, seagrass beds, kelp fields, oyster reefs, and areas where rare and endangered species are distributed.

[0091] If there is any spatial overlap among the above red line areas, control will be implemented according to the area with a larger distribution range.

[0092] Further, step S104 includes the following steps:

[0093] Step S201, traversing the target tracks and speeds of all fishing boats in the detection area within the detection cycle time;

[0094] Step S202, tracing back the continuous trajectory of the target within a detection cycle time according to the target trajectory of all fishing boats;

[0095] Step S203: When the speed and the sailing time are within the set range and the continuous tracks are in the form of cross-overlapping, there is fishing behavior by the fishing boat.

[0096] Specifically, the purpose of anomaly detection of marine trawling behavior is mainly to detect the abnormal information hidden in the target data through computer means, so as to provide decision-making basis for management departments at all levels of marine ecological protection red lines.

[0097] This application mainly combines data and knowledge-driven, integrates field background knowledge and literature research knowledge to identify and classify abnormal behaviors of maritime targets, and on this basis matches the maritime target perception data with predefined rules to identify targets with abnormal behaviors.

[0098] During the detection cycle, the target tracks and speeds of all fishing boats in the detection area are traversed; the continuous track of the target within a detection cycle is traced back. When the speed and sailing time are within the set range, and the continuous track forms cross-overlap, it is determined that there is fishing behavior. Figure 2 ,In the fishing vessel trajectory features, the sequence of serial numbers represents the ,time order.

[0099] Furthermore, the judgment of cross-overlap is achieved in the following way:

[0100] Step S301, obtaining the timestamp and geographic coordinates of the trajectory points from the continuous trajectory;

[0101] Step S302, calculating the ship track direction distribution according to the timestamp and geographic coordinates of the track points;

[0102] Step S303, calculating the position rotation angle according to the ship track direction distribution;

[0103] Step S304, calculating the standard deviation of the x-axis and the standard deviation of the y-axis according to the position rotation angle;

[0104] Step S305, calculating a ratio according to the standard deviation of the x-axis and the standard deviation of the y-axis;

[0105] Step S306: When the ratio is within a first preset threshold range, there is cross-overlap.

[0106] Specifically, in order to extract the shape features of the trajectory in the time and space dimensions, the timestamps and geographic coordinates of the trajectory points are used as input to calculate the spatial distribution of the ship's trajectory points, and whether the ship is performing an operation is determined based on the characteristics of the ship's trajectory.

[0107] The timestamp T of the track point is taken as the element i of the sample, and the geographic coordinates (longitude and latitude coordinates) are taken as the sample values ​​to calculate the direction distribution of the ship track, that is, the standard deviation ellipse form refers to formula (1):

[0108]

[0109] Among them, x i and i is the coordinate of feature i, is the mean center of the features, and n is equal to the total number of features.

[0110] Further, step S303 includes:

[0111] Calculate the position rotation angle according to formula (2):

[0112]

[0113] in, is the difference between the mean center and the x-coordinate, is the difference between the mean center and the y coordinate, θ is the position rotation angle, and the timestamp of the trajectory point is used as the element i of the sample, x i is the horizontal coordinate of feature i, y i is the ordinate of feature i.

[0114] Further, step S304 includes:

[0115] The standard deviation of the x-axis and the standard deviation of the y-axis are calculated according to formula (3):

[0116]

[0117] Among them, σ x is the standard deviation of the x-axis, σ y is the standard deviation of the y-axis.

[0118] When the standard deviation ellipse of the fishing boat trajectory distribution It can be preliminarily determined that the ship is carrying out trawling activities. The first preset threshold range may be (2.97, 10.91).

[0119] Further, step S102 includes the following steps:

[0120] Step S401, intercepting any area within the marine ecological protection red line and marking the area as a target water area;

[0121] Step S402, if multiple points in the trajectory appear continuously in the target water area, the trajectory is marked as target water area data;

[0122] Step S403, obtaining all trajectories passing through the target water area;

[0123] Step S404, counting the number of track points in each track passing through the target water area;

[0124] Step S405, when the number of trajectory points is less than the first value, the current trajectory is removed;

[0125] Step S406: when the number of trajectory points is greater than the first value, the navigation time is greater than the second value, and the navigation speed is within the second preset threshold range, the sub-trajectory segments are divided by MMSI.

[0126] Specifically, the acquired data is processed initially, including AIS data deduplication, dynamic and static data fusion, and data sorting. Incorrect data in the original data, such as field data range errors, format errors, track point data drift, speed changes, etc., are resolved and maintained, and target waters data are extracted. The processing flow is as follows:

[0127] Cut off any area from the marine ecological protection red line and mark the area as the target water area S; for the trajectory Tr = {p1, p2, ..., pn}, if some points in the trajectory appear continuously in the target area S, the trajectory Tr as a whole is marked as the target water area data; integrate all trajectories passing through the area S, and count the number of trajectory points in each trajectory respectively; when the number of trajectory points is less than the first value, it proves that the trajectory is not complete, and the current trajectory is eliminated.

[0128] The shape of the track generated by a normal ship navigation is relatively simple, with a more concentrated distribution of track points, while the fishing track often has more complex shape features. Therefore, the shape feature extraction is performed using the ship's navigation track and the fishing track, and the speed is within the second preset threshold range (set to 2kn to 6kn), the number of track points is screened (greater than the first value), and the sailing time is greater than the second value (set to 2 hours). The preliminarily processed sub-track segments based on the ship's MMSI number are divided to achieve ship track segmentation. Among them, the first value can be set to 5.

[0129] Further, step S104 includes the following steps:

[0130] Step S501, building a big data computing and storage framework;

[0131] Step S502, taking key data as input parameters;

[0132] Step S503, according to the predefined abnormal rules, using threshold comparison, spatial operation, feature matching and comparative analysis, and combining multi-threading technology to perform concurrent detection of multiple types of abnormal features;

[0133] Step S504, determining the type of abnormal event according to the classification of abnormal trawling behavior;

[0134] Here, based on the classification of abnormal trawling behavior, the abnormality of each type of abnormal event is determined and behavioral abnormalities are distinguished.

[0135] Step S505, issuing an early warning according to the abnormal event type and abnormal management requirements;

[0136] Step S506, outputting the abnormal event detection result in an array format, the abnormal event detection result including an ordered combination of the current time, the target location, the target identifier, and the abnormal event;

[0137] Step S507, determining the presence of fishing behavior by a fishing vessel based on the abnormal event detection result.

[0138] Specifically, the marine trawling identification model is aimed at real-time / quasi-real-time analysis scenarios of massive targets. Based on the big data computing and storage architecture, it uses a distributed real-time computing framework to stream marine fishing vessel data, detect predefined target abnormal events in real time, and store the abnormal information in the database in real time to support dynamic display and monitoring and early warning on the front-end interface.

[0139] In the process of building a big data computing and storage framework, a three-level storage architecture of real-time database, historical database and special database is adopted for the scenarios of real-time perception of abnormal fishing boat status and quasi-real-time perception of abnormal fishing behavior. The real-time database uses MySQL and Redis, the historical database uses HBase and Hive, and the special database uses MySQL.

[0140] Based on the big data storage and computing framework, event-level anomaly detection algorithm integration is carried out, and the data input and result output modules are integrated to form the overall process of the abnormal fishing behavior identification model at sea.

[0141] The main advantages of this application include: 1) It is the first time to propose a method for determining trawling behavior within the marine ecological protection red line, which can effectively support marine fishing and marine ecological protection management decisions. 2) The method is simple and easy to implement. By making full use of ship AIS data information, there is no need to increase the cost of marine monitoring equipment and manual patrols. The use of data and models can carry out automatic identification of marine trawling in real time, reducing the technical threshold and labor costs.

[0142] The application of the red line supervision of marine ecological protection in the distribution area of ​​rare and endangered species includes the following steps:

[0143] Step S601, carry out fishing vessel AIS data processing, extract the April fishing vessel AIS data of the marine ecological protection red line of the rare and endangered species distribution area of ​​Dalian spotted seal in Liaoning, perform quality control on the data, delete incomplete and unreasonable data records, and extract the MMSI code.

[0144] Step S602, abnormal behavior of fishing vessels is determined. According to the red line control requirements, in order to protect the habitat environment of rare and endangered species, fishing operations are prohibited within the red line of their distribution area, and the trawling behavior is determined based on the processed AIS data of fishing vessels.

[0145] According to the trawling behavior recognition model, based on the analysis of single-day data, the target trajectories, speeds (2kn to 6kn) and flight times (T ≥ 2 hours) of all fishing vessels in the detection area within T time were traversed, and three suspicious trawling vessels were screened out. The trajectory points and trajectory distribution are as follows: Figure 3 and Figure 4 shown.

[0146] Step S603, complete the red line supervision warning and processing according to the result of the judgment of the suspicious violation of the vessel within the red line.

[0147] Embodiment 2:

[0148] Figure 5 Schematic diagram of the supervision system for fishing operations within the marine ecological protection red line provided in Example 2 of the present invention.

[0149] Reference Figure 5 The system comprises:

[0150] The acquisition module is used to acquire AIS data and extract key data from the AIS data; wherein the key data includes MMSI, position, speed, heading and sailing time;

[0151] A division module, used for dividing sub-trajectory segments by MMSI;

[0152] A segmentation module, used for segmenting the ship trajectory according to the sub-trajectory segments;

[0153] The first judgment module is used to judge whether there is fishing behavior of a fishing vessel based on the segmentation of the ship trajectory;

[0154] The second judgment module is used to judge whether it is a closed fishing period when there is fishing behavior by fishing boats;

[0155] An output module is used to output the vessel identity information when fishing vessels are fishing in the core protection areas, general control areas of nature reserves and other species distribution areas within the marine ecological protection red line when it is not a closed fishing season;

[0156] Among them, other species distribution areas include coral reefs, seagrass beds, seaweed fields, oyster reefs, and rare and endangered species.

[0157] The beneficial effects of this application are:

[0158] 1) Division of management system. Based on the actual situation and combined with the actual needs of the management of fishing behavior within the red line of marine ecological protection, this application proposes management rules for fishing behavior within the red line from the perspective of time and space, which greatly improves the pertinence and applicability of the identification of abnormal fishing behavior at sea.

[0159] 2) Model algorithm construction. Starting from real-time and operability, this application makes full use of ship AIS data to establish an integrated identification system of trajectory, speed, and time. Under the conditions of speed and time restrictions, through trajectory feature determination based on the directional distribution algorithm, it can more accurately and quickly locate trawling vessels at sea, improve the efficiency of human activities management at sea within the marine ecological protection red line, and facilitate functional departments to make timely management and control decisions.

[0160] An embodiment of the present invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of the method for supervising fishing operations within the marine ecological protection red line provided in the above embodiment are implemented.

[0161] An embodiment of the present invention also provides a computer-readable medium having a non-volatile program code executable by a processor, on which a computer program is stored. When the computer program is executed by the processor, the steps of the method for supervising fishing operations within the marine ecological protection red line of the above embodiment are executed.

[0162] The computer program product provided in the embodiment of the present invention includes a computer-readable storage medium storing program code. The instructions included in the program code can be used to execute the method described in the previous method embodiment. The specific implementation can be found in the method embodiment and will not be repeated here.

[0163] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process of the system and device described above can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0164] In addition, in the description of the embodiments of the present invention, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0165] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc., which can store program codes.

[0166] In the description of the present invention, it should be noted that the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", etc., indicating the orientation or positional relationship, are based on the orientation or positional relationship shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, the terms "first", "second", and "third" are used for descriptive purposes only, and cannot be understood as indicating or implying relative importance.

[0167] Finally, it should be noted that the above-described embodiments are only specific implementations of the present invention, which are used to illustrate the technical solutions of the present invention, rather than to limit them. The protection scope of the present invention is not limited thereto. Although the present invention is described in detail with reference to the above-described embodiments, ordinary technicians in the field should understand that any technician familiar with the technical field can still modify the technical solutions recorded in the above-described embodiments within the technical scope disclosed by the present invention, or can easily think of changes, or make equivalent replacements for some of the technical features therein; and these modifications, changes or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention shall be based on the protection scope of the claims.

Claims

1. A method for supervising fishing operations within the marine ecological protection red line, characterized in that: The method comprises: Acquire AIS data, and extract key data from the AIS data; wherein the key data includes MMSI, position, speed, heading and sailing time; Dividing sub-trajectory segments by the MMSI; Segmenting the ship trajectory according to the sub-trajectory segments; Based on the ship trajectory segmentation, determining whether there is fishing behavior by a fishing vessel; If the fishing behavior described above exists, determine whether it is a closed fishing season; If it is not a closed fishing season, then if the fishing vessel is fishing in the core protection area, general control area of ​​the nature reserve and other species distribution areas within the marine ecological protection red line, the vessel identity information is output; Among them, the distribution areas of other species include coral reefs, seagrass beds, seaweed fields, oyster reefs, and rare and endangered species.

2. The method for supervising fishing operations within the marine ecological protection red line according to claim 1 is characterized in that: Based on the ship track segmentation, judging whether there is fishing behavior of the fishing vessel includes: During the detection cycle, the target tracks and speeds of all fishing vessels in the detection area are traversed; Tracing the continuous trajectory of the target within one detection cycle time according to the target trajectory of all the fishing vessels; When the speed and the sailing time are within the set range and the continuous trajectories are in the form of cross-overlapping, the fishing behavior of the fishing boat exists.

3. The method for supervising fishing operations within the marine ecological protection red line according to claim 2 is characterized in that: The judgment of cross-overlap is achieved in the following way: Obtaining timestamps and geographic coordinates of trajectory points from the continuous trajectory; Calculating the ship track direction distribution according to the timestamp of the track point and the geographic coordinates; Calculating the position rotation angle according to the ship track direction distribution; Calculate the standard deviation of the x-axis and the standard deviation of the y-axis according to the position rotation angle; Calculating a ratio according to the standard deviation of the x-axis and the standard deviation of the y-axis; When the ratio is within a first preset threshold range, there is a cross-overlap.

4. The method for supervising fishing operations within the marine ecological protection red line according to claim 1 is characterized in that: The sub-trajectory segments are divided by the MMSI, including: Intercept any area within the marine ecological protection red line and mark the area as the target waters; If a plurality of points in the track appear continuously in the target water area, the track is marked as target water area data; Obtain all tracks passing through the target water area; Counting the number of track points in each track passing through the target water area; When the number of trajectory points is less than a first value, the current trajectory is removed; When the number of the trajectory points is greater than the first value, the navigation time is greater than the second value, and the navigation speed is within a second preset threshold range, the MMSI is divided into the sub-trajectory segments.

5. The method for supervising fishing operations within the marine ecological protection red line according to claim 1 is characterized in that: Based on the ship track segmentation, judging whether there is fishing behavior of the fishing vessel includes: Build a big data computing and storage framework; Taking the key data as input parameter; According to the predefined anomaly rules, multiple types of anomaly features are detected concurrently by using threshold comparison, spatial operation, feature matching and comparative analysis combined with multi-threading technology; Determine the type of abnormal event based on the classification of abnormal trawling behavior; Produce early warnings based on the abnormal event type and abnormal management requirements; Outputting abnormal event detection results in an array format, wherein the abnormal event detection results include an ordered combination of current time, target location, target identifier, and abnormal event; The presence of the fishing behavior by the fishing boat is determined based on the abnormal event detection result.

6. The method for supervising fishing operations within the marine ecological protection red line according to claim 3 is characterized in that: Calculating the position rotation angle according to the ship track direction distribution includes: The position rotation angle is calculated according to the following formula: in, is the difference between the mean center and the x-coordinate, is the difference between the mean center and the y coordinate, θ is the position rotation angle, and the timestamp of the trajectory point is used as the element i of the sample, x i is the horizontal coordinate of the element i, y i is the ordinate of the element i.

7. The method for supervising fishing operations within the marine ecological protection red line according to claim 3 is characterized in that: Calculating the standard deviation of the x-axis and the standard deviation of the y-axis according to the position rotation angle includes: The standard deviation of the x-axis and the standard deviation of the y-axis are calculated according to the following formula: Among them, σ x is the standard deviation of the x-axis, σ y is the standard deviation of the y-axis.

8. A supervision system for fishing operations within the marine ecological protection red line, characterized in that: The system comprises: An acquisition module, used to acquire AIS data and extract key data from the AIS data; wherein the key data includes MMSI, position, speed, heading and sailing time; A division module, used for dividing sub-trace segments according to the MMSI; A segmentation module, used for segmenting the ship track according to the sub-track segments; A first judgment module is used to judge whether there is fishing behavior of a fishing vessel based on the ship trajectory segmentation; The second judgment module is used to judge whether it is a fishing ban period when the fishing boat is fishing; An output module is used to output the vessel identity information when the fishing vessel is fishing in the core protection area, general control area of ​​the nature reserve and other species distribution areas within the marine ecological protection red line when it is not a closed fishing period; Among them, the distribution areas of other species include coral reefs, seagrass beds, seaweed fields, oyster reefs, and rare and endangered species.

9. An electronic device comprising a memory and a processor, wherein the memory stores a computer program that can be run on the processor, wherein: When the processor executes the computer program, the method according to any one of claims 1 to 7 is implemented.

10. A computer readable medium having a non-volatile program code executable by a processor, characterized in that: The program code enables the processor to execute the method according to any one of claims 1 to 7.

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