Computing and visualizing method of fishing boat number grading statistics and fishing boat trajectory density statistics based on Beidou positioning and grid coding
Based on Beidou positioning and grid coding, geographical coding and grading statistics of the Beidou ship's position data of the fishing boat solved the problem of low efficiency of fishing boat data processing and analysis in existing technologies, and achieved efficient number of fishing boats and trajectory statistics and trajectory statistics and trajectory statistics and trajectory statistics and trajectory statistics. Visual analysis, support refined fishery resource management and marine monitoring.
Patent Information
- Application Number
- CN202411000395.5
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-07-25
- Publication Date
- 2025-01-28
Smart Images
Figure SMS_1 
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Abstract
Description
Technical Field
[0001] The present invention relates to the fields of fishery management, Beidou navigation and positioning application, spatial analysis and geographic information system application, and in particular to a calculation and visualization method for fishing vessel quantity classification statistics and fishing vessel track density statistics based on Beidou positioning and grid coding. Background Art
[0002] my country's fishing areas are divided with a fixed spatial resolution and numbered in order from north to south and from west to east. The existing division and numbering of my country's fishing areas has a weak direct correspondence with geographic space, which is not conducive to the implementation of more refined management of marine fisheries based on geospatial grids.
[0003] With the rapid development of global fisheries, the increase in the number of fishing vessels and the frequency of fishing activities have brought huge challenges to the management of marine environment and fishery resources. In order to effectively manage and monitor fishery activities and ensure the sustainable development of marine ecological environment and fishery resources, the number statistics and trajectory analysis of fishing vessels are particularly important. In recent years, with the popularization of the application of navigation satellite positioning systems, especially the popularization of the Beidou satellite positioning and navigation system with independent intellectual property rights in my country's fishing terminals, the acquisition of fishing vessel positioning data has become more convenient and accurate. However, how to efficiently process and analyze a large amount of Beidou ship position data is still a technical problem that needs to be solved urgently.
[0004] The present invention proposes an analysis method for the hierarchical statistics of the number of fishing vessels and the density of fishing vessel trajectories based on navigation satellite positioning and grid coding. By finely dividing the fishing area into grids and performing geographic coding, efficient statistics and visual analysis of the number and trajectories of fishing vessels are achieved, providing powerful data support and technical guarantee for fishery resource management and fishery law enforcement. Summary of the invention
[0005] The technical problem to be solved by the present invention is to provide a method for calculating and visualizing the hierarchical statistics of the number of fishing vessels and the density of fishing vessel tracks based on Beidou positioning and grid coding. By geocoding the Beidou position data of fishing vessels, the number of fishing vessels and the density of fishing vessel tracks in different accuracy ranges can be efficiently and quickly hierarchically counted and calculated, and a visual display can be given.
[0006] The technical solution adopted by the present invention to solve the technical problem is: to provide a calculation and visualization method for the classification statistics of the number of fishing vessels and the density statistics of fishing vessel tracks based on Beidou positioning and grid coding, which specifically includes the following steps:
[0007] (1) The area covering the Chinese fishing area is divided into different levels and geocoded, with the division accuracy reaching 0.5°×0.5°, 10′×10′, 5′×5′, 1′×1′ and 0.5′×0.5′. Different geocoding character lengths represent different accuracy ranges, and the grid lines after division are completely matched with the longitude and latitude lines;
[0008] (2) Encode the acquired Beidou positioning ship position data according to its longitude and latitude with the highest accuracy, and write the encoding result as a newly added position code column into each ship position data;
[0009] (3) According to the accuracy requirement of hierarchical statistics, the Beidou ship position data position code column obtained in step (2) is truncated to a position code string of corresponding length, and then the truncated position code string is efficiently grouped and aggregated according to the unique value, and the number of fishing vessels with different ship names in each position code string unique value group is grouped and counted, and a statistical table containing a position code string unique value column and a fishing vessel number column is generated;
[0010] (4) For the fishing boat trajectories, the Beidou ship position data is efficiently grouped and aggregated according to the fishing boat name. For the position code of each fishing boat, only the unique value of the position code is retained to obtain the non-repetitive trajectory code of a single fishing boat. The unique values of the position codes of all fishing boats are counted to obtain the fishing boat trajectory code statistics table;
[0011] (5) To facilitate the visualization of the geographic information system, multiple grid surface vector files with different spatial resolutions corresponding to different levels of coding precision are created, the longitude and latitude of the grid center point are coded at different levels of precision, and coding characters with corresponding precision length are assigned to each grid;
[0012] (6) According to the accuracy requirements of hierarchical statistics, the grid surface vector file of corresponding accuracy is associated with the fishing vessel quantity statistical table according to the coding field of corresponding accuracy, and the distribution density map of fishing vessels at different statistical levels is drawn;
[0013] (7) The grid surface vector file with the highest spatial resolution accuracy and the fishing vessel trajectory coding statistical table are associated through the position coding column to draw a fishing vessel trajectory density map.
[0014] Preferably, the grid coding rule in step (1) is to geocode the longitude and latitude range of 105°~169°E, 0°~64°N, which is divided 11 times in total, and the longitude and latitude range is divided by a combination of binary and multi-division.
[0015] Preferably, the different accuracy ranges in step (1) are: 32°×32°, 16°×16°, 8°×8°, 4°×4°, 2°×2°, 1°×1°, 0.5°×0.5°, 10′×10′, 5′×5′, 1′×1′ and 0.5′×0.5′.
[0016] Preferably, the first to seventh subdivisions adopt the binary method, that is, the grid code to the east of the bisecting line in the longitude direction is 1, and the grid code to the west is 0, the grid code to the north of the bisecting line in the latitude direction is 1, and the grid code to the south of the bisecting line is 0, and the longitude and latitude are binary coded, and the digits of the longitude and latitude binary codes are cross-combined and converted into one-dimensional binary codes in the order of longitude first and latitude later, generating 14-bit binary codes, and performing 2 2 Bit character code, binary 00, 01, 10, 11 correspond to the character codes 'A', 'B', 'C', 'D' respectively. After conversion, the character code is added to the encoding result. The accuracy after 7 subdivisions is 0.5°×0.5°, that is, 30′×30′, and the code length is 7 bits;
[0017] The eighth subdivision adopts the three-part method to divide 0.5°×0.5° into a 3×3 grid. The encoding method is column-first and row-later. The column and row numbers start from 1 and are added to the end of the encoding result. The accuracy after 8 subdivisions is 10′×10′, and the encoding length is 9 bits.
[0018] The 9th subdivision adopts the binary method to divide 10′×10′ into a grid with a precision of 5′×5′. Referring to the encoding method of the 1st to 7th subdivisions, the binary code is converted into characters and added to the end of the encoding result. The encoding length is 10 bits.
[0019] The 10th subdivision adopts the five-point method to divide the 5′×5′ grid into 5×5 grids with an accuracy of 1′×1′. The encoding adopts the encoding method of column first and then row. The column and row numbers start from 1 and are added to the end of the encoding result. The encoding length is 12 bits.
[0020] The 11th split adopts binary division to divide 1′×1′ into 0.5′×0.5′ with precision. Referring to the encoding method of the 1st to 7th splits, the binary code is converted into characters and added to the encoding result. The encoding length is 13 bits.
[0021] Preferably, the step (2) pre-processes the acquired ship position data, encodes all the Beidou ship position data of the fishing vessels according to the latitude and longitude of the fishing vessels with the highest accuracy of 0.5′×0.5′, forms a 13-bit geographic grid code, and writes the encoding result as a newly added position code column into each ship position data.
[0022] Preferably, in step (3), the prefix character codes of corresponding lengths are truncated for the code column of the Beidou ship position data according to different hierarchical statistical accuracies. For example, when statistics are performed according to the traditional fishing area size of 30′ 0.5°×0.5°, the prefix 7 bits of the grid code are truncated; when statistics are performed according to the statistical grid of 10′×10′, the prefix 9 bits are truncated; and when statistics are performed according to the statistical grid of 5′×5′, the prefix 10 bits are truncated.
[0023] Preferably, the step (3) converts the Beidou position data of all fishing vessels in the position database into monthly position data sets, that is, the statistical time is in months, and the intercepted position coding strings are efficiently grouped and aggregated according to unique values, the data processing efficiency is improved by vectorized operations, and the number of different ship names in each position coding string unique value group is grouped and counted, that is, the number of fishing vessels is counted with the ship name as the unique value, and a statistical table containing position coding string unique value columns and fishing vessel quantity columns with corresponding accuracy to the hierarchical statistics is generated.
[0024] Preferably, the step (4) converts the Beidou position data of all fishing vessels in the position database into monthly position data sets, that is, the statistical time is in months, and uses Python's pandas library to efficiently group and aggregate the monthly Beidou position data by fishing vessel name to improve data processing efficiency, encode the position of each fishing vessel with the highest accuracy, and the encoding length is 13 bits. Only unique codes are retained to obtain non-repetitive single-month trajectory codes of a single fishing vessel, and statistics are performed on the unique codes of all fishing vessels to obtain a statistical table of single-month trajectory codes of fishing vessels.
[0025] Preferably, the step (5) uses geographic information system software to create grid surface vector files with spatial resolutions of 0.5°×0.5°, 10′×10′, and 5′×5′, respectively, uses computational geometry functions to calculate the longitude and latitude of the center point of each grid, uses the calculated field function Python code to implement encoding according to the longitude and latitude of the center point of each grid, and assigns a code of corresponding precision length to each grid.
[0026] Preferably, the step (7) associates the grid surface vector file with the highest spatial resolution accuracy of 0.5′×0.5′ with the fishing vessel track coding statistical table through the position coding column to draw a fishing vessel track density map.
[0027] Beneficial effects:
[0028] The present invention adopts grid coding technology to hierarchically encode and process the fishing vessel position data, realizes the efficient organization and management of the ship position spatial data, and greatly improves the data processing efficiency. It supports grid division and hierarchical statistics of multiple precision levels, including 0.5°×0.5°, 10′×10′, 5′×5′, etc., to meet the statistical analysis needs of fishing vessels with different precisions; the single fishing vessel coding retains a unique coding to obtain the fishing vessel track coding, and the fishing vessel track density can be counted, and the fishing vessel number distribution density map and track density map can be drawn to intuitively display the spatial distribution of the number and track of fishing vessels, providing strong technical support for fishery resource management and marine monitoring. DETAILED DESCRIPTION
[0029] The following is a detailed description of an embodiment of the present invention: This embodiment is implemented on the premise of the technical solution of the present invention, and a detailed implementation method and a specific operation process are given, but the protection scope of the present invention is not limited to the following embodiments.
[0030] The embodiment of the present invention relates to a method for calculating and visualizing the hierarchical statistics of the number of fishing vessels and the density statistics of fishing vessel tracks based on Beidou positioning and grid coding, which specifically includes the following steps:
[0031] (1) The area containing the Chinese fishing area (105°~169°E, 0°~64°N) is divided into different levels and geocoded, with the division accuracy reaching 0.5°×0.5°, 10′×10′, 5′×5′, etc. Different geocoding character lengths represent different accuracy ranges, and the grid lines after division are completely matched with the longitude and latitude lines;
[0032] (2) Encode the acquired Beidou positioning ship position data according to its longitude and latitude with the highest accuracy, and write the encoding result as a newly added position code column at the end of each ship position data;
[0033] (3) According to the accuracy requirement of hierarchical statistics, the Beidou ship position data position code column obtained in the above step (2) is truncated to a position code string of corresponding length, and then the truncated position code string is efficiently grouped and aggregated according to the unique value, and the number of fishing vessels with different ship names (counted by the ship name as the unique value) in each position code string unique value group is grouped and counted to generate a statistical table containing a position code string unique value column and a fishing vessel number column;
[0034] (4) For the fishing boat trajectories, the Beidou ship position data is efficiently grouped and aggregated according to the fishing boat name. The position code of each fishing boat (with the highest accuracy and a code length of 13 bits) is retained to obtain the non-repetitive trajectory code of a single fishing boat. The unique values of the position codes of all fishing boats are counted to obtain a statistical table of fishing boat trajectory codes.
[0035] (5) To facilitate the visualization of the geographic information system, multiple grid surface vector files with different spatial resolutions corresponding to different levels of coding precision are created, the longitude and latitude of the grid center point are coded at different levels of precision, and coding characters with corresponding precision length are assigned to each grid;
[0036] (6) According to the accuracy requirements of hierarchical statistics, the grid surface vector file of corresponding accuracy is associated with the fishing vessel quantity statistical table according to the coding field of corresponding accuracy, and the distribution density map of fishing vessels at different statistical levels is drawn;
[0037] (7) The grid surface vector file with the highest spatial resolution accuracy (0.5′×0.5′) and the fishing vessel trajectory coding statistical table are associated through the position coding column to draw a fishing vessel trajectory density map.
[0038] 1. Regional Geocoding
[0039] The rule of grid coding in step (1) is to geocode the longitude and latitude range (105°~169°E, 0°~64°N), which is divided 11 times in total, and the longitude and latitude range is divided by a combination of binary and multi-division, and the Python code realizes the coding function;
[0040] The first to seventh subdivisions use the binary method, that is, the grid code to the east of the bisecting line in the longitude is 1, and the grid code to the west is 0. The grid code to the north of the bisecting line in the latitude is 1, and the grid code to the south of the bisecting line is 0. The longitude and latitude are binary coded in the order of longitude first and latitude later. The digits of the longitude and latitude binary codes are cross-combined and converted into one-dimensional binary codes to generate 14 binary bits. According to 2 2 Bit character code, binary 00, 01, 10, 11 correspond to the character codes 'A', 'B', 'C', 'D' respectively. After conversion, the character code is added to the encoding result. The accuracy after 7 subdivisions is 0.5°×0.5°, that is, 30′×30′, and the code length is 7 bits;
[0041] The eighth subdivision adopts the three-part method to divide 0.5°×0.5° into a 3×3 grid. The encoding method is column-first and row-later. The column and row numbers start from 1 and are added to the end of the encoding result. The accuracy after 8 subdivisions is 10′×10′, and the encoding length is 9 bits.
[0042] The 9th subdivision adopts the binary method to divide 10′×10′ into a grid with a precision of 5′×5′. Referring to the encoding method of the 1st to 7th subdivisions, the binary code is converted into characters and added to the end of the encoding result. The encoding length is 10 bits.
[0043] The 10th subdivision adopts the five-point method to divide the 5′×5′ grid into 5×5 grids with an accuracy of 1′×1′. The encoding adopts the encoding method of column first and then row. The column and row numbers start from 1 and are added to the end of the encoding result. The encoding length is 12 bits.
[0044] The 11th split adopts binary division to divide 1′×1′ into 0.5′×0.5′ with precision. Referring to the encoding method of the 1st to 7th splits, the binary code is converted into characters and added to the encoding result. The encoding length is 13 bits.
[0045] According to the above binary and multi-division combined coding rules, the code is written based on the Python programming language to implement the geographic grid coding of the area (105°~169°E, 0°~64°N). Different coding prefix lengths represent different precision ranges, taking the code ADBBADB21D24C as an example, as shown in Table 1.
[0046] Table 1 shows the geographic grid sizes corresponding to different levels and coding accuracy
[0047]
[0048]
[0049] 2. Coding of ship position data
[0050] The acquired Beidou positioning ship position data is encoded with the highest accuracy according to its longitude and latitude, and the encoding result is written into the end of each ship position data as a new position code column. Taking Ji Le Yu 02378 as an example, the encoding is shown in Table 2.
[0051] Table 2 is an example of the position coding of the ship position data of this embodiment - Ji Le Yu 02378 is taken as an example
[0052]
[0053] 3. Fishing vessel quantity classification statistics
[0054] The Beidou position data of all fishing vessels in the position database are converted into monthly position data sets, that is, the statistical time period is in months.
[0055] The prefix character codes of the corresponding lengths are truncated for the position code columns of the Beidou ship position data according to different hierarchical statistical accuracies. For example, the prefix is truncated to 7 bits for the statistical unit of 0.5°×0.5°, the prefix is truncated to 9 bits for the statistical unit of 10′×10′, and the prefix is truncated to 10 bits for the statistical unit of 5′×5′. The truncated position code strings are efficiently grouped and aggregated by unique values using Python's Pandas library. The number of fishing vessels with different ship names (counted by the unique value of the ship name) in each unique value group of the position code string is grouped and counted, and a statistical table containing the unique value column of the position code string and the number of fishing vessels column is generated. The hierarchical statistical results of the 0.5°×0.5° statistical unit are shown in Table 3, and the hierarchical statistical results of the 10′×10′ statistical unit are shown in Table 4.
[0056] Table 3 Schematic diagram of the statistical results of the classification with an accuracy of 30 points (0.5°×0.5°)
[0057]
[0058] Table 4 Schematic diagram of the statistical results of the classification with an accuracy of 10 points (10′×10′)
[0059]
[0060] Table 5 Schematic diagram of the statistical results of the classification of 5-point accuracy (5′×5′)
[0061]
[0062] 4. Fishing vessel track coding statistics
[0063] The Beidou position data of all fishing vessels in the position database are converted into monthly position data sets, that is, the statistical time period is in months.
[0064] The fishing vessel trajectory coding statistics use the most detailed coding, that is, the coding with an accuracy of 0.5′×0.5′ and a coding length of 13 bits. The Python pandas library is used to efficiently group and aggregate the monthly ship position data set by fishing vessel name to improve the calculation efficiency. A single fishing vessel only retains the unique code of a single month, and obtains the single-month trajectory code of a single fishing vessel without duplication. The unique codes of all fishing vessels are counted to obtain a single-month trajectory coding statistical table of fishing vessels containing code columns and quantity columns, as shown in Table 6.
[0065] Table 6 shows the density of fishing vessel tracks in January 2018
[0066] Grid center longitude Grid center latitude Grid corresponding code Track density in January 122.4791641 28.6541672 ADBBACB33D41C 60 122.4875031 28.6541672 ADBBACB33D51A 59 122.4958344 28.6541672 ADBBACB33D51C 77 122.5041656 28.6541672 ADBBACD13B11A 112 122.5124969 28.6541672 ADBBACD13B11C 82 122.5208359 28.6541672 ADBBACD13B21A 73 122.5291672 28.6541672 ADBBACD13B21C 96 122.5374985 28.6541672 ADBBACD13B31A 108 122.5458298 28.6541672 ADBBACD13B31C 104 122.5541687 28.6541672 ADBBACD13B41A 88 122.5625 28.6541672 ADBBACD13B41C 111 122.5708313 28.6541672 ADBBACD13B51A 107 122.5791702 28.6541672 ADBBACD13B51C 96 122.5875015 28.6541672 ADBBACD13D11A 81 122.5958328 28.6541672 ADBBACD13D11C 76 122.6041641 28.6541672 ADBBACD13D21A 95
[0067] 5. Create multiple grid surface vector files with different spatial resolutions and assign a code of corresponding length to each grid to facilitate spatial visualization and mapping of statistical results.
[0068] ArcGIS Pro was used to create grid surface vector files with precisions of 0.5°×0.5°, 10′×10′, and 5′×5′, respectively. The computational geometry function was used to obtain the longitude and latitude of the center point of each grid. The calculated field function Python code was used to encode the longitude and latitude of the center point of each grid. The encoding result was assigned to the encoding field, and each different grid was assigned a code with the corresponding precision length.
[0069] 6. Drawing of fishing vessel distribution density map
[0070] The grid surface vector files of corresponding precision and the statistical table of fishing vessel numbers were connected according to the coding fields, and ArcGIS Pro software was used to draw the density maps of fishing vessel numbers with precisions of 0.5°×0.5°, 10′×10′, and 5′×5′, respectively.
[0071] 7. Fishing boat track density map drawing
[0072] ArcGIS Pro software was used to create a grid surface vector file with an accuracy of 0.5′×0.5′ along the coast of Zhejiang Province and assign a corresponding code to each grid. The fishing vessel track coding statistical table was associated with the grid surface vector file through the coding field to draw a fishing vessel track density map.
[0073] The above shows and describes the basic principles and main features of the present invention and the advantages of the present invention. It should be understood by those skilled in the art that the present invention is not limited to the above embodiments. The above embodiments and descriptions are only for explaining the principles of the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, which fall within the scope of the present invention to be protected. The scope of protection of the present invention is defined by the attached claims and their equivalents.
Claims
1. A calculation and visualization method for the classification statistics of fishing boat numbers and the density statistics of fishing boat tracks based on Beidou positioning and grid coding, characterized in that: The specific steps include: (1) The area covering the Chinese fishing area is divided into different levels and geocoded, with the division accuracy reaching 0.5°×0.5°, 10′×10′, 5′×5′, 1′×1′ and 0.5′×0.5′. Different geocoding character lengths represent different accuracy ranges, and the grid lines after division are completely matched with the longitude and latitude lines; (2) Encode the acquired Beidou positioning ship position data according to its longitude and latitude with the highest accuracy, and write the encoding result as a newly added position code column into each ship position data; (3) According to the accuracy requirement of hierarchical statistics, the Beidou ship position data position code column obtained in step (2) is truncated to a position code string of corresponding length, and then the truncated position code string is efficiently grouped and aggregated according to the unique value, and the number of fishing vessels with different ship names in each position code string unique value group is grouped and counted, and a statistical table containing a position code string unique value column and a fishing vessel number column is generated; (4) For the fishing boat trajectories, the Beidou ship position data is efficiently grouped and aggregated according to the fishing boat name. For the position code of each fishing boat, only the unique value of the position code is retained to obtain the non-repetitive trajectory code of a single fishing boat. The unique values of the position codes of all fishing boats are counted to obtain the fishing boat trajectory code statistics table; (5) To facilitate the visualization of the geographic information system, multiple grid surface vector files with different spatial resolutions corresponding to different levels of coding precision are created, the longitude and latitude of the grid center point are coded at different levels of precision, and coding characters with corresponding precision length are assigned to each grid; (6) According to the accuracy requirements of hierarchical statistics, the grid surface vector file of corresponding accuracy is connected with the fishing vessel quantity statistical table according to the coding field of corresponding accuracy, and the distribution density map of fishing vessels at different statistical levels is drawn; (7) The grid surface vector file with the highest spatial resolution accuracy of 0.5′×0.5′ and the fishing vessel trajectory coding statistical table are associated through the position coding column to draw a fishing vessel trajectory density map.
2. The method for calculating and visualizing the number of fishing vessels and the density of fishing vessel tracks based on Beidou positioning and grid coding according to claim 1 is characterized in that: The rule of grid coding in the step (1) is to geocode the longitude and latitude range of 105°~169°E, 0°~64°N, which is divided 11 times in total, and the longitude and latitude range is divided by a combination of binary and multi-division, and the different accuracy ranges are: 32°×32°, 16°×16°, 8°×8°, 4°×4°, 2°×2°, 1°×1°, 0.5°×0.5°, 10′×10′, 5′×5′, 1′×1′ and 0.5′×0.5′.
3. The method for calculating and visualizing the number of fishing vessels and the density of fishing vessel tracks based on Beidou positioning and grid coding according to claim 1 is characterized in that: The different accuracy ranges in step (1) are: 32°×32°, 16°×16°, 8°×8°, 4°×4°, 2°×2°, 1°×1°, 0.5°×0.5°, 10′×10′, 5′×5′, 1′×1′ and 0.5′×0.5′.
4. The method for calculating and visualizing the number of fishing vessels and the density of fishing vessel tracks based on Beidou positioning and grid coding according to claim 2 is characterized in that: The first to seventh subdivisions use the binary method, that is, the grid code to the east of the bisecting line in the longitude is 1, and the grid code to the west is 0. The grid code to the north of the bisecting line in the latitude is 1, and the grid code to the south of the bisecting line is 0. The longitude and latitude are binary coded in the order of longitude first and latitude later. The digits of the longitude and latitude binary codes are cross-combined and converted into one-dimensional binary codes to generate 14 binary bits. According to 2 2 Bit character code, binary 00, 01, 10, 11 correspond to the character codes 'A', 'B', 'C', 'D' respectively. After conversion, the character code is added to the encoding result. The accuracy after 7 subdivisions is 0.5°×0.5°, that is, 30′×30′, and the code length is 7 bits; The eighth subdivision adopts the three-part method to divide 0.5°×0.5° into a 3×3 grid. The encoding method is column-first and row-later. The column and row numbers start from 1 and are added to the end of the encoding result. The accuracy after 8 subdivisions is 10′×10′, and the encoding length is 9 bits. The 9th subdivision adopts the binary method to divide 10′×10′ into a grid with a precision of 5′×5′. Referring to the encoding method of the 1st to 7th subdivisions, the binary code is converted into characters and added to the end of the encoding result. The encoding length is 10 bits. The 10th subdivision adopts the five-point method to divide the 5′×5′ grid into 5×5 grids with an accuracy of 1′×1′. The encoding adopts the encoding method of column first and then row. The column and row numbers start from 1 and are added to the end of the encoding result. The encoding length is 12 bits. The 11th split adopts binary division to divide 1′×1′ into 0.5′×0.5′ with precision. Referring to the encoding method of the 1st to 7th splits, the binary code is converted into characters and added to the encoding result. The encoding length is 13 bits.
5. The method for calculating and visualizing the number of fishing vessels and the density of fishing vessel tracks based on Beidou positioning and grid coding according to claim 1 is characterized in that: The step (2) pre-processes the acquired ship position data, encodes all the Beidou ship position data of the fishing vessels according to the latitude and longitude of the fishing vessels with the highest accuracy of 0.5′×0.5′, forms a 13-bit geographic grid code, and writes the encoding result as a newly added position code column at the end of each ship position data.
6. The method for calculating and visualizing the number of fishing vessels and the density of fishing vessel tracks based on Beidou positioning and grid coding according to claim 1 is characterized in that: The step (3) extracts prefix character codes of corresponding lengths from the code column of the Beidou ship position data according to different hierarchical statistical precisions. For example, when statistics are performed based on the traditional fishing area size of 30′ 0.5°×0.5°, the prefix 7 bits of the grid code are extracted; when statistics are performed based on the statistical grid of 10′×10′, the prefix 9 bits are extracted; and when statistics are performed based on the statistical grid of 5′×5′, the prefix 10 bits are extracted.
7. The method for calculating and visualizing the number of fishing vessels and the density of fishing vessel tracks based on Beidou positioning and grid coding according to claim 1 is characterized in that: The step (3) converts the Beidou ship position data of all fishing vessels in the ship position database into monthly ship position data sets, that is, the statistical time is in months, and the intercepted position code character strings are efficiently grouped and aggregated according to unique values, and the data processing efficiency is improved by vectorized operation, and the number of different ship names in each position code character string unique value group is grouped and counted, that is, the number of fishing vessels is counted by the ship name as the unique value, and a statistical table containing a position code character string unique value column and a fishing vessel number column with a precision corresponding to the hierarchical statistics is generated.
8. The method for calculating and visualizing the number of fishing vessels and the density of fishing vessel tracks based on Beidou positioning and grid coding according to claim 1 is characterized in that: The step (4) converts the Beidou ship position data of all fishing vessels in the ship position database into monthly ship position data sets, that is, the statistical time is in months, and the monthly Beidou ship position data is efficiently grouped and aggregated according to the fishing vessel name to improve data processing efficiency. The position of each fishing vessel is encoded with the highest accuracy, the encoding length is 13 bits, and only the unique code is retained to obtain the non-repetitive single-month trajectory code of a single fishing vessel, and the unique codes of all fishing vessels are counted to obtain a statistical table of the single-month trajectory codes of fishing vessels.
9. The method for calculating and visualizing the number of fishing vessels and the density of fishing vessel tracks based on Beidou positioning and grid coding according to claim 1, characterized in that: The step (5) uses geographic information system software to create grid surface vector files with spatial resolutions of 0.5°×0.5°, 10′×10′, and 5′×5′, respectively, and uses computational geometry functions to obtain the longitude and latitude of the center point of each grid. Each grid is encoded according to the longitude and latitude of the center point, and each grid is assigned a code with a corresponding precision length.
10. The method for calculating and visualizing the number of fishing vessels and the density of fishing vessel tracks based on Beidou positioning and grid coding according to claim 1, characterized in that: The maximum spatial resolution accuracy of step (7) is 0.5′×0.5′.