A method for processing and analyzing marine ecological data on the impact of marine environment

Abstract

The present invention relates to the technical field of marine data processing, and in particular to a method for processing and analyzing marine ecological data of marine environment impact, comprising: step one, determining data collection points in a marine area based on historically collected data; step two, performing data analysis on the historically collected marine ecological data to determine a single interval, then calculating the environmental normal value of the marine ecological data according to the data frequency in the single interval, and then combining the real-time collected marine ecological data with the environmental normal value for calculation to obtain an ecological risk value of the data collection point; step three: determining an abnormal collection point and an edge collection point and the straight-line distance therebetween, and combining the calculation with the ecological risk value of the abnormal collection point to obtain a data priority value, arranging the data priority values ​​in position to obtain a priority sequence, and then processing the real-time collected marine ecological data according to the priority sequence, thereby improving the response efficiency of risk data and enhancing the overall risk prevention and control capability.

Description

Technical Field

[0001] The present invention relates to the technical field of marine data processing, and in particular to a method for processing and analyzing marine ecological data on the impact of marine environment. Background Art

[0002] The ocean is rich in resources. In today's tight energy supply, the rational development and utilization of marine resources is the key to solving resource scarcity. To achieve sustainable development of marine resources and marine ecological environment, it is necessary to accurately acquire and analyze massive monitoring data.

[0003] The prior art CN116298151A discloses a data processing method and device based on marine environment monitoring, including: obtaining multiple node data sets monitored by multiple sensors at different time nodes in a certain period of time and the time nodes corresponding to the node data sets, wherein each type of sensor has multiple; dividing the node data sets into multiple node category data sets according to the sensor type, and performing a first-level fusion on the multiple node category sub-data in each of the node category data sets to obtain a fusion value corresponding to each of the node category data sets; performing a second-level heterogeneous fusion according to the fusion value corresponding to each of the node category data sets to obtain a preliminary evaluation result corresponding to each of the node data sets; performing a third-level time node fusion according to each of the preliminary evaluation results to obtain a comprehensive evaluation result of the water quality of the monitored sea area in a certain period of time.

[0004] However, due to the large area of ​​the ocean and the large amount of data collected and processed, there will be hysteresis in the data processing process, which will lead to delayed response to marine ecological warnings, affect the optimal processing time, and further increase the risk of ocean pollution. Summary of the invention

[0005] The purpose of the present invention is to solve the problems in the background technology and to propose a method for processing and analyzing marine environment impact marine ecological data.

[0006] In order to achieve the above object, the present invention adopts the following technical solutions:

[0007] A method for processing and analyzing marine ecological data of marine environment impact, the method specifically comprises the following steps:

[0008] Step 1: Based on the geographic information of the ocean area, obtain the historical data collected per unit area and calculate the individual standard deviation. Based on the individual standard deviations of multiple unit areas, determine the overall standard deviation. Then combine the overall standard deviation with the expected error to determine the collection base area. Set data collection points according to the collection base area and collect marine ecological data.

[0009] Step 2: Obtain historically collected marine ecological data and arrange them in order to obtain a data sequence. Based on the two endpoint values ​​in the data sequence and the set unit data distance, determine multiple nodes, and determine the single interval according to the node order. Then classify the marine ecological data in the single interval, and calculate the data frequency of the single interval based on the marine ecological data in each single interval. Determine the environmental normal value based on the data frequency and the average value of the marine ecological data in the single interval. Then obtain the marine ecological data collected in real time at the data collection point, and combine it with the environmental normal value to determine the ecological risk value of each data collection point;

[0010] Step 3: Determine the abnormal collection point based on the ecological risk value, and determine the edge collection point according to the location of the abnormal collection point, obtain the straight-line distance between the abnormal collection point and the edge collection point, and determine the data priority value of the corresponding edge collection point in combination with the ecological risk value of the edge collection point. Then, the ecological risk values ​​of the abnormal collection point and the remaining data collection points are directly used as the data priority value to obtain the data priority value of the data collection point;

[0011] Step 4: Arrange the data priority values ​​of the data collection points from large to small to obtain the priority sequence of the data collection points. Then the Marine Information Center processes the real-time collected marine ecological data according to the priority sequence of the data collection points.

[0012] As a further solution of the present invention, a specific method for setting the data collection points includes:

[0013] S01: Set the unit area, and arbitrarily select a unit area as the target analysis area, and obtain the historical collection data LCi in the target analysis area, i is the data number of the historical collection data, and i∈[1,I], I represents the total amount of historical collection data obtained, where the unit area is the threshold;

[0014] S02: Calculate the mean of the historical collected data LCi and mark the mean calculation result as LCa. Get the standard deviation of the monomer ;

[0015] S03: Select N different unit area regions as target analysis regions, and process them according to the above steps S01 and S02 to obtain the monomer standard deviation of each unit area region. , n represents the number of different unit area areas, and n∈[1,N], then the mean of the N individual standard deviations is calculated, and the mean calculation result is marked as the overall standard deviation ;

[0016] S04: Using formula Get the minimum sample size b, is the confidence level, E is the expected error, The value is 1.96, and the E value is 5%;

[0017] S05: Divide the unit area by the minimum sample number b to obtain the collection base area. According to the collection base area, divide the unit collection area in the ocean plane image. At the same time, set the center point of each unit collection area as a data collection point, and collect marine ecological data through collection equipment.

[0018] As a further solution of the present invention, a method for setting a monomer interval includes:

[0019] The marine ecological data are arranged from small to large to obtain a data sequence, and then the two endpoint values ​​in the data sequence are taken and marked as DL and DR respectively, where DL represents the leftmost value in the data sequence, that is, the minimum value, and DR represents the rightmost value in the data sequence, that is, the maximum value;

[0020] Then obtain the unit data distance d, take DL as the initial data, take DL+d as the first node, take DL+2d as the second node, and so on, and get a total of K nodes, among which, the Kth node DL+Kd≥DR, and the unit data distance d is the threshold;

[0021] Taking the initial data DL as the starting point, the adjacent nodes are taken as endpoints in sequence according to the node order to obtain multiple monomer intervals. Specifically, the monomer intervals include [DL, DL+d), [DL+d, DL+2d), ..., [DL+(K-1)d, DL+Kd].

[0022] As a further solution of the present invention, a method for determining an ecological risk value includes:

[0023] S14: Classify the marine ecological data HY in the data sequence into monomer intervals. At this time, each monomer interval contains corresponding marine ecological data, using the formula The data frequency Fj is obtained, where j represents the interval number of the monomer interval, and j∈[1, K], Lj represents the number of marine ecological data in the monomer interval j, and ZL represents the total amount of data in the data sequence;

[0024] Then based on the formula The environmental conventional value HC is obtained, where Pj represents the average value of the marine ecological data existing in the monomer interval j;

[0025] S15: Obtain the marine ecological data of each data collection point, and arbitrarily select a data collection point as the target collection point, and extract the marine ecological data CD collected in real time at the target collection point, and then use the formula The ecological risk value XZ of the target collection point is obtained, where r1 is a fixed constant and 0<r1<1.

[0026] As a further solution of the present invention, after obtaining the historically collected marine ecological data, it is necessary to remove the obvious outliers in the historically collected marine ecological data to obtain the marine ecological data HY under normal conditions. The obvious outliers refer to data that is not within the standard data range of the marine ecological data.

[0027] As a further solution of the present invention, a method for calculating the data priority value includes:

[0028] SS1: Compare the ecological risk value XZ with the risk threshold. If the ecological risk value is greater than or equal to the risk threshold, obtain the corresponding data collection point and mark this data collection point as an abnormal collection point.

[0029] SS2: Obtain the location of the abnormal collection point in the ocean image, and based on the abnormal collection point, mark the data collection points adjacent to the abnormal collection point as edge collection points with the center of the abnormal collection point as the center of the abnormal collection point;

[0030] Get the straight-line distance from the abnormal collection point to the edge collection point and mark it as Dstr, and get the ecological risk value corresponding to the edge collection point , and based on the formula Get the data priority value YD of the edge acquisition point, where: represents the ecological risk value of the abnormal collection point, r2 represents the constant coefficient, and 0<r2<1, is the influence coefficient;

[0031] Afterwards, the ecological risk values ​​of the abnormal collection points and the remaining data collection points are directly used as data priority values, and then the data priority value of each data collection point is obtained.

[0032] As a further solution of the present invention, if the ecological risk values ​​of all data collection points are less than the risk threshold, the ecological risk value is directly used as the data priority value.

[0033] Compared with the prior art, the advantages of the present invention are:

[0034] The present invention obtains the environmental normal value of the marine ecological data by analyzing the marine ecological data collected historically, and then determines the ecological risk value of the data collection point based on the environmental normal value and the marine ecological data collected in real time, and then determines the abnormal collection point and the edge collection point according to the ecological risk value, and determines the data priority value of the edge collection point according to the straight-line distance between the abnormal collection point and the edge collection point, and then directly uses the ecological risk value of the abnormal collection point and the remaining data collection points as the data priority value, thereby obtaining the data priority value of each data collection point, and finally arranges the data priority values ​​of the data collection points in a descending order to obtain the priority sequence of the data collection points, and then processes the marine ecological data collected in real time according to the priority sequence, thereby improving the response efficiency of the risk data, helping to timely discover and solve potential problems, thereby enhancing the overall risk prevention and control capabilities, and further enhancing the system decision-making capabilities;

[0035] The present invention determines the minimum sample quantity per unit area by analyzing the individual standard deviation of historically collected data, and sets a collection base area based on the minimum sample quantity. Finally, data collection points are set in the ocean area according to the collection base area, and the data collection points are determined by the minimum sample quantity, thereby reasonably allocating resources, improving resource utilization efficiency, and ensuring the rationality of data collection. There will be no shortage of data due to too few collection points, and no waste of resources due to too many collection points. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 It is a schematic diagram of the method flow structure of the present invention. DETAILED DESCRIPTION

[0037] The technical solutions in the embodiments of the present invention will be described clearly and completely below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments.

[0038] Reference Figure 1 , a method for processing and analyzing marine ecological data of marine environment impact, the method specifically comprises the following steps:

[0039] Step 1: Collect geographic information of the ocean area and set data collection points for the ocean area based on the geographic information. The geographic information refers to ocean images collected by ocean remote sensing technology. The specific method of setting data collection points includes:

[0040] S01: Set a unit area, and arbitrarily select a unit area as the target analysis area, and obtain the historical collection data LCi in the target analysis area, where i is the data number of the historical collection data, and i∈[1, I], I represents the total amount of historical collection data obtained, wherein the unit area is a threshold, and the specific values ​​of the unit area and I are obtained by technicians in this field based on big data experience;

[0041] S02: Calculate the mean of the historical collected data LCi and mark the mean calculation result as LCa. Then use the formula Get the standard deviation of the monomer ;

[0042] S03: Select N different unit area regions as target analysis regions, and process them according to the above steps S01 and S02 to obtain the monomer standard deviation of each unit area region. , where n represents the number of different unit area regions, and n∈[1, N], then the mean of the N individual standard deviations is calculated, and the mean calculation result is marked as the overall standard deviation ;

[0043] S04: Using formula Get the minimum sample size b, where is the confidence level, E is the expected error, and the specific The values ​​of and E are obtained by those skilled in the art after big data calculation. In this embodiment, The value is 1.96, and the E value is 5%;

[0044] S05: Then, the unit area is divided by the minimum sample number b to obtain the collection base area. Then, the unit collection area is divided in the ocean plane image according to the collection base area. At the same time, the center point of each unit collection area is set as a data collection point, and the marine ecological data is collected through the collection equipment;

[0045] Step 2: Based on the data collection points, collect marine ecological data, including marine chemical data and marine physical data. Marine chemical data refers to data such as pH value, dissolved oxygen, active phosphorus and active silicate, and marine physical data refers to data such as water temperature and salinity. Then, determine the ecological risk value of each data collection point based on the collected marine ecological data. The specific methods for determining the ecological risk value include:

[0046] S11: Taking the current time as a reference, obtaining historically collected marine ecological data, and removing obvious outliers in the historically collected marine ecological data to obtain normal marine ecological data HY, wherein obvious outliers refer to data that is not within the standard data interval of the marine ecological data, and the specific standard data interval is set by technicians in this field based on big data experience;

[0047] S12: Then, the marine ecological data is arranged from small to large to obtain a data sequence, and then two endpoint values ​​in the data sequence are taken and marked as DL and DR respectively, where DL represents the leftmost value in the data sequence, that is, the minimum value, and DR represents the rightmost value in the data sequence, that is, the maximum value, and then the unit data distance d is obtained, DL is used as the initial data, DL+d is used as the first node, DL+2d is used as the second node, and so on, a total of K nodes are obtained. It should be further explained that the Kth node DL+Kd≥DR, the unit data distance d is the threshold, and the specific value is obtained by those skilled in the art based on big data experience;

[0048] S13: Taking the initial data DL as the starting point, according to the node order, the adjacent nodes are sequentially used as endpoints to obtain multiple monomer intervals. Specifically, the monomer intervals include [DL, DL+d), [DL+d, DL+2d), ..., [DL+(K-1)d, DL+Kd];

[0049] The above example illustrates that there is a data sequence with a minimum value of 5 and a maximum value of 10. The unit data distance d is 1. At this time, the initial data is 5, and the nodes include 6, 7, 8, 9, and 10. Then, starting from the initial data, the adjacent nodes are used as endpoints to obtain the monomer intervals [5, 6), [6, 7), [7, 8), [8, 9), [9, 10].

[0050] S14: Classify the marine ecological data HY in the data sequence into monomer intervals. At this time, each monomer interval contains corresponding marine ecological data. Then, the formula The data frequency Fj is obtained, where j represents the interval number of the monomer interval, and j∈[1, K], Lj represents the number of marine ecological data in the monomer interval j, and ZL represents the total amount of data in the data sequence;

[0051] Then based on the formula The environmental conventional value HC is obtained, where Pj represents the average value of the marine ecological data existing in the monomer interval j;

[0052] S15: Then obtain the marine ecological data of each data collection point, and arbitrarily select a data collection point as the target collection point, and extract the marine ecological data CD collected in real time at the target collection point, and then use the formula The ecological risk value XZ of the target collection point is obtained, where r1 is a fixed constant, and 0<r1<1, and the specific value of r1 is obtained by technicians in this field after big data calculation;

[0053] After that, the remaining data collection points are taken as target collection points in turn, and the ecological risk value is calculated. It should be further explained that the higher the ecological risk value, the greater the risk that the marine ecological data collected by the corresponding data collection point is abnormal data;

[0054] Step 3: Based on the ecological risk value of the data collection point, calculate the data priority value of the data collection point. The specific method for calculating the data priority value includes:

[0055] SS1: First, compare the ecological risk value XZ with the risk threshold. If the ecological risk values ​​of all data collection points are less than the risk threshold, the ecological risk value is directly used as the data priority value. If there is an ecological risk value greater than or equal to the risk threshold, obtain the corresponding data collection point and mark this data collection point as an abnormal collection point. The specific value of the risk threshold is obtained by technicians in this field after big data calculation.

[0056] SS2: After that, the position of the abnormal collection point is obtained in the ocean image, and based on the abnormal collection point, the data collection points adjacent to the abnormal collection point are marked as edge collection points with the center of the abnormal collection point as the center of the abnormal collection point;

[0057] Get the straight-line distance from the abnormal collection point to the edge collection point and mark it as Dstr, and get the ecological risk value corresponding to the edge collection point , and based on the formula Get the data priority value YD of the edge acquisition point, where: represents the ecological risk value of the abnormal collection point, r2 represents the constant coefficient, and 0<r2<1, is the influence coefficient, r2 and The specific values ​​of are obtained by technicians in this field after big data calculation;

[0058] Afterwards, the ecological risk values ​​of the abnormal data collection points and the remaining data collection points are directly used as data priority values, thereby obtaining the data priority value of each data collection point;

[0059] Step 4: Arrange the data priority values ​​of the data collection points from large to small to obtain the priority sequence of the data collection points. The Marine Information Center then processes the real-time collected marine ecological data according to the priority sequence of the data collection points, which helps to promptly discover and resolve potential problems, thereby enhancing the overall risk prevention and control capabilities.

[0060] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical scheme and inventive concept of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. A method for processing and analyzing marine ecological data of marine environment impact, characterized in that: The method specifically comprises the following steps: Step 1: Based on the geographic information of the ocean area, which refers to the ocean images collected by marine remote sensing technology, obtain the historical collection data of the unit area and calculate the individual standard deviation. Based on the individual standard deviations of multiple unit areas, determine the overall standard deviation, then combine the overall standard deviation with the expected error to determine the collection base area, set data collection points according to the collection base area, and collect marine ecological data. The method of setting data collection points includes: S01: Set the unit area, and arbitrarily select a unit area as the target analysis area, and obtain the historical collection data LCi in the target analysis area, i is the data number of the historical collection data, and i∈[1,I], I represents the total amount of historical collection data obtained, where the unit area is the threshold; S02: Calculate the mean of the historical collected data LCi and mark the mean calculation result as LCa. Get the standard deviation of the monomer ; S03: Select N different unit area regions as target analysis regions, and process them according to the above steps S01 and S02 to obtain the monomer standard deviation of each unit area region. , n represents the number of different unit area areas, and n∈[1,N], then the mean of the N individual standard deviations is calculated, and the mean calculation result is marked as the overall standard deviation ; S04: Using formula Get the minimum sample size b, is the confidence level, E is the expected error, The value is 1.96, and the E value is 5%; S05: Divide the unit area by the minimum sample number b to obtain the collection base area. According to the collection base area, divide the unit collection area in the ocean plane image, set the center point of each unit collection area as a data collection point, and collect marine ecological data through the collection equipment; Step 2: Obtain historically collected marine ecological data and arrange them in order to obtain a data sequence. Based on the two endpoint values ​​in the data sequence and the set unit data distance, determine multiple nodes, and determine the single interval according to the node order. Then classify the marine ecological data in the single interval, and calculate the data frequency of the single interval based on the marine ecological data in each single interval. Determine the environmental normal value based on the data frequency and the average value of the marine ecological data in the single interval. Then obtain the marine ecological data collected in real time at the data collection point, and combine it with the environmental normal value to determine the ecological risk value of each data collection point; Step 3: Determine the abnormal collection point based on the ecological risk value, and determine the edge collection point according to the location of the abnormal collection point, obtain the straight-line distance between the abnormal collection point and the edge collection point, and determine the data priority value of the corresponding edge collection point in combination with the ecological risk value of the edge collection point. Then, the ecological risk values ​​of the abnormal collection point and the remaining data collection points are directly used as the data priority value to obtain the data priority value of the data collection point. Specifically, the calculation method of the data priority value includes: SS1: Compare the ecological risk value XZ with the risk threshold. If the ecological risk value is greater than or equal to the risk threshold, obtain the corresponding data collection point and mark this data collection point as an abnormal collection point. SS2: Obtain the location of the abnormal collection point in the ocean image, and based on the abnormal collection point, mark the data collection points adjacent to the abnormal collection point as edge collection points with the center of the abnormal collection point as the center of the abnormal collection point; Get the straight-line distance from the abnormal collection point to the edge collection point and mark it as Dstr, and get the ecological risk value corresponding to the edge collection point , and based on the formula Get the data priority value YD of the edge acquisition point, where: represents the ecological risk value of the abnormal collection point, r2 represents the constant coefficient, and 0<r2<1, is the influence coefficient; Afterwards, the ecological risk values ​​of the abnormal data collection points and the remaining data collection points are directly used as data priority values, thereby obtaining the data priority value of each data collection point; Step 4: Arrange the data priority values ​​of the data collection points from large to small to obtain the priority sequence of the data collection points. Then the Marine Information Center processes the real-time collected marine ecological data according to the priority sequence of the data collection points.

2. A method for processing and analyzing marine ecological data of marine environment impact according to claim 1, characterized in that: The methods for setting the monomer interval include: The marine ecological data are arranged from small to large to obtain a data sequence, and then the two endpoint values ​​in the data sequence are taken and marked as DL and DR respectively, where DL represents the leftmost value in the data sequence, that is, the minimum value, and DR represents the rightmost value in the data sequence, that is, the maximum value; Then obtain the unit data distance d, take DL as the initial data, take DL+d as the first node, take DL+2d as the second node, and so on, and get a total of K nodes, among which, the Kth node DL+Kd≥DR, and the unit data distance d is the threshold; Taking the initial data DL as the starting point, the adjacent nodes are taken as endpoints in sequence according to the node order to obtain multiple monomer intervals. Specifically, the monomer intervals include [DL, DL+d), [DL+d, DL+2d), ..., [DL+(K-1)d, DL+Kd].

3. A method for processing and analyzing marine ecological data of marine environment impact according to claim 2, characterized in that: The methods for determining ecological risk values ​​include: S14: Classify the marine ecological data HY in the data sequence into monomer intervals. At this time, each monomer interval contains corresponding marine ecological data, using the formula The data frequency Fj is obtained, where j represents the interval number of the monomer interval, and j∈[1, K], Lj represents the number of marine ecological data in the monomer interval j, and ZL represents the total amount of data in the data sequence; Then based on the formula The environmental conventional value HC is obtained, where Pj represents the average value of the marine ecological data existing in the monomer interval j; S15: Obtain the marine ecological data of each data collection point, and arbitrarily select a data collection point as the target collection point, and extract the marine ecological data CD collected in real time at the target collection point, and then use the formula The ecological risk value XZ of the target collection point is obtained, where r1 is a fixed constant and 0<r1<1.

4. A method for processing and analyzing marine ecological data of marine environment impact according to claim 2, characterized in that: After obtaining the historically collected marine ecological data, it is necessary to remove the obvious outliers in the historically collected marine ecological data to obtain the marine ecological data HY under normal conditions. The obvious outliers refer to the data that are not within the standard data range of the marine ecological data.

5. The method for processing and analyzing marine ecological data of marine environment impact according to claim 1 is characterized in that: If the ecological risk values ​​of all data collection points are less than the risk threshold, the ecological risk value will be directly used as the data priority value.

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