Method and system for identifying lightning falling area

Abstract

The invention relates to a lightning falling area identification method and system, and belongs to the field of lightning data processing, and the method comprises the following steps: (1) obtaining the real-time lightning positioning data of an area to be forecasted; (2) searching and determining a thunder and lightning group for identifying the thunder and lightning group, namely identifying an area where thunder and lightning are densely generated within a preset time and space range; and (3) delimiting a lightning falling area which is used for determining a specific geographical falling area of the lightning group so as to carry out accurate lightning early warning and disaster prevention. The method has the advantages that (1) the method for determining the thunder and lightning groups through optimization and searching is more efficient and lower in complexity compared with a traditional proximity method; (2) the provided convex hull method is more accurate than the traditional ellipse method for delimiting the lightning falling area, so that the prediction of the future lightning falling area is more accurate; compared with a traditional ellipse method, the convex hull method is simpler in calculation and lower in consumed computing power, and is very important for business real-time prediction of future lightning falling areas.

Description

Technical Field

[0001] The invention relates to a method and a system for identifying a lightning strike zone, and belongs to the field of lightning data processing. Background Art

[0002] Lightning is a common and extremely harmful natural disaster that occurs in all parts of my country. Lightning can cause casualties, damage to buildings, damage to electrical and electronic equipment, forest and grassland fires, and fires or explosions in flammable and explosive places. Current technology cannot prevent the occurrence of lightning, so the best way to defend against lightning is to predict the occurrence of lightning and take preventive measures in advance. The common method of predicting the occurrence of lightning is to use the lightning strike zone of the previous moment to extrapolate the strike zone of the next moment. If the lightning strike zone cannot be accurately delineated, the lightning strike zone of the next moment cannot be correctly predicted. Since the occurrence of lightning has a certain randomness, the lightning strike point also has a certain randomness and high discreteness, which brings great difficulty to the delineation of the lightning strike zone.

[0003] The occurrence of lightning is random, the lightning landing point is also discrete, and lightning may occur in multiple areas or multiple thunderstorm clouds at the same time. If all these lightnings are identified as one lightning landing area, it will contain a large number of blank areas, resulting in a high false alarm rate of lightning warning. Since the occurrence of lightning often corresponds to thunderstorm clouds, and thunderstorm clouds mostly exist in the form of thunderstorm cells, a relatively dense area of ​​lightning will be formed under or around the thunderstorm cells, which is called a lightning group. At present, the recognition algorithm of lightning groups is relatively complex. The commonly used recognition of lightning groups is the neighbor method, that is, the lightning position is gridded, and if the grid points are adjacent, they are considered to be the same lightning group. This method is relatively easy to identify with the naked eye, but if it is allowed to be recognized by a computer, it is necessary to calculate the distance between all points (lightning positions) and then determine whether the distance between each point and all other points is less than a given threshold. If it is less than this threshold, it is considered to be adjacent. The calculation amount of this algorithm is about n2(n-1)! If it is a business application, it will require a lot of computing power support, especially if it is run on a single machine, the calculation time will be relatively long.

[0004] At present, the commonly used method for delineating the lightning strike zone is the ellipse method, which is to take the average value of the longitude and latitude of all lightning locations within a certain period of time as the center of mass of the ellipse, and then use these position data to calculate the major and minor axes of the ellipse and the angle with the x-axis, and finally draw this ellipse, which is the lightning strike zone. This method has certain shortcomings:

[0005] (1) The drawn ellipse deviates from the actual lightning strike area. Since the center of mass of the ellipse is the average value of all lightning positions, if the lightning is concentrated in a certain area, the ellipse will deviate to this position, and the drawn ellipse cannot cover the entire lightning strike area well.

[0006] (2) The shape of the ellipse does not match the actual lightning strike area. Since the actual lightning strike area is often irregular, the ellipse will circle many blank areas, which will cause a high false alarm rate of lightning warning.

[0007] (3) The calculation method of the ellipse is relatively complicated. It requires calculating the covariance matrix of the longitude and latitude of all lightning locations, as well as the eigenvalues, standard deviations, eigenvectors, inverse trigonometric functions of the angles of this matrix, and using integrals to solve the lightning zone area, which increases the difficulty of calculation and the computing power consumed. Summary of the invention

[0008] In order to overcome the defects of the prior art, the present invention provides a method and system for identifying a lightning strike zone. The technical solution of the present invention is:

[0009] A method for identifying a lightning strike zone comprises the following steps:

[0010] (1) Obtain real-time lightning location data in the forecast area;

[0011] (2) Check and determine the lightning group, which is used to identify the lightning group, that is, to identify the area where lightning occurs densely within a preset time and space range;

[0012] (3) Delineate lightning strike zones to determine the specific geographical locations where lightning groups will fall, so as to provide accurate lightning warnings and disaster prevention.

[0013] The step (2) is specifically as follows:

[0014] 2.1 Initialize the data set: take the location of each lightning point as a subset;

[0015] 2.2. Subset merging: Enumerate each lightning point, calculate the Euclidean distance between the current lightning point and other lightning points, and determine whether the subsets need to be merged into one set;

[0016] 2.3. Merge optimization: In subset merging, compare the path lengths of each subset, merge the tree with the short path under the root node of the tree with the long path, and continue in this way until all subsets that can be merged are merged into a set;

[0017] 2.4 Path compression optimization: In the merged tree, all child nodes and leaf nodes are hung under the root node, so that the tree structure becomes a two-layer structure;

[0018] 2.5. Determine the lightning group: Repeat the above steps until all subsets cannot be merged, so that each merged set is an independent lightning group.

[0019] The step (3) is specifically as follows:

[0020] 3.1 Obtain data: obtain lightning location data within a preset time period;

[0021] 3.2 Calculate the points on the convex hull: use the scanning algorithm for calculation;

[0022] 3.3 Draw the convex hull: connect the calculated points in sequence to form a closed convex polygon; 3.4 Calculate the area of ​​the convex hull: calculate the area of ​​the convex polygon, that is, the area of ​​the lightning strike zone.

[0023] The step 3.2 is specifically as follows:

[0024] 3.2.1 Find the origin of the coordinate axis, that is, the point with the smallest ordinate;

[0025] 3.2.2: Put all points into the coordinate system;

[0026] 3.2.3: Calculate the angle between each point and the x-axis, and sort them from small to large;

[0027] 3.2.4: Push the first two points into the stack and use the third point as the current point;

[0028] 3.2.5: Determine the relative position of the current point on line segment S; if it is on the left side, proceed to step 2.2.7; if it is on the right side, proceed to step 3.2.6;

[0029] 3.2.6: If the element at the top of the stack is not a point on the convex hull, pop the element out of the stack;

[0030] 3.2.7: If the current point is a point on the convex hull, push the point into the stack;

[0031] 3.2.8: Is it the last point? If yes, then end, that is, the points in the stack are the points on the convex hull; if no, then return to step 3.2.5.

[0032] A system for realizing a method for identifying a lightning strike zone, comprising:

[0033] A lightning group identification module is used to identify lightning groups, that is, to identify areas where lightning occurs intensively within a preset time and space range;

[0034] The lightning strike zone delineation module is used to determine the specific geographical strike zone of lightning groups in order to provide accurate lightning warning and disaster prevention.

[0035] The advantages of the present invention are:

[0036] (1) The method of determining lightning groups by optimizing and searching is more efficient and less complex than the traditional proximity method.

[0037] (2) The convex hull method provided by the system is more accurate than the traditional ellipse method in delineating the lightning strike zone, so the prediction of the future lightning strike zone will also be more accurate. In addition, the convex hull method is simpler to calculate than the traditional ellipse method and consumes less computing power, which is very important for real-time prediction of the future lightning strike zone. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 It is a schematic diagram of solving points on the convex hull of the present invention.

[0039] Figure 2 yes Figure 1 Schematic diagram of the process.

[0040] Figure 3 It is the overall flow chart of determining lightning groups and demarcating lightning strike areas of the present invention.

[0041] Figure 4 It is a system structure block diagram of the present invention.

[0042] Figure 5 This is a comparison of lightning strike areas identified by the convex hull method and the ellipse method of the present invention (lightning data: 00:00-9:00, October 3, 2022). DETAILED DESCRIPTION

[0043] The present invention will be further described below in conjunction with specific embodiments, and the advantages and features of the present invention will become clearer as the description proceeds. However, these embodiments are exemplary only and do not constitute any limitation to the scope of the present invention. It should be understood by those skilled in the art that the details and forms of the technical solution of the present invention may be modified or replaced without departing from the spirit and scope of the present invention, but these modifications and replacements all fall within the scope of protection of the present invention.

[0044] See also Figures 1 to 5 The present invention relates to a method for identifying a lightning strike zone, comprising the following steps:

[0045] (1) Obtain real-time lightning location data in the forecast area;

[0046] (2) Check and determine the lightning group, which is used to identify the lightning group, that is, to identify the area where lightning occurs densely within a preset time and space range;

[0047] (3) Delineate lightning strike zones to determine the specific geographical locations where lightning groups will fall, so as to provide accurate lightning warnings and disaster prevention.

[0048] Based on the settings in the above steps, the following are achieved:

[0049] Real-time data processing: By obtaining real-time lightning location data, the latest lightning strike area information can be provided, thereby achieving more timely warnings.

[0050] Efficient lightning group identification: The union-find algorithm is used to determine lightning groups, which improves the efficiency of data processing and reduces the consumption of computing resources.

[0051] Precise geographic positioning: The step of demarcating lightning strike zones can provide the specific geographic location of lightning groups, which helps in accurate early warning and effective disaster prevention.

[0052] Reduce false alarms: By accurately identifying lightning groups and strike areas, false alarms and misreporting are reduced, and the reliability of the early warning system is improved.

[0053] The step (2) is specifically as follows:

[0054] 2.1 Initialize the data set: take the location of each lightning point as a subset;

[0055] 2.2. Subset merging: Enumerate each lightning point, calculate the Euclidean distance between the current lightning point and other lightning points, and determine whether the subsets need to be merged into one set;

[0056] 2.3. Merge optimization: In subset merging, compare the path lengths of each subset. The path length of a tree refers to the sum of the paths from the root node to each child node, that is, the total number of nodes passed through from the root node to each child node. Merge the tree with a short path under the root node of the tree with a long path. This will not increase the height of the tree, and the amount of calculation will be relatively less in the next step of path compression optimization. Continue in this way until all subsets that can be merged are merged into a tree (set), where each subset and set is presented as a tree structure;

[0057] 2.4 Path compression optimization: In the merged tree, all child nodes and leaf nodes are hung under the root node, so that the tree structure becomes a two-layer structure;

[0058] 2.5. Determine the lightning group: Repeat the above steps until all subsets cannot be merged, so that each merged set (including subsets that cannot be merged) is an independent lightning group.

[0059] In the present invention, the lightning group identification method adopts an optimized union-find set, and the specific steps are as follows: Step 1: Set initialization. According to the time when the lightning occurs, each lightning position forms a subset (i.e., a tree). If n lightnings occur, n subsets are formed. Initially, the i-th subset only has the i-th point. Since the union-find set needs to record the root node of each node, the root node of each subset at the initial moment is the only point in it.

[0060] Step 2: Subset merging. Enumerate each point and calculate the Euclidean distance to other points. If the distance is less than (or equal to) the threshold for being put into the same subset, find the root nodes of the two points in the union-find set. If the root nodes are the same, it means that the two points have been added to the same subset and no operation is performed; if the root nodes are different, it means that the two subsets need to be merged, and the two subsets are merged according to the union-find rule.

[0061] Step 3: Merge optimization. Use the negative value of the root node of the current set to represent the total number of nodes in the tree. Each time a merge operation is performed, the tree with a short path is merged under the root node of the tree with a long path.

[0062] Step 4: Path compression optimization. For each search operation, first find the root node of the current node, and then hang all nodes on the path from the current node to the root node under the root node. This tree structure becomes a two-layer structure. Such a tree structure will greatly shorten the traversal time.

[0063] Step 5: Determine the lightning group. Repeat the above steps until all subsets cannot be merged, so that each set after merging (including the subsets that cannot be merged) is an independent lightning group.

[0064] The step (3) is specifically as follows:

[0065] 3.1 Obtain data: obtain lightning location data within a preset time period;

[0066] 3.2 Calculate the points on the convex hull: use the scanning algorithm for calculation;

[0067] 3.3 Draw the convex hull: connect the calculated points in sequence to form a closed convex polygon; 3.4 Calculate the area of ​​the convex hull: calculate the area of ​​the convex polygon, that is, the area of ​​the lightning strike zone.

[0068] The step 3.2 is specifically as follows:

[0069] 3.2.1 Find the origin of the coordinate axis, that is, the point with the smallest ordinate:

[0070] If all points of a lightning group (i.e. the location of lightning) are placed in a two-dimensional coordinate system, the point with the smallest ordinate must be a point on the convex hull, denoted as L0.

[0071] 3.2.2: Put all points into the coordinate system:

[0072] With L0 as the origin, the east-west direction (longitude) as the x-axis, and the north-south direction (latitude) as the y-axis, the coordinates of all points are translated into this coordinate system.

[0073] 3.2.3: Calculate the angle between each point and the x-axis, and sort them from smallest to largest:

[0074] Calculate the angle α of each point relative to the x-axis, and sort the points in order of angle α from small to large. When α is the same, the point closer to L0 is ranked first. The other points are marked as L1, L2, L3, etc. From geometric knowledge, we can know that the first point L1 and the last point Ln in the sorting result must be points on the convex hull.

[0075] 3.2.4: Push the first two points into the stack and make the third point the current point:

[0076] We already know the first point L0 and the second point L1 on the convex hull, and put them in the stack. Now from the result obtained in step 3, take the point after L1 (L2) as the current point, and then start looking for the third point.

[0077] 3.2.5: Determine the relative position of the current point on line segment S; if it is on the left, proceed to step 3.2.7; if it is on the right, proceed to step 3.2.6:

[0078] Draw a straight line S through the top two elements of the stack (the lightning positions). Determine whether the current point is on the right or left side of the line S (from the previous point to the next point on the line). If the current point is on the right side of the line S, the element on the top of the stack is not a point on the convex hull, pop the top element out of the stack, and execute step 3.2.6; if it is on the line, or on the left side of the line, execute step 3.2.7.

[0079] exist Figure 1 In the example, draw a straight line S(L1L2) through points L1 and L2. From the line of sight from L1 to L2, the current point L3 is on the left side of the straight line S(L1L2), which means that L2 is a point on the convex hull. Similarly, draw a new straight line S(L2L3) through points L2 and L3. It can be seen that L4 is on the right side of the straight line S(L2L3), which means that L3 is not a point in the convex hull. Pop L3 from the stack and push L4 into the stack instead. Repeat these two steps to find all the points on the convex hull.

[0080] 3.2.6: If the element at the top of the stack is not a point on the convex hull, pop the element out of the stack;

[0081] 3.2.7: If the current point is a point on the convex hull, push the point into the stack;

[0082] 3.2.8: Is it the last point? If yes, then end, that is, the point in the stack is the point on the convex hull; if no, then return to step 3.2.5:

[0083] Check whether the current point is the last point Ln. If it is the last point, then end; if not, take the point after the current point as the new current point and return to step 5. After all the above steps are completed, the remaining elements in the stack are the points on the convex hull.

[0084] A severe thunderstorm weather process that occurred on the Shandong Peninsula on October 3, 2022 was selected. The data used was the lightning location data observed by the lightning location monitoring network of the Shandong Meteorological Department from 0:00 to 9:00 (10 minutes) on October 3. After identification, two lightning strike areas were determined, and the lightning strike areas were delineated using the ellipse method and the convex hull method respectively ( Figure 5 ).pass Figure 5 It can be clearly seen that, no matter the lightning strike zone with a larger area in the west or the lightning strike zone with a smaller area in the east, the lightning strike zone delineated by the method of the present invention is significantly better than the ellipse method in terms of accuracy.

[0085] The present invention also relates to a system for realizing a method for identifying a lightning strike zone, comprising:

[0086] A lightning group identification module 1 is used to identify lightning groups, that is, to identify areas where lightning occurs intensively within a preset time and space range;

[0087] The lightning strike zone delineation module 2 is used to determine the specific geographical strike zone of the lightning group in order to carry out accurate lightning warning and disaster prevention.

[0088] 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 identifying a lightning strike zone, characterized in that: The following steps are involved: (1) Obtain real-time lightning location data in the forecast area; (2) Check and determine the lightning group, which is used to identify the lightning group, that is, to identify the area where lightning occurs densely within a preset time and space range; (3) Delineate lightning strike zones to determine the specific geographical locations where lightning groups will fall, so as to provide accurate lightning warnings and disaster prevention.

2. The method for identifying a lightning strike zone according to claim 1, characterized in that: The step (2) is specifically as follows: 2.1 Initialize the data set: take the location of each lightning point as a subset; 2.

2. Subset merging: Enumerate each lightning point, calculate the Euclidean distance between the current lightning point and other lightning points, and determine whether the subsets need to be merged into one set; 2.

3. Merge optimization: In subset merging, compare the path lengths of each subset, merge the tree with the short path under the root node of the tree with the long path, and continue in this way until all subsets that can be merged are merged into a set; 2.4 Path compression optimization: In the merged tree, all child nodes and leaf nodes are hung under the root node, so that the tree structure becomes a two-layer structure; 2.

5. Determine the lightning group: Repeat the above steps until all subsets cannot be merged, so that each merged set is an independent lightning group.

3. The method for identifying a lightning strike zone according to claim 1, characterized in that: The step (3) is specifically as follows: 3.1 Obtain data: obtain lightning location data within a preset time period; 3.2 Calculate the points on the convex hull: use the scanning algorithm for calculation; 3.3 Draw the convex hull: connect the calculated points in sequence to form a closed convex polygon; 3.4 Calculate the convex hull area: Calculate the area of ​​the convex polygon, that is, the area of ​​the lightning strike zone.

4. The method for identifying a lightning strike zone according to claim 1, characterized in that: The step 3.2 is specifically as follows: 3.2.1 Find the origin of the coordinate axis, that is, the point with the smallest ordinate; 3.2.2: Put all points into the coordinate system; 3.2.3: Calculate the angle between each point and the x-axis, and sort them from small to large; 3.2.4: Push the first two points into the stack and use the third point as the current point; 3.2.5: Determine the relative position of the current point on line segment S; if it is on the left side, proceed to step 2.2.7; if it is on the right side, proceed to step 3.2.6; 3.2.6: If the element at the top of the stack is not a point on the convex hull, pop the element out of the stack; 3.2.7: If the current point is a point on the convex hull, push the point into the stack; 3.2.8: Is it the last point? If yes, then end, that is, the points in the stack are the points on the convex hull; if no, then return to step 3.2.

5.

5. A system for implementing the method for identifying a lightning strike zone according to any one of claims 1 to 4, characterized in that: include: A lightning group identification module is used to identify lightning groups, that is, to identify areas where lightning occurs intensively within a preset time and space range; The lightning strike zone delineation module is used to determine the specific geographical strike zone of lightning groups in order to provide accurate lightning warning and disaster prevention.

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