A method for screening monitoring point positions in the boundary area of adjacent monitoring units

Abstract

The present invention relates to a method for screening monitoring point positions in the boundary region of adjacent monitoring units. The method includes: calculating the area S of the monitoring unit according to the formula #imgabs0# i and the number n of monitoring points therein i , and the calculation result is the threshold L i ; calculating the shortest distance dis from all monitoring points to the boundary line of the monitoring unit. When dis ≤ L i , the monitoring point is marked as class A; when dis > L i , the monitoring point is marked as class B; setting the monitoring points as a set Z in ascending order of dis for all monitoring points, Z = {a1, a2, …, a i}; determining the dis pairing between the monitoring points A in the monitoring unit and the monitoring points in the adjacent unit, putting dis and the corresponding point pairs into the matrix M, and after pairing each point, putting the shortest distance and the corresponding point pairs into the matrix M; calculating the distance k between two positions of the monitoring points A, selecting the two point pairs corresponding to the two points with the largest k as the point pairs to be screened, and taking the point closest to the common boundary of the adjacent monitoring unit among these two points as the first point, sorting the k of the other points in A except these two points and the first point, and uniformly selecting one or more point pairs corresponding to the points according to the distance, finally realizing the screening.

Description

Technical Field

[0001] The present application belongs to the field of monitoring, and specifically relates to a method for screening monitoring points in the boundary area of adjacent monitoring units. Background Art

[0002] When conducting monitoring surveys, especially large-scale surveys, the monitoring area is often divided into different monitoring units for the convenience of organization and management. Different monitoring teams are responsible for different monitoring units. There are situations where the sampling, sample preparation, testing and other monitoring work of two adjacent monitoring units are not completed by the same organization or the same team of personnel. Generally speaking, the monitoring data of spatially adjacent areas will be relatively close and will not have large differences. Therefore, when reviewing the monitoring data, it is necessary to detect the differences in the monitoring data of different monitoring units in the boundary areas of adjacent monitoring units to measure whether the monitoring data is accurate. Before performing the boundary value change rate detection, the monitoring points in the boundary areas of adjacent monitoring units must be found first, so that the monitoring data of the found monitoring points can be used for difference testing.

[0003] The "buffer" function of the geographic information system software can automatically generate a buffer zone with the common edge as the center line after the monitoring unit base map and monitoring points are uploaded to the geographic information system software. The buffer zone is given the width of the buffer zone and the common edge as the center line, and then the points falling within the buffer zone are selected. Alternatively, after the monitoring unit base map and monitoring points are uploaded, the points near the common edge can be manually selected one by one.

[0004] However, the width of adjacent areas circled by the buffer function is the same, which leads to the selected points being clustered together, or too many points being selected on one side of the common edge and too few points on the other side, which is not conducive to the subsequent inspection of monitoring data on both sides. In addition, when there are multiple monitoring units adjacent to each other, that is, when they share a common edge, the buffers overlap with each other, and it is impossible to distinguish the ownership of the points in each buffer. Manually selecting one point at a time, judging the distance between the point and the common edge with the naked eye, and marking the ownership of the monitoring units of the selected points one by one is time-consuming and labor-intensive, with a high error rate, and cannot be completed manually when there are many monitoring units.

[0005] This application intends to design a spatial analysis algorithm to solve the problem of uneven distribution of monitoring points on both sides of the common boundary of adjacent monitoring units, quickly select one or more point pairs closest to the common edge from adjacent monitoring units, and ensure that the selected points belonging to the same monitoring unit are not clustered. Summary of the invention

[0006] For large-scale monitoring and investigation work, this application proposes a method for accurately and quickly finding the monitoring points in the boundary area of adjacent monitoring units. This method uses the spatial positions of the monitoring points in adjacent monitoring units to find the monitoring points that belong to different monitoring units in the boundary area of adjacent monitoring units, so as to verify the differences in their monitoring data.

[0007] To solve the above technical problems, the method for finding the monitoring points in the boundary area of adjacent monitoring units includes the following steps:

[0008] Step S1: Calculate the area S i of the monitoring unit and the number n i of the monitoring points therein according to the formula and take the calculation result as the threshold L i ;

[0009] Step S2: Calculate the shortest distance dis from all monitoring points to the boundary line of the monitoring unit, and take the threshold L i as the standard: when dis ≤ L i , mark the monitoring point as type A; when dis > L i , mark the monitoring point as type B;

[0010] Step S3: Sort all the monitoring points according to the shortest distance dis calculated in Step S2 from small to large, and set the monitoring points as the set Z {{a1, a2, ···, a i}} in order;

[0011] Step S4: Determine the closest distance pairing between the monitoring points A in the monitoring unit and the monitoring points in the adjacent unit, and put the closest distance and the corresponding point pairs into the matrix M:

[0012] Step S5: Repeat Step S4 for the monitoring unit to obtain the final matrix M of the monitoring unit;

[0013] Step S6: Calculate the distance k between every two points among the A monitoring points, select the two point pairs corresponding to the two points with the farthest distance as the point pairs to be screened, and take the point closest to the common boundary line of the adjacent monitoring unit among these two points as the first point. Sort the distances k between the other points in A except these two points and the first point from small to large, and select one or more point pairs corresponding to the points evenly according to the distance.

[0014] In the set Z in Step S3, the numbers, coordinates, distance values, and A and B classifications of the monitoring points are saved.

[0015] In Step S4, this operation is performed on each type A monitoring point to find the point closest to each type A monitoring point in the adjacent monitoring unit.

[0016] The specific steps in Step S4 include:

[0017] Step S4a: Locate adjacent monitoring units of the monitoring unit, and calculate the distances from monitoring point a1 in the monitoring unit to all monitoring points in the adjacent monitoring units;

[0018] Step S4b: Match the point in the adjacent monitoring unit with the shortest distance to a1 with point a1, and put the matched point pair p1 and the corresponding distance d min into matrix M, and delete a1 from set Z;

[0019] Step S4c: Repeat the above pairing steps for a2, and iterate all monitoring points in set Z in this way to obtain matrix M of {(p1, d min1 ),(p2, d min2 ), ···, (p i , d mini )};

[0020] Step S4d: Compare d min in matrix M with the threshold of the monitoring unit, and finally delete the point pairs where d min > L i + L i+1 from matrix M; where the L i+1 is the threshold of the adjacent unit;

[0021] Step S4e: Prune type A monitoring points according to a i in the remaining p i in the final matrix M, only retain the monitoring points existing in M, and put other points into type B monitoring points.

[0022] The point pair information in step S4b includes: the number, coordinates of point a1 and the point with the shortest distance to point a1 in the adjacent monitoring unit, and the distance between point a1 and the point with the shortest distance to point a1 in the adjacent monitoring unit.

[0023] The L i + L i+1 in step S4d is the sum of the thresholds of two adjacent monitoring units.

[0024] In step S6, first screen out the point pairs corresponding to two points in the type A points with the largest k as the reference for subsequent point selection.

[0025] Compared with the prior art, the advantages and effects of the present application are as follows:

[0026] 1. The present application intends to design a spatial analysis algorithm, which can efficiently solve the problem of screening points in the adjacent monitoring unit area when the distribution of monitoring points on both sides of the common boundary of adjacent monitoring units is uneven.

[0027] 2. The method adopted in this application can quickly select one or more point pairs closest to the common edge from adjacent monitoring units, and ensure that the points belonging to the same monitoring unit are not clustered together.

[0028] The above description is only an overview of the technical solution of this application. In order to understand the technical means of this application more clearly, so as to be implemented in accordance with the content of the specification, and in order to make the above and other purposes, features and advantages of this application more obvious and understandable, the following takes the preferred embodiments of this application and combines with the drawings to describe in detail as follows.

[0029] According to the following detailed description of the specific embodiments of this application in conjunction with the drawings, those skilled in the art will understand the above and other purposes, advantages and features of this application more clearly. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] In order to more clearly illustrate the technical solutions in the embodiments of this application or in the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the following drawings are some embodiments of this application. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained according to these drawings. In all the drawings, similar elements or parts are generally denoted by similar reference numerals. In the drawings, the elements or parts are not necessarily drawn to actual scale.

[0031] Wherein:

[0032] Att Figure 1 is a distribution diagram of monitoring units and monitoring points;

[0033] Att Figure 2 is a threshold range diagram;

[0034] Att Figure 3 is a diagram of Class A monitoring points and Class B monitoring points of data;

[0035] Att Figure 4 is a distance diagram between a1 and points in adjacent monitoring units;

[0036] Att Figure 5 is a correction diagram of monitoring point A;

[0037] Att Figure 6 is a diagram of the (p1, d min ) point pair and the distances from a1 to other monitoring points in the same monitoring unit. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0038] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the following will clearly and completely describe the technical solutions in the embodiments of this application with reference to the accompanying drawings in the embodiments of this application. Obviously, the described embodiments are some, but not all, of the embodiments of this application. In the following description, specific details such as specific configurations and components are provided only to assist in a comprehensive understanding of the embodiments of this application. Therefore, those skilled in the art should clearly understand that various changes and modifications can be made to the embodiments described here without departing from the scope and spirit of this application. Additionally, for the sake of clarity and conciseness, descriptions of known functions and structures are omitted in the embodiments.

[0039] It should be understood that the phrase "one embodiment" or "this embodiment" mentioned throughout the specification means that a specific feature, structure, or characteristic related to the embodiment is included in at least one embodiment of this application. Therefore, the phrase "one embodiment" or "this embodiment" appearing throughout the specification does not necessarily refer to the same embodiment. In addition, these specific features, structures, or characteristics can be combined in one or more embodiments in any suitable manner.

[0040] In addition, this application may repeat reference numerals and / or letters in different instances. This repetition is for the purpose of simplicity and clarity, and in itself does not indicate the relationship between the various embodiments and / or arrangements discussed.

[0041] The term "and / or" in this document is merely a description of the association relationship of associated objects, indicating that three relationships can exist. For example, A and / or B can represent: A exists alone, B exists alone, and both A and B exist simultaneously. The term " / and" in this document describes another association relationship of associated objects, indicating that two relationships can exist. For example, A / and B can represent: A exists alone, and both A and B exist. Additionally, the character " / " in this document generally indicates that the associated objects before and after are in an "or" relationship.

[0042] The term "at least one" in this document is merely a description of the association relationship of associated objects, indicating that three relationships can exist. For example, at least one of A and B can represent: A exists alone, both A and B exist simultaneously, and B exists alone.

[0043] It should also be noted that in this document, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise", or any other variant thereof are intended to cover non-exclusive inclusion.

[0044] Embodiment 1

[0045] According toFigure 1 As shown, there is an uneven distribution of monitoring points on both sides in the monitoring unit. In this embodiment, a method for screening monitoring point positions in the boundary area of adjacent monitoring units is designed. The specific steps are as follows:

[0046] According to Figure 2 As shown, step S1: Calculate the area S i of each monitoring unit and the number n i of the monitoring points therein according to the formula , and take the calculation result as the threshold L i ;

[0047] According to Figure 3 As shown, step S2: Calculate the shortest distance dis from all monitoring point data to the boundary line of the monitoring unit. Taking the threshold L i as the standard: when dis < L i , mark the monitoring point data as A; when dis > L i , mark the monitoring point data as B;

[0048] Step S3: In each monitoring unit, sort all the shortest distances dis calculated in step S2 from small to large, and set the monitoring points as the set Z = {a1, a2, ···, a i} in order;

[0049] Step S4: Determine the shortest distance pairing between the monitoring points A in the monitoring unit and the monitoring points of the adjacent monitoring unit, and put the shortest distance and the corresponding point pairs into the matrix M:

[0050] Step S5: Repeat step S4 for each monitoring unit to obtain the final M matrix in each monitoring unit;

[0051] According to Figure 6 As shown, step S6: In each monitoring unit, calculate the distance k between every two positions of the monitoring points A, select the point pair corresponding to the two farthest points as the point pair to be screened, and take the point closest to the common boundary line of the adjacent monitoring unit among these two points as the first point. Sort the distances k between the other points in A except these two points and the first point from small to large, and uniformly select one or more point pairs corresponding to the points according to the distance.

[0052] This application intends to design a spatial analysis algorithm. By using the two point pairs corresponding to the two farthest points as comparison data, and sorting according to the distance k from the first point in the two point pairs to the other points in the A-type points of the monitoring unit, uniformly selecting one or more point pairs corresponding to the intermediate points as the point pairs to be screened, it can efficiently solve the problem of uneven distribution of monitoring points on both sides of the common boundary of adjacent monitoring units, and can quickly select one or more point pairs closest to the common side from adjacent monitoring units.

[0053] Example 2

[0054] In this example, a method for screening monitoring point positions in the boundary area of adjacent monitoring units is designed, which is further designed on the basis of Example 1.

[0055] In the set Z in step S3, the numbers, coordinates, distance values, and A and B classifications of the monitoring points are stored.

[0056] In step S4, this operation is performed on each A-class monitoring point, and the point closest to each A-class monitoring point is found in the adjacent monitoring units.

[0057] The specific steps in step S4 include:

[0058] According to Figure 4 As shown, in step S4a, find the adjacent monitoring units of each monitoring unit, and calculate the distances from the a1 monitoring point in the monitoring unit to all the monitoring points in the adjacent monitoring units;

[0059] In step S4b, match the point with the shortest distance to a1 in the adjacent monitoring unit with point a1, and put the matched point pair p1 and the corresponding distance d min into matrix M, and delete a1 from the set Z;

[0060] In step S4c, repeat the above pairing steps for a2, and iterate all the monitoring points in the set Z to obtain the matrix M of {(p1,d min1 ),(p2,d min2 ),···,(p i ,d mini )};

[0061] In step S4d, compare the d min in matrix M with the threshold of the monitoring unit, and finally delete the point pairs in matrix M where d min > L i + L i+1 (the threshold of the monitoring unit is L i , and the threshold of the adjacent unit is L i+1 );

[0062] According to Figure 6 As shown, in step S4e, delete the A-class monitoring points according to the a i in the retained p i in the final matrix M, and only retain the monitoring points existing in M, and put the other points into the B-class monitoring points.

[0063] The point pair information in step S4b includes: the number and coordinates of point a1 and the point closest to point a1 in the adjacent monitoring unit, and the distance between point a1 and the point closest to point a1 in the adjacent monitoring unit.

[0064] The L described in the step S4d i +L i+1 is the sum of the thresholds of two adjacent monitoring units.

[0065] In the step S6, first, select the point pairs corresponding to two points among the A-type points with the largest k as the reference for subsequent point selection.

[0066] A method for screening monitoring point positions in the boundary area of adjacent monitoring units provided by the present application can, for large-scale monitoring and investigation work, utilize the spatial positions of the monitoring point positions of adjacent monitoring units to find out the monitoring point positions belonging to different monitoring units in the boundary area of adjacent monitoring units, so as to verify the differences in their monitoring data, and has the characteristics of accuracy and rapidity.

[0067] The above are only the preferred embodiments of the present invention, and it does not limit the protection scope of the present invention thereby. For those skilled in the art, the present invention can have various changes and modifications. All changes, modifications, substitutions, integrations, and parameter changes made to these embodiments by means of conventional substitutions or capable of achieving the same functions without departing from the principle and spirit of the present invention fall within the protection scope of the present invention.

Claims

1. A method for screening monitoring point positions in the boundary area of adjacent monitoring units, characterized in that, The method specifically includes: Step S1: Calculate the area S of the monitoring unit i and the number n of monitoring points therein i According to the formula and take the calculation result as the threshold L i ; Step S2: Calculate the nearest distance dis from all monitoring points to the boundary line of the monitoring unit, with the threshold L i as the criterion: When dis ≤ L i the monitoring point is labeled as Class A; when dis > L i the monitoring point is labeled as Class B; Step S3: Sort all the calculated nearest distances dis of the monitoring points in step S2 from smallest to largest, and set the monitoring points as the set Z = {a1, a2, ···, a i} in sequence; Step S4: Determine the nearest distance pairing between the monitoring point A in the monitoring unit and the monitoring points in adjacent units, and put the nearest distance and the corresponding point pairs into the matrix M: Step S5: Repeat step S4 for the monitoring unit to obtain the final matrix M of the monitoring unit; Step S6: Calculate the distance k between two points in the A monitoring points, select the two point pairs corresponding to the two points with the farthest distance as the point pairs to be screened, and take the point closest to the common boundary line of the adjacent monitoring unit among these two points as the first point. Sort the distances k between the other points in A and the first point from small to large, and uniformly select one or more point pairs corresponding to the points according to the distance.

2. The screening method for monitoring points in the boundary area of adjacent monitoring units according to claim 1, characterized in that In step S3, the set Z stores the numbers, coordinates, distance values, and A and B classifications of the monitoring points.

3. A method for screening monitoring points in the boundary area of adjacent monitoring units according to claim 1, characterized in that In step S4, this operation is performed on each A-class monitoring point to find the point with the closest distance to each A-class monitoring point in the adjacent monitoring unit.

4. A method for screening monitoring point positions in the boundary region of adjacent monitoring units according to claim 3, characterized in that The specific steps in step S4 include: Step S4a: Search for the adjacent monitoring units of the monitoring unit, and calculate the distances from the a1 monitoring point in the monitoring unit to all the monitoring points in the adjacent monitoring units; Step S4b: Match the point with the shortest distance to a1 in adjacent monitoring units with point a1, and put the matched point pair p1 and the corresponding distance d min into matrix M, and delete a1 from set Z; Step S4c: Repeat the above pairing steps for a2, and iterate through all the monitoring points in set Z in this way to obtain the matrix M = {(p1, d min1 ),(p2, d min2 ), ···, (p i , d mini )}; Step S4d: Compare d in matrix M min with the threshold of the monitoring unit, and finally delete d in matrix M min > L i + L i+1 of the point pairs; where the L i+1 is the threshold of adjacent units. Step S4e: According to the p retained in the final matrix M i a in i delete the Class A monitoring points, only retain the monitoring points existing in M, and put the other points into the Class B monitoring points.

5. A method for screening monitoring points in the boundary region of adjacent monitoring units according to claim 4, characterized in that, In step S4b, the point pair information includes: the point a1, the numbers and coordinates of the points in the adjacent monitoring unit that are closest to the point a1, and the distance between the point a1 and the point in the adjacent monitoring unit that is closest to the point a1.

6. A method for screening monitoring point positions in the boundary region of adjacent monitoring units according to claim 4, characterized in that, The L described in the step S4d i +L i+1 is the sum of the thresholds of two adjacent monitoring units.

7. The method for screening monitoring points in the boundary area of adjacent monitoring units according to claim 1, characterized in that, In step S6, first screen out the point pairs corresponding to the two points in the A-class points with the largest k as the reference for subsequent point selection.

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