A Geographic Information Survey and Calibration Method and System

Abstract

The present invention relates to the technical field of geographic information surveying and mapping, and specifically discloses a geographic information surveying and mapping calibration method and system, which specifically includes the following steps: Step 1: Obtain the survey data of the geographic area to be surveyed, analyze it, and calculate the change judgment value; Step 2: Compare the change judgment value with the change judgment threshold to obtain the sub-region with a large degree of change; Step 3: Based on the obtained sub-region with a large degree of change, obtain the survey change information of the sub-region with a large degree of change in historical data, obtain the ratio of the number of changes in historical data, and compare the ratio of the number of changes with the ratio threshold of the number of changes to generate a high change frequency signal. Thereby reducing the cost of surveying and calibration, and through optimizing the survey cycle and integrating the survey area, the reasonable allocation of surveying and calibration resources, the improvement of surveying efficiency calibration, and the guarantee of surveying accuracy are realized.

Description

Technical Field

[0001] The present invention relates to the technical field of geographic information surveying and mapping, and in particular to a method and system for calibrating geographic information surveying and mapping. Background Art

[0002] Geographic information surveying and mapping calibration is a process of collecting, processing, comparing, and correcting geographic space data using professional surveying and mapping techniques and methods to ensure that the accuracy, integrity, and consistency of these data meet specific requirements. This process includes precise measurement of geographic features such as terrain, landform, vegetation, and water systems to ensure the accuracy and reliability of the data.

[0003] For geographic information data, it is necessary to conduct surveying and mapping calibration at regular intervals to update the geographic information data. Since the geographic environment is dynamically changing, regular surveying and mapping calibration can ensure the timeliness and accuracy of the data. However, traditional methods often have difficulty accurately determining which survey areas need to be preferentially surveyed and calibrated, resulting in a lack of pertinence and efficiency in the allocation of surveying resources. Some important areas may not be surveyed and calibrated in a timely and effective manner due to insufficient resources, while some areas with little change may be over-surveyed, causing waste of resources. Summary of the Invention

[0004] The purpose of the present invention is to provide a method and system for calibrating geographic information surveying and mapping to solve the technical problems in the above background.

[0005] The technical solution adopted by the present invention to solve the above technical problems is as follows:

[0006] In the first aspect, the present invention provides a method for calibrating geographic information surveying and mapping, specifically including the following steps: Step 1: Obtain the survey data of the geographic area to be surveyed, analyze it, and calculate the change judgment value; Step 2: Compare the change judgment value with the change judgment threshold to obtain the sub-areas with large change degree; Step 3: Based on the obtained sub-areas with large change degree, obtain the survey change information of the sub-areas with large change degree in historical data, obtain the ratio of the number of change times in historical data, and compare the ratio of the number of change times with the ratio threshold of the number of change times to generate a high change frequency signal; Step 4: Based on the high change frequency signal, obtain the sub-areas to be analyzed, obtain the change time points, and analyze them to obtain the sub-areas with regular changes; Step 5: Based on the obtained sub-areas with regular changes, obtain the optimized survey period value, and integrate the sub-areas with regular changes to obtain the integrated area.

[0007] As a further solution of the present invention: The process of obtaining the change judgment value is as follows:

[0008] Obtain the ratio of the number of change time points, the ratio of the time points with the largest continuous number, and the ratio of the distribution of change time points;

[0009] Substitute into the formula to calculate the change judgment value BH. Among them, GS represents the proportion of the number of time points with changes, LX represents the proportion of the time points of the continuous maximum number, FB represents the proportion of the distribution of the time points with changes, and a1, a2, and a3 are weight coefficients. The value of a1 is 0.58, the value of a2 is 0.20, and the value of a3 is 0.22.

[0010] As a further solution of the present invention: the obtaining process of the proportion of the number of time points with changes, the proportion of the time points of the continuous maximum number, and the proportion of the distribution of the time points with changes is as follows:

[0011] Divide the geographical information area to be surveyed into several survey sub-areas in a grid pattern, preset a survey period, divide the survey period into several survey sub-periods, and use the start time point of each survey sub-period as the survey time point;

[0012] In each survey sub-area, obtain the survey data at each survey time point;

[0013] In each survey sub-area, compare the survey data obtained at two adjacent survey time points. If the survey information at two adjacent survey time points is different, mark it as a survey time point with changes;

[0014] Obtain the value of the number of survey time points with changes, calculate the ratio of the value of the number of survey time points with changes to the value of the number of survey time points, and obtain the proportion of the number of time points with changes;

[0015] Obtain the survey time points with changes, mark the continuous survey time points with changes as a group of survey time points with changes, obtain the value of the number of groups of survey time points with changes, calculate the ratio of the value of the number of groups of survey time points with changes to the value of the number of survey time points with changes, and obtain the proportion of the distribution of the time points with changes;

[0016] Extract the maximum value of the number of survey time points contained in the group of survey time points with changes, calculate the ratio of it to the value of the number of survey time points with changes, and obtain the proportion of the time points of the continuous maximum number.

[0017] As a further solution of the present invention: the obtaining process of the sub-area with a large degree of change is as follows:

[0018] Obtain the change judgment value of each survey sub-area, and compare the change judgment value with the change judgment threshold;

[0019] If the change judgment value is greater than the change judgment threshold, generate a signal of a large degree of change;

[0020] Based on the generated signal of a large degree of change, obtain the survey sub-area corresponding to the generated signal of a large degree of change, and mark it as the sub-area with a large degree of change.

[0021] As a further solution of the present invention: The process of generating a signal with a high change frequency is as follows:

[0022] Obtain a sub-region with a large degree of change, extract the number of changes corresponding to the sub-region with a large degree of change in the historical data, perform a ratio process on the number of changes and the total number of surveys in the historical data to obtain the ratio of the number of changes;

[0023] Compare the ratio of the number of changes with the ratio threshold of the number of changes;

[0024] If the ratio of the number of changes is greater than the ratio threshold of the number of changes, generate a signal with a high change frequency.

[0025] As a further solution of the present invention: The process of obtaining the regularly changing sub-region is as follows:

[0026] Based on the generated signal with a high change frequency, obtain the ratio of the number of small deviation counts;

[0027] Compare the ratio of the number of small deviation counts with the ratio threshold of the number of small deviation counts;

[0028] If the ratio of the number of small deviation counts is greater than the ratio threshold of the number of small deviation counts, generate a regular signal,

[0029] Based on the generated regular signal, obtain the corresponding sub-region to be analyzed and mark it as a regularly changing sub-region.

[0030] As a further solution of the present invention: The process of obtaining the ratio of the number of small deviation counts is as follows:

[0031] Obtain the absolute deviation value of the adjacent time difference, and compare the absolute deviation value of the adjacent time difference with the absolute deviation threshold of the adjacent time difference;

[0032] If the absolute deviation value of the adjacent time difference is less than the absolute deviation threshold of the adjacent time difference, generate a small deviation signal. If the absolute deviation value of the adjacent time difference is greater than or equal to the absolute deviation threshold of the adjacent time difference, generate a large deviation signal;

[0033] Obtain the number value of the generated small deviation signals and the number value of the generated large deviation signals, and sum them to obtain the total number. Perform a ratio process on the number value of the generated small deviation signals and the total number to obtain the ratio of the number of small deviation counts.

[0034] As a further solution of the present invention: The process of obtaining the absolute deviation value of the adjacent time difference is as follows:

[0035] Obtain the surveyed sub-region corresponding to the generated high change frequency and mark it as the sub-region to be analyzed;

[0036] For each sub-region to be analyzed, obtain the time points when the survey data changes in the historical data, and mark them as change time points;

[0037] Calculate the difference between adjacent change time points to obtain the adjacent time difference, and sum and average all the adjacent time differences to obtain the average adjacent time difference;

[0038] Calculate the difference between each of the adjacent time differences and the average adjacent time difference, and take the absolute value of the difference to obtain the absolute deviation value of the adjacent time difference.

[0039] As a further solution of the present invention: the process of obtaining the integration region is as follows:

[0040] Obtain the regularly changing sub-regions, extract the minimum value of the corresponding adjacent time differences in the regularly changing sub-regions, and mark it as the optimized survey period value;

[0041] Extract the minimum value A and the maximum value B in the optimized survey period value, preset the interval threshold N, and group the optimized survey period value based on the minimum value A, the maximum value B and the preset interval threshold N, where the number of groups is ;

[0042] Obtain the regularly changing sub-regions corresponding to the optimized survey period value of each group and the number of values, obtain the groups with the number of values greater than 1, and mark them as the groups to be integrated;

[0043] Integrate the adjacent regularly changing sub-regions in the groups to be integrated to obtain the integration region.

[0044] In a second aspect, the present invention provides a geographic information survey calibration system, which includes:

[0045] Survey data acquisition and processing module: acquire the survey data of the geographic information region to be surveyed, analyze it, and calculate the change judgment value;

[0046] Change degree judgment module: compare the change judgment value with the change judgment threshold to obtain the sub-regions with large change degree;

[0047] Change frequency acquisition module: based on the obtained sub-regions with large change degree, obtain the survey change information of these sub-regions in the historical data, obtain the ratio of the number of changes in the historical data, and compare the ratio of the number of changes with the change number ratio threshold to generate a high change frequency signal;

[0048] Regularity judgment module: based on the high change frequency signal, obtain the sub-regions to be analyzed, obtain the change time points, and perform analysis to obtain the regularly changing sub-regions;

[0049] Region integration module: Based on the obtained regularly varying sub-regions, obtain the optimized value of the survey period, and integrate the regularly varying sub-regions to obtain the integrated region.

[0050] Advantages of the present invention:

[0051] (1) By obtaining the survey data of each survey time point corresponding to the survey sub-region within the survey period, comparing the survey data to obtain the changed survey time points, calculating the proportion of the number of changed time points, the distribution proportion of the changed time points, and the proportion of the continuous maximum number of time points based on the changed survey time points, and substituting the calculated proportion of the number of changed time points, the distribution proportion of the changed time points, and the proportion of the continuous maximum number of time points into the formula for data processing to calculate the change judgment value, comparing the calculated change judgment value with the threshold value to judge the change degree of the corresponding survey sub-region. Thus, by combining multiple change indicators and weight coefficients, it is possible to comprehensively and accurately evaluate the change degree of the survey sub-region, and give priority to survey calibration for these regions in subsequent surveys, which helps to optimize the allocation of survey resources and improve the efficiency of survey calibration.

[0052] (2) After obtaining the sub-regions with large change degrees, analyzing the change frequencies of these sub-regions in the historical data, calculating the proportion of the number of change times based on the change frequencies, comparing the proportion of the number of change times with the threshold value to obtain the sub-regions with more change times, i.e., the sub-regions to be analyzed, and analyzing based on the change time points of the sub-regions to be analyzed in the historical data to judge whether there is a regular change in the time series of the sub-regions to be analyzed, and obtaining the regularly varying sub-regions. Thus, it is possible to more deeply understand the change characteristics of these survey sub-regions, formulate more specific survey calibration strategies for these regions, and improve the pertinence of survey calibration.

[0053] (3) By obtaining the regularly varying sub-regions and the corresponding optimized values of the survey period, integrating the regularly varying sub-regions based on the optimized values of the survey period, and formulating survey calibration strategies for the integrated region and the regularly varying sub-regions other than the integrated region, the cost of survey calibration is reduced. By optimizing the survey period and integrating the survey regions, the reasonable allocation of survey calibration resources, the improvement of survey efficiency calibration, and the guarantee of survey accuracy are realized. Description of the Drawings

[0054] The present invention will be further described below with reference to the accompanying drawings.

[0055] Figure 1 is a flowchart of a geographic information survey calibration method of the present invention;

[0056] Figure 2It is a flowchart for obtaining a change judgment value in a geographic information survey and calibration method of the present invention;

[0057] Figure 3 It is a flowchart of a geographic information survey and calibration system of the present invention. Detailed implementation manners

[0058] Next, the technical solutions of the present invention will be clearly and completely described in conjunction with the accompanying drawings and specific embodiments.

[0059] Embodiment 1:

[0060] As Figure 1 and Figure 2 shown, a geographic information survey and calibration method described in an embodiment of the present invention specifically includes the following steps:

[0061] Step 1: Obtain the survey data of the geographic area to be surveyed, analyze it, and calculate to obtain a change judgment value;

[0062] In some embodiments, the geographic area to be surveyed is divided into a number of survey sub-areas in a grid format, a preset survey time period is set, and the survey time period is divided into a number of survey sub-time periods, and the start time point of each survey sub-time period is used as the survey time point;

[0063] Among them, the survey time period is set by those skilled in the art according to experience;

[0064] In each survey sub-area, obtain the survey data at each survey time point, where the survey data includes but is not limited to topographic data, vegetation data, hydrological data, and building data;

[0065] In each survey sub-area, compare the survey data obtained at two adjacent survey time points. If the survey information at two adjacent survey time points is different, it is marked as a changed survey time point. If the survey information at two adjacent survey time points is the same, it is marked as an unchanged survey time point;

[0066] It should be noted that the starting point of the survey time period is the initial survey time point (i.e., the first survey time point), and the survey data obtained at the first initial survey time point is compared with the original survey data;

[0067] Obtain the numerical value of the number of changed survey time points, and calculate the ratio of the numerical value of the number of changed survey time points to the numerical value of the number of survey time points to obtain the proportion of the number of changed time points;

[0068] It should be noted that the meaning reflected by the proportion of the number of time points with changes is as follows: The time points with changes indicate the survey time points where data changes occur during the survey period. The larger the proportion of the number of time points with changes, the more frequent the changes occur during the survey period, and the higher the degree of change in the surveyed sub-region during the survey period;

[0069] Obtain the survey time points with changes, mark the consecutive survey time points with changes as groups of survey time points with changes, obtain the value of the number of groups of survey time points with changes, and calculate the ratio of the value of the number of groups of survey time points with changes to the value of the number of survey time points with changes to obtain the proportion of the distribution of time points with changes;

[0070] It should be noted that the meaning reflected by the proportion of the distribution of time points with changes is as follows: The proportion of the distribution of time points with changes represents the distribution of time points with changes during the survey period. The fewer the groups of time points with changes, the stronger the continuity of the time points with changes during the survey period, and the higher the degree of change in the surveyed sub-region during the survey period;

[0071] Extract the maximum value of the number of survey time points contained in the group of survey time points with changes, and calculate the ratio of it to the value of the number of survey time points with changes to obtain the proportion of the time points with the largest consecutive number;

[0072] It should be noted that the meaning reflected by the proportion of the time points with the largest consecutive number is as follows: The proportion of the time points with the largest consecutive number represents the continuity of the time points with changes during the survey period. The larger the proportion of the time points with the largest consecutive number, the stronger the persistence of the time points with changes during the survey period, and the higher the degree of change in the surveyed sub-region during the survey period;

[0073] Substitute into the formula , and calculate to obtain the change judgment value BH. Among them, GS represents the proportion of the number of time points with changes, LX represents the proportion of the time points with the largest consecutive number, FB represents the proportion of the distribution of time points with changes, and a1, a2, and a3 are weight coefficients. The value of a1 is 0.58, the value of a2 is 0.20, and the value of a3 is 0.22;

[0074] It should be noted that the meaning reflected by the change judgment value BH is as follows: The change judgment value is calculated from three values: the proportion of the number of time points with changes, the proportion of the time points with the largest consecutive number, and the proportion of the distribution of time points with changes. If both the proportion of the number of time points with changes and the proportion of the time points with the largest consecutive number are relatively high, while the proportion of the distribution of time points with changes is relatively low, this may indicate that the surveyed sub-region has experienced continuous and frequent changes during the survey period, and these changes are mainly concentrated in one or a few time periods;

[0075] Step 2: Compare the change judgment value with the change judgment threshold to obtain the sub-region with a large degree of change;

[0076] In some embodiments, a change judgment value for each surveyed sub-region is obtained and compared with a change judgment threshold value. The change judgment threshold value is a critical value used to judge the degree of change of the corresponding surveyed sub-region, and is set by those skilled in the art based on the summary of historical experimental data for multiple times;

[0077] If the change judgment value is less than or equal to the change judgment threshold value, it indicates that the degree of change of the surveyed sub-region is small, and a small change degree signal is generated;

[0078] Based on the generated small change degree signal, the surveyed sub-region corresponding to the generated small change degree signal is obtained, and its reasons for change are analyzed. The reasons for change include but are not limited to: mistakes made by technicians during the survey process;

[0079] If the change judgment value is greater than the change judgment threshold value, it indicates that the degree of change of the surveyed sub-region is large, and a large change degree signal is generated;

[0080] Based on the generated large change degree signal, the surveyed sub-region corresponding to the generated large change degree signal is obtained and marked as a large change degree sub-region;

[0081] The technical solution of the embodiment of the present invention is mainly as follows: First, by obtaining the survey data of the surveyed sub-region corresponding to each survey time point during the survey period, the survey data are compared to obtain the survey time points with changes. Based on the survey time points with changes, the proportion of the number of time points with changes, the proportion of the distribution of time points with changes, and the proportion of the time points with the largest continuous number are calculated, and the calculated proportion of the number of time points with changes, the proportion of the distribution of time points with changes, and the proportion of the time points with the largest continuous number obtained from the survey time points with changes are substituted into the formula for data processing to calculate the change judgment value. The calculated change judgment value is compared with the threshold value to judge the degree of change of the corresponding surveyed sub-region. Thus, by combining multiple change indicators and weight coefficients, the degree of change of the surveyed sub-region can be evaluated more comprehensively and accurately, and these regions can be preferentially surveyed and calibrated in subsequent surveys, which helps to optimize the allocation of survey resources and improve the efficiency of survey calibration.

[0082] Embodiment 2:

[0083] Based on Embodiment 1, the method for calibrating geographic information survey described in the embodiment of the present invention specifically further includes the following steps:

[0084] Step 3: Based on the obtained large change degree sub-regions, obtain the survey change information of the large change degree sub-regions of historical data, obtain the proportion of the number of change times in historical data, and judge the change frequency;

[0085] In some embodiments, a sub-region with a large degree of change is obtained, the number of changes corresponding to the sub-region with a large degree of change in the historical data is extracted, and the ratio of the number of changes to the total number of surveys in the historical data is processed to obtain the ratio of the number of changes;

[0086] The ratio of the number of changes is compared with the threshold ratio of the number of changes, where the threshold ratio of the number of changes is set by those skilled in the art based on the summary of historical experimental data;

[0087] If the ratio of the number of changes is less than or equal to the threshold ratio of the number of changes, it indicates that the number of changes in this sub-region in the historical data is small, and a low change frequency signal is generated;

[0088] If the ratio of the number of changes is greater than the threshold ratio of the number of changes, it indicates that the number of changes in this sub-region in the historical data is large, and a high change frequency signal is generated;

[0089] Step Four: Based on the signal with a large number of changes, obtain the sub-region to be analyzed, obtain the change time points, and conduct analysis to obtain the regularly changing sub-region;

[0090] In some embodiments, based on the generated high change frequency signal, obtain the survey sub-region corresponding to the high change frequency generation, and mark it as the sub-region to be analyzed;

[0091] For each sub-region to be analyzed, obtain the time points when the survey data changes in the historical data, and mark them as change time points;

[0092] Calculate the difference between adjacent change time points to obtain the adjacent time difference, sum up all the adjacent time differences and take the average to obtain the average adjacent time difference;

[0093] Calculate the difference between each of all the adjacent time differences and the average adjacent time difference, and take the absolute value of the difference to obtain the absolute deviation value of the adjacent time difference;

[0094] Compare the absolute deviation value of the adjacent time difference with the absolute deviation threshold of the adjacent time difference, where the absolute deviation threshold of the adjacent time difference is set by those skilled in the art based on the summary of historical experimental data;

[0095] If the absolute deviation value of the adjacent time difference is less than the absolute deviation threshold of the adjacent time difference, a small deviation signal is generated. If the absolute deviation value of the adjacent time difference is greater than or equal to the absolute deviation threshold of the adjacent time difference, a large deviation signal is generated;

[0096] Obtain the number value of the generated small deviation signal and the number value of the generated large deviation signal, and sum them up to obtain the total number. Process the ratio of the number value of the generated small deviation signal to the total number to obtain the ratio of the number of small deviations;

[0097] Compare the ratio of the number of small deviations to the threshold of the ratio of the number of small deviations, where the threshold of the ratio of the number of small deviations is set by those skilled in the art based on historical experimental data from multiple experiments;

[0098] If the ratio of the number of small deviations is greater than the threshold of the ratio of the number of small deviations, generate a regular signal; if the ratio of the number of small deviations is less than or equal to the threshold of the ratio of the number of small deviations, generate an irregular signal;

[0099] Based on the generated regular signal, obtain the corresponding sub-region to be analyzed and mark it as a regularly changing sub-region;

[0100] The technical solution of the embodiment of the present invention mainly includes: after obtaining the sub-regions with large change degrees, analyze the change frequencies of these sub-regions in historical data. Based on the change frequencies, calculate the ratio of the number of change times, compare the ratio of the number of change times with the threshold, obtain the sub-regions with more change times, that is, the sub-regions to be analyzed, and based on the change time points of the sub-regions to be analyzed in historical data, and conduct analysis to determine whether there is a regular change in the time series of the sub-regions to be analyzed, and obtain the regularly changing sub-regions, so as to more deeply understand the change characteristics of these survey sub-regions, formulate more specific survey calibration strategies for these regions, and improve the pertinence of survey calibration.

[0101] Embodiment 3

[0102] Based on Embodiment 1 and Embodiment 2, a geographic information survey calibration method described in an embodiment of the present invention specifically further includes the following steps:

[0103] Step Five: Based on the obtained regularly changing sub-regions, obtain an optimized survey period value, and integrate the regularly changing sub-regions to obtain an integrated region;

[0104] In some embodiments, obtain the regularly changing sub-regions, extract the minimum value of the corresponding adjacent time difference in the regularly changing sub-regions, and mark it as the optimized survey period value;

[0105] Extract the minimum value A and the maximum value B in the optimized survey period value, preset an interval threshold N, and group the optimized survey period value based on the minimum value A, the maximum value B and the preset interval threshold N, where the number of groups is ;

[0106] Exemplarily, the grouping range of the optimized survey period value is: the first group [A, A + N], the second group [A + N, A + 2N]... the (N - 1)th group [A + (GS - 2)*N, A + (GS - 1)*N], the Nth group [A + (GS - 1)*N, B];

[0107] Obtain the regularly varying sub-regions corresponding to the optimized values of the survey cycle for each group and the individual values, and obtain the groups with individual values greater than 1, which are marked as groups to be integrated;

[0108] Integrate adjacent regularly varying sub-regions in the groups to be integrated to obtain an integrated region, and obtain the minimum optimized value of the survey cycle corresponding to the regularly varying sub-region in the integrated region;

[0109] Among them, adjacent regularly varying sub-regions refer to: vertically adjacent sub-regions and horizontally adjacent sub-regions

[0110] It should be noted that for the integrated region, survey calibration is carried out at intervals of the minimum optimized value of the survey cycle, so that the task of survey calibration can be concentrated, reducing the movement and waiting time of survey personnel, optimizing the allocation of survey resources, and improving survey efficiency;

[0111] For the remaining regularly varying sub-regions other than the integrated region, survey calibration is carried out at intervals of the optimized value of the survey cycle, so that key changes can be captured more efficiently and ineffective surveys are reduced;

[0112] The technical solution of the embodiment of the present invention is mainly: by obtaining regularly varying sub-regions and obtaining the corresponding optimized values of the survey cycle, integrating the regularly varying sub-regions based on the optimized values of the survey cycle, and formulating survey calibration strategies for the integrated region and the regularly varying sub-regions other than the integrated region, thereby reducing the cost of survey calibration. By optimizing the survey cycle and integrating the survey region, the reasonable allocation of survey calibration resources, the improvement of survey efficiency calibration, and the guarantee of survey accuracy are realized.

[0113] Embodiment 4:

[0114] Based on Embodiments 1, 2, and 3, as Figure 3 shown, a geographic information survey calibration system described in an embodiment of the present invention specifically includes:

[0115] Survey data acquisition and processing module: acquire survey data of the geographic information area to be surveyed, analyze it, and calculate a change judgment value;

[0116] Change degree judgment module: compare the change judgment value with the change judgment threshold to obtain sub-regions with large change degrees;

[0117] Change frequency acquisition module: based on the obtained sub-regions with large change degrees, acquire the survey change information of the sub-regions with large change degrees in historical data, obtain the ratio of the number of changes in historical data, and judge the change frequency;

[0118] Regularity judgment module: Based on the signals with high change frequency, obtain the sub-region to be analyzed, obtain the change time points, and conduct analysis to obtain the regularly changing sub-region;

[0119] Region integration module: Based on the obtained regularly changing sub-region, obtain the optimized value of the survey period, and integrate the regularly changing sub-region to obtain the integrated region.

[0120] The setting of the magnitude of the above threshold is for the convenience of comparison. Regarding the magnitude of the threshold, it depends on the amount of sample data and the base quantity set by those skilled in the art for each group of sample data; for example: in the actual obtaining process, there are many groups of ratios of the number of change time points, ratios of the time points of consecutive maximum numbers, and ratios of the distribution of change time points. Process these ratios of the number of change time points, ratios of the time points of consecutive maximum numbers, and ratios of the distribution of change time points for many groups to obtain the change judgment values of the corresponding groups. The staff evaluates the change degree of the survey sub-region based on these change judgment values of many groups, thereby obtaining a corresponding relationship between the change judgment value and the change degree of the survey sub-region. Then, based on the change degree of the survey sub-region, deduce and divide the threshold of the change judgment value, thereby obtaining the change judgment threshold. Compare the obtained different change judgment values with the change judgment threshold, and the recognition of the change degree of the survey sub-region corresponding to the change judgment value is completed.

[0121] The above has described the embodiments of the present invention in detail, but the content described is only the preferred embodiments of the present invention and cannot be considered as limiting the scope of implementation of the present invention. All equivalent changes and improvements made according to the scope of the application of the present invention should still fall within the scope covered by the patent of the present invention.

Claims

1. A geographic information survey and calibration method, characterized in that: The specific steps include: Step 1: Obtain survey data of the geographic area to be surveyed, analyze it, and calculate the change judgment value; Step 2: Compare the change judgment value with the change judgment threshold to obtain the sub-region with the largest change degree; Step 3: Based on the obtained sub-region with a large degree of change, obtain the survey change information of the sub-region with a large degree of change in the historical data, obtain the value of the proportion of the number of changes in the historical data, and compare the value of the proportion of the number of changes with the threshold value of the proportion of the number of changes to generate a high-frequency change signal; Step 4: Based on the high-frequency change signal, obtain the sub-region to be analyzed, obtain the change time point, and perform analysis to obtain the sub-region with regular changes; The process of obtaining the regularly changing sub-regions is as follows: Obtaining an absolute deviation value of adjacent time differences, and comparing the absolute deviation value of adjacent time differences with an absolute deviation threshold of adjacent time differences; If the absolute deviation value of the adjacent time difference is less than the absolute deviation threshold of the adjacent time difference, a small deviation signal is generated; if the absolute deviation value of the adjacent time difference is greater than or equal to the absolute deviation threshold of the adjacent time difference, a large deviation signal is generated; Obtain the number of generated small deviation signals and the number of generated large deviation signals, sum them up to obtain the total number value, perform ratio processing on the number of generated small deviation signals and the total number value to obtain the ratio of small deviation numbers; Compare the small deviation number ratio value with the small deviation number ratio threshold; If the value of the small deviation ratio is greater than the small deviation ratio threshold, a regular signal is generated. Based on the generated regular signal, the corresponding sub-region to be analyzed is obtained and marked as a sub-region with regular changes; Step 5: Based on the obtained regularly changing sub-regions, obtain the optimized value of the survey period, and integrate the regularly changing sub-regions to obtain the integrated region; The process of obtaining the integrated area is: Extract the minimum value of the adjacent time difference corresponding to the regularly changing sub-area and mark it as the survey cycle optimization value; Extract the minimum value A and the maximum value B in the survey cycle optimization value, preset the interval threshold N, and group the survey cycle optimization value based on the minimum value A, the maximum value B and the preset interval threshold N, where the number of groups is ; Obtain the regularly changing sub-areas and numerical values ​​corresponding to the survey cycle optimization value of each group, obtain the groups with numerical values ​​greater than 1, and mark them as groups to be integrated; Adjacent sub-regions with regular changes in the group to be integrated are integrated to obtain an integrated region.

2. A geographic information survey and calibration method according to claim 1, characterized in that: The change judgment value acquisition process is as follows: Obtain the percentage of time points with changes, the percentage of time points with the maximum number of consecutive changes, and the percentage of distribution of time points with changes; Divide the geographical area to be surveyed into a number of survey sub-areas in a grid format, preset a survey period, divide the survey period into a number of survey sub-periods, and take the start time point of each survey sub-period as the survey time point; In each survey sub-area, obtaining survey data at each survey time point; In each survey sub-area, the survey data obtained at two adjacent survey time points are compared. If the survey information of the two adjacent survey time points is different, it is marked as a survey time point with changes; Obtain the number of survey time points with changes, calculate the ratio of the number of survey time points with changes to the number of survey time points, and obtain the ratio of the number of time points with changes; Obtaining a survey time point with changes, marking consecutive survey time points with changes as a survey time point group with changes, obtaining a value of the survey time point group with changes, calculating a ratio between the value of the survey time point group with changes and the value of the survey time point with changes, and obtaining a distribution ratio of the time points with changes; Extract the maximum value of the number of survey time points in the survey time point group with changes, calculate the ratio of the maximum number of survey time points with changes, and obtain the ratio of the continuous maximum number of time points; Substitute into the formula , the change judgment value BH is calculated, where GS represents the proportion of the number of time points with changes, LX represents the proportion of the continuous maximum number of time points, FB represents the distribution proportion of the time points with changes, and a1, a2, and a3 are weight coefficients.

3. A geographic information survey and calibration method according to claim 1, characterized in that: The process of obtaining the sub-region with large variation degree is as follows: Obtaining a change judgment value of each survey sub-area, and comparing the change judgment value with a change judgment threshold; If the change judgment value is greater than the change judgment threshold, a large change degree signal is generated; Based on the generated large change degree signal, a survey sub-region corresponding to the generated large change degree signal is obtained and marked as a large change degree sub-region.

4. A geographic information survey and calibration method according to claim 1, characterized in that: The process of generating a high-frequency signal is as follows: Obtain the sub-region with the largest change degree, extract the number of changes corresponding to the sub-region with the largest change degree in the historical data, perform ratio processing on the number of changes and the total number of surveys in the historical data, and obtain the ratio of the number of changes; Compare the change times ratio value with the change times ratio threshold; If the change frequency ratio value is greater than the change frequency ratio threshold, a high change frequency signal is generated.

5. A geographic information survey and calibration method according to claim 1, characterized in that: The process of obtaining the absolute deviation value of adjacent time differences is as follows: Obtain the survey sub-area corresponding to the high generation change frequency and mark it as the sub-area to be analyzed; For each sub-area to be analyzed, the time point at which the survey data changes is obtained in the historical data and marked as the change time point; Calculate the difference between adjacent change time points to obtain adjacent time differences, sum and average all adjacent time differences to obtain the mean of adjacent time differences; All adjacent time differences are calculated separately from the adjacent time difference mean, and the absolute value of the difference is taken to obtain the adjacent time difference absolute deviation value.

6. A geographic information survey and calibration system, characterized in that: The system includes: Survey data acquisition and processing module: obtain survey data of the geographic information area to be surveyed, analyze it, and calculate the change judgment value; Change degree judgment module: compares the change judgment value with the change judgment threshold to obtain the sub-region with the largest change degree; Change frequency acquisition module: based on the acquired sub-areas with large changes, obtain the survey change information of these sub-areas in the historical data, obtain the percentage of the number of changes in the historical data, and compare the percentage of the number of changes with the percentage threshold of the number of changes to generate a high-frequency change signal; Regularity judgment module: based on the high-frequency change signal, obtain the sub-region to be analyzed, obtain the change time point, and perform analysis to obtain the sub-region with regular changes; The process of obtaining the regularly changing sub-regions is as follows: Obtaining an absolute deviation value of adjacent time differences, and comparing the absolute deviation value of adjacent time differences with an absolute deviation threshold of adjacent time differences; If the absolute deviation value of the adjacent time difference is less than the absolute deviation threshold of the adjacent time difference, a small deviation signal is generated; if the absolute deviation value of the adjacent time difference is greater than or equal to the absolute deviation threshold of the adjacent time difference, a large deviation signal is generated; Obtain the number of generated small deviation signals and the number of generated large deviation signals, sum them up to obtain the total number value, perform ratio processing on the number of generated small deviation signals and the total number value to obtain the ratio of small deviation numbers; Compare the small deviation number ratio value with the small deviation number ratio threshold; If the value of the small deviation ratio is greater than the small deviation ratio threshold, a regular signal is generated. Based on the generated regular signal, the corresponding sub-region to be analyzed is obtained and marked as a sub-region with regular changes; Regional integration module: based on the obtained regularly changing sub-regions, the optimization value of the survey period is obtained, and the regularly changing sub-regions are integrated to obtain the integrated region; The process of obtaining the integrated area is: Extract the minimum value of the adjacent time difference corresponding to the regularly changing sub-area and mark it as the survey cycle optimization value; Extract the minimum value A and the maximum value B in the survey cycle optimization value, preset the interval threshold N, and group the survey cycle optimization value based on the minimum value A, the maximum value B and the preset interval threshold N, where the number of groups is ; Obtain the regularly changing sub-areas and numerical values ​​corresponding to the survey cycle optimization value of each group, obtain the groups with numerical values ​​greater than 1, and mark them as groups to be integrated; Adjacent sub-regions with regular changes in the group to be integrated are integrated to obtain an integrated region.

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