Regional hydraulic erosion intensity area data determination method and system based on adjustment

Abstract

The invention discloses a regional hydraulic erosion intensity area data determination method and system based on adjustment, and relates to the field of water and soil conservation, and the method comprises the steps: obtaining the grid areas of a target region under different hydraulic erosion intensity grades in two years, and generating an initial transfer matrix and two initial sum vectors according to the grid areas; by taking the total area as a constraint, performing adjustment processing of normalization, truncation, sorting and replacement on the two initial sum vectors to obtain two sum vectors after adjustment processing; and by taking the two adjustment processed data, the vector and a control proportion threshold as constraints, performing adjustment processing of normalization, truncation, sorting and replacement on the initial transfer matrix to obtain an initial transfer matrix after adjustment processing, and determining the initial transfer matrix after adjustment processing as the water erosion intensity area data of the target area, so as to obtain the water erosion intensity area data of the target area. According to the method, the efficiency and accuracy of regional hydraulic erosion data statistics can be improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of soil and water conservation, and particularly relates to a method and system for determining regional water erosion intensity area data based on adjustment. BACKGROUND

[0002] In order to accurately grasp the annual variation of water loss, the basin management agencies and departments at all levels of provinces and cities regularly carry out regional water loss monitoring work, and comprehensively statistics the relevant data of regional water loss. Among them, water erosion, as the main type of water loss, has the most extensive distribution. However, in the process of making regional water erosion intensity grid area transfer matrix, due to the influence of regional land area value control, remote sensing and geographic information data characteristics and grid processing method, as well as the size of statistical unit and other factors, a series of complex operations such as chart data conversion, significant figure retention and adjustment are involved. At present, most of the processing methods mainly rely on data normalization overall scaling, limited decimal rounding and manual adjustment process, but these methods have the problems of long operation time, strong artificial subjectivity and poor result repeatability, which seriously restricts the further improvement of the efficiency and accuracy of regional water erosion data statistics. SUMMARY

[0003] The purpose of the present application is to provide a method and system for determining regional water erosion intensity area data based on adjustment, which can improve the efficiency and accuracy of regional water erosion intensity area data statistics.

[0004] To achieve the above purpose, the present application provides the following solutions.

[0005] In a first aspect, the present application provides a method for determining regional water erosion intensity area data based on adjustment, comprising: determining the total area of a target region; obtaining the grid area of the target region under different water erosion intensity levels in two years, and generating an initial transfer matrix and two initial sum vectors according to the grid area; one initial sum vector corresponds to one year; the initial transfer matrix is a matrix generated by taking the grid area under different water erosion intensity levels in one year of the two years as rows and the grid area under different water erosion intensity levels in the other year of the two years as columns; the initial sum vector is the grid area under different water erosion intensity levels; under the constraint of the total area, the two initial sum vectors are subjected to adjustment processing of normalization, truncation, sorting and return, to obtain two adjusted sum vectors; under the constraint of the two adjusted sum vectors and a control proportion threshold, the initial transfer matrix is subjected to adjustment processing of normalization, truncation, sorting and return, to obtain an adjusted initial transfer matrix, and the adjusted initial transfer matrix is determined as the water erosion intensity area data of the target region.

[0006] In the second aspect, the present application provides a regional water erosion intensity area data determination system based on adjustment, including: a determination module for determining the total area of ​​the target area; an acquisition module for acquiring the grid area of ​​the target area under different water erosion intensity levels in two years, and generating an initial transfer matrix and two initial sum vectors based on the grid area; one initial sum vector corresponds to one year; the initial transfer matrix is ​​generated with the grid area under different water erosion intensity levels of one of the two years as rows and the grid area under different water erosion intensity levels of the other of the two years as columns matrix; the initial sum vector is the grid area under different water erosion intensity levels; the first adjustment processing module is used to normalize, truncate, sort and replace the two initial sum vectors with the total area as a constraint, and obtain two adjusted sum vectors; the second adjustment processing module is used to normalize, truncate, sort and replace the initial transfer matrix with the two adjusted sum vectors and the control ratio threshold as constraints, and obtain the initial transfer matrix after adjustment, and determine the initial transfer matrix after adjustment as the water erosion intensity area data of the target area.

[0007] According to the specific embodiments provided in this application, this application has the following technical effects: The present application provides a method for determining regional water erosion intensity area data based on adjustment. By adjusting two initial sum vectors through normalization, truncation, sorting and replacement, it is possible to quickly and accurately achieve that the sum of the grid areas under different water erosion intensity levels in the target area in two years is the same as the total area of ​​the target area. Among them, normalization ensures that the final calculated area sum is the same. Truncation, sorting and replacement can quickly fill in the normalized initial sum vector, thereby quickly and accurately obtaining the adjusted sum vector. Further, the initial transfer matrix is ​​adjusted through normalization, truncation, sorting and replacement, which can quickly and accurately obtain the water erosion intensity area data of the target area in two years with different water erosion intensity levels, thereby improving the efficiency and accuracy of the statistics of the water erosion intensity area data of the target area. BRIEF DESCRIPTION OF THE DRAWINGS

[0008] In order to more clearly illustrate the technical solutions in the embodiments of the present application or related technologies, the following briefly introduces the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0009] Figure 1 A flowchart of a method for determining regional hydraulic erosion intensity area data based on adjustment is provided in one embodiment of the present application.

[0010] Figure 2 A schematic structural diagram of a system for determining regional hydraulic erosion intensity area data based on adjustment provided in another embodiment of the present application. DETAILED DESCRIPTION

[0011] The following will be combined with the drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0012] In general statistical work, rounding to significant figures is a common practice. However, for statistical data under total control, this method can cause deviations in the statistical data, resulting in discrepancies between the adjusted statistical data and the control total. Since rounding is based on half the magnitude of the last digit, rounding is most effective when the discarded portion of the statistical data is equal to or slightly greater than half the magnitude of the last digit, inevitably resulting in the processed statistical data sum being greater than the control total. Conversely, rounding is most effective when the discarded portion of the statistical data is slightly less than half the magnitude of the last digit, inevitably resulting in the processed statistical data sum being less than the control total. This requires additional processing to eliminate this discrepancy. However, this additional processing typically involves manual balancing of the statistical data, which is time-consuming, subjective, and lacks reproducibility, hindering the efficiency and accuracy of regional hydraulic erosion data statistics. This application adopts a method for determining regional hydraulic erosion intensity area data based on adjustment, which improves the efficiency and accuracy of regional hydraulic erosion data statistics.

[0013] In order to make the above-mentioned purposes, features and advantages of the present application more obvious and easy to understand, the present application is further described in detail below with reference to the accompanying drawings and specific implementation methods.

[0014] In an exemplary embodiment, Figure 1 As shown, a method for determining regional water erosion intensity area data based on adjustment is provided. The method is executed by a computer device, and can be executed separately by a computer device such as a terminal or a server, or can be executed jointly by a terminal and a server. In the embodiment of the present application, the method is applied to a server as an example for explanation, including the following steps S1 to S4.

[0015] Step S1: Determine the total area of ​​the target region.

[0016] Specifically, the total area of the target region is determined by a government service page in a relevant official website. For example, the land area of the target region is queried as 2030 km 2 , which is the total area of the target region under different water erosion intensity levels. The total area is used as a control value.

[0017] Step S2: Obtain the raster area of the target region under different water erosion intensity levels in two years, and generate an initial transition matrix and two initial sum vectors according to the raster area; one initial sum vector corresponds to one year; the initial transition matrix is a matrix generated by taking the raster area under different water erosion intensity levels in one of the two years as the row and the raster area under different water erosion intensity levels in the other of the two years as the column; the initial sum vector is the raster area under different water erosion intensity levels.

[0018] Further, the initial sum vector includes a first initial sum vector and a second initial sum vector; step S2 specifically includes steps S21-S25.

[0019] Step S21: Obtain the raster area of the target region under different water erosion intensity levels in two years.

[0020] Step S22: Determine the raster area of the target region under different water erosion intensity levels in the first year and the raster area of the target region under different water erosion intensity levels in the second year according to the area.

[0021] Specifically, the m-year (first year) and n-year (second year) (m

[0022] Step S23: Generate a first initial sum vector according to the raster area of the target region under different water erosion intensity levels in the first year.

[0023] Specifically, the raster area of the target region under different water erosion intensity levels in the m-year is written as a 1-row 6-column vector as the first initial sum vector (m-year, unit: km 2 ) is: [1803.6047, 206.2629, 8.1009, 3.4521, 3.7518, 5.3054].

[0024] Step S24: Construct a second initial sum vector according to the raster area of the target region under different water erosion intensity levels in the second year.

[0025] Specifically, the grid areas of the target region in different water erosion intensity levels for n years are written into a 1-row 6-column vector as a second initial sum vector (n years, unit: km 2 ) as: [1805.9985, 202.0419, 7.9193, 5.0195, 3.6187, 5.2295].

[0026] Since there may be some differences between the two periods of water erosion factor grid data, the ranges of the two periods of water erosion intensity maps may not completely overlap, and the grid areas may not be completely equal.

[0027] Step S25: generating an initial transition matrix according to the grid areas of the target region in different water erosion intensity levels in the first year and the grid areas of the target region in different water erosion intensity levels in the second year.

[0028] Specifically, according to the water erosion intensity maps of the target region in the mth year (the first year) and the nth year (the second year) (m

[0029] The water erosion intensity code is two digits, such as micro, mild, moderate, strong, extremely strong, and severe, which are represented by numbers 11, 12, 13, 14, 15, and 16, respectively. The grid data of the target region in the mth year can be multiplied by 100 and then added to the grid data of the target region in the nth year to obtain a four-digit code, which can clearly indicate the water erosion intensity conversion relationship from the mth year to the nth year. Then, through unique value statistics, 6x6=36 water erosion intensity conversion code corresponding grid quantities (each grid size is 10m x 10m) are divided by 10000, and then filled into the square matrix, which is the initial transition matrix (unit: km 2 ), and the initial transition matrix is as follows.

[0030] .

[0031] According to the initial transition matrix, a statistical table of the initial transition matrix is generated, as shown in Table 1.

[0032] Table 1: Statistical table of the initial transition matrix

[0033] Since there are differences between the two years of water erosion intensity grid data, the sum of the initial transition matrix is 2029.8174, which is not equal to 2030.

[0034] Step S3: normalizing, truncating, sorting, and returning adjustment processing of the two initial sum vectors with total area as a constraint to obtain two adjustment-processed sum vectors.

[0035] Furthermore, step S3 specifically includes steps S31 to S35.

[0036] Step S31: for each initial sum vector, normalize the initial sum vector according to the total area to obtain a normalized sum vector.

[0037] Specifically, according to the total area of ​​2030 obtained in step S1, the initial sum vector is normalized, and each element in the initial sum vector is multiplied by the total area 2030 divided by the sum of the elements in the initial sum vector as a proportional coefficient to obtain a normalized sum vector.

[0038] Taking year m as an example, the first initial sum vector is normalized to obtain the normalized first initial sum vector (year m, unit: km 2 , rounded to 4 decimal places) is: [1803.1803, 206.2144, 8.0990, 3.4513, 3.7509, 5.3042].

[0039] The second initial sum vector is normalized to obtain the normalized second initial sum vector (nth year, unit: km 2 , rounded to 4 decimal places) is: [1806.1521, 202.0591, 7.9200, 5.0199, 3.6190, 5.2299].

[0040] Step S32: truncating the normalized sum vector according to a preset number of decimal places to obtain a residual vector and a reference sum vector corresponding to the normalized sum vector.

[0041] Step S33: Determine the minimum unit of measurement according to the preset number of decimal places.

[0042] Step S34: Calculate the first quantity of the minimum measurement unit based on the sum of the elements in the normalized sum vector, the sum of the elements in the reference sum vector, and the minimum measurement unit.

[0043] Specifically, the normalized sum vector is truncated at two decimal places, based on the requirement of retaining two decimal places, to generate the reference sum vector and the residual vector. Because two decimal places are retained, the minimum unit of measurement is 0.01 (for example, if three decimal places are retained, the minimum unit of measurement is 0.001). The formula for the first number of replacements is then used to calculate the number of replacements required to normalize the first and second initial sum vectors.

[0044] Furthermore, the calculation formula for putting back the first quantity of the minimum measurement unit is as follows.

[0045] .

[0046] in, To replace the first quantity of the smallest unit of measurement; is the sum of the elements in the normalized sum vector; is the sum of the elements in the base and vector; The smallest unit of measurement.

[0047] Step S35: Taking the total area as a constraint, sorting and replacing the first quantity of the minimum measurement unit, the benchmark sum vector and the residual vector are adjusted to obtain the sum vector after adjustment.

[0048] Furthermore, step S35 specifically includes steps S351 to S353.

[0049] Step S351: sorting the elements in the residual vector from large to small according to the sizes of the elements in the residual vector to obtain a sorted residual vector.

[0050] Step S352: Determine the replacement order of the elements in the base sum vector corresponding to the elements in the sorted residual vector, using the first number of the smallest measurement unit as the replacement number and the order of the elements in the sorted residual vector as the replacement order.

[0051] Step S353: Using the total area as a constraint, replace the minimum measurement unit in the order in which the elements in the benchmark sum vector are replaced to obtain the sum vector after adjustment.

[0052] Specifically, according to the descending order of the elements in the residual vector and the number of minimum measurement units determined in step S34, one minimum measurement unit is added to the corresponding position elements in the reference sum vector in sequence until the end. The result is the sum vector after adjustment processing, which is used as the control vector for the row and column sums of the initial transfer matrix.

[0053] Through the above step 3, the first initial sum vector (mth year, unit: km 2 ) and the second initial sum vector (nth year, unit: km 2 ) is adjusted. The sum vector corresponding to the first initial sum vector after adjustment is: [1803.18, 206.22, 8.10, 3.45, 3.75, 5.30], and the sum vector corresponding to the second initial sum vector after adjustment is: [1806.15, 202.06, 7.92, 5.02, 3.62, 5.23]. The total is 2030, which can be closed.

[0054] However, if the rounding method is used for the first initial sum vector (mth year, unit: km 2 ) and the second initial sum vector (nth year, unit: km 2) is processed, and the result after rounding the first initial sum vector is: [1803.18, 206.21, 8.10, 3.45, 3.75, 5.30], where the second element is less by 0.01. The current sum is 2029.99, which is not equal to 2030 and is not closed.

[0055] Step S4: With the two adjusted sum vectors and the control ratio threshold as constraints, the initial transfer matrix is ​​normalized, truncated, sorted and replaced to obtain the initial transfer matrix after adjustment, and the initial transfer matrix after adjustment is determined as the hydraulic erosion intensity area data of the target area.

[0056] Furthermore, step S4 specifically includes steps S41 to S43.

[0057] Step S41: normalizing the initial transfer matrix according to the total area to obtain a normalized transfer matrix.

[0058] Specifically, according to the total area of ​​2030 obtained in step S1, the initial transfer matrix is ​​normalized, and the total area of ​​2030 divided by the sum of the elements in the initial transfer matrix is ​​multiplied by each element of the initial transfer matrix as a proportional coefficient to obtain a normalized transfer matrix. The normalized transfer matrix is ​​as follows.

[0059] .

[0060] This matrix is ​​rounded to 4 decimal places, and the actual sum is 2030. It is not difficult to see that the changes in the elements are not significant.

[0061] Step S42: performing truncation processing on the normalized transfer matrix according to a preset number of decimal places to obtain a reference transfer matrix and a transfer residual matrix corresponding to the normalized transfer matrix.

[0062] Specifically, according to the requirement of retaining 2 decimal places, the normalized transfer matrix is ​​truncated to generate the reference transfer matrix and the transfer residual matrix, which are as follows.

[0063] .

[0064] .

[0065] The reference transfer matrix is ​​expressed to two decimal places, and the transfer residual matrix is ​​expressed after two decimal places, which is rounded off to four decimal places.

[0066] Step S43: Determine the minimum measurement unit according to the preset number of decimal places.

[0067] Step S44: Calculate the second quantity in the minimum measurement unit based on the sum vector after the two adjustment processes, the sum of each row and column of the elements in the benchmark transfer matrix, and the minimum measurement unit; the second quantity in the minimum measurement unit is included in: the quantity of the minimum measurement unit of each row element in the benchmark transfer matrix and the quantity of the minimum measurement unit of each column element in the benchmark transfer matrix.

[0068] Specifically, with 2 decimal places as the preset number of decimal places, according to the minimum measurement unit 0.01 determined by retaining 2 decimal places, the number of minimum measurement units required to be replaced in the normalized transfer matrix is ​​calculated from both the row and column directions using the calculation formula for the second number of minimum measurement units replaced, and written as a row (column) vector of the number of minimum measurement units, as shown below.

[0069] [4, 2, 3, 4, 3, 3].

[0070] [3, 4, 3, 2, 4, 3].

[0071] It can be seen that the number of row (column) elements that need to be put back into the smallest unit of measurement is 19, which is the same.

[0072] Furthermore, the two adjusted sum vectors are the adjusted row sum vector and the adjusted column sum vector respectively.

[0073] The calculation formula for the number of elements in each row of the reference transfer matrix returned to the minimum unit of measurement is as follows.

[0074] .

[0075] The calculation formula for the number of elements in each column of the benchmark transfer matrix returned to the minimum measurement unit is as follows.

[0076] .

[0077] in, is the first The number of row elements returned to the smallest unit of measurement; is the first The first row in the row and vector after adjustment processing corresponding to the row element The value of the element; is the first The sum of row elements; is the first Put the column elements back into the smallest unit of measurement; is the first The first column and vector corresponding to the column element after adjustment The value of the element; is the first The sum of the column elements; The smallest unit of measurement.

[0078] Step S45: Using the two adjusted sum vectors and the control ratio threshold as constraints, sort and replace the second quantity of the replaced minimum measurement unit, the reference transfer matrix, and the transfer residual matrix to obtain an initial transfer matrix after adjustment.

[0079] Furthermore, step S45 specifically includes step S451 and step S452.

[0080] Step S451: Calculate the minimum measurement unit control quantity based on the control ratio threshold and the number of elements in the reference transfer matrix.

[0081] Specifically, the number of minimum measurement units to be replaced should be used to determine whether the area deviation of the original two-period hydraulic erosion intensity map is too large. For example, if the control ratio threshold is set to 60%, and the current transfer matrix is ​​6×6 with a total of 36 elements, 36×60% = 21.6 elements can be calculated. If the number of minimum measurement units to be replaced is less than 21.6, the next adjustment is performed. Otherwise, the original data is judged to be incorrect, and the original two-period hydraulic erosion intensity map needs to be modified or remade, and the initial transfer matrix and two initial sum vectors need to be regenerated for adjustment.

[0082] Step S452: Determine whether the second quantity of the minimum measurement unit is less than the control quantity of the minimum measurement unit; if so, then remove the elements of the corresponding rows and columns of the transfer residual matrix by comparing the rows in which the number of the minimum measurement unit of each row element in the benchmark transfer matrix is ​​0 and the columns in which the number of the minimum measurement unit of each column element in the benchmark transfer matrix is ​​0 to obtain the transferred residual matrix after removal; use the position of the element in the benchmark transfer matrix corresponding to the position of the maximum numerical element in the transferred residual matrix after removal as the replacement position; use the sum vector after two adjustment processes as a constraint, replace the minimum measurement unit to the replacement position, and obtain the benchmark transfer matrix after replacement; replace the number of the minimum measurement unit and the number of the minimum measurement unit for the rows corresponding to the replacement position respectively. The number of minimum measurement units of the column corresponding to the return position is updated by minus 1 to obtain the updated number of rows and columns; the updated number of rows is the number of minimum measurement units of the elements in each row of the updated benchmark transfer matrix; the updated number of columns is the number of minimum measurement units of the elements in each column of the updated benchmark transfer matrix; according to the return position, the corresponding elements in the transfer residual matrix after elimination are eliminated again to obtain the transfer residual matrix after elimination again, and the replacement process is performed again until the updated number of rows and the updated number of columns are both 0, and the replacement is stopped to obtain the initial transfer matrix after adjustment; if not, the statistics of the water erosion intensity area data of the target area are terminated.

[0083] Specifically, after the two adjustments are processed and the vector is determined in step S3, the two-dimensional positioning constraints of the initial transfer matrix rows and columns are performed. First, it is identified that all element positions involved in the rows (columns) with a put-back quantity of 0 are inoperable element positions, and then the elements at the corresponding positions of the transfer residual matrix are eliminated. The position of the maximum value is found in the remaining elements of the transfer residual matrix. Then, a single minimum measurement unit is added to the elements at the corresponding positions of the reference transfer matrix, and this position is synchronously marked as inoperable. The number of row (column) vectors of the minimum measurement units put back is subtracted by 1 in the corresponding rows and columns to update (i.e., the number of the minimum measurement units put back in the rows corresponding to the put-back positions and the number of the minimum measurement units put back in the columns corresponding to the put-back positions are subtracted by 1 and updated). This step is repeated until all elements in the updated row put-back quantity and the updated column put-back quantity are 0 (i.e., the matrix is ​​closed), and the initial transfer matrix after adjustment is obtained, as shown below.

[0084] .

[0085] However, if the normalized transfer matrix is ​​rounded to two decimal places, the rounded initial transfer matrix is ​​as follows.

[0086] .

[0087] The sum of the matrix elements is 2030.03, which does not meet the control value of 2030. Among them, four elements (0.38, 0.49, 1.06, and 1.70) are 0.01 larger than the elements of the adjusted transfer matrix obtained by this method, and one element (0.2) is 0.01 smaller than the elements of the adjusted transfer matrix obtained by this method. Therefore, it is inaccurate.

[0088] The beneficial effects of the method for determining regional hydraulic erosion intensity area data based on adjustment proposed in this application are mainly manifested in: (1) Through the adjustment process of normalization, truncation, sorting and replacement, normalization ensures that the final calculated area sum is the same, and truncation, sorting and replacement can quickly fill in the normalized data, so as to quickly and accurately obtain the adjusted data. Compared with the traditional "rounding" + "manual modification" method, the adjustment work that traditional manual labor takes more than ten or even dozens of hours can be completed in a few seconds, which has a breakthrough improvement in efficiency.

[0089] (2) This method can be widely applied to the one-dimensional row and column vector and two-dimensional square matrix adjustment of remote sensing and geographic information data chart statistics under various total area constraints, such as the statistics of water erosion intensity area and its transfer area at the regional, provincial, municipal and county levels in the field of soil and water conservation. It can effectively support the dynamic monitoring of soil and water loss in the country, timely grasp the status of soil and water loss and changes, and provide data and technical support for government departments at all levels to formulate soil and water conservation plans, design soil and water conservation measures and accelerate the comprehensive prevention and control of soil and water loss.

[0090] (3) This method can also be applied to the statistics of land use classification area and its transfer area in the field of natural resources, the statistics of garden grass area and its transfer area in the field of ecological forestry, etc., to improve the work efficiency of graphic data statistics in land management and ecological forestry management, and reduce the burden on relevant statistical staff.

[0091] Based on the same inventive concept, embodiments of the present application also provide a system for determining regional hydraulic erosion intensity and area data based on adjustment. The implementation solution provided by this system is similar to the implementation solution described in the aforementioned method. Therefore, the specific limitations of one or more embodiments of the system for determining regional hydraulic erosion intensity and area data based on adjustment provided below can be found in the limitations of the method for determining regional hydraulic erosion intensity and area data based on adjustment above, and will not be repeated here.

[0092] In an exemplary embodiment, Figure 2 As shown, a system for determining regional water erosion intensity area data based on adjustment is provided, including: a determination module for determining the total area of ​​a target area; an acquisition module for acquiring the grid areas of the target area under different water erosion intensity levels in two years, and generating an initial transfer matrix and two initial sum vectors based on the grid areas; one initial sum vector corresponds to one year; the initial transfer matrix is ​​a matrix generated with the grid areas under different water erosion intensity levels in one of the two years as rows and the grid areas under different water erosion intensity levels in the other of the two years as columns; the initial sum vectors are the grid areas under different water erosion intensity levels; a first adjustment processing module is used to perform normalization, truncation, sorting and replacement adjustment processing on the two initial sum vectors with the total area as a constraint to obtain two adjusted sum vectors; a second adjustment processing module is used to perform normalization, truncation, sorting and replacement adjustment processing on the initial transfer matrix with the two adjusted sum vectors and a control ratio threshold as constraints to obtain the adjusted initial transfer matrix, and the adjusted initial transfer matrix is ​​determined as the water erosion intensity area data of the target area.

[0093] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.

[0094] Those skilled in the art will appreciate that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the above-mentioned embodiments. In particular, any reference to memory, database, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM may be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM).

[0095] The databases involved in the various embodiments provided herein may include at least one of a relational database and a non-relational database. Non-relational databases may include, but are not limited to, distributed databases based on blockchains. The processors involved in the various embodiments provided herein may include, but are not limited to, general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic units, data processing logic units based on quantum computing, and the like.

[0096] The technical features of the above embodiments can be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0097] This document uses specific examples to illustrate the principles and implementation methods of this application. The description of the above examples is only intended to help understand the method and core concept of this application. At the same time, for those skilled in the art, based on the concept of this application, there may be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting this application.

Claims

1. A method for determining regional water erosion intensity area data based on adjustment, characterized in that: The method for determining regional water erosion intensity area data based on adjustment includes: Determine the total area of ​​the target region; Obtain the grid areas of the target area at different hydraulic erosion intensity levels in two years, and generate an initial transfer matrix and two initial sum vectors based on the grid areas; one initial sum vector corresponds to one year; the initial transfer matrix is ​​a matrix generated with the grid areas at different hydraulic erosion intensity levels in one of the two years as rows and the grid areas at different hydraulic erosion intensity levels in the other of the two years as columns; the initial sum vectors are the grid areas at different hydraulic erosion intensity levels; Taking the total area as a constraint, respectively performing normalization, truncation, sorting, and replacement adjustment processing on the two initial sum vectors to obtain two adjusted sum vectors; The initial transfer matrix is ​​normalized, truncated, sorted and replaced with two adjusted sum vectors and a control ratio threshold as constraints to obtain an adjusted initial transfer matrix, which is then determined as the target area water erosion intensity area data.

2. The method for determining regional water erosion intensity area data based on adjustment according to claim 1, wherein: The initial sum vector includes: a first initial sum vector and a second initial sum vector; Obtain the grid areas of the target area under different water erosion intensity levels in two years, and generate an initial transfer matrix and two initial sum vectors based on the grid areas, specifically including: Obtain the grid area of ​​the target area under different water erosion intensity levels in two years; Determining, based on the grid areas, grid areas of the target area at different water erosion intensity levels in the first year and grid areas of the target area at different water erosion intensity levels in the second year; Generate the first initial sum vector according to the grid areas under different water erosion intensity levels in the target area in the first year; According to the grid areas of the target area at different water erosion intensity levels in the second year, a second initial sum vector is formed; The initial transfer matrix is ​​generated based on the grid areas under different hydraulic erosion intensity levels in the first year of the target area and the grid areas under different hydraulic erosion intensity levels in the second year of the target area.

3. The method for determining regional water erosion intensity area data based on adjustment according to claim 1, wherein: Taking the total area as a constraint, the two initial sum vectors are respectively normalized, truncated, sorted, and replaced to obtain two adjusted sum vectors, specifically including: For each initial sum vector, normalizing the initial sum vector according to the total area to obtain a normalized sum vector; The normalized sum vector is truncated according to a preset number of decimal places to obtain a residual vector and a reference sum vector corresponding to the normalized sum vector; Determine the minimum unit of measurement based on the preset number of decimal places; Calculate the first quantity of the minimum measurement unit according to the sum of the elements in the normalized sum vector, the sum of the elements in the base sum vector, and the minimum measurement unit; Taking the total area as a constraint, an adjustment process of sorting and replacing the first number of replaced minimum measurement units, the reference sum vector, and the residual vector is performed to obtain an adjusted sum vector.

4. The method for determining regional water erosion intensity area data based on adjustment according to claim 3, wherein: Taking the total area as a constraint, performing an adjustment process of sorting and replacing the first quantity of the replaced minimum measurement unit, the reference sum vector, and the residual vector to obtain an adjusted sum vector, specifically comprising: According to the sizes of the elements in the residual vector, the elements in the residual vector are sorted from large to small to obtain a sorted residual vector; Determine the replacement order of the elements in the base sum vector corresponding to the elements in the sorted residual vector, using the first number of the minimum replacement measurement units as the replacement number and the order of the elements in the sorted residual vector as the replacement order; With the total area as a constraint, the minimum measurement unit is replaced in the order of replacing the elements in the benchmark sum vector to obtain the sum vector after adjustment processing.

5. The method for determining regional water erosion intensity area data based on adjustment according to claim 3, wherein: The calculation formula for returning the first quantity of the minimum measurement unit is: ； in, To replace the first quantity of the smallest unit of measurement; is the sum of the elements in the normalized sum vector; is the sum of the elements in the base and vector; The smallest unit of measurement.

6. The method for determining regional water erosion intensity area data based on adjustment according to claim 1, wherein: The initial transfer matrix is ​​normalized, truncated, sorted, and replaced using the two adjusted sum vectors and the control ratio threshold as constraints to obtain the adjusted initial transfer matrix, specifically including: Normalizing the initial transfer matrix according to the total area to obtain a normalized transfer matrix; The normalized transfer matrix is ​​truncated according to a preset number of decimal places to obtain a reference transfer matrix and a transfer residual matrix corresponding to the normalized transfer matrix; Determine the minimum unit of measurement based on the preset number of decimal places; According to the sum vector after two adjustment processes, the sum of each row and column of elements in the benchmark transfer matrix and the minimum measurement unit, calculating the second quantity of the minimum measurement unit; the second quantity of the minimum measurement unit is returned; the second quantity of the minimum measurement unit is returned includes: the quantity of the minimum measurement unit returned to each row element in the benchmark transfer matrix and the quantity of the minimum measurement unit returned to each column element in the benchmark transfer matrix; Taking the two adjusted sum vectors and the control ratio threshold as constraints, the second number of replaced minimum measurement units, the reference transfer matrix and the transfer residual matrix are sorted and replaced to obtain an initial transfer matrix after adjustment.

7. The method for determining regional water erosion intensity area data based on adjustment according to claim 6, characterized in that: Taking the two adjusted sum vectors and the control ratio threshold as constraints, the adjustment process of sorting and replacing the second number of the minimum measurement unit, the reference transfer matrix, and the transfer residual matrix is ​​performed to obtain the initial transfer matrix after adjustment, specifically including: Calculating the minimum measurement unit control quantity based on the control ratio threshold and the number of elements of the reference transfer matrix; Determine whether the second quantity of the minimum measurement unit returned is less than the control quantity of the minimum measurement unit returned; If so, then the elements of the corresponding rows and columns of the transfer residual matrix are removed by replacing the row elements of the reference transfer matrix with the rows of the minimum measurement unit of 0 and replacing the column elements of the reference transfer matrix with the columns of the minimum measurement unit of 0 to obtain the removed transfer residual matrix; The position of the element in the reference transfer matrix corresponding to the position of the element with the largest value in the transfer residual matrix after elimination is used as the replacement position; Using the two adjusted sum vectors as constraints, the minimum measurement unit is placed back to the replacement position to obtain a post-replacement benchmark transfer matrix; Subtract 1 from the number of minimum measurement units of the row and the column corresponding to the replacement position to obtain an updated row replacement number and an updated column replacement number; the updated row replacement number is the number of minimum measurement units of each row element in the updated reference transfer matrix; the updated column replacement number is the number of minimum measurement units of each column element in the updated reference transfer matrix; According to the described putting back position, the corresponding element in the rear transfer residual matrix is ​​eliminated again, the rear transfer residual matrix is ​​eliminated again, and the putting back process is performed again, until the rear row quantity and the rear column quantity after the update are 0, stop putting back, and obtain the initial transfer matrix after the adjustment process; If not, the statistics of the hydraulic erosion intensity area data of the target area will be terminated.

8. The method for determining regional water erosion intensity area data based on adjustment according to claim 6, characterized in that: The two sum vectors after adjustment processing are the row sum vector after adjustment processing and the column sum vector after adjustment processing respectively; The calculation formula for the number of minimum measurement units of each row element in the reference transfer matrix is: ； The calculation formula for the number of elements in each column of the reference transfer matrix returned to the minimum measurement unit is: ； in, is the first The number of row elements is returned to the smallest unit of measurement; is the first The first row in the row and vector after adjustment processing corresponding to the row element The value of the element; is the first The sum of row elements; is the first Put the column elements back into the smallest unit of measurement; is the first The first column and vector corresponding to the column element after adjustment The value of the element; is the first The sum of the column elements; The smallest unit of measurement.

9. A system for determining regional water erosion intensity area data based on adjustment, characterized in that: The regional water erosion intensity area data determination system based on adjustment includes: A determination module, for determining the total area of ​​the target area; An acquisition module is used to obtain the grid areas of the target area under different hydraulic erosion intensity levels in two years, and generate an initial transfer matrix and two initial sum vectors based on the grid areas; one initial sum vector corresponds to one year; the initial transfer matrix is ​​a transfer matrix generated with the grid areas under different hydraulic erosion intensity levels in one of the two years as rows and the grid areas under different hydraulic erosion intensity levels in the other of the two years as columns; the initial sum vectors are the grid areas under different hydraulic erosion intensity levels; A first adjustment processing module is used for performing normalization, truncation, sorting and replacement adjustment processing on the two initial sum vectors respectively with the total area as a constraint to obtain two sum vectors after adjustment processing; The second adjustment processing module is used to perform normalization, truncation, sorting and replacement adjustment processing on the initial transfer matrix with two adjusted sum vectors and a control ratio threshold as constraints to obtain the initial transfer matrix after adjustment processing, and determine the initial transfer matrix after adjustment processing as the water erosion intensity area data of the target area.

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