A Method and System for Determining Regional Hydraulic Erosion Intensity Area Data Based on Adjustment

Abstract

This application discloses a method and system for determining regional hydraulic erosion intensity area data based on adjustment, relating to the field of soil and water conservation. The method includes: obtaining the grid area of ​​the target area under different hydraulic erosion intensity levels in two years, and generating an initial transition matrix and two initial sum vectors based on the grid area; performing adjustment processing on the two initial sum vectors by normalization, truncation, sorting, and replacement, respectively, with the total area as a constraint, to obtain two adjusted sum vectors; performing adjustment processing on the initial transition matrix by normalization, truncation, sorting, and replacement, with the two adjusted sum vectors and a control ratio threshold as constraints, to obtain an adjusted initial transition matrix; and determining the adjusted initial transition matrix as the hydraulic erosion intensity area data of the target area. This application can improve the efficiency and accuracy of regional hydraulic erosion data statistics.

Description

Technical Field

[0001] This application relates to the field of soil and water conservation, and in particular to a method and system for determining the area data of regional hydraulic erosion intensity based on adjustment. Background Technology

[0002] To accurately grasp the annual changes in soil erosion, river basin management agencies and departments at all levels, including provincial and municipal governments, regularly conduct regional soil erosion monitoring and comprehensively collect relevant data. Among these, water erosion, as the main type of soil erosion, has the widest distribution. However, the creation of the regional water erosion intensity raster area transfer matrix involves a series of complex operations, including data conversion, significant figure retention, and adjustment, due to factors such as regional land area numerical control, the characteristics of remote sensing and geographic information data, raster processing methods, and the size of statistical units. Currently, most processing methods rely on data normalization and scaling, rounding of finite decimals, and manual balancing. However, these methods suffer from time-consuming operations, high human subjectivity, and poor repeatability, severely hindering further improvements in the efficiency and accuracy of regional water erosion data statistics. Summary of the Invention

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

[0004] To achieve the above objectives, this application provides the following solution.

[0005] In a first aspect, this application provides a method for determining regional hydraulic 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 hydraulic erosion intensity levels in two years, and generating an initial transition matrix and two initial sum vectors based on the grid area; one initial sum vector corresponds to one year; the initial transition matrix is ​​a matrix generated with the grid area under different hydraulic erosion intensity levels in one of the two years as rows and the grid area 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; with the total area as a constraint, performing adjustment processing on the two initial sum vectors by normalization, truncation, sorting, and replacement respectively to obtain two adjusted sum vectors; with the two adjusted sum vectors and a control ratio threshold as constraints, performing adjustment processing on the initial transition matrix by normalization, truncation, sorting, and replacement to obtain an adjusted initial transition matrix, and determining the adjusted initial transition matrix as the hydraulic erosion intensity area data of the target region.

[0006] Secondly, this application provides a system for determining the area of ​​regional hydraulic erosion intensity based on adjustment, comprising: a determination module for determining the total area of ​​a target area; and an acquisition module for acquiring the grid area of ​​the target area under different hydraulic erosion intensity levels in two years, and generating an initial transition matrix and two initial sum vectors based on the grid areas; one initial sum vector corresponds to one year; the initial transition matrix is ​​generated with the grid area under different hydraulic erosion intensity levels in one of the two years as rows and the grid area under different hydraulic erosion intensity levels in the other of the two years as columns. The matrix; the initial sum vector is the grid area under different hydraulic erosion intensity levels; the first adjustment processing module is used to perform normalization, truncation, sorting and replacement adjustment processing on the two initial sum vectors respectively with the total area as a constraint, to obtain two adjusted sum vectors; the second adjustment processing module is used to perform normalization, truncation, sorting and replacement adjustment processing on the initial transition matrix with the two adjusted sum vectors and the control ratio threshold as constraints, to obtain the adjusted initial transition matrix, and the adjusted initial transition matrix is ​​determined as the hydraulic 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:

[0008] This application provides a method for determining the area data of regional hydraulic erosion intensity based on adjustment. By normalizing, truncating, sorting, and replacing two initial sum vectors, it can quickly and accurately ensure that the sum of the grid areas under different hydraulic erosion intensity levels in two years of the target area is the same as the total area of ​​the target area. Normalization ensures that the final calculated total area is the same. Truncating, sorting, and replacing can quickly fill in the numbers of the normalized initial sum vector, thus quickly and accurately obtaining the adjusted sum vector. Further adjustment of the initial transition matrix by normalizing, truncating, sorting, and replacing can quickly and accurately obtain the area data of different hydraulic erosion intensities in the target area in two years, improving the efficiency and accuracy of the statistical analysis of hydraulic erosion intensity area data of the target area. Attached Figure Description

[0009] To more clearly illustrate the technical solutions in the embodiments of this application or related technologies, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0010] Figure 1 This is a flowchart illustrating a method for determining the area data of regional hydraulic erosion intensity based on adjustment, provided in an embodiment of this application.

[0011] Figure 2 This is a schematic diagram of a system for determining the area data of regional hydraulic erosion intensity based on adjustment, provided in another embodiment of this application. Detailed Implementation

[0012] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0013] In general data statistics, rounding to retain significant figures is the most common method. However, for the statistical analysis of individual data under total control, this method can cause deviations in the statistical data, resulting in the adjusted sum of individual data not closing with the control total. Since the dividing point for rounding is half the last order of magnitude, the rounding effect is best when the discarded portion of the individual data is as much as possible equal to or slightly greater than half the last order of magnitude, inevitably leading to the processed sum of individual data being greater than the control total. Conversely, the discarding effect is best when the discarded portion of the individual data is as much as possible slightly less than half the last order of magnitude, inevitably leading to the processed sum of individual data being less than the control total. This requires additional processing to eliminate this closure error. However, the additional processing typically involves manually balancing the statistical data where it doesn't close, but this method suffers from long processing times, strong subjectivity in balancing, and poor repeatability of results, thus limiting the efficiency and accuracy of regional hydraulic erosion data statistics. This application employs a method for determining the area data of regional hydraulic erosion intensity based on adjustment, which improves the efficiency and accuracy of regional hydraulic erosion data statistics.

[0014] To make the above-mentioned objectives, features and advantages of this application more apparent and understandable, this application will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0015] In one exemplary embodiment, such as Figure 1 As shown, a method for determining the area data of regional hydraulic erosion intensity based on adjustment is provided. This method is executed by a computer device, specifically by a computer device such as a terminal or a server alone, or by a terminal and a server together. In this embodiment, the method is described using a server as an example, including the following steps S1 to S4.

[0016] Step S1: Determine the total area of ​​the target region.

[0017] Specifically, determine the total area of the target area through the government service page on the relevant official website. For example, it is found that the land area of the target area is 2030 km 2 , which is the sum of the areas under different water erosion intensity levels in the target area, and this sum of areas is used as the control value.

[0018] Step S2: Obtain the grid areas of the target area under different water erosion intensity levels for 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 of different water erosion intensity levels in one of the two years as rows and the grid areas of 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.

[0019] Furthermore, the initial sum vector includes: the first initial sum vector and the second initial sum vector; Step S2 specifically includes Steps S21 - S25.

[0020] Step S21: Obtain the grid areas of the target area under different water erosion intensity levels for two years.

[0021] Step S22: Determine the grid areas of the target area under different water erosion intensity levels in the first year and the grid areas of the target area under different water erosion intensity levels in the second year according to the areas.

[0022] Specifically, obtain the water erosion intensity raster maps of the target area in year m (the first year) and year n (the second year) (m < n), and based on the water erosion intensity raster maps of the target area in year m (the first year) and year n (the second year) (m < n), count the grid areas of different levels of water erosion intensity (6 levels such as slight, mild, moderate, strong, extremely strong, and severe) in year m and year n of the target area from the GIS software.

[0023] Step S23: Generate the first initial sum vector according to the grid areas of the target area under different water erosion intensity levels in the first year.

[0024] Specifically, write the grid areas of different water erosion intensity levels in year m of the target area as a 1 - row and 6 - column vector, which is used as the first initial sum vector (in the mth year, unit: km 2 ): [1803.6047, 206.2629, 8.1009, 3.4521, 3.7518, 5.3054].

[0025] Step S24: Construct the second initial sum vector according to the grid areas of the target area under different water erosion intensity levels in the second year.

[0026] Specifically, write the raster areas of different hydraulic erosion intensity grades in the target area for n years as a vector with 1 row and 6 columns, which serves as the second initial sum vector (for the nth year, unit: km 2 ) and it is: [1805.9985, 202.0419, 7.9193, 5.0195, 3.6187, 5.2295].

[0027] Since there may be certain differences in the raster data of the hydraulic erosion factors for the two periods, the ranges of the two-phase hydraulic erosion intensity maps may not completely overlap, and the raster areas are not exactly equal either.

[0028] Step S25: Generate an initial transfer matrix based on the raster areas of different hydraulic erosion intensity grades in the target area for the first year and the raster areas of different hydraulic erosion intensity grades in the target area for the second year.

[0029] Specifically, according to the hydraulic erosion intensity maps of the target area for year m (the first year) and year n (the second year) (m < n), use the overlay assignment processing of the raster calculator in the GIS software to generate a statistical table, and what is obtained is the initial transfer matrix.

[0030] Among them, the hydraulic erosion intensity code is a two-digit number. For example, the 6 grades such as slight, mild, moderate, strong, extremely strong, and severe are represented by the numbers 11, 12, 13, 14, 15, and 16 respectively. The raster data of the hydraulic erosion intensity in the target area for year m can be multiplied by 100 and then added to the raster data of the hydraulic erosion intensity in the target area for year n to obtain a four-digit number code, which can clarify the conversion relationship of the hydraulic erosion intensity of each raster from year m to year n. Then, through unique value statistics, the number of rasters corresponding to 6×6 = 36 hydraulic erosion intensity conversion codes (each raster size is 10m×10m) is divided by 10000, and the corresponding values are filled into the square matrix, which is the initial transfer matrix (unit: km 2 ), and the initial transfer matrix is as follows.

[0031] .

[0032] Generate a statistical table of the initial transfer matrix according to the initial transfer matrix, as shown in Table 1.

[0033] Table 1 Statistical table of the initial transfer matrix

[0034]

[0035] Since there are differences in the raster data of the hydraulic erosion intensity for the two years, the sum of the initial transfer matrix is 2029.8174, which is not equal to 20,300.

[0036] Step S3: Using the total area as a constraint, normalize, truncate, sort, and adjust the two initial sum vectors respectively to obtain two adjusted sum vectors.

[0037] Furthermore, step S3 specifically includes steps S31-S35.

[0038] Step S31: For each initial sum vector, normalize the initial sum vector according to the total area to obtain a normalized sum vector.

[0039] Specifically, based on the total area of ​​2030 obtained in step S1, the initial sum vector is normalized by multiplying each element of the initial sum vector by the sum of the elements in the initial sum vector with the total area of ​​2030 divided by the sum of the elements in the initial sum vector as a scaling factor, thus obtaining the normalized sum vector.

[0040] 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 only) is: [1803.1803, 206.2144, 8.0990, 3.4513, 3.7509, 5.3042].

[0041] The second initial sum vector is normalized to obtain the normalized second initial sum vector (year n, unit: km). 2 (Rounded to 4 decimal places only) is: [1806.1521, 202.0591, 7.9200, 5.0199, 3.6190, 5.2299].

[0042] Step S32: Truncate the normalized sum vector according to the preset number of decimal places to obtain the residual vector and the reference sum vector corresponding to the normalized sum vector.

[0043] Step S33: Determine the minimum unit of measurement based on the preset number of decimal places.

[0044] Step S34: Calculate the first quantity of the smallest unit of measurement with replacement based on the sum of the elements in the normalized sum vector, the sum of the elements in the benchmark sum vector, and the smallest unit of measurement.

[0045] Specifically, with two decimal places as the preset decimal place requirement, the normalized sum vector is truncated at two decimal places to generate the baseline sum vector and the residual vector. Because two decimal places are retained, the smallest unit of measurement is 0.01 (if three decimal places are retained, the smallest unit of measurement is 0.001). Then, the number of units of measurement to be replaced in the first and second normalized initial sum vectors are calculated using the formula for the first number of units of measurement to be replaced.

[0046] Furthermore, the formula for calculating the first quantity of the smallest unit of measurement is as follows.

[0047] .

[0048] in, To replace the first quantity of the smallest unit of measurement; This is the sum of the elements in the normalized sum vector; The sum of the elements in the reference and vector; It is the smallest unit of measurement.

[0049] Step S35: Using the total area as a constraint, sort and adjust the first quantity of the smallest unit of measurement with replacement, the reference and vector and the residual vector, to obtain the adjusted sum vector.

[0050] Furthermore, step S35 specifically includes steps S351-S353.

[0051] Step S351: Sort the elements in the residual vector from largest to smallest according to their size to obtain the sorted residual vector.

[0052] Step S352: Using the first quantity of the smallest unit of measurement to be replaced as the replacement quantity, and the order of the elements in the sorted residual vector as the replacement order, determine the reference corresponding to the elements in the sorted residual vector and the replacement order of the elements in the vector.

[0053] Step S353: With the total area as a constraint, replace the smallest unit of measurement according to the replacement order of the elements in the reference and vector to obtain the adjusted vector.

[0054] Specifically, based on the elements in the residual vector sorted from largest to smallest, and the number of minimum units to be added as determined in step S34, one minimum unit is added to the corresponding element in the reference and vectors in turn until the end. The result is the adjusted sum vector, which is used as the control vector for the row and column sums of the initial transition matrix.

[0055] Through step 3 above, the first initial sum vector (in year m, unit: km) is obtained. 2 ) and the second initial sum vector (year n, unit: km) 2 After adjustment, the sum vectors corresponding to the first initial sum vector are: [1803.18, 206.22, 8.10, 3.45, 3.75, 5.30], and the sum vectors corresponding to the second initial sum vector are: [1806.15, 202.06, 7.92, 5.02, 3.62, 5.23]. The sum of both is 2030, which is sufficient for closure.

[0056] However, if the rounding method is used to round the first initial sum vector (in the m-th year, unit: km) 2 ) and the second initial sum vector (year n, unit: km) 2 After processing, the first initial sum vector, after rounding, is: [1803.18, 206.21, 8.10, 3.45, 3.75, 5.30]. The second element is 0.01 less, and the current sum is 2029.99, which is not equal to 2030, so it is not closed.

[0057] Step S4: Using the two adjusted sum vectors and the control ratio threshold as constraints, the initial transition matrix is ​​normalized, truncated, sorted, and replaced to obtain the adjusted initial transition matrix. The adjusted initial transition matrix is ​​then used as the hydraulic erosion intensity area data of the target area.

[0058] Furthermore, step S4 specifically includes steps S41-S43.

[0059] Step S41: Normalize the initial transition matrix based on the total area to obtain the normalized transition matrix.

[0060] Specifically, based on the total area of ​​2030 obtained in step S1, the initial transition matrix is ​​normalized by multiplying each element of the initial transition matrix by the sum of the elements in the initial transition matrix, with the total area of ​​2030 divided by the sum of the elements in the initial transition matrix as the scaling factor, to obtain the normalized transition matrix, which is as follows.

[0061] .

[0062] This matrix is ​​only rounded to four decimal places, and the actual sum is 2030. It is easy to see that the changes in each element are not significant.

[0063] Step S42: Truncate the normalized transition matrix according to the preset number of decimal places to obtain the reference transition matrix and the transition residual matrix corresponding to the normalized transition matrix.

[0064] Specifically, in accordance with the requirement of retaining two decimal places, the normalized transition matrix is ​​truncated to generate the baseline transition matrix and the transition residual matrix, as follows.

[0065] .

[0066] .

[0067] The baseline transfer matrix is ​​displayed with two decimal places, and the transfer residual matrix is ​​displayed with two decimal places and then rounded to four decimal places.

[0068] Step S43: Determine the minimum unit of measurement based on the preset number of decimal places.

[0069] Step S44: Calculate the second number of minimum units of measurement with replacement based on the sum of the two adjusted vectors, the sum of each row and column of the elements in the reference transition matrix, and the minimum unit of measurement; the second number of minimum units of measurement with replacement includes: the number of elements in each row of the reference transition matrix with replacement of minimum units of measurement and the number of elements in each column of the reference transition matrix with replacement of minimum units of measurement.

[0070] Specifically, with 2 decimal places as the preset decimal place, and based on the minimum unit of measurement of 0.01 determined by retaining 2 decimal places, the number of minimum units of measurement required for the normalized transition matrix to be replaced is calculated from both the row and column directions using the calculation formula for the second number of minimum units of measurement to be replaced. This is written as a row (column) vector of the number of minimum units of measurement, as shown below.

[0071] [4, 2, 3, 4, 3, 3].

[0072] [3, 4, 3, 2, 4, 3].

[0073] It is evident that the number of rows (columns) that need to be replaced with the smallest unit of measurement is 19, which is consistent.

[0074] Furthermore, the two adjusted sum vectors are the adjusted row sum vector and the adjusted column sum vector, respectively.

[0075] The formula for calculating the number of elements in each row of the reference transition matrix that are replaced with the smallest unit of measurement is as follows.

[0076] .

[0077] The formula for calculating the number of elements in each column of the baseline transfer matrix that are replaced with the smallest unit of measurement is as follows.

[0078] .

[0079] in, The first in the reference transition matrix The number of row elements replaced by the smallest unit of measurement; The first in the reference transition matrix After adjustment, the row sum vector corresponding to the row element is the first row. The value of each element; The first in the reference transition matrix The sum of row elements; The first in the reference transition matrix The number of column elements returned to the smallest unit of measurement; The first in the reference transition matrix After adjustment, the column and vector corresponding to the column elements are in the first position. The value of each element; The first in the reference transition matrix The sum of the column elements; It is the smallest unit of measurement.

[0080] Step S45: Using the two adjusted sum vectors and the control ratio threshold as constraints, sort and adjust the second quantity of the smallest unit of measurement with replacement, the reference transition matrix, and the transition residual matrix to obtain the initial transition matrix after adjustment.

[0081] Furthermore, step S45 specifically includes steps S451-S452.

[0082] Step S451: Calculate the minimum unit of measurement control quantity with replacement based on the control ratio threshold and the number of elements in the reference transfer matrix.

[0083] Specifically, at this point, the deviation of the area of ​​the original two-stage hydraulic erosion intensity maps should be judged by the number of minimum measurement units to be replaced. If the control ratio threshold is set to 60%, and the current transition matrix is ​​6×6 with 36 elements, 36×60%=21.6 can be calculated. If the number of minimum measurement units to be replaced is less than 21.6, proceed to the next adjustment step; otherwise, it is judged that the original data is incorrect, and the original two-stage hydraulic erosion intensity maps need to be modified or remade, and the initial transition matrix and two initial sum vectors should be regenerated for adjustment.

[0084] Step S452: Determine whether the second quantity of the minimum unit of measurement returned is less than the control quantity of the minimum unit of measurement returned; if so, remove the elements of the corresponding rows and columns of the transfer residual matrix by referring to the rows in the reference transfer matrix where the number of the minimum unit of measurement returned is 0 and the columns in the reference transfer matrix where the number of the minimum unit of measurement returned is 0, to obtain the transfer residual matrix after removal; take the position of the element in the reference transfer matrix corresponding to the position of the largest element in the transfer residual matrix after removal as the replacement position; use the two adjusted sum vectors as constraints to return the minimum unit of measurement to the replacement position, to obtain the reference transfer matrix after replacement; and respectively adjust the number of the minimum unit of measurement returned in the row corresponding to the replacement position and the number of the minimum unit of measurement returned. The number of minimum units of measurement returned to the column corresponding to the return position is reduced by 1 to update the number of rows and columns returned after the update. The number of rows returned after the update is the number of minimum units of measurement returned to each element in the updated baseline transition matrix. The number of columns returned after the update is the number of minimum units of measurement returned to each element in the updated baseline transition matrix. Based on the return position, the corresponding elements in the transition residual matrix after removal are removed again to obtain the transition residual matrix after removal. Replacement is performed again until the number of rows and columns returned after the update is 0. Replacement is then stopped, and the initial transition matrix after adjustment is obtained. Otherwise, the statistical analysis of the hydraulic erosion intensity area data of the target area is terminated.

[0085] Specifically, based on the two adjusted vectors determined in step S3, the initial transition matrix is ​​constrained in two dimensions. First, all elements in the row (column) with a replacement quantity of 0 are marked as inoperable. Then, the elements at the corresponding positions in the transition residual matrix are removed. The position with the maximum value is found among the remaining elements in the transition residual matrix. Then, a single minimum unit of measurement is added to the element at the corresponding position in the baseline transition matrix. Simultaneously, this position is marked as inoperable. The number of replacement minimum units in the row (column) vector is decremented by 1 in the corresponding row and column to update (i.e., the number of replacement minimum units in the row and the number of replacement minimum units in the column corresponding to the replacement position are both decremented by 1 to update). This process is repeated until all elements in the updated row replacement quantity and the updated column replacement quantity are 0 (i.e., the matrix is ​​closed), resulting in the initial transition matrix after adjustment, as shown below.

[0086] .

[0087] However, if the normalized transition matrix is ​​rounded to two decimal places, the resulting rounded initial transition matrix is ​​as follows.

[0088] .

[0089] 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, 1.70) are 0.01 larger than the elements of the adjusted transition matrix obtained by this method, and one element (0.2) is 0.01 smaller than the elements of the adjusted transition matrix obtained by this method. Therefore, it is inaccurate.

[0090] The beneficial effects of the method for determining the area data of regional hydraulic erosion intensity based on adjustment proposed in this application are mainly reflected in:

[0091] (1) Through normalization, truncation, sorting and replacement adjustment processing, normalization ensures that the total area calculated in the end is the same. 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, it can complete the adjustment work that would take tens or even hundreds of hours in the traditional way in a few seconds, and the efficiency has been improved by a breakthrough.

[0092] (2) This method can be widely applied to the adjustment of one-dimensional row and column vectors and two-dimensional square matrix of remote sensing and geographic information data charts under various total area constraints, such as the statistics of regional, provincial, municipal and county-level water erosion intensity area and its transfer area in the field of soil and water conservation. It can effectively support the dynamic monitoring of soil erosion across the country, timely grasp the status of soil erosion and its changes, and provide data and technical support for government departments at all levels to formulate targeted soil and water conservation plans, design soil and water conservation measures and accelerate the comprehensive prevention and control of soil erosion.

[0093] (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, and the statistics of garden grassland area and its transfer area in the field of ecological forestry, so as to improve the efficiency of chart data statistics in land management and ecological forestry management and reduce the burden on relevant statistical staff.

[0094] Based on the same inventive concept, this application also provides a system for determining the area data of regional hydraulic erosion intensity based on adjustment. The solution provided by this system is similar to the solution described in the above method. Therefore, the specific limitations of one or more embodiments of the system for determining the area data of regional hydraulic erosion intensity based on adjustment provided below can be found in the limitations of the method for determining the area data of regional hydraulic erosion intensity based on adjustment described above, and will not be repeated here.

[0095] In one exemplary embodiment, such as Figure 2 As shown, a system for determining regional hydraulic erosion intensity area data based on adjustment is provided, comprising: a determination module for determining the total area of ​​the target region; an acquisition module for acquiring the raster area of ​​the target region under different hydraulic erosion intensity levels in two years, and generating an initial transition matrix and two initial sum vectors based on the raster area; one initial sum vector corresponds to one year; the initial transition matrix is ​​a matrix generated with the raster area under different hydraulic erosion intensity levels in one of the two years as rows and the raster area under different hydraulic erosion intensity levels in the other of the two years as columns; the initial sum vectors are the raster areas under different hydraulic erosion intensity levels; a first adjustment processing module for performing 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; and a second adjustment processing module for performing normalization, truncation, sorting, and replacement adjustment processing on the initial transition matrix with the two adjusted sum vectors and a control ratio threshold as constraints, to obtain an adjusted initial transition matrix, and determining the adjusted initial transition matrix as the hydraulic erosion intensity area data of the target region.

[0096] 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, data stored, data displayed, 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 the relevant data must comply with relevant regulations.

[0097] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments described above. Any references to memory, databases, 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 can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM).

[0098] The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0099] The technical features of the above embodiments can be combined in any way. For the sake of brevity, 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.

[0100] This document uses specific examples to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the methods and core ideas of this application. Furthermore, those skilled in the art will recognize that, based on the ideas of this application, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A method for determining the area of ​​regional hydraulic erosion intensity based on adjustment, characterized in that, The method for determining the area data of regional hydraulic erosion intensity based on adjustment includes: Determine the total area of ​​the target region; Obtain the grid area of ​​the target area under different water erosion intensity levels in two years, and generate an initial transition matrix and two initial sum vectors based on the grid area; one initial sum vector corresponds to one year; the initial transition matrix is ​​a matrix generated with the grid area under different water erosion intensity levels in one of the two years as the rows and the grid area under different water erosion intensity levels in the other of the two years as the columns; the initial sum vectors are the grid areas under different water erosion intensity levels; the different water erosion intensity levels include: slight, mild, moderate, strong, very strong, and severe. Using the total area as a constraint, the two initial sum vectors are normalized, truncated, sorted, and adjusted with replacement to obtain two adjusted sum vectors. Specifically, the elements in the residual vector are sorted from largest to smallest according to their size to obtain the sorted residual vector; the residual vector is the vector obtained by normalizing and truncating the two initial sum vectors. The order of elements in the sorted residual vector is used as the replacement order to determine the pivot corresponding to the elements in the sorted residual vector and the replacement order of the elements in the vector. Using two adjusted vectors and a control ratio threshold as constraints, the initial transition matrix is ​​normalized, truncated, sorted, and replaced to obtain the adjusted initial transition matrix. The adjusted initial transition matrix is ​​then used as the area data of hydraulic erosion intensity in the target region.

2. The method for determining the area data of regional hydraulic erosion intensity based on adjustment according to claim 1, characterized in that, The initial sum vector includes: a first initial sum vector and a second initial sum vector; Obtain the grid area of ​​the target area under different water erosion intensity levels in two years, and generate an initial transition matrix and two initial sum vectors based on the grid area, specifically including: Obtain the grid area of ​​the target area under different water erosion intensity levels in two years; Based on the grid area, determine the grid area of ​​the target area under different water erosion intensity levels in the first year and the grid area of ​​the target area under different water erosion intensity levels in the second year; Based on the grid area of ​​the target area under different water erosion intensity levels in the first year, generate the first initial sum vector; Based on the grid area of ​​the target area under different water erosion intensity levels in the second year, a second initial sum vector is constructed. An initial transition matrix is ​​generated based on the grid area of ​​the target area under different water erosion intensity levels in the first year and the grid area of ​​the target area under different water erosion intensity levels in the second year.

3. The method for determining the area data of regional hydraulic erosion intensity based on adjustment according to claim 1, characterized in that, Using the total area as a constraint, the two initial sum vectors are normalized, truncated, sorted, and adjusted with replacement to obtain two adjusted sum vectors, specifically including: For each initial sum vector, the initial sum vector is normalized according to the total area to obtain a normalized sum vector; The normalized sum vector is truncated according to the preset number of decimal places to obtain the residual vector and the reference sum vector corresponding to the normalized sum vector; The minimum unit of measurement is determined based on the preset number of decimal places. Calculate the first quantity of the smallest unit of measurement with replacement based on the sum of the elements in the normalized sum vector, the sum of the elements in the benchmark sum vector, and the smallest unit of measurement. Using the total area as a constraint, the first quantity of the smallest unit of measurement with replacement, the benchmark and vector, and the residual vector are sorted and adjusted with replacement to obtain the adjusted sum vector.

4. The method for determining the area data of regional hydraulic erosion intensity based on adjustment according to claim 3, characterized in that, Using the total area as a constraint, the first quantity of the smallest unit of measurement with replacement, the benchmark and vector, and the residual vector are sorted and adjusted with replacement to obtain the adjusted sum vector, specifically including: The replacement quantity is the first quantity of the smallest unit of measurement for replacement. Using the total area as a constraint, the smallest unit of measurement is replaced according to the replacement order of the elements in the reference and vector to obtain the adjusted vector.

5. The method for determining the area data of regional hydraulic erosion intensity based on adjustment according to claim 3, characterized in that, The formula for calculating the first quantity of the smallest unit of measurement to be replaced is: ； in, To replace the first quantity of the smallest unit of measurement; This is the sum of the elements in the normalized sum vector; The sum of the elements in the reference and vector; It is the smallest unit of measurement.

6. The method for determining the area data of regional hydraulic erosion intensity based on adjustment according to claim 1, characterized in that, Using two adjusted sum vectors and a control ratio threshold as constraints, the initial transition matrix is ​​normalized, truncated, sorted, and adjusted with replacement to obtain the adjusted initial transition matrix, specifically including: The initial transition matrix is ​​normalized based on the total area to obtain a normalized transition matrix; The normalized transition matrix is ​​truncated according to the preset number of decimal places to obtain the reference transition matrix and the transition residual matrix corresponding to the normalized transition matrix; The minimum unit of measurement is determined based on the preset number of decimal places. Based on the sum vectors after two adjustment processes, the sum of each row and column of the elements in the reference transition matrix, and the minimum unit of measurement, calculate the second number of minimum units of measurement with replacement; the second number of minimum units of measurement with replacement includes: the number of minimum units of measurement with replacement for each row element in the reference transition matrix and the number of minimum units of measurement with replacement for each column element in the reference transition matrix; Using the two adjusted sum vectors and the control ratio threshold as constraints, the second quantity of the minimum unit of measurement with replacement, the reference transition matrix, and the transition residual matrix are sorted and adjusted with replacement to obtain the initial transition matrix after adjustment.

7. The method for determining the area data of regional hydraulic erosion intensity based on adjustment according to claim 6, characterized in that, Using the two adjusted sum vectors and the control ratio threshold as constraints, the second quantity of the minimum unit of measurement with replacement, the baseline transition matrix, and the transition residual matrix are sorted and adjusted with replacement to obtain the initial transition matrix after adjustment, specifically including: Calculate the minimum unit of measurement control quantity for replacement based on the control ratio threshold and the number of elements in the reference transfer matrix; Determine whether the second quantity of the smallest unit of measurement returned is less than the control quantity of the smallest unit of measurement returned. If so, then by comparing the rows in the reference transition matrix where the number of elements with the smallest unit of measurement returned is 0 and the columns in the reference transition matrix where the number of elements with the smallest unit of measurement returned is 0, the elements of the corresponding rows and columns in the transition matrix are removed to obtain the transition residual matrix after removal. The position of the element in the reference transition matrix corresponding to the position of the largest element in the transition residual matrix after removal is taken as the replacement position; Using the two adjusted sum vectors as constraints, the smallest unit of measurement is placed back to the placed position to obtain the reference transition matrix after replacement; The number of minimum replacement units in the row corresponding to the replacement position and the number of minimum replacement units in the column corresponding to the replacement position are both decreased by 1 to update the number of row replacements and the number of column replacements. The updated number of row replacements is the number of minimum replacement units in each row element of the updated base transition matrix. The updated number of column replacements is the number of minimum replacement units in each column element of the updated base transition matrix. Based on the replacement position, the corresponding elements in the transition residual matrix after removal are removed again to obtain the transition residual matrix after removal again. Replacement is performed again until the number of rows and columns after the update are both 0, then replacement is stopped, and the initial transition matrix after adjustment is obtained. If not, then the statistical analysis of the area data on the intensity of hydraulic erosion in the target region will be terminated.

8. The method for determining the area data of regional hydraulic erosion intensity based on adjustment according to claim 6, characterized in that, The two adjusted sum vectors are the row sum vector and the column sum vector, respectively. The formula for calculating the number of elements in each row of the reference transition matrix that have the smallest unit of measurement replaced is as follows: ； The formula for calculating the number of elements in each column of the reference transfer matrix that have their smallest unit of measurement replaced is as follows: ； in, The first in the reference transition matrix The number of row elements replaced by the smallest unit of measurement; The first in the reference transition matrix After adjustment, the row sum vector corresponding to the row element is the first row. The value of each element; The first in the reference transition matrix The sum of row elements; The first in the reference transition matrix The number of column elements returned to the smallest unit of measurement; The first in the reference transition matrix After adjustment, the column and vector corresponding to the column elements are in the first position. The value of each element; The first in the reference transition matrix The sum of the column elements; It is the smallest unit of measurement.

9. A system for determining the area of ​​regional hydraulic erosion intensity based on adjustment data, characterized in that, The system for determining the area data of regional hydraulic erosion intensity based on adjustment includes: The determination module is used to determine the total area of ​​the target region; The acquisition module is used to acquire the grid area of ​​the target area under different water erosion intensity levels in two years, and generate an initial transition matrix and two initial sum vectors based on the grid area; one initial sum vector corresponds to one year; the initial transition matrix is ​​a transition matrix generated with the grid area under different water erosion intensity levels in one of the two years as the rows and the grid area under different water erosion intensity levels in the other of the two years as the columns; the initial sum vectors are the grid areas under different water erosion intensity levels; the different water erosion intensity levels include: slight, mild, moderate, strong, very strong, and severe; The 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. Specifically, the elements in the residual vector are sorted from largest to smallest according to their size to obtain the sorted residual vector; the residual vector is the vector obtained by normalizing and truncating the two initial sum vectors. The order of elements in the sorted residual vector is used as the replacement order to determine the pivot corresponding to the elements in the sorted residual vector and the replacement order of the elements in the vector. The second adjustment module is used to perform adjustment processing on the initial transition matrix by normalizing, truncating, sorting and replacing it, with the two adjusted sum vectors and control ratio threshold as constraints, to obtain the adjusted initial transition matrix, and to determine the adjusted initial transition matrix as the hydraulic erosion intensity area data of the target area.

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