A method for evaluating the quality acceptance of reclaimed cultivated land and an acceptance management system

Abstract

The present invention discloses a method for acceptance evaluation of supplementary cultivated land quality and an acceptance management system, which relates to the technical field of cultivated land management. The present invention includes a detection module for collecting the detection values of each basic evaluation factor of each evaluation unit; collecting the detection values of each soil fertility evaluation factor of each preliminary screening evaluation unit according to the planned detection density of the preliminary screening evaluation unit; the acceptance management module divides the cultivated land acceptance evaluation area into multiple evaluation units; obtains the detection values of each basic evaluation factor of each evaluation unit; screens out the preliminary screening evaluation units that meet the basic evaluation factors according to the detection values of each basic evaluation factor of each evaluation unit, and obtains the planned detection density of each preliminary screening evaluation unit; performs soil fertility evaluation factor detection on each preliminary screening evaluation unit according to the planned detection density of each preliminary screening evaluation unit to obtain the acceptance evaluation result of the supplementary cultivated land quality in the cultivated land acceptance evaluation area. The present invention improves the efficiency of acceptance evaluation.

Description

Technical Field

[0001] The present invention belongs to the technical field of cultivated land management, and particularly relates to a method for evaluating the quality acceptance of supplementary cultivated land and an acceptance management system. Background Art

[0002] With the acceleration of the urbanization process and the rapid development of the economy, cultivated land resources are facing increasingly severe challenges. On the one hand, the demand for urban construction land is continuously increasing, resulting in a continuous reduction in the area of cultivated land; on the other hand, the quality of existing cultivated land is declining, and problems such as soil pollution and soil fertility decline are becoming increasingly prominent.

[0003] In order to effectively protect cultivated land resources, the state has introduced a series of policies and regulations, requiring the strict implementation of the cultivated land occupation and compensation balance system, that is, non-agricultural construction occupying cultivated land must supplement cultivated land with equivalent quantity and quality. However, there are still some problems in the current cultivated land occupation and compensation balance work, especially in the evaluation of the quality acceptance of supplementary cultivated land. It is necessary to conduct large-area and multiple complex samplings manually to complete the evaluation of the quality acceptance of supplementary cultivated land, and the evaluation efficiency is low. Summary of the Invention

[0004] The purpose of the present invention is to provide a method for evaluating the quality acceptance of supplementary cultivated land and an acceptance management system, which can improve the efficiency of acceptance evaluation by allocating the planned detection density for different evaluation units in the cultivated land acceptance evaluation area during the compliance evaluation stage of agricultural production conditions.

[0005] To solve the above technical problems, the present invention is realized through the following technical solutions:

[0006] The present invention provides a method for evaluating the quality acceptance of supplementary cultivated land, including:

[0007] Obtaining multiple types of evaluation indicators for agricultural production compliance evaluation as basic evaluation factors;

[0008] Obtaining multiple types of evaluation indicators for cultivated land fertility evaluation as fertility evaluation factors;

[0009] Dividing the cultivated land acceptance evaluation area into multiple evaluation units;

[0010] Obtaining the detection values of each basic evaluation factor for each evaluation unit;

[0011] Screening out the initially screened evaluation units that meet the basic evaluation factors according to the detection values of each basic evaluation factor for each evaluation unit, and obtaining the planned detection density of each initially screened evaluation unit;

[0012] Performing fertility evaluation factor detection on each initially screened evaluation unit according to the planned detection density of each initially screened evaluation unit to obtain the evaluation result of the quality acceptance of supplementary cultivated land in the cultivated land acceptance evaluation area.

[0013] The present invention also discloses a supplementary cultivated land quality acceptance management system, including

[0014] a detection module, configured to collect the detection values of each basic evaluation factor of each evaluation unit;

[0015] collect the detection values of each soil fertility evaluation factor of each preliminary screening evaluation unit according to the planned detection density of the preliminary screening evaluation unit;

[0016] an acceptance management module, configured to obtain multiple types of evaluation indicators for agricultural production compliance evaluation as basic evaluation factors;

[0017] obtain multiple types of evaluation indicators for cultivated land fertility evaluation as soil fertility evaluation factors;

[0018] divide the cultivated land acceptance evaluation area into multiple evaluation units;

[0019] collect the detection values of each basic evaluation factor of each evaluation unit;

[0020] screen out the preliminary screening evaluation units that meet the basic evaluation factors according to the detection values of each basic evaluation factor of each evaluation unit, and obtain the planned detection density of each preliminary screening evaluation unit;

[0021] perform soil fertility evaluation factor detection on each preliminary screening evaluation unit according to the planned detection density of each preliminary screening evaluation unit to obtain the supplementary cultivated land quality acceptance evaluation result of the cultivated land acceptance evaluation area.

[0022] The present invention detects the detection values of each basic evaluation factor of each evaluation unit through the detection module, and then comprehensively evaluates the conditions of each evaluation unit through the acceptance management module, so as to obtain the degree that each evaluation unit should focus on more detection in the subsequent soil fertility detection process, thereby realizing targeted planned detection density allocation for different evaluation units in the cultivated land acceptance evaluation area at the stage of agricultural production basic condition compliance evaluation, and improving the efficiency and accuracy of cultivated land detection in the limited number of detection processes.

[0023] Of course, it is not necessary for any product implementing the present invention to achieve all the above-mentioned advantages simultaneously. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0025] Figure 1Schematic diagram of functional modules and information flow of a cultivated land quality acceptance management system according to an embodiment of the present invention;

[0026] Figure 2 Schematic diagram of the step flow of an acceptance management module according to an embodiment of the present invention;

[0027] Figure 3 Schematic diagram of the step flow of step S5 according to an embodiment of the present invention;

[0028] Figure 4 Schematic diagram of the step flow of step S51 according to an embodiment of the present invention;

[0029] Figure 5 Schematic diagram of the step flow of step S52 according to an embodiment of the present invention;

[0030] Figure 6 Schematic diagram of the step flow of step S54 according to an embodiment of the present invention;

[0031] In the attached drawings, the list of components represented by each reference numeral is as follows:

[0032] 1 - Detection module, 2 - Acceptance management module. Detailed implementation manners

[0033] To make the objectives, technical solutions, and advantages of the present application clearer, the following will further describe the embodiments of the present application in detail with reference to the attached drawings.

[0034] It should be noted that the terms "first", "second", etc. in the present application are used to distinguish similar objects and do not necessarily describe a specific order or sequence. It should be understood that such data can be interchanged under appropriate circumstances so that the embodiments of the present application described here can be implemented in an order other than those illustrated or described here. The implementation manners described in the following exemplary embodiments do not represent all implementation manners consistent with the present application. On the contrary, they are only examples of devices and methods consistent with some aspects of the present application as detailed in the appended claims.

[0035] Please refer to Figures 1 to 2 As shown, the present invention provides a cultivated land quality acceptance management system, which is functionally divided into a detection module 1 and an acceptance management module 2. The detection module 1 collects the detection values of each basic evaluation factor and soil fertility evaluation factor of each evaluation unit. The types of basic evaluation factors include soil body thickness, gravel content, soil organic matter content, and terrain slope. The types of soil fertility evaluation factors include terrain aspect, field surface slope, plough layer thickness, soil texture, soil erosion, irrigation guarantee rate, pollution direction, distance from pollution source, and waterlogging drainage capacity.

[0036] Due to the economic and time costs of testing, the number of tests performed by the testing module 1 is limited, especially since there are many items in the soil fertility evaluation factor and the testing cost is high. Therefore, it is necessary to reduce the number of tests while maintaining the accuracy of the test. This requires the acceptance management module 2 in the system to guide the testing work of the testing module 1. During operation, the acceptance management module 2 can first execute steps S1 and S2 to obtain multiple types of evaluation indicators for agricultural production compliance evaluation as basic evaluation factors, and obtain multiple types of evaluation indicators for cultivated land fertility evaluation as soil fertility evaluation factors. Next, step S3 can be executed to divide the cultivated land acceptance evaluation area into multiple evaluation units, which can be evenly divided or divided by staff according to specific circumstances. Next, step S4 can be executed to obtain the test value of each basic evaluation factor of each evaluation unit. This part of the test value is detected and obtained by the testing module 1 and transmitted to the acceptance management module 2.

[0037] See also Figures 1 to 4 As shown, since the cultivated land conditions of some evaluation units, especially adjacent evaluation units, are similar, it is not necessary to conduct too much testing on such evaluation units to obtain relatively accurate cultivated land fertility testing and evaluation results. Based on the same principle, if there are large differences between adjacent evaluation units, more cultivated land fertility testing resources should be allocated in a targeted manner. In view of this, in order to make the limited testing resources play a greater role, step S5 can be executed next to screen the initial screening evaluation units that meet the basic evaluation factors according to the test values of each basic evaluation factor of each evaluation unit, and obtain the planned testing density of each initial screening evaluation unit, that is, to execute step S51 to obtain a combination of initial screening evaluation units with consistent agricultural production compliance status according to the test values of each basic evaluation factor of each initial screening evaluation unit.

[0038] Specifically, first, step S511 can be executed to take the cumulative sum of the difference in the detection value of each basic evaluation factor between the primary screening evaluation units as the basic state difference between the primary screening evaluation units, and calculate the basic state difference between any two primary screening evaluation units. Next, step S512 can be executed to select several of the primary screening evaluation units as marked primary screening evaluation units from all the primary screening evaluation units. Next, step S513 can be executed to respectively calculate the basic state difference between each marked primary screening evaluation unit and other primary screening evaluation units. Next, step S514 can be executed to divide each other primary screening evaluation unit other than the marked primary screening evaluation unit and the marked primary screening evaluation unit with the smallest basic state difference into the same primary screening evaluation unit combination to obtain multiple primary screening evaluation unit combinations.

[0039] The initial screening evaluation units within the initially screened evaluation unit combination obtained at this time do not necessarily have a consistent agricultural production compliance status. Therefore, consistency verification needs to be carried out next. First, step S515 can be executed to calculate and obtain the average detection value of each basic evaluation factor of all the initial screening evaluation units included in each initially screened evaluation unit combination. Next, step S516 can be executed to determine whether the initial screening evaluation unit with the smallest basic state difference degree from the average detection value of each basic evaluation factor of all the initial screening evaluation units included in each initially screened evaluation unit combination is the marked initial screening evaluation unit. If so, then step S517 can be executed next to determine that the initial screening evaluation units within the initially screened evaluation unit combination have a consistent agricultural production compliance status; an initially screened evaluation unit combination with a consistent agricultural production compliance status is obtained.

[0040] If the above judgment is negative, it is determined that the initial screening evaluation units within the initially screened evaluation unit combination do not have a consistent agricultural production compliance status. And then step S518 can be executed to use the initial screening evaluation unit with the smallest basic state difference degree from the average detection value of each basic evaluation factor of all the initial screening evaluation units included in each initially screened evaluation unit combination as the reselected marked initial screening evaluation unit. Next, steps S513 to S516 can be executed to re-group the initial screening evaluation units according to the reselected marked initial screening evaluation unit to obtain an initially screened evaluation unit combination, and determine whether the agricultural production compliance status is consistent until an initially screened evaluation unit combination with a consistent agricultural production compliance status is obtained. The above process continuously generates initially screened evaluation unit combinations with a more consistent internal cultivated land state through an iterative manner until the requirements are met.

[0041] To supplement the implementation process of steps S511 to S518 above, the source code of some functional modules is provided, and corresponding explanations are given in the comment section. Some data that do not affect the implementation of the solution are desensitized, and the same applies hereinafter.

[0042] #include <iostream>

[0043] #include <vector>

[0044] #include <map>

[0045] #include <cmath>

[0046] #include <limits>

[0047] / / Define the basic evaluation factor structure

[0048] struct BasicFactor {

[0049] double soilThickness; / / Soil thickness

[0050] double gravelContent; / / Gravel content

[0051] double organicMatter; / / Soil organic matter content

[0052] double terrainSlope; / / Terrain slope

[0053] };

[0054] / / Define the evaluation unit structure

[0055] struct EvaluationUnit {

[0056] int id; / / Evaluation unit ID

[0057] BasicFactor basicFactors; / / Basic evaluation factors

[0058] int groupId; / / Group ID

[0059] };

[0060] / / Function: Calculate the difference in basic state between two evaluation units

[0061] double calculateDifference(const EvaluationUnit& unit1, const EvaluationUnit& unit2) {

[0062] double diffSoilThickness = std::abs(unit1.basicFactors.soilThickness - unit2.basicFactors.soilThickness);

[0063] double diffGravelContent = std::abs(unit1.basicFactors.gravelContent - unit2.basicFactors.gravelContent);

[0064] double diffOrganicMatter = std::abs(unit1.basicFactors.organicMatter - unit2.basicFactors.organicMatter);

[0065] double diffTerrainSlope = std::abs(unit1.basicFactors.terrainSlope - unit2.basicFactors.terrainSlope);

[0066] return diffSoilThickness + diffGravelContent + diffOrganicMatter + diffTerrainSlope;

[0067] }

[0068] / / Function: Select the initial marked preliminary screening evaluation unit

[0069] std::vector <int>selectInitialMarkedUnits(const std::vector <evaluationunit>&units, int numMarked) {

[0070] std::vector <int>markedUnits;

[0071] for (int i = 0; i < numMarked; ++i) {

[0072] markedUnits.push_back(units[i].id); / / Simply select the first numMarked units as the marked units

[0073] }

[0074] return markedUnits;

[0075] }

[0076] / / Function: Calculate the average detection value of the basic evaluation factors for each combination

[0077] BasicFactor calculateAverageFactors(const std::vector <evaluationunit>&units, const std::vector <int>&group) {

[0078] BasicFactor avgFactors = {0.0, 0.0, 0.0, 0.0};

[0079] for (int unitId : group) {

[0080] auto unitIt = std::find_if(units.begin(), units.end(),

[0081] [unitId](const EvaluationUnit&u) { return u.id == unitId;});

[0082] if (unitIt != units.end()) {

[0083] avgFactors.soilThickness += unitIt->basicFactors.soilThickness;

[0084] avgFactors.gravelContent += unitIt->basicFactors.gravelContent;

[0085] avgFactors.organicMatter += unitIt->basicFactors.organicMatter;

[0086] avgFactors.terrainSlope += unitIt->basicFactors.terrainSlope;

[0087] }

[0088] }

[0089] avgFactors.soilThickness / = group.size();

[0090] avgFactors.gravelContent / = group.size();

[0091] avgFactors.organicMatter / = group.size();

[0092] avgFactors.terrainSlope / = group.size();

[0093] return avgFactors;

[0094] }

[0095] / / Function: Group and check if the compliance status of agricultural production is consistent

[0096] bool groupAndCheckConsistency(std::vector <evaluationunit>&units, const std::vector <int>&markedUnits) {

[0097] std::map<int, std::vector <int>>groups; / / Combination ID -> List of unit IDs

[0098] bool isConsistent = true;

[0099] / / Assign each unit to the combination with the smallest difference from the marked unit

[0100] for (auto&unit : units) {

[0101] double minDiff = std::numeric_limits <double>::max();

[0102] int bestMarkedUnitId = -1;

[0103] for (int markedUnitId : markedUnits) {

[0104] auto markedUnitIt = std::find_if(units.begin(), units.end(),

[0105] [markedUnitId](const EvaluationUnit&u) { return u.id == markedUnitId;});

[0106] if (markedUnitIt != units.end()) {

[0107] double diff = calculateDifference(unit, *markedUnitIt);

[0108] if (diff<minDiff) {

[0109] minDiff = diff;

[0110] bestMarkedUnitId = markedUnitId;

[0111] }

[0112] }

[0113] }

[0114] if (bestMarkedUnitId != -1) {

[0115] groups[bestMarkedUnitId].push_back(unit.id);

[0116] unit.groupId = bestMarkedUnitId;

[0117] }

[0118] }

[0119] / / Check the consistency of each combination

[0120] for (const auto&group : groups) {

[0121] BasicFactor avgFactors = calculateAverageFactors(units,group.second);

[0122] double minDiff = std::numeric_limits <double>::max();

[0123] int closestUnitId = -1;

[0124] / / Find the unit with the smallest difference from the average detection value

[0125] for (int unitId : group.second) {

[0126] auto unitIt = std::find_if(units.begin(), units.end(),

[0127] [unitId](const EvaluationUnit&u) { return u.id == unitId;});

[0128] if (unitIt != units.end()) {

[0129] double diff = calculateDifference(*unitIt, {0, avgFactors});

[0130] if (diff < minDiff) {

[0131] minDiff = diff;

[0132] closestUnitId = unitId;

[0133] }

[0134] }

[0135] }

[0136] / / Determine whether the unit with the smallest difference is the marked unit

[0137] if (std::find(markedUnits.begin(), markedUnits.end(), closestUnitId) == markedUnits.end()) {

[0138] isConsistent = false;

[0139] break;

[0140] }

[0141] }

[0142] return isConsistent;

[0143] }

[0144] / / Main function

[0145] int main() {

[0146] / / Example of multiple preliminary screening and evaluation units

[0147] std::vector <evaluationunit>evaluationUnits = {

[0148] {1, {60, 20, 2.0, 10}, -1},

[0149] {2, {65, 18, 2.1, 12}, -1},

[0150] {3, {58, 22, 1.9, 11}, -1},

[0151] {4, {70, 15, 2.5, 8}, -1},

[0152] {5, {62, 19, 2.2, 9}, -1}

[0153] };

[0154] / / Step 1: Select the initial marker pre-screening evaluation units

[0155] std::vector <int>markedUnits = selectInitialMarkedUnits(evaluationUnits, 2);

[0156] / / Step 2: Group and check consistency

[0157] bool isConsistent = false;

[0158] while (!isConsistent) {

[0159] isConsistent = groupAndCheckConsistency(evaluationUnits,markedUnits);

[0160] if (!isConsistent) {

[0161] / / Re-select marked units

[0162] markedUnits.clear();

[0163] for (const auto&unit : evaluationUnits) {

[0164] if (unit.groupId != -1) {

[0165] markedUnits.push_back(unit.id);

[0166] }

[0167] }

[0168] }

[0169] }

[0170] / / Output the combination of preliminary screening evaluation units with consistent agricultural production compliance status

[0171] std::cout << "Combination of preliminary screening evaluation units with consistent agricultural production compliance status: " << std::endl;

[0172] for (const auto&unit : evaluationUnits) {

[0173] std::cout << "Evaluation unit ID: " << unit.id << ", combination ID: " << unit.groupId << std::endl;

[0174] }

[0175] return 0;

[0176] }

[0177] During the running of this code, the basic state difference degree is first calculated. By accumulating the difference values of the detection values of each basic evaluation factor, the basic state difference degree between any two pre-screened evaluation units is calculated. Then, the pre-screened evaluation units are selected and marked, and several of them are selected as marked units from all the pre-screened evaluation units. Next, grouping is performed and the average detection value is calculated. Each non-marked unit is assigned to the group with the smallest difference degree from the marked units, and the average detection value of the basic evaluation factor of each group is calculated. Then, consistency is judged. It is checked whether the unit with the smallest difference degree from the average detection value within each group is a marked unit. If not, the marked units are reselected and regrouped. Finally, the result is output, and the combination of pre-screened evaluation units with consistent agricultural production compliance status is output.

[0178] The code stores the evaluation unit data through a structure, and uses functions to implement the logic of difference degree calculation, grouping, and consistency judgment, and finally outputs the combination of pre-screened evaluation units with consistent compliance status.

[0179] Please continue to refer to Figure 3 and 5 As shown, after completing the consistency grouping of the pre-screened evaluation units, the next step is to execute step S52 to take the pre-screened evaluation units that do not belong to the same combination of pre-screened evaluation units and are adjacent in position as key pre-screened evaluation units and obtain the corresponding distribution coefficients. Specifically, first, step S521 can be executed. For each key pre-screened evaluation unit, calculate and obtain the basic state difference degree between it and each adjacent evaluation unit. Then, step S522 can be executed. The mean value of the accumulated values of the basic state difference degrees between the key pre-screened evaluation unit and each adjacent evaluation unit is used as the distribution coefficient of this key pre-screened evaluation unit.

[0180] To supplement the implementation process of the above steps S521 to S522, the source code of some functional modules is provided, and corresponding explanations are given in the comment part.

[0181] #include <iostream>

[0182] #include <vector>

[0183] #include <map>

[0184] #include <cmath>

[0185] / / Define the basic evaluation factor structure

[0186] struct BasicFactor {

[0187] double soilThickness; / / Soil thickness

[0188] double gravelContent; / / Gravel content

[0189] double organicMatter; / / Soil organic matter content

[0190] double terrainSlope; / / Terrain slope

[0191] };

[0192] / / Define the evaluation unit structure

[0193] struct EvaluationUnit {

[0194] int id; / / Evaluation unit ID

[0195] BasicFactor basicFactors; / / Basic evaluation factors

[0196] int groupId; / / Group ID

[0197] std::vector <int>neighbors; / / List of adjacent evaluation unit IDs

[0198] double allocationCoefficient; / / Allocation coefficient

[0199] };

[0200] / / Function: Calculate the difference in basic state between two evaluation units

[0201] double calculateDifference(const EvaluationUnit& unit1, const EvaluationUnit& unit2) {

[0202] double diffSoilThickness = std::abs(unit1.basicFactors.soilThickness - unit2.basicFactors.soilThickness);

[0203] double diffGravelContent = std::abs(unit1.basicFactors.gravelContent - unit2.basicFactors.gravelContent);

[0204] double diffOrganicMatter = std::abs(unit1.basicFactors.organicMatter - unit2.basicFactors.organicMatter);

[0205] double diffTerrainSlope = std::abs(unit1.basicFactors.terrainSlope - unit2.basicFactors.terrainSlope);

[0206] return diffSoilThickness + diffGravelContent + diffOrganicMatter + diffTerrainSlope;

[0207] }

[0208] / / Function: Obtain key pre-screened evaluation units

[0209] std::vector <evaluationunit>getKeyEvaluationUnits(const std::vector <evaluationunit>&units) {

[0210] std::vector <evaluationunit>keyUnits;

[0211] for (const auto& unit : units) {

[0212] for (int neighborId : unit.neighbors) {

[0213] / / Find adjacent units

[0214] auto neighborIt = std::find_if(units.begin(), units.end(),

[0215] [neighborId](const EvaluationUnit& u) { return u.id == neighborId;});

[0216] if (neighborIt != units.end() && neighborIt->groupId != unit.groupId) {

[0217] / / If the adjacent unit does not belong to the same group, the current unit is a key unit

[0218] keyUnits.push_back(unit);

[0219] break;

[0220] }

[0221] }

[0222] }

[0223] return keyUnits;

[0224] }

[0225] / / Function: Calculate the allocation coefficient of the key preliminary screening evaluation units

[0226] void calculateAllocationCoefficients(std::vector <evaluationunit>&keyUnits, const std::vector <evaluationunit>&allUnits) {

[0227] for (auto& keyUnit : keyUnits) {

[0228] double totalDifference = 0.0;

[0229] int neighborCount = 0;

[0230] / / Calculate the difference degree of the basic state with each adjacent unit

[0231] for (int neighborId : keyUnit.neighbors) {

[0232] auto neighborIt = std::find_if(allUnits.begin(), allUnits.end(),

[0233] [neighborId](const EvaluationUnit& u) { return u.id == neighborId;});

[0234] if (neighborIt != allUnits.end()) {

[0235] totalDifference += calculateDifference(keyUnit, *neighborIt);

[0236] neighborCount++;

[0237] }

[0238] }

[0239] / / Calculate the allocation coefficient (the mean value of the accumulated difference degree)

[0240] if (neighborCount > 0) {

[0241] keyUnit.allocationCoefficient = totalDifference / neighborCount;

[0242] } else {

[0243] keyUnit.allocationCoefficient = 0.0;

[0244] }

[0245] }

[0246] }

[0247] / / Main function

[0248] int main() {

[0249] / / Example of multiple preliminary screening evaluation units

[0250] std::vector <evaluationunit>evaluationUnits = {

[0251] {1, {60, 20, 2.0, 10}, 1, {2, 3}, 0.0}, / / Unit 1, combination ID is 1, adjacent units are 2 and 3

[0252] {2, {65, 18, 2.1, 12}, 2, {1, 4}, 0.0}, / / Unit 2, combination ID is 2, adjacent units are 1 and 4

[0253] {3, {58, 22, 1.9, 11}, 1, {1, 4}, 0.0}, / / Unit 3, combination ID is 1, adjacent units are 1 and 4

[0254] {4, {70, 15, 2.5, 8}, 2, {2, 3}, 0.0} / / Unit 4, combination ID is 2, adjacent units are 2 and 3

[0255] };

[0256] / / Step 1: Obtain the key preliminary screening evaluation units

[0257] std::vector <evaluationunit>keyUnits = getKeyEvaluationUnits(evaluationUnits);

[0258] / / Step 2: Calculate the allocation coefficients of the key preliminary screening evaluation units

[0259] calculateAllocationCoefficients(keyUnits, evaluationUnits);

[0260] / / Output the allocation coefficients of the key preliminary screening evaluation units

[0261] std::cout << "The allocation coefficients of the key preliminary screening evaluation units: " << std::endl;

[0262] for (const auto& unit : keyUnits) {

[0263] std::cout << "Evaluation unit ID: " << unit.id << ", Allocation coefficient: " << unit.allocationCoefficient << std::endl;

[0264] }

[0265] return 0;

[0266] }

[0267] During the running of the code, it first screens the key preliminary screening evaluation units, and identifies the evaluation units that do not belong to the same combination and are adjacent as key units. Then it calculates the basic state difference degree, calculating the basic state difference degree between each key unit and its adjacent units. Next, it calculates the allocation coefficients, taking the average value of the accumulated basic state difference degrees between each key unit and all its adjacent units as the allocation coefficient. Finally, it outputs the results, outputting the allocation coefficients of each key preliminary screening evaluation unit.

[0268] The code stores the evaluation unit data through a structure, and uses functions to implement the screening, difference degree calculation, and allocation coefficient calculation logic, and finally outputs the allocation coefficients of the key preliminary screening evaluation units.

[0269] Please continue to refer to Figure 3 and 6 As shown, after assigning distribution coefficients to the status of each key preliminary screening evaluation unit, the next step is to execute step S53 to obtain the total number of soil fertility evaluation plan detections. Next, step S54 can be executed to allocate the total number of soil fertility evaluation plan detections to each preliminary screening evaluation unit according to the distribution coefficient of each key preliminary screening evaluation unit, and obtain the planned detection density of each preliminary screening evaluation unit. Specifically, first, step S541 can be executed to allocate one soil fertility evaluation detection number to other preliminary screening evaluation units except the key preliminary screening evaluation units, and obtain the planned detection density of other preliminary screening evaluation units except the key preliminary screening evaluation units. Finally, step S542 can be executed to allocate the remaining soil fertility evaluation detection numbers according to the ratio between the distribution coefficients of each key preliminary screening evaluation unit, take the integer, obtain the soil fertility evaluation detection number of each key preliminary screening evaluation unit, and obtain the planned detection density of each key preliminary screening evaluation unit.

[0270] Please continue to refer to Figures 1 to 2 As shown, after completing the allocation of the planned detection density for each preliminary screening evaluation unit, finally, step S6 can be executed to perform soil fertility evaluation factor detections on each preliminary screening evaluation unit according to the planned detection density of each preliminary screening evaluation unit, and obtain the supplementary cultivated land quality acceptance evaluation results of the cultivated land acceptance evaluation area. Specifically, a number of soil fertility collection points can be evenly spaced within the preliminary screening unit according to the planned detection density of each preliminary screening evaluation unit, and the cultivated land fertility of the preliminary screening evaluation unit can be evaluated and graded based on the detection values of each soil fertility evaluation factor at the soil fertility collection points of the preliminary screening evaluation unit, so as to obtain the supplementary cultivated land quality acceptance evaluation results of each evaluation unit within the cultivated land acceptance evaluation area.

[0271] The flowcharts and block diagrams in the accompanying drawings show the possible architectures, functions, and operations of devices, systems, methods, and computer program products according to multiple embodiments of the present application. In this regard, each block in the flowchart or block diagram may represent a module, a program segment, or a part of an instruction, and the part of the module, program segment, or instruction contains one or more executable instructions for implementing the specified logical function. In some alternative implementations, the functions marked in the block may occur in a different order than that marked in the accompanying drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in the reverse order, depending on the functions involved.

[0272] It should also be noted that each block in the block diagram and / or flowchart, and the combination of blocks in the block diagram and / or flowchart, can be implemented by hardware that performs the corresponding functions or actions, such as a circuit or an ASIC (Application Specific Integrated Circuit), or can be implemented by a combination of hardware and software, such as firmware, etc.

[0273] Although the present invention has been described in connection with various embodiments, those skilled in the art will recognize other variations of the disclosed embodiments while practicing the claimed invention by viewing the drawings, the disclosure, and the appended claims. In the claims, the word "comprising" does not exclude other components or steps, and the singular "a" or "an" does not exclude a plurality. A single processor or other unit may implement several functions recited in the claims. Certain measures are recited in mutually different dependent claims, but this does not mean that these measures cannot be combined to good effect.

[0274] The embodiments of the present application have been described above. The above description is exemplary, not exhaustive, and is not limited to the disclosed embodiments. Many modifications and variations will be obvious to those of ordinary skill in the art without departing from the scope of the described embodiments. The choice of terms used herein is intended to best explain the principles of the embodiments, the practical application, or improvements to the technology in the market, or to enable other ordinary skill in the art to understand the embodiments disclosed herein.< / evaluationunit> < / evaluationunit> < / evaluationunit> < / evaluationunit> < / evaluationunit> < / evaluationunit> < / evaluationunit> < / int> < / cmath> < / map> < / vector> < / iostream> < / int> < / evaluationunit> < / double> < / double> < / int> < / int> < / evaluationunit> < / int> < / evaluationunit> < / int> < / evaluationunit> < / int> < / limits> < / cmath> < / map> < / vector> < / iostream>

Claims

1. A method for evaluating the quality of supplementary cultivated land, characterized in that: include, Obtain multiple types of evaluation indicators for agricultural production conformity assessment as basic evaluation factors, where the types of basic evaluation factors include soil thickness, gravel content, soil organic matter content, and terrain slope; Obtain multiple types of evaluation indicators for arable land fertility evaluation as soil fertility evaluation factors, where the types of soil fertility evaluation factors include terrain slope, field slope, plow layer thickness, soil texture, soil erosion, irrigation guarantee rate, pollution direction, distance from pollution source and drainage capacity; Divide the cultivated land acceptance and evaluation area into multiple evaluation units; Obtain the test value of each basic evaluation factor of each evaluation unit; According to the detection value of each basic evaluation factor of each evaluation unit, the preliminary screening evaluation unit that meets the basic evaluation factor is screened, and the cumulative sum of the detection value differences of each basic evaluation factor between the preliminary screening evaluation units is used as the basic state difference between the preliminary screening evaluation units, and the basic state difference between any two preliminary screening evaluation units is calculated; According to the basic status difference between any two preliminary screening evaluation units, all preliminary screening evaluation units are grouped into consistency groups to obtain multiple preliminary screening evaluation unit combinations; Calculate and obtain the average detection value of each basic evaluation factor of all preliminary screening evaluation units contained in each preliminary screening evaluation unit combination; Determine whether the primary screening evaluation unit with the smallest difference in the basic status from the average detection value of each basic evaluation factor of all the included primary screening evaluation units in each primary screening evaluation unit combination is a marked primary screening evaluation unit; If so, it is determined that the preliminary screening evaluation units within the preliminary screening evaluation unit combination have consistent agricultural production compliance status, and a preliminary screening evaluation unit combination with consistent agricultural production compliance status is obtained; If not, on the contrary, regroup and judge until a combination of preliminary screening evaluation units with consistent agricultural production compliance status is obtained; The primary screening evaluation units that do not belong to the same primary screening evaluation unit combination and are adjacent in position are taken as key primary screening evaluation units and the corresponding allocation coefficients are obtained; Obtain the total number of soil fertility assessment plan inspections; Allocate the total number of soil fertility assessment test plans to each primary screening evaluation unit according to the allocation coefficient of each key primary screening evaluation unit to obtain the planned test density of each primary screening evaluation unit; According to the planned detection density of each preliminary screening evaluation unit, the soil fertility evaluation factor of each preliminary screening evaluation unit is tested to obtain the supplementary cultivated land quality acceptance evaluation results of the cultivated land acceptance evaluation area.

2. The method according to claim 1, characterized in that The step of grouping all the primary screening evaluation units according to the basic state difference between any two primary screening evaluation units to obtain multiple primary screening evaluation unit combinations includes: Select several of the primary screening evaluation units from among all the primary screening evaluation units as marked primary screening evaluation units; Calculate and obtain the basic state difference between each marked primary screening evaluation unit and other primary screening evaluation units respectively; Each primary screening evaluation unit other than the marked primary screening evaluation unit is divided into the same primary screening evaluation unit combination with the marked primary screening evaluation unit having the smallest difference from the basic state, to obtain multiple primary screening evaluation unit combinations.

3. The method according to claim 1, characterized in that The step of regrouping and judging until a combination of primary screening evaluation units with consistent agricultural production compliance status is obtained, include, The primary screening evaluation unit with the smallest difference in the basic status from the average detection value of each basic evaluation factor of all the included primary screening evaluation units in each primary screening evaluation unit combination is used as the reselected marker primary screening evaluation unit; The marked preliminary screening evaluation units after reselection are regrouped to obtain a preliminary screening evaluation unit combination, and whether the agricultural production compliance status is consistent is determined until a preliminary screening evaluation unit combination with a consistent agricultural production compliance status is obtained.

4. The method according to claim 1, wherein The step of taking the primary screening evaluation units that do not belong to the same primary screening evaluation unit combination and are adjacent in position as key primary screening evaluation units and obtaining the corresponding allocation coefficients includes: For each key initial screening evaluation unit, calculate and obtain the basic status difference between it and each adjacent evaluation unit; The average of the cumulative values of the basic state difference between the key initial screening evaluation unit and each adjacent evaluation unit is used as the allocation coefficient of the key initial screening evaluation unit.

5. The method according to claim 1, wherein The step of allocating the total number of soil fertility evaluation test plans to each primary screening evaluation unit according to the allocation coefficient of each key primary screening evaluation unit to obtain the planned test density of each primary screening evaluation unit includes: Allocate one soil fertility evaluation test frequency to other primary screening evaluation units except the key primary screening evaluation unit, and obtain the planned test density of other primary screening evaluation units except the key primary screening evaluation unit; The remaining soil fertility evaluation test times are distributed according to the ratio between the distribution coefficients of each key initial screening evaluation unit, and the integer is taken to obtain the soil fertility evaluation test times of each key initial screening evaluation unit to obtain the planned test density of each key initial screening evaluation unit.

6. A supplementary cultivated land quality acceptance management system, characterized in that: include, A detection module is used to collect the detection value of each basic evaluation factor of each evaluation unit, wherein the types of basic evaluation factors include soil thickness, gravel content, soil organic matter content and terrain slope; Collect the test values of each soil fertility evaluation factor of each preliminary screening evaluation unit according to the planned test density of the preliminary screening evaluation unit. The types of soil fertility evaluation factors include terrain slope, field slope, plough layer thickness, soil texture, soil erosion, irrigation guarantee rate, pollution direction, distance from pollution source and drainage capacity; The acceptance management module is used to obtain multiple types of evaluation indicators for agricultural production conformity evaluation as basic evaluation factors; Acquire multiple types of evaluation indicators for arable land fertility evaluation as soil fertility evaluation factors; Divide the cultivated land acceptance and evaluation area into multiple evaluation units; Obtain the test value of each basic evaluation factor of each evaluation unit; According to the detection value of each basic evaluation factor of each evaluation unit, the preliminary screening evaluation unit that meets the basic evaluation factor is screened, and the cumulative sum of the detection value differences of each basic evaluation factor between the preliminary screening evaluation units is used as the basic state difference between the preliminary screening evaluation units, and the basic state difference between any two preliminary screening evaluation units is calculated; According to the basic status difference between any two preliminary screening evaluation units, all preliminary screening evaluation units are grouped into consistency groups to obtain multiple preliminary screening evaluation unit combinations; Calculate and obtain the average detection value of each basic evaluation factor of all preliminary screening evaluation units contained in each preliminary screening evaluation unit combination; Determine whether the primary screening evaluation unit with the smallest difference in the basic status from the average detection value of each basic evaluation factor of all the included primary screening evaluation units in each primary screening evaluation unit combination is a marked primary screening evaluation unit; If so, it is determined that the preliminary screening evaluation units within the preliminary screening evaluation unit combination have consistent agricultural production compliance status, and a preliminary screening evaluation unit combination with consistent agricultural production compliance status is obtained; If not, on the contrary, regroup and judge until a combination of preliminary screening evaluation units with consistent agricultural production compliance status is obtained; The primary screening evaluation units that do not belong to the same primary screening evaluation unit combination and are adjacent in position are taken as key primary screening evaluation units and the corresponding allocation coefficients are obtained; Obtain the total number of soil fertility assessment plan inspections; Allocate the total number of soil fertility assessment test plans to each primary screening evaluation unit according to the allocation coefficient of each key primary screening evaluation unit to obtain the planned test density of each primary screening evaluation unit; According to the planned detection density of each preliminary screening evaluation unit, the soil fertility evaluation factor of each preliminary screening evaluation unit is tested to obtain the supplementary cultivated land quality acceptance evaluation results of the cultivated land acceptance evaluation area.

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