Partition investigation and evaluation system based on black land cultivated land quality red line evaluation protection

Abstract

The invention relates to the technical field of land evaluation, and discloses a zoning survey evaluation system based on black land cultivated land quality red line evaluation protection. Comprising a cultivated land area identification module, a cultivated land area segmented from a high-angle image, an evaluation point marking module, an area evaluation point marking in the cultivated land area, an area yield prediction module, a cultivated land quality evaluation module, a cultivated land quality evaluation module and a cultivated land quality evaluation module, a cultivated land quality improvement strategy is formulated; the method realizes the effect of breaking up the whole into parts in black land cultivated land quality analysis and evaluation, provides a distinguishing and limiting basis for data acquisition positions of cultivated land quality analysis and evaluation, and realizes corresponding adjustment operation of data acquisition positions of cultivated land areas with different structural forms. The limitation when single-position data acquisition is adopted in the cultivated land areas with different structural forms is avoided, and the effect of dynamically associating the data acquisition position with the structural forms of the cultivated land areas is achieved.

Description

Technical Field

[0001] The present invention relates to the field of land assessment technology, and more specifically, to a zoning investigation and assessment system based on the red line evaluation and protection of black soil arable land quality. Background Art

[0002] As a precious soil resource, black soil has extremely high agricultural productivity. However, under the influence of long-term high-intensity utilization, soil erosion, organic matter decline and environmental pollution, black soil has degraded. In order to understand the arable land quality of black soil in a timely and accurate manner, it is necessary to establish a scientific evaluation system and implement zoning survey operations to achieve accurate assessment of the arable land quality of black soil.

[0003] Patent application CN117132175A discloses a new method for evaluating the quality of reclaimed farmland based on satellite remote sensing data sources. This method uses a "bell-shaped" area enclosed by the multi-temporal satellite remote sensing normalized vegetation index (MDVI) calculated from multiple satellite remote sensing images within a predetermined period as an evaluation indicator. The method then compares the "bell-shaped" area of ​​newly added farmland plots with that of existing farmland, achieving a comprehensive evaluation of the quality of newly added farmland. When investigating and evaluating the quality of existing black soil arable land, the overall arable land quality of the arable land area is analyzed and evaluated by analyzing and comparing the increase and decrease in the area of ​​the arable land area, and combining it with the method of collecting data at fixed points in the arable land area. Since the area occupied by the arable land area is usually large, the use of large-scale overall data collection and analysis will lead to a heavy burden of data collection and calculation. At the same time, due to the rigid deviation of structural morphology between arable land areas with different structural morphology, the fixed-point data collection method will result in the collected data being not objective and accurate enough, and there are certain limitations. It is impossible to achieve a dynamic correlation effect between the data collection location and the structural morphology of the arable land area, and it cannot truly reflect the arable land quality, thereby reducing the accuracy and reliability of the black soil arable land quality assessment.

[0004] In view of this, the present invention proposes a zoning investigation and assessment system based on the red line evaluation and protection of black soil arable land quality to solve the above problems. Summary of the Invention

[0005] In order to overcome the above-mentioned defects of the prior art and to achieve the above-mentioned purpose, the present invention provides the following technical solution: a zoning survey and assessment system based on the red line evaluation and protection of black soil arable land quality, comprising: The cultivated land area recognition module is used to obtain an overhead image of black soil, identify the regional boundary line from the overhead image, segment the cultivated land area from the overhead image using the regional boundary line as the dividing line, and mark the regional boundary of the cultivated land area; The assessment point marking module is used to establish a median line between the boundaries of two adjacent regions, determine the positional relationship between the median line and the cultivated land area, identify the regional attributes of the cultivated land area, which include regular areas and irregular areas, and mark regional assessment points in the cultivated land area according to different regional attributes; The regional yield prediction module is used to collect the cultivated land quality data at the regional assessment point and predict the regional yield of the cultivated land area through the cultivated land yield prediction model; The cultivated land quality assessment module is used to conduct quality red line analysis on the predicted regional yield, analyze the cultivated land quality level of the cultivated land area, and formulate a cultivated land quality improvement strategy.

[0006] Furthermore, the steps for segmenting the cultivated land area are: Computer vision technology is used to identify the ridge roads in the overhead image, and lines are drawn along the ridge roads to draw regional boundaries; The aerial image is divided into adjacent sub-regions using the region boundary as the dividing line, and the intersection of two adjacent region boundary lines is recorded as the dividing point; In the overhead image, the sub-regions with the outer sides all surrounded by regional boundaries are recorded as farmland regions, and A farmland regions are obtained.

[0007] Furthermore, the method for identifying regular areas and irregular areas is as follows: The angle formed by the boundaries of any two adjacent areas in the A cultivated land area is recorded as the boundary angle, and the angles of the boundary angles are measured one by one to obtain the angle value; When the angle value is less than 90 degrees, the boundary angle is recorded as an irregular angle; Mark each of the A cultivated land areas one by one The midpoints of the boundaries of two adjacent regions are connected to generate The connection When the middle line is outside the cultivated land area, the positional relationship is a non-inclusion relationship; When the middle line is inside the cultivated land area, the positional relationship is a containment relationship; When there are both irregular corners and non-containment relationships in the cultivated land area, the area attribute of the cultivated land area is set as an irregular area; When irregular corners and non-containment relationships do not exist simultaneously in the cultivated land area, the regional attribute of the cultivated land area is set as a regular area.

[0008] Furthermore, when the cultivated land area is a regular area, the marking steps of the regional assessment points are as follows: Measure the distance between two adjacent midpoints in the cultivated land area one by one, and obtain The first distance value, and The first distance values ​​are accumulated and averaged to calculate the distance mean; A demarcation point is randomly selected as the starting point in the cultivated land area, and an auxiliary line is drawn toward the inner side of the cultivated land area. The intersection of the auxiliary line and the area boundary is recorded as the end point, and the part of the auxiliary line between the starting point and the end point is recorded as the extension line. The areas on both sides of the extension line in the cultivated land area are respectively recorded as the first area and the second area, and the position of the end point of the extension line is continuously adjusted until the areas of the first area and the second area are the same, at which time the adjustment of the end point of the extension line is stopped; Draw a point circle with the midpoint of the extended line as the center and half of the distance to the mean as the radius; Measure all points on the point circle one by one The point distance value of the dividing point is recorded as the point corresponding to the minimum value of the point distance value as the regional evaluation point. regional assessment points.

[0009] Furthermore, when the cultivated land area is an irregular area, the marking steps of the regional assessment points are as follows: Measure one by one The first distance value between a dividing point and its two adjacent dividing points, and The two first distance values ​​of the dividing points are added and averaged to calculate The dividing distance value; Pass The location of the dividing point is along the vertical Draw auxiliary lines extending into the cultivated land area in the direction of the boundary of the area where the dividing points are located. a perpendicular bisector; One third of the demarcation distance value is recorded as the marking distance value, and Mark the distance on the perpendicular line A dividing point and a marking distance value point are obtained. regional assessment points.

[0010] Furthermore, the arable land quality data include tillage depth, soil capacity, soil pH, organic matter content, total nitrogen content, available phosphorus content, fast-acting potassium content, and slow-acting potassium content; The steps for collecting tillage layer depth values ​​are as follows: Soil samplers were used to collect soil samples from the cultivated areas of Soil samples were collected at each regional assessment point, and the soil samples were photographed and converted into grayscale to obtain Sample grayscale images; Mark them one by one The pixel values ​​of all pixels in the sample grayscale image are recorded as target pixels if the pixel value is less than the preset pixel value; Along the vertical direction of the sample grayscale image, the distance between the target pixel and the upper surface of the soil sample is measured one by one, recorded as the point-to-surface distance value, the target pixel corresponding to the maximum point-to-surface distance value is recorded as the edge pixel, and the area between the upper surface of the soil sample and the edge pixel is recorded as the tillage layer to be identified; Based on the calibrated interval depth, the soil hardness is detected one by one by inserting the soil hardness tester. The hardness values ​​of different depth positions in the tillage layer to be identified are obtained, and the last depth position where the hardness value is greater than the preset hardness threshold for the first time is recorded as the tillage layer position; Read the soil hardness tester one by one The value of the tillage layer position is obtained sub-depth value, and The depth of each seed is accumulated and averaged to calculate the depth of the tillage layer.

[0011] Furthermore, the steps for collecting soil capacity values ​​are as follows: Will Soil samples from each regional assessment point are placed in a drying device for heating and drying. The soil samples are weighed regularly at preset intervals to obtain weight values. When the weighing value of the soil sample no longer changes, the weighing value that no longer changes is recorded as the soil weight value, and the Soil weight value; Query the sampling volume of the soil sampler and After comparing the soil weight value with the sampling volume of the soil sampler, the Sub-capacity value; After removing the maximum and minimum values ​​of the sub-capacity values, the remaining The soil capacity value is calculated by accumulating the individual seed capacity values ​​and averaging them.

[0012] Furthermore, the steps for predicting regional output are: Collect multiple sets of farmland quality data and regional yields in advance, mark a set of farmland quality data as a set of feature vectors, and convert regional yields into labels corresponding to the feature vectors; One feature vector corresponds to one label, forming a set of training data, and the labeled training data is divided into a training set and a test set; The feature vector is used as the input of the machine learning model, and the regional yield corresponding to the cultivated land quality data is used as the output of the machine learning model. The machine learning model is trained using the training set and tested using the test set. When the mean prediction error of all training data in the test set is less than the preset error threshold, the cultivated land yield prediction model is obtained. The collected arable land quality data are input into the arable land yield prediction model to predict the regional yield corresponding to the arable land quality data.

[0013] Furthermore, the arable land quality grades include high quality grade, medium quality grade and low quality grade. The analysis steps of high quality grade, medium quality grade and low quality grade are as follows: When the predicted regional yield is greater than or equal to the preset first yield red line value, the cultivated land area is of high quality level; When the predicted regional yield is less than the preset first yield red line value, and the predicted regional yield is greater than or equal to the preset second yield red line value, the cultivated land area is of medium quality grade; When the predicted regional yield is less than the preset second yield red line value, the cultivated land area is of low quality level.

[0014] Furthermore, the steps for formulating strategies to improve farmland quality are as follows: If the cultivated land quality level is medium or low, the cultivated land quality data will be compared with the corresponding red line value; When the tillage depth value is greater than or less than the depth red line value, a strategy of increasing or decreasing the tillage depth is formulated; When the soil capacity value is greater than or less than the capacity red line value, formulate a strategy to increase or decrease the soil capacity; When the soil pH value is greater than or less than the pH red line value, formulate a strategy to increase or decrease the soil pH; When the organic matter content is greater than or less than the organic matter red line value, formulate a strategy to increase or decrease organic matter; When the total nitrogen content is greater than or less than the total nitrogen red line value, formulate a strategy to increase or decrease the total nitrogen; When the available phosphorus content is greater than or less than the available phosphorus red line value, formulate a strategy to increase or decrease the available phosphorus; When the available potassium content is greater than or less than the available potassium red line value, formulate a strategy to increase or decrease available potassium; When the slow-release potassium content is greater than or less than the slow-release potassium red line value, a strategy to increase or decrease the slow-release potassium is formulated.

[0015] The technical effects and advantages of the zoning survey and assessment system based on the black soil arable land quality red line evaluation and protection of the present invention are as follows: (1): By identifying regional boundaries, accurate boundary definitions can be provided for the identification and determination of cultivated land areas, and large areas of black soil can be divided and cut in an orderly manner, achieving the effect of breaking up the quality analysis and evaluation of black soil cultivated land into small pieces, avoiding the huge burden of overall analysis and evaluation of black soil cultivated land quality, and by effectively identifying cultivated land areas with different structural forms, providing a basis for distinguishing and limiting the data collection locations for subsequent cultivated land quality analysis and evaluation, achieving the corresponding adjustment operation of the data collection locations of cultivated land areas with different structural forms, avoiding the limitations of using a single location for data collection of cultivated land areas with different structural forms, and thus achieving the effect of dynamic association between the data collection location and the structural form of the cultivated land area; (2): By using the multi-dimensional collection method of cultivated land regional analysis and evaluation data and combining it with the cultivated land yield prediction model for intelligent prediction, the regional yield of the cultivated land area can be predicted quickly and accurately, providing an accurate data basis for the cultivated land quality analysis and evaluation of the cultivated land area, and providing targeted cultivated land quality improvement strategies for low-quality cultivated land areas. Ultimately, the dual effects of accurate analysis and evaluation of cultivated land quality and formulation of cultivated land quality improvement recommendations are achieved, achieving the ultimate goal of evaluating and protecting the red line of black soil cultivated land quality. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 This is a module diagram of a zoning investigation and assessment system based on the black soil arable land quality red line evaluation and protection provided in the first embodiment of the present invention; Figure 2 A flow chart of a zoning survey and assessment method based on the black soil arable land quality red line evaluation and protection provided in the second embodiment of the present invention. DETAILED DESCRIPTION

[0017] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0018] Example 1: Please refer to Figure 1 As shown, the zoning survey and assessment system based on the black soil arable land quality red line evaluation and protection described in this embodiment includes: The cultivated land area recognition module obtains an overhead image of black soil, identifies the regional boundary line from the overhead image, uses the regional boundary line as the dividing line to segment the cultivated land area, and marks the regional boundaries of the cultivated land area; Aerial images are images taken from a high altitude and covering large areas of black soil. They can provide an image basis for the subsequent zoning survey and assessment of arable land quality and protection of black soil, thereby realizing a series of evaluation and assessment processing. Specifically, when obtaining the overhead image, an aircraft equipped with a camera device is used to fly along the planned route of the black soil that needs to be surveyed and evaluated for arable land quality protection, and then high-definition images of the black soil are obtained by looking down with the camera device; exemplarily, the aircraft is a drone and the camera device is a high-definition camera.

[0019] After obtaining the overhead image of black soil, it is necessary to identify and differentiate the large area of ​​black soil contained in the overhead image, and accurately identify the cultivated land areas for zoning survey and assessment of cultivated land quality protection; When determining the cultivated land area, it is necessary to first identify the regional boundary lines in the overhead image, and make the regional boundary lines provide a basis for segmenting the cultivated land areas at different locations in the overhead image to ensure the accuracy of the cultivated land area segmentation.

[0020] The steps for segmenting the cultivated land area are: Computer vision technology is used to identify the ridge roads in the overhead image, and lines are drawn along the ridge roads to draw regional boundaries; The aerial image is divided into adjacent sub-regions using the region boundary as the dividing line, and the intersection of two adjacent region boundary lines is recorded as the dividing point; In the overhead image, the sub-regions with the outer sides all surrounded by regional boundaries are recorded as farmland regions, and A farmland regions are obtained.

[0021] After obtaining the cultivated land area, it is necessary to identify and mark the regional boundaries of each cultivated land area so that the regional boundaries can be used as the outer edge position of the cultivated land area and as the division position of two adjacent cultivated land areas; Specifically, when marking the regional boundary, the regional boundary line adjacent to the cultivated land area is used as the target boundary line, and the boundary point adjacent to the cultivated land area is used as the segmentation point of the target boundary line. The target boundary line is segmented by the segmentation point, and the segmented target boundary line is recorded as the regional boundary of the cultivated land area.

[0022] It should be noted that, since the cultivated land area is a land shape with a closed structure, the number of regional boundaries of the cultivated land area is at least three, and due to the different specific shapes of each cultivated land area, the number of regional boundaries may also vary.

[0023] The assessment point marking module establishes a midline between the midpoints of the boundaries of two adjacent regions, determines the positional relationship between the midline and the cultivated land area, identifies the regional attributes of the cultivated land area, and marks regional assessment points in the cultivated land area based on the regional attributes; After identifying the cultivated land areas and regional boundaries, each cultivated land area can be further analyzed according to the actual cultivated land quality evaluation and assessment needs; Before further analysis and identification of cultivated land areas, it is necessary to first identify the regional attributes of cultivated land areas so that the regional attributes can represent the area structure of each different cultivated land area, thus providing a basis for further analysis and evaluation. Specifically, regional attributes include regular areas and irregular areas; regular areas refer to areas where the overall morphological structure of cultivated land is in a relatively regular and flat state, and there are no serious depressions, protrusions, sharp structures, etc. in the cultivated land area; irregular areas refer to areas where the overall morphological structure of cultivated land is not in a relatively regular and flat state, and there are serious depressions, protrusions, sharp structures, etc. in the cultivated land area.

[0024] The identification method of regular and irregular areas is: The angle formed by the boundaries of any two adjacent areas in the A cultivated land area is recorded as the boundary angle, and the angles of the boundary angles are measured one by one to obtain the angle value; When the angle value is less than 90 degrees, it means that the boundaries between the two regions of the boundary angle are in a relatively sharp shape, and the boundary angle is recorded as an irregular angle; Mark each of the A cultivated land areas one by one The midpoints of the boundaries of two adjacent regions are connected to generate The connection Identify one by one The positional relationship between the connecting lines and the corresponding cultivated land areas; When the middle line is outside the cultivated land area, the positional relationship between the middle line and the cultivated land area is a non-inclusion relationship. When the middle line is outside the cultivated land area, it means that the extension directions of the boundaries of the two midpoints corresponding to the middle line are quite different, and the direction consistency between the two boundaries is poor, so the structural morphology of the cultivated land area is relatively irregular. When the middle line is inside the cultivated land area, the positional relationship between the middle line and the cultivated land area is a containment relationship; When irregular angles and non-containment relationships exist in the cultivated land area at the same time, it means that the structural form of the cultivated land area is not a regular and complete structure, and the regional attribute of the cultivated land area is set as an irregular area; When there are no irregular angles and non-containment relationships in the cultivated land area, it means that the structural form of the cultivated land area is a regular and complete structure, and the regional attribute of the cultivated land area is a regular area.

[0025] After identifying the regional attributes of the cultivated land area, it is necessary to locate and mark the regional assessment points within the cultivated land area according to the specific morphological structures of regular and irregular areas, so that the regional assessment points can be used as data collection points for subsequent zoning surveys and assessments of cultivated land area quality evaluation and protection, thereby limiting the location of all subsequent collected analysis and evaluation data; The steps for marking regional assessment points are: When the cultivated land area is a regular area, the location distribution of regional assessment points in the cultivated land area is relatively regular; Measure the distance between two adjacent midpoints in the cultivated land area one by one, and obtain The first distance value, and The first distance values ​​are accumulated and averaged to calculate the distance mean; The expression of the distance mean is: ; Where, is the distance mean, For the First distance value; A demarcation point is randomly selected as the starting point in the cultivated land area, and an auxiliary line is drawn toward the inner side of the cultivated land area. The intersection of the auxiliary line and the area boundary is recorded as the end point, and the part of the auxiliary line between the starting point and the end point is recorded as the extension line. The areas on both sides of the extension line in the cultivated land area are respectively recorded as the first area and the second area, and the position of the end point of the extension line is continuously adjusted until the areas of the first area and the second area are the same, at which time the adjustment of the end point of the extension line is stopped; the areas of the first area and the second area can be calculated using area calculation tools in computer vision technology, or by counting the number of pixels in the first area and the second area, that is, when the number of pixels in the first area and the second area is the same, the areas of the first area and the second area are the same; Draw a point circle with the midpoint of the extended line as the center and half of the distance to the mean as the radius; Measure all points on the point circle one by one The point distance value of the dividing point is recorded as the point corresponding to the minimum value of the point distance value as the regional evaluation point. regional assessment points; the positions of regional assessment points can be limited in a relatively regular position form within a regular cultivated land area, thereby achieving a regular multi-point determination effect for cultivated land quality assessment in the cultivated land area; When the cultivated land area is an irregular area, the location distribution of the regional assessment points in the cultivated land area is relatively irregular; Measure one by one The first distance value between a dividing point and its two adjacent dividing points, and The two first distance values ​​of the dividing points are added and averaged to calculate The dividing distance value; Pass The location of the dividing point is along the vertical Draw auxiliary lines extending into the cultivated land area in the direction of the boundary of the area where the dividing points are located. a perpendicular bisector; One third of the demarcation distance value is recorded as the marking distance value, and Mark the distance on the perpendicular line A dividing point and a marking distance value point are obtained. Regional assessment points can be defined in a relatively regular position within irregular cultivated land areas, ensuring that the regional assessment points can provide relatively regular point marking effects for cultivated land areas with irregular structural morphology.

[0026] It should be noted that when the cultivated land area is a regular area or an irregular area, the marking process and method of regional assessment points in the cultivated land area are inconsistent. Therefore, when marking regional assessment points in the cultivated land area, it is necessary to mark them according to the regional attributes of the cultivated land area.

[0027] The regional yield prediction module collects the cultivated land quality data at the regional assessment point and predicts the regional yield corresponding to the cultivated land quality data through the cultivated land yield prediction model; After the regional assessment points are marked in the cultivated land area, the regional assessment points can be used as the data collection locations in the cultivated land area to collect the cultivated land quality data in the cultivated land area; Cultivated land quality data is a diversified data that can be used to analyze and evaluate the quality of cultivated land in cultivated areas. Cultivated land quality data can also directly affect the corresponding cultivated land yield in cultivated areas, thereby providing diversified and multi-dimensional data support for the cultivated land quality of cultivated areas. The quality data of cultivated land include tillage depth, soil capacity, soil pH, organic matter content, total nitrogen content, available phosphorus content, fast-acting potassium content and slow-acting potassium content; The tillage depth value refers to the soil depth provided for the root growth of crops when the crop is actually cultivated at the location of the regional assessment point in the cultivated land area. When the tillage depth value is too large or too small, it will have a negative impact on the yield of crops in the cultivated land area. Specifically, the steps for collecting the tillage layer depth value are as follows: Soil samplers were used to collect soil samples from the cultivated areas of Soil samples were collected at each regional assessment point, and the soil samples were photographed and converted into grayscale to obtain Sample grayscale images; Mark them one by one The pixel values ​​of all pixels in the sample grayscale image are calculated, and the pixel values ​​of the pixels that are less than the preset pixel value are recorded as target pixels; the preset pixel value refers to the maximum value of the pixel values ​​marked as target pixels, which can limit the size of the pixel value of the black soil in the grayscale image, thereby achieving the preliminary recognition and determination effect of the black soil depth belonging to the cultivated height in the sample grayscale image; Along the vertical direction of the sample grayscale image, the distance between the target pixel and the upper surface of the soil sample is measured one by one, recorded as the point-to-surface distance value, the target pixel corresponding to the maximum point-to-surface distance value is recorded as the edge pixel, and the area between the upper surface of the soil sample and the edge pixel is recorded as the tillage layer to be identified; Based on the calibrated interval depth, the soil hardness is detected one by one by inserting the soil hardness tester. The hardness values ​​of different depth positions in the tillage layer to be identified are obtained, and the last depth position where the hardness value is greater than the preset hardness threshold for the first time is recorded as the tillage layer position; the calibrated interval depth is used to limit the size of the insertion depth of the soil hardness meter to ensure that the soil hardness meter can maintain a constant insertion depth to perform insertion-type hardness detection in the soil sample; for example, the calibrated interval depth is 1 cm; the preset hardness threshold refers to the minimum value of the soil hardness recorded as the tillage layer position, thereby achieving the hardness distinction effect between the tillage layer position and the non-tillage layer position. Specifically, since the roots of crops will extend into the tillage layer position, the soil hardness in the tillage layer position will be less than the soil hardness in the non-tillage layer position; Read the soil hardness tester one by one The value of the tillage layer position is obtained sub-depth value, and The depth of each seed is accumulated and averaged to calculate the depth of the tillage layer; The calculation formula for the tillage layer depth is: ; Where, is the tillage layer depth value, For the The sub-depth value of each area evaluation point.

[0028] Soil capacity refers to the weight of soil per unit volume in the cultivated land area when it is actually used for cultivating crops at the location of the regional assessment point. When the soil capacity is too large or too small, it will have a negative impact on the yield of crops in the cultivated land area. Specifically, the steps for collecting soil capacity values ​​are as follows: Will Soil samples from each regional assessment point are placed in a drying device for heating and drying. The weight of the soil samples is weighed regularly at a preset interval to obtain a weight value. The preset interval is the time interval between two adjacent soil sample weighings, so as to achieve a timing effect for soil sample weighing. When the weighing value of the soil sample no longer changes, the weighing value that no longer changes is recorded as the soil weight value, and the Soil weight value; Query the sampling volume of the soil sampler and After comparing the soil weight value with the sampling volume of the soil sampler, the Sub-capacity value; The calculation formula of subcapacity value is: ; Where, For the The sub-capacity value of each regional assessment point, For the Soil weight value of each regional assessment point, is the sampling volume of the soil sampler; After removing the maximum and minimum values ​​of the sub-capacity values, the remaining The capacity values ​​of each seed are accumulated and averaged to calculate the soil capacity value; The calculation formula for soil capacity value is: ; Where, is the soil capacity value, For the The sub-capacity value of each regional assessment point.

[0029] Soil pH refers to the acidity and alkalinity of the soil in the cultivated area at the location of the regional assessment point when it is actually used for cultivating crops. When the soil pH is too high or too low, it will have a negative impact on the yield of crops in the cultivated area. The soil pH is tested one by one using an electronic pH meter. The pH values ​​of the soil samples were measured and then added up to obtain the average.

[0030] Organic matter content refers to the amount of organic matter in the soil at the location of the regional assessment point when the cultivated land area is actually used for cultivating crops. When the organic matter content is too high or too low, it will have a negative impact on the yield of crops in the cultivated land area. The organic matter content is tested one by one using an organic matter determination kit. The organic matter content of each soil sample was calculated and then added up to obtain the average.

[0031] Total nitrogen content, available phosphorus content, fast-acting potassium content and slow-acting potassium content refer to the content of total nitrogen, available phosphorus, fast-acting potassium and slow-acting potassium in the soil of the cultivated land area at the location of the regional assessment point when the crop is actually cultivated. When the total nitrogen content, available phosphorus content, fast-acting potassium content and slow-acting potassium content are too high or too low, it will have a negative impact on the yield of crops in the cultivated land area; Specifically, when collecting total nitrogen content, available phosphorus content, fast-acting potassium content and slow-acting potassium content, the standard laboratory collection method or the rapid field collection method can be used; When the standard laboratory collection method is used, the total nitrogen content is determined by the Kjeldahl method, the available phosphorus content is determined by the Olsen method or the Bray method, the fast-acting potassium content is determined by the NH4OAc-flame photometry method, and the slow-acting potassium content is determined by the HNO3 extraction method.

[0032] When collecting data using the rapid field collection method, the total nitrogen content is tested by the alkaline diffusion method, the available phosphorus content is tested using a colorimetric card or a rapid tester, the fast-acting potassium content is tested using the sodium tetraphenylborate turbidimetric method, and there is no rapid field collection method for the slow-acting potassium content.

[0033] It should be noted that when using the laboratory standard collection method or the field rapid collection method to collect the total nitrogen content, available phosphorus content, fast-acting potassium content and slow-acting potassium content, the The soil samples were tested one by one and The method of accumulating and averaging the test values ​​is used to ensure that the collected data can maintain accuracy and universality.

[0034] After collecting the cultivated land quality data of the cultivated land area, it is necessary to import the cultivated land quality data into the cultivated land yield prediction model, so as to quickly predict the regional yield of crops in the cultivated land area corresponding to the cultivated land quality data; Among them, regional yield refers to the actual yield of crops in the cultivated land area. The regional yield of the same type of crops will vary depending on the quality data of the cultivated land. When collecting regional yield, it is obtained by statistically summarizing the crop weights of crops in the cultivated land area and then adding them up.

[0035] The cultivated land yield prediction model is based on the machine learning model. After collecting a large amount of different cultivated land quality data and the corresponding regional yields, the artificial intelligence model is obtained by repeatedly training and iterating the machine learning model through the cultivated land quality data and regional yields. The cultivated land yield prediction model can be used to accurately predict the regional yield corresponding to the cultivated land quality data.

[0036] Specifically, the steps for predicting regional output are: Collect multiple sets of cultivated land quality data and regional yields corresponding to the cultivated land quality data in advance, mark a set of cultivated land quality data as a set of feature vectors, obtain multiple sets of feature vectors, and convert regional yields into labels corresponding to the feature vectors; One feature vector corresponds to one label, forming a set of training data. Multiple sets of training data constitute a training set. The labeled training data are divided into a training set and a test set, with 70% of the training data used as the training set and 30% of the training data used as the test set. The feature vector is used as the input of the machine learning model, and the regional yield corresponding to the cultivated land quality data is used as the output of the machine learning model. The machine learning model is trained using the training set and tested using the test set. An error threshold is preset. When the mean of the prediction errors of all training data in the test set is less than the preset error threshold, a cultivated land yield prediction model that predicts regional yield based on the cultivated land quality data is obtained. The collected arable land quality data are input into the arable land yield prediction model to predict the regional yield corresponding to the arable land quality data.

[0037] In this embodiment, the predicted regional yield can provide accurate data support for the analysis and evaluation of the actual arable land quality in the arable land area, thereby realizing the criterion evaluation and prediction effect of combining arable land quality assessment with artificial intelligence technology.

[0038] The arable land quality assessment module conducts quality red line analysis on the predicted regional yield, analyzes the arable land quality level of the arable land area, and formulates strategies to improve the arable land quality; After predicting the regional yield of the cultivated land area, the regional yield can be used as a basis for analyzing the quality of the cultivated land in the cultivated land area, thereby performing a quality red line analysis on the predicted regional yield and analyzing the cultivated land quality level of the cultivated land area; Among them, the cultivated land quality grade is used to express the results of the cultivated land quality red line assessment and protection in cultivated land areas, and is used to distinguish cultivated land areas with different cultivated land quality levels; The quality grades of cultivated land include high quality grade, medium quality grade and low quality grade; the quality of cultivated land in the cultivated land areas corresponding to high quality grade, medium quality grade and low quality grade is from high to low.

[0039] The analysis steps for high quality level, medium quality level and low quality level are: The predicted regional yield is compared with a preset first yield red line value and a preset second yield red line value, and the preset first yield red line value is greater than the preset second yield red line value; the preset first yield red line value and the preset second yield red line value are used to determine the critical values ​​of regional yield corresponding to the high quality level, medium quality level and low quality level of the cultivated land area, thereby effectively distinguishing the cultivated land quality levels corresponding to regional yields of different sizes; When the predicted regional yield is greater than or equal to the preset first yield red line value, the crop yield in the cultivated land area is high and the cultivated land quality in the cultivated land area is good, and the cultivated land area is of high quality grade; When the predicted regional yield is less than the preset first yield red line value, and the predicted regional yield is greater than or equal to the preset second yield red line value, the crop yield of the cultivated land area is medium, and the cultivated land quality of the cultivated land area is average, then the cultivated land area is of medium quality grade; When the predicted regional yield is less than the preset second yield red line value, the yield of crops in the cultivated land area is low and the cultivated land quality in the cultivated land area is poor, and the cultivated land area is of low quality level.

[0040] After analyzing the farmland quality level of the farmland area, it is necessary to give a reasonable and accurate farmland quality improvement strategy to the farmland area with low farmland quality, so that the farmland quality improvement strategy can serve as an opinion for improving the farmland quality of the farmland area with low farmland quality, and play a positive and effective role in improving the farmland quality of black soil; When formulating strategies for improving arable land quality, it is necessary to clarify which arable land quality data in which arable land areas of which arable land quality levels need to be optimized and adjusted, and to formulate corresponding strategies for improving arable land quality based on specific arable land areas and arable land quality data.

[0041] Specifically, the steps for formulating a strategy to improve farmland quality are as follows: When the farmland quality level is high quality, there is no need to improve the farmland quality in the farmland area, so no farmland quality improvement strategy is formulated; When the farmland quality level is medium or low, it is necessary to improve the farmland quality in the farmland area; Compare the tillage layer depth, soil capacity, soil pH, organic matter content, total nitrogen content, available phosphorus content, fast-acting potassium content and slow-acting potassium content with the corresponding red line values ​​one by one; When the tillage depth value is greater than or less than the depth red line value, it means that the tillage depth of the cultivated land area is too deep or too shallow, and a strategy of increasing or decreasing the tillage depth is formulated; the depth red line value refers to the optimal tillage depth value when the cultivated land area is of high quality grade; When the soil capacity value is greater than or less than the capacity redline value, it indicates that the soil capacity of the cultivated land area is too much or too little, and a strategy to increase or decrease the soil capacity is formulated; the capacity redline value refers to the optimal value of the soil capacity value when the cultivated land area is of high quality. When the soil pH value is greater than or less than the pH red line value, it means that the soil acidity and alkalinity of the cultivated land area is too high or too low, and a strategy to increase or decrease the soil pH is formulated; the pH red line value refers to the optimal soil pH value when the cultivated land area is of high quality grade; When the organic matter content is greater than or less than the organic matter red line value, it indicates that the soil organic matter content in the cultivated land area is too high or too low, and a strategy to increase or decrease the organic matter content is formulated; the organic matter red line value refers to the optimal value of the organic matter content when the cultivated land area is of high quality grade; When the total nitrogen content is greater than or less than the total nitrogen red line value, it means that the total nitrogen content of the soil in the cultivated land area is too high or too low, and a strategy to increase or decrease the total nitrogen is formulated; the total nitrogen red line value refers to the optimal value of the total nitrogen content when the cultivated land area is of high quality grade; When the available phosphorus content is greater than or less than the available phosphorus red line value, it indicates that the available phosphorus content in the soil of the cultivated land area is too high or too low, and a strategy to increase or decrease the available phosphorus is formulated; the available phosphorus red line value refers to the optimal value of the available phosphorus content when the cultivated land area is of high quality grade; When the available potassium content is greater than or less than the available potassium red line value, it indicates that the available potassium content in the soil of the cultivated land area is too high or too low, and a strategy to increase or decrease available potassium is formulated; the available potassium red line value refers to the optimal value of available potassium content when the cultivated land area is of high quality grade; When the slowly available potassium content is greater than or less than the slow available potassium red line value, it indicates that the slowly available potassium content in the cultivated land area is too high or too low, and a strategy to increase or decrease the slowly available potassium content is formulated. The slow available potassium red line value refers to the optimal value of the slowly available potassium content when the cultivated land area is of high quality.

[0042] It should be noted that the cultivated land quality improvement strategy formulated is only used as a guide for improving and optimizing the cultivated land quality in medium-quality and low-quality cultivated land areas. It is used to provide targeted macro-optimization suggestions for improving cultivated land quality to ensure that the subsequent cultivated land quality improvement operations in cultivated land areas remain accurate and reasonable. For example, when a strategy to increase or decrease available potassium is formulated, and the available potassium content is greater than the available potassium red line value, the available potassium content in the cultivated land area needs to be reduced, and vice versa; similarly, the logic corresponding to other cultivated land quality improvement strategies is the same.

[0043] In this embodiment, by identifying regional dividing lines, accurate boundary definitions can be provided for the identification and determination of cultivated land areas, and large areas of black soil can be partitioned and cut in an orderly manner, achieving the effect of breaking up the black soil cultivated land quality analysis and evaluation into small pieces, avoiding the huge burden of overall analysis and evaluation of black soil cultivated land quality, and through effective identification of cultivated land areas with different structural forms, it is possible to provide a basis for distinguishing and limiting the data collection positions for subsequent cultivated land quality analysis and evaluation, and achieve corresponding adjustment operations for data collection positions of cultivated land areas with different structural forms, avoiding the use of single-position data collection for cultivated land areas with different structural forms. The limitations that exist at the time of evaluation are overcome, thereby achieving the effect of dynamically associating the data collection location with the structural morphology of the cultivated land area. At the same time, the multi-dimensional collection method of cultivated land regional analysis and evaluation data is used, and combined with the cultivated land yield prediction model for intelligent prediction, the regional yield of the cultivated land area can be predicted quickly and accurately, providing an accurate data basis for the cultivated land quality analysis and evaluation of the cultivated land area, and can also provide targeted cultivated land quality improvement strategies for low-quality cultivated land areas. Finally, the dual effects of accurate analysis and evaluation of cultivated land quality and formulation of cultivated land quality improvement suggestions are achieved, and the ultimate goal of evaluating and protecting the red line of black soil cultivated land quality is achieved.

[0044] Example 2: Please refer to Figure 2 As shown, for the parts not described in detail in this embodiment, please refer to the description of embodiment 1. A zoning investigation and assessment method based on the red line evaluation and protection of black soil arable land quality is provided, which is implemented through a zoning investigation and assessment based on the red line evaluation and protection of black soil arable land quality, including: S1: Obtain an overhead image of black soil, identify a regional boundary line from the overhead image, segment the cultivated land area from the overhead image using the regional boundary line as a dividing line, and mark the regional boundary of the cultivated land area; S2: Establish a median line between the boundaries of two adjacent regions, determine the positional relationship between the median line and the cultivated land area, identify the regional attributes of the cultivated land area, and mark regional assessment points in the cultivated land area according to the different regional attributes; S3: Collect the cultivated land quality data at the regional assessment points and predict the regional yield of the cultivated land area through the cultivated land yield prediction model; S4: Conduct quality red line analysis on the predicted regional yield, analyze the arable land quality level of the arable land area, and formulate strategies to improve the arable land quality.

[0045] The above description is only a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any technician familiar with this technical field can easily think of changes or replacements within the technical scope disclosed by the present invention, which should be covered by the scope of protection of the present invention.

Claims

1. A zoning survey and assessment system based on the black soil arable land quality red line evaluation and protection is characterized by: include: The cultivated land area recognition module is used to obtain an overhead image of black soil, identify the regional boundary line from the overhead image, segment the cultivated land area from the overhead image using the regional boundary line as the dividing line, and mark the regional boundary of the cultivated land area; The assessment point marking module is used to establish a median line between the boundaries of two adjacent regions, determine the positional relationship between the median line and the cultivated land area, identify the regional attributes of the cultivated land area, which include regular areas and irregular areas, and mark regional assessment points in the cultivated land area according to different regional attributes; The regional yield prediction module is used to collect the cultivated land quality data at the regional assessment point and predict the regional yield of the cultivated land area through the cultivated land yield prediction model; The cultivated land quality assessment module is used to conduct quality red line analysis on the predicted regional yield, analyze the cultivated land quality level of the cultivated land area, and formulate a cultivated land quality improvement strategy.

2. The zoning survey and assessment system based on the black soil arable land quality red line evaluation and protection according to claim 1 is characterized in that: The steps for segmenting the cultivated land area are: Computer vision technology is used to identify the ridge roads in the overhead image, and lines are drawn along the ridge roads to draw regional boundaries; The aerial image is divided into adjacent sub-regions using the region boundary as the dividing line, and the intersection of two adjacent region boundary lines is recorded as the dividing point; In the overhead image, the sub-regions with the outer sides all surrounded by regional boundaries are recorded as farmland regions, and A farmland regions are obtained.

3. The zoning survey and assessment system based on the black soil arable land quality red line evaluation and protection according to claim 2 is characterized in that: The identification method of regular and irregular areas is: The angle formed by the boundaries of any two adjacent areas in the A cultivated land area is recorded as the boundary angle, and the angles of the boundary angles are measured one by one to obtain the angle value; When the angle value is less than 90 degrees, the boundary angle is recorded as an irregular angle; Mark each of the A cultivated land areas one by one The midpoints of the boundaries of two adjacent regions are connected to generate The connection When the middle line is outside the cultivated land area, the positional relationship is a non-inclusion relationship; When the middle line is inside the cultivated land area, the positional relationship is a containment relationship; When there are both irregular corners and non-containment relationships in the cultivated land area, the area attribute of the cultivated land area is set as an irregular area; When irregular corners and non-containment relationships do not exist simultaneously in the cultivated land area, the regional attribute of the cultivated land area is set as a regular area.

4. The zoning survey and assessment system based on the black soil arable land quality red line evaluation and protection according to claim 3 is characterized in that: When the cultivated land area is a regular area, the marking steps of the regional assessment points are as follows: Measure the distance between two adjacent midpoints in the cultivated land area one by one, and obtain The first distance value, and The first distance values ​​are accumulated and averaged to calculate the distance mean; A demarcation point is randomly selected as the starting point in the cultivated land area, and an auxiliary line is drawn toward the inner side of the cultivated land area. The intersection of the auxiliary line and the area boundary is recorded as the end point, and the part of the auxiliary line between the starting point and the end point is recorded as the extension line. The areas on both sides of the extension line in the cultivated land area are respectively recorded as the first area and the second area, and the position of the end point of the extension line is continuously adjusted until the areas of the first area and the second area are the same, at which time the adjustment of the end point of the extension line is stopped; Draw a point circle with the midpoint of the extended line as the center and half of the distance to the mean as the radius; Measure all points on the point circle one by one The point distance value of the dividing point is recorded as the point corresponding to the minimum value of the point distance value as the regional evaluation point. regional assessment points.

5. The zoning survey and assessment system based on the black soil arable land quality red line evaluation and protection according to claim 4 is characterized in that: When the cultivated land area is irregular, the marking steps of the regional assessment points are as follows: Measure one by one The first distance value between a dividing point and its two adjacent dividing points, and The two first distance values ​​of the dividing points are added and averaged to calculate The dividing distance value; Pass The location of the dividing point is along the vertical Draw auxiliary lines extending into the cultivated land area in the direction of the boundary of the area where the dividing points are located. a perpendicular bisector; One third of the demarcation distance value is recorded as the marking distance value, and Mark the distance on the perpendicular line A dividing point and a marking distance value point are obtained. regional assessment points.

6. The zoning survey and assessment system based on the black soil arable land quality red line evaluation and protection according to claim 5 is characterized in that: The quality data of cultivated land include tillage depth, soil capacity, soil pH, organic matter content, total nitrogen content, available phosphorus content, fast-acting potassium content and slow-acting potassium content; The steps for collecting tillage layer depth values ​​are as follows: Soil samplers were used to collect soil samples from the cultivated areas of Soil samples were collected at each regional assessment point, and the soil samples were photographed and converted into grayscale to obtain Sample grayscale images; Mark them one by one The pixel values ​​of all pixels in the sample grayscale image are recorded as target pixels if the pixel value is less than the preset pixel value; Along the vertical direction of the sample grayscale image, the distance between the target pixel and the upper surface of the soil sample is measured one by one, recorded as the point-to-surface distance value, the target pixel corresponding to the maximum point-to-surface distance value is recorded as the edge pixel, and the area between the upper surface of the soil sample and the edge pixel is recorded as the tillage layer to be identified; Based on the calibrated interval depth, the soil hardness is detected one by one by inserting the soil hardness tester. The hardness values ​​of different depth positions in the tillage layer to be identified are obtained, and the last depth position where the hardness value is greater than the preset hardness threshold for the first time is recorded as the tillage layer position; Read the soil hardness tester one by one The value of the tillage layer position is obtained sub-depth value, and The depth of each seed is accumulated and averaged to calculate the depth of the tillage layer.

7. The zoning survey and assessment system based on the black soil arable land quality red line evaluation and protection according to claim 6 is characterized in that: The steps for collecting soil capacity values ​​are: Will Soil samples from each regional assessment point are placed in a drying device for heating and drying. The soil samples are weighed regularly at preset intervals to obtain weight values. When the weighing value of the soil sample no longer changes, the weighing value that no longer changes is recorded as the soil weight value, and the Soil weight value; Query the sampling volume of the soil sampler and After comparing the soil weight value with the sampling volume of the soil sampler, the Sub-capacity value; After removing the maximum and minimum values ​​of the sub-capacity values, the remaining The soil capacity value is calculated by accumulating the individual seed capacity values ​​and averaging them.

8. The zoning survey and assessment system based on the black soil arable land quality red line evaluation and protection according to claim 7 is characterized in that: The steps for predicting regional output are: Collect multiple sets of farmland quality data and regional yields in advance, mark a set of farmland quality data as a set of feature vectors, and convert regional yields into labels corresponding to the feature vectors; One feature vector corresponds to one label, forming a set of training data, and the labeled training data is divided into a training set and a test set; The feature vector is used as the input of the machine learning model, and the regional yield corresponding to the cultivated land quality data is used as the output of the machine learning model. The machine learning model is trained using the training set and tested using the test set. When the mean prediction error of all training data in the test set is less than the preset error threshold, the cultivated land yield prediction model is obtained. The collected arable land quality data are input into the arable land yield prediction model to predict the regional yield corresponding to the arable land quality data.

9. The zoning survey and assessment system based on the black soil arable land quality red line evaluation and protection according to claim 8 is characterized in that: The quality grades of cultivated land include high quality grade, medium quality grade and low quality grade. The analysis steps of high quality grade, medium quality grade and low quality grade are as follows: When the predicted regional yield is greater than or equal to the preset first yield red line value, the cultivated land area is of high quality level; When the predicted regional yield is less than the preset first yield red line value, and the predicted regional yield is greater than or equal to the preset second yield red line value, the cultivated land area is of medium quality grade; When the predicted regional yield is less than the preset second yield red line value, the cultivated land area is of low quality level.

10. The zoning survey and assessment system based on the black soil arable land quality red line evaluation and protection according to claim 9 is characterized in that: The steps for formulating a strategy to improve farmland quality are as follows: If the cultivated land quality level is medium or low, the cultivated land quality data will be compared with the corresponding red line value; When the tillage depth value is greater than or less than the depth red line value, a strategy of increasing or decreasing the tillage depth is formulated; When the soil capacity value is greater than or less than the capacity red line value, formulate a strategy to increase or decrease the soil capacity; When the soil pH value is greater than or less than the pH red line value, formulate a strategy to increase or decrease the soil pH; When the organic matter content is greater than or less than the organic matter red line value, formulate a strategy to increase or decrease the organic matter; When the total nitrogen content is greater than or less than the total nitrogen red line value, formulate a strategy to increase or decrease the total nitrogen; When the available phosphorus content is greater than or less than the available phosphorus red line value, formulate a strategy to increase or decrease the available phosphorus; When the available potassium content is greater than or less than the available potassium red line value, a strategy to increase or decrease available potassium is developed; When the slow-release potassium content is greater than or less than the slow-release potassium red line value, a strategy to increase or decrease the slow-release potassium is formulated.

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