Farmland soil health evaluation method and system

Abstract

The invention discloses a farmland soil health evaluation method and system, and relates to the field of soil health evaluation. The method comprises the following steps: acquiring remote sensing image data in a target area, decomposing color features of a remote sensing image by using an HIS model, acquiring a hue value, a saturation value and a brightness value of a unit grid, constructing a color feature vector set, clustering elements in the color feature vector set of the unit grid into K unit grid types, corresponding the unit grid types to a soil type, and constructing a soil model. Soil in a target area is divided into K categories, adjacent unit grid areas of the same type are combined into independent areas, the number of sampling points in any independent area is determined, soil sampling is conducted at the sampling points, the concentration value of all pollutants in soil samples of the independent areas is measured, and the distribution situation of all the pollutants in the target area is obtained. And calculating a single pollution index of the pollutant in the independent area according to the obtained concentration value of the dyed object, and dividing the pollution degree grade of the independent area.

Description

Technical Field

[0001] The present invention relates to the field of soil health assessment, and in particular to a method and system for assessing farmland soil health. Background Art

[0002] Soil health is a key factor in maintaining the productivity, diversity and environmental services of terrestrial ecosystems. For a long time, soil quality has been defined by measurable physical and chemical properties. The current agricultural industry standards focus on evaluating the ability of soil to provide and coordinate nutrition and environmental conditions for plant growth from the perspective of physical, chemical and biological properties related to soil and nutrient supply (such as regional natural conditions, soil fertility status and crop nutrition diagnostic indicators); from the perspective of agricultural production, the comprehensive index method is used to evaluate the ability of cultivated land fertility, soil health status and field infrastructure to meet the continuous output and quality safety of agricultural products, and the quality of cultivated land is divided into 10 cultivated land quality levels. At present, the evaluation process of soil health is to first sample soil samples in the test area, and then determine the types and content data of pollutants in the samples, and use this as the basis for quantitative evaluation. Therefore, in the actual farmland soil health evaluation process, determining the location of soil testing sampling points is a key issue.

[0003] In the prior art, the determination of soil sampling points usually relies on experience or simple grid division methods, mainly including the single diagonal method, double diagonal method, chessboard method, serpentine method, etc. Although the above methods are effective to a certain extent, they still have limitations. For example, the single diagonal method is suitable for farmland soil irrigated with sewage; the double diagonal method is suitable for plots with a small area, flat terrain, relatively uniform soil composition and pollution degree; the chessboard method is suitable for plots with a medium area, flat terrain, and uneven soil; the serpentine method is suitable for plots with a large area, uneven soil and uneven terrain. In the case of uneven distribution of soil pollution, the sampling points are not representative enough, which may lead to deviations in the monitoring results, so that the collected soil samples often cannot accurately reflect the actual distribution of soil pollution. To this end, we propose a farmland soil health assessment method and system. Summary of the invention

[0004] The main purpose of the present invention is to provide a method and system for evaluating farmland soil health, which can effectively solve the problems in the background technology.

[0005] In order to achieve the above object, the technical solution adopted by the present invention is:

[0006] A method for evaluating farmland soil health, comprising:

[0007] The target area is divided into several ε×ε unit grids, and the remote sensing image data in the target area is obtained. The high-resolution panchromatic remote sensing image is fused with the low-resolution multispectral remote sensing image using the HIS model. The color features of the remote sensing image of each unit grid are decomposed into three dimensions: hue, saturation, and brightness. The hue value H of the i-th unit grid is obtained. i , saturation value S i , brightness value I i ;

[0008] Construct the color feature vector set C of the i-th unit grid i ={H i , S i , I i}, get the color feature vector set C of the target area = [C i , C2, ..., C n ] T , C n is the color feature vector set of the nth unit grid, clustering the elements in the vector set C to obtain K unit grid types, corresponding the unit grid types to the soil types, and classifying the soil in the target area into K categories;

[0009] The classification process of unit grid types includes the following steps:

[0010] Step s21: Set the color feature vector set C of the i-th unit grid i ={H i , S i , I i} to obtain the normalized color feature vector set in, i∈n;

[0011] Step s22: Set the calibration vector set C0 = {0, 0, 0}, and calculate the normalized vector sets C i The distance value D between the calibration vector set C0 0i ,

[0012] Step s23: Using the distance value D 0i Create a sample set D, denoted as {D 01 , D 02 , ..., D 0n}, calculate the mean and standard deviation in the sample set D, and standardize each data point according to the calculation results. The formula is: In the formula D 0i The standard parameters of , σ and μ are the variance and mean of the data in the sample set D respectively;

[0013] Step s24: Set the standard parameters Use the Sigmoid function to map and adjust to [0,1], and use standard parameters The Sigmoid function value For distance value D 0i Classification is performed, and the classification mechanism is:

[0014] when When the distance value D 0i Classified as the first category;

[0015] when When the distance value D 0i Classified as the second category;

[0016] when When the distance value D 0i Classified as the third category;

[0017] And so on.

[0018] when When the distance value D 0i Classify into the Kth category;

[0019] in, Standard parameters The Sigmoid function value The minimum and maximum values ​​of

[0020] Step s25: According to the distance value D 0i According to the classification situation, determine the unit grid type, and the determination principle is:

[0021] When the distance value D 0i When classified as the first category, the corresponding unit grid type is the first category;

[0022] When the distance value D 0i When classified as the second category, the corresponding unit grid type is the second category;

[0023] When the distance value D 0i When classified as the third category, the corresponding unit grid type is the third category;

[0024] And so on.

[0025] When the distance value D 0i When classified into the Kth category, the corresponding unit grid type is the Kth category.

[0026] Merge adjacent unit grid areas of the same type, divide the target area into several independent areas according to the merging result, determine the number of sampling points in any independent area, take soil samples at the sampling points, and measure the rth pollutant concentration value c in the soil sample of the hth independent area. hr , obtain the distribution of various pollutants in the target area;

[0027] The process of determining the number of sampling points in an independent area includes the following steps:

[0028] Step s31: Counting the number of independent areas corresponding to the k-th soil type in the target area;

[0029] Step s32: Obtain the areas of all independent regions corresponding to the kth soil type, respectively denoted as is the area of ​​the mth independent region corresponding to the kth soil type;

[0030] Step s33: Set the total number of sampling points required for the kth soil type to D k , the number of sampling points corresponding to m independent regions are Then the number of sampling points in the mth independent area corresponding to the kth soil type is determined according to the following model, where the expression of the model is:

[0031]

[0032] According to the obtained dye concentration value c hr Calculate the single pollution index P of the rth pollutant in the hth independent area hr , where P hr =c kr / S r , where S r It is expressed as the risk screening value of the rth pollutant, according to the obtained single pollution index P hr The pollution level of the h-th independent area is divided.

[0033] The principles for classification of pollution levels are:

[0034] When P hr When ≤1, it indicates that the pollution level of the hth independent area is unpolluted;

[0035] When 1<P hr When ≤2, it indicates that the pollution level of the hth independent area is slightly polluted;

[0036] When 2<P hr When ≤3, it indicates that the pollution level of the hth independent area is slightly polluted;

[0037] When 3<P hr When ≤5, it indicates that the pollution level of the hth independent area is severely polluted;

[0038] When P hr When ≥5, it indicates that the pollution level of the hth independent area is severely polluted.

[0039] Also includes:

[0040] According to the obtained single pollution index P hr Calculate the comprehensive pollution index of the hth independent area The calculation formula is: Among them, ω r The pollution hazard coefficient of the rth pollutant, and

[0041] A farmland soil health assessment system, comprising:

[0042] A remote sensing image acquisition module is used to divide the target area into a plurality of ε×ε unit grids and acquire remote sensing image data in the target area;

[0043] The remote sensing image processing module is used to fuse the high-resolution panchromatic remote sensing image with the low-resolution multispectral remote sensing image using the HIS model, decompose the color features of the remote sensing image of each unit grid into three dimensions: hue, saturation, and brightness, and obtain the hue value H of the i-th unit grid. i , saturation value S i , brightness value I i ;

[0044] Soil classification module, used to construct the color feature vector set C of the i-th unit grid i ={H i , S i , I i}, get the color feature vector set C of the target area = [C i , C2, ..., C n ] T , clustering each element in the vector set C, obtaining K unit grid types, corresponding the unit grid types to the soil types, and classifying the soil in the target area into K categories;

[0045] A sampling point quantity calculation module is used to merge adjacent unit grid areas of the same type, divide the target area into a plurality of independent areas according to the merging result, and determine the number of sampling points in any of the independent areas;

[0046] The pollutant data acquisition module is used to sample the soil at the sampling point and determine the rth pollutant concentration value c in the soil sample of the hth independent area. hr , obtain the distribution of various pollutants in the target area;

[0047] The pollution degree assessment module is used to obtain the pollution concentration value c hr Calculate the single pollution index P of the rth pollutant in the hth independent area hr , according to the obtained single pollution index P hr Classify the pollution level of the h-th independent area;

[0048] The comprehensive pollution index calculation module is used to obtain the single pollution index P hr Calculate the comprehensive pollution index of the hth independent area

[0049] The system includes a memory, a processor, and a computer program stored in the memory and executable on the processor.

[0050] Furthermore, the number of sampling points of any two soil types in the target area is equal, and the locations of the sampling points are evenly distributed in any of the independent areas.

[0051] The present invention has the following beneficial effects:

[0052] Compared with the existing technology, the target area is divided into several unit grids, the remote sensing image data in the target area is obtained, the high-resolution panchromatic remote sensing image is fused with the low-resolution multispectral remote sensing image by using the HIS model, the color features of the remote sensing image of each unit grid are decomposed, the hue value, saturation value and brightness value of the i-th unit grid are obtained, the color feature vector set of the unit grid and the target area is constructed, the elements in the color feature vector set of the unit grid are clustered, K types of unit grid types are obtained, the unit grid types correspond to the soil types, the soil in the target area is classified into K categories, and the soil type is obtained. The same type and adjacent unit grid areas are divided into several independent areas, the number of sampling points in any independent area is determined, soil sampling is carried out at the sampling points, the concentration values ​​of various pollutants in the soil samples of the independent area are measured, the distribution of various pollutants in the target area is obtained, and the single pollution index of pollutants in the independent area is calculated according to the obtained pollutant concentration values. The pollution degree level of the independent area is divided, and the location and number of sampling points in the target area can be optimized and determined, so as to obtain more representative soil samples, so that the collected soil samples often cannot accurately reflect the actual distribution of soil pollution. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] Figure 1A schematic diagram of a method for evaluating farmland soil health according to the present invention;

[0054] Figure 2 This is a schematic diagram of the structure of a farmland soil health assessment system of the present invention;

[0055] Figure 3 a is a schematic diagram of dividing the target area into several ε×ε unit grids;

[0056] Figure 3 b is a schematic diagram of the independent area formed after merging the unit grids. DETAILED DESCRIPTION

[0057] The present invention will be further described below in conjunction with specific implementation methods, wherein the accompanying drawings are only used for exemplary descriptions and represent only schematic diagrams rather than actual drawings, and should not be understood as limiting the present invention. In order to better illustrate the specific implementation methods of the present invention, some parts of the accompanying drawings may be omitted, enlarged or reduced, and do not represent the size of the actual product.

[0058] The specific implementation process of the technical solution of the present invention includes the following steps:

[0059] Step 1: Divide the target area into several ε×ε unit grids, such as Figure 3 As shown, remote sensing image data within the target area is obtained;

[0060] Step 2: Use the HIS model to fuse the high-resolution panchromatic remote sensing image with the low-resolution multispectral remote sensing image, decompose the color features of the remote sensing image of each unit grid into three dimensions: hue, saturation, and brightness, and obtain the hue value H of the i-th unit grid. i , saturation value S i , brightness value I i ;

[0061] It should be noted that there is a certain correlation between the color of farmland soil and the degree of pollution, specifically:

[0062] Soil color changes due to pollutants Heavy metal pollution: When farmland soil is polluted by heavy metals, the soil color may change. For example, if the content of heavy metals such as cadmium and mercury in the soil is too high, it will affect the activity of microorganisms in the soil and the redox conditions of the soil, and then change the valence and form of elements such as iron and manganese in the soil, resulting in abnormal soil color. For example, soil that was originally reddish brown may turn grayish black due to heavy metal pollution.

[0063] Organic pollutant pollution: When organic pollutants such as petroleum hydrocarbons and polycyclic aromatic hydrocarbons enter the soil, they will form an organic film on the surface of soil particles, changing the optical properties of the soil, making the soil darker or mottled. For example, soil contaminated by petroleum may appear brown or black or have oily patches.

[0064] Different colors of soil may indicate different levels of contamination

[0065] Black soil: Under normal circumstances, black soil usually means that the soil has a high organic matter content and good fertility. However, if black soil appears in an area that was not originally this color, or its black color becomes abnormally darker, you should be alert to possible pollution. For example, in some industrial wastewater irrigation areas, due to the large amount of organic pollutants and heavy metals contained in the wastewater, long-term irrigation will cause the soil color to turn black. This black color is different from the black color brought by organic matter in texture and smell, and is often accompanied by a pungent odor, suggesting that the soil may have been seriously polluted.

[0066] Gray soil: Healthy gray soil is often found in some special soil-forming environments, such as swamp soil. However, if the originally dark farmland soil suddenly turns gray, it may be affected by reducing pollutants, such as a large amount of industrial waste landfill or the sedimentation of sulfur-containing waste gas, which reduces the iron oxide in the soil to ferrous oxide, thus showing gray. This usually means that the soil is heavily polluted and the soil structure and function may have been greatly damaged.

[0067] Colored soil: Some polluted soils may show abnormal colored patches or streaks. For example, if the soil contains excessive amounts of heavy metals such as copper and lead, it may appear green, blue, or other colored patches; if the soil is polluted by wastewater containing dyes, it may be dyed with bright artificial colors. These abnormal colors are usually obvious signs that the soil is seriously polluted.

[0068] Step 3: Construct the color feature vector set C of the i-th unit grid i ={H i , S i , I i}, get the color feature vector set C of the target area = [C i , C2, ..., C n ] T , C n is the color feature vector set of the nth unit grid, clusters each element in the vector set C, obtains K unit grid types, corresponds the unit grid type to the soil type, and classifies the soil in the target area into K categories; wherein the classification process of the unit grid type includes the following steps:

[0069] Step s31: Set the color feature vector set C of the i-th unit grid i ={H i , S i , I i} to obtain the normalized color feature vector set in, i∈n;

[0070] Step s32: Set the calibration vector set C0 = {0, 0, 0}, and calculate the normalized vector sets C i The distance value D between the calibration vector set C0 0i ,

[0071] Step s33: Using the distance value D 0i Create a sample set D, denoted as {D 01 , D 02 , ..., D 0n}, calculate the mean and standard deviation in the sample set D, and standardize each data point according to the calculation results. The formula is: In the formula D 0i The standard parameters of , σ and μ are the variance and mean of the data in the sample set D respectively;

[0072] Step s34: Set the standard parameters Use the Sigmoid function to map and adjust to [0,1], and use standard parameters The Sigmoid function value For distance value D 0i Classification is performed, and the classification mechanism is:

[0073] when When the distance value D 0i Classified as the first category;

[0074] when When the distance value D 0i Classified as the second category;

[0075] when When the distance value D 0i Classified as the third category;

[0076] And so on.

[0077] when When the distance value D 0i Classify into the Kth category;

[0078] in, Standard parameters The Sigmoid function value The minimum and maximum values ​​of

[0079] Step s35: According to the distance value D 0i According to the classification situation, determine the unit grid type, and the determination principle is:

[0080] When the distance value D 0i When classified as the first category, the corresponding unit grid type is the first category;

[0081] When the distance value D 0i When classified as the second category, the corresponding unit grid type is the second category;

[0082] When the distance value D 0i When classified as the third category, the corresponding unit grid type is the third category;

[0083] And so on.

[0084] When the distance value D 0i When classified into the Kth category, the corresponding unit grid type is the Kth category.

[0085] Step 4: Merge adjacent unit grid areas of the same type, and divide the target area into several independent areas according to the merging results;

[0086] Step 5: Determine the number of sampling points in any independent area, take soil samples at the sampling points, and measure the rth pollutant concentration value c in the soil sample of the hth independent area. hr , obtain the distribution of each pollutant in the target area; wherein, the process of determining the number of sampling points in an independent area includes the following steps:

[0087] Step s51: Count the number of independent areas corresponding to the kth soil type in the target area;

[0088] Step s52: Obtain the areas of all independent regions corresponding to the k-th soil type, respectively denoted as is the area of ​​the mth independent region corresponding to the kth soil type;

[0089] Step s53: Set the total number of sampling points required for the kth soil type to D k , the number of sampling points corresponding to m independent regions are Then the number of sampling points in the mth independent area corresponding to the kth soil type is determined according to the following model, where the expression of the model is:

[0090]

[0091] Step 6: According to the obtained dye concentration value c hr Calculate the single pollution index P of the rth pollutant in the hth independent area hr , where P hr =c kr / S r , where S r It is expressed as the risk screening value of the rth pollutant, according to the obtained single pollution index P hr The pollution level of the hth independent area is divided. Among them, the risk screening value of pollutants is determined according to GB15618-2018 "Soil Environmental Quality-Agricultural Land Soil Pollution Risk Control Standard (Trial)". The following Tables 1 and 2 are the risk screening values ​​of common pollutants in farmland soil, specifically:

[0092] Table 1 Screening value of agricultural land soil pollution risk 1

[0093]

[0094]

[0095] Table 2 Agricultural land soil pollution risk screening value 2

[0096]

[0097] The principles for classification of pollution levels are:

[0098] When P hr When ≤1, it indicates that the pollution level of the hth independent area is unpolluted;

[0099] When 1<P hr When ≤2, it indicates that the pollution level of the hth independent area is slightly polluted;

[0100] When 2<P hr When ≤3, it indicates that the pollution level of the hth independent area is slightly polluted;

[0101] When 3<P hr When ≤5, it indicates that the pollution level of the hth independent area is severely polluted;

[0102] When P hr When ≥5, it indicates that the pollution level of the hth independent area is severely polluted.

[0103] Step 7: According to the obtained single pollution index P hr Calculate the comprehensive pollution index of the hth independent area The calculation formula is: Among them, ω rThe pollution hazard coefficient of the rth pollutant, and

[0104]

[0105] The above shows and describes the basic principles and main features of the present invention and the advantages of the present invention. It should be understood by those skilled in the art that the present invention is not limited to the above embodiments. The above embodiments and descriptions are only for explaining the principles of the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, which fall within the scope of the present invention to be protected. The scope of protection of the present invention is defined by the attached claims and their equivalents.

Claims

1. A method for evaluating farmland soil health, characterized in that: include: The target area is divided into several ε×ε unit grids, and the remote sensing image data in the target area is obtained. The high-resolution panchromatic remote sensing image is fused with the low-resolution multispectral remote sensing image using the HIS model. The color features of the remote sensing image of each unit grid are decomposed into three dimensions: hue, saturation, and brightness. The hue value H of the i-th unit grid is obtained. i , saturation value S i , brightness value I i ; Construct the color feature vector set C of the i-th unit grid i ={H i , S i , I i }, get the color feature vector set C of the target area = [C i , C2, ..., C n ] T , C n is the color feature vector set of the nth unit grid, clustering the elements in the vector set C to obtain K unit grid types, corresponding the unit grid types to the soil types, and classifying the soil in the target area into K categories; Merge adjacent unit grid areas of the same type, divide the target area into several independent areas according to the merging result, determine the number of sampling points in any independent area, take soil samples at the sampling points, and measure the rth pollutant concentration value c in the soil sample of the hth independent area. hr , obtain the distribution of various pollutants in the target area; According to the obtained dye concentration value c hr Calculate the single pollution index P of the rth pollutant in the hth independent area hr , where P hr =c kr / S r , where S r It is expressed as the risk screening value of the rth pollutant, according to the obtained single pollution index P hr The pollution level of the h-th independent area is divided.

2. A method for evaluating farmland soil health according to claim 1, characterized in that: Also includes: According to the obtained single pollution index P hr Calculate the comprehensive pollution index of the hth independent area The calculation formula is: Among them, ω r The pollution hazard coefficient of the rth pollutant, and 3. A method for evaluating farmland soil health according to claim 1, characterized in that: The classification process of unit grid types includes the following steps: Step s21: Set the color feature vector set C of the i-th unit grid i ={H i , S i , I i } to obtain the normalized color feature vector set in, Step s22: Set the calibration vector set C0 = {0, 0, 0}, and calculate the normalized vector sets C i The distance value D between the calibration vector set C0 0i , Step s23: Using the distance value D 0i Create a sample set D, denoted as {D 01 , D 02 , ..., D 0n }, calculate the mean and standard deviation in the sample set D, and standardize each data point according to the calculation results. The formula is: In the formula D 0i The standard parameters of , σ and μ are the variance and mean of the data in the sample set D respectively; Step s24: Set the standard parameters Use the Sigmoid function to map and adjust to [0,1], and use standard parameters The Sigmoid function value For distance value D 0i Classification is performed, and the classification mechanism is: when When the distance value D 0i Classified as the first category; when When the distance value D 0i Classified as the second category; when When the distance value D 0i Classified as the third category; And so on. when When the distance value D 0i Classify into the Kth category; in, Standard parameters The Sigmoid function value The minimum and maximum values ​​of Step s25: According to the distance value D 0i According to the classification situation, determine the unit grid type, and the determination principle is: When the distance value D 0i When classified as the first category, the corresponding unit grid type is the first category; When the distance value D 0i When classified as the second category, the corresponding unit grid type is the second category; When the distance value D 0i When classified as the third category, the corresponding unit grid type is the third category; And so on. When the distance value D 0i When classified into the Kth category, the corresponding unit grid type is the Kth category.

4. A method for evaluating farmland soil health according to claim 1, characterized in that: The process of determining the number of sampling points in an independent area includes the following steps: Step s31: Counting the number of independent areas corresponding to the k-th soil type in the target area; Step s32: Obtain the areas of all independent regions corresponding to the kth soil type, respectively denoted as is the area of ​​the mth independent region corresponding to the kth soil type; Step s33: Set the total number of sampling points required for the kth soil type to D k , the number of sampling points corresponding to m independent regions are Then the number of sampling points in the mth independent area corresponding to the kth soil type is determined according to the following model, where the expression of the model is:

5. A method for evaluating farmland soil health according to claim 1, characterized in that: The number of sampling points of any two soil types in the target area is equal, and the locations of the sampling points are evenly distributed in any of the independent areas.

6. A method for evaluating farmland soil health according to claim 1, characterized in that: The principles for classification of pollution levels are: When P hr When ≤1, it indicates that the pollution level of the hth independent area is unpolluted; When 1<P hr When ≤2, it indicates that the pollution level of the hth independent area is slightly polluted; When 2<P hr When ≤3, it indicates that the pollution level of the hth independent area is slightly polluted; When 3<P hr When ≤5, it indicates that the pollution level of the hth independent area is severely polluted; When P hr When ≥5, it indicates that the pollution level of the hth independent area is severely polluted.

7. A farmland soil health assessment system, characterized in that: The system is used to implement the steps of a method for evaluating farmland soil health according to any one of claims 1 to 6, including: A remote sensing image acquisition module is used to divide the target area into a plurality of ε×ε unit grids and acquire remote sensing image data in the target area; The remote sensing image processing module is used to fuse the high-resolution panchromatic remote sensing image with the low-resolution multispectral remote sensing image using the HIS model, decompose the color features of the remote sensing image of each unit grid into three dimensions: hue, saturation, and brightness, and obtain the hue value H of the i-th unit grid. i , saturation value S i , brightness value I i ; Soil classification module, used to construct the color feature vector set C of the i-th unit grid i ={H i , S i , I i }, get the color feature vector set C of the target area = [C i , C2, ..., C n ] T , clustering each element in the vector set C, obtaining K unit grid types, corresponding the unit grid types to the soil types, and classifying the soil in the target area into K categories; A sampling point quantity calculation module is used to merge adjacent unit grid areas of the same type, divide the target area into a plurality of independent areas according to the merging result, and determine the number of sampling points in any of the independent areas; The pollutant data acquisition module is used to sample the soil at the sampling point and determine the rth pollutant concentration value c in the soil sample of the hth independent area. hr , obtain the distribution of various pollutants in the target area; The pollution degree assessment module is used to obtain the pollution concentration value c hr Calculate the single pollution index P of the rth pollutant in the hth independent area hr , according to the obtained single pollution index P hr Classify the pollution level of the h-th independent area; The comprehensive pollution index calculation module is used to obtain the single pollution index P hr Calculate the comprehensive pollution index of the hth independent area 8. The farmland soil health assessment system according to claim 7, characterized in that: The system includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor can implement the steps of a method for evaluating farmland soil health as described in any one of claims 1 to 7 when executing the program.

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