A method, device, medium and product for identifying the thickness of thick black soil

Abstract

The present invention discloses a method, device, medium and product for identifying the thickness of thick black soil, and relates to the technical field of soil layer measurement. The method comprises: obtaining image data of soil cores of a black soil block to be measured; obtaining organic carbon determination results of multiple soil samples; each soil sample is a soil core of a preset depth; preprocessing the image data to obtain a soil brightness curve in the depth direction; fitting the organic carbon determination results of each soil sample to obtain a fitting function; taking the preset black soil thickness range of the soil sample as a constraint condition and taking the minimum organic carbon error value of all soil samples as the objective function, calculating the black soil thickness of the black soil block to be measured. The present invention can improve the accuracy of black soil thickness identification.

Description

Technical Field

[0001] The present invention relates to the technical field of soil layer measurement, and in particular to a method, device, medium and product for identifying the thickness of thick black soil. Background Art

[0002] Black soil is a very fertile soil type. Due to its high humus content and soft texture, it is very suitable for agricultural cultivation. The black soil layer is the key diagnostic layer of black soil. The thickness of black soil is the key information for studying soil erosion. It plays an important role in the estimation of soil organic carbon reserves, black soil formation, crop productivity, farmland protection and utilization. Taking the accurate assessment of black soil erosion as an example, due to wind erosion and water erosion caused by extreme climatic conditions, and large-scale soil and water loss caused by large-scale farming, the fertility of black soil began to decline and the thickness of black soil began to thin. At present, the average erosion rate in the Northeast Black Soil Region has reached 2.22mm / a. Therefore, it is very necessary to accurately measure the thickness of black soil.

[0003] At present, the main methods for identifying the thickness of black soil include the multi-index comprehensive judgment method and the expert on-site identification method. Globally, different countries or institutions have different definitions for the determination of black soil and black soil layer. These methods usually identify the black soil layer through multi-index comprehensive judgment. Multi-index comprehensive judgment requires laboratory measurement of multiple indicators. The following are the main methods used to identify the thickness of black soil worldwide: (1) The diagnostic criteria set by the World Reference Base for Soil Resources (WRB) include soil aggregate structure, organic carbon, Munsell color, and alkalinity saturation, where the organic carbon threshold is defined as greater than 0.6%; (2) The characteristics selected by the USDA Natural Resources Conservation Service include structure, rock structure, n value, color, alkalinity saturation, SOC, and soil temperature, where the SOC value is defined as greater than 0.6%. (3) The International Network of Black Soils of the Food and Agriculture Organization of the United Nations defined black soil in 2018. The core characteristics include organic carbon, color, base saturation, and soil aggregates. The organic carbon threshold is differentiated according to the geographical region where the black soil is located. The organic carbon in the cold temperate zone is greater than 1.2%, and the organic carbon in the tropical and subtropical regions is greater than 0.6%. This type of multi-index comprehensive judgment has certain disadvantages. First, in field work, the comprehensive judgment is made after all the selected characteristics are measured, which is too costly and inefficient. Secondly, these comprehensive judgment methods select a fixed threshold for soil organic carbon to delineate the black soil layer, and such a fixed threshold is not accurate enough for delineating the black soil layer, especially when facing high-precision soil organic carbon storage estimation in a small area. In many studies on black soil thickness, the more widely used method is to identify the soil layer based on color as the main feature, that is, the expert field identification method, including some current methods that use cameras and smartphone photos for machine identification. Although it can be quickly identified in the field, the expert identification method may be subject to personal expert experience, which will seriously affect the accuracy of the thickness.

[0004] From the above analysis, we can see that there is currently a lack of high-precision and efficient means to obtain the thickness of black soil, especially thick black soil with a transition layer, and the expert judgment method has great uncertainty. It is very important to obtain the thickness of black soil with high precision and efficiency. In field work, combining soil organic carbon measured in the laboratory and core drilling photos is the core idea for determining the thickness of black soil. Summary of the invention

[0005] The purpose of the present invention is to provide a method, device, medium and product for identifying the thickness of thick black soil, which can improve the accuracy of black soil thickness identification.

[0006] To achieve the above object, the present invention provides the following solutions:

[0007] A method for identifying the thickness of thick black soil, the method comprising:

[0008] Acquire image data of soil cores of black soil blocks to be tested;

[0009] Obtaining organic carbon determination results of a plurality of soil samples; each of the soil samples is a soil core drilled at a preset depth;

[0010] Preprocessing the image data to obtain a soil brightness curve in a depth direction;

[0011] Fitting the organic carbon determination results of each of the soil samples to obtain a fitting function;

[0012] Taking the preset black soil thickness range of the soil sample as a constraint condition and the minimum organic carbon error value of all the soil samples as the objective function, the black soil thickness of the black soil block to be tested is calculated; wherein the organic carbon error value of the soil sample is the difference between the organic carbon measurement result of the soil sample and the fitting value of the corresponding fitting function.

[0013] Optionally, each 10 cm depth of the soil core is a soil sample.

[0014] Alternatively, the organic carbon of several soil samples was determined using the potassium dichromate volumetric method.

[0015] Optionally, the image data is preprocessed to obtain a soil brightness curve in the depth direction, specifically including:

[0016] converting the image data into a brightness image;

[0017] Performing Savitzky-Golay filtering on the brightness image in the horizontal direction to obtain a filtered image;

[0018] Averaging the filtered image in the horizontal direction to obtain a soil brightness curve in the depth direction after averaging;

[0019] The soil brightness curve in the depth direction after averaging is subjected to Savitzky-Golay filtering to obtain the filtered soil brightness curve in the depth direction, and the filtered soil brightness curve in the depth direction is used as the soil brightness curve in the depth direction.

[0020] Optionally, the fitting function is:

[0021]

[0022] Where SOC(x) is the fitted soil organic carbon value, x is the depth of the soil sample, SOC0 is the soil organic carbon value of the surface soil, and SOC Inf represents the soil organic carbon value remaining below the black soil thickness, that is, the threshold for determining the black soil thickness, α is the fitting parameter, and BSD is the black soil thickness.

[0023] Optionally, the constraint condition is:

[0024] lb≤BSD≤ub;

[0025] 0≤α≤1000;

[0026] 1≤SOC0≤8;

[0027] Wherein, BSD is the black soil thickness, lb is the pre-estimated minimum depth of the black soil thickness, ub is the pre-estimated maximum depth of the black soil thickness; α is the fitting parameter; SOC0 is the soil organic carbon value of the surface soil.

[0028] Optionally, the objective function is:

[0029] f(x)=min∑(y m -y p ) 2 ;

[0030] Among them, f(x) is the loss function, y m is the measured value of soil organic carbon, y p is the fitted value of soil organic carbon.

[0031] A computer device comprises: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement any of the above-mentioned methods for identifying the thickness of thick black soil.

[0032] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements any of the above-mentioned methods for identifying the thickness of thick black soil.

[0033] A computer program product comprises a computer program, which, when executed by a processor, implements any of the above-mentioned methods for identifying the thickness of thick black soil.

[0034] According to the specific embodiments provided by the present invention, the present invention discloses the following technical effects:

[0035] The present invention provides a method, device, medium and product for identifying the thickness of thick black soil, which greatly improves the accuracy and determination efficiency of the black soil thickness by combining the fitting function results of soil organic carbon with the core photo and soil brightness curve. In addition, the present invention does not use a fixed threshold of soil organic carbon to determine the black soil thickness, but uses a variable threshold to improve the rationality and scientificity of the black soil thickness determination process, and also avoids the problem of mismatch between the black soil thickness and the threshold caused by the fixed threshold. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0037] Figure 1 A schematic flow chart of a method for identifying the thickness of thick black soil provided in Example 1 of the present invention;

[0038] Figure 2 This is a schematic diagram of the original soil core photo and the complete soil core photo after splicing;

[0039] Figure 3 It is a schematic diagram of the comparison between soil organic carbon fitting, core photographs and soil brightness curve;

[0040] Figure 4 A schematic flow chart of a method for identifying the thickness of thick black soil provided in Example 1 of the present invention;

[0041] Figure 5 This is a diagram of the internal structure of a computer device. DETAILED DESCRIPTION

[0042] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. 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 creative work are within the scope of protection of the present invention.

[0043] The purpose of the present invention is to provide a method, device, medium and product for identifying the thickness of thick black soil, aiming to improve the accuracy of black soil thickness identification.

[0044] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0045] Example 1

[0046] like Figures 1 to 4 As shown, the method for identifying the thickness of thick black soil in this embodiment includes:

[0047] Step S1: Acquire the image data of the soil core of the black soil block to be tested.

[0048] In practical applications, select the test site, determine the black soil plot to be tested, and select the sampling site inside the plot as much as possible, avoiding the edge of the field, roadside, ditch side, special terrain and places where fertilizers have been piled. Select a soil sampler with side windows, use a gasoline-powered drill to take soil samples, and take photos of the soil core as soon as the sample is taken. The soil core photos obtained are cropped and spliced ​​to form a coherent soil core photo. Figure 2 shown.

[0049] Step S2: Obtaining organic carbon determination results of a plurality of soil samples; each of the soil samples is a soil core drilled at a preset depth.

[0050] Specifically, each soil core drilled at a depth of 10 cm is a soil sample. The organic carbon of multiple soil samples is determined by potassium dichromate volumetric method.

[0051] In practical applications, soil samples are collected, one soil sample per 10 cm depth, and sent to the laboratory for soil organic carbon determination, which is determined using the potassium dichromate volumetric method.

[0052] Step S3: pre-process the image data to obtain a soil brightness curve in the depth direction.

[0053] S3 specifically includes:

[0054] Step S31: converting the image data into a brightness image.

[0055] Step S32: performing Savitzky-Golay filtering on the brightness image in the horizontal direction to obtain a filtered image.

[0056] Step S33: averaging the filtered image in the horizontal direction to obtain a soil brightness curve in the depth direction after averaging.

[0057] Step S34: performing Savitzky-Golay filtering on the soil brightness curve in the depth direction after averaging to obtain the filtered soil brightness curve in the depth direction, and using the filtered soil brightness curve in the depth direction as the soil brightness curve in the depth direction.

[0058] In practical applications, the RGB photo is first converted into a brightness image, and the Savitzky-Golay filter is performed in the horizontal direction of the drill core photo. After the filtering is completed, the average is calculated to obtain the brightness average of all pixels in the horizontal direction of the depth. After obtaining the brightness values ​​of all depths, the Savitzky-Golay filter is performed in the depth direction to eliminate the influence of noise and show the most reasonable and objective soil brightness curve.

[0059] Step S4: fitting the organic carbon determination results of each soil sample to obtain a fitting function.

[0060] Specifically, the fitting function is:

[0061]

[0062] Where SOC(x) is the fitted soil organic carbon value, x is the depth of the soil sample, SOC0 is the soil organic carbon value of the surface soil, and SOC Inf represents the soil organic carbon value remaining below the black soil thickness, that is, the threshold for determining the black soil thickness, α is the fitting parameter, BSD is the black soil thickness, lb is the minimum depth of the black soil thickness estimated in advance, and ub is the maximum depth of the black soil thickness estimated in advance.

[0063] Step S5: Taking the preset black soil thickness range of the soil sample as a constraint condition and the minimum organic carbon error value of all the soil samples as the objective function, calculate the black soil thickness of the black soil block to be tested; wherein the organic carbon error value of the soil sample is the difference between the organic carbon measurement result of the soil sample and the fitting value of the corresponding fitting function.

[0064] Specifically, the constraints are:

[0065] lb≤BSD≤ub.

[0066] 0≤α≤1000.

[0067] 1≤SOC0≤8.

[0068] Wherein, BSD is the black soil thickness, lb is the pre-estimated minimum depth of the black soil thickness, ub is the pre-estimated maximum depth of the black soil thickness; α is the fitting parameter; SOC0 is the soil organic carbon value of the surface soil.

[0069] The objective function is:

[0070] f(x)=min∑(y m -y p ) 2 .

[0071] Among them, f(x) is the loss function, y mis the measured value of soil organic carbon, y p is the fitted value of soil organic carbon.

[0072] In practical applications, such as Figure 3 As shown in the figure, due to the existence of transition layer in black soil, the upper and lower limits of the black soil thickness range are determined by combining photos, color curves and on-site observations. When determining the upper and lower limits of the range, 5 cm is taken as the starting point from the surface and the determination is made every 10 cm. Taking a certain borehole as an example, the black soil thickness range is determined to be 0.55m to 0.65m.

[0073] The measured soil organic carbon results were fitted. The upper and lower limits of the determined black soil thickness range were used during fitting. The loss function was defined for the fitting formula of soil organic carbon. The loss function was optimized to the minimum to fit the results of black soil thickness.

[0074] The beneficial effects of the present invention are:

[0075] 1. The present invention innovatively combines the fitting function results of soil organic carbon with core drilling photos and soil brightness curves, which greatly improves the accuracy and determination efficiency of black soil thickness compared with previous black soil thickness determination methods.

[0076] 2. The present invention first determines a method for determining the thickness of black soil without using a fixed threshold of soil organic carbon, thereby improving the rationality and scientificity of the black soil thickness measurement process, and also avoiding the problem of mismatch between black soil thickness and threshold caused by a fixed threshold.

[0077] Example 2

[0078] A computer device includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the method for identifying the thickness of thick black soil in Example 1.

[0079] Example 3

[0080] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the method for identifying the thickness of thick black soil in Example 1.

[0081] Example 4

[0082] A computer program product includes a computer program, which implements the method for identifying the thickness of thick black soil in embodiment 1 when executed by a processor.

[0083] Example 5

[0084] A computer device, which may be a database, may have an internal structure as shown in Figure 5As shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, referred to as I / O) and a communication interface. The processor, the memory and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store pending transactions. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, the method for identifying the thickness of thick black soil in Example 1 is implemented.

[0085] It should be noted that the object information (including but not limited to object device information, object personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in the present invention are all information and data authorized by the object or fully authorized by all parties, and the collection, use and processing of relevant data need to comply with relevant laws, regulations and standards of relevant countries and regions.

[0086] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiments can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided by the present invention can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided by the present invention may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited thereto. The processor involved in each embodiment provided by the present invention may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but are not limited thereto.

[0087] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0088] The principles and implementation methods of the present invention are described in this article using specific examples. The description of the above embodiments is only used to help understand the method and core idea of ​​the present invention. At the same time, for those skilled in the art, according to the idea of ​​the present invention, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting the present invention.

Claims

1. A method for identifying the thickness of thick black soil, It is characterized in that The method comprises: Acquire image data of soil cores of black soil blocks to be tested; Obtaining organic carbon determination results of a plurality of soil samples; each of the soil samples is a soil core drilled at a preset depth; Preprocessing the image data to obtain a soil brightness curve in a depth direction; Fitting the organic carbon determination results of each of the soil samples to obtain a fitting function; Taking the preset black soil thickness range of the soil sample as a constraint condition and the minimum organic carbon error value of all the soil samples as the objective function, the black soil thickness of the black soil block to be tested is calculated; wherein the organic carbon error value of the soil sample is the difference between the organic carbon measurement result of the soil sample and the fitting value of the corresponding fitting function.

2. The method for identifying the thickness of thick black soil according to claim 1, It is characterized in that Every 10 cm depth of the soil core is a soil sample.

3. The method for identifying the thickness of thick black soil according to claim 1, It is characterized in that The potassium dichromate volumetric method was used to determine the organic carbon in several soil samples.

4. The method for identifying the thickness of thick black soil according to claim 1, It is characterized in that The image data is preprocessed to obtain a soil brightness curve in the depth direction, specifically including: converting the image data into a brightness image; Performing Savitzky-Golay filtering on the brightness image in the horizontal direction to obtain a filtered image; Averaging the filtered image in the horizontal direction to obtain a soil brightness curve in the depth direction after averaging; The soil brightness curve in the depth direction after averaging is subjected to Savitzky-Golay filtering to obtain the filtered soil brightness curve in the depth direction, and the filtered soil brightness curve in the depth direction is used as the soil brightness curve in the depth direction.

5. The method for identifying the thickness of thick black soil according to claim 1, It is characterized in that The fitting function is: Where SOC(x) is the fitted soil organic carbon value, x is the depth of the soil sample, and SOC 0 is the soil organic carbon value of the surface soil, SOC Inf represents the soil organic carbon value remaining below the black soil thickness, that is, the threshold for determining the black soil thickness, α is the fitting parameter, and BSD is the black soil thickness.

6. The method for identifying the thickness of thick black soil according to claim 1, It is characterized in that The constraints are: lb≤BSD≤ub; 0≤α≤1000； 1≤SOC 0 ≤8; Where BSD is the thickness of black soil, lb is the minimum depth of the black soil thickness estimated in advance, ub is the maximum depth of the black soil thickness estimated in advance; α is the fitting parameter; SOC 0 is the soil organic carbon value of the topsoil.

7. The method for identifying the thickness of thick black soil according to claim 1, It is characterized in that The objective function is: f(x)=min∑(y m -y p ) 2 ; Among them, f(x) is the loss function, y m is the measured value of soil organic carbon, y p is the fitted value of soil organic carbon.

8. A computer device, include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the method for identifying the thickness of thick black soil as described in any one of claims 1-7.

9. A computer-readable storage medium having a computer program stored thereon, It is characterized in that When the computer program is executed by a processor, the method for identifying the thickness of thick black soil as described in any one of claims 1 to 7 is implemented.

10. A computer program product comprising a computer program, It is characterized in that When the computer program is executed by a processor, the method for identifying the thickness of thick black soil as described in any one of claims 1 to 7 is implemented.

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