Method and system for inverting iron element in soil based on vegetation spectral characteristics

Abstract

The invention discloses a method and system for inverting an iron element in soil based on vegetation spectral characteristics, and the method comprises the steps: obtaining the spectral data of a target vegetation canopy, and enabling the spectral range to cover 350-2500nm; preprocessing the spectral data of the target vegetation canopy, at least removing abnormal spectrums and envelope lines, and obtaining preprocessed spectral data of the target vegetation canopy; extracting reflectivity absorption depth data of a characteristic absorption valley position in the preprocessed spectral data of the target vegetation canopy; and inputting the reflectivity absorption depth data into a preset multiple linear regression equation to obtain the concentration of the iron element in the soil. By analyzing the quantitative relation between the vegetation spectral characteristics and the iron element concentration of the soil, the iron element concentration of the soil in the vegetation coverage area can be rapidly and accurately detected.

Description

Technical Field

[0001] The present invention relates to the technical field of soil element content detection, and more specifically, to a method and system for inverting iron elements in soil based on vegetation spectral characteristics. Background Art

[0002] The existing technology mainly relies on traditional geological exploration methods and hyperspectral remote sensing technology; traditional geological exploration methods include geological survey, drilling, trenching, etc. Although these methods can obtain accurate geological information, they have the disadvantages of low efficiency, long exploration cycle, difficulty in quickly obtaining information in large areas, high cost, environmental damage, etc.; hyperspectral remote sensing technology obtains the spectral characteristics of vegetation and analyzes its relationship with the concentration of soil iron elements. However, the existing technology has the following disadvantages: insufficient accuracy: in the application of the existing model in vegetated areas, the inversion accuracy is low and it is difficult to meet the actual needs; limited applicability: the adaptability of different vegetation types and growth stages is poor and it is difficult to be widely promoted; lack of quantitative relationship: the quantitative relationship between vegetation spectral characteristics and soil iron element concentration has not been fully established, resulting in insufficient reliability of the inversion results. Summary of the Invention

[0003] In view of the above problems, the purpose of the present invention is to provide a method and system for inverting iron elements in soil based on vegetation spectral characteristics, and by analyzing the quantitative relationship between vegetation spectral characteristics and soil iron element concentration, to achieve rapid and accurate detection of the soil iron element concentration in vegetated areas.

[0004] The first aspect of the present invention provides a method for inverting iron elements in soil based on vegetation spectral characteristics, including: Obtaining spectral data of the target vegetation canopy, with the spectral range covering 350 - 2500 nm; Preprocessing the spectral data of the target vegetation canopy, at least including removing abnormal spectra and detrending, to obtain the preprocessed spectral data of the target vegetation canopy; Extracting the reflectance absorption depth data at the positions of characteristic absorption valleys in the preprocessed spectral data of the target vegetation canopy; Inputting the reflectance absorption depth data into a preset multiple linear regression equation to obtain the concentration of iron elements in the soil.

[0005] In this solution, the step of obtaining the spectral data of the target vegetation canopy specifically includes: Extracting the canopy leaves of the target vegetation and setting at least one collection point on the canopy leaves of the target vegetation; Based on a preset spectrometer, obtaining the spectral data of the collection point; Calculating the average value of the spectral data of the collection point to obtain the spectral data corresponding to the target vegetation canopy.

[0006] In this solution, it further includes: Obtain the environmental data information of the canopy leaves of the target vegetation and the status data information of the corresponding canopy leaves; Extract the environmental parameters from the environmental data information of the canopy leaves of the target vegetation. If the environmental parameters are not within the preset environmental parameter range, delete the canopy leaves of the corresponding target vegetation and replace the canopy leaves of the target vegetation again; Extract the status parameters from the status data information of the canopy leaves of the target vegetation. If the status parameters are not within the preset status parameter range, delete the canopy leaves of the corresponding target vegetation and replace the canopy leaves of the target vegetation again.

[0007] In this solution, the step of removing the envelope line specifically includes: Based on the spectral data, construct the corresponding spectral curve and extract the maximum points in the corresponding spectral curve, which are set as the peak points; Starting from the peak point, calculate the slopes of each maximum point in the long-wave direction and the short-wave direction respectively. Use the points with the maximum and minimum slopes as the next endpoints of the envelope line. Then, starting from the endpoints, calculate the slopes of each maximum point in the long-wave direction and the short-wave direction respectively. Use the points with the maximum and minimum slopes as the next endpoints of the envelope line, and so on until the end of the spectral curve to find all endpoints; Connect all the endpoints and the starting point to form the envelope line; Based on the spectral reflectance, remove the reflectance of the corresponding wavelength band on the envelope line to obtain the preprocessed spectral data.

[0008] In this solution, after extracting the reflectance absorption depth data at the characteristic absorption valley positions in the preprocessed spectral data of the target vegetation canopy, it further includes: Extract the absolute value of the correlation coefficient between the characteristic absorption valley positions and the iron element content at the corresponding positions; If the absolute value of the correlation coefficient is less than or equal to the preset first threshold, delete the reflectance absorption depth data at the corresponding characteristic absorption valley positions; If the absolute value of the correlation coefficient is greater than the preset correlation coefficient threshold, save the reflectance absorption depth data at the corresponding characteristic absorption valley positions.

[0009] In this solution, the steps of constructing the multiple linear regression equation specifically include: Obtain the characteristics and characteristic values of the experimental vegetation; Compare and analyze the experimental vegetation with the preset sample vegetation to obtain the similarity value; If the similarity value is greater than or equal to a preset similarity threshold, the experimental vegetation corresponding to the similarity value is saved; if the similarity value is less than the preset similarity threshold, the experimental vegetation corresponding to the similarity value is deleted; Extract the iron element concentration value of the soil where the saved experimental vegetation is located, and set it as the dependent variable; Extract the spectral data of the canopy of the saved experimental vegetation, and based on the spectral data of the canopy of the saved experimental vegetation, obtain the reflectance absorption depth data at different spectral absorption valley positions in the spectral data of the canopy of the corresponding saved experimental vegetation, and divide it according to different spectral absorption valley positions to obtain multiple independent variable sets; Form a linear equation with one variable from the independent variable and the dependent variable in any one of the independent variable sets, and solve it to obtain a linear regression equation with one variable; After traversing all the independent variable sets, obtain multiple linear regression equations with one variable, and fuse the multiple linear regression equations with one variable to obtain a multiple linear regression equation.

[0010] In this solution, after obtaining the linear regression equation with one variable, it further includes: Extract the goodness of fit and root mean square error corresponding to the linear regression equation with one variable; If the goodness of fit is greater than a preset first threshold, or the root mean square error is less than a preset second threshold, the corresponding linear regression equation with one variable is saved; If the goodness of fit is less than or equal to the preset first threshold and the root mean square error is greater than or equal to the preset second threshold, the corresponding linear regression equation with one variable is deleted.

[0011] In the second aspect of the present invention, a system for inverting iron elements in soil based on vegetation spectral characteristics is provided, including a memory and a processor. A method program for inverting iron elements in soil based on vegetation spectral characteristics is stored in the memory. When the method program for inverting iron elements in soil based on vegetation spectral characteristics is executed by the processor, the following steps are implemented: Obtain the spectral data of the canopy of the target vegetation, and the spectral range covers 350 - 2500 nm; Preprocess the spectral data of the canopy of the target vegetation, including at least removing abnormal spectra and detrending to obtain the preprocessed spectral data of the canopy of the target vegetation; Extract the reflectance absorption depth data at the characteristic absorption valley positions in the preprocessed spectral data of the canopy of the target vegetation; Input the reflectance absorption depth data into a preset multiple linear regression equation to obtain the iron element concentration in the soil.

[0012] In this solution, the step of obtaining the spectral data of the canopy of the target vegetation specifically includes: Extract the canopy leaves of the target vegetation and set at least one collection point on the canopy leaves of the target vegetation; Based on a preset spectrometer, obtain the spectral data of the collection point; Calculate the average value of the spectral data of the collection point to obtain the spectral data corresponding to the canopy of the target vegetation.

[0013] In this solution, it also includes: Obtain the environmental data information where the canopy leaves of the target vegetation are located and the status data information of the corresponding canopy leaves; Extract the environmental parameters in the environmental data information where the canopy leaves of the target vegetation are located. If the environmental parameters are not within the preset environmental parameter range, delete the canopy leaves of the corresponding target vegetation and replace the canopy leaves of the target vegetation again; Extract the status parameters in the status data information of the canopy leaves of the target vegetation. If the status parameters are not within the preset status parameter range, delete the canopy leaves of the corresponding target vegetation and replace the canopy leaves of the target vegetation again.

[0014] The present invention discloses a method and system for inverting iron elements in soil based on vegetation spectral characteristics. The method includes: obtaining the spectral data of the target vegetation canopy, with the spectral range covering 350 - 2500 nm; preprocessing the spectral data of the target vegetation canopy, including at least removing abnormal spectra and detrending, to obtain the preprocessed spectral data of the target vegetation canopy; extracting the reflectance absorption depth data at the positions of the characteristic absorption valleys in the preprocessed spectral data of the target vegetation canopy; inputting the reflectance absorption depth data into a preset multiple linear regression equation to obtain the iron element concentration in the soil. The present invention realizes the rapid and accurate detection of the iron element concentration in the soil in the vegetation-covered area by analyzing the quantitative relationship between the vegetation spectral characteristics and the soil iron element concentration. Description of the Drawings

[0015] Figure 1 Shows the flowchart of a method for inverting iron elements in soil based on vegetation spectral characteristics of the present invention; Figure 2 Shows the block diagram of a system for inverting iron elements in soil based on vegetation spectral characteristics of the present invention. Detailed Embodiments

[0016] In order to be able to more clearly understand the above objects, features, and advantages of the present invention, the present invention will be further described in detail below with reference to the drawings and specific embodiments. It should be noted that, without conflict, the embodiments of the present application and the features in the embodiments can be combined with each other.

[0017] In the following description, many specific details are set forth in order to provide a thorough understanding of the present invention. However, the present invention may be practiced in other ways than those specifically described herein. Therefore, the scope of the present invention is not limited by the specific embodiments disclosed below.

[0018] Figure 1 The flowchart of a method for inverting iron elements in soil based on the spectral characteristics of vegetation according to the present invention is shown.

[0019] As Figure 1 shown, the present invention discloses a method for inverting iron elements in soil based on the spectral characteristics of vegetation, including: S101, obtaining the spectral data of the target vegetation canopy, where the spectral range covers 350 - 2500 nm; S102, preprocessing the spectral data of the target vegetation canopy, including at least removing abnormal spectra and detrending, to obtain the preprocessed spectral data of the target vegetation canopy; S103, extracting the reflectance absorption depth data at the positions of characteristic absorption valleys in the preprocessed spectral data of the target vegetation canopy; S104, inputting the reflectance absorption depth data into a preset multiple linear regression equation to obtain the concentration of iron elements in the soil.

[0020] According to an embodiment of the present invention, the spectral data includes spectral data in the visible light, near-infrared, and short-wave infrared regions. During measurement, with a black board surface as the background, the leaves of the target vegetation canopy are laid flat on the corresponding black board surface and completely covered, and the measurement window of the spectrometer is tightly attached to the coverage to ensure that no external light enters to interfere. The abnormal spectra are usually removed visually or by software processing, aiming to eliminate the spectral data that obviously does not belong to parts such as leaves. After obtaining the preprocessed spectral data of the target vegetation canopy, the absorption valley positions in the spectral curve within the spectral range of 350 - 2500 nm are obtained by using the preprocessed text format data or the corresponding software, such as absorption valley positions at 501 nm, 674 nm, 972 nm, 1166 nm, etc., and then the reflectance absorption depth corresponding to the spectral absorption valley positions obtained by screening is read by the preprocessed text format data or the corresponding software.

[0021] According to an embodiment of the present invention, the step of obtaining the spectral data of the target vegetation canopy specifically includes: extracting the canopy leaves of the target vegetation and setting at least one collection point on the canopy leaves of the target vegetation; obtaining the spectral data of the collection point based on a preset spectrometer; calculating the average value of the spectral data of the collection point to obtain the spectral data corresponding to the target vegetation canopy.

[0022] It should be noted that at least 5 spectral measurements are performed at each collection point. The spectral data of each collection point is the average value of the corresponding multiple spectral measurements. The difference between each spectral measurement data of the collection point and the average value of the corresponding multiple spectral measurements is calculated to obtain the measurement error. When the measurement error is greater than the preset measurement error threshold, the spectral measurement data of this time is deleted.

[0023] According to an embodiment of the present invention, it further includes: Obtain the environmental data information of the canopy leaves of the target vegetation and the status data information of the corresponding canopy leaves; Extract the environmental parameters in the environmental data information of the canopy leaves of the target vegetation. If the environmental parameters are not within the preset environmental parameter range, the canopy leaves of the corresponding target vegetation are deleted, and the canopy leaves of the target vegetation are replaced again; Extract the status parameters in the status data information of the canopy leaves of the target vegetation. If the status parameters are not within the preset status parameter range, the canopy leaves of the corresponding target vegetation are deleted, and the canopy leaves of the target vegetation are replaced again.

[0024] It should be noted that the environmental parameters include light, temperature, humidity, etc. When the environmental parameters of the canopy leaves are not within the preset environmental parameter range, it indicates that the corresponding canopy leaves may be injured, damaged, etc. due to environmental changes, so it may cause errors in the spectral measurement data; the status parameters include color, degree of unfolding, integrity, etc. For example, situations such as the color being withered yellow, the degree of unfolding being less than 90%, and the integrity being less than 100% are set as the corresponding status parameters not being within the preset status parameter range. The degree of unfolding is the area value of the corresponding canopy leaves unfolded in the natural state divided by the area value when fully unfolded. The integrity determines whether the corresponding canopy leaves are complete. When the corresponding canopy leaves are complete, the corresponding integrity is 100%.

[0025] According to an embodiment of the present invention, the step of removing the envelope line specifically includes: Based on the spectral data, construct the corresponding spectral curve, and extract the maximum points in the corresponding spectral curve, which are set as peak points; Starting from the peak point, calculate the slopes of each maximum point in the long-wave direction and the short-wave direction respectively. Use the points with the maximum and minimum slopes as the next endpoints of the envelope line. Then, starting from the endpoints, calculate the slopes of each maximum point in the long-wave direction and the short-wave direction respectively. Use the points with the maximum and minimum slopes as the next endpoints of the envelope line, and so on until the end of the spectral curve to find all endpoints; Connect all the endpoints and the starting point to form an envelope line; Based on the spectral reflectance, remove the reflectance of the corresponding band on the envelope line to obtain the preprocessed spectral data.

[0026] It should be noted that the spectral reflectance is subtracted from the reflectance on the envelope line to obtain the preprocessed spectral data.

[0027] According to an embodiment of the present invention, after extracting the reflectance absorption depth data at the position of the characteristic absorption valley in the preprocessed spectral data of the target vegetation canopy, the following steps are further included: Extracting the absolute value of the correlation coefficient between the position of the characteristic absorption valley and the iron element content at the corresponding position; If the absolute value of the correlation coefficient is less than or equal to a preset first threshold, the reflectance absorption depth data at the corresponding characteristic absorption valley position is deleted; If the absolute value of the correlation coefficient is greater than the preset correlation coefficient threshold, the reflectance absorption depth data at the corresponding characteristic absorption valley position is saved.

[0028] It should be noted that the position of the characteristic absorption valley is the spectral absorption valley position. By comparing and analyzing the absorption depth at the spectral absorption valley position with the iron element content in the leaf, the corresponding correlation coefficient is determined. For example, if the preset correlation coefficient threshold is 0.7, the characteristic positions with the absolute value of the correlation coefficient greater than 0.7 are extracted, such as 972nm, 1166nm, etc.

[0029] According to an embodiment of the present invention, the steps for constructing the multiple linear regression equation specifically include: Obtaining the characteristics and characteristic values of the experimental vegetation; Comparing and analyzing the experimental vegetation with the preset sample vegetation to obtain a similarity value; If the similarity value is greater than or equal to the preset similarity threshold, the experimental vegetation corresponding to the similarity value is saved; if the similarity value is less than the preset similarity threshold, the experimental vegetation corresponding to the similarity value is deleted; Extracting the iron element concentration value of the soil where the saved experimental vegetation is located, and setting it as the dependent variable; Extracting the spectral data of the canopy of the saved experimental vegetation, and according to the spectral data of the canopy of the saved experimental vegetation, obtaining the reflectance absorption depth data at different spectral absorption valley positions in the spectral data of the canopy of the saved experimental vegetation, and dividing them according to different spectral absorption valley positions to obtain multiple independent variable sets; Forming a linear equation with one variable by combining the independent variable in any one of the independent variable sets and the dependent variable, and solving it to obtain a linear regression equation with one variable; After traversing all the independent variable sets, multiple linear regression equations with one variable are obtained, and the multiple linear regression equations with one variable are fused to obtain a multiple linear regression equation.

[0030] It should be noted that taking the iron element concentration value in the soil where the vegetation is located as the dependent variable and the reflectance absorption depth at different spectral absorption valley positions in the spectral data of the vegetation canopy leaves as the independent variable, the inversion models of soil iron element concentration are constructed by using the unary linear regression method and the multiple linear regression method respectively. For example, taking wheat as the experimental object, six experimental groups of iron elements with different concentration gradients are set, the initial effective concentration is 2.38 mg / kg, six parallel samples are set in each group, and pot experiments are carried out under controlled conditions to ensure that the conditions such as soil, fertilization, water, temperature, and light are consistent to reduce the influence of the external environment on the experimental results. After a certain time period, the experimental objects are screened to prevent other potential disease factors.

[0031] According to an embodiment of the present invention, after obtaining the unary linear regression equation, it further includes: Extracting the goodness of fit and root mean square error corresponding to the unary linear regression equation; If the goodness of fit is greater than a preset first threshold or the root mean square error is less than a preset second threshold, the corresponding unary linear regression equation is saved; If the goodness of fit is less than or equal to the preset first threshold and the root mean square error is greater than or equal to the preset second threshold, the corresponding unary linear regression equation is deleted.

[0032] It should be noted that the linear regression equation is screened by the goodness of fit and root mean square error of the linear regression equation. For example, the preset first threshold is 0.85 and the preset second threshold is 0.5 mg / kg.

[0033] Figure 2 The block diagram of a system for inverting iron elements in soil based on vegetation spectral characteristics according to the present invention is shown.

[0034] As Figure 2 shown, the second aspect of the present invention provides a system 2 for inverting iron elements in soil based on vegetation spectral characteristics, including a memory 21 and a processor 22. A method program for inverting iron elements in soil based on vegetation spectral characteristics is stored in the memory. When the method program for inverting iron elements in soil based on vegetation spectral characteristics is executed by the processor, the following steps are implemented: Obtaining the spectral data of the target vegetation canopy, and the spectral range covers 350 - 2500 nm; Preprocessing the spectral data of the target vegetation canopy, at least including removing abnormal spectra and de-enveloping to obtain the preprocessed spectral data of the target vegetation canopy; Extracting the reflectance absorption depth data at the characteristic absorption valley positions in the preprocessed spectral data of the target vegetation canopy; Inputting the reflectance absorption depth data into a preset multiple linear regression equation to obtain the iron element concentration in the soil.

[0035] In this solution, the steps of obtaining the spectral data of the target vegetation canopy specifically include: Extract the canopy leaves of the target vegetation and set at least one collection point on the canopy leaves of the target vegetation; Based on a preset spectrometer, obtain the spectral data of the collection point; Calculate the average value of the spectral data of the collection point to obtain the spectral data corresponding to the target vegetation canopy.

[0036] This solution also includes: Obtain the environmental data information of the canopy leaves of the target vegetation and the status data information of the corresponding canopy leaves; Extract the environmental parameters in the environmental data information of the canopy leaves of the target vegetation. If the environmental parameters are not within the preset environmental parameter range, delete the corresponding canopy leaves of the target vegetation and replace the canopy leaves of the target vegetation again; Extract the status parameters in the status data information of the canopy leaves of the target vegetation. If the status parameters are not within the preset status parameter range, delete the corresponding canopy leaves of the target vegetation and replace the canopy leaves of the target vegetation again.

[0037] The present invention discloses a method and system for inverting iron elements in soil based on vegetation spectral characteristics. The method includes: obtaining the spectral data of the target vegetation canopy, and the spectral range covers 350 - 2500 nm; preprocessing the spectral data of the target vegetation canopy, including at least removing abnormal spectra and detrending, to obtain the preprocessed spectral data of the target vegetation canopy; extracting the reflectance absorption depth data at the positions of characteristic absorption valleys in the preprocessed spectral data of the target vegetation canopy; inputting the reflectance absorption depth data into a preset multiple linear regression equation to obtain the concentration of iron elements in the soil. The present invention realizes the rapid and accurate detection of the concentration of iron elements in the soil in the vegetation-covered area by analyzing the quantitative relationship between the vegetation spectral characteristics and the concentration of soil iron elements.

[0038] In several embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are only illustrative. For example, the division of the units is only a logical function division, and there may be other division methods in actual implementation. For example, multiple units or components can be combined, or can be integrated into another system, or some features can be ignored, or not executed. In addition, the coupling, direct coupling, or communication connection between the components shown or discussed with each other can be through some interfaces. The indirect coupling or communication connection of devices or units can be electrical, mechanical, or other forms.

[0039] The units described above as separate components may or may not be physically separated, and the components shown as units may or may not be physical units; they may be located in one place or distributed over multiple network units; some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0040] In addition, in each embodiment of the present invention, each functional unit may be fully integrated in a processing unit, or each unit may be separately regarded as a unit alone, or two or more units may be integrated in one unit; the above integrated unit may be implemented in the form of hardware, or in the form of a combination of hardware and software functional units.

[0041] Those of ordinary skill in the art can understand that all or part of the steps of implementing the above method embodiments can be completed by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When the program is executed, it performs the steps including the above method embodiments; and the aforementioned storage medium includes: removable storage devices, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical discs and other various media that can store program codes.

[0042] Alternatively, if the above integrated units of the present invention are implemented in the form of software functional modules and sold or used as independent products, they can also be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of the embodiments of the present invention, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the methods described in each embodiment of the present invention. And the aforementioned storage medium includes: removable storage devices, ROM, RAM, magnetic disks, or optical discs and other various media that can store program codes.

Claims

1. A method for inverting iron elements in soil based on vegetation spectral characteristics, characterized in that, Including: Obtain the spectral data of the target vegetation canopy, with the spectral range covering 350 - 2500 nm; Preprocess the spectral data of the target vegetation canopy, including at least removing abnormal spectra and detrending to obtain the preprocessed spectral data of the target vegetation canopy; Extract the reflectance absorption depth data at the positions of characteristic absorption valleys in the preprocessed spectral data of the target vegetation canopy; Input the reflectance absorption depth data into a preset multiple linear regression equation to obtain the concentration of iron elements in the soil.

2. The method for inverting iron elements in soil based on vegetation spectral characteristics according to claim 1, wherein The step of obtaining the spectral data of the target vegetation canopy specifically includes: Extract the canopy leaves of the target vegetation and set at least one collection point on the canopy leaves of the target vegetation; Based on a preset spectrometer, obtain the spectral data of the collection point; Calculate the average value of the spectral data of the collection point to obtain the spectral data corresponding to the target vegetation canopy.

3. A method for inverting iron elements in soil based on vegetation spectral characteristics according to claim 2, characterized in that, Also including: Obtain the environmental data information of the canopy leaves of the target vegetation and the status data information of the corresponding canopy leaves; Extract the environmental parameters in the environmental data information of the canopy leaves of the target vegetation. If the environmental parameters are not within the preset environmental parameter range, delete the corresponding canopy leaves of the target vegetation and replace the canopy leaves of the target vegetation again; Extract the status parameters in the status data information of the canopy leaves of the target vegetation. If the status parameters are not within the preset status parameter range, delete the corresponding canopy leaves of the target vegetation and replace the canopy leaves of the target vegetation again.

4. A method for inverting iron elements in soil based on vegetation spectral characteristics according to claim 1, characterized in that The step of detrending specifically includes: Based on the spectral data, construct the corresponding spectral curve and extract the maximum points in the corresponding spectral curve, set as peak points; Starting from the peak point, calculate the slopes of each maximum point in the long - wave direction and the short - wave direction respectively. Use the points with the maximum and minimum slopes as the next endpoints of the envelope line. Then, starting from the endpoints, calculate the slopes of each maximum point in the long - wave direction and the short - wave direction respectively. Use the points with the maximum and minimum slopes as the next endpoints of the envelope line, and so on until the end of the spectral curve to find all endpoints; Connect all the endpoints and the starting point to form the envelope line; Based on the spectral reflectance, remove the reflectance of the corresponding wavelength band on the envelope line to obtain the preprocessed spectral data.

5. A method for inverting iron elements in soil based on vegetation spectral characteristics according to claim 1, characterized in that, After extracting the reflectance absorption depth data at the positions of characteristic absorption valleys in the preprocessed spectral data of the target vegetation canopy, it further includes: Extract the absolute value of the correlation coefficient between the position of the characteristic absorption valley and the iron element content at the corresponding position; If the absolute value of the correlation coefficient is less than or equal to a preset first threshold, delete the reflectance absorption depth data at the corresponding characteristic absorption valley position; If the absolute value of the correlation coefficient is greater than the preset correlation coefficient threshold, save the reflectance absorption depth data at the corresponding characteristic absorption valley position.

6. A method for inverting iron elements in soil based on vegetation spectral characteristics according to claim 1, characterized in that, The construction steps of the multiple linear regression equation specifically include: Obtain the characteristics and characteristic values of the experimental vegetation; Compare and analyze the experimental vegetation with the preset sample vegetation to obtain the similarity value; If the similarity value is greater than or equal to the preset similarity threshold, save the experimental vegetation corresponding to the similarity value; if the similarity value is less than the preset similarity threshold, delete the experimental vegetation corresponding to the similarity value. Extract the iron element concentration value of the soil where the preserved experimental vegetation is located, and set it as the dependent variable; Extract the spectral data of the canopy of the preserved experimental vegetation, and based on the spectral data of the canopy of the preserved experimental vegetation, obtain the reflectance absorption depth data at different spectral absorption valley positions in the spectral data of the corresponding preserved experimental vegetation canopy, and divide them according to different spectral absorption valley positions to obtain multiple independent variable sets; Form a linear equation with one variable by combining the independent variable and the dependent variable in any one of the independent variable sets, and solve it to obtain a linear regression equation with one variable; After traversing all the independent variable sets, obtain multiple linear regression equations with one variable, and fuse the multiple linear regression equations with one variable to obtain a multiple linear regression equation.

7. A method for inverting iron elements in soil based on vegetation spectral characteristics according to claim 6, characterized in that After obtaining the linear regression equation with one variable, it further includes: Extract the goodness of fit and root mean square error corresponding to the linear regression equation with one variable; If the goodness of fit is greater than a preset first threshold, or the root mean square error is less than a preset second threshold, then save the corresponding linear regression equation with one variable; If the goodness of fit is less than or equal to the preset first threshold and the root mean square error is greater than or equal to the preset second threshold, then delete the corresponding linear regression equation with one variable.

8. A system for retrieving iron elements in soil based on vegetation spectral characteristics, characterized in that, It includes a memory and a processor. A method program for inverting iron elements in soil based on vegetation spectral characteristics is stored in the memory. When the method program for inverting iron elements in soil based on vegetation spectral characteristics is executed by the processor, the following steps are implemented: Obtain the spectral data of the target vegetation canopy, and the spectral range covers 350 - 2500 nm; Preprocess the spectral data of the target vegetation canopy, including at least removing abnormal spectra and de-enveloping to obtain the preprocessed spectral data of the target vegetation canopy; Extract the reflectance absorption depth data at the characteristic absorption valley positions in the preprocessed spectral data of the target vegetation canopy; Input the reflectance absorption depth data into a preset multiple linear regression equation to obtain the iron element concentration in the soil.

9. A system for inverting iron elements in soil based on vegetation spectral characteristics according to claim 8, characterized in that, The step of obtaining the spectral data of the target vegetation canopy specifically includes: Extract the canopy leaves of the target vegetation, and set at least one collection point on the canopy leaves of the target vegetation; Based on a preset spectrometer, obtain the spectral data of the collection point; Calculate the average value of the spectral data of the collection point to obtain the spectral data corresponding to the target vegetation canopy.

10. A system for inverting iron elements in soil based on vegetation spectral characteristics according to claim 9, characterized in that, It further includes: Obtain the environmental data information of the canopy leaves of the target vegetation and the status data information of the corresponding canopy leaves; Extract the environmental parameters in the environmental data information of the canopy leaves of the target vegetation. If the environmental parameters are not within the preset environmental parameter range, then delete the corresponding canopy leaves of the target vegetation and replace the canopy leaves of the target vegetation again; Extract the status parameters in the status data information of the canopy leaves of the target vegetation. If the status parameters are not within the preset status parameter range, then delete the corresponding canopy leaves of the target vegetation and replace the canopy leaves of the target vegetation again.

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