Submarine Sediment Inversion Verification Method

Abstract

The present invention belongs to the technical field of marine surveying and mapping, and particularly relates to a method for verifying seabed sediment inversion, which includes: respectively drawing an actual sediment distribution map and an inverted sediment distribution map according to sediment sampling and inversion results; calculating the areas occupied by different sediment types in the actual sediment distribution map and the overlapping areas with the inverted sediment distribution map; calculating the coincidence rate of each type of sediment in the inverted sediment distribution map relative to the actual sediment distribution map, and using this as the accuracy rate of the inversion method used for each type of sediment. By calculating the coincidence rate of each sediment type in the inverted sediment distribution map relative to the actual sediment distribution map and through the comparison of surface with surface, the present invention reflects the inversion accuracy rate of the inversion method for each sediment type, reduces the adverse impact on the overall inversion result caused by inversion errors at some points, and improves the accuracy of the verification result.

Description

Technical Field

[0001] The present invention belongs to the technical field of marine surveying and mapping, and particularly relates to a method for verifying seabed sediment inversion. Background Art

[0002] Seabed sediment mainly refers to the shallow surface sediments and seabed rocks of the seabed. Seabed sediment detection is an important part of marine geological research and marine surveying and mapping. At present, there are two main sediment detection methods: sampling analysis method and acoustic telemetry method. The sampling analysis method can directly obtain accurate information of the sediment, but the sampling process is time-consuming and laborious, and only discrete sediment data can be obtained. The acoustic telemetry method refers to using technical methods such as multi-beam, side-scan sonar, and shallow stratigraphic profile to obtain the acoustic echo signals of the seabed sediment, and then processing and analyzing the echo signals to invert the classification of the seabed sediment. Compared with the sampling analysis method, the acoustic telemetry method can obtain continuous sediment information and has higher efficiency when conducting large-area sediment detection.

[0003] There are mainly two ways to carry out sediment inversion by acoustic telemetry: one is based on the geoacoustic model, input relevant sediment parameters into the model, make the acoustic parameters calculated by the model closest to the measured results, output other parameters of the sediment, and then invert the sediment classification information. The other is to use statistical and machine learning methods to analyze and train a certain amount of sampling data and acoustic parameter information to realize the automatic classification of the seabed sediment. No matter which way is used, the workload of later data processing is relatively large, and the inversion accuracy depends relatively on the accuracy of data processing and interpretation.

[0004] At present, the methods for verifying the sediment inversion results are all to compare the measured sediment information at a certain number of sampling sites with the sediment information at the corresponding positions obtained by inversion, analyze the number of correct and wrong samples, and evaluate the inversion accuracy. However, when the spatial resolution of the acoustic signal is low, this verification method is prone to the situation that the inversion results do not match the measured results at some positions, resulting in inaccurate evaluation of the sediment inversion results. Summary of the Invention

[0005] The purpose of the present invention is to provide a method for verifying seabed sediment inversion to solve the problems existing in the background art.

[0006] To achieve the above purpose, the present invention provides the following technical solution: A method for verifying seabed sediment inversion, characterized in that it includes the following steps:

[0007] Step 1: According to the sampling and inversion results, draw the actual sediment distribution map and the inverted sediment distribution map respectively;

[0008] Step 2: Import the above image files into the computer, and use the MATLAB programming software to calculate the areas occupied by different sediment types in the actual sediment distribution map and the overlapping area with the inverted sediment distribution map respectively;

[0009] Step 3: Calculate the coincidence rate of each type of sediment in the inverted sediment distribution map relative to the actual sediment distribution map based on the areas obtained in Step 2, and use this as the accuracy rate of this inversion method for each type of sediment.

[0010] Preferably, in Step 1, according to the sampling and inversion results, use the Surfer drawing software, and use the Kriging interpolation method to draw the actual sediment distribution map and the inverted sediment distribution map, and set the same colorbar. In a single distribution map, fill different colors to represent different sediment types.

[0011] Preferably, in Step 1, it is required that the coordinate ranges, actual regional areas, and map sizes represented by the actual sediment distribution map and the inverted sediment distribution map are the same, and export and save them as JPG format image files with the same pixel size.

[0012] Preferably, in Step 2, use the MATLAB programming software to calculate the areas occupied by different types of sediment in the actual sediment distribution map and the overlapping areas of each type of sediment with the inverted sediment distribution map, specifically including:

[0013] Step 2-1: Use MATLAB to read the corresponding JPG image files of the actual sediment distribution map and the inverted sediment distribution map respectively;

[0014] Step 2-2: Convert the RGB values of the image to grayscale values, and determine the grayscale values corresponding to the filling colors used for each sediment type;

[0015] Step 2-3: Convert the grayscale value matrix to a binary matrix in the form of 0-1 according to the grayscale values corresponding to different sediment types;

[0016] Step 2-4: Calculate the actual distribution area sizes corresponding to each sediment type;

[0017] Step 2-5: Calculate the overlapping areas of each sediment type in the actual sediment distribution map and the inverted sediment distribution map.

[0018] Preferably, in Step 2-1, use the imread function to read the corresponding JPG image files of the actual sediment distribution map and the inverted sediment distribution map respectively, and save them in the form of a three-dimensional numerical matrix of unit8 data format, and the matrix order depends on the image pixel size.

[0019] Preferably, in the step 2-2, the RGB values of the image are converted into grayscale values by the rgb2gray function, and the pcolor function is used to plot the converted grayscale value matrix. By comparing with the original substrate distribution map, the grayscale values corresponding to the filling colors used for each substrate type are determined, and the grayscale values corresponding to various substrates are clarified.

[0020] Preferably, the step 2-3 specifically includes: taking the grayscale value corresponding to a certain substrate as a reference, and using ±10 as the screening error within the allowable accuracy. The grayscale value matrices formed by the actual substrate distribution map and the inverted substrate distribution map are respectively screened and assigned values. The pixel points corresponding to this type of substrate are assigned a value of 1, and the pixel points in the remaining positions are assigned a value of 0, so as to convert the numerical matrix of 0-255 into a binary matrix of 0-1 form.

[0021] Preferably, in the step 2-4, the specific method for calculating the distribution area: for the binary matrix converted from the actual substrate distribution map, calculate the number of pixel points with the value of "1" therein, which represents the size of the actual distribution area corresponding to this substrate type, and is denoted as S1 i , where the subscript i represents different substrate types.

[0022] Preferably, the step 2-5 specifically includes: subtracting the binary matrices converted from the actual substrate distribution map and the inverted substrate distribution map to obtain a new numerical matrix. The pixel point area with the value of "1" in the new matrix represents the area of the inaccurate inversion result area, and the number of pixel points represents the area of the inaccurate area, denoted as S2 i , subtracting the area of the inaccurate inversion area from the actual distribution area of this substrate obtained in the step 2-4, which is the overlapping area size of this substrate in the actual substrate distribution map and the inverted substrate distribution map, denoted as S3 i , S3 i =S1 i -S2 i .

[0023] Preferably, the step 3 specifically includes: comparing the overlapping area calculated in the step 2 with the actual distribution area to obtain the overlapping rate, and the calculation formula is:

[0024] For multiple substrate types, repeat the operation to sequentially obtain the overlapping rates of each substrate type in the inverted substrate distribution map relative to the actual substrate distribution map, and use this as the inversion accuracy rate of this inversion method for each substrate type, so as to verify and evaluate this inversion method.

[0025] The beneficial effects of the present invention are:

[0026] Compared with the traditional point-to-point comparison and verification, the method of the present invention calculates the coincidence rate of each sediment type in the inverted sediment distribution map relative to the actual sediment distribution map, and uses the ratio between surfaces to represent the inversion accuracy of the inversion method for each sediment type, reducing the adverse impact on the overall inversion result caused by inversion errors at some points. Especially in the case of large-area surveys and insufficient acoustic inversion spatial resolution, the effect is more significant and has important application value. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 is the flowchart of the work of the present invention;

[0028] Figure 2 is the actual sediment distribution map in a specific embodiment;

[0029] Figure 3 is the inverted sediment distribution map in a specific embodiment;

[0030] Figure 4 is the image drawn after converting the actual sediment distribution map in a specific embodiment into a grayscale matrix. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0031] The following describes the specific embodiments of the present invention in detail with reference to the accompanying drawings and preferred embodiments.

[0032] In the description of the present invention, it should be understood that the terms "center", "longitudinal", "lateral", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", etc. indicate the orientation or positional relationship based on the orientation or positional relationship shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation of the present invention. In addition, the terms "first", "second", etc. are only used for descriptive purposes and cannot be understood as indicating or implying relative importance or implicitly indicating the quantity of the indicated technical features. Thus, the features defined with "first", "second", etc. may explicitly or implicitly include one or more of such features. In the description of the present invention, unless otherwise specified, the meaning of "plurality" is two or more.

[0033] In the description of the present invention, it should be noted that unless otherwise clearly specified and defined, the terms "installation", "connection", "linkage", "fixed connection", and "fixed joint" shall be understood in a broad sense. For example, it may be a fixed connection, a detachable connection, or an integral connection; it may be a mechanical connection or an electrical connection; it may be a direct connection or an indirect connection through an intermediate medium, and it may be the communication inside two components. For those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0034] The following further describes the present invention patent in conjunction with the accompanying drawings.

[0035] As Figure 1 shown, the present invention proposes a method for verifying seabed sediment inversion, and the method steps are as follows:

[0036] Step 1: Import the actual sediment point information obtained by sampling analysis and the sediment point information obtained by inversion into the Surfer drawing software respectively, establish a grid file by using the Kriging interpolation method, and draw the actual sediment distribution map and the inverted sediment distribution map respectively. Set the same colorbar for both, and fill them with red, yellow, and blue colors respectively to represent the ranges of mud, sand, and rock of the three sediment types. As Figure 2 、 Figure 3 shown.

[0037] Limit the longitude and latitude range of the grid to make the coordinate ranges, actual area, and map size represented by the actual sediment distribution map and the inverted sediment distribution map consistent, and export and save them as JPG format image files with the same pixel size: 690*400.

[0038] Step 2: Import the above image files into the computer, and use the MATLAB programming software to calculate the areas occupied by different sediment types in the actual sediment distribution map and the overlapping area between the actual and inverted sediment distribution maps respectively.

[0039] Step 2-1: In MATLAB, use the imread function to read the JPG image files corresponding to the actual sediment distribution map and the inverted sediment distribution map respectively, and save them in the form of a three-dimensional numerical matrix of unit8 data format. The matrix order is the same as the image pixel size, which is 690*400.

[0040] Step 2-2: Convert the RGB values of the image to grayscale values through the rgb2gray function, and use the pcolor function to plot the grayscale value matrix after conversion of the actual distribution map. As Figure 4 shown, by comparing with the original sediment distribution map, it is determined that in this embodiment, the mud corresponds to the grayscale value of 76, the sand corresponds to the grayscale value of 38, and the rock corresponds to the grayscale value of 238.

[0041] Step 2-3: Taking mud as an example, with a grayscale value of 76 as the benchmark and 76±10 as the screening range within the allowable accuracy, the grayscale value matrices formed by the actual substrate distribution map and the inverted substrate distribution map are screened and assigned respectively. The pixel points corresponding to this type of substrate are assigned a value of 1, and the pixel points in other positions are assigned a value of 0, so as to convert the numerical matrix of 0-255 into a binary matrix in the form of 0-1.

[0042] Step 2-4: For the binary matrix converted from the actual substrate distribution map, calculate the number of pixel points with the value of "1" in it, which can be used to represent the actual distribution area size corresponding to this substrate type. In this embodiment, the number of pixel points corresponding to mud is 125287, that is, S1 1 = 125287.

[0043] Step 2-5: Subtract the binary matrices converted from the actual substrate distribution map and the inverted substrate distribution map to obtain a new numerical matrix. The pixel point area with the value of "1" in the new matrix represents the area where the inversion result is inaccurate, and the number of pixel points represents the area of the inaccurate area, denoted as S2 i . In this embodiment, the S2 corresponding to mud 1 = 0, which means that for all areas where the actual substrate type is mud, the inversion results are also all mud.

[0044] Repeat steps 2-3 to 2-5 to sequentially obtain the areas S1 i occupied by mud, sand, and rock in the actual substrate distribution map, i and the overlapping area S3 with the inverted substrate distribution map.

[0045] Table 1:

[0046] Substrate type <![CDATA[S1 1 > <![CDATA[S2 i > <![CDATA[S3 i > Mud 125287 0 125287 Sand 25011 10675 14366 Rock 30416 20150 10266

[0047] Step 3: According to the areas obtained in step 2, calculate the coincidence rate of each type of substrate in the inverted substrate distribution map relative to the actual substrate distribution map. The formula is:

[0048] Taking the coincidence rate as the inversion accuracy of this inversion method for each substrate type, the calculation results are shown in Table 2:

[0049] Inversion target substrate type Inversion accuracy rate Mud 100％ Sand 57.44％ Rock 33.75％

[0050] The present invention proposes to compare the inverted substrate distribution map with the actual substrate distribution map, and verify the accuracy of substrate inversion according to the area of the region corresponding to different substrate types, so as to reduce the adverse effects caused by errors in the single-point inversion process and improve the accuracy of the substrate inversion verification result.

[0051] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements on some or all of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for verifying seabed sediment inversion, characterized in that : It includes the following steps: Step 1: According to the sampling and inversion results, respectively draw the actual sediment distribution map and the inverted sediment distribution map; Step 2: Import the above image files into the computer, and use the MATLAB programming software to calculate the area occupied by different sediment types in the actual sediment distribution map and the overlapping area with the inverted sediment distribution map respectively; Step 3: According to the areas obtained in Step 2, calculate the coincidence rate of various sediment types in the inverted sediment distribution map relative to the actual sediment distribution map, and use this as the accuracy rate of this inversion method for various sediment types; In the said Step 2, using the MATLAB programming software to calculate the area occupied by different types of sediment in the actual sediment distribution map and the overlapping area of each type of sediment with the inverted sediment distribution map, specifically including: Step 2-1: Use MATLAB to read the corresponding JPG image files of the actual sediment distribution map and the inverted sediment distribution map respectively; Step 2-2: Convert the RGB values of the image to grayscale values, and determine the grayscale values corresponding to the filling colors used for each sediment type; Step 2-3: According to the grayscale values corresponding to different sediment types, convert the grayscale value matrix into a binary matrix in the form of 0-1; Step 2-4: Calculate the actual distribution area size corresponding to each sediment type; Step 2-5: Calculate the overlapping area of each sediment type in the actual sediment distribution map and the inverted sediment distribution map; The specific steps 2-5 include: subtracting the binary matrices converted from the actual substrate distribution map and the inverted substrate distribution map to obtain a new numerical matrix. The pixel point area with a value of "1" in the new matrix represents the area of inaccurate inversion results, and the number of pixel points represents the area of the inaccurate region, denoted as S2 i , subtracting the area of the inaccurate inversion region from the actual substrate distribution area obtained in step 2-4, which is the overlapping area size of the substrate in the actual substrate distribution map and the inverted substrate distribution map, denoted as S3 i , S3 i = S1 i - S2 i .

2. The method for verifying seabed sediment inversion according to claim 1, characterized in that : In Step 1, according to the sampling and inversion results, use the Surfer drawing software, and use the Kriging interpolation method to draw the actual sediment distribution map and the inverted sediment distribution map, and set the same colorbar. In a single distribution map, different sediment types are filled with different colors.

3. The method for verifying seabed sediment inversion according to claim 1, characterized in that : In Step 1, it is required that the coordinate ranges, actual regional areas, and map sizes represented by the actual sediment distribution map and the inverted sediment distribution map are the same, and they are exported and saved as JPG format image files with the same pixel size.

4. The method for verifying seabed sediment inversion according to claim 1, characterized in that: In the said Step 2-1, use the imread function to read the corresponding JPG image files of the actual sediment distribution map and the inverted sediment distribution map respectively, and save them in the form of a three-dimensional numerical matrix in the unit8 data format, and the matrix order depends on the image pixel size.

5. The method for verifying seabed sediment inversion according to claim 4, characterized in that: In the said Step 2-2, through the rgb2gray function, convert the RGB values of the image to grayscale values, use the pcolor function to draw the converted grayscale value matrix, and by comparing with the original sediment distribution map, determine the grayscale values corresponding to the filling colors used for each sediment type, and clarify the grayscale values corresponding to each type of sediment.

6. The method for verifying seabed sediment inversion according to claim 4, characterized in that: The specific steps of step 2-3 include: taking the gray value corresponding to a certain type of bottom sediment as a reference, and using ±10 as the screening error within the allowable accuracy. The gray value matrices formed by the actual bottom sediment distribution map and the inverted bottom sediment distribution map are screened and assigned respectively. The pixel points corresponding to this type of bottom sediment are assigned 1, and the pixel points in other positions are assigned 0, so as to convert the numerical matrix of 0-255 into a binary matrix of 0-1 form.

7. The method for verifying the inversion of submarine bottom sediment according to claim 4, characterized in that: In the above steps 2-4, the specific method for calculating the distribution area is as follows: for the binary matrix converted from the actual substrate distribution map, calculate the number of pixels with a value of "1", which represents the actual distribution area size corresponding to the substrate type, denoted as S1 i , where the subscript i represents different substrate types.

8. The method for verifying the inversion of submarine bottom sediment according to claim 1, characterized in that: Step 3 specifically includes: comparing the overlapping area calculated in Step 2 with the actual distribution area to obtain an overlapping rate, and the calculation formula is: , For multiple types of bottom sediment, the coincidence rate of each type of bottom sediment in the inverted bottom sediment distribution map relative to the actual bottom sediment distribution map is obtained by repeating the operation in turn, and this is used as the inversion accuracy rate of the inversion method for each type of bottom sediment, so as to verify and evaluate the inversion method.

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