Method for Inverting Water Content of Beach Surface Layer Based on Point Cloud Intensity

Abstract

The present invention relates to a method for inverting the moisture content of the beach surface layer based on point cloud intensity. It includes: Step 1, select a beach sample plot and use a three-dimensional laser scanner to obtain the point cloud data of the beach; Step 2, preprocess the obtained point cloud data and construct a correction model for the incident angle and distance effect of the point cloud intensity; Step 3, conduct an indoor scanning experiment, calibrate the point cloud intensity of sand samples with different moisture contents, fit the function between the point cloud intensity and the moisture content, construct a moisture content inversion model, and finally obtain the inversion result of the moisture content of the beach surface layer. The present invention utilizes the point cloud intensity information obtained by the three-dimensional laser scanner to construct a moisture content inversion model for the beach surface layer, reduces the monitoring difficulty of the moisture content of the beach surface layer, and improves the monitoring efficiency and accuracy.

Description

Technical Field

[0001] The present invention belongs to the field of coastal zone environmental monitoring, and particularly relates to a method for retrieving the water content of the beach surface layer based on point cloud intensity. Background Technique

[0002] The water content of the beach surface layer is considered a key factor in coastal aeolian sand movement and is crucial for studying coastal aeolian sand movement problems. However, due to the combined effects of factors such as beach topography, tides, groundwater, precipitation, and evaporation, the water content of the beach surface layer shows highly dynamic characteristics in space and time. Existing technologies are insufficient to monitor the surface water dynamics of a large area of the beach, which hinders the development of more practical aeolian sand transport models on larger beach sections.

[0003] Currently, the measurement methods for the water content of the beach surface are mainly divided into two categories:

[0004] One is measurement based on on-site sampling, including traditional drying and weighing methods, probe methods, etc. This method often requires a large amount of manpower and can only obtain data at some sparse discrete points, and cannot well reflect the water distribution of the entire area.

[0005] The other is the remote sensing image inversion method. This method has the advantages of a wide measurement range and non-contact, but its ground resolution can often only reach the meter level and is easily affected by factors such as weather, clouds, and light.

[0006] In summary, existing technical means cannot achieve high-efficiency and high-precision monitoring of the water content of a large area of the beach. To solve the existing problems, the present invention provides a method for retrieving the water content of the beach surface layer based on point cloud intensity. Summary of the Invention

[0007] The purpose of the present invention is to provide a method for retrieving the water content of the beach surface layer based on point cloud intensity to solve the problems raised in the background technique.

[0008] To achieve the above purpose, the technical solution of the present invention is: A method for retrieving the water content of the beach surface layer based on point cloud intensity, including the following steps:

[0009] Step 1: Select a beach sample plot and use a three-dimensional laser scanner to obtain the point cloud data of the beach;

[0010] Step 2: Preprocess the obtained point cloud data and construct a correction model for the incident angle and distance effect of the point cloud intensity;

[0011] Step 3: Conduct an indoor scanning experiment, calibrate the point cloud intensity of sand samples with different water contents, fit the point cloud intensity - water content function, construct a water content inversion model, and finally obtain the inversion result of the water content of the beach surface layer.

[0012] In an embodiment of the present invention, in step 1, the process of obtaining beach point cloud data using a three-dimensional laser scanner is that the investigator selects the center point of the sample plot and sets up and scans the three-dimensional laser scanner through a tripod to obtain beach point cloud data.

[0013] In an embodiment of the present invention, step 2 specifically includes the following process:

[0014] A01. Perform filtering and denoising processing on the point cloud data, and cut out a rectangular area starting from the position of the three-dimensional laser scanner.

[0015] A02. Ignoring secondary factors such as atmospheric attenuation and only considering the influence of the incident angle and distance factors on the point cloud intensity, the point cloud intensity can be expressed as:

[0016] I = f(ρ)·f(θ,d)

[0017] where I is the original point cloud intensity value, f(ρ) represents the target reflectivity function, and f(θ,d) represents the function of the incident angle θ and the distance d.

[0018] A03. Calculate the incident angle θ and the distance d from each point in the point cloud data of the rectangular area to the origin of the three-dimensional laser scanner. The calculation formulas for the incident angle θ and the distance d are as follows:

[0019]

[0020]

[0021] In the formula, S(x,y,z) is the three-dimensional coordinate of the point cloud space, O(x0,y0,z0) is the origin coordinate of the three-dimensional laser scanner, is the point cloud normal vector, is the laser incident angle vector.

[0022] A04. Use the Levenberg-Marquardt method to fit f(θ,d), establish a fitting function model, and correct the point cloud intensity. The correction formula is as follows:

[0023]

[0024] In the formula, I s is the corrected point cloud intensity value, θ s is the reference angle, d s is the reference distance.

[0025] In an embodiment of the present invention, step 3 specifically includes the following process:

[0026] B01. Prepare a sand sample with a water content of 23% in a plastic box without a seal in the laboratory, and scan the sand sample using a three-dimensional laser scanner.

[0027] B02. Place the sand sample in an oven at 80 °C for drying. During the drying process, take out the sand sample every 10 minutes for scanning and weighing until the mass of the sand sample no longer changes, and calculate the water content of the sand sample at each time. The water content calculation formula is as follows:

[0028]

[0029] In the formula, w is the water content of the sand sample, m1 is the weight of the box, m2 is the weight of the box and the wet sample, and m3 is the weight of the box and the dry sample.

[0030] B03. Correct the point cloud intensity of the sand sample obtained in each time period through step 2, and select the reference angle θ s to be 45°, and the reference distance d s to be 10 m.

[0031] B04. Calculate the average value of the corrected point cloud intensity as the point cloud intensity of the sand sample with this water content.

[0032] B05. Fit the function model of point cloud intensity - water content, and use the least squares method to calculate the fitting parameters. The fitting formula is as follows:

[0033]

[0034] In the formula, w max is the maximum water content of the sand sample, w min is the minimum water content of the sand sample, I s is the corrected point cloud intensity of the sand sample, and a and b are the undetermined fitting parameters.

[0035] B06. After filtering and denoising all the beach point cloud data obtained in step 1, perform point cloud intensity correction according to step 2, and substitute the corrected intensity data into the function model for calculation, then the inversion result of the water content of the beach surface layer can be obtained.

[0036] Compared with the prior art, the present invention has the following beneficial effects: The present invention obtains the point cloud data of the beach through a three-dimensional laser scanner to invert the surface moisture content. Compared with the traditional method, the present invention improves the acquisition efficiency and accuracy of the beach surface moisture content. Specifically, the traditional method mostly uses on-site sampling or remote sensing image inversion. The sampling points of the on-site sampling method are sparse and cannot reflect the overall situation of the beach. The three-dimensional laser scanner can obtain a large amount of point cloud data in a short time, with very rich information, and can quickly invert the surface moisture content of the beach. Remote sensing images are easily affected by weather, and the ground resolution is between dozens of meters and sub-meter levels, while the point cloud resolution obtained by the three-dimensional laser scanner can reach the millimeter level and is not affected by factors such as weather and light, so the inversion accuracy is higher. Description of the Drawings

[0037] Figure 1 It is a flowchart of the method for inverting the surface moisture content of the beach based on point cloud intensity according to an embodiment of the present invention.

[0038] Figure 2 It is a schematic diagram of the cropping area of the point cloud data according to an embodiment of the present invention.

[0039] Figure 3 It is a fitting result diagram of the function model of the point cloud intensity and moisture content of the sand sample in an example of the present invention.

[0040] Figure 4 It is a distribution diagram of the aerial image and the surface moisture content inversion result of the beach sample plot in an example of the present invention.

[0041] Figure 5 It is a precision comparison diagram of the moisture content inversion result in an example of the present invention. Detailed Embodiments

[0042] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art belong to the scope of protection of the present invention.

[0043] According to an embodiment of the present invention, a method for inverting the surface moisture content of the beach based on point cloud intensity is provided. Figure 1 It is a complete technical flowchart provided by an embodiment of the present invention, specifically including the following steps:

[0044] Step 1: Select a beach sample plot. The investigator selects the center point of the sample plot and uses a tripod to set up a three-dimensional laser scanner at the center point to scan and obtain the point cloud data of the beach.

[0045] Step 2: Preprocess the obtained point cloud data and construct a correction model for the incident angle and distance effect of the point cloud intensity.

[0046] Step 3: Conduct indoor scanning experiments, calibrate the point cloud intensity of sand samples with different water contents, fit the point cloud intensity - water content function, construct a water content inversion model, and finally obtain the inversion results of the water content on the beach surface.

[0047] In Step 2, the specific process is as follows:

[0048] A01: First, perform filtering and denoising on the point cloud data, remove the error points, and classify the point cloud data to ensure that the point cloud data only records the beach information. Secondly, refer to Figure 2 As shown, starting from the position of the 3D laser scanner, crop out the point cloud data of a rectangular area with a length of 50m and a width of 1m as the training set for the subsequent point cloud intensity correction model.

[0049] A02: The point cloud intensity records the reflected spectral information of the target on the laser, characterizing the physical properties of the target. At the same time, the point cloud intensity is affected by various factors such as the system characteristics of the 3D laser scanner, atmospheric attenuation, and the physical properties of the target surface, resulting in the phenomenon of the same object with different spectra or different objects with the same spectra. Among them, during the ground scanning process, due to the small scanning range, the atmospheric attenuation can be ignored, and only the influence of the incident angle and distance factors on the point cloud intensity is considered. The point cloud intensity can be expressed as:

[0050] I = f(ρ)·f(θ, d);

[0051] In the formula, I is the original point cloud intensity value, f(ρ) represents the target reflectivity function, and f(θ, d) represents the function of the incident angle θ and the distance d.

[0052] A03: Import the cropped rectangular area point cloud data into the open - source software Cloudcompare for calculation to determine the incident angle θ of each point and the distance d from the origin of the 3D laser scanner. The calculation formulas for the incident angle θ and the distance d are as follows:

[0053]

[0054]

[0055] In the formula, S(x, y, z) is the three - dimensional coordinate of the point cloud space, O(x0, y0, z0) is the origin coordinate of the 3D laser scanner, is the point cloud normal vector, is the laser incident angle vector.

[0056] A04. Using the neural network fitting toolbox in Matlab software and the Levenberg-Marquardt method, the incident angle θ and distance d of the point cloud obtained in A03 are used as independent variables, and the point cloud intensity is used as the dependent variable for input to obtain a fitting function model of f(θ, d), and the point cloud intensity is corrected. The correction formula is as follows:

[0057]

[0058] In the formula, Is is the corrected point cloud intensity value, θ s is the reference angle, d s is the reference distance.

[0059] In step 3, it specifically includes the following process:

[0060] B01. Under natural conditions, the saturated water content of the beach fluctuates around 20% - 22%. When the water content is greater than 22%, free water remains on the surface of the beach. Therefore, in the indoor experiment, a sand sample with a water content of 23% is prepared in an uncovered plastic box, and the sand sample is scanned using a three-dimensional laser scanner, weighed, and the start time of drying is recorded.

[0061] B02. Place the sand sample in an oven at 80°C for drying. During this period, take out the sand sample for scanning, weighing, and recording every 10 minutes until the mass of the sand sample no longer changes, and calculate the water content of the sand sample at each time.

[0062]

[0063] In the formula, w is the water content of the sand sample, m1 is the weight of the box, m2 is the weight of the box and the wet sample, and m3 is the weight of the box and the dry sample.

[0064] B03. Correct the point cloud intensity of the sand sample obtained in each time period through the point cloud intensity correction model established in step 2. The reference angle and distance can be selected arbitrarily. In this embodiment, the reference angle θ s is 45°, and the reference distance d s is 10m.

[0065] B04. Calculate the corrected average point cloud intensity. At this time, calibrate this average point cloud intensity value as the point cloud intensity of the sand sample corresponding to the water content.

[0066] B05. Fit the function model of the point cloud intensity and water content of the sand sample, and calculate the fitting parameters using the least squares method. The fitting formula is as follows:

[0067]

[0068] In the formula, w max is the maximum water content of the sand sample, w minis the minimum water content of the sand sample, I s is the corrected point cloud intensity of the sand sample, and a and b are undetermined fitting parameters.

[0069] Refer to Figure 3 As shown, a total of 31 groups of data were input in this embodiment for fitting calculation. The fitting parameters were calculated as a = -0.04213 and b = -142.2. In the fitting result, the RMSE was 1.1165, and R 2 was 0.9747. A good fitting result was obtained.

[0070] B06. After filtering and denoising all the beach point cloud data obtained in step 1, perform point cloud intensity correction according to step 2, and substitute the corrected intensity data into the function model for calculation to obtain the inversion result of the water content of the beach surface layer.

[0071] As Figure 4 shown, based on the water content inversion model of point cloud intensity, the water content distribution map of the beach surface layer was finally inverted. The left figure is the aerial image of the beach, and the right figure is the inverted water content distribution map, where the gray scale from light to dark represents that the water content of the beach surface layer is getting higher and higher. It can be clearly seen from the overall figure the overall distribution pattern of the water content of the beach surface layer.

[0072] As Figure 5 shown, to verify the accuracy of the inversion result, 20 samples were taken on-site in this example, weighed, dried, and the water content was calculated in the laboratory, and compared with the inversion result. The maximum inversion error was 5.03%, and the RMSE of all inversion result errors was 2.05%.

[0073] The present invention inverts the water content of the beach surface layer by obtaining the point cloud data of the beach through a three-dimensional laser scanner. Compared with the traditional method, the present invention improves the acquisition efficiency and accuracy of the water content of the beach surface layer. Specifically, the traditional method mostly uses on-site sampling or remote sensing image inversion. The sampling points of the on-site sampling method are sparse and cannot reflect the overall situation of the beach. The three-dimensional laser scanner can obtain a large amount of point cloud data in a short time, with very rich information, and can quickly invert the water content of the beach surface layer. Remote sensing images are easily affected by the weather, and the ground resolution is between dozens of meters and sub-meter levels, while the point cloud resolution obtained by the three-dimensional laser scanner can reach the millimeter level and is not affected by factors such as weather and light, and the inversion accuracy is higher. It will surely play a greater value in future work and production.

[0074] The preferred embodiments of the present invention disclosed above are only used to help illustrate the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to the specific embodiments described. Obviously, many modifications and variations can be made according to the content of this specification. This specification selects and specifically describes these embodiments in order to better explain the principle and practical application of the present invention, so that those skilled in the art can well understand and utilize the present invention. Any changes or substitutions that can be thought of without creative work should be covered within the protection scope of the present invention.

Claims

1. A method for retrieving the water content of the beach surface layer based on point cloud intensity, characterized in that It includes the following steps: Step 1: Select a beach plot and use a three-dimensional laser scanner to obtain beach point cloud data at the center of the plot; Step 2: Preprocess the obtained beach point cloud data and construct a correction model for the incident angle of point cloud intensity and distance effect; Step 3: Conduct an indoor scanning experiment, calibrate the point cloud intensity of sand samples with different water contents, fit the point cloud intensity - water content function, construct a water content inversion model, and finally obtain the inversion result of the beach surface water content; Step 2 specifically includes the following process: A01: Filter and denoise the beach point cloud data, and cut out a rectangular area starting from the position of the three-dimensional laser scanner; A02: Ignore the secondary factors including atmospheric attenuation, and only consider the influence of the incident angle and distance factors on the point cloud intensity. Express the point cloud intensity as: I = f(ρ)·f(θ,d) where I is the original point cloud intensity value, f(ρ) represents the target reflectivity function, and f(θ,d) represents the function of the incident angle θ and distance d; A03: Calculate the incident angle θ of each point and the distance d to the origin of the three-dimensional laser scanner in the point cloud data of the rectangular area; A04: Use the Levenberg - Marquardt method to fit f(θ,d), establish a fitting function model, and correct the point cloud intensity; In step A03, the calculation formulas for the incident angle θ of each point and the distance d to the origin of the three-dimensional laser scanner are as follows: Wherein, S(x, y, z) is the three-dimensional coordinate of the point cloud space, and O(x0, y0, z0) is the origin coordinate of the three-dimensional laser scanner. is the normal vector of the point cloud. is the laser incident angle vector.

2. The method for inverting the moisture content of the beach surface layer based on point cloud intensity according to claim 1, wherein In step A04, the formula for correcting the point cloud intensity is as follows: Where, I s is the corrected point cloud intensity value, θ s is the reference angle, and d s is the reference distance.

3. The method for inverting the moisture content of the beach surface layer based on point cloud intensity according to claim 1, characterized in that Step 3 specifically includes the following process: B01: Prepare sand samples with saturated water content in a plastic box without a lid in the laboratory, and use a three-dimensional laser scanner to scan the sand samples; B02: Put the sand samples into an oven at 80°C for drying. During this period, take out the sand samples for scanning and weighing every 10 minutes until the mass of the sand samples no longer changes, and calculate the water content of the sand samples at each time; B03. Correct the point cloud intensity of the sand samples obtained in each time period through Step 2, and select the reference angle θ s to be 45°, and the reference distance d s to be 10 m; B04: Calculate the average value of the corrected point cloud intensity as the point cloud intensity of the water content sand sample; B05: Fit the function model of point cloud intensity - water content, and calculate the fitting parameters using the least squares method; B06: After filtering and denoising all the beach point cloud data obtained in step 1, correct the point cloud intensity according to step 2, substitute the corrected intensity data into the function model for calculation, and obtain the inversion result of the beach surface water content.

4. The method for inverting the water content of the beach surface layer based on point cloud intensity according to claim 3, characterized in that, In step B02, the water content calculation formula is as follows: In the formula, w is the water content of the sand sample, m1 is the weight of the box, m2 is the weight of the box and the wet sample, and m3 is the weight of the box and the dry sample.

5. The method for inverting the water content of the beach surface layer based on point cloud intensity according to claim 3, wherein, In step B05, the fitting formula is as follows: where, w max is the maximum water content of the sand sample, w min is the minimum water content of the sand sample, I s is the corrected point cloud intensity of the sand sample, and a and b are undetermined fitting parameters.

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