A method, device and medium for estimating the amount of river bank collapse in river artificial afforestation

Abstract

The application discloses a riverway artificial afforestation bank collapse square amount estimation method, equipment and medium, and the riverway artificial afforestation bank collapse square amount estimation method comprises the following steps: vertical aerial photography is formed by aerial photography on the bank collapse area; fallen trees are selected in the vertical aerial photography image range, the inclination angle θ of the fallen trees is measured i , the real tree height H real,i is measured, and the projection pixel length L of the trees on the vertical aerial photography image is measured px,i ; the pixel-metre proportion coefficient α is calculated i ; the original bank line and the present bank line are respectively sketched on the vertical aerial photography image and closed to form a bank collapse recession area polygon, and the pixel area A is obtained px ; the pixel area is converted into the real area A z ; the average bank collapse bank height H is measured b , the bank collapse volume V is calculated, the error between the aerial photography image and the real area in the traditional remote sensing method is solved, and the area calculation error is reduced.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of river artificial forest beach bank collapse volume estimation, and particularly relates to a river artificial forest bank collapse volume estimation method, device and medium. BACKGROUND

[0002] River beach bank collapse is a phenomenon of bank slope instability caused by river erosion, and although the tree roots of river artificial forest can reinforce the soil, factors such as flood scouring, sudden water level drop or soil saturation can still cause bank collapse.

[0003] The existing bank collapse volume estimation generally uses remote sensing images to estimate the bank collapse volume, and the remote sensing image estimation method is as follows: collecting remote sensing images before and after bank collapse; extracting the change area: identifying the bank line change area, generating the bank collapse range, and obtaining the bank collapse volume by multiplying the area of the bank collapse range by the fixed bank height.

[0004] However, the aerial image is projected and deformed due to the inclination of the trees, the traditional method ignores the geometric characteristics of the fallen trees, resulting in two-dimensional area conversion error, and the bank collapse volume cannot be accurately estimated. SUMMARY

[0005] The present application aims to overcome the above technical deficiencies and provide a river artificial forest bank collapse volume estimation method, device and medium, which solves the technical problem that the traditional method ignores the geometric characteristics of the fallen trees, resulting in two-dimensional area conversion error and inaccurate bank collapse volume estimation.

[0006] To achieve the above technical purpose, the present application adopts the following technical scheme:

[0007] In a first aspect, the present application provides a river artificial forest bank collapse volume estimation method, comprising the following steps:

[0008] Aerial photography is performed on the bank collapse area to form a vertical aerial image;

[0009] In the range of the vertical aerial image, fallen trees are selected, the inclination angle θ of the fallen trees is measured i , the true tree height H real,i is measured, and the projection pixel length L of the trees on the vertical aerial image is measured px,i ;

[0010] According to the formula:

[0011] ,

[0012] The pixel-meter proportion coefficient a is calculated i ;

[0013] The original bank line and the present bank line are respectively outlined on the vertical aerial image and closed to form a bank collapse recession area polygon, and the pixel area A is obtained px ;

[0014] According to the formula:

[0015] ,

[0016] Convert the pixel area to the real area A z ;

[0017] Measure the average bank height H b , and calculate the bank volume V, V = 1 / 2A z ×H b .

[0018] In one of the embodiments, in the step of calculating the pixel-meter ratio coefficient α i :

[0019] Select n fallen trees in the vertical aerial image range, and measure the inclination angle θ i , the real tree height H real,i , and the projected pixel length L px,i on the vertical aerial image of the n fallen trees;

[0020] According to the formula:

[0021] ,

[0022] Calculate the pixel-meter ratio coefficient α i , and average all α i to obtain ;

[0023] In the step of calculating the real area A z , according to the formula:

[0024] ,

[0025] Calculate the real area A z ;

[0026] Wherein, n is an integer greater than 1.

[0027] In one of the embodiments, based on error propagation analysis, the uncertainty of the bank volume V is quantified, and it is judged whether the variance of the bank volume V is within the preset accuracy range X.

[0028] In one of the embodiments, based on error propagation analysis, the uncertainty of the bank volume V is quantified, and it is judged whether the variance of the bank volume V is within the preset accuracy range X. The specific steps are as follows:

[0029] Calculate the variance of the pixel-meter ratio coefficient α i of a single tree:

[0030] ,

[0031] Calculate the pixel-meter ratio coefficient α of the multi-tree i The variance of the volume V is calculated as follows:

[0032] ,

[0033] The variance of the volume V is calculated as follows:

[0034] ,

[0035] And determine whether the variance of the bank collapse volume V is within the preset accuracy range X;

[0036] Wherein, , , The measurement uncertainty of the true tree height H real,i , the projected pixel length L px,i , and the inclination angle θ i , , , , The uncertainty of the bank collapse volume, the pixel area, the pixel-meter ratio coefficient, and the average bank collapse height, respectively.

[0037] In one of the embodiments, after calculating the variance of the volume V, the confidence interval of the bank collapse volume V is given.

[0038] In one of the embodiments, the confidence interval of the bank collapse volume V is calculated as follows:

[0039] ,

[0040] Wherein, t α / 2,df is the critical value of t-distribution, the confidence level is 85%, α=0.15, the degree of freedom df is the minimum sample size in all independent measurements, and t α / 2,df is obtained by querying the t-distribution critical value table according to α and df.

[0041] In one of the embodiments, in the step of selecting the fallen tree, the spectral characteristics of the soil attached by the fallen tree are identified, the spectral characteristics of the soil on the bank collapse area are matched, and if the spectral characteristics do not match, the fallen tree is abandoned.

[0042] In one of the embodiments, the bank collapse area is photographed to form a vertical aerial image;

[0043] The fallen tree is selected within the range of the vertical aerial image, the inclination angle θ i of the fallen tree is measured, and the true tree height H real,iand the projected pixel length L of the tree on the vertical aerial image is measured px,i The steps are as follows:

[0044] The real tree height H of the selected collapsed tree is measured real,i The starting point and the ending point of the tree height H are marked, and the tree height H between the starting point and the ending point is measured real,i The projected pixel length L of the starting point and the ending point on the vertical aerial image is measured px,i .

[0045] The present application also relates to a computer device, comprising:

[0046] The memory stores a computer program, and the computer program is executed by the processor to make the processor execute the steps of the river artificial afforestation bank collapse volume estimation method.

[0047] The present application also relates to a computer readable storage medium,

[0048] The computer readable storage medium stores a computer program, and the computer program is suitable for being loaded and executed by the processor to execute the river artificial afforestation bank collapse volume estimation method.

[0049] Compared with the prior art, the river artificial afforestation bank collapse volume estimation method, device and medium provided by the present application are compared with the prior art, the projected length L of the collapsed tree on the vertical aerial image px,i , the inclination angle θ i is compressed, and the formula is introduced to dynamically correct the proportion coefficient and eliminate the image distortion caused by the inclination angle; based on the corrected proportion coefficient α i , the bank collapse area pixel area A px drawn is converted into a real area; the collapsed tree is taken as a natural reference object to realize the mapping of the image coordinates to the geographic coordinates; in order to calculate the bank collapse volume, the bank collapse volume V is calculated, V=1 / 2A z ×H b ; through the above estimation method, the error problem between the aerial image and the real area in the traditional remote sensing method is solved, and the area calculation error is reduced. BRIEF DESCRIPTION OF DRAWINGS

[0050] Figure 1 is a flowchart of the river artificial afforestation bank collapse volume estimation method provided by an embodiment of the present application;

[0051] Figure 2 is a vertical aerial image provided by an embodiment of the present application;

[0052] Figure 3 is a tree inclination angle measurement schematic diagram provided by an embodiment of the present application;

[0053] Figure 4 Figure 1 is a schematic view of the original shoreline and the present shoreline closing to form a landslide collapse area polygon according to an embodiment of the present application. DETAILED DESCRIPTION

[0054] In order to make the objects, technical solutions and advantages of the present application clearer, the present application will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and should not be used to limit the present application.

[0055] In order to solve the technical problem that the two-dimensional area conversion error cannot be accurately estimated for the landslide square due to the neglect of the geometric characteristics of the fallen trees by the traditional method, the present application provides a river artificial forest landslide square estimation method, device and medium, which can solve the technical problem that the two-dimensional area conversion error cannot be accurately estimated for the landslide square due to the neglect of the geometric characteristics of the fallen trees by the traditional method in the prior art.

[0056] Please refer to Figure 1 , Figure 1 Figure 1 is a flowchart of the river artificial forest landslide square estimation method according to an embodiment of the present application. The river artificial forest landslide square estimation method comprises the following steps:

[0057] Taking a vertical aerial image of the landslide area by aerial photography;

[0058] Selecting fallen trees in the range of the vertical aerial image, measuring the inclination angle θ of the fallen trees i , measuring the real tree height H real,i , and measuring the projected pixel length L of the trees on the vertical aerial image px,i ;

[0059] According to the formula , the pixel-meter proportion coefficient a is calculated i ;

[0060] On the vertical aerial image, the original shoreline and the present shoreline are respectively outlined and closed to form a landslide collapse area polygon, and the pixel area A is obtained px ;

[0061] According to the formula , the pixel area is converted into the real area A z ;

[0062] Measuring the average landslide bank height H b , calculating the landslide volume V, V=1 / 2A z ×H b .

[0063] Specifically, in the present embodiment, the projected length L of the fallen trees on the vertical aerial image px,i , due to the inclination angle θ iCompressed, formula introduced Dynamically correct the scaling factor to eliminate image distortion caused by tilt angle; based on the corrected scaling factor α i The pixel area A of the delineated bank collapse area px Convert to actual area; use fallen trees as natural reference points to map image coordinates to geographic coordinates; calculate the volume of the collapsed bank, V, where V = 1 / 2A. z ×H b The above estimation method solves the error between aerial images and the actual area in traditional remote sensing methods, and reduces the area calculation error.

[0064] It should be understood that the angle of inclination θ of the fallen trees is... i The measuring tools can be mobile phone angle measuring apps or portable inclinometers, etc.; actual tree height H real,i The measuring tools can be tape measures, total stations, and laser rangefinders, etc.; aerial images can be taken using drones, helicopters, and other equipment.

[0065] It should be understood that the pixel area A of the bank collapse and erosion zone px The pixel area A of the bank collapse and landslide retreat area can be automatically calculated by GIS software or image processing software, or it can be determined manually or by other methods. px Perform the calculation.

[0066] It should be understood that if the bank collapses to a height of H... b If the bank is stepped, the volume of the collapsed bank can be obtained by multiplying the height of each step by the sum of their areas.

[0067] When a riverbank collapses, the angle at which different trees on the riverbank fall may vary. If only one type of tree is used to calculate the pixel-to-meter ratio α... i This can lead to significant errors. Measurement errors may also occur when measuring a single tree. Therefore, in one embodiment, the pixel-to-meter ratio coefficient α is calculated... i In this step, n fallen trees are selected within the vertical aerial image range, and the tilt angle θ of the n fallen trees is measured. i Real tree height H real,i and the length of the projected pixels L on the vertical aerial image. px,i ;

[0068] According to the formula Calculate the pixel-to-meter ratio factor α i and all α i Calculate the average to get ;

[0069] In calculating the actual area A z In the steps, according to the formula The real area A is calculated z ;

[0070] Wherein, n is an integer greater than 1.

[0071] Through the above steps, on the basis of the single tree ratio coefficient α i , the mean value processing of multi-tree is introduced, which can suppress random error.

[0072] It should be understood that n can be 2, 3, 4, 5, 6, 7, 8, 9, 10, etc.

[0073] In the existing remote sensing estimation method, only a single square estimation value can be output, and the reliability of the square estimation value cannot be answered. Therefore, in one embodiment, based on error propagation analysis, the uncertainty of the bank collapse volume V is quantified, and it is judged whether the variance of the bank collapse volume V is within the preset accuracy range X.

[0074] By introducing error propagation analysis into bank collapse square estimation, by quantifying the variance of the bank collapse volume, it can be judged whether the accuracy of the measured bank collapse volume V meets the requirements.

[0075] It should be understood that the accuracy range X can be 10%, 15%, and 20%, etc.

[0076] It should be understood that bank collapse volume estimation involves multiple links, such as tree measurement, area delineation, and bank height measurement, and the error of each link will be transmitted to the final result step by step, but the traditional method cannot quantify the cumulative effect of these errors. In order to evaluate the reliability of the bank collapse volume V through error propagation analysis, in one embodiment, based on error propagation analysis, the uncertainty of the bank collapse volume V is quantified, and it is judged whether the variance of the bank collapse volume V is within the preset accuracy range X. The specific steps are as follows:

[0077] Calculate the variance of the pixel-meter ratio coefficient α i of a single tree:

[0078] , calculate the variance of the pixel-meter ratio coefficient α i of multiple trees: , calculate the variance of the volume V: , and judge whether the variance of the bank collapse volume V is within the preset accuracy range X.

[0079] Wherein, , , are the measurement uncertainties of the real tree height H real,i , the projected pixel length L px,i , and the inclination angle θ i , respectively, , , , are the uncertainties of the bank collapse volume, pixel area, pixel-meter proportion coefficient, and average bank collapse height, respectively.

[0080] In this embodiment, the specific formula for variance calculation is given, and the above problems are converted into quantifiable and operable solutions through a three-layer progressive error transmission model.

[0081] It should be understood that the requirement of the precision range X is that the error is not more than 15%, and it can also be 12%, 10%, etc.

[0082] Output variance after is an abstract statistical quantity, and the decision maker cannot intuitively understand the actual significance of the bank collapse volume V and the variance of the volume V, and it is unclear how much safety margin should be reserved. In one embodiment, after calculating the variance of the volume V, the confidence interval of the bank collapse volume V is given.

[0083] By calculating the variance of the volume V, the confidence interval of the bank collapse volume V is quantified, and the abstract variance is converted into upper and lower limit values familiar to engineers.

[0084] In order to calculate the confidence interval of the bank collapse volume V in detail, in one embodiment, the confidence interval calculation formula of the bank collapse volume V is .

[0085] where t α / 2,df is the critical value of t-distribution, the confidence level is 85%, α=0.15, the degree of freedom df is the minimum sample size in all independent measurements, and the t α / 2,df value is obtained by querying the t-distribution critical value table according to α and df.

[0086] In this embodiment, the volume variance is calculated, the minimum sample size is determined, and then the critical value t is obtained by querying the t-distribution table; the confidence interval is output, which can quantify the confidence interval of the bank collapse volume V. Through the standardized t-distribution parameters and the operable calculation process, the confidence interval is converted into an engineering decision tool, realizing the risk-controllable and cost-optimized bank collapse volume estimation.

[0087] Since trees do not necessarily fall due to bank collapse, the angle of fall when trees fall for reasons other than bank collapse will differ from that caused by bank collapse, which will affect the accuracy of the estimated data. Therefore, in order to exclude trees that fall for reasons other than bank collapse, in one embodiment, during the step of selecting fallen trees, the spectral characteristics of the soil attached to the roots of the fallen trees are identified and matched with the surface soil spectrum of the bank collapse area. If the spectral characteristics do not match, the fallen tree is not selected.

[0088] In this embodiment, fallen trees are identified by spectral analysis. The spectral characteristics of the soil at the site of the fallen tree are compared with those of the collapsed bank surface. If the spectral characteristics of the two do not match, the tree fall is not caused by the bank collapse, and the tree fall samples that are not caused by the bank collapse are eliminated.

[0089] Specifically, UAV multispectral imaging can be used to identify the type of soil to which the roots of fallen trees are attached. If the spectral characteristics of the soil to which the roots are attached match those of the surface soil in the landslide area by less than 90%, the tree is determined to be not caused by the landslide and the fallen tree is not selected.

[0090] It should be understood that the color of the root soil can also be observed artificially to differentiate it from the color of the collapsed bank area, such as humidity and particle size, to determine whether the trees were caused by the collapse of the bank.

[0091] Measuring the true tree height H of the fallen tree real,i In such cases, the actual tree height H of a fallen tree is usually measured manually using equipment such as a total station and a measuring tape. real,i， However, since the starting position of the above-mentioned equipment is different from that of the vertical aerial image measurement, there will be measurement errors. Therefore, in one embodiment, aerial photography is carried out on the collapsed bank area to form a vertical aerial image.

[0092] Select fallen trees within the vertical aerial imagery area and measure the tilt angle θ of the fallen trees. i Measure the actual tree height H real,i The length L of the projected pixels of the trees on the vertical aerial image was measured. px,i In the steps;

[0093] The actual tree height H of the selected fallen trees real,i Mark the start and end points, and measure the tree height H between the start and end points. real,i And measure the length L of the projected pixels on the vertical aerial images at the starting and ending points. px,i ;

[0094] By marking the fallen trees, the actual tree height H can be measured. real,i With the projected pixel length L px,i The measurement is performed on the same section of the fallen tree to avoid affecting the accuracy of the measurement due to different measurement locations.

[0095] It should be understood that the mark can be the trace of the fallen tree itself, such as bifurcation / scars, etc., or can be a mark made artificially, such as colored paint, sprayed color marks, etc.

[0096] Specifically, as shown in Figures 1 to 4 The working principle of the riverway afforestation bank collapse volume estimation method of the present application is:

[0097] An unmanned aerial vehicle is used to take aerial photographs 50 meters above the bank collapse area, with a heading overlap degree ≥80% and a lateral overlap degree ≥60%, to generate a resolution of 2cm / pixel aerial orthophoto;

[0098] In the image, the fallen trees with exposed root systems are identified, the spectral curve of the soil attached to the root system is collected by the multispectral camera of the unmanned aerial vehicle, and the spectral curve is matched with the spectral curve of the surface soil in the bank collapse area. 7 fallen trees with matched spectra are selected;

[0099] The base and the tip of the trunk of the selected fallen trees are marked with colored paint as the starting point and the ending point, and a laser range finder is used to measure the real tree height H real,i between the starting point and the ending point; a portable inclinometer is used to measure the inclination angle θ i of the fallen trees; the inclination angle θ i of the 7 fallen trees ranges from 5-15°, and the tree height H real,i ranges from 9.8-10.2m.

[0100] The projected pixel length Lpx,i corresponding to the tree height of the 7 fallen trees is measured one by one using the line segment tool in ImageJ, and the average value is 200px;

[0101] The α i of the 7 fallen trees is calculated according to the formula, and all α i are averaged to obtain =0.0493m / px ;

[0102] After forming a polygon of the bank collapse area using QGIS software, the pixel area A px =1.12×10 5 px 2 is automatically calculated;

[0103] The pixel area is converted into the real area A z , =1.12×10 5 ×(0.0493) 2 =272m 2 ;

[0104] The bank collapse volume can be regarded as a triangular wedge, and the average bank collapse height H b is about 4m; V=1 / 2A z ×H b =0.5×272m 2 ×4.0m=544m 3 ;

[0105] The pixel-meter ratio coefficient a of a single tree is calculated i The variance of a is calculated as follows: ;

[0106] The pixel-meter ratio coefficient a of multiple trees is calculated i The variance of a is calculated as follows: ;

[0107] The variance of the volume V is calculated as follows: ;

[0108] Wherein, Taking the pixel area circle error of 2%, which is px2;

[0109] Taking the standard deviation of 7 fallen trees when is calculated, which is 0.0018m / px;

[0110] Taking the average bank collapse height sampling error of 0.3m;

[0111] The calculation result is 58m 3 , and the relative error is / V=58 / 544≈±10.7%, which is within the preset accuracy range X (less than 15%);

[0112] The confidence level is 85%, the significance level a=0.15, the two-tailed probability a / 2=0.075, and the degree of freedom df=min(n trees, n bank height, n area);

[0113] Wherein: n trees: the sample size of fallen trees (≥5 trees);

[0114] n bank height: the number of bank height measurement points (≥1 measurement point per 20m of bank line);

[0115] n area: the number of polygon vertices in the bank collapse area (≥10 vertices);

[0116] df=min(7,5,12)=5;

[0117] The critical value table is consulted to obtain t 0.075,5 =1.895;

[0118] Confidence interval .

[0119] The present application also relates to a computer device comprising a memory (not shown in the figure) and a processor (not shown in the figure), the memory storing a computer program, the computer program being executed by the processor to make the processor execute the steps of the river artificial afforestation bank collapse volume estimation method. The computer device can be a database, specifically, in one embodiment thereof, the computer device comprises a processor (not shown in the figure), a memory (not shown in the figure), an input / output interface (I / O) and a communication interface (not shown in the figure). Among them, 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. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device comprises 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 transactions to be processed. The input / output interface of the computer device is used to exchange information between the processor and external devices. The communication interface of the computer device is used to communicate with external terminals through network connection. The computer program is executed by the processor to implement the river artificial afforestation bank collapse volume estimation method described above.

[0120] The present application also relates to a computer readable storage medium, the computer readable storage medium storing a computer program, the computer program being adapted to be loaded and executed by a processor to implement the river artificial afforestation bank collapse volume estimation method described above.

[0121] The computer readable storage medium described above can be an internal storage unit of the computer device, such as a hard disk or an internal memory of the computer device. The computer readable storage medium can also be an external storage device of the computer device, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. equipped on the computer device. Further, the computer readable storage medium can include both the internal storage unit and the external storage device of the computer device. The computer readable storage medium is used to store the computer program and other programs and data required by the computer device. The computer readable storage medium can also be used to temporarily store data that has been output or will be output.

[0122] The various embodiments described in this specification are presented for the purpose of illustration and description. Each of the embodiments highlights a different aspect of the application, and the embodiments are presented separately for ease of understanding. However, the same or similar features can be combined in any suitable manner in one or more embodiments.

[0123] The order of the steps of the estimation method described in this specification can be adjusted as needed.

[0124] The specific embodiments of the application described above are not intended to limit the scope of the application. Any other corresponding changes and modifications made according to the technical concept of the application should be included in the scope of protection of the claims of the application.

Claims

1. A method for estimating the volume of a riverbank collapse in a river channel afforestation, characterized by, The method comprises the following steps: taking aerial photography of the bank collapse area to form a vertical aerial image; Select the fallen trees in the vertical aerial image range, measure the inclination angle θ of the fallen trees i , measure the real tree height H real,i , and measure the projection pixel length L of the tree in the vertical aerial image px,i ; According to the formula: ， Computing the pixel-meters scale factor a i ; The original bank line and the present bank line are respectively outlined on the vertical aerial image to form a polygon of the bank collapse recession area, and a pixel area A is obtained px ; According to the formula: ， Converting pixel area to real area A z ; measuring the average eroded bank height H b , calculating the volume of the erosion V, V = 1 / 2 A z x H b ; In the step of calculating the pixel-meter scale factor a i : In the vertical aerial image range, select n collapsed trees, measure the n collapsed trees angle θ i , the true height H real,i and the projection pixel length L px,i in the vertical aerial image; According to the formula: ， The pixel-metre scale factor a is calculated i and all a i are averaged to obtain ; In the step of calculating the real area A z According to the formula: ， The true area A is calculated z ; wherein n is an integer greater than 1; Based on error propagation analysis, the uncertainty of the bank collapse volume V is quantified, and it is judged whether the variance of the bank collapse volume V is within the preset accuracy range X; In the step of quantifying the uncertainty of the bank collapse volume V based on error propagation analysis and judging whether the variance of the bank collapse volume V is within the preset accuracy range X, the specific steps are: Calculating the pixel-meters scaling factor a for individual trees i of the variance: ， Calculating a pixel-meters scaling factor a for multiple trees i of the variance: ， Calculate the variance of the volume V: ， and judge whether the variance of the bank collapse volume V is within the preset accuracy range X. wherein, , , are the measurement uncertainties of the real tree height H real,i , the projected pixel length L px,i , the inclination angle θ i , , , , are the uncertainties of the bank collapse volume, the pixel area, the pixel-meter proportionality factor, the average bank collapse bank height, respectively.

2. The bank collapse volume estimation method according to claim 1, wherein After calculating the variance of the volume V, the confidence interval of the bank collapse volume V is given.

3. The bank collapse volume estimation method according to claim 2, wherein The confidence interval of the bank collapse volume V is calculated according to the formula: ， Wherein, t α / 2,df is the critical value of t distribution, the confidence level is 85%, α = 0.15, the degree of freedom df is the minimum sample size in all independent measurements, and t α / 2,df is obtained by querying the t distribution critical value table according to α and df.

4. The bank collapse volume estimation method according to claim 1, wherein In the step of selecting the fallen trees, the spectral characteristics of the soil attached by the fallen trees are identified, and the spectral characteristics of the soil on the surface of the bank collapse area are matched. If the spectral characteristics do not match, the fallen tree is discarded.

5. The bank collapse volume estimation method according to claim 1, wherein taking aerial photography of the bank collapse area to form a vertical aerial image; In the step of selecting the fallen trees in the vertical aerial image range, the inclination angle θ of the fallen trees is measured i , the real tree height H is measured real,i , and the projected pixel length L of the tree in the vertical aerial image is measured px,i . The true height H of the selected fallen tree is measured real,i The starting point and the ending point are marked, the height H between the starting point and the ending point is measured real,i , and the projected pixel length L on the vertical aerial image of the starting point and the ending point is measured px,i .

6. A computer device, comprising: comprising: a memory and a processor, the memory storing a computer program, the computer program being executed by the processor to make the processor execute the steps of the bank collapse volume estimation method according to any one of claims 1-5.

7. A computer readable storage medium, comprising: The computer readable storage medium stores a computer program, and the computer program is suitable for being loaded and executed by a processor to execute the bank collapse volume estimation method according to any one of claims 1-5.

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