A landslide volume estimation method, device and medium based on post-disaster remote sensing data

Abstract

The present application discloses a landslide volume estimation method, device and medium based on post-disaster remote sensing data, relating to the field of remote sensing technology. The method obtains post-disaster remote sensing data; identifies and demarcates the boundary ranges on the left and right sides of the landslide accumulation area, the boundary range of the landslide wall area, and the boundary range of the area required for toe reconstruction according to the UAV aerial image data; reconstructs the original toe terrain boundary before the landslide occurs based on the three-dimensional laser ground point cloud data within the area required for toe reconstruction; determines the elevation data of the original toe before the landslide occurs based on the reconstructed original toe terrain boundary before the landslide occurs; reconstructs the sliding interface based on the elevation data of the original toe before the landslide occurs, and the three-dimensional laser ground point cloud data within the boundary ranges on the left and right sides of the landslide accumulation area and within the boundary range of the landslide wall area; determines the landslide volume according to the elevation data of the sliding interface and the elevation data of the landslide accumulation area. The present application can improve the accuracy of landslide volume estimation.

Description

Technical Field

[0001] The present application relates to the field of remote sensing technology, and in particular to a landslide volume estimation method, device and medium based on post-disaster remote sensing data. Background Art

[0002] Landslide disasters are one of the most frequent types of geological disasters globally, causing huge impacts on human society and the natural environment. Especially in mountainous areas, due to unique topographical and geomorphological features and increasingly severe extreme weather, the frequency and damage caused by landslide disasters are particularly serious.

[0003] The landslide volume is a key parameter for evaluating the scale of a landslide, assessing the scope and degree of the disaster impact. In the emergency rescue after a landslide disaster and the engineering construction in the landslide accumulation area, landslide volume estimation is an extremely important task. Currently, landslide volume estimation mainly adopts methods such as geophysical exploration and geological drilling to generate a three-dimensional model of the landslide accumulation body through engineering fitting and calculate the volume of the fitted landslide accumulation body model. However, such methods require personnel to reach the landslide site, consuming a large amount of manpower, material resources and time; the landslide volume can also be estimated by comparing the changes in elevation data before and after the landslide. However, if the landslide body has not been continuously monitored before the disaster, it will be difficult to obtain high-precision elevation data before the landslide; in addition, related technologies have proposed a method for estimating the fitted landslide volume by interpolating and fitting the sliding interface based on high-precision elevation data after the landslide. However, this method ignores the importance of the original foot-of-slope topography in the fitting of the sliding interface, resulting in a large error in the landslide volume estimation. Summary of the Invention

[0004] The purpose of the present application is to provide a landslide volume estimation method, device and medium based on post-disaster remote sensing data, which can solve the problem of inaccurate landslide volume estimation in related technologies.

[0005] To achieve the above purpose, the present application provides the following solutions.

[0006] In a first aspect, the present application provides a landslide volume estimation method based on post-disaster remote sensing data, including: obtaining post-disaster remote sensing data, where the post-disaster remote sensing data includes three-dimensional laser ground point cloud data and unmanned aerial vehicle (UAV) aerial image data of the landslide disaster area; the landslide disaster area includes a landslide accumulation area, a landslide wall area, and an area required for slope foot reconstruction; identifying and delineating the boundary ranges on the left and right sides of the landslide accumulation area, the boundary range of the landslide wall area, and the boundary range of the area required for slope foot reconstruction according to the UAV aerial image data; reconstructing the original slope foot topographic boundary before the landslide occurred based on the three-dimensional laser ground point cloud data within the area required for slope foot reconstruction; determining the elevation data of the original slope foot before the landslide occurred based on the reconstructed original slope foot topographic boundary before the landslide occurred; the elevation data is determined based on the values on the Z-axis of the three-dimensional laser ground point cloud data in a spatial rectangular coordinate system; the spatial rectangular coordinate system is established with the central meridian and the equator as the center, the projection of the equator as the X-axis, and the projection of the central meridian as the Y-axis; reconstructing the sliding interface based on the elevation data of the original slope foot before the landslide occurred and the three-dimensional laser ground point cloud data within the boundary ranges on the left and right sides of the landslide accumulation area and within the boundary range of the landslide wall area; determining the landslide volume based on the elevation data of the sliding interface and the elevation data of the landslide accumulation area.

[0007] In a second aspect, the present application provides a computer device, including: a memory, a processor, and a computer program stored on the memory and executable on the processor, where the processor executes the computer program to implement the landslide volume estimation method based on post-disaster remote sensing data described above.

[0008] In a third aspect, the present application provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, it implements the landslide volume estimation method based on post-disaster remote sensing data described above.

[0009] According to the specific embodiments provided by the present application, the following technical effects are disclosed in the present application.

[0010] The present application reconstructs the original toe of the slope terrain boundary before the landslide occurs by using the three-dimensional laser ground point cloud data within the area required for reconstruction of the toe of the landslide disaster area; based on the drone aerial image data, the boundary ranges on the left and right sides of the landslide accumulation area, the boundary range of the landslide wall area, and the boundary range of the area required for reconstruction of the toe of the slope are identified and delineated, thereby ensuring the accuracy of the terrain boundary of the landslide disaster area and the accuracy and reliability of the subsequent landslide volume estimation results. Based on the reconstructed original toe of the slope terrain boundary before the landslide occurs, the elevation data of the original toe of the slope before the landslide occurs is determined, thereby avoiding the problem in the prior art of inaccurate elevation data of the original toe of the slope before the landslide occurs, which leads to inaccurate subsequent landslide volume estimation. Furthermore, based on the elevation data of the original toe of the slope before the landslide occurs, as well as the three-dimensional laser ground point cloud data within the boundary ranges on the left and right sides of the landslide accumulation area and the boundary range of the landslide wall area, the sliding interface is reconstructed. And based on the elevation data of the reconstructed sliding interface and the elevation data of the landslide accumulation area, a high-precision estimation of the landslide volume is achieved. This application considers the importance of the original toe topography in fitting the sliding interface. Therefore, the original toe topography boundary before the landslide occurred was reconstructed. The sliding interface was reconstructed based on the reconstructed toe topography boundary, as well as the 3D laser ground point cloud data within the boundaries of the landslide accumulation area and the landslide wall area. This significantly improves the accuracy of landslide volume estimation and provides important data support for emergency rescue and engineering construction. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0012] Figure 1 This is a flow chart of a landslide volume estimation method based on post-disaster remote sensing data provided in an embodiment of the present application.

[0013] Figure 2 (a) is a schematic diagram of UAV aerial image data of the landslide disaster area.

[0014] Figure 2 (b) is a schematic diagram of the three-dimensional laser ground point cloud data of the landslide disaster area.

[0015] Figure 3 (a) is a schematic diagram of UAV aerial image data of various parts of the landslide disaster area.

[0016] Figure 3(b) is a three-dimensional shadow diagram of the elevation data of various parts of the landslide hazard area. DETAILED DESCRIPTION

[0017] The following will clearly and completely describe the technical solutions in the embodiments of the present application with reference to the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present application.

[0018] To make the above objects, features, and advantages of the present application more obvious and understandable, the present application will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0019] Embodiment 1: As Figure 1 shown, the present application provides a landslide volume estimation method based on post-disaster remote sensing data, including Step 101 - Step 106.

[0020] Step 101: Obtain post-disaster remote sensing data, where the post-disaster remote sensing data includes three-dimensional laser ground point cloud data and unmanned aerial vehicle (UAV) aerial image data of the landslide disaster area; the landslide disaster area includes the landslide accumulation area, the landslide wall area, and the area required for rebuilding the slope foot.

[0021] Step 102: According to the UAV aerial image data, identify and demarcate the boundary ranges on the left and right sides of the landslide accumulation area, the boundary range of the landslide wall area, and the boundary range of the area required for rebuilding the slope foot.

[0022] Step 103: According to the three-dimensional laser ground point cloud data within the area required for rebuilding the slope foot, reconstruct the original slope foot topographic boundary before the landslide occurred.

[0023] Step 104: Based on the reconstructed original slope foot topographic boundary before the landslide occurred, determine the elevation data of the original slope foot before the landslide occurred; the elevation data is determined based on the values on the Z-axis of the three-dimensional laser ground point cloud data in the space rectangular coordinate system; the space rectangular coordinate system is established with the central meridian and the equator as the center, the projection of the equator as the X-axis, and the projection of the central meridian as the Y-axis.

[0024] Among them, the UTM (Universal Transverse Mercator) projection is a widely used map projection method. Each longitude zone of the Universal Transverse Mercator projection is defined by the following coordinate system: Center (origin): The intersection of the central meridian and the equator. X-axis: Based on the projection of the equator, representing the east-west direction (eastward is positive). Y-axis: Based on the projection of the central meridian, representing the north-south direction (northward is positive).

[0025] Step 105: Reconstruct the sliding interface based on the elevation data of the original slope foot before the landslide occurred, and the three-dimensional laser ground point cloud data within the boundary range of the left and right sides of the landslide accumulation area and the boundary range of the landslide wall area.

[0026] Step 106: Determine the landslide volume based on the elevation data of the sliding interface and the elevation data of the landslide accumulation area.

[0027] In some embodiments, step 103 specifically includes: reconstructing the original slope foot terrain boundary before the landslide occurred using a spatial sphere interpolation method based on the three-dimensional laser ground point cloud data in the area required for the slope foot reconstruction; the calculation formula of the spatial sphere interpolation method is as follows.

[0028] .

[0029] in,( , , ) is the first The values of the three-dimensional laser ground point cloud data on the X-axis, Y-axis, and Z-axis in the spatial rectangular coordinate system; =1,2,..., ; is the total number of 3D laser ground point cloud data; is the coordinate value of the center of the sphere in the spatial rectangular coordinate system used by the spatial spherical interpolation method; is the radius of the sphere.

[0030] In some embodiments, step 105 specifically includes: reconstructing the sliding interface based on the gradient descent Kriging interpolation method; the calculation formula of the gradient descent Kriging interpolation method is: .

[0031] in, To reconstruct any point selected on the sliding interface o Corresponding elevation data; Any point selected from the boundary ranges of the left and right sides of the landslide accumulation area, the boundary range of the landslide wall area, and the boundary range of the reconstructed original slope foot Elevation data on the Z axis of the spatial rectangular coordinate system; n is the number of points randomly selected from the boundary ranges of the left and right sides of the landslide accumulation area, the boundary range of the landslide wall area, and the boundary range of the area required for slope foot reconstruction; for point Weight coefficient.

[0032] in, , for example, , As a pointo The true value is unknown. Assume that n has a value of 3, and interpolation can only be performed through the three points o around it. That is, the values of , and are known, and is 's weight, and The values add up to 1, and in this way, the estimated value of is calculated. For example, is 1200, is 1260, is 1300; is 0.2, is 0.5, is 0.3, + + = 1. Then = 1200×0.2 + 1260×0.5 + 1300×0.3 = 1260.

[0033] In some embodiments, before step 106, step 201 is further included.

[0034] Step 201: With the goal of minimizing the value of the error function, update the elevation data corresponding to each point on the reconstructed sliding interface.

[0035] In some embodiments, step 201 specifically includes: With the goal of minimizing the value of the error function, according to , update to determine the weight coefficient of the updated point ; where is the weight coefficient of the updated point ; α is the learning rate; ; and j are respectively two points randomly selected from the boundary ranges on the left and right sides of the landslide accumulation area, the boundary range of the landslide wall area, and the boundary range of the reconstructed original toe of the slope; is the semi - variance of the elevation data corresponding to point and point j respectively; is the planar distance between point and point j ; w is the slope; is the intercept; According to the updated weight coefficient and the calculation formula of the gradient - descent Kriging interpolation method, determine the updated ; Use the updated as the elevation data corresponding to the points on the final reconstructed sliding interface o .

[0036] In some embodiments, the calculation formula of the error function is: .

[0037] Where J is the error function; ; is the semi - variance of the elevation data of the left and right boundaries of the landslide accumulation area, the landslide wall area, and the inner points of the original slope foot of the reconstruction and the points j ; is the semi - variance of the elevation data corresponding to the point and the point o respectively; r oo is the semi - variance of the elevation data corresponding to the point o ; λ j is the weight coefficient; is the planar distance between the point and the point j ; w is the slope; b is the intercept.

[0038] In some embodiments, according to the elevation data of the sliding interface and the elevation data of the landslide accumulation area, determine the landslide volume, specifically including: randomly select multiple points on the reconstructed sliding interface; use the original elevation data corresponding to each point on the landslide accumulation area as the elevation data of the landslide accumulation area; use the elevation data corresponding to each point on the reconstructed sliding interface as the elevation data of the sliding interface; determine the landslide volume according to the pixel area, the original elevation data corresponding to each point on the landslide accumulation area, and the elevation data corresponding to each point on the reconstructed sliding interface.

[0039] In some embodiments, the calculation formula of the landslide volume is: .

[0040] Where V is the landslide volume; M is the landslide disaster area; is the original elevation data corresponding to the point o on the landslide accumulation area; is the elevation data corresponding to the point o on the reconstructed sliding interface; S is the pixel area.

[0041] Among them, grid division is performed on the reconstructed sliding interface to determine the pixel area of each grid. For example, if the reconstructed sliding interface is an area of 100 meters × 100 meters, it can be divided into 100 rows × 100 columns, for a total of 10,000 grids. The area of each grid is 1 square meter, so the total area of all grids is 10,000 square meters.

[0042] This application considers the situation where the landslide accumulation covers the shear outlet. Reconstructing the landslide shear outlet marks the starting point where the landslide material begins to detach from its original position and move downward along the slope, that is, the reconstructed original toe topography. And the elevation data of the reconstructed original toe topography is crucial for reconstructing the sliding interface. Therefore, after reconstructing the original toe topography using the spatial sphere interpolation method, the Kriging interpolation method based on gradient descent is used to reconstruct the sliding interface, which can significantly improve the estimation accuracy of the landslide volume and provide important data decision support for the emergency rescue and engineering construction of landslide disasters.

[0043] Example 2: Taking the estimation of a certain landslide volume as an example, the specific steps and processes are as follows.

[0044] S1: Obtain the three-dimensional laser ground point cloud data and UAV aerial image data of the landslide and its surrounding area, as shown in Figures 2(a) and 2(b). Among them, the landslide area is the landslide accumulation area. The surrounding area of the landslide is the landslide wall area and the area required for toe reconstruction.

[0045] S2: According to the UAV aerial images, identify and delineate the boundary ranges of the landslide accumulation area, the landslide wall area, and the area required for toe reconstruction, as shown in Figures 3(a) and 3(b).

[0046] S3: According to the three-dimensional laser ground point cloud data within the area required for toe reconstruction, reconstruct the original toe topographic boundary before the landslide occurred.

[0047] Among them, the spatial sphere interpolation method used for reconstruction is:

[0048] 。

[0049] Among them, ( x 1, y 1, z 1), ( x 2, y 2, z 2) … ( x 20 , y 20 , z 20 )are the values of the X-axis, Y-axis, and Z-axis of 20 three-dimensional laser ground points selected within the area required for toe reconstruction in the 3-degree 34-band spatial coordinate system, respectively; is the coordinate value of the center of the sphere in the spatial coordinate system used by the spatial sphere interpolation method, and here we solve =511965, b =3276733, c =1277; r is the radius of the sphere, where we can solve r =21697.

[0050] S4: Reconstruct the sliding interface by combining the fitted data of the original slope foot before the landslide occurred with the 3D laser point cloud data of the left and right boundaries of the landslide accumulation area and the landslide wall area. The fitted data is the elevation data, and the elevation values are the fitted values. The fitted data includes multiple fitted values, and the elevation data includes multiple elevation values.

[0051] Among them, the Kriging interpolation method based on gradient descent used to reconstruct the sliding interface is: .

[0052] in, Any point on the reconstructed sliding interface o The elevation value on the Z axis of the spatial rectangular coordinate system; Points selected for the left and right boundaries of the landslide accumulation area, the landslide wall area, and the reconstructed original slope foot The elevation value on the Z axis of the spatial rectangular coordinate system; n The number of points selected for the left and right boundaries of the landslide accumulation area, the landslide wall area, and the reconstructed original slope foot, n It can be 30; is the weight coefficient, as follows.

[0053] .

[0054] .

[0055] .

[0056] in, The left and right boundaries of the landslide accumulation area, the landslide wall area, and any point within the reconstructed original slope foot and point j semivariance of elevation values; for point and point o The semivariance of the corresponding elevation value; r oo for point o Semivariance of own elevation value; λ j is the weight coefficient; for point and point jPlane distance; w is the slope; b is the intercept, here w =1.2654, b =287.36; J is the error function, which needs to be iterated continuously to J Take the minimum value, specifically: . The point after iteration The weight coefficient of is the point (before update) The weight coefficient of α is the learning rate, usually set to 0.001.

[0057] Among them, the error function J The minimum value can be 1796.62, corresponding to the updated weight coefficient , exemplarily, as shown in Table 1.

[0058] Table 1 Updated weight coefficient table

[0059]

[0060] At this point, any point selected on the reconstructed sliding interface can be obtained o Fitting value on the Z axis of the spatial rectangular coordinate system .

[0061] S5: The landslide volume is obtained by integrating the difference between the reconstructed sliding interface elevation data and the surface elevation data of the accumulation area. The specific expression of the landslide volume is: .

[0062] in, For landslide hazard areas, for example, the landslide hazard area is divided into 87,500 grids; Z o It is the elevation value of any point selected in the landslide hazard area on the Z axis of the spatial coordinate system, which is directly read from the digital elevation model; is the pixel area, preferably a 2m×2m grid; is the landslide volume, and the calculated result is 875810m 3 .

[0063] Based on the spatial spherical interpolation method to reconstruct the original topography at the foot of the slope, this application uses the gradient descent Kriging interpolation method to reconstruct the landslide sliding interface, which can improve the accuracy of sliding interface fitting and improve the accuracy of landslide volume estimation.

[0064] In an exemplary embodiment, a computer device is further provided, including a memory and a processor. A computer program is stored in the memory, and when the processor executes the computer program, the above method is implemented.

[0065] In an exemplary embodiment, a computer-readable storage medium is provided, storing a computer program, and when the computer program is executed by a processor, the above method is implemented.

[0066] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use, and processing of relevant data need to comply with relevant regulations.

[0067] Those of ordinary skill in the art can understand that all or part of the processes in the above-described embodiment methods can be completed by instructing relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the above-described method embodiments. Among them, any reference to a memory, database, or other medium used in the various embodiments provided in this application can include at least one of non-volatile and volatile memories. Non-volatile memories can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memories can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc.

[0068] In each of the embodiments provided in this application, the databases involved may include at least one of a relational database and a non-relational database. The non-relational database may include a distributed database based on blockchain, etc., without limitation. In each of the embodiments provided in this application, the processor may be a general-purpose processor, a central processing unit, a graphics processing unit, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., without limitation.

[0069] The technical features of the above embodiments can be combined arbitrarily. For the sake of brevity of description, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, it should be considered as the scope described in this specification.

[0070] In this article, specific examples are used to elaborate on the principles and implementation manners of this application. The descriptions of the above embodiments are only used to help understand the method and its core idea of this application; at the same time, for those of ordinary skill in the art, according to the idea of this application, there will be changes in the specific implementation manners and application scopes. In summary, the content of this specification should not be construed as a limitation to this application.

Claims

1. A landslide volume estimation method based on post-disaster remote sensing data, characterized in that Including: Obtain post-disaster remote sensing data, where the post-disaster remote sensing data includes three-dimensional laser ground point cloud data and unmanned aerial vehicle (UAV) aerial image data of the landslide disaster area; the landslide disaster area includes the landslide accumulation area, the landslide wall area, and the area required for slope foot reconstruction; Based on the UAV aerial image data, identify and demarcate the boundary ranges on the left and right sides of the landslide accumulation area, the boundary range of the landslide wall area, and the boundary range of the area required for slope foot reconstruction; Based on the three-dimensional laser ground point cloud data within the area required for slope foot reconstruction, reconstruct the original slope foot topographic boundary before the landslide occurred; specifically, use the spatial sphere interpolation method to reconstruct the original slope foot topographic boundary before the landslide occurred; Based on the reconstructed original slope foot topographic boundary before the landslide occurred, determine the elevation data of the original slope foot before the landslide occurred; the elevation data is determined based on the values on the Z-axis of the three-dimensional laser ground point cloud data in the spatial rectangular coordinate system; the spatial rectangular coordinate system is established with the central meridian and the equator as the center, the projection of the equator as the X-axis, and the central meridian as the Y-axis; Based on the elevation data of the original slope foot before the landslide occurred, and the three-dimensional laser ground point cloud data within the boundary ranges on the left and right sides of the landslide accumulation area and within the boundary range of the landslide wall area, reconstruct the sliding interface; specifically, use the Kriging interpolation method based on gradient descent to reconstruct the sliding interface; Determine the landslide volume based on the elevation data of the sliding interface and the elevation data of the landslide accumulation area; Wherein, before determining the landslide volume based on the elevation data of the sliding interface and the elevation data of the landslide accumulation area, it further includes: aiming at minimizing the value of the error function, update the elevation data corresponding to each point on the reconstructed sliding interface; specifically, update the weight coefficient aiming at minimizing the value of the error function, and update the elevation data corresponding to each point on the reconstructed sliding interface according to the updated weight coefficient and the calculation formula of the Kriging interpolation method based on gradient descent.

2. The landslide volume estimation method based on post-disaster remote sensing data according to claim 1, wherein Reconstruct the original slope foot topographic boundary before the landslide occurred based on the three-dimensional laser ground point cloud data within the area required for slope foot reconstruction, specifically including: Based on the three-dimensional laser ground point cloud data within the area required for slope foot reconstruction, use the spatial sphere interpolation method to reconstruct the original slope foot topographic boundary before the landslide occurred; The calculation formula of the spatial sphere interpolation method is: ； Among them, ( , , ) are the values of the X-axis, Y-axis, and Z-axis of the th three-dimensional laser terrestrial point cloud data selected within the area required for toe slope reconstruction in the space rectangular coordinate system; = 1, 2,..., ; is the total number of three-dimensional laser terrestrial point cloud data; are the coordinate values of the center of the sphere adopted by the spatial sphere interpolation method in the space rectangular coordinate system; is the sphere radius.

3. The landslide volume estimation method based on post-disaster remote sensing data according to claim 1, characterized in that Based on the elevation data of the original slope foot before the landslide occurred, and the three-dimensional laser ground point cloud data within the boundary ranges on the left and right sides of the landslide accumulation area and within the boundary range of the landslide wall area, reconstruct the sliding interface, specifically including: Use the Kriging interpolation method based on gradient descent to reconstruct the sliding interface; the calculation formula of the Kriging interpolation method based on gradient descent is: ； Among them, is the elevation data corresponding to an arbitrarily selected point on the reconstructed sliding surface o ; is the elevation data on the Z-axis of the spatial rectangular coordinate system for an arbitrarily selected point from the boundary ranges on both the left and right sides of the landslide accumulation area, the boundary range of the landslide wall area, and the boundary range of the reconstructed original toe of the slope ; is the number of arbitrarily selected points from the boundary ranges on both the left and right sides of the landslide accumulation area, the boundary range of the landslide wall area, and the boundary range of the area required for toe reconstruction ; is the weight coefficient of the selected point .

4. The landslide volume estimation method based on post-disaster remote sensing data according to claim 3, wherein, Before determining the landslide volume based on the elevation data of the sliding interface and the elevation data of the landslide accumulation area, it further includes: Aim at minimizing the value of the error function and update the elevation data corresponding to each point on the reconstructed sliding interface.

5. The landslide volume estimation method based on post-disaster remote sensing data according to claim 4, wherein Aim at minimizing the value of the error function and update the elevation data corresponding to each point on the reconstructed sliding interface, specifically including: Aiming at minimizing the value of the error function, according to , update to determine the weight coefficient of the updated point ; where is the weight coefficient of the updated point ; α is the learning rate; ; and j are two points randomly selected from the boundary ranges on the left and right sides of the landslide accumulation area, the boundary range of the landslide wall area, and the boundary range of the reconstructed original toe of the slope, respectively; is the semi-variance of the elevation data corresponding to point and point j respectively; is the planar distance between point and point j ; is the slope; is the intercept; Determine the updated one according to the updated weight coefficient and the calculation formula of the gradient descent Kriging interpolation method ; Use the updated as the elevation data corresponding to the points on the final reconstructed sliding interface o .

6. The landslide volume estimation method based on post-disaster remote sensing data according to claim 4, characterized in that The calculation formula of the error function is: ； Among them, J is the error function; ; is the semi-variance of the elevation data of the left and right boundaries on both sides of the landslide accumulation area, the landslide wall area, and the inner points of the reconstructed original toe of the slope and point j ; is the semi-variance of the elevation data corresponding to point and point o respectively; r oo is the semi-variance of the elevation data corresponding to point o ; is the weight coefficient of point j ; is the planar distance between point and point j ; is the slope; is the intercept.

7. The landslide volume estimation method based on post-disaster remote sensing data according to claim 1, wherein Determine the landslide volume according to the elevation data of the sliding interface and the elevation data of the landslide accumulation area, specifically including: Multiple points arbitrarily selected from the reconstructed sliding interface; Use the original elevation data corresponding to each point on the landslide accumulation area as the elevation data of the landslide accumulation area; Use the elevation data corresponding to each point on the reconstructed sliding interface as the elevation data of the sliding interface; Determine the landslide volume according to the pixel area, the original elevation data corresponding to each point on the landslide accumulation area, and the elevation data corresponding to each point on the reconstructed sliding interface.

8. The landslide volume estimation method based on post-disaster remote sensing data according to claim 1, characterized in that The calculation formula for the landslide volume is: ； Among them, is the landslide volume; is the landslide disaster area; is the original elevation data corresponding to the upper point o in the landslide accumulation area; is the elevation data corresponding to the upper point o on the reconstructed sliding boundary; is the pixel area.

9. A computer device, comprising: A memory, a processor, and a computer program stored on the memory and executable on the processor, wherein the processor executes the computer program to implement the landslide volume estimation method based on post-disaster remote sensing data according to any one of claims 1-8.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the landslide volume estimation method based on post-disaster remote sensing data according to any one of claims 1-8.

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