Method and device for screening elevation control points based on ICESat-2 data

Abstract

The present invention provides a method and device for screening elevation control points based on ICESat-2 data, which relates to the technical field of data processing. The method and device include: combining ATL03 and ATL08 of ICESat-2 to extract all original ground photon points from ATL03; taking each 100-meter segment in the along-track direction of ATL08 as a unit, converting all original ground photon points in each 100-meter segment in ATL03 to a horizontal reference plane to obtain ground photon points after removing the terrain; constructing an elevation frequency histogram and calculating the skewness of the elevation frequency histogram and the vertical concentration of ground photons in each 100-meter segment; screening potential elevation control points in ATL08 based on the attribute parameters of each potential elevation control point in ATL08, the corresponding vertical concentration and skewness of the ground photons, obtaining elevation control point screening results, and effectively improving the extraction accuracy of elevation control points.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and in particular to a method and device for screening elevation control points based on ICESat-2 data. Background Art

[0002] Elevation control points are primarily used for fine-grained topographic mapping, and their extraction accuracy directly impacts the accuracy of the final topographic mapping results. Low accuracy of elevation control points will increase terrain fitting errors, reducing the reliability of the mapping results.

[0003] The existing ICESat-2 elevation control point screening method mainly relies on the ATL08 product, which selects elevation control points by setting empirical thresholds. However, since only ATL08 parameters are used, it is difficult to effectively eliminate anomalies in the vertical distribution of discrete ground points (such as multiple scattering, complex terrain, and confusion between low vegetation and ground points), resulting in limited accuracy of elevation control points. Summary of the Invention

[0004] The purpose of the present invention is to provide a method and device for screening elevation control points based on ICESat-2 data, so as to alleviate the technical problem of poor elevation control point extraction accuracy in existing ICESat-2 elevation control point screening methods.

[0005] In a first aspect, the present invention provides a method for screening elevation control points based on ICESat-2 data, comprising: combining the ATL03 data product and the ATL08 data product of ICESat-2 to extract all original ground photon points from the ATL03 data product; taking the ATL08 data product as a unit of each 100-meter segment along the track direction, converting all original ground photon points in each 100-meter segment of the ATL03 data product to a horizontal reference plane to obtain all ground photon points after removing the terrain in each 100-meter segment; constructing an elevation frequency histogram for each 100-meter segment based on all ground photon points after removing the terrain in each 100-meter segment, and calculating the skewness of the elevation frequency histogram and the elevation frequency of each 100-meter segment. The vertical concentration of ground photons is expressed as follows: the horizontal axis of the elevation frequency histogram represents the elevation interval, and the vertical axis represents the proportion of the number of ground photon points falling into the elevation interval to the total number of ground photon points in the 100m segment to which it belongs; the vertical concentration of ground photons represents the ratio of the peak of the elevation frequency histogram to the height standard deviation of the ground photon points in the 100-meter segment; based on the attribute parameters of each potential elevation control point in the ATL08 data product, the vertical concentration of ground photons in the 100-meter segment to which it belongs, and the skewness of the corresponding elevation frequency histogram, the potential elevation control points in the ATL08 data product are screened to obtain the elevation control point screening results; the potential elevation control points represent the ATL08 ground photon points used for elevation control screening.

[0006] In an optional embodiment, the ATL03 data product and the ATL08 data product of ICESat-2 are combined to extract all original ground photon points from the ATL03 data product, including: extracting attribute parameters of each photon point in the ATL03 data product and the ATL08 data product; spatially matching the ATL03 data product and the ATL08 data product based on the attribute parameters; using the classification information of the target photon point in the ATL08 data product as the classification label of the photon point in the ATL03 data product that matches it spatially; wherein the target photon point represents any photon point among all the photon points in the ATL08 data product; and determining all original ground photon points based on the classification labels of all photon points in the ATL03 data product.

[0007] In an optional embodiment, all original ground photon points in each 100-meter segment of the ATL08 data product in the along-track direction are converted to a horizontal reference plane, including: obtaining the along-track distance and elevation value of each original ground photon point in the target 100-meter segment in the ATL03 data product; wherein the target 100-meter segment represents any segment of all 100-meter segments in the ATL03 data product; fitting the along-track distance and elevation value of the original ground photon point in the target 100-meter segment to obtain the terrain slope of the target 100-meter segment; constructing a two-dimensional rotation matrix based on the terrain slope; and converting each original ground photon point in the target 100-meter segment to a horizontal reference plane based on the two-dimensional rotation matrix to obtain the corresponding ground photon point after removing the terrain.

[0008] In an optional embodiment, the along-track distance and elevation value of the original ground photon point within the target 100-meter segment are fitted to obtain the terrain slope of the target 100-meter segment, including: constructing a univariate linear regression equation of the elevation and along-track distance of the original ground photon point; wherein the elevation of the original ground photon point is the dependent variable of the univariate linear regression equation, the along-track distance of the original ground photon point is the independent variable of the univariate linear regression equation, and the terrain slope of the segment to which the original ground photon point belongs is the slope of the univariate linear regression equation; substituting the along-track distance and elevation value of the original ground photon point within the target 100-meter segment into the univariate linear regression equation to obtain the target equation group; and solving the target equation group using the least squares method to obtain the terrain slope of the target 100-meter segment.

[0009] In an optional embodiment, based on all ground photon points after removing the terrain in each 100-meter segment, an elevation frequency histogram of each 100-meter segment is constructed, and the skewness of the elevation frequency histogram and the vertical concentration of ground photons in each 100-meter segment are calculated, including: grouping all ground photon points after removing the terrain in the target 100-meter segment at preset elevation intervals, and counting the number of ground photon points falling into each elevation interval; wherein the target 100-meter segment represents any segment of all 100-meter segments in the ATL03 data product; with the elevation interval as the horizontal axis, the ground photon points falling into the elevation interval are counted. The ratio of the number of photon points to the total number of ground photon points in the 100m segment to which it belongs is the vertical axis, and an elevation frequency histogram of the target 100-meter segment is constructed; the peak of the elevation frequency histogram of the target 100-meter segment is determined; the height standard deviation of all ground photon points after removing the terrain in the target 100-meter segment is calculated; based on the height standard deviation and the elevation of all ground photon points after removing the terrain in the target 100-meter segment, the skewness of the elevation frequency histogram of the target 100-meter segment is calculated; the ratio of the peak and the height standard deviation is calculated, and the ratio result is used as the vertical concentration of ground photons in the target 100-meter segment.

[0010] In an optional embodiment, based on the attribute parameters of each potential elevation control point in the ATL08 data product, the ground photon vertical concentration of the 100-meter segment to which it belongs, and the skewness of the corresponding elevation frequency histogram, the potential elevation control points in the ATL08 data product are screened, including: calculating the difference between the elevation of the target potential elevation control point and its reference elevation; wherein the target potential elevation control point represents any potential elevation control point in the ATL08 data product; and eliminating the target potential elevation control point when it is determined that the target potential elevation control point meets any of the following preset conditions; wherein the preset condition Including: the absolute value of the difference is greater than the first threshold, the cloud cover identifier is greater than the second threshold, the surface type identifier is equal to the third threshold, the number of ground photon points in the 100-meter segment is less than or equal to the fourth threshold, the total number of photon points in the 100-meter segment is greater than or equal to the fifth threshold, the proportion of ground photon points in the 100-meter segment is less than or equal to the sixth threshold, the point discrete distribution identifier is equal to 1, the sum of the ground photon distribution identifiers of the 100-meter segment is not equal to 5, the vertical concentration of ground photons in the 100-meter segment is less than the seventh threshold, and the absolute value of the skewness of the elevation frequency histogram of the 100-meter segment is greater than the eighth threshold.

[0011] In a second aspect, the present invention provides a device for screening elevation control points based on ICESat-2 data, comprising: an extraction module for combining the ATL03 data product and the ATL08 data product of ICESat-2 to extract all original ground photon points from the ATL03 data product; a conversion module for converting all original ground photon points in each 100-meter segment of the ATL08 data product in the along-track direction to a horizontal reference plane, thereby obtaining all ground photon points after removing the terrain in each 100-meter segment; and a calculation module for constructing an elevation frequency histogram for each 100-meter segment based on all ground photon points after removing the terrain in each 100-meter segment, and calculating the skewness and the value of the elevation frequency histogram. The vertical concentration of ground photons in each 100-meter segment; the horizontal axis of the elevation frequency histogram represents the elevation interval, and the vertical axis represents the proportion of ground photon points falling into the elevation interval to the total number of ground photon points in the 100-meter segment to which it belongs; the vertical concentration of ground photons represents the ratio of the peak of the elevation frequency histogram to the height standard deviation of the ground photon points in the 100-meter segment; the screening module is used to screen the potential elevation control points in the ATL08 data product based on the attribute parameters of each potential elevation control point in the ATL08 data product, the vertical concentration of ground photons in the 100-meter segment to which it belongs, and the skewness of the corresponding elevation frequency histogram, to obtain the elevation control point screening results; the potential elevation control point represents the ATL08 ground photon point used for elevation control screening.

[0012] In an optional embodiment, the extraction module is specifically used to: extract the attribute parameters of each photon point in the ATL03 data product and the ATL08 data product; spatially match the ATL03 data product and the ATL08 data product based on the attribute parameters; use the classification information of the target photon point in the ATL08 data product as the classification label of the photon point in the ATL03 data product that matches it spatially; wherein the target photon point represents any photon point among all the photon points in the ATL08 data product; and determine all original ground photon points based on the classification labels of all photon points in the ATL03 data product.

[0013] In a third aspect, the present invention provides an electronic device comprising a memory and a processor, wherein the memory stores a computer program that can be run on the processor, and when the processor executes the computer program, it implements the method for screening elevation control points based on ICESat-2 data as described in any one of the aforementioned embodiments.

[0014] In a fourth aspect, the present invention provides a computer-readable storage medium storing computer instructions, which, when executed by a processor, implement the method for screening elevation control points based on ICESat-2 data as described in any one of the aforementioned embodiments.

[0015] The present invention provides a method for screening elevation control points based on ICESat-2 data. First, the ATL03 data product and the ATL08 data product of ICESat-2 are combined to extract all original ground photon points from the ATL03 data product. Then, based on each 100-meter segment of the ATL08 data product in the along-track direction, all original ground photon points in each 100-meter segment of the ATL03 data product are converted to a horizontal reference plane to obtain all ground photon points in each 100-meter segment after removing the terrain. Then, an elevation frequency histogram that can accurately reflect the photon concentration is constructed for each 100-meter segment, and the skewness of the elevation frequency histogram and the ground photon vertical concentration of each 100-meter segment are calculated. Finally, based on the attribute parameters of each potential elevation control point in the ATL08 data product, the ground photon vertical concentration of the 100-meter segment to which it belongs, and the skewness of the corresponding elevation frequency histogram, the potential elevation control points in the ATL08 data product are screened to obtain an elevation control point screening result. By combining the ATL03 and ATL08 data products, this paper proposes two new parameters for screening elevation control points: ground photon vertical concentration and skewness. Compared with screening using only the ATL08 parameters, this method can effectively improve the extraction accuracy of elevation control points and provide technical support for global elevation control point extraction and fine terrain mapping. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the specific embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0017] Figure 1 A flowchart of a method for screening elevation control points based on ICESat-2 data provided by an embodiment of the present invention;

[0018] Figure 2 The frequency distribution histogram of the ground elevation error between the original data and the elevation control points in the flat area;

[0019] Figure 3 The frequency distribution histogram of the ground elevation error between the original data and the elevation control points in the hilly area;

[0020] Figure 4 The frequency distribution histogram of the ground elevation error between the original data and the elevation control points in the mountainous area;

[0021] Figure 5This is the comparison result of the elevation control point accuracy verification of ATL08 original data, without adding new parameters, and after adding new parameters;

[0022] Figure 6 A comparison chart of the results of the solution provided by the embodiment of the present invention and the elevation control point screening solution proposed by Li et al., (2021);

[0023] Figure 7 A functional module diagram of a device for screening elevation control points based on ICESat-2 data provided by an embodiment of the present invention;

[0024] Figure 8 A schematic diagram of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0025] To make the objectives, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions of the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Generally, the components of the embodiments of the present invention described and shown in the drawings herein can be arranged and designed in various different configurations.

[0026] Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the invention as claimed, but rather merely represents selected embodiments of the present invention. All other embodiments derived by persons of ordinary skill in the art based on the embodiments of the present invention without creative effort shall fall within the scope of protection of the present invention.

[0027] The following embodiments of the present invention are described in detail with reference to the accompanying drawings. In the absence of conflict, the following embodiments and features in the embodiments may be combined with each other.

[0028] Example 1

[0029] Figure 1 A flowchart of a method for screening elevation control points based on ICESat-2 data is provided in an embodiment of the present invention, such as Figure 1 As shown, the method specifically includes the following steps:

[0030] Step S102 : Combining the ATL03 data product and the ATL08 data product of ICESat-2 to extract all original ground photon points from the ATL03 data product.

[0031] ICESat-2 / ATLAS provides 23 standard data products (ATL00 to ATL23, excluding ATL05). This embodiment of the present invention primarily studies ATL03 and ATL08. ATL03 calculates the precise geolocation information (latitude, longitude, and elevation) for each received photon based on the photon's round-trip time, laser position, and attitude angle. ATL08, building on the preprocessing of ATL03, removes a significant amount of noise photons and classifies the remaining photons into noise points, ground points, canopy points, and top canopy points.

[0032] The ATL08 data product also includes ground photon points used for elevation control screening (only one point per 100m segment). This embodiment of the present invention refers to them as potential elevation control points. The method provided by this embodiment of the present invention is to eliminate abnormal elevation control points from these potential elevation control points to obtain high-precision elevation control points, thereby providing technical support for subsequent fine terrain mapping.

[0033] At the beginning of the execution of the method of the embodiment of the present invention, the ATL03 data product and the ATL08 data product of ICESat-2 are first combined to spatially match and classify the photon points in the above two data products, thereby assigning the classification information of ATL08 to the ATL03 photon points to construct photon-level classified point cloud data, and then all the original ground photon points in the ATL03 data product are determined based on the classification information.

[0034] In step S104, all original ground photon points in each 100-meter segment of the ATL08 data product along the track direction are converted to a horizontal reference plane to obtain all ground photon points in each 100-meter segment after removing the terrain.

[0035] It is known that the vertical concentration of ground photon points is closely related to their accuracy. The more dispersed the elevation distribution of ground photon points, the higher the probability that the ground photon points deviate from the true ground. To quantify the vertical concentration of raw ground photon points, this embodiment of the present invention combines the ATL08 and ATL03 data products. Taking each 100-meter segment of the ATL08 data product along the track as a unit, the elevation frequency histogram of raw ground photon points in each 100-meter segment of the ATL03 data product is calculated. The peak value and elevation standard deviation are extracted, and the peak value / elevation standard deviation is used as the concentration indicator.

[0036] However, since the terrain undulation affects the distribution of the original ground photon points, if the elevation standard deviation is calculated directly based on the original ground photon points or the elevation frequency histogram is constructed, the photon concentration cannot be accurately reflected. In order to eliminate the influence of terrain, the embodiment of the present invention converts all the original ground photon points in each 100-meter segment in the ATL03 data product to a horizontal reference plane, that is, removes the influence of terrain undulation and obtains the ground photon points after removing the terrain. Optionally, linear regression is used to fit the terrain slope, and a rotation matrix is ​​constructed to transform the ground photon points, thereby obtaining the photon distribution after removing the influence of terrain undulation, so as to improve the accuracy of the photon concentration assessment.

[0037] Step S106: Based on all ground photon points after removing the terrain in each 100-meter segment, an elevation frequency histogram of each 100-meter segment is constructed, and the skewness of the elevation frequency histogram and the vertical concentration of ground photons in each 100-meter segment are calculated.

[0038] Among them, the horizontal axis of the elevation frequency histogram represents the elevation interval, and the vertical axis represents the proportion of the number of ground photon points falling into the elevation interval to the total number of ground photon points in the 100m segment to which it belongs; the vertical concentration of ground photons represents the ratio of the peak of the elevation frequency histogram to the height standard deviation of the ground photon points in the 100-meter segment.

[0039] According to the definitions of the horizontal and vertical axes of the elevation frequency histogram above, to construct an elevation frequency histogram for each 100-meter segment, it is necessary to divide the elevation in the segment into fixed intervals, count the number of ground photon points that fall into each elevation interval, and then calculate the proportion of the total number of ground photon points in the 100-meter segment to which it belongs.

[0040] The embodiment of the present invention characterizes the vertical dispersion of ground photon points within a 100-meter segment by calculating the standard deviation of the heights of the ground photon points within the 100-meter segment. The peak of the elevation frequency histogram represents the highest frequency value in the elevation frequency histogram (that is, the maximum value of the proportion of the number of ground photon points falling into the elevation interval to the total number of ground photon points), that is, the main peak of the elevation frequency distribution, corresponding to the elevation value where the ground photons are most concentrated. The skewness of the elevation frequency histogram is used to measure the symmetry of the elevation distribution of ground photon points, reflecting the skewness of the distribution of ground photon points. A positive skewness value indicates that the distribution is right-skewed, and a negative skewness value indicates that the distribution is left-skewed.

[0041] Step S108, based on the attribute parameters of each potential elevation control point in the ATL08 data product, the vertical concentration of ground photons in the 100-meter segment to which it belongs, and the skewness of the corresponding elevation frequency histogram, the potential elevation control points in the ATL08 data product are screened to obtain the elevation control point screening results.

[0042] Among them, potential elevation control points represent ATL08 ground photon points used for elevation control screening.

[0043] In the prior art, elevation control points are screened only based on the attribute parameters of potential elevation control points in the ATL08 data product by setting empirical thresholds. However, this screening method cannot effectively eliminate abnormal situations in the vertical discrete distribution of ground points (such as multiple scattering, complex terrain, and confusion between low vegetation and ground points). Therefore, an embodiment of the present invention proposes to calculate two parameters: the vertical concentration of ground photons in the 100-meter segment to which the potential elevation control points belong and the skewness of the corresponding elevation frequency histogram, and further screen the potential elevation control points in the ATL08 data product based on the above two parameters, thereby eliminating potential elevation control points affected by abnormal elevation, clouds, water bodies, ground reflection, solar radiation, atmospheric interference and the vertical discreteness of ground photons, thereby improving the accuracy of elevation control point extraction.

[0044] An embodiment of the present invention provides a method for screening elevation control points based on ICESat-2 data. First, the ATL03 data product and the ATL08 data product of ICESat-2 are combined to extract all original ground photon points from the ATL03 data product. Then, based on each 100-meter segment in the along-track direction of the ATL08 data product, all original ground photon points in each 100-meter segment of the ATL03 data product are converted to a horizontal reference plane to obtain all ground photon points in each 100-meter segment after removing the terrain. Then, an elevation frequency histogram that can accurately reflect the photon concentration is constructed for each 100-meter segment, and the skewness of the elevation frequency histogram and the ground photon vertical concentration of each 100-meter segment are calculated. Finally, based on the attribute parameters of each potential elevation control point in the ATL08 data product, the ground photon vertical concentration of the 100-meter segment to which it belongs, and the skewness of the corresponding elevation frequency histogram, potential elevation control points in the ATL08 data product are screened to obtain an elevation control point screening result. The embodiment of the present invention proposes two new parameters for screening elevation control points by combining the ATL03 and ATL08 data products: ground photon vertical concentration and skewness. Compared with screening using only the ATL08 parameters, the extraction accuracy of elevation control points can be effectively improved, providing technical support for global elevation control point extraction and fine terrain mapping.

[0045] In an optional embodiment, the above step S102 combines the ATL03 data product and the ATL08 data product of ICESat-2 to extract all original ground photon points from the ATL03 data product, specifically including the following steps:

[0046] Step S1021 , extracting attribute parameters of each photon point in the ATL03 data product and the ATL08 data product.

[0047] Step S1022 : spatially matching the ATL03 data product and the ATL08 data product based on the attribute parameters.

[0048] Specifically, first, the attribute parameters of each photon point are extracted from the ATL03 data product and the ATL08 data product. The following Table 1 shows the attribute parameters of the photon point in the ATL03 data product, and Table 2 shows the attribute parameters of the photon point in the ATL08 data product.

[0049] The following describes step S1022 using the method of spatially matching any classified photon point in the ATL08 data product with a photon point in the ATL03 data product as an example. Specifically, to spatially match photon points in the ATL03 data product and the ATL08 data product, the ATL03 attribute parameters in Table 1 are first used to connect each segmented photon to obtain the global index of all ATL03 photons. The classed_pc_indx and ph_segment_id corresponding to any classified photon point in the ATL08 data product (hereinafter referred to as the classified photon point) are then obtained. Finally, the global index position of the classified photon point in the ATL03 original photon sequence is calculated based on the classed_pc_indx and ph_segment_id parameters and the ph_index_beg and segment_id parameters provided by ATL03, thereby determining the original photon point in the ATL03 data product that matches the classified photon point. This completes the spatial matching of a pair of photon points.

[0050] Table 1 Attribute parameters of photon points in ATL03 data products

[0051]

[0052] Table 2 Attribute parameters of photon points in ATL08 data products

[0053]

[0054] Step S1023 , using the classification information of the target photon point in the ATL08 data product as the classification label of the photon point spatially matched with it in the ATL03 data product; wherein the target photon point represents any photon point among all the photon points in the ATL08 data product.

[0055] In this embodiment of the present invention, the classification information classed_pc_flag of each photon point in the ATL08 data product is assigned to the ATL03 photon that matches its space, thereby completing the classification information transfer from the ATL08 data product to the ATL03 data product. As a result, most of the photon points in the ATL03 data product have classification labels (i.e., classification information). The classification labels include: noise point, ground point, canopy point, and top canopy point.

[0056] Step S1024: Determine all original ground photon points based on the classification labels of all photon points in the ATL03 data product.

[0057] That is to say, the photon points classified as ground points in the ATL03 data product are extracted, and all the original ground photon points are obtained as the basic data for subsequent data processing steps.

[0058] In an optional embodiment, the above step S104, taking the ATL08 data product as a unit of each 100-meter segment in the along-track direction, converts all original ground photon points in each 100-meter segment of the ATL03 data product to a horizontal reference plane, specifically comprising the following steps:

[0059] Step S1041, obtaining the along-track distance and elevation value of each original ground photon point in the target 100-meter segment in the ATL03 data product; wherein the target 100-meter segment represents any segment among all 100-meter segments in the ATL03 data product.

[0060] Step S1042 , fitting the along-track distance and elevation value of the original ground photon point within the target 100-meter segment to obtain the terrain slope of the target 100-meter segment.

[0061] As described above, this embodiment of the present invention processes raw ground photon points within each 100-meter segment of the ATL08 data product along the track. Specifically, the along-track distance and elevation values ​​of each raw ground photon point within the target 100-meter segment of the ATL03 data product are first obtained. Then, a linear regression is used to fit the along-track distance and elevation values ​​of the raw ground photon points to estimate the terrain slope along the track for the target 100-meter segment.

[0062] Step S1043: construct a two-dimensional rotation matrix based on the terrain slope.

[0063] In the embodiment of the present invention, the terrain slope is the slope angle The tangent value of Therefore, after obtaining the terrain slope, we can construct a two-dimensional rotation matrix by rotating around the X axis in the slope direction: .

[0064] In step S1044 , each original ground photon point within the target 100-meter segment is converted to a horizontal reference plane based on the two-dimensional rotation matrix to obtain a corresponding ground photon point after removing the terrain.

[0065] For each original ground photon point within the target 100-meter segment, a two-dimensional rotation matrix transformation is applied to obtain the ground photon point after removing the slope effect (that is, removing the terrain). The above transformation process is expressed as: ;in, represents the original ground photon point coordinates, represents the along-track distance of the original ground photon point, represents the elevation of the original ground photon point, Represents the coordinates of the ground photon point after removing the terrain, represents the distance along the track of the ground photon point after removing the terrain, Indicates the elevation of the ground photon point after removing the terrain.

[0066] After the above steps, all original ground photon points within the target 100-meter segment will be converted to a horizontal reference plane, eliminating the slope effect, so that the elevation frequency histogram and photon distribution characteristics can more accurately reflect the vertical aggregation degree of ground photon points.

[0067] In an optional embodiment, step S1042 is to fit the along-track distance and elevation value of the original ground photon point within the target 100-meter segment to obtain the terrain slope of the target 100-meter segment, which specifically includes the following steps:

[0068] Step S10421, construct a univariate linear regression equation of the elevation and along-track distance of the original ground photon point; wherein, the elevation of the original ground photon point is the dependent variable of the univariate linear regression equation, the along-track distance of the original ground photon point is the independent variable of the univariate linear regression equation, and the terrain slope of the segment to which the original ground photon point belongs is the slope of the univariate linear regression equation.

[0069] That is, the univariate linear regression equation is expressed as: ,in, represents the original ground photon point coordinates, Indicates the terrain slope of the segment to which the original ground photon point belongs, represents the intercept.

[0070] Step S10422: Substitute the along-track distance and elevation value of the original ground photon point within the target 100-meter segment into the univariate linear regression equation to obtain the target equation group.

[0071] Step S10423, using the least squares method to solve the target equation group to obtain the terrain slope of the target 100-meter segment.

[0072] Specifically, the least squares method (LSM) is used to calculate the regression parameters of the linear regression equation and , so that the sum of squared errors is minimized, that is: ,in, Represents the total number of raw ground photon points within the 100-meter segment of the target.

[0073] Taking the derivative of a and b and setting the derivative to zero, we can get the optimal solution: .

[0074] In an optional embodiment, step S106, based on all ground photon points after removing terrain in each 100-meter segment, constructs an elevation frequency histogram for each 100-meter segment, and calculates the skewness of the elevation frequency histogram and the vertical concentration of ground photons for each 100-meter segment, specifically comprising the following steps:

[0075] Step S1061, group all ground photon points after removing the terrain in the target 100-meter segment according to the preset elevation interval, and count the number of ground photon points falling into each elevation interval; wherein, the target 100-meter segment represents any segment of all 100-meter segments in the ATL03 data product.

[0076] In step S1062, an elevation frequency histogram of the target 100-meter segment is constructed, with the elevation interval as the horizontal axis and the ratio of the number of ground photon points falling into the elevation interval to the total number of ground photon points in the 100-meter segment to which it belongs as the vertical axis.

[0077] Specifically, all ground photon points after removing the terrain in the target 100-meter segment are grouped at fixed elevation intervals (exemplarily 0.1m), and the number of photons in each elevation interval is counted. The proportion of the number of ground photon points in each elevation interval to the total number of ground photon points in the 100-meter segment to which it belongs is then calculated, and an elevation frequency histogram is constructed. The height of the bars in the elevation frequency histogram corresponds to the proportion of the number of ground photon points in each elevation interval to the total number of ground photon points, reflecting the frequency of occurrence of the elevation.

[0078] Step S1063, determine the peak of the elevation frequency histogram of the target 100-meter segment. That is, determine the frequency value where the ground photon points are most concentrated in the segment. .

[0079] Step S1064, calculating the standard deviation of the heights of all ground photon points after removing the terrain within the target 100-meter segment.

[0080] Specifically, use the following formula to calculate the height standard deviation Calculation: ,in, Represents the average elevation of all ground photon points within the target 100-meter segment after removing the terrain, that is, .

[0081] Step S1065 , calculating the skewness of the elevation frequency histogram of the target 100-meter segment based on the height standard deviation and the elevations of all ground photon points after removing the terrain within the target 100-meter segment.

[0082] The calculation formula for skewness is: .

[0083] Step S1066, calculate the ratio of the peak value to the height standard deviation, and use the ratio result as the ground photon vertical concentration of the target 100-meter segment.

[0084] In order to quantify the vertical distribution concentration of ground photon points, the embodiment of the present invention proposes to use the ratio of the peak value to the elevation standard deviation as the ground photon vertical concentration, which is expressed as: Obviously, the vertical concentration of ground photons can represent the degree of aggregation of ground photon points. The larger the value of the vertical concentration of ground photons, the more concentrated the ground photon points are at a certain elevation and the flatter the terrain surface. The smaller the value of the vertical concentration of ground photons, the more dispersed the distribution of ground photon points is, which may be greatly affected by multiple scattering, low vegetation or local undulations.

[0085] In an optional embodiment, step S108 screens the potential elevation control points in the ATL08 data product based on the attribute parameters of each potential elevation control point in the ATL08 data product, the vertical concentration of ground photons in the 100-meter segment to which it belongs, and the skewness of the corresponding elevation frequency histogram. Specifically, the steps include:

[0086] Step S1081, calculating the difference between the elevation of the target potential elevation control point and its reference elevation; wherein the target potential elevation control point represents any potential elevation control point in the ATL08 data product.

[0087] Step S1082: When it is determined that the target potential elevation control point satisfies any of the following preset conditions, the target potential elevation control point is eliminated.

[0088] Among them, the preset conditions include: the absolute value of the difference is greater than the first threshold, the cloud cover identifier is greater than the second threshold, the surface type identifier is equal to the third threshold, the number of ground photon points in the 100-meter segment is less than or equal to the fourth threshold, the total number of photon points in the 100-meter segment is greater than or equal to the fifth threshold, the proportion of ground photon points in the 100-meter segment is less than or equal to the sixth threshold, the point discrete distribution identifier is equal to 1, the sum of the ground photon distribution identifiers of the 100-meter segment is not equal to 5, the vertical concentration of ground photons in the 100-meter segment is less than the seventh threshold, and the absolute value of the skewness of the elevation frequency histogram of the 100-meter segment is greater than the eighth threshold.

[0089] Based on the above steps, it can be seen that to improve the accuracy of the elevation control point screening results, this embodiment of the present invention adopts a multiple screening strategy to eliminate potential elevation control points affected by abnormal elevation, cloud cover, water bodies, ground reflection, solar radiation, atmospheric interference, and the vertical dispersion of ground photons. This embodiment of the present invention does not impose specific restrictions on the values ​​of the first through eighth thresholds, and users can configure them according to their actual needs.

[0090] For example, the screening scheme for elevation control points is as follows:

[0091] Step 1. Remove elevation outliers: Calculate the difference between the elevation of the target potential elevation control point (h_te_best_fit) and its reference elevation (dem_h), and remove outliers with an absolute value greater than 50m.

[0092] Step 2. Eliminate potential elevation control points affected by clouds: Based on the cloud coverage reflected by the cloud_flag_atm flag, eliminate ground points with cloud_flag_atm greater than 2 to prevent high-density clouds or misclassified points from interfering with the accuracy of terrain extraction.

[0093] Step 3. Remove Water Interference: In water areas, laser echoes are primarily specular, resulting in minimal pulse expansion and energy loss. The instrument will detect multiple surface echoes, concentrating the received photon signals at lower elevations, thus affecting the accuracy of terrain extraction. Therefore, this embodiment of the present invention removes potential elevation control points with the surface type identifier segment_landcover = 80 (water) to reduce the influence of the water surface.

[0094] Step 4. Eliminate ground reflection, solar radiation, and atmospheric influences: Use the number of ground photon points (n_te_photons), the total number of photon points (n_seg_ph), and the ratio of ground photon points to signal photon number (te_radio) to screen and retain potential elevation control points that meet the following conditions:

[0095] ①n_te_photons>40. Based on this condition to ensure sufficient ground photon signals, the target potential elevation control points whose number of ground photon points in the 100-meter segment is less than or equal to the fourth threshold are eliminated as described above.

[0096] ②n_seg_ph<500, based on this condition, the abnormally high-density photon areas are removed, which corresponds to the removal of the target potential elevation control points whose total photon points in the 100-meter segment are greater than or equal to the fifth threshold in the above text.

[0097] ③te_radio>0.5, based on this condition to ensure the effective surface photon ratio, where, , Indicates the number of ground photon points contained in the 100m segment, Indicates the number of canopy photon points contained in the 100m segment, represents the number of photons at the top of the canopy contained in the 100m segment. This inequality corresponds to the above-mentioned elimination of target potential elevation control points whose ground photon point ratio within the 100m segment is less than or equal to the sixth threshold.

[0098] Step 5. Eliminate potential elevation control points with large vertical geolocation errors: The point discrete distribution flag psf_flag indicates the total vertical geolocation error caused by ranging error and local terrain slope. psf_flag has two values: 0 and 1, which respectively indicate that the total vertical geolocation error of the potential elevation control point is less than or equal to 1 and greater than 1. This embodiment of the present invention eliminates potential elevation control points with psf_flag=1 to improve the accuracy of elevation control points.

[0099] Step 6. Identify and eliminate potential elevation control points with uneven ground photon distribution or large surface fitting errors: The ground photon distribution identifier subset_te_flag reflects the source of the original ground photons used to calculate the 100-meter segment statistics. The values ​​of subset_te_flag -1, 0, and 1 respectively indicate that each 20-meter ATL03 segment has no photon points, no ground photon points, and contains ground photon points. If the sum of subset_te_flag is 5, it means that all five 20-meter ATL03 segments contain ground photon points, ensuring the spatial uniformity of the data and reducing the impact of uneven photon distribution or surface fitting errors. This embodiment of the present invention only retains potential elevation control points with a subset_te_flag sum equal to 5.

[0100] Step 7. Eliminate potential elevation control points affected by multiple scattering, complex terrain and low vegetation: and Further screen potential elevation control points, remove abnormal points with large vertical dispersion, and retain potential elevation control points that meet the following conditions:

[0101] ① , which corresponds to the above-mentioned elimination of target potential elevation control points whose ground photon vertical concentration in the 100-meter segment is less than the seventh threshold.

[0102] ② , corresponding to the above elimination of the target potential elevation control points whose absolute value of the skewness of the elevation frequency histogram of the 100-meter segment is greater than the eighth threshold.

[0103] In summary, the present invention combines the two data products ATL03 and ATL08, comprehensively considers the influence of factors such as laser characteristics, clouds, water bodies, ground reflection, solar radiation, atmosphere and vertical concentration of ground photons on the elevation accuracy of potential elevation control points, and proposes the above-mentioned multiple screening strategy for high-precision elevation control points, which can effectively improve the extraction accuracy of elevation control points, enhance the reliability of data, and provide technical support for global elevation control point extraction and fine terrain mapping.

[0104] To verify the functionality of the method provided by the embodiments of the present invention, the following experiment was conducted. Given that the accuracy requirements for elevation control points vary between flat, hilly, and mountainous areas (0.5m, 0.7m, and 1.5m, respectively), potential elevation control points were divided into flat (slope < 2°), hilly (2° ≤ slope < 6°), and mountainous (6° ≤ slope < 25°) areas based on terrain slope before the experiment began. The accuracy of these areas was then verified in each region.

[0105] The accuracy of the elevation control points extracted by the present invention was verified using the DEM product extracted from airborne lidar data. Figure 2 is the frequency distribution histogram of the ground elevation error between the original data and the elevation control points in the flat area. Figure 3 is the frequency distribution histogram of the ground elevation error between the original data and the elevation control points in the hilly area. Figure 4 It is the frequency distribution histogram of the ground elevation error between the original data and the elevation control points in the mountainous area. Figures 2 to 4 The results show that through the screening of elevation control points, the proportion of potential elevation control points within the low error range has increased significantly, while the proportion of potential elevation control points with high errors has decreased significantly, especially in hilly and mountainous areas.

[0106] Figure 5 The comparison results of the ATL08 original data, the elevation control point accuracy verification without adding the new parameters (ground photon vertical concentration and skewness), and the elevation control point accuracy verification with the new parameters added are shown. Figure 5As can be seen, in the plain, hilly, and mountainous areas, the proportion of ground points meeting the accuracy requirements in the original data was only 83.92%, 68.54%, and 48.5%, respectively; the corresponding elevation error RMSEs were 1.69m, 3.35m, and 6m, respectively, all exceeding the required accuracy for elevation control points. After filtering through steps 1-6 of the above screening scheme, the proportion of potential elevation control points meeting the accuracy requirements increased to 93.5%, 92.88%, and 94.23%, respectively; and the elevation error RMSEs decreased to 0.3m, 0.43m, and 0.81m, respectively. After adding the new parameters (step 7), the proportion of potential elevation control points meeting the accuracy requirements further increased to 94.47%, 96.44%, and 97.01%, and the elevation error RMSEs decreased to 0.27m, 0.33m, and 0.56m. The results show that the elevation control point screening method provided by the embodiment of the present invention can significantly improve the extraction accuracy of elevation control points and effectively eliminate potential elevation control points that do not meet the accuracy requirements. The addition of new parameters further improves the accuracy, especially in mountainous areas.

[0107] Furthermore, the results are compared with the elevation control point screening scheme proposed by Li et al. (2021) (Li, B; Xie H; Tong X; Tang H; Wang X. A method of extracting high-accuracy elevation control pointsfrom ICESat-2 altimetry data. Photogrammetric Engineering&Remote Sensing. 2021, 87(11)11: 821-830). Figure 6 Compared with the method of Li et al. (2021), the embodiment of the present invention effectively eliminates potential elevation control points with large elevation dispersion by adding new screening parameters (ground photon vertical concentration and skewness). In flat, hilly, and mountainous areas, the proportion of elevation control points that meet the accuracy requirements increases by 1.05%, 2.95%, and 2.67%, respectively, and the RMSE error decreases by 0.04m, 0.09m, and 0.21m, respectively.

[0108] Example 2

[0109] An embodiment of the present invention further provides a device for screening elevation control points based on ICESat-2 data. The device is primarily used to execute the method for screening elevation control points based on ICESat-2 data provided in the first embodiment. The device for screening elevation control points based on ICESat-2 data provided in an embodiment of the present invention is described in detail below.

[0110] Figure 7A functional module diagram of a device for screening elevation control points based on ICESat-2 data provided by an embodiment of the present invention is shown in FIG. Figure 7 As shown, the device mainly includes: an extraction module 10, a conversion module 20, a calculation module 30, and a screening module 40, wherein:

[0111] The extraction module 10 is used to combine the ATL03 data product and the ATL08 data product of ICESat-2 to extract all original ground photon points from the ATL03 data product.

[0112] The conversion module 20 is used to convert all original ground photon points in each 100-meter segment of the ATL03 data product to a horizontal reference plane, with each 100-meter segment of the ATL08 data product along the track as a unit, to obtain all ground photon points in each 100-meter segment after removing the terrain.

[0113] The calculation module 30 is used to construct an elevation frequency histogram for each 100-meter segment based on all ground photon points after removing the terrain in each 100-meter segment, and calculate the skewness of the elevation frequency histogram and the vertical concentration of ground photons in each 100-meter segment; wherein the horizontal axis of the elevation frequency histogram represents the elevation interval, and the vertical axis represents the proportion of the number of ground photon points falling into the elevation interval to the total number of ground photon points in the 100-meter segment to which it belongs; the vertical concentration of ground photons represents the ratio of the peak of the elevation frequency histogram to the standard deviation of the height of the ground photon points in the 100-meter segment.

[0114] The screening module 40 is used to screen the potential elevation control points in the ATL08 data product based on the attribute parameters of each potential elevation control point in the ATL08 data product, the vertical concentration of ground photons in the 100-meter segment to which it belongs, and the skewness of the corresponding elevation frequency histogram, to obtain the elevation control point screening results; wherein the potential elevation control point represents the ATL08 ground photon point used for elevation control screening.

[0115] An embodiment of the present invention provides a device for screening elevation control points based on ICESat-2 data. First, the ATL03 data product and the ATL08 data product of ICESat-2 are combined to extract all original ground photon points from the ATL03 data product. Then, based on each 100-meter segment of the ATL08 data product along the track, all original ground photon points in each 100-meter segment of the ATL03 data product are converted to a horizontal reference plane to obtain all ground photon points in each 100-meter segment after removing the terrain. Then, an elevation frequency histogram that can accurately reflect the photon concentration is constructed for each 100-meter segment, and the skewness of the elevation frequency histogram and the ground photon vertical concentration of each 100-meter segment are calculated. Finally, based on the attribute parameters of each potential elevation control point in the ATL08 data product, the ground photon vertical concentration of the 100-meter segment to which it belongs, and the skewness of the corresponding elevation frequency histogram, potential elevation control points in the ATL08 data product are screened to obtain an elevation control point screening result. The embodiment of the present invention proposes two new parameters for screening elevation control points by combining the ATL03 and ATL08 data products: ground photon vertical concentration and skewness. Compared with screening using only the ATL08 parameters, the extraction accuracy of elevation control points can be effectively improved, providing technical support for global elevation control point extraction and fine terrain mapping.

[0116] Optionally, the extraction module 10 is specifically configured to:

[0117] Extract the attribute parameters of each photon point in ATL03 data products and ATL08 data products.

[0118] The ATL03 data product and the ATL08 data product are spatially matched based on attribute parameters.

[0119] The classification information of the target photon point in the ATL08 data product is used as the classification label of the photon point in the ATL03 data product that matches its space; wherein the target photon point represents any photon point among all the photon points in the ATL08 data product.

[0120] Based on the classification labels of all photon points in the ATL03 data product, all original ground photon points are determined.

[0121] Optionally, the conversion module 20 includes:

[0122] The acquisition unit is used to obtain the along-track distance and elevation value of each original ground photon point within the target 100-meter segment in the ATL03 data product; wherein the target 100-meter segment represents any segment of all 100-meter segments in the ATL03 data product.

[0123] The fitting unit is used to fit the along-track distance and elevation value of the original ground photon point within the target 100-meter segment to obtain the terrain slope of the target 100-meter segment.

[0124] Construction unit for constructing a two-dimensional rotation matrix based on the terrain slope.

[0125] The conversion unit is used to convert each original ground photon point within the 100-meter segment of the target to a horizontal reference plane based on a two-dimensional rotation matrix to obtain the corresponding ground photon point after removing the terrain.

[0126] Optionally, the fitting unit is specifically configured to:

[0127] Construct a univariate linear regression equation of the elevation and along-track distance of the original ground photon point; wherein, the elevation of the original ground photon point is the dependent variable of the univariate linear regression equation, the along-track distance of the original ground photon point is the independent variable of the univariate linear regression equation, and the terrain slope of the segment to which the original ground photon point belongs is the slope of the univariate linear regression equation.

[0128] Substitute the along-track distance and elevation values ​​of the original ground photon points within the target 100-meter segment into the univariate linear regression equation to obtain the target equation group.

[0129] The least square method is used to solve the target equations and obtain the terrain slope of the target 100-meter segment.

[0130] Optionally, the calculation module 30 is specifically configured to:

[0131] All ground photon points after removing terrain within the target 100-meter segment are grouped at preset elevation intervals, and the number of ground photon points falling into each elevation interval is counted; the target 100-meter segment represents any segment of all 100-meter segments in the ATL03 data product.

[0132] With the elevation interval as the horizontal axis and the ratio of the number of ground photon points falling into the elevation interval to the total number of ground photon points in the 100m segment to which it belongs as the vertical axis, an elevation frequency histogram of the target 100-meter segment is constructed.

[0133] Identify the peaks of the elevation frequency histogram for the target 100-meter segment.

[0134] Calculate the standard deviation of the height of all ground photon points after removing the terrain within the target 100-meter segment.

[0135] The skewness of the elevation frequency histogram of the target 100-meter segment is calculated based on the height standard deviation and the elevation of all ground photon points within the target 100-meter segment after removing the terrain.

[0136] The ratio of the peak value to the height standard deviation is calculated and the ratio result is used as the vertical concentration of ground photons in the target 100-meter segment.

[0137] Optionally, the screening module 40 is specifically configured to:

[0138] Calculate the difference between the elevation of a target potential elevation control point and its reference elevation; where the target potential elevation control point represents any potential elevation control point in the ATL08 data product.

[0139] If it is determined that the target potential elevation control point meets any of the following preset conditions, the target potential elevation control point is eliminated.

[0140] Among them, the preset conditions include: the absolute value of the difference is greater than the first threshold, the cloud cover identifier is greater than the second threshold, the surface type identifier is equal to the third threshold, the number of ground photon points in the 100-meter segment is less than or equal to the fourth threshold, the total number of photon points in the 100-meter segment is greater than or equal to the fifth threshold, the proportion of ground photon points in the 100-meter segment is less than or equal to the sixth threshold, the point discrete distribution identifier is equal to 1, the sum of the ground photon distribution identifiers of the 100-meter segment is not equal to 5, the vertical concentration of ground photons in the 100-meter segment is less than the seventh threshold, and the absolute value of the skewness of the elevation frequency histogram of the 100-meter segment is greater than the eighth threshold.

[0141] Example 3

[0142] See also Figure 8 An embodiment of the present invention provides an electronic device, which includes: a processor 60, a memory 61, a bus 62 and a communication interface 63, wherein the processor 60, the communication interface 63 and the memory 61 are connected via the bus 62; the processor 60 is used to execute an executable module stored in the memory 61, such as a computer program.

[0143] Memory 61 may include high-speed random access memory (RAM) and may also include non-volatile memory, such as at least one disk drive. Communication between the system network element and at least one other network element is achieved via at least one communication interface 63 (which may be wired or wireless), and may utilize the Internet, a wide area network, a local area network, a metropolitan area network, or the like.

[0144] The bus 62 may be an ISA bus, a PCI bus, or an EISA bus. The bus may be divided into an address bus, a data bus, a control bus, and the like. For ease of representation, Figure 8 Only one bidirectional arrow is used in the diagram, but this does not mean that there is only one bus or one type of bus.

[0145] Among them, the memory 61 is used to store programs, and the processor 60 executes the program after receiving the execution instruction. The method executed by the device defined by the process disclosed in any embodiment of the above-mentioned embodiment of the present invention can be applied to the processor 60 or implemented by the processor 60.

[0146] The processor 60 may be an integrated circuit chip with signal processing capabilities. During implementation, the steps of the above method may be performed by hardware integrated logic circuits or software instructions within the processor 60. The processor 60 may be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it may also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. It may implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of the present invention. The general-purpose processor may be a microprocessor or any conventional processor. The steps of the methods disclosed in the embodiments of the present invention may be directly executed by a hardware decoding processor or by a combination of hardware and software modules within the decoding processor. The software modules may be located in storage media well-known in the art, such as random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, or the like. The storage medium is located in the memory 61 , and the processor 60 reads the information in the memory 61 and completes the steps of the above method in combination with its hardware.

[0147] Embodiments of the present invention provide a computer program product for a method and apparatus for screening elevation control points based on ICESat-2 data, including a computer-readable storage medium storing non-volatile program code executable by a processor. The program code includes instructions that can be used to execute the methods described in the preceding method embodiments. For specific implementations, please refer to the method embodiments and will not be described in detail here.

[0148] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0149] If the functions are implemented as software functional units and sold or used as independent products, they can be stored in a processor-executable, non-volatile, computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the portion that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods described in various embodiments of the present invention. The aforementioned storage media include various media capable of storing program code, such as USB flash drives, mobile hard drives, read-only memories (ROMs), random access memories (RAMs), magnetic disks, or optical disks.

[0150] It should be noted that similar reference numerals and letters denote similar items in the following drawings, and therefore, once an item is defined in one drawing, it does not need to be further defined or explained in subsequent drawings.

[0151] In the description of the present invention, it should be noted that the terms "center," "upper," "lower," "left," "right," "vertical," "horizontal," "inner," and "outer" and the like indicate positions or locations based on the positions shown in the accompanying drawings, or the positions or locations in which the inventive product is typically placed when in use. These terms are intended solely to facilitate the description of the present invention and to simplify the description, and are not intended to indicate or imply that the devices or components referred to must have a specific orientation, be constructed, or operate in a specific orientation. Therefore, they should not be construed as limitations on the present invention. Furthermore, the terms "first," "second," and "third," etc., are used solely to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0152] Furthermore, terms such as "horizontal," "vertical," and "overhanging" do not necessarily imply that a component must be absolutely horizontal or overhanging, but rather that it can be slightly tilted. For example, "horizontal" simply means that its direction is more horizontal than "vertical," and does not mean that the structure must be completely horizontal, but rather that it can be slightly tilted.

[0153] In the description of the present invention, it should also be noted that, unless otherwise expressly specified or limited, the terms "disposed," "installed," "connected," and "connected" should be understood in a broad sense. For example, they may refer to fixed connections, detachable connections, or integral connections; they may refer to mechanical connections or electrical connections; they may refer to direct connections or indirect connections through an intermediate medium; and they may refer to internal communication between two components. Those skilled in the art will understand the specific meanings of the above terms in the present invention based on the specific circumstances.

[0154] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the above embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for screening elevation control points based on ICESat-2 data, characterized in that: include: Combine ICESat-2's ATL03 data product and ATL08 data product to extract all raw ground photon points from the ATL03 data product; Taking each 100-meter segment of the ATL08 data product along the track as a unit, all original ground photon points in each 100-meter segment of the ATL03 data product are converted to a horizontal reference plane to obtain all ground photon points in each 100-meter segment after removing the terrain; Based on all ground photon points after removing the terrain in each 100-meter segment, an elevation frequency histogram of each 100-meter segment is constructed, and the skewness of the elevation frequency histogram and the vertical concentration of ground photons in each 100-meter segment are calculated; wherein the horizontal axis of the elevation frequency histogram represents the elevation interval, and the vertical axis represents the proportion of the number of ground photon points falling into the elevation interval to the total number of ground photon points in the 100-meter segment to which it belongs; the vertical concentration of ground photons represents the ratio of the peak of the elevation frequency histogram to the height standard deviation of the ground photon points in the 100-meter segment; Based on the attribute parameters of each potential elevation control point in the ATL08 data product, the ground photon vertical concentration of the 100-meter segment to which it belongs, and the skewness of the corresponding elevation frequency histogram, the potential elevation control points in the ATL08 data product are screened to obtain elevation control point screening results; wherein the potential elevation control points represent ATL08 ground photon points used for elevation control screening; Among them, based on all ground photon points after removing the terrain in each 100-meter segment, an elevation frequency histogram of each 100-meter segment is constructed, and the skewness of the elevation frequency histogram and the vertical concentration of ground photons in each 100-meter segment are calculated, including: Group all ground photon points after removing terrain within a target 100-meter segment at preset elevation intervals, and count the number of ground photon points falling into each elevation interval; wherein the target 100-meter segment represents any segment among all 100-meter segments in the ATL03 data product; With the elevation interval as the horizontal axis and the ratio of the number of ground photon points falling into the elevation interval to the total number of ground photon points in the 100m segment to which it belongs as the vertical axis, an elevation frequency histogram of the target 100m segment is constructed; Determining the peak of the elevation frequency histogram of the target 100-meter segment; Calculate the standard deviation of the heights of all ground photon points within the 100-meter segment of the target after removing the terrain; Calculating the skewness of the elevation frequency histogram of the target 100-meter segment based on the height standard deviation and the elevations of all ground photon points within the target 100-meter segment after removing the terrain; The ratio of the peak value to the height standard deviation is calculated, and the ratio result is used as the ground photon vertical concentration of the target 100-meter segment.

2. The method for screening elevation control points based on ICESat-2 data according to claim 1, wherein: Combine ICESat-2's ATL03 data product with the ATL08 data product to extract all raw ground photon points from the ATL03 data product, including: Extracting attribute parameters of each photon point in the ATL03 data product and the ATL08 data product; spatially matching the ATL03 data product and the ATL08 data product based on the attribute parameters; Using the classification information of the target photon point in the ATL08 data product as the classification label of the photon point spatially matched with it in the ATL03 data product; wherein the target photon point represents any photon point among all the photon points in the ATL08 data product; Based on the classification labels of all photon points in the ATL03 data product, all original ground photon points are determined.

3. The method for screening elevation control points based on ICESat-2 data according to claim 1, wherein: Taking the ATL08 data product as a unit of each 100-meter segment in the along-track direction, all original ground photon points in each 100-meter segment of the ATL03 data product are converted to a horizontal reference plane, including: Obtaining the along-track distance and elevation value of each original ground photon point within a target 100-meter segment in the ATL03 data product; wherein the target 100-meter segment represents any segment among all 100-meter segments in the ATL03 data product; Fitting the along-track distance and elevation value of the original ground photon point within the target 100-meter segment to obtain the terrain slope of the target 100-meter segment; constructing a two-dimensional rotation matrix based on the terrain slope; Based on the two-dimensional rotation matrix, each original ground photon point within the 100-meter segment of the target is converted to a horizontal reference plane to obtain a corresponding ground photon point after removing the terrain.

4. The method for screening elevation control points based on ICESat-2 data according to claim 3, wherein: Fitting the along-track distance and elevation value of the original ground photon point within the target 100-meter segment to obtain the terrain slope of the target 100-meter segment includes: Constructing a univariate linear regression equation for the elevation and along-track distance of the original ground photon point; wherein the elevation of the original ground photon point is the dependent variable of the univariate linear regression equation, the along-track distance of the original ground photon point is the independent variable of the univariate linear regression equation, and the terrain slope of the segment to which the original ground photon point belongs is the slope of the univariate linear regression equation; Substituting the along-track distance and elevation value of the original ground photon point within the target 100-meter segment into the univariate linear regression equation to obtain a target equation group; The target equation group is solved using the least squares method to obtain the terrain slope of the target 100-meter segment.

5. The method for screening elevation control points based on ICESat-2 data according to claim 1, wherein: Based on the attribute parameters of each potential elevation control point in the ATL08 data product, the vertical concentration of ground photons in the 100-meter segment to which it belongs, and the skewness of the corresponding elevation frequency histogram, the potential elevation control points in the ATL08 data product are screened, including: Calculating the difference between the elevation of a target potential elevation control point and its reference elevation; wherein the target potential elevation control point represents any potential elevation control point in the ATL08 data product; When it is determined that the target potential elevation control point meets any of the following preset conditions, the target potential elevation control point is eliminated; Among them, the preset conditions include: the absolute value of the difference is greater than the first threshold, the cloud cover identifier is greater than the second threshold, the surface type identifier is equal to the third threshold, the number of ground photon points in the 100-meter segment is less than or equal to the fourth threshold, the total number of photon points in the 100-meter segment is greater than or equal to the fifth threshold, the proportion of ground photon points in the 100-meter segment is less than or equal to the sixth threshold, the point discrete distribution identifier is equal to 1, the sum of the ground photon distribution identifiers of the 100-meter segment is not equal to 5, the vertical concentration of ground photons in the 100-meter segment is less than the seventh threshold, and the absolute value of the skewness of the elevation frequency histogram of the 100-meter segment is greater than the eighth threshold.

6. A device for screening elevation control points based on ICESat-2 data, characterized in that: include: an extraction module for combining the ATL03 data product and the ATL08 data product of ICESat-2 to extract all raw ground photon points from the ATL03 data product; A conversion module is used to convert all original ground photon points in each 100-meter segment of the ATL03 data product to a horizontal reference plane, taking each 100-meter segment of the ATL08 data product in the along-track direction as a unit, to obtain all ground photon points in each 100-meter segment after removing the terrain; A calculation module is used to construct an elevation frequency histogram for each 100-meter segment based on all ground photon points after terrain removal in each 100-meter segment, and calculate the skewness of the elevation frequency histogram and the vertical concentration of ground photons in each 100-meter segment; wherein the horizontal axis of the elevation frequency histogram represents the elevation interval, and the vertical axis represents the proportion of the number of ground photon points falling into the elevation interval to the total number of ground photon points in the 100-meter segment to which it belongs; the vertical concentration of ground photons represents the ratio of the peak of the elevation frequency histogram to the height standard deviation of the ground photon points in the 100-meter segment; a screening module for screening potential elevation control points in the ATL08 data product based on attribute parameters of each potential elevation control point in the ATL08 data product, the vertical concentration of ground photons in the 100-meter segment to which the potential elevation control point belongs, and the skewness of the corresponding elevation frequency histogram, to obtain elevation control point screening results; wherein the potential elevation control point represents an ATL08 ground photon point used for elevation control screening; The calculation module is specifically used for: Group all ground photon points after removing terrain within a target 100-meter segment at preset elevation intervals, and count the number of ground photon points falling into each elevation interval; wherein the target 100-meter segment represents any segment among all 100-meter segments in the ATL03 data product; With the elevation interval as the horizontal axis and the ratio of the number of ground photon points falling into the elevation interval to the total number of ground photon points in the 100m segment to which it belongs as the vertical axis, an elevation frequency histogram of the target 100m segment is constructed; Determining the peak of the elevation frequency histogram of the target 100-meter segment; Calculate the standard deviation of the heights of all ground photon points within the 100-meter segment of the target after removing the terrain; Calculating the skewness of the elevation frequency histogram of the target 100-meter segment based on the height standard deviation and the elevations of all ground photon points within the target 100-meter segment after removing the terrain; The ratio of the peak value to the height standard deviation is calculated, and the ratio result is used as the ground photon vertical concentration of the target 100-meter segment.

7. The device for screening elevation control points based on ICESat-2 data according to claim 6, characterized in that: The extraction module is specifically used for: Extracting attribute parameters of each photon point in the ATL03 data product and the ATL08 data product; spatially matching the ATL03 data product and the ATL08 data product based on the attribute parameters; Using the classification information of the target photon point in the ATL08 data product as the classification label of the photon point spatially matched with it in the ATL03 data product; wherein the target photon point represents any photon point among all the photon points in the ATL08 data product; Based on the classification labels of all photon points in the ATL03 data product, all original ground photon points are determined.

8. An electronic device comprising a memory and a processor, wherein the memory stores a computer program that can be run on the processor, wherein: When the processor executes the computer program, the method for screening elevation control points based on ICESat-2 data according to any one of claims 1 to 5 is implemented.

9. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer instructions, and when the computer instructions are executed by a processor, the method for screening elevation control points based on ICESat-2 data according to any one of claims 1 to 5 is implemented.

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