A digital riverbed reconstruction method, device and medium based on DEM

Abstract

The present application discloses a method, device and medium for digital riverbed reconstruction based on DEM, the method comprising: performing inverse distance weighted spatial interpolation processing on river surface vector data to determine riverbed DEM interpolation data; smoothing the riverbed DEM interpolation data by weighted average method to obtain smoothed riverbed DEM data; fusing and reconstructing the smoothed riverbed DEM data with preset original DEM data, and performing hydrological analysis on the fused and reconstructed data to determine hydrological analysis data; performing centerline elevation simulation on the hydrological analysis data to obtain vertical elevation distribution data of the river centerline data; and determining the spatial position construction function corresponding to the vertical elevation distribution data based on the preset riverbed morphology category. The present application solves the technical problems of inaccurate river channel terrain description, low elevation simulation accuracy and low efficiency of unknown river channel elevation analysis through the above method.

Description

Technical Field

[0001] The present application relates to the technical field, and in particular to a method, device and medium for digital riverbed reconstruction based on DEM. Background Art

[0002] With the rapid development of geographic information technology and digital elevation models (DEM), digital riverbed terrain reconstruction plays an increasingly important role in water conservancy projects, river ecological research, water disaster warning and other fields. Through high-precision digital riverbed terrain models, river hydrological processes can be simulated more accurately, providing a scientific basis for river management and planning. Digital elevation models (DEM) are digital expressions of surface morphology. Commonly used raster DEM data has the advantages of simple structure and easy processing, and is widely used in the field of hydrological simulation.

[0003] The existing two-dimensional distributed simulation solves the problem of differences in cross-section settings, but at the same time, it also places higher requirements on data accuracy. In addition, for the method of constructing underwater terrain based on measured cross-section or scattered data spatial interpolation, there are technical problems such as inaccurate description of river terrain, low accuracy of elevation simulation, and low efficiency of unknown river elevation analysis. Summary of the invention

[0004] The embodiments of the present application provide a DEM-based digital riverbed reconstruction method, device and medium, which solve the technical problems in the prior art of inaccurate river terrain description, low elevation simulation accuracy and low efficiency of unknown river elevation analysis.

[0005] In the first aspect, an embodiment of the present application provides a digital riverbed reconstruction method based on DEM, characterized in that the method includes: performing inverse distance weighted spatial interpolation processing on river surface vector data to determine riverbed DEM interpolation data; smoothing the riverbed DEM interpolation data by weighted averaging method to obtain smoothed riverbed DEM data; fusing and reconstructing the smoothed riverbed DEM data with preset original DEM data, and performing hydrological analysis on the fused and reconstructed data to determine hydrological analysis data; wherein the hydrological analysis data includes: river flow direction data, sub-basin boundary data, river network threshold data, river centerline data; performing centerline elevation simulation on the hydrological analysis data to obtain vertical elevation distribution data of the river centerline data; and determining the spatial position construction function corresponding to the vertical elevation distribution data based on a preset riverbed morphology category.

[0006] In one implementation of the present application, the river surface vector data is subjected to inverse distance weighted spatial interpolation processing to determine the riverbed DEM interpolation data, specifically including: converting the river surface vector file through a preset spatial analysis tool to obtain river surface mask data; performing curvature judgment on the preset river network data to determine the river network curvature radius data of the river network data, and based on the river network curvature radius data, determining the interpolation moving window radius corresponding to the river network curvature radius data; based on the interpolation moving window radius, determining the interpolation range covering the river surface mask data by extending the interpolation width; according to the interpolation range, performing inverse distance weighted spatial interpolation processing on the river surface mask data to determine the riverbed DEM interpolation data.

[0007] In one implementation of the present application, the riverbed DEM interpolation data is smoothed by a weighted averaging method to obtain smoothed riverbed DEM data, specifically including: obtaining window data of the riverbed DEM interpolation data, and determining the minimum unit window center point of the window data; determining the points to be weighted of the minimum unit window according to the minimum unit window center point; wherein the points to be weighted include: the minimum unit window center point, the border points of the minimum unit window, and the four corner points of the minimum unit window; and smoothing the points to be weighted by a weighted averaging method to obtain smoothed riverbed DEM data.

[0008] In one implementation of the present application, a centerline elevation simulation is performed on the hydrological analysis data to obtain the vertical elevation distribution data of the river centerline data, specifically including: obtaining the hydrological analysis data, and determining the vertical direction data of the river flow direction data based on the hydrological analysis data; taking the center grid of the river flow direction as the starting point, extending according to the vertical direction data to determine the river elevation data to be processed; wherein the river elevation data to be processed includes: elevation points on both sides of the river channel and constraint points of the corresponding elevations of the river centerline data; linearly extending the processed river elevation data in a preset bilateral vertical direction to determine the vertical direction data.

[0009] In one implementation of the present application, based on a preset riverbed morphology category, a spatial position construction function corresponding to the vertical elevation distribution data is determined, specifically including: segmenting the preset riverbed data according to the riverbed morphology category to obtain segmented riverbed morphology category data; wherein the riverbed morphology categories include: V-type, U-type, and flat-bottom type; and matching the spatial position construction function corresponding to the vertical elevation distribution data according to the segmented riverbed morphology category data.

[0010] In one implementation of the present application, after matching the spatial position construction function corresponding to the vertical elevation distribution data according to the segmented riverbed morphology category data, the method also includes: processing the vertical elevation distribution data through the spatial position construction function to determine the riverbed elevation data; and reconstructing the riverbed elevation data through riverbed elevation fusion to determine the digital riverbed terrain data.

[0011] In one implementation of the present application, riverbed elevation data is reconstructed through riverbed elevation fusion to determine digital riverbed terrain data, specifically including: performing DEM preprocessing on the riverbed elevation data to obtain elevation data to be fused; performing raster differentiation on the elevation data to be fused to determine riverbed raster data; and fusing the riverbed raster data into preset initial elevation data through a preset elevation reconstruction method to determine digital riverbed terrain data.

[0012] In one implementation of the present application, before performing inverse distance weighted spatial interpolation processing on the river surface vector data to determine the riverbed DEM interpolation data, the method also includes: determining the DEM resolution based on a preset river basin range; based on the DEM resolution, clipping the DEM through the river basin range to obtain river DEM data; based on the river DEM data, when the river surface vector data cannot be obtained through a preset extraction method, extracting the river surface vector data through slope extraction to determine the river surface vector data.

[0013] In a second aspect, an embodiment of the present application also provides a digital riverbed reconstruction device based on DEM, characterized in that the device includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can: perform inverse distance weighted spatial interpolation processing on the river surface vector data to determine the riverbed DEM interpolation data; smooth the riverbed DEM interpolation data by weighted averaging method to obtain the smoothed riverbed DEM data; fuse and reconstruct the smoothed riverbed DEM data with the preset original DEM data, and perform hydrological analysis on the fused and reconstructed data to determine the hydrological analysis data; wherein the hydrological analysis data includes: river flow direction data, sub-basin boundary data, river network threshold data, and river centerline data; perform centerline elevation simulation on the hydrological analysis data to obtain the vertical elevation distribution data of the river centerline data; and determine the spatial position construction function corresponding to the vertical elevation distribution data based on the preset riverbed morphology category.

[0014] In a third aspect, an embodiment of the present application also provides a non-volatile computer storage medium for a DEM-based digital riverbed reconstruction method, storing computer executable instructions, characterized in that the computer executable instructions are set to: perform inverse distance weighted spatial interpolation processing on river surface vector data to determine riverbed DEM interpolation data; smooth the riverbed DEM interpolation data by weighted averaging to obtain smoothed riverbed DEM data; fuse and reconstruct the smoothed riverbed DEM data with preset original DEM data, and perform hydrological analysis on the fused and reconstructed data to determine hydrological analysis data; wherein the hydrological analysis data includes: river flow direction data, sub-basin boundary data, river network threshold data, and river centerline data; perform centerline elevation simulation on the hydrological analysis data to obtain vertical elevation distribution data of the river centerline data; and determine the spatial position construction function corresponding to the vertical elevation distribution data based on a preset riverbed morphology category.

[0015] The embodiments of the present application provide a method, device and medium for digital riverbed reconstruction based on DEM, which fuses and reconstructs riverbed elevation data through inverse distance weighted spatial interpolation, solves the technical problems of inaccurate river channel topography description, low elevation simulation accuracy and low efficiency of unknown river channel elevation analysis, realizes the construction of river channel data in areas with no data, improves the accuracy of river channel topography description, and provides a data basis for subsequent unsteady flow simulation and inundation analysis. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0017] Figure 1 A flow chart of a digital riverbed reconstruction method based on DEM provided in an embodiment of the present application;

[0018] Figure 2 A schematic diagram of a weighted smoothing pixel selection range provided in an embodiment of the present application;

[0019] Figure 3 A schematic diagram of a river cross section provided in an embodiment of the present application;

[0020] Figure 4 A schematic diagram of the internal structure of a DEM-based digital riverbed reconstruction device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0021] In order to make the purpose, technical solution and advantages of the present application clearer, the technical solution of the present application will be clearly and completely described below in combination with the specific embodiments of the present application and the corresponding drawings. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present application.

[0022] The embodiments of the present application provide a method, device and medium for digital riverbed reconstruction based on DEM, which fuses and reconstructs riverbed elevation data through inverse distance weighted spatial interpolation, solves the technical problems of inaccurate river channel topography description, low elevation simulation accuracy and low efficiency of unknown river channel elevation analysis, realizes the construction of river channel data in areas with no data, improves the accuracy of river channel topography description, and provides a data basis for subsequent unsteady flow simulation and inundation analysis.

[0023] The technical solution proposed in the embodiments of the present application is described in detail below with reference to the accompanying drawings.

[0024] Figure 1 The following is a flow chart of a method for digital riverbed reconstruction based on DEM provided in the embodiment of the present application. Figure 1 As shown, a digital riverbed reconstruction method based on DEM provided in an embodiment of the present application specifically includes the following steps:

[0025] Step 101: Perform inverse distance weighted spatial interpolation processing on the river surface vector data to determine the riverbed DEM interpolation data.

[0026] Specifically, it includes: converting the river surface vector file through a preset spatial analysis tool to obtain river surface mask data; performing curvature judgment on the preset river network data to determine the river network curvature radius data of the river network data, and based on the river network curvature radius data, determining the interpolation moving window radius corresponding to the river network curvature radius data; based on the interpolation moving window radius, determining the interpolation range covering the river surface mask data by extending the interpolation width; according to the interpolation range, performing inverse distance weighted spatial interpolation processing on the river surface mask data to determine the riverbed DEM interpolation data.

[0027] Before performing inverse distance weighted spatial interpolation processing on the river surface vector data to determine the riverbed DEM interpolation data, the method also includes: determining the DEM resolution according to a preset river basin range; based on the DEM resolution, clipping the DEM by the river basin range to obtain river DEM data; based on the river DEM data, when the river surface vector data cannot be obtained by a preset extraction method, extracting the river surface vector data by slope extraction to determine the river surface vector data.

[0028] This application interpolates the river surface mask data through inverse distance weighted spatial interpolation processing, determines the river surface vector data, improves the accuracy of the river surface vector data, and provides a data basis for subsequent spatial interpolation operations.

[0029] In the embodiments of the present application, detailed explanation is given through the following Examples 1 and 2.

[0030] Example 1: First, you need to obtain relevant river data, including: river DEM data and river surface vector data.

[0031] With the rapid development of new surveying and mapping technologies, the continuous emergence of new technologies and methods, especially the widespread application of LiDAR and UAV surveying and mapping technologies, the accuracy of DEM has reached the centimeter level. The publicly released SRTM (Shuttle Radar Terrain Mission, SRTM) has a grid data resolution of 1″ (about 30m) in a large-scale low-resolution global area, covering a total area of ​​more than 80% of the earth's land surface between 60 degrees north latitude and 60 degrees south latitude. The latest 10-meter grid new generation digital elevation model has completed the construction of a three-dimensional model of about 6 million square kilometers of terrain that is better than the 5-meter grid. According to the river basin range, a DEM with a suitable resolution is selected, and the DEM is clipped with the basin range to obtain the DEM within the river basin range.

[0032] Then it is necessary to obtain the river surface vector data. For most rivers, there is usually archived data that can be used directly. For seasonal rivers, remote sensing images of the river during the flood season can be selected to extract river surface vector files through single-band threshold method, normalized difference vegetation index method (NDVI) and various water body extraction index methods.

[0033] In addition, when the above methods are unable to determine the river surface vector data, the DEM data is often generated by leveling the water area, and the slope (S), aspect (A), and slope variation rate (SOS) are extracted from the DEM in the river basin. For any point on the river surface, S=0, A=-1, and SOS=0, and the river surface vector data can be obtained through threshold segmentation.

[0034] Example 2: Inverse Distance Weighting (IDW) spatial interpolation method, the interpolation control range is controlled by the river mask file. The river mask file is converted into a raster file with a resolution of 1m to accurately describe the river surface information of about 3m at its narrowest point. The spatial analysis tool IDW in ArcGIS software is used to perform spatial interpolation on the river mask file.

[0035] The metadata of the first interpolation is the river network grid data. The value of the interpolation moving window radius must be less than the minimum value of the river network curvature radius. The interpolation process can be repeated to extend the interpolation width, but each repetition must use the previous interpolation result as metadata until the interpolation range covers the entire mask file range. The most basic theoretical assumption of spatial interpolation technology is that the closer the points in spatial position are, the more similar the features are, and the farther the points are, the less likely they are to have similar features. It is assumed that the elevation value of the unknown river surface elevation grid point is affected by the distance from the known elevation point position.

[0036] The IDW interpolation algorithm is expressed by the following formula (1):

[0037]

[0038] Among them, H Surface is the estimated river surface elevation;

[0039] H i is the known elevation value of the river;

[0040] ω i is the interpolation algorithm weight;

[0041] n is the number of pixels covered by the interpolation window.

[0042] It should be noted that the interpolation moving window radius is inversely proportional to the radius of curvature of the river network. Since the radius of curvature of a straight river is infinite, the interpolation result will not be affected by the size of the moving window radius. Therefore, a value greater than the half-width of the river surface can be taken, and the interpolation can be completed in one operation.

[0043] For non-straight rivers, the interpolation moving window radius needs to be controlled within the curvature radius of the river section to ensure the accuracy of data collection. If it exceeds the curvature radius of the river section, a large amount of non-river data will be collected, causing data pollution.

[0044] Step 102: Smoothing the riverbed DEM interpolation data by weighted averaging method to obtain smoothed riverbed DEM data.

[0045] Specifically, the method includes: obtaining window data of riverbed DEM interpolation data, and determining the center point of the minimum unit window of the window data; determining the points to be weighted of the minimum unit window according to the center point of the minimum unit window; wherein the points to be weighted include: the center point of the minimum unit window, the border points of the minimum unit window, and the four corner points of the minimum unit window; and smoothing the points to be weighted by the weighted average method to obtain the smoothed riverbed DEM data.

[0046] The present application realizes smoothing processing by performing nine-point weighted averaging on the interpolation moving window, thereby improving the stability and smoothness of the interpolation moving window value and realizing accurate processing of DEM interpolation data.

[0047] Figure 2 A schematic diagram of a weighted smoothed pixel selection range is provided for an embodiment of the present application. In the embodiment of the present application, a detailed explanation is given through the following Example 3.

[0048] Example 3: After spatial interpolation, take the terrain point as the center and take 8 points around it, and use the nine-point weighted average method to smooth it. The central grid of the nine grids is the center point of the minimum unit window; with the center point of the minimum unit window as the center, the four adjacent grids on the top, bottom, left and right are the border points of the minimum unit window; with the center point of the minimum unit window as the center, the four diagonal minimum unit windows are the four corner points of the minimum unit window.

[0049] The point weighted average method smoothing process is expressed by the following formula (2):

[0050]

[0051] in, Indicates the elevation after smoothing;

[0052] The Chinese characters in the subscripts are the location numbers of the topographic points;

[0053] Indicates the elevation before smoothing.

[0054] When the values ​​of the border points of the minimum unit window are 10, 11, 9, 9; and the values ​​of the four corner points of the minimum unit window are 11, 11, 9, 9, after smoothing by the nine-point weighted average method, the weighted value (dark center point) changes from 10 to 9.9. Similarly, smoothing can be performed on other windows, that is, selecting the window as the center point and determining the four corner points and border points around it.

[0055] Step 103: Fuse and reconstruct the smoothed riverbed DEM data with the preset original DEM data, and perform hydrological analysis on the fused and reconstructed data to determine the hydrological analysis data.

[0056] Among them, hydrological analysis data include: river flow direction data, sub-basin boundary data, river network threshold data, and river centerline data.

[0057] This application determines the river centerline data through river centerline fusion reconstruction, realizes the accurate extraction of river centerline data, and improves the stability and accuracy of the system.

[0058] In the examples of the present application, a detailed explanation is given by the following Example 4.

[0059] Example 4: The smoothed underwater terrain was fused and reconstructed with the original DEM. The Arc Hydro Tools software was used to extract the river centerline in the river basin based on the D8 algorithm, the steepest slope principle and the minimum catchment area threshold. The main processes included DEM preprocessing, water flow direction determination, confluence grid calculation, river network generation according to threshold value and sub-basin boundary division.

[0060] Step 104: Perform centerline elevation simulation on the hydrological analysis data to obtain vertical elevation distribution data of the river centerline data.

[0061] The centerline elevation simulation of the hydrological analysis data is performed to obtain the vertical elevation distribution data of the river centerline data, specifically including: obtaining the hydrological analysis data, and determining the vertical direction data of the river flow direction data based on the hydrological analysis data; taking the center grid of the river flow direction as the starting point, extending according to the vertical direction data to determine the river elevation data to be processed; the river elevation data to be processed includes: elevation points on both sides of the river channel and constraint points of the river centerline data corresponding to the elevation; linearly extending the processed river elevation data in a preset bilateral vertical direction to determine the vertical direction data.

[0062] Based on the preset riverbed morphology category, the spatial position construction function corresponding to the vertical elevation distribution data is determined, specifically including: dividing the preset riverbed data into segments according to the riverbed morphology category to obtain segmented riverbed morphology category data; wherein the riverbed morphology categories include: V-type, U-type, and flat-bottom type; according to the segmented riverbed morphology category data, matching the spatial position construction function corresponding to the vertical elevation distribution data.

[0063] After matching the spatial position construction function corresponding to the vertical elevation distribution data according to the segmented riverbed morphology category data, the method also includes: processing the vertical elevation distribution data through the spatial position construction function to determine the riverbed elevation data; and reconstructing the riverbed elevation data through riverbed elevation fusion to determine the digital riverbed terrain data.

[0064] The riverbed elevation data is reconstructed through riverbed elevation fusion to determine the digital riverbed terrain data, specifically including: performing DEM preprocessing on the riverbed elevation data to obtain the elevation data to be fused; performing raster differentiation on the elevation data to be fused to determine the riverbed raster data; and fusing the riverbed raster data into the preset initial elevation data through a preset elevation reconstruction method to determine the digital riverbed terrain data.

[0065] This application performs centerline elevation simulation on river centerline data to obtain vertical elevation distribution data of river centerline data, realizes elevation simulation of river centerline, improves elevation simulation accuracy and utilization rate of centerline grid, realizes elevation analysis of existing river channel and unknown river channel data, and improves system versatility.

[0066] Figure 3 A schematic diagram of a river cross section is provided for an embodiment of the present application, and in the embodiment of the present application, it is explained in detail through the following Example 5.

[0067] Example 5: Since the flow direction of a river changes tangentially with the centerline of the river curve, for the elevation value on the centerline of the river, the flow direction at the center grid (i.e., the tangent direction of the center line) is calculated based on the spatial position of the center grid and its adjacent grids, and the vertical direction of the flow direction is obtained.

[0068] The vertical line segments are generated from the center grid to both sides. The generated vertical line segments include the known elevation points on both sides of the river channel and the elevation constraint points on the center line of the river channel (i.e., the constraint points on the center line). The elevation of the elevation constraint points on the center line of the river channel is recalculated through the known elevation points on both sides of the river channel, which is expressed by the following formula (3):

[0069] H p =ω L H PL +ω R H PR (3);

[0070] Among them, H PL is the elevation on the left side of the center line;

[0071] H PR is the elevation on the right side of the center line;

[0072] ω L H PL The weight, ω R H Pr The weight of .

[0073] The calculation method is expressed by the following formula (4):

[0074]

[0075] Among them, or means "or", ω L or R That is ω L or R ;

[0076] Point L0 or R0 is the first known elevation point outside the range of the river mask file;

[0077] D L0orR0The distance to the first known elevation point on the left and right of the elevation constraint point in the vertical direction of the river flow at the center of the river channel;

[0078] D max It is the distance to the first known elevation point on the left and right in the vertical direction along the river flow direction.

[0079] Since the center grid is extended to the left and right (i.e., both sides of the river), the tangent on the center line is the straight line where the river direction is located, and the specific direction can be determined according to the flow conditions; then the left and right sides of the center line are extended to the river bank. It should be noted that the "left and right" here refers to the left and right sides with the river direction corresponding to the center line as the positive direction.

[0080] Take the left point L i Linear expansion to obtain the elevation H of point P Li It is expressed by the following formula (5):

[0081]

[0082] Among them, H L0 is the elevation of point L0;

[0083] D Li is the distance from the i-th known point on the left to point L0;

[0084] D P is the distance between point P and point L0;

[0085] D max is the maximum distance considered.

[0086] From L0 to the left, look for the left point L from near to far i In the case of interpolation calculation, L i The distance D from point P Li >D max , then L0 and L i The interpolation is still calculated normally, but the calculation no longer looks for points outward.

[0087] D max The value is the distance (i.e. the width of the water surface) between L0 and R0 (i.e. the intersection of the water surface and the right bank on the left and right sides where L0 and R0 are located in the figure).

[0088] After determining the centerline elevation, it is necessary to determine H Li The initial weight is expressed by the following formula (6):

[0089]

[0090] in, H Li Initial weight

[0091] The weights are normalized and expressed by the following formula (7):

[0092]

[0093] ω Li The calculation method of is expressed by the following formula (8):

[0094]

[0095] Through weighted calculation, the elevation of point P is reconstructed with L0 as the anchor point to obtain the reconstructed elevation of point P H PL , expressed by the following formula (9):

[0096]

[0097] Similarly, for the right point R i Linear expansion to obtain the elevation H of point P Ri The process is similar to the left side. You only need to search for the right point R from near to far from R0. i The calculation method is the same as above. It should be noted that in order to distinguish the left and right directions in the calculation of determining the elevation, the subscript L represents the left direction; similarly, for the right point R i Linear expansion to obtain the elevation H of point P Ri In the process, the subscript R represents the right direction, and the rest are consistent.

[0098] Step 105: Based on the preset riverbed morphology category, determine the spatial position construction function corresponding to the vertical elevation distribution data.

[0099] Specifically, the method includes: dividing the preset riverbed data into sections according to the riverbed morphology categories to obtain the sectioned riverbed morphology category data; wherein the riverbed morphology categories include: V-type, U-type, and flat-bottom type; and constructing a function by matching the spatial position corresponding to the vertical elevation distribution data according to the sectioned riverbed morphology category data.

[0100] After matching the spatial position construction function corresponding to the vertical elevation distribution data according to the segmented riverbed morphology category data, the method also includes: processing the vertical elevation distribution data through the spatial position construction function to determine the riverbed elevation data; and reconstructing the riverbed elevation data through riverbed elevation fusion to determine the digital riverbed terrain data.

[0101] The riverbed elevation data is reconstructed through riverbed elevation fusion to determine the digital riverbed terrain data, specifically including: performing DEM preprocessing on the riverbed elevation data to obtain the elevation data to be fused; performing raster differentiation on the elevation data to be fused to determine the riverbed raster data; and fusing the riverbed raster data into the preset initial elevation data through a preset elevation reconstruction method to determine the digital riverbed terrain data.

[0102] This application classifies the terrain conditions of the riverbed and constructs the spatial position of each section of the riverbed according to the terrain conditions of the riverbed to complete the fusion reconstruction of the riverbed elevation, thereby realizing the concrete presentation of existing river channel and unknown river channel data.

[0103] In the examples of the present application, this is explained in detail through the following Example 6.

[0104] Example 6: Determine the simulated elevation H of the river centerline P Then, according to the estimated river elevation H PSurface The spatial position function relationship is constructed, and the relationship is expressed by the following formula (10):

[0105] H P =F(H PSurface )(10);

[0106] The river bottom elevation is recalculated for the interpolated digital river channel based on this functional relationship.

[0107] According to the theory of river geomorphology, the river channel morphology of the upper, middle and lower reaches of a river is quite different. For the convenience of calculation, it is simplified into three types: V-type, U-type and flat bottom. When speculating the river channel topography, determining the river channel morphology has an important impact on the selection of the speculation model and the accuracy of the final speculation result.

[0108] The geomorphic similarity of river channel morphology within a certain scale is determined by analyzing the cross-sectional morphology of the river channel after inverse distance interpolation to determine the cross-sectional type of the river channel area. According to the cross-sectional type of each section of the river channel, the spatial position function relationship is determined segmentally to match the spatial position corresponding to the vertical elevation distribution data to construct a function.

[0109] After completing the spatial position construction function of the entire river channel, the elevation data of the riverbed can be recalculated to obtain the required riverbed elevation data.

[0110] Finally, the riverbed elevation data is preprocessed with DEM to obtain the elevation data to be fused; the elevation data to be fused is rasterized to determine the riverbed raster data; the riverbed raster data is fused into the preset initial elevation data through a preset elevation reconstruction method to determine the digital riverbed terrain data.

[0111] The above is an embodiment of the method proposed in this application. Based on the same inventive concept, this application embodiment also provides a digital riverbed reconstruction device based on DEM, whose structure is as follows: Figure 4 shown.

[0112] Figure 4 The internal structure diagram of a DEM-based digital riverbed reconstruction device provided in the embodiment of the present application. Figure 4 As shown, the device includes:

[0113] at least one processor 401;

[0114] and, a memory 402 communicatively coupled to the at least one processor;

[0115] The memory 402 stores instructions that can be executed by at least one processor, and the instructions are executed by at least one processor 401 to enable at least one processor 401 to:

[0116] The river surface vector data is processed by inverse distance weighted spatial interpolation to determine the river DEM interpolation data; the river DEM interpolation data is smoothed by weighted average method to obtain the river centerline DEM data to be extracted; the river centerline DEM data to be extracted is fused and reconstructed to determine the river centerline data; wherein the river centerline data includes: river flow direction data, sub-basin boundary data, river network threshold data; the river centerline data is simulated by centerline elevation to obtain the vertical elevation distribution data of the river centerline data; based on the preset riverbed morphology category, the spatial position construction function corresponding to the vertical elevation distribution data is determined.

[0117] Some embodiments of the present application provide corresponding Figure 1 A non-volatile computer storage medium for a digital riverbed reconstruction method based on DEM stores computer executable instructions, wherein the computer executable instructions are set as follows:

[0118] The river surface vector data is processed by inverse distance weighted spatial interpolation to determine the river DEM interpolation data; the river DEM interpolation data is smoothed by weighted average method to obtain the river centerline DEM data to be extracted; the river centerline DEM data to be extracted is fused and reconstructed to determine the river centerline data; wherein the river centerline data includes: river flow direction data, sub-basin boundary data, river network threshold data; the river centerline data is simulated by centerline elevation to obtain the vertical elevation distribution data of the river centerline data; based on the preset riverbed morphology category, the spatial position construction function corresponding to the vertical elevation distribution data is determined.

[0119] Each embodiment in this application is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the IoT device and medium embodiments, since they are basically similar to the method embodiments, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiments.

[0120] The system and medium provided in the embodiments of the present application correspond one-to-one to the method. Therefore, the system and medium also have similar beneficial technical effects to the corresponding methods. Since the beneficial technical effects of the methods have been described in detail above, the beneficial technical effects of the system and medium will not be repeated here.

[0121] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program code.

[0122] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0123] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0124] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0125] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0126] The memory may include non-permanent storage in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0127] Computer readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include temporary computer readable media (transitory media), such as modulated data signals and carrier waves.

[0128] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0129] The above are only embodiments of the present application and are not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included within the scope of the claims of the present application.

Claims

1. A digital riverbed reconstruction method based on DEM, characterized in that: The method comprises: The river surface vector data is processed by inverse distance weighted spatial interpolation to determine the riverbed DEM interpolation data; Smoothing the riverbed DEM interpolation data by weighted average method to obtain smoothed riverbed DEM data; The smoothed riverbed DEM data is fused and reconstructed with the preset original DEM data, and the fused and reconstructed data is subjected to hydrological analysis to determine hydrological analysis data; wherein the hydrological analysis data includes: river flow direction data, sub-basin boundary data, river network threshold data, and river centerline data; Performing centerline elevation simulation on the hydrological analysis data to obtain vertical elevation distribution data of the river centerline data; Based on a preset riverbed morphology category, a spatial position construction function corresponding to the vertical elevation distribution data is determined.

2. The method for digital riverbed reconstruction based on DEM according to claim 1 is characterized in that: The river surface vector data is processed by inverse distance weighted spatial interpolation to determine the riverbed DEM interpolation data, including: The river surface vector data is transformed by a preset spatial analysis tool to obtain river surface mask data; Performing curvature determination on preset river network data to determine river network curvature radius data of the river network data, and determining an interpolation moving window radius corresponding to the river network curvature radius data based on the river network curvature radius data; Based on the interpolation moving window radius, the interpolation range covering the river surface mask data is determined by extending the interpolation width; According to the interpolation range, the river surface mask data is subjected to inverse distance weighted spatial interpolation processing to determine the riverbed DEM interpolation data.

3. The method for digital riverbed reconstruction based on DEM according to claim 1 is characterized in that: The riverbed DEM interpolation data is smoothed by weighted average method to obtain smoothed riverbed DEM data, which specifically includes: Obtaining window data of the riverbed DEM interpolation data, and determining the minimum unit window center point of the window data; Determine the points to be weighted of the minimum unit window according to the center point of the minimum unit window; wherein the points to be weighted include: the center point of the minimum unit window, the border points of the minimum unit window, and the four corner points of the minimum unit window; The points to be weighted are smoothed by weighted averaging method to obtain the smoothed riverbed DEM data.

4. The method for digital riverbed reconstruction based on DEM according to claim 1 is characterized in that: Performing centerline elevation simulation on the hydrological analysis data to obtain vertical elevation distribution data of the river centerline data specifically includes: Acquire the hydrological analysis data, and determine the vertical direction data of the river flow direction data according to the hydrological analysis data; Taking the central grid of the river flow direction as the starting point, extending according to the vertical direction data to determine the elevation data of the river to be processed; wherein the elevation data of the river to be processed includes: elevation points on both sides of the river channel and constraint points corresponding to the elevation of the centerline data of the river; The processed river elevation data is linearly extended in a preset bilateral vertical direction to determine the vertical direction data.

5. The method for digital riverbed reconstruction based on DEM according to claim 1 is characterized in that: Based on the preset riverbed morphology category, determining the spatial position construction function corresponding to the vertical elevation distribution data specifically includes: The preset riverbed data is segmented according to the riverbed morphology category to obtain segmented riverbed morphology category data; wherein the riverbed morphology category includes: V-type, U-type, and flat bottom type; According to the segmented riverbed morphology category data, a function is constructed by matching the spatial position corresponding to the vertical elevation distribution data.

6. A method for digital riverbed reconstruction based on DEM according to claim 5, characterized in that: After matching the spatial position corresponding to the vertical elevation distribution data to construct a function according to the segmented riverbed morphology category data, the method further includes: Processing the vertical elevation distribution data through the spatial position construction function to determine riverbed elevation data; The riverbed elevation data is reconstructed through riverbed elevation fusion to determine digital riverbed terrain data.

7. The method for digital riverbed reconstruction based on DEM according to claim 6 is characterized in that: The riverbed elevation data is reconstructed by riverbed elevation fusion to determine digital riverbed terrain data, specifically including: The riverbed elevation data is subjected to DEM preprocessing to obtain elevation data to be fused; Performing raster division on the elevation data to be fused to determine riverbed raster data; The riverbed raster data is fused into the preset initial elevation data through a preset elevation reconstruction method to determine the digital riverbed terrain data.

8. The method for digital riverbed reconstruction based on DEM according to claim 1 is characterized in that: Before performing inverse distance weighted spatial interpolation processing on the river surface vector data to determine the riverbed DEM interpolation data, the method further includes: Determine the DEM resolution based on the preset river basin range; Based on the DEM resolution, the DEM is clipped by the river basin range to obtain river DEM data; According to the river DEM data, when the river surface vector data cannot be obtained through a preset extraction method, the river surface vector data is extracted through slope extraction to determine the river surface vector data.

9. A digital riverbed reconstruction device based on DEM, characterized in that: The device comprises: at least one processor; and, a memory communicatively coupled to the at least one processor; The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to: The river surface vector data is processed by inverse distance weighted spatial interpolation to determine the riverbed DEM interpolation data; Smoothing the riverbed DEM interpolation data by weighted average method to obtain smoothed riverbed DEM data; The smoothed riverbed DEM data is fused and reconstructed with the preset original DEM data, and the fused and reconstructed data is subjected to hydrological analysis to determine hydrological analysis data; wherein the hydrological analysis data includes: river flow direction data, sub-basin boundary data, river network threshold data, and river centerline data; Performing centerline elevation simulation on the hydrological analysis data to obtain vertical elevation distribution data of the river centerline data; Based on a preset riverbed morphology category, a spatial position construction function corresponding to the vertical elevation distribution data is determined.

10. A non-volatile computer storage medium for a DEM-based digital riverbed reconstruction method, storing computer executable instructions, characterized in that: The computer executable instructions are configured to: The river surface vector data is processed by inverse distance weighted spatial interpolation to determine the riverbed DEM interpolation data; Smoothing the riverbed DEM interpolation data by weighted average method to obtain smoothed riverbed DEM data; The smoothed riverbed DEM data is fused and reconstructed with the preset original DEM data, and the fused and reconstructed data is subjected to hydrological analysis to determine hydrological analysis data; wherein the hydrological analysis data includes: river flow direction data, sub-basin boundary data, river network threshold data, and river centerline data; Performing centerline elevation simulation on the hydrological analysis data to obtain vertical elevation distribution data of the river centerline data; Based on a preset riverbed morphology category, a spatial position construction function corresponding to the vertical elevation distribution data is determined.

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