Methods, systems, electronic devices and storage media for extracting large cross-sectional data of river channels

Abstract

The present invention discloses a method, system, electronic device and storage medium for extracting large-section data of a river channel, and relates to the technical field of numerical simulation of flood evolution. The method comprises: obtaining a plurality of original terrain data of a target area, and generating a grid river network digital elevation model based on the original terrain data; determining the center line of the river channel based on the original terrain data and the grid river network digital elevation model, and dividing the center line of the river channel into a plurality of straight micro-bend sub-center lines and a plurality of strong bend sub-center lines by using a radius of curvature method; determining a large-section distribution vector map of the river channel based on all the straight micro-bend sub-center lines and all the strong bend sub-center lines; and using a stack profile tool, batch extracting large-section data of the river channel in the target area based on the large-section distribution vector map of the river channel and the grid river network digital elevation model. The present invention improves the speed and accuracy of extracting large-section data of the river channel.

Description

Technical Field

[0001] The present invention relates to the technical field of flood evolution numerical simulation, and in particular to a method, system, electronic equipment and storage medium for extracting large-section data of a river channel. Background Art

[0002] Flood evolution numerical simulation is to establish mathematical models and use computers to simulate the flood evolution process to predict the occurrence and evolution trend of flood disasters. Its main purpose is to improve flood control capabilities and reduce flood losses.

[0003] In the process of numerical simulation of flood evolution, it is necessary to collect data required for flood evolution, such as topography, landform, rainfall and other information. Among them, topographic data is an important foundation, which requires digital mapping of physical river channel related elements in the study area, construction of digital base plate, and collection of large-section river channel information. Large-section river channel data is one of the key input data in hydrological and hydrodynamic models, and has a vital impact on the accuracy and reliability of simulation results. Therefore, extracting accurate and reliable large-section river channel data is a key link in accurately constructing hydrological and hydrodynamic models. The evaluation and analysis of simulation results will provide a scientific basis for flood control work and play an important role in flood warning, emergency response and other aspects.

[0004] In the current field of hydrological simulation and forecasting, the commonly used hydrological and hydrodynamic models include the Hydrological Engineering Center-River Analysis System (HEC-RAS), the one-dimensional hydrodynamic model (MIKE 11) and the Storm Water Management Model (SWMM). These models have the characteristics of high accuracy, strong adaptability and more realistic, and have been verified in many hydrological and hydraulic fields. The large-section data of the river can be directly input into the above hydrological and hydrodynamic models to simulate the runoff flow, water level, flow rate and other parameters under different hydrological conditions, which can not only help predict the future hydrological and hydrodynamic change trends and flood risks of the river, but also help evaluate the effects of water resource utilization plans and water conservancy project construction, and provide decision support for ecological protection and pollution control.

[0005] By inputting data, adjusting parameters, optimizing models, etc., the hydraulic response of rivers and the trend of hydrological changes under different scenarios can be simulated. For example, in the case of flood prediction, different meteorological and hydrological conditions such as rainfall data, temperature, and flow can be input to estimate the potential flood risk and possible impact range of rivers under different circumstances. The results of the model can also be used to evaluate different governance plans or water conservancy project construction plans, and select the optimal plan with the least impact on the basin and river.

[0006] In short, large-section river data can not only be used to establish water level-flow relationship curves and simulate hydraulic parameters such as water level and flow velocity distribution in hydrological and hydrodynamic models, but can also be used as model input data to help predict future hydrological and hydrodynamic change trends and flood risks of rivers, providing decision-making support for water resources management and water conservancy project construction.

[0007] The methods for extracting large-section data of river channels usually include manual extraction, CAD polyline extraction, and river channel centerline. Among them, the manual extraction method is cumbersome, labor-intensive, and has large subjective errors. Data can only be extracted one by one, and the efficiency of data extraction is low. The CAD polyline extraction method is based on measured fixed-section data and uses a semi-automatic method to improve work efficiency, but its accuracy is still relatively low. It cannot accurately identify each section line and is easily affected by other line segments, resulting in the interruption of the extracted section line, which requires manual visual correction and manual repair. In addition, the data source is single, and it is impossible to obtain section data in rivers that lack fixed section data, resulting in sampling intervals between large sections of the river. If the distance is too large, it will affect the reliability and applicability of the model, resulting in deviations in the simulation results; the river centerline method realizes the automatic layout of large river sections, and achieves good results in straight river sections. However, in river sections with a large degree of curvature, the section lines laid out by this method often intersect with each other, resulting in incomplete or inaccurate extracted section data, the continuity is destroyed, and it cannot represent the true morphological characteristics of the river. In addition, the data after the intersection point will be repeatedly calculated, thereby reducing the accuracy of the hydrodynamic model and having a greater adverse impact on the accuracy of the simulation results.

[0008] In addition to the above methods, scholars have proposed many automated methods to extract large-section river data, but all of them have extremely high requirements for the original data. Automated methods are often implemented under the premise of existing measured cross-sectional data, large-section river line data, river surface data, and bathymetric data. The conditions are extremely harsh and the applicability is not strong. Under actual conditions, there are often only DEM data from space satellite telemetry and measured underwater terrain point set data. Under these data conditions, automated methods lack judgment basis, and cannot process complex river sections during the automatic layout and data extraction of large-section river sections, making it difficult to obtain accurate large-section river data.

[0009] Therefore, it is urgent to propose a method for rapid deployment and batch extraction of large-section river data with strong applicability. Summary of the invention

[0010] The purpose of the present invention is to provide a method, system, electronic equipment and storage medium for extracting large-section data of a river channel, thereby improving the speed and accuracy of extracting large-section data of a river channel.

[0011] To achieve the above object, the present invention provides the following solutions:

[0012] A method for extracting large-section river data, comprising:

[0013] Acquire a variety of original terrain data of the target area, and generate a grid river network digital elevation model based on the original terrain data;

[0014] Determine the centerline of the river channel based on the original terrain data and the grid river network digital elevation model, and divide the centerline of the river channel into a plurality of straight slightly curved section sub-centerlines and a plurality of strongly curved section sub-centerlines using a curvature radius method;

[0015] Determine a large-section distribution vector diagram of the river channel based on all the sub-center lines of the straight and slightly curved sections and all the sub-center lines of the strongly curved sections;

[0016] The stack profile tool is used to batch extract the large-section river data of the target area based on the large-section river distribution vector map and the grid river network digital elevation model.

[0017] Optionally, generating a grid river network digital elevation model based on the original terrain data includes:

[0018] Adopting multi-source data fusion technology, converting the original terrain data, unifying them into the same data format and integrating them into the geographic information system to obtain integrated data;

[0019] Removing duplicate data and abnormal data from the integrated data to obtain accurate terrain data;

[0020] The accurate terrain data is used as an input element of an irregular triangulated network model to construct an irregular triangulated network, and the irregular triangulated network is converted into a digital elevation model in a grid form to obtain the grid river network digital elevation model.

[0021] Optionally, the centerline of the river channel is divided into a plurality of straight slightly curved section sub-centerlines and a plurality of strongly curved section sub-centerlines using a curvature radius method, including:

[0022] Starting from the upstream of the center line of the river channel and ending at the downstream, n segmentation points are determined on the center line of the river channel; n≥3;

[0023] Determine the river channel centerline between the i-th segmentation point and the i+1-th segmentation point as the i-th segmentation centerline, thereby dividing the river channel centerline into n-1 segmentation centerlines;

[0024] Determine the length of the center line of each segment;

[0025] Calculate the radius of curvature of each segment centerline, and calculate the mean of the radius of curvature based on the radii of curvature of all segment centerlines; where for the i-th segment centerline 1≤i≤n:

[0026] The slope at the i-th segment point is determined as the slope of the i-th segment centerline;

[0027] Calculate the turning angle of the i-th segment centerline based on the slope of the i-th segment centerline and the slope of the i+1-th segment centerline;

[0028] Calculate the curvature of the i-th segment centerline according to the length and turning angle of the i-th segment centerline;

[0029] Calculate the curvature radius of the i-th segment centerline according to the slope of the i-th segment centerline;

[0030] According to the curvature radius of each segment center line and the average value of the curvature radius, the corresponding segment center line is determined as a straight slightly curved segment center line or a strongly curved segment center line.

[0031] Optionally, based on all the sub-center lines of the straight slightly curved sections and all the sub-center lines of the strongly curved sections, a large-section distribution vector diagram of the river channel is determined, including:

[0032] Traverse the center lines of each segment from upstream to downstream;

[0033] The adjacent straight and slightly curved section sub-center lines are merged, and the large river section is arranged vertically and equidistantly on the merged straight and slightly curved section sub-center lines using the centerline method; the adjacent strong curved section sub-center lines are merged, and the large river section is arranged using the convex bank base point arrangement strategy on the merged strong curved section sub-center lines, so as to obtain the distribution vector diagram of the large river section.

[0034] Optionally, using a stack profile tool, based on the river channel large section distribution vector map and the grid river network digital elevation model, batch extracting the river channel large section data of the target area includes:

[0035] By using the 3D analysis toolbox, the large-section distribution vector map of the river channel is taken as an input element, the grid river network digital elevation model is selected as a profile target, and the large-section data of the river channel are extracted in batches.

[0036] A river large cross-section data extraction system, comprising:

[0037] A grid river network digital elevation model determination module is used to obtain a variety of original terrain data of the target area and generate a grid river network digital elevation model based on the original terrain data;

[0038] A river channel centerline division module, used to determine the river channel centerline based on the original terrain data and the grid river network digital elevation model, and divide the river channel centerline into a plurality of straight slightly curved section sub-centerlines and a plurality of strongly curved section sub-centerlines using a curvature radius method;

[0039] A river channel large cross-section distribution vector diagram determination module, used to determine the river channel large cross-section distribution vector diagram based on all the straight slightly curved section sub-center lines and all the strong curved section sub-center lines;

[0040] The river channel large section data extraction module is used to use the stack profile tool to batch extract the river channel large section data of the target area based on the river channel large section distribution vector map and the grid river network digital elevation model.

[0041] An electronic device, comprising:

[0042] one or more processors;

[0043] a storage device having one or more programs stored thereon;

[0044] When the one or more programs are executed by the one or more processors, the one or more processors implement the method for extracting large-section river data as described above.

[0045] A storage medium stores a computer program thereon, wherein when the computer program is executed by a processor, the method for extracting large-section data of a river channel as described above is implemented.

[0046] According to the specific embodiments provided by the present invention, the present invention discloses the following technical effects:

[0047] The present invention discloses a method, system, electronic device and storage medium for extracting river channel large cross-section data. First, a grid river network digital elevation model is generated based on the original terrain data of the target area to determine the center line of the river channel, and the center line of the river channel is divided into a plurality of straight micro-bend sub-center lines and a plurality of strong bend sub-center lines by using the curvature radius method; based on all the straight micro-bend sub-center lines and all the strong bend sub-center lines, a river channel large cross-section distribution vector diagram is determined; and based on the river channel large cross-section distribution vector diagram and the grid river network digital elevation model, a stack profile tool is used to batch extract the river channel large cross-section data of the target area. Under limited data conditions, the river channel is segmented by the curvature radius method, which overcomes the drawback of the automated method in drawing the river channel large cross-section in the strong bend section, avoids the large cross-section of the river channel from crossing each other, realizes the rapid layout of any large cross-section of the river channel, and reduces the error caused by the subjectivity of the researchers. It also realizes the batch extraction of large-section river data, greatly reduces the workload, significantly improves the accuracy, continuity and reliability of large-section river data extraction, and improves the efficiency and effectiveness of constructing one- and two-dimensional hydrodynamic mathematical models in flood evolution simulation analysis. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0049] Figure 1 A schematic diagram of a flow chart of a method for extracting river channel large cross-section data provided in Example 1 of the present invention;

[0050] Figure 2 This is a flow chart of the curvature radius method;

[0051] Figure 3 This is a schematic diagram for calculating the turning angle;

[0052] Figure 4 This is a schematic diagram of the strategy for arranging base points on the convex bank;

[0053] Figure 5 It is a large cross-section distribution vector diagram of the river;

[0054] Figure 6 This is a large cross-sectional view of the river channel. DETAILED DESCRIPTION

[0055] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in 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. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0056] The purpose of the present invention is to provide a method, system, electronic device and storage medium for extracting large-section data of a river channel, aiming to improve the speed and accuracy of extracting large-section data of a river channel.

[0057] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0058] Example 1

[0059] Figure 1 This is a flow chart of a method for extracting river channel large cross-section data provided in Example 1 of the present invention. Figure 1 As shown, the method for extracting river channel large cross-section data in this embodiment includes:

[0060] Step 101: Acquire a variety of original terrain data of the target area, and generate a grid river network digital elevation model based on the original terrain data.

[0061] Step 102: Determine the centerline of the river channel based on the original terrain data and the grid river network digital elevation model, and divide the centerline of the river channel into a plurality of straight slightly curved section sub-centerlines and a plurality of strongly curved section sub-centerlines using the curvature radius method.

[0062] Specifically, the centerline of a river channel is determined based on the original terrain data and the grid river network digital elevation model, including: extracting the centerline of the river channel from the original terrain data; if there is no centerline data of the river channel in the original terrain data, extracting the river channel depth line from the grid river network digital elevation model instead.

[0063] Step 103: Determine the large-section distribution vector diagram of the river channel based on the sub-center lines of all straight and slightly curved sections and the sub-center lines of all strongly curved sections.

[0064] Step 104: Using the stack profile tool, batch extract the large-section river data of the target area based on the large-section river distribution vector map and the grid river network digital elevation model.

[0065] As an optional implementation, step 101 includes:

[0066] The multi-source data fusion technology is used to convert the original terrain data, unify them into the same data format and integrate them into the Geographic Information System (GIS) to obtain integrated data.

[0067] The integrated data is processed to remove duplicate and abnormal data to obtain accurate terrain data.

[0068] Specifically, the integrated data is processed to remove duplicate data and abnormal data to obtain accurate terrain data including:

[0069] Open the layer attribute table of the point features, line features, and surface features of the integrated data in GIS; add fields X and Y to store the XY coordinate values ​​of the point features, and calculate the XY coordinate values ​​through computational geometry; add a length field to store the length information of the line features, and calculate the length value through computational geometry; add an area field to store the area of ​​the surface features, and obtain the area value through calculation; call the "Data Management Tools-General-Delete Duplicate Items" tool, enter the layer of point features, line features, and surface features that need to remove duplicate data, and select the corresponding fields to complete the removal of duplicate data.

[0070] Use point and line data to generate a rough grid model, color it and overlay it with the point and line layer, place the point and line layer on the grid model layer, and find and delete abnormal point and line data in the mutation area of ​​the grid image.

[0071] The accurate terrain data is used as the input element of the irregular triangulated network model to construct an irregular triangulated network (TIN), and the irregular triangulated network is converted into a digital elevation model in raster form to obtain a raster river network digital elevation model.

[0072] Specifically, the accurate terrain data is used as the input element of the irregular triangulated network model, and the irregular triangulated network is constructed, and the irregular triangulated network is converted into a digital elevation model in the form of a grid, and a grid river network digital elevation model is obtained, including:

[0073] Select the "Create TIN" tool in the 3D Analysis Toolbox, use the accurate terrain data as input features, set the input feature type, height field, and coordinate system, and generate an irregular triangulated network TIN that can accurately represent the complex terrain changes.

[0074] Considering that different types of terrain data have different forms of TIN surface, the form of the TIN surface in the model is set while inputting the accurate terrain data to ensure that the constructed TIN model can accurately express and simulate the actual terrain. In the process of creating TIN, point data with elevation information is input in the form of discrete multipoints (Mass_Points), line data is input in the form of soft breaklines (Soft_Line), and contour lines without elevation information are input in the form of hard breaklines (Hard_Line).

[0075] Considering that the data structure of the TIN model is relatively complex, which is not conducive to the layout of large sections of the river and the batch extraction of section data, the irregular triangulated network TIN model is converted into a raster river network digital elevation model with a regular data format to ensure the efficiency and accuracy of the layout of large sections of the river and data extraction. Select the "TIN to Raster" tool in the 3D Analysis Toolbox, input the constructed irregular triangulated network TIN, set the data type, interpolation method, pixel size and height factor variable of the output raster, and convert the irregular triangulated network TIN into a raster river network digital elevation model.

[0076] As an optional implementation, Figure 2 and Figure 3 As shown, the curvature radius method is used in step 102 to divide the river channel centerline into a plurality of straight slightly curved section sub-centerlines and a plurality of strongly curved section sub-centerlines, including:

[0077] Starting from the upstream of the center line of the river and ending at the downstream, n segmentation points are determined on the center line of the river; n≥3.

[0078] Specifically, the center line of the river channel is taken as the object, and n segmentation points are determined (the segmentation points are determined by manual visual inspection). Among them, the segmentation point P1 at the upstream entrance of the river channel is determined and used as the starting point. The segmentation points are determined from the upstream to the downstream of the river channel until the river channel exit. The i-th segmentation point is recorded as P i , i = 1…n, record its plane coordinates as (x i ,y i ), i is the segment point number, P i is the i-th segmentation point, x i is the x-axis coordinate of the i-th segment point, y i is the y-axis coordinate of the i-th segment point.

[0079] The river channel centerline between the i-th segmentation point and the i+1-th segmentation point is determined as the i-th segmentation centerline, thereby dividing the river channel centerline into n-1 segmentation centerlines.

[0080] Specifically, the center line of the i-th segment is denoted as L i , are two segmentation points P i and P i+1 The part between.

[0081] Determine the length of each segment centerline. The length of the i-th segment centerline is denoted as S i .

[0082] Calculate the radius of curvature of each segment centerline, and calculate the mean of the radius of curvature based on the radii of curvature of all segment centerlines; where for the i-th segment centerline 1≤i≤n:

[0083] The slope at the i-th segment point is determined as the slope of the i-th segment centerline.

[0084] Specifically, the segment center line L i After discretization, import it into scientific drawing software, perform curve fitting on the discretized center line, use the tangent function, check the tangent point information, slope, and tangent function, and calculate the slope k of the tangent corresponding to the i-th segment point in the xy plane i (i.e. the slope of the center line of the i-th segment), if k i <0, then k i Take the absolute value.

[0085] The turning angle of the i-th segment centerline is calculated based on the slope of the i-th segment centerline and the slope of the (i+1)-th segment centerline.

[0086] Specifically, the turning angle α iThe calculation formula is as follows:

[0087] α i =arctan[(k i +k i+1 ) / (1-k i k i+1 )], (i=1…n-1)

[0088] Among them, k i+1 is the slope of the i+1th segment centerline.

[0089] The curvature of the i-th segment centerline is calculated based on the length and turning angle of the i-th segment centerline.

[0090] Specifically, the curvature K i The calculation formula is: K i =α i / S i .

[0091] The radius of curvature of the i-th segment centerline is calculated based on the slope of the i-th segment centerline.

[0092] Specifically, the radius of curvature R i The calculation formula is: i =1 / K i .

[0093] According to the curvature radius and the average curvature radius of each segment center line, the corresponding segment center line is determined as a straight slightly curved segment center line or a strongly curved segment center line.

[0094] Specifically, according to the curvature radius and the mean curvature radius of each segment center line, the corresponding segment center line is determined as a straight slightly curved segment center line or a strong curved segment center line, specifically including:

[0095] (1) Calculate the average of the curvature radii of all segment center lines to obtain the mean curvature radius The threshold coefficient λ is set, and the threshold coefficient multiplied by the mean value of the curvature radius is used as the curvature radius threshold. The value of the threshold coefficient λ is determined by the overall change trend and characteristics of the river terrain, and the value range of the threshold coefficient λ is 0<λ≤1. In this embodiment, the threshold coefficient λ is 0.5.

[0096] (2) The center line L of each segment i The corresponding radius of curvature R i Compared with the curvature radius threshold, the smaller the curvature radius, the greater the degree of river curvature; if the curvature radius of a segment centerline is less than the threshold, that is, Then L i Divide into strong bend section and center line; otherwise, L iDivided into straight and slightly curved sections and center lines.

[0097] As an optional implementation, step 103 includes:

[0098] Traverse the center lines of each segment from upstream to downstream.

[0099] The adjacent straight and slightly curved section center lines are merged, and the large river sections are arranged vertically and equidistantly on the merged straight and slightly curved section center lines using the center line method; the adjacent strong curved section center lines are merged, and the convex bank base point layout strategy is used to layout the large river sections on the merged strong curved section center lines, and the distribution vector diagram of the large river sections is obtained.

[0100] Specifically, step 103 specifically includes: defining and counting the attributes of the sub-center lines of the straight and slightly curved sections and the sub-center lines of the strong curved sections, traversing the sub-center lines of each section from upstream to downstream, merging the adjacent sub-center lines of the straight and slightly curved sections, automatically and equidistantly arranging the large cross-sections of the river channel vertically using the center line method for the merged center lines of the straight and slightly curved sections, and obtaining the distribution vector diagram of the large cross-sections of the river channel after arranging the large cross-sections of the river channel, merging the adjacent sub-center lines of the strong curved sections, and manually arranging the large cross-sections of the river channel using the convex bank base point arrangement strategy for the merged center lines of the strong curved sections (such as Figure 4 As shown), a large cross-section distribution vector diagram of the river channel is obtained.

[0101] The specific strategy for the layout of convex bank base points is as follows: Figure 4 The highest point of terrain elevation is selected as the base point on the convex bank of the strong bend section shown in the figure. A vertical section line is drawn from this base point to the center line of the river. Considering that the data at the base point is repeatedly calculated, which leads to a larger calculation result of the model, the section line within a certain range with the base point as the center is drawn ( Figure 4 The partial section line within the dotted circle is cut out to obtain the large section line of the river without intersection.

[0102] In addition, in complex river sections such as river bifurcations and confluences, or areas with hydraulic structures, large river sections are manually added or deleted according to research needs, and the following is finally obtained: Figure 5 The large cross-section distribution vector diagram of the river is shown.

[0103] As an optional implementation, step 104 includes:

[0104] Using the 3D analysis toolbox, the large-section distribution vector map of the river channel is taken as the input element, and the raster river network digital elevation model is selected as the profile target to batch extract large-section data of the river channel.

[0105] Specifically, step 104 includes:

[0106] Create serial points for large sections of the river channel, calibrate serial numbers for large sections of the river channel, select the "Stack Profile" tool in the 3D Analysis Toolbox, use the large section distribution vector map of the river channel as the input element, select the raster river network digital elevation model as the profile target, interpolate the large section distribution vector map of the river channel into the river network digital elevation model, and batch extract the large section data of the river channel into the set data table to obtain the large section data table of the river channel as shown in Table 1, so as to realize the batch extraction of large section data of the river channel. In addition, the Stack Profile tool can also perform statistics and analysis of profile data, such as calculating the average value, maximum and minimum water depths, etc.

[0107] Table 1 Data table of large river sections

[0108]

[0109]

[0110] Step 104 also includes: using the point set data in the river section data table, importing it into GIS or mapping software, and creating a map of each river section. Figure 6 Check the cross-section diagram shown to see if its smoothness, continuity, accuracy and other aspects meet the requirements. If there are any problems, adjustments and optimizations need to be made.

[0111] Example 2

[0112] The river channel large cross-section data extraction system in this embodiment includes:

[0113] The grid river network digital elevation model determination module is used to obtain a variety of original terrain data of the target area and generate a grid river network digital elevation model based on the original terrain data.

[0114] The river centerline division module is used to determine the river centerline based on the original terrain data and the grid river network digital elevation model, and divide the river centerline into multiple straight and slightly curved section centerlines and multiple strongly curved section centerlines using the curvature radius method.

[0115] The module for determining the large-section distribution vector diagram of the river channel is used to determine the large-section distribution vector diagram of the river channel based on the sub-center lines of all straight and slightly curved sections and the sub-center lines of all strongly curved sections.

[0116] The river channel large section data extraction module is used to batch extract the river channel large section data of the target area based on the river channel large section distribution vector map and the grid river network digital elevation model using the stack profile tool.

[0117] Example 3

[0118] An electronic device, comprising:

[0119] One or more processors.

[0120] A storage device having one or more programs stored thereon.

[0121] When one or more programs are executed by one or more processors, the one or more processors implement the large-section river data extraction method as in Example 1.

[0122] Example 4

[0123] A storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, a method for extracting large-section river data as in Example 1 is implemented.

[0124] In this specification, each embodiment is described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the embodiments can be referred to each other. For the system disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the method part.

[0125] The principles and implementation methods of the present invention are described in this article using specific examples. The description of the above embodiments is only used to help understand the method and core idea of ​​the present invention. At the same time, for those skilled in the art, according to the idea of ​​the present invention, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting the present invention.

Claims

1. A method for extracting large-section river data, characterized in that: The method comprises: Acquire a variety of original terrain data of the target area, and generate a grid river network digital elevation model based on the original terrain data; Determine the centerline of the river channel based on the original terrain data and the grid river network digital elevation model, and divide the centerline of the river channel into a plurality of straight slightly curved section sub-centerlines and a plurality of strongly curved section sub-centerlines using a curvature radius method; Determine a large-section distribution vector diagram of the river channel based on all the sub-center lines of the straight and slightly curved sections and all the sub-center lines of the strongly curved sections; Using a stack profile tool, batch extracting the river channel large section data of the target area based on the river channel large section distribution vector map and the grid river network digital elevation model; The curvature radius method is used to divide the river centerline into a number of straight and slightly curved sub-centerlines and a number of strong curved sub-centerlines, including: Starting from the upstream of the center line of the river and ending at the downstream, n segmentation points are determined on the center line of the river; n ≥ 3; The river channel centerline between the i-th segmentation point and the i+1-th segmentation point is determined as the i-th segmentation centerline, thereby dividing the river channel centerline into n-1 segmentation centerlines; Determine the length of the center line of each segment; Calculate the radius of curvature of each segment centerline, and calculate the mean of the radius of curvature based on the radii of curvature of all segment centerlines; where for the i-th segment centerline 1≤i≤n: The slope at the i-th segment point is determined as the slope of the i-th segment centerline; Calculate the turning angle of the i-th segment centerline based on the slope of the i-th segment centerline and the slope of the i+1-th segment centerline; Calculate the curvature of the i-th segment centerline according to the length and turning angle of the i-th segment centerline; Calculate the curvature radius of the i-th segment centerline according to the slope of the i-th segment centerline; According to the curvature radius and the average curvature radius of each segment center line, the corresponding segment center line is determined as a straight slightly curved segment center line or a strongly curved segment center line.

2. The method for extracting large-section river data according to claim 1, characterized in that: Generating a grid river network digital elevation model based on the original terrain data includes: Adopting multi-source data fusion technology, converting the original terrain data, unifying them into the same data format and integrating them into the geographic information system to obtain integrated data; Removing duplicate data and abnormal data from the integrated data to obtain accurate terrain data; The accurate terrain data is used as an input element of an irregular triangulated network model to construct an irregular triangulated network, and the irregular triangulated network is converted into a digital elevation model in a grid form to obtain the grid river network digital elevation model.

3. The method for extracting large-section river data according to claim 1, characterized in that: Based on the sub-center lines of all the straight and slightly curved sections and the sub-center lines of all the strongly curved sections, a large-section distribution vector diagram of the river channel is determined, including: Traverse the center lines of each segment from upstream to downstream; The adjacent straight and slightly curved section sub-center lines are merged, and the large river section is arranged vertically and equidistantly on the merged straight and slightly curved section sub-center lines using the centerline method; the adjacent strong curved section sub-center lines are merged, and the large river section is arranged using the convex bank base point arrangement strategy on the merged strong curved section sub-center lines, so as to obtain the distribution vector diagram of the large river section.

4. The method for extracting river channel large cross-section data according to claim 1, characterized in that: Using the stack profile tool, based on the river channel large section distribution vector map and the grid river network digital elevation model, batch extracting the river channel large section data of the target area includes: By using the 3D analysis toolbox, the large-section distribution vector map of the river channel is taken as an input element, the grid river network digital elevation model is selected as a profile target, and the large-section data of the river channel are extracted in batches.

5. A river channel large section data extraction system, characterized in that: The system comprises: A grid river network digital elevation model determination module is used to obtain a variety of original terrain data of the target area and generate a grid river network digital elevation model based on the original terrain data; A river channel centerline division module, used to determine the river channel centerline based on the original terrain data and the grid river network digital elevation model, and divide the river channel centerline into a plurality of straight slightly curved section sub-centerlines and a plurality of strongly curved section sub-centerlines using a curvature radius method; A river channel large cross-section distribution vector diagram determination module, used to determine the river channel large cross-section distribution vector diagram based on all the straight slightly curved section sub-center lines and all the strong curved section sub-center lines; A river channel large section data extraction module is used to batch extract the river channel large section data of the target area based on the river channel large section distribution vector map and the grid river network digital elevation model using a stack profile tool; The curvature radius method is used to divide the river centerline into a number of straight and slightly curved sub-centerlines and a number of strong curved sub-centerlines, including: Starting from the upstream of the center line of the river and ending at the downstream, n segmentation points are determined on the center line of the river; n ≥ 3; The river channel centerline between the i-th segmentation point and the i+1-th segmentation point is determined as the i-th segmentation centerline, thereby dividing the river channel centerline into n-1 segmentation centerlines; Determine the length of the center line of each segment; Calculate the radius of curvature of each segment centerline, and calculate the mean of the radius of curvature based on the radii of curvature of all segment centerlines; where for the i-th segment centerline 1≤i≤n: The slope at the i-th segment point is determined as the slope of the i-th segment centerline; Calculate the turning angle of the i-th segment centerline based on the slope of the i-th segment centerline and the slope of the i+1-th segment centerline; Calculate the curvature of the i-th segment centerline according to the length and turning angle of the i-th segment centerline; Calculate the curvature radius of the i-th segment centerline according to the slope of the i-th segment centerline; According to the curvature radius and the average curvature radius of each segment center line, the corresponding segment center line is determined as a straight slightly curved segment center line or a strongly curved segment center line.

6. An electronic device, characterized in that: include: one or more processors; a storage device having one or more programs stored thereon; When the one or more programs are executed by the one or more processors, the one or more processors implement the method for extracting large-section river data as described in any one of claims 1 to 4.

7. A storage medium, characterized in that: A computer program is stored thereon, wherein when the computer program is executed by a processor, the method for extracting large-section river data as described in any one of claims 1 to 4 is implemented.

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