Underwater isobath automatic generation and optimization method considering river trend

Abstract

The invention discloses an underwater isobath automatic generation and optimization method taking river trend into consideration, which comprises the following steps: preprocessing underwater measuring points, constructing a triangulation network conforming to the river direction by using the preprocessed underwater measuring points and water boundary points, and adopting a Constrained Delaunay Triangulation method as a constraint condition of river water boundary, so that the generated triangulation network meets the actual demand, and the method has the advantages of high efficiency, high accuracy and high efficiency. And automatically generating the underwater isobath according to the constructed triangulation network, optimizing nodes for automatically generating the underwater isobath by adopting a node thinning method, only reserving nodes near a section line, redrawing the underwater isobath according to node data after thinning processing, and obtaining a final optimized underwater isobath. The underwater isobath which is more accurate and conforms to the reality is obtained through measurement point preprocessing and a triangulation network optimization mode considering the river trend, underwater isobath mapping is simpler and more attractive through node thinning editing, and consumption of computing resources can be reduced and the data processing speed can be increased on the premise that precision is guaranteed.

Description

Technical Field

[0001] The present invention relates to the technical field of underwater surveying and engineering drawing, and specifically to an automatic generation and optimization method for underwater isobaths considering the river trend. Background Art

[0002] Underwater topographic surveying technology, as the basic support for river regulation and hydrological sediment research, its core value lies in helping to understand the topographic evolution law of the riverbed by obtaining the elevation data of the riverbed, which has important guiding significance for the planning and implementation of water conservancy projects. The isobaths drawn from the underwater measured points at different scales can intuitively display the undulation and changes of the riverbed topography, the river flow direction, the riverbed morphology and the complex features of the near-shore topography, which are of great significance for the site selection of water conservancy projects, the construction of dikes, and flood control and disaster reduction.

[0003] Traditional methods use discrete elevation points to construct a triangular network to generate isobaths. Although they can maintain the accuracy of the original data, there are significant defects in practical applications: (1) When there is no constraint on the water-land boundary, the triangular network is prone to elevation mutations, such as steep slopes appearing at the junction of the water surface and the bank slope. (2) The constructed original triangular network is irregular and does not consider the characteristics of the river itself, resulting in a decrease in accuracy. (3) The generated isobaths have problems of node redundancy and rough graphics, resulting in terrain feature distortion and point-line contradictions, and manual intervention is required to clean the nodes, which greatly reduces the drawing efficiency. The existing technologies have not effectively solved the contradiction between the characteristics of the measurement data and the requirements of engineering drawing, and an intelligent processing method that takes into account both terrain authenticity and drawing display friendliness needs to be developed. Summary of the Invention

[0004] In order to solve the deficiencies in the existing technologies, the present invention proposes an automatic generation and optimization method for underwater isobaths considering the river trend, constructs a triangular network optimization algorithm based on underwater measurement points and water edge points, and automatically generates isobaths, significantly improving the measurement accuracy and processing efficiency.

[0005] The present invention provides the following technical solutions: An automatic generation and optimization method for underwater isobaths considering the river trend, comprising the following steps: S1. Preprocess the underwater measurement points, delete the invalid underwater measurement points, and divide the regional scope according to the geographical location of the underwater measurement points.

[0006] S2. Construct a triangular network together with the underwater measurement points and water boundary points preprocessed in the step S1, and make the triangular network conform to the river direction, so that the generated triangular network meets the actual requirements.

[0007] S3. Automatically generate underwater isobaths according to the triangular network constructed in the step S2.

[0008] S4. Edit and thin the nodes of the underwater isobaths automatically generated in step S3, only retain the nodes near the section lines, and redraw the underwater isobaths according to the thinned node data to obtain the finally optimized underwater isobaths.

[0009] Furthermore, for step S1, the pretreatment of underwater measurement points, deleting invalid underwater measurement points, specifically: S11. Set the vertical distance threshold m between the section line and the underwater measurement points, project perpendicular lines to each section line with the vertical distance threshold m to obtain the adjacent areas of each section line.

[0010] S12. Retain the underwater measurement points that fall into the adjacent area of any section line.

[0011] S13. If no underwater measurement points are found in the adjacent area of a certain section line, this area is regarded as a blank section area, and retain the underwater measurement point closest to this section line in terms of vertical distance.

[0012] S14. For the remaining underwater measurement points that are not retained in step S12 and step S13, they are identified as invalid underwater measurement points and deleted.

[0013] Furthermore, for step S2, construct a triangular mesh together with the underwater measurement points and water boundary points pretreated in step S1, and make the triangular mesh conform to the river direction, so that the generated triangular mesh meets the actual requirements, specifically: S21. Statistically analyze the elevation data of the underwater measurement points after pretreatment, and trace the elevation valley points to obtain the river centerline.

[0014] S22. Construct a triangular mesh together with the underwater measurement points and water boundary points. Use the Constrained Delaunay Triangulation (CDT) method as the constraint condition for the river water boundary. Define the water boundary point set as the forced constraint edge, and define the river centerline as the constraint direction. By taking the water boundary points and the river center direction as inputs, ensure that during the triangulation process, the river water boundary point set becomes part of the triangular mesh, and the edges of the mesh are consistent with the river flow direction, so that the vertices of the triangular mesh not only meet the Delaunay condition, but also can conform to the natural flow direction of the river, ensuring the elevation continuity of the water boundary line and its surrounding areas.

[0015] Furthermore, for step S3, according to the triangular mesh constructed in step S2, automatically generate underwater isobaths, specifically: Judge whether the difference in water depth values between the two endpoints of each triangle side is greater than the set target value a, and automatically generate underwater isobaths by linearly interpolating the endpoints that meet the judgment conditions.

[0016] Further, for step S4, node editing and thinning are performed on the underwater isobaths automatically generated in step S3, and only the nodes near the section line are retained. The underwater isobaths are redrawn based on the thinned node data to obtain the finally optimized underwater isobaths. Specifically: S41. Encode and calibrate the section lines in the measurement area.

[0017] S42. Node-ify the underwater isobaths automatically generated in step S3. Set a predetermined node distance limit value n, calculate the vertical distance from each underwater isobath node to each section line, retain the nodes with the minimum vertical distance less than or equal to the node distance limit value n, and delete the nodes with the minimum vertical distance greater than the node distance limit value n.

[0018] S43. Check each section line to ensure that there is at least one node on or near each section line.

[0019] S44. Redraw the underwater isobaths based on the thinned node data to obtain the finally optimized underwater isobaths.

[0020] Further, the method for obtaining the river centerline in step S21 may also be that for a single river section, the river centerline can also be obtained by calculating the midline of the water edge lines on both sides of the river.

[0021] Further, the linear interpolation adopts bilinear interpolation or piecewise linear interpolation.

[0022] Further, the set target value a is set according to the riverbed slope condition.

[0023] Compared with the prior art, the beneficial effects of the present invention are: 1. By dynamically screening and optimizing underwater measurement points through the algorithm, the present invention can ensure the reasonable distribution of measurement points in the underwater space. The optimized measurement point distribution is more in line with the actual changes of the underwater terrain, improving the representativeness and accuracy of the data. In addition, the workload of manual screening and data preprocessing is greatly reduced, the data processing efficiency is improved, and a large amount of time and resources are saved.

[0024] 2. The present invention effectively optimizes the traditional Delaunay triangulation by introducing the Constrained Delaunay Triangulation (CDT) method, successfully solving the problem of abrupt elevation changes in the generation of triangular meshes at the water-land junction. In addition, the triangular mesh conforms to the actual river morphology. During the construction of the triangular mesh, the constraint conditions ensure that the distribution of grid elements is consistent with the river direction, and the river boundary is effectively retained. This process effectively reflects the natural morphology of the river channel, enhances the authenticity of the water area terrain, makes subsequent analysis and modeling more in line with reality, reduces the grid error in the water boundary area, and optimizes the data processing accuracy. At the same time, by introducing the constraint of the river boundary, the workload of subsequent manual correction is reduced, a large amount of time and labor costs are saved, and the work efficiency is improved.

[0025] 3. By adding a node thinning method, the generated isobaths are more concise and smooth, avoiding redundant information caused by over-dense nodes. Moreover, on the premise of ensuring accuracy, it can reduce the consumption of computing resources, improve the data processing speed, and reduce the storage burden and processing time under large data volumes. Brief Description of the Drawings

[0026] Figure 1 It is a schematic diagram of the preprocessing of underwater measurement points of the present invention.

[0027] Figure 2 It is a comparison diagram before and after the optimization of the triangular mesh of the present invention.

[0028] Figure 3 It is a comparison diagram before and after the optimization of node thinning of the present invention. Specific Embodiments

[0029] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0030] An automatic generation and optimization method for underwater isobaths considering the river trend includes the following steps: S1. Preprocess the underwater measurement points, delete the invalid underwater measurement points, and divide the regional scope according to the geographical location of the underwater measurement points.

[0031] S2. Construct a triangular mesh together with the preprocessed underwater measurement points and water boundary points in step S1, and make the triangular mesh conform to the river direction, so that the generated triangular mesh meets the actual requirements.

[0032] S3. Based on the triangular network constructed in step S2, determine whether the difference in water depth values at both ends of each triangle side is greater than the set target value a. By linearly interpolating the endpoints that meet the judgment conditions, underwater isobaths are automatically generated.

[0033] S4. Perform node editing and thinning on the underwater isobaths automatically generated in step S3, only retain the nodes near the cross-section line, and redraw the underwater isobaths according to the node data after thinning processing to obtain the finally optimized underwater isobaths.

[0034] Furthermore, for step S1, the preprocessing of underwater measurement points, deleting invalid underwater measurement points, specifically: S11. Set the vertical distance threshold m between the cross-section line and the underwater measurement points, and project perpendicular lines to each cross-section line with the vertical distance threshold m to obtain the adjacent areas of each cross-section line.

[0035] S12. Retain the underwater measurement points that fall within the adjacent area of any cross-section line.

[0036] S13. If no underwater measurement points are found in the adjacent area of a certain cross-section line, this area is regarded as a blank cross-section area, and retain the underwater measurement point closest to this cross-section line in terms of vertical distance.

[0037] S14. For the remaining underwater measurement points that are not retained in step S12 and step S13, they are identified as invalid underwater measurement points and deleted.

[0038] Taking the application in actual production as an example, an underwater topographic survey was carried out on a certain water area. Figure 1 It is a schematic diagram of the preprocessing of underwater measurement points. In the data preprocessing stage, set the vertical distance threshold m between the cross-section line and the underwater measurement points in the drawing system. If the underwater measurement points deviate far from the cross-section line, greater than the vertical distance threshold m, the points to be deleted will be marked with small red flags, and these measurement points can be deleted after confirmation.

[0039] Furthermore, for step S2, construct a triangular network with the underwater measurement points and water boundary points preprocessed in step S1, and make the triangular network conform to the river direction, so that the generated triangular network meets the actual requirements, specifically: S21. Statistically analyze the elevation data of the preprocessed underwater measurement points, and track the elevation valley bottom points to obtain the river centerline.

[0040] S22. A triangular network is constructed by underwater measurement points and water boundary points. The Constrained Delaunay Triangulation (CDT) method is used as the constraint condition for the river water boundary. The water boundary point set is defined as the forced constraint edge, and the river centerline is defined as the constraint direction. By taking the water boundary points and the river center direction as inputs, it is ensured that during the triangulation process, the river water boundary point set becomes part of the triangular network, and the edges of the grid are consistent with the river trend, so that the vertices of the triangular network not only satisfy the Delaunay condition but also conform to the natural flow direction of the river, ensuring the elevation continuity of the water boundary line and its surrounding area.

[0041] Furthermore, regarding the method for obtaining the river centerline in step S21, for a single river section, the river centerline can also be obtained by calculating the midline of the water edge lines on both sides of the river.

[0042] In the actual triangulation process, the traditional Delaunay condition is enhanced to "constrained Delaunay triangulation", that is, in addition to requiring that each interior angle in the triangular network is greater than or equal to 60 degrees, it is also necessary to force certain edges to be constraint edges, especially in the area at the water-land junction. Through this constraint, the generation of the triangular network not only ensures the smoothness and excellence of Delaunay but also makes the boundary of the triangular network completely fit the water boundary and extend along the river direction.

[0043] Such as Figure 2 As shown in the comparison diagram of the triangular network before and after optimization, where (1) is before the triangular network optimization and (2) is after the triangular network optimization. In the implementation of triangular network generation, the water boundary point set is defined as the forced constraint edge, and the river centerline is defined as the constraint direction, so that the boundary of the triangular network completely fits the water boundary and extends along the river direction, effectively avoiding unreasonable triangle distribution and mutation problems.

[0044] Furthermore, for step S3, according to the triangular network constructed in step S2, underwater isobaths are automatically generated, specifically: Judge whether the difference in water depth values between the two endpoints of each triangle side is greater than the set target value a. By linearly interpolating the endpoints that meet the judgment conditions, underwater isobaths are automatically generated. The linear interpolation uses bilinear interpolation or piecewise linear interpolation. The set target value a is set according to the riverbed slope situation of the river.

[0045] Furthermore, for step S4, node editing and thinning are performed on the underwater isobaths automatically generated in step S3. Only the nodes near the cross-section line are retained, and the underwater isobaths are redrawn according to the node data after thinning processing to obtain the finally optimized underwater isobaths, specifically: S41. Encode and calibrate the cross-section lines in the measurement area.

[0046] S42. Node the underwater contour lines automatically generated in step S3. Set a predetermined node spacing value n, calculate the vertical distance from each underwater contour line node to each section line, retain the nodes with the minimum vertical distance less than or equal to the node spacing value n, and delete the nodes with the minimum vertical distance greater than the node spacing value n.

[0047] S43. Check each section line to ensure that there is at least one node on or near each section line.

[0048] S44. Redraw the underwater contour lines according to the node data after thinning processing to obtain the finally optimized underwater contour lines.

[0049] Figure 3 This is a comparison diagram before and after node thinning optimization. Among them, (1) is before node thinning optimization, and (2) is after node thinning optimization, showing the actual effects before and after node thinning optimization of underwater contour lines. As can be seen from the figure, the fewer the curve nodes, the smoother the underwater contour lines. Based on the characteristics of the established section measurement during the actual measurement process, the strategy of only retaining the key nodes on or near the section line is adopted to avoid the chaos caused by too many details, making the mapping results beautiful and smooth while retaining the actual terrain undulation changes. This method realizes only retaining the nodes on or near the section line, thereby realizing the smoothness of underwater contour lines. Since there will be a certain offset between the measurement points and the section line during the actual measurement process, therefore, while identifying the section line code on the map, this method sets a spacing to retain the nodes within the specified distance range of the section to ensure that there is at least 1 node on this section line.

[0050] The above are only embodiments of the present invention, and common knowledge such as specific structures and characteristics known in the solution is not described in detail here. For those skilled in the art, it is obvious that the present invention is not limited to the details of the above exemplary embodiments, and can be implemented in other specific forms without departing from the spirit or basic characteristics of the present invention. Therefore, from any point of view, the embodiments should be regarded as exemplary and non-limiting. The scope of the present invention is defined by the appended claims rather than the above description. Therefore, it is intended to include all changes within the meaning and scope of the equivalent elements of the claims in the present invention. Any reference signs in the claims should not be regarded as limiting the claimed rights.

Claims

1. An automatic generation and optimization method for underwater contour lines considering river trends, characterized in that, It includes the following steps: S1. Preprocess the underwater measurement points, delete the invalid underwater measurement points, and divide the regional scope according to the geographical locations of the underwater measurement points; S2. Construct a triangular mesh together with the underwater measurement points and water boundary points after the preprocessing in step S1, and make the triangular mesh conform to the river direction, so that the generated triangular mesh meets the actual requirements; S3. Automatically generate underwater isobaths according to the triangular mesh constructed in step S2; S4. Perform node editing and thinning on the underwater isobaths automatically generated in step S3, only retain the nodes near the section line, and redraw the underwater isobaths according to the node data after the thinning process to obtain the finally optimized underwater isobaths.

2. The automatic generation and optimization method of underwater contour lines taking into account the river course according to claim 1, characterized in that For step S1, the preprocessing of the underwater measurement points to delete the invalid underwater measurement points is specifically as follows: S11. Set the vertical distance threshold m between the section line and the underwater measurement points, project perpendicular lines to each section line with the vertical distance threshold m to obtain the adjacent areas of each section line; S12. Retain the underwater measurement points falling within the adjacent area of any section line; S13. If no underwater measurement points are found in the adjacent area of a certain section line, this area is regarded as a blank section area, and retain the underwater measurement point closest to this section line in terms of vertical distance; S14. Identify the remaining underwater measurement points that are not retained in step S12 and step S13 as invalid underwater measurement points and delete them.

3. An automatic generation and optimization method for underwater contour lines considering the river trend according to claim 1, characterized in that, For step S2, constructing a triangular mesh together with the underwater measurement points and water boundary points after the preprocessing in step S1 and making the triangular mesh conform to the river direction so that the generated triangular mesh meets the actual requirements is specifically as follows: S21. Statistically analyze the elevation data of the underwater measurement points after preprocessing, and trace the elevation valley bottom points to obtain the river centerline; S22. Construct a triangular mesh together with the underwater measurement points and water boundary points, use the Constrained Delaunay Triangulation method as the constraint condition for the river water boundary, define the water boundary point set as the forced constraint edge, define the river channel centerline as the constraint direction, and ensure that the river water boundary point set becomes part of the triangular mesh and the edge of the mesh is consistent with the river trend during the triangulation process by taking the water boundary points and the river center direction as inputs, so that the vertices of the triangular mesh not only meet the Delaunay condition but also can conform to the natural flow direction of the river, ensuring the elevation continuity of the water boundary line and its surrounding area.

4. An automatic generation and optimization method for underwater contour lines considering river trends according to claim 1, characterized in that, For step S3, automatically generating underwater isobaths according to the triangular mesh constructed in step S2 is specifically as follows: Judge whether the difference in water depth values between the two endpoints of each triangle side is greater than the set target value a, and automatically generate underwater isobaths by linearly interpolating the endpoints that meet the judgment conditions.

5. An automatic generation and optimization method for underwater contour lines considering river trends according to claim 1, characterized in that, For step S4, performing node editing and thinning on the underwater isobaths automatically generated in step S3, only retaining the nodes near the section line, and redrawing the underwater isobaths according to the node data after the thinning process to obtain the finally optimized underwater isobaths is specifically as follows: S41. Encode and calibrate the section lines within the measurement area; S42. Node-ize the underwater contour lines automatically generated in step S3. Set a predetermined node distance limit value n, calculate the vertical distance from each underwater contour line node to each cross-section line, retain the nodes with the minimum vertical distance less than or equal to the node distance limit value n, and delete the nodes with the minimum vertical distance greater than the node distance limit value n; S43. Check each cross-section line to ensure that there is at least one node on or near each cross-section line; S44. Redraw the underwater contour lines according to the thinned node data to obtain the finally optimized underwater contour lines.

6. The automatic generation and optimization method of underwater contour lines considering river trends according to claim 3, characterized in that For a single river reach, the method of obtaining the river center line in step S21 can also be obtained by calculating the midline of the water edge lines on both banks of the river.

7. An automatic generation and optimization method for underwater contour lines considering the river trend according to claim 4, characterized in that, The linear interpolation uses bilinear interpolation or piecewise linear interpolation.

8. An automatic generation and optimization method for underwater contour lines considering river trends according to claim 4, characterized in that The set target value a is set according to the river bed slope condition.

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