A method for constructing water-land integrated DEM by constraining reservoir near-shore sounding blind area

Abstract

The application discloses a reservoir near-shore sounding blind area constrained water-land integrated DEM construction method, comprising the following steps: S1, multi-source data preparation and coordinate unification; S2, generating a shoreline point set based on a line layer; S3, establishing a connection relationship from the shoreline point to the nearest sounding point to generate a near-shore connection skeleton line; S4, extracting a shore side control elevation, a shore slope gradient and a water side control elevation and relating to the corresponding near-shore connection skeleton line; S5, determining an index control parameter and a transition point step according to the length of the near-shore connection skeleton line and the shore slope gradient; S6, generating a near-shore transition point and calculating the elevation of each near-shore transition point to form a near-shore transition point set; S7, giving a vertex elevation to the encrypted shoreline based on the land DEM to obtain a three-dimensional shoreline constraint line; S8, constructing a constrained TIN based on the three-dimensional shoreline constraint line and a total point set; and S9, converting the constrained TIN into a DEM and performing smoothing processing.

Description

Technical Field

[0001] This invention relates to the field of remote sensing mapping technology, and in particular to a method for constructing a land-water integrated DEM constrained by nearshore depth sounding blind zone of a reservoir. Background Technology

[0002] The integrated land-water DEM of a reservoir is a crucial foundation for reservoir capacity calculation, scour and sedimentation analysis, bank slope stability assessment, hydraulic structure layout, 2D / 3D hydrodynamic simulation, and digital twin base construction. In existing projects, a common approach to constructing the terrain surface is "land area point cloud + underwater sounding points + TIN surface construction + rasterization." While this approach is simple to implement and easily promoted in engineering, it often exposes problems at the land-water interface in reservoir scenarios. For the land area, high-precision LiDAR point clouds can effectively represent the shoreline topography. For the underwater portion, single-beam bathymetry is a common source of underwater topographic data in many reservoir projects due to its low equipment cost and ease of operation. However, single-beam bathymetry is limited by factors such as shallow water safety, shoreline obstacles, and algae / floating debris, often preventing it from reaching the shoreline and creating a near-shore bathymetry blind zone between the shoreline and the nearest underwater measuring point. Furthermore, the width of this blind zone dynamically changes with the slope steepness and the safe operating distance.

[0003] Traditional methods directly merge land and underwater measurement points to construct a TIN. However, due to the lack of effective shape constraints in blind areas, the triangulation network will freely cross boundaries and follow the structure, directly generating problems such as abnormal triangular faces, unnatural hard slopes, abrupt elevation differences, and distorted shoreline morphology. After being converted into a raster DEM, it will exhibit a blocky, stepped appearance and discontinuous terrain, which seriously affects the accuracy of subsequent reservoir capacity calculations and terrain analysis. To correct these defects, existing projects almost entirely rely on manual TIN editing, manual edge trimming, and manual surface pressing. This is not only labor-intensive and inefficient, but also results in quality that is dominated by the operator's experience, with poor consistency and reproducibility, failing to meet the needs of large-scale and standardized reservoir production.

[0004] Existing similar technologies only focus on coordinate unification, data stitching, and conventional interpolation to supplement points. They have not designed dedicated models for the unique bank slope patterns of some reservoirs, which have large near-shore slopes and gradually become gentler towards the interior of the water area. They have not established a structured constraint relationship between the shoreline and sounding points, and they cannot fundamentally suppress TIN anomalies in network construction. They have always been unable to get rid of the dependence on manual editing. The industry has long lacked an automated, process-oriented, and reproducible integrated DEM construction framework for reservoirs. Summary of the Invention

[0005] The purpose of this invention is to overcome the shortcomings of the prior art and provide a method for constructing a water-land integrated DEM with constraints on the nearshore sounding blind zone of a reservoir. By establishing the nearshore constraint relationship from the shoreline point to the nearest sounding point, and using this as the structured basis for the reconstruction of the nearshore sounding blind zone, two control factors, the width of the sounding blind zone and the slope of the shore, are introduced to construct a two-factor adaptive nonlinear transition elevation point generation mechanism, which effectively alleviates the problems of abnormal slope breaks, sudden changes in local elevation differences, and topographic distortion at the boundary zone in the nearshore area.

[0006] To achieve the above objectives, the technical solution adopted by this invention is: a method for constructing a water-land integrated DEM constrained by nearshore sounding blind zones in a reservoir. The water-land integrated DEM construction method includes: Step S1, multi-source data preparation and coordinate unification; Step S2, extracting a shoreline layer using a water surface area layer as the boundary, and performing discrete sampling along the shoreline at equal intervals based on the line layer to generate a shoreline point set P; Step S3, establishing the shoreline point set P for each shoreline point... To the nearest depth sounding point The connection relationships are established to generate nearshore connection skeleton lines; Step S4: Extract the shore-side control elevation Z. shore,i bank slope S i Waterside control elevation Z bathy,i And associate it with the corresponding nearshore connection skeleton line; Step S5: According to the length of the nearshore connection skeleton line and bank slope S i The combination of parameters determines the exponential control parameter k corresponding to each nearshore connection skeleton line from the preset parameter mapping table. i and transition point step size h i Step S6: Based on the transition point step size h i Multiple nearshore transition elevation points Q are generated along each nearshore connecting skeleton line. ij And based on the exponential control parameter k i Calculate its elevation Z ij Step S7: Decrypt the shoreline layer extracted in Step S2, and assign vertex elevations to the encrypted shoreline based on the land area DEM to obtain a three-dimensional shoreline constraint line with vertex information; Step S8: Construct a constrained TIN terrain surface based on the three-dimensional shoreline constraint line and the total point set M; Step S9: Convert the constrained TIN terrain surface into a DEM and perform smoothing processing.

[0007] Preferably, the multi-source data includes land LiDAR point clouds, single-beam bathymetry points, surface area layers, and line layers; the land LiDAR point clouds are processed by ground point classification, and non-ground points are removed to generate land LiDAR ground points, and a land DEM is constructed based on the land LiDAR ground points; the single-beam bathymetry points include planar coordinates and underwater elevation.

[0008] Preferably, the length L of the nearshore connecting skeleton line i It can be expressed as follows:

[0009]

[0010] In the formula: Represents the length of the i-th nearshore connecting line; (x si y si ( ) is the shoreline point Plane coordinates; (x bi y bi ) is the point on the shoreline Corresponding nearest depth sounding point The plane coordinates.

[0011] Preferably, the preset parameter mapping relationship is respectively applied to the nearshore connection skeleton line length L i and bank slope S i The system is classified, and corresponding index control parameters k are configured for different combinations of length and slope grades. i and transition point step size h i ;

[0012] For the j-th nearshore transition elevation point Q on the i-th nearshore connecting skeleton line ij Its distance from the shoreline point P i The distance along the line is:

[0013]

[0014] The nearshore transition elevation point Q ij The normalized distance is:

[0015] , where 0≤t ij ≤1

[0016] A nonlinear elevation transition function from the shore to the waterside is constructed using a normalized exponential model:

[0017]

[0018] The nearshore transition elevation point Q ij Elevation Z ij for:

[0019]

[0020] In the formula: k i Z is the exponential control parameter. shore,i For the control elevation on the shore side; Z bathy,i The elevation is controlled by the water side.

[0021] Preferably, the shore-side control elevation Z shore,i Based on the shoreline points of the land area DEM Extracted elevation values; the waterside control elevation Z bathy,i It is based on the underwater elevation read from the sounding points corresponding to the endpoints of each nearshore connecting line.

[0022] Preferably, the smoothing process is performed using... Neighborhood mean smoothing, the smoothing result is denoted as Z. smooth ,

[0023]

[0024] In the formula: m and n are the row index and column index of the cell in the neighborhood, and Z(m, n) is the elevation value of cell (m, n).

[0025] This invention also discloses a water-land integrated DEM construction system constrained by nearshore sounding blind zone of a reservoir, including a preprocessing module, a shoreline point set construction module, a shoreline skeleton construction module, an elevation and slope extraction module, an adaptive parameter determination module, a nearshore transition elevation point set construction module, a three-dimensional shoreline construction module, a constrained TIN construction module, and a DEM construction module;

[0026] The preprocessing module is used for multi-source data preparation and coordinate unification.

[0027] The shoreline point set construction module is used to extract the shoreline line layer with the water surface area layer as the boundary, and to perform discrete sampling along the shoreline at equal intervals based on the line layer to generate the shoreline point set P;

[0028] The shoreline skeleton construction module is used to establish the connection relationship between each shoreline point in the shoreline point set P and the nearest sounding point, and to generate the nearshore connection skeleton line.

[0029] The elevation and slope extraction module is used to extract the control elevation Z on the bank side. shore,i bank slope S i Waterside control elevation Z bathy,i And associate it with the corresponding nearshore connection skeleton line;

[0030] The adaptive parameter determination module is used to determine the parameters based on the length of the nearshore connection skeleton line. and bank slope S i The combination of parameters determines the exponential control parameter k corresponding to each nearshore connection skeleton line from the preset parameter mapping table. i and transition point step size h i ;

[0031] The nearshore transition elevation point set construction module is used to construct the transition point step size h. iMultiple nearshore transition elevation points Q are generated along each nearshore connecting skeleton line. ij And based on the exponential control parameter k i Calculate its elevation Z ij This forms the nearshore transition elevation point set Q;

[0032] The three-dimensional shoreline construction module is used to encrypt the shoreline layer and assign vertex elevations to the encrypted shoreline based on the land area DEM to obtain a three-dimensional shoreline constraint line with vertex information.

[0033] The constrained TIN construction module is used to construct a constrained TIN terrain surface based on the three-dimensional shoreline constraint line and the total point set M.

[0034] The DEM construction module is used to convert constrained TIN terrain surfaces into DEMs and perform smoothing.

[0035] Compared with the prior art, the present invention has the following advantages:

[0036] 1. This invention establishes the nearshore constraint relationship from the shoreline point to the nearest sounding point, and uses this as the structured basis for the reconstruction of the nearshore sounding blind zone. On this basis, two control factors, the width of the sounding blind zone and the slope of the shore, are introduced to construct a two-factor adaptive nonlinear transition elevation point generation mechanism, which effectively alleviates the problems of abnormal slope breaks, sudden changes in local elevation differences, and topographic distortion in the boundary zone in the nearshore area.

[0037] 2. This invention densifies and assigns elevation values ​​to the shoreline to form an elevation-assigned three-dimensional shoreline feature constraint line, which is then used as the constraint line input for the TIN surface. This provides geometric constraints on the triangular network construction process at the land-water interface, effectively suppressing the free crossing of triangular networks at the land-water interface and reducing abnormal triangular surfaces, shoreline morphology distortion, and hard boundary barriers.

[0038] The present invention will now be described in further detail with reference to the accompanying drawings and embodiments. Attached Figure Description

[0039] Figure 1 This is a schematic diagram of the method flow of the present invention;

[0040] Figure 2 This is a schematic diagram of the system structure of the present invention;

[0041] Figure 3 This is a schematic diagram showing the relationship between the depth sounding point and the water surface in this invention;

[0042] Figure 4 This is a DEM result diagram of the present invention. Detailed Implementation

[0043] Example 1:

[0044] like Figure 1 As shown, this invention discloses a method for constructing a land-water integrated DEM (Digital Elevation Model) constrained by near-shore sounding blind zones in a reservoir. The land-water integrated DEM construction method includes:

[0045] Step S1: Multi-source data preparation and coordinate unification;

[0046] The multi-source data includes land LiDAR point clouds, single-beam bathymetry points, surface and line layers of water; all data are unified to the same plane coordinate system and unified elevation datum; the land LiDAR point clouds are processed by ground point classification, and non-ground points are removed to generate land LiDAR ground points, and a land DEM is constructed based on the land LiDAR ground points; the single-beam bathymetry points include plane coordinates and underwater elevation.

[0047] Step S2: Extract the shoreline layer using the water surface area layer as the boundary, and perform discrete sampling along the shoreline at equal intervals based on the line layer to generate the shoreline point set P;

[0048] Discrete sampling is performed along the shoreline at fixed intervals Δs, preferably Δs=10m, to generate a shoreline point set. Each shoreline point Record the shoreline number and cumulative distance along the shoreline, and shoreline points. It serves as the basic calculation unit for reconstructing nearshore sounding blind zones.

[0049] Step S3: Establish each shoreline point in the shoreline point set P. To the nearest depth sounding point Based on the connection relationships, generate nearshore connection skeleton lines; using the length of the nearshore connection skeleton lines... Characterizes the width of the nearshore sounding blind zone for the corresponding shoreline section;

[0050] For each shoreline point Search for the nearest sounding point in the single-beam sounding point set B. And establish a connecting line; the length of the connecting line can be used to characterize the width of the nearshore sounding blind zone of that shoreline section, shoreline points To the nearest depth sounding point The connection length is expressed by the following formula:

[0051] (1)

[0052] In the formula: Represents the length of the i-th nearshore connecting line; (x si y si ( ) is the shoreline point Plane coordinates; (x bi y bi ) is the point on the shoreline Corresponding nearest depth sounding point The plane coordinates.

[0053] Step S4: Extract the control elevation Z on the shore side. shore,i bank slope S i Waterside control elevation Z bathy,i And associate it with the corresponding nearshore connection skeleton line;

[0054] Ground points were extracted from the LiDAR point cloud data of the land area, and the influence of buildings and trees was removed to generate land area DEM data. Coastline points were then extracted based on the land area DEM data. The corresponding shore control elevation Z shore,i ; Generate a slope raster based on the land area DEM and add it to the shoreline points. Extracting the slope value of the bank slope , Used to characterize the steepness of the shoreline near the shoreline; based on each shoreline point Corresponding nearest depth sounding point Extracting underwater elevation values ​​for waterside control elevation Z bathy,i ; and control elevation Z on the shore side shore,i bank slope S i Waterside control elevation Z bathy,i This is then linked to the corresponding nearshore connection framework line; thus, each nearshore connection framework line now has a shore-side control elevation Z. shore,i bank slope S i Waterside control elevation Z bathy,i and depth sounding blind zone width .

[0055] Step S5: Based on the length of the nearshore connection skeleton line and bank slope S i The combination of parameters determines the exponential control parameter k corresponding to each nearshore connection skeleton line from the preset parameter mapping table. i and transition point step size h i ;

[0056] The preset parameter mapping relationship is respectively applied to the nearshore connection skeleton line length L i and bank slope S i The system is classified, and corresponding index control parameters k are configured for different combinations of length and slope grades. i and transition point step size h i Due to the varying widths of the sounding blind zones on different shore sections bank slope If the difference is significant, the adaptive control parameters should vary with the width of the sounding blind zone. and bank slope Adaptive adjustment.

[0057] Step S6: Based on the transition point step size h i Multiple nearshore transition elevation points Q are generated along each nearshore connecting skeleton line. ij And based on the exponential control parameter k i Calculate its elevation Z ij This forms the nearshore transition elevation point set Q;

[0058] For the j-th nearshore transition elevation point Q on the i-th nearshore connecting skeleton line ij Its distance from the shoreline point The distance along the line is:

[0059] (2)

[0060] The nearshore transition elevation point Q ij Normalize the distance as

[0061] , where 0≤t≤1 (3)

[0062] The exponential control parameter k i Substitute the normalized exponential elevation transition function to calculate the nearshore transition elevation point Q. ij Elevation Z ij :

[0063] A nonlinear elevation transition function from the shore to the waterside is constructed using a normalized exponential model:

[0064] (4)

[0065] The nearshore transition elevation point Q ij Elevation Z ij for:

[0066] (5)

[0067] In the formula: k i Z is the exponential control parameter. shore,i For the control elevation on the shore side; Z bathy,i The elevation is controlled by the water side.

[0068] Exponential control parameters The speed of the initial phase and the pace of the subsequent nearshore transition are determined by the width of the sounding blind zone. and bank slope Jointly determined, and at the same time, the step size of the nearshore transition point. Also based on the width of the depth sounding blind zone and bank slope The system is jointly determined; the elevation of transition points is calculated for each nearshore connecting skeleton line to form a set of nearshore transition points Q that conforms to the geometric characteristics of different shore sections; by establishing nearshore constraint relationships from shoreline points to the nearest sounding point, and using this as the structured basis for the reconstruction of nearshore sounding blind zones, two control factors, the width of the sounding blind zone and the slope of the shore, are introduced to facilitate the construction of a two-factor adaptive nonlinear transition elevation point generation mechanism, which effectively alleviates abnormal slope breaks, sudden changes in local elevation differences, and topographic distortion of the boundary zone in the nearshore area.

[0069] The nearshore transition elevation point set Q is clipped using a water surface area layer, retaining only the nearshore transition elevation points located within the water area.

[0070] Step S7: Encrypt the shoreline layer extracted in step S2, assign vertex elevations to the encrypted shoreline based on the land area DEM, and obtain a three-dimensional shoreline constraint line with vertex information.

[0071] To prevent the Triangulated Irregular Network (TIN) from freely crossing at the land-water interface, the shoreline layer extracted from the water surface layer in step S2 is densified before surface construction. Then, based on the land area DEM, elevations are assigned to each vertex of the densified shoreline, resulting in a 3D shoreline constraint line with vertex elevation information. This 3D shoreline constraint line is used as the surface construction constraint line input to the TIN. For scenarios with large shoreline slope differences and stronger junction constraint requirements, it can be used as a hard constraint line; for scenarios that need to reduce junction rigidity and soften boundary transitions, it can be used as a soft constraint line. By densifying the shoreline and assigning elevation values, an elevation-assigned 3D shoreline feature constraint line is formed and used as the constraint line input for TIN surface construction. This facilitates geometric constraints on the triangulation network construction process at the land-water interface, effectively suppressing abnormal crossings and reducing abnormal triangular faces, shoreline morphology distortion, and hard boundary barriers.

[0072] Step S8: Based on the three-dimensional shoreline constraint line and the total point set M, construct the constrained TIN terrain surface;

[0073] The total point set M includes the land LiDAR point cloud, single-beam bathymetry points, and the nearshore transition elevation point set Q generated in step S6. Using the total point set M as the mass point and the three-dimensional shoreline constructed in step S7 as the constraint line, a surface is constructed in the TIN environment to obtain the integrated land and water TIN topographic surface constrained by the nearshore bathymetry blind zone.

[0074] Step S9: Convert the constrained TIN terrain surface into a DEM and perform smoothing.

[0075] To mitigate the local pixel blockiness and residual abrupt changes at boundaries after rasterizing constrained TIN terrain surfaces, a small-window smoothing process was applied to the DEM. Neighborhood mean smoothing, the smoothing result is denoted as Z. smooth ,

[0076] (6)

[0077] In the formula: m and n are the row index and column index of the cell in the neighborhood, and Z(m, n) is the elevation value of cell (m, n).

[0078] Example 2:

[0079] like Figure 2 As shown, a water-land integrated DEM construction system constrained by nearshore sounding blind zone of a reservoir includes a preprocessing module, a shoreline point set construction module, a shoreline skeleton construction module, an elevation and slope extraction module, an adaptive parameter determination module, a nearshore transition elevation point set construction module, a three-dimensional shoreline construction module, a constrained TIN construction module, and a DEM construction module.

[0080] The preprocessing module is used for multi-source data preparation and coordinate unification.

[0081] The shoreline point set construction module is used to extract the shoreline line layer with the water surface area layer as the boundary, and to perform discrete sampling along the shoreline at equal intervals based on the line layer to generate the shoreline point set P;

[0082] The shoreline skeleton construction module is used to establish the shoreline point set P for each shoreline point. To the nearest depth sounding point The connection relationships are used to generate nearshore connection skeleton lines;

[0083] The elevation and slope extraction module is used to extract the control elevation Z on the bank side. shore,i bank slope S i Waterside control elevation Z bathy,i And associate it with the corresponding nearshore connection skeleton line;

[0084] The adaptive parameter determination module: uses the length of the nearshore connection skeleton line as a reference. and bank slope S i The combination of parameters determines the exponential control parameter k corresponding to each nearshore connection skeleton line from the preset parameter mapping table. i and transition point step size h i ;

[0085] The nearshore transition elevation point set construction module: uses a step size h based on the transition points. i Multiple nearshore transition elevation points Q are generated along each nearshore connecting skeleton line. ij And based on the exponential control parameter k i Calculate its elevation Z ij This forms the nearshore transition elevation point set Q;

[0086] The three-dimensional shoreline construction module is used to encrypt the shoreline layer and assign vertex elevations to the encrypted shoreline based on the land area DEM to obtain a three-dimensional shoreline constraint line with vertex information.

[0087] The constrained TIN construction module is used to construct a constrained TIN terrain surface based on the three-dimensional shoreline constraint line and the total point set M.

[0088] The DEM construction module is used to convert constrained TIN terrain surfaces into DEMs and perform smoothing.

[0089] Example 3:

[0090] This embodiment is implemented on ArcGIS 10.2 and MicroStation V8i platforms. The input data includes water surface area layer, land LiDAR point data and single beam bathymetry point data. After unifying all types of data into the same plane coordinate system and elevation datum, the method of this application is used to complete the reconstruction of nearshore bathymetry blind zone, the construction of three-dimensional shoreline feature constraint lines with vertex information, and the output of 10m resolution integrated land and water DEM results.

[0091] First, using the water surface area layer as the boundary base, ArcGIS is used to extract the shoreline layer, and shoreline points are generated by discrete sampling at fixed intervals along the shoreline. The fixed interval is 10m, and the source number of the shoreline and the cumulative distance along the shoreline are recorded to form a nearshore calculation unit.

[0092] like Figure 3 As shown, using shoreline points Starting from the single-beam bathymetry point, shoreline points are established using the single-beam bathymetry point as the nearest target. Establish the correspondence with the nearest sounding point and create a connecting line, specifying the length of the connecting line. It can be used to characterize the width of the nearshore sounding blind zone of this shoreline section, and further define the shoreline points. Connecting the nearest sounding points forms a nearshore connecting skeleton line, which represents the nearshore sounding blind zone between the shoreline and the underwater measurement points. This nearshore connecting skeleton line also serves as the subsequent shoreline control elevation Z. shore,i Waterside control elevation Z bathy,i and nearshore transition points The calculation provides a unified geometric framework.

[0093] The land area LiDAR point cloud data is classified into ground points to obtain land area LiDAR ground point cloud data. Then, a land area DEM is obtained using ArcGIS's TIN generation and TIN-to-raster conversion tools. Finally, the shoreline points of the land area DEM are analyzed. Elevation extraction was performed to obtain the shoreline control elevation Z for each shoreline point. shore,iTo reflect the differences in slope steepness across different shoreline sections, shoreline points were extracted after generating a slope raster based on the land area DEM. slope value at Simultaneously, the endpoint of the nearshore connecting skeleton line is extracted and a correspondence is established with the single-beam bathymetry points to obtain the underwater elevation corresponding to the endpoint of the connecting skeleton line, which serves as the waterside control elevation Z. bathy,i .

[0094] Complete the control elevation Z on the shore. shore,i bank slope S i Waterside control elevation Z bathy,i After extraction, the connection line number and length, among other attributes, are calculated on the nearshore connection skeleton line. Then, through methods such as starting point extraction and spatial connection, the shore-side control elevation Z is determined. shore,i bank slope S i Waterside control elevation Z bathy,i A unified connection skeleton line is attached to form a complete nearshore control unit. This nearshore control unit simultaneously possesses information on shoreline elevation, shore slope, underwater elevation, and depth sounding blind zone width.

[0095] With depth measurement blind zone width L i and bank slope S i As a joint control factor, the exponential parameter k is configured according to Table 1. i and transition point step size h i The elevations of each supplementary point are calculated using a hierarchical assignment method and a normalized index model, forming a nearshore transition point set Q that conforms to the geometric characteristics of different shore sections.

[0096] Table 1 Adaptive Hierarchy Table

[0097] <![CDATA[L i <20 m]]> <![CDATA[S i <8°]]> 1.8 2.0m <![CDATA[L i <20 m]]> <![CDATA[8°≤S i <20°]]> 2.4 2.0m <![CDATA[L i <20 m]]> <![CDATA[S i ≥20°]]> 3.0 1.5m <![CDATA[20m≤L i <50 m]]> <![CDATA[S i <8°]]> 3.0 2.0m <![CDATA[20m ≤L i <50 m]]> <![CDATA[8°≤S i <20°]]> 3.8 2.0m <![CDATA[20m ≤L i <50 m]]> <![CDATA[S i ≥20°]]> 4.6 1.5m <![CDATA[L i ≥50m]]> <![CDATA[S i <8°]]> 4.2 1.5m <![CDATA[L i ≥50m]]> <![CDATA[8°≤S i <20°]]> 5.0 1.0m <![CDATA[L i ≥50m]]> <![CDATA[S i ≥20°]]> 5.8 1.0m

[0098] Generate nearshore transition points Subsequently, the set of nearshore transition elevation points was trimmed according to the water surface area, retaining only the transition elevation points located within the water area to avoid the participation of land-based extrapolation points in underwater construction.

[0099] To control the crossing behavior of triangular networks at the land-water interface, a three-dimensional shoreline constraint line is further constructed. First, the shoreline layer is densified, and then the vertex elevations are assigned to the densified shorelines based on the land area DEM, forming a three-dimensional shoreline constraint line with elevation information. This three-dimensional shoreline constraint line is used as a soft constraint line or a hard constraint line during the surface construction stage to control the geometric orientation of the triangular network at the interface.

[0100] During the construction phase, land-based LiDAR ground points, single-beam bathymetry points, and near-shore transition points will be classified after ground point classification. After unifying the elevation fields, they are merged into a total point set M. Using the total point set M as the mass points and the three-dimensional shoreline as the constraint line, a constrained TIN topographic surface is constructed, realizing the land point, underwater measured point, and nearshore transition point. A unified building surface under shoreline constraints; the constrained TIN topographic surface is converted into a 10m resolution DEM, and the DEM is further processed. Neighborhood mean smoothing reduces the potential local blockiness and residual abrupt changes at boundaries that may occur after TIN-to-raster conversion, thus obtaining a final smooth integrated land and water DEM, such as... Figure 4 As shown.

[0101] Under conventional reservoir surveying data conditions and ArcGIS platform environment, this application can use the nearshore connection skeleton formed by shoreline points and the nearest sounding point as a basis, adaptively supplement nearshore points by the width of the sounding blind zone and the slope of the shoreline, and realize the automatic reconstruction of the nearshore sounding blind zone by three-dimensional shoreline constraint surface construction, reduce the workload of manual TIN trimming, and obtain a continuous, accuracy-controlled and reproducible integrated land and water DEM.

[0102] The above description is merely a preferred embodiment of the present invention and does not constitute any limitation on the present invention. Any simple modifications, alterations, or equivalent structural transformations made to the above embodiments based on the technical essence of the present invention shall still fall within the protection scope of the present invention.

Claims

1. A method for constructing an integrated land-water DEM constrained by near-shore sounding blind zones in a reservoir, characterized in that, The method for constructing an integrated land and water DEM includes: Step S1: Multi-source data preparation and coordinate unification; Step S2: Extract the shoreline layer using the water surface area layer as the boundary, and perform discrete sampling along the shoreline at equal intervals based on the line layer to generate the shoreline point set P; Step S3: Establish each shoreline point in the shoreline point set P. To the nearest depth sounding point The connection relationships are used to generate nearshore connection skeleton lines; Step S4: Extract the control elevation Z on the shore side. shore,i bank slope S i Waterside control elevation Z bathy,i And associate it with the corresponding nearshore connection skeleton line; Step S5: Based on the length of the nearshore connection skeleton line and bank slope S i The combination of parameters determines the exponential control parameter k corresponding to each nearshore connection skeleton line from the preset parameter mapping table. i and transition point step size h i ; Step S6: Based on the transition point step size h i Multiple nearshore transition elevation points Q are generated along each nearshore connecting skeleton line. ij And based on the exponential control parameter k i Calculate its elevation Z ij This forms the nearshore transition elevation point set Q; Step S7: Encrypt the shoreline layer extracted in step S2, and assign vertex elevations to the encrypted shoreline based on the land area DEM to obtain a three-dimensional shoreline constraint line with vertex information. Step S8: Based on the three-dimensional shoreline constraint line and the total point set M, construct the constrained TIN terrain surface; Step S9: Convert the constrained TIN terrain surface into a DEM and perform smoothing.

2. The method for constructing an integrated land-water DEM with near-shore sounding blind zone constraints for a reservoir according to claim 1, characterized in that, The multi-source data includes land LiDAR point clouds, single-beam bathymetry points, surface area layers and line layers; the land LiDAR point clouds are processed by ground point classification, and non-ground points are removed to generate land LiDAR ground points, and a land DEM is constructed based on the land LiDAR ground points; A single-beam bathymetry point includes both planar coordinates and underwater elevation.

3. The method for constructing an integrated land-water DEM with near-shore sounding blind zone constraints for a reservoir according to claim 1, characterized in that, The length L of the nearshore connecting skeleton line i It can be expressed as follows: ； In the formula: Represents the length of the i-th nearshore connecting line; (x si y si ( ) is the shoreline point Plane coordinates; (x bi y bi ) is the point on the shoreline Corresponding nearest depth sounding point The plane coordinates.

4. The method for constructing an integrated land-water DEM with nearshore sounding blind zone constraints for a reservoir according to claim 1, characterized in that, The preset parameter mapping relationship corresponds to the nearshore connection skeleton line length L. i and bank slope S i The system is classified, and corresponding index control parameters k are configured for different combinations of length and slope grades. i and transition point step size h i ; For the j-th nearshore transition elevation point Q on the i-th nearshore connecting skeleton line ij Its distance from the shoreline point P i The distance along the line is: ； The nearshore transition elevation point Q ij The normalized distance is: where 0 ≤ t ≤ 1; A nonlinear elevation transition function from the shore to the waterside is constructed using a normalized exponential model: ； The nearshore transition elevation point Q ij Elevation Z ij for: ； In the formula: k i Z is the exponential control parameter. shore,i For the control elevation on the shore side; Z bathy,i The elevation is controlled by the water side.

5. A method for constructing an integrated land-water DEM with nearshore sounding blind zone constraints for a reservoir, as described in claim 1, is characterized in that... The shore-side control elevation Z shore,i Based on the shoreline points of the land area DEM Extracted elevation values; The waterside control elevation Z bathy,i It is based on the underwater elevation read from the sounding points corresponding to the endpoints of each nearshore connecting line.

6. The method for constructing an integrated land-water DEM with nearshore sounding blind zone constraints for a reservoir according to claim 1, characterized in that, The smoothing process is adopted as follows: Neighborhood mean smoothing, the smoothing result is denoted as Z. smooth , ； In the formula: m and n are the row index and column index of the cell in the neighborhood, and Z(m, n) is the elevation value of cell (m, n).

7. A water-land integrated DEM construction system for implementing the nearshore sounding blind zone constraint of a reservoir as described in any one of claims 1 to 5, comprising a preprocessing module, a shoreline point set construction module, a shoreline skeleton construction module, an elevation and slope extraction module, an adaptive parameter determination module, a nearshore transition elevation point set construction module, a three-dimensional shoreline construction module, a constrained TIN construction module, and a DEM construction module; The preprocessing module is used for multi-source data preparation and coordinate unification. The shoreline point set construction module is used to extract the shoreline line layer with the water surface area layer as the boundary, and to perform discrete sampling along the shoreline at equal intervals based on the line layer to generate the shoreline point set P; The shoreline skeleton construction module is used to establish the connection relationship between each shoreline point in the shoreline point set P and the nearest sounding point, and to generate the nearshore connection skeleton line. The elevation and slope extraction module is used to extract the control elevation Z on the bank side. shore,i bank slope S i Waterside control elevation Z bathy,i And associate it with the corresponding nearshore connection skeleton line; The adaptive parameter determination module is used to determine the parameters based on the length of the nearshore connection skeleton line. and bank slope S i The combination of parameters determines the exponential control parameter k corresponding to each nearshore connection skeleton line from the preset parameter mapping table. i and transition point step size h i ; The nearshore transition elevation point set construction module is used to construct the transition point step size h. i Multiple nearshore transition elevation points Q are generated along each nearshore connecting skeleton line. ij And based on the exponential control parameter k i Calculate its elevation Z ij This forms the nearshore transition elevation point set Q; The three-dimensional shoreline construction module is used to encrypt the shoreline layer and assign vertex elevations to the encrypted shoreline based on the land area DEM to obtain a three-dimensional shoreline constraint line with vertex information. The constrained TIN construction module is used to construct a constrained TIN terrain surface based on the three-dimensional shoreline constraint line and the total point set M. The DEM construction module is used to convert constrained TIN terrain surfaces into DEMs and perform smoothing.

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