Coastal SBT-DEM construction method based on UAV and unmanned ship

Abstract

The present invention discloses a method for constructing a coastal zone SBT-DEM based on an unmanned aerial vehicle and an unmanned ship, comprising: step S1: within the coastal zone survey area, use an unmanned aerial vehicle laser radar and a depth-measuring unmanned ship to measure the coastal zone topography and water depth; step S2: error correction, coordinate solution, and benchmark conversion processing are performed on the original land point cloud data measured by the unmanned aerial vehicle and the water depth data measured by the unmanned ship to obtain the three-dimensional coordinate points of the land and seabed in the survey area in the same coordinate system; step S3: using a geographic information system spatial data processing method, respectively obtain the DEM of the land and the seabed, perform seamless mosaic processing, and obtain the coastal zone SBT-DEM. The present invention solves the problems of low water depth accuracy in nearshore shallow waters, low spatial resolution of the constructed SBT-DEM, and complex and cumbersome construction technology process in the prior art, and realizes the simple, rapid and refined construction of the coastal zone SBT-DEM.

Description

Technical Field

[0001] The present invention relates to the field of computer vision technology, and in particular to a method for constructing a coastal zone SBT-DEM based on an unmanned aerial vehicle (UAV) and an unmanned ship. Background Art

[0002] The coastal zone is considered to be one of the most active areas of land-sea interaction. In order to better understand the coastal zone, many coastal applications require land-sea integrated terrain data, such as tsunami propagation and coastal inundation modeling, coastal erosion and siltation monitoring, hydrodynamics and sediment transport modeling. SBT-DEM is a digital elevation model that seamlessly splices water depth and terrain data, which is the basis for coastal process modeling.

[0003] In the prior art, the construction method of coastal SBT-DEM is mainly to integrate airborne laser radar (LiDAR) topographic survey data and shipborne single-beam / multi-beam water depth measurement data for spatial interpolation. However, due to the large draft value, the survey ship cannot perform water depth measurement in shallow waters, which leads to data gaps in the nearshore shallow water area. In order to fill the nearshore data gaps, the existing solutions mainly include: direct interpolation construction based on land topography and nearshore water depth data, optical remote sensing nearshore shallow water depth inversion, and airborne laser radar water depth measurement. Among them, the direct interpolation method is obviously unable to truly reflect the water depth of the nearshore shallow water area, the water depth remote sensing inversion accuracy is low, and the expensive airborne laser radar water depth measurement accuracy will be greatly reduced with the increase of water turbidity. Because it is difficult to obtain high-precision nearshore water depth data with existing measurement technology, the construction of a fine SBT-DEM has been difficult to achieve. In addition, the operation cost of manned aircraft laser radar and manned sounding ship is high, the personnel safety is low, and the deployment process is complicated.

[0004] With the advancement of measurement technology, unmanned aerial vehicle lidar and acoustic bathymetric unmanned ships have been successfully developed. Both unmanned ships and unmanned aerial vehicles have the advantages of small size, high integration, simple operation, low cost, flexible operation time and easy transportation. In recent years, unmanned aerial vehicle lidar has been widely used in land topography surveying, three-dimensional modeling, forest resource survey, etc., and bathymetric unmanned ships have been widely used in water depth measurement and underwater topography mapping in rivers, lakes and offshore areas. Unmanned ships are small in size and light in weight, so their draft value is small. Therefore, unmanned ships can well solve the problem of shallow water depth measurement near the coast, which provides a technical prerequisite for seamless high-precision data acquisition for SBT-DEM construction. However, there is still a lack of effective solutions for the construction of coastal SBT-DEM based on unmanned aerial vehicle lidar and bathymetric unmanned ships, and fine SBT-DEM is of great significance to coastal process monitoring and modeling. Therefore, it is necessary to provide technical solutions to existing problems.

[0005] The shortcomings of the existing coastal seamless bathymetric and topographic digital elevation model (SBT-DEM) construction technology are as follows:

[0006] (1) The existing technology integrates topographic survey data based on airborne lidar and water depth measurement data based on shipborne single-beam / multi-beam to construct SBT-DEM. However, due to the large draft of the survey ship, it is impossible to perform water depth measurement operations in dangerous shallow waters. This leads to data gaps in the nearshore shallow water area, and the existing methods are difficult to achieve high-precision filling.

[0007] (2) Existing technology is still at the stage of constructing SBT-DEM with medium spatial resolution (10 or 30 m), while some fine-scale coastal applications require high-resolution SBT-DEM.

[0008] (3) Existing topographic survey and bathymetric data use different measurement datums. The unification of horizontal and vertical datums of multi-source data is a complex and tedious process.

[0009] (4) Traditional manned aircraft lidar and manned bathymetric vessels have high operating costs, low personnel safety, and complex deployment processes. Summary of the invention

[0010] In view of the above-mentioned deficiencies in the prior art, the present invention provides a method for constructing SBT-DEM of the coastal zone based on unmanned aerial vehicles and unmanned ships. The method realizes seamless measurement of water depth and terrain of the coastal zone by combining unmanned aerial vehicle lidar and bathymetric unmanned ships into an unmanned measurement system, and then realizes fine-scale SBT-DEM construction based on geographic information system technology, thereby obtaining a high-precision and high-resolution SBT-DEM of the coastal zone.

[0011] In order to achieve the above object, the technical solution of the present invention is:

[0012] The coastal zone SBT-DEM construction method based on drones and unmanned ships includes the following steps:

[0013] Step S1: In the coastal zone survey area, the UAV laser radar and the depth measuring unmanned ship are used to measure the coastal zone topography and water depth to obtain the original land point cloud data and water depth point cloud data;

[0014] Step S2: error correction, coordinate calculation, and benchmark conversion are performed on the original land point cloud data and water depth data to obtain the three-dimensional coordinate point data of the land and seabed in the survey area in the same coordinate system;

[0015] Step S3: Use the geographic information system spatial data processing method to obtain the DEM of the land and the seabed respectively, perform seamless mosaic processing, and obtain the coastal zone SBT-DEM.

[0016] The step S1 is specifically as follows:

[0017] Step S11: Survey the survey area and collect remote sensing image maps, select the operation date and time according to the weather and sea condition forecast data, and select the control points and measurement points in the survey area; the survey area is the area where the coastal zone extends to the land and the sea respectively, including the land area and the sea area, and the two overlap to form the intertidal zone; the control points are the existing topographic survey points, and the measurement points are the topographic points of the target to be monitored, which are used for subsequent calculation and verification;

[0018] Step S12: Calculate the error correction value according to the control point coordinates;

[0019] Step S13: When the intertidal zone is exposed during low tide, the coordinate data of the measuring points of the intertidal zone are collected in the survey area by using a handheld GNSS RTK device, and corrected according to the error correction value to obtain the coordinate data of the standard measuring points in the required plane and elevation coordinate systems after correction; part of the standard data and standard points are used for the accuracy control of the measuring point data of the drone and the unmanned boat, and the other part of the standard data is used as verification points for the subsequent SBT-DEM accuracy verification;

[0020] Step S14: During the high tide period with relatively small wind and waves, the unmanned boat is controlled in automatic cruise mode to measure the water depth in the sea area along the set trajectory to obtain the original water depth point cloud data; at the same time, the seawater temperature, salinity and depth parameters are measured to calculate the actual seawater sound velocity value;

[0021] Step S15: During low tide, the UAV is controlled in automatic cruise mode to measure the land terrain along the set target track line to obtain original land point cloud data;

[0022] Among them, the measurement data of unmanned ships and drones overlap in the intertidal zone.

[0023] The calculation of the error correction value includes: collecting the measured coordinate data of at least three control points, and subtracting them from the existing standard coordinate data in three dimensions, and then taking the average to obtain the error correction values ​​(a, b, c) in three directions.

[0024] The measurement trajectory of the unmanned ship is in two directions: the main measurement line is arranged perpendicular to the coast, and the inspection line is arranged parallel to the coast; the unmanned ship sails and measures along the main measurement line and the inspection line;

[0025] The measurement line of the UAV is arranged parallel to the coast.

[0026] The control of the unmanned boat to perform water depth measurement is achieved by using a single-beam echo sounder or a multi-beam echo sounder carried by the unmanned boat; the control of the drone to perform land measurement is achieved by using a laser radar sensor device carried by the drone.

[0027] The step S2 is specifically as follows:

[0028] Step S21: Combine the static GNSS data of the base station and the POS positioning and orientation data of the UAV during flight to perform navigation and calculation to obtain the track file of the UAV: ​​the real track line and real-time attitude angle of the UAV; the POS positioning and orientation data includes GNSS positioning and IMU attitude and orientation data;

[0029] Step S22: performing point cloud solution based on the original land point cloud data and the track file of the UAV to obtain a land laser point cloud, deleting deviation points, and outputting a land point cloud file in LAS format;

[0030] Step S23: a. Filter out abnormal depth points from the original depth data of the echo sounder; b. Use the actual seawater sound velocity calculated to correct the depth data; c. Finally, use the real-time attitude angle data recorded by the attitude sensor of the unmanned ship to correct the depth data, the attitude angle data includes the pitch angle and the roll angle, and obtain the depth correction data z' of the echo sounder;

[0031] Step S24: Calculate the seabed three-dimensional coordinate point cloud data (x, y, zt-z') based on the three-dimensional coordinate data (x, y, z) of the GNSS receiver carried by the unmanned ship, the depth correction data z' of the echo sounder, and the fixed height t from the phase center of the GNSS receiver antenna to the bottom center of the echo sounder transducer;

[0032] Step S25: unify the coordinate systems of the land point cloud and the seabed point cloud to obtain the three-dimensional coordinate point clouds of the land and the seabed in the same coordinate system.

[0033] The step S3 is specifically as follows:

[0034] Step S31: Based on the overlapping data of the submarine topography point cloud and the land topography point cloud in the intertidal zone, the fixed errors of the submarine topography point cloud and the land topography point cloud are calculated using the standard point coordinates, and the fixed error correction is performed on the elevation values ​​of all the submarine topography point cloud data and the land topography point cloud data;

[0035] Step S32: Generate a seafloor DEM using a spatial interpolation method based on the seafloor topography point cloud after fixed error correction;

[0036] Step S33: Based on the land point cloud after the fixed error correction, use point cloud filtering to separate ground points and non-ground points, and use a spatial interpolation method for the ground points to generate a land DEM; the use of point cloud filtering to separate ground points and non-ground points includes distinguishing ground points and non-ground points according to an empirical threshold in the elevation z direction;

[0037] Step S34: Generate a one-sided buffer zone starting from the sea-side boundary of the land-sea DEM overlap zone toward the land direction, perform DEM mosaic operation in the buffer zone using the inverse distance weighted mosaic method, retain the land DEM that meets the accuracy threshold requirement in the non-buffered area in the overlap zone as the output result; the land-sea DEM in the non-overlapping area is directly output without being processed; and is used to obtain a coastal zone SBT-DEM that meets both seamless smooth splicing and low elevation accuracy loss; the coastal zone SBT-DEM includes the estimated elevation values ​​of each location;

[0038] Step S35: Based on the vertical distance L from the theoretical depth reference plane to the mean sea level of the two nearest tide gauge stations in the measurement area A , L B and the plane distance D from the two stations to the survey area A , D B , use the inverse distance weighted method to calculate the L value of the survey area: L = (D B L A +D A L B ) / (D A +D B ), and then perform vertical datum conversion to obtain the SBT-DEM of the chart datum.

[0039] Step S35 also uses the following visualization method to draw:

[0040] The SBT-DEM image of the chart datum is colored with different colors to distinguish the elevation data;

[0041] Depth contours are drawn on the SBT-DEM image of the chart datum.

[0042] The inverse distance weighted mosaic algorithm in step S34 is specifically:

[0043]

[0044] Where Z is the elevation value of the output pixel in the overlapping area, and the elevation values ​​of the land and seabed DEM overlaps are Z Land and Z Seabed , D1 and D2 are the distances from pixel P to the edge in the overlapping area.

[0045] The method for constructing coastal zone SBT-DEM based on drones and unmanned ships also includes step S4 of evaluating the accuracy of SBT-DEM using terrain verification points measured by RTK, which is specifically:

[0046] Based on the terrain verification points collected by handheld GNSS RTK, the elevation accuracy of SBT-DEM is evaluated using the mean absolute error (MAE) and root mean square error (RMSE):

[0047]

[0048]

[0049] In the formula, h i is the elevation value estimated by DEM, h i ' is the standard elevation value of the verification point measured by handheld RTK, and n is the number of terrain verification points.

[0050] The present invention has the following beneficial effects and advantages:

[0051] 1. The present invention utilizes UAV laser radar and unmanned sounding boat to carry out collaborative operations at the same time and on the same basis, thus solving the problem of seamless high-precision measurement of coastal topography and water depth. Combined with the spatial data processing technology of the geographic information system, the construction of fine-scale coastal SBT-DEM is realized.

[0052] 2. The present invention has the advantages of high feasibility, simple and efficient technical process, high resolution and accuracy of DEM products, low measurement operation cost and high personnel safety, and is worthy of further promotion and application in coastal engineering and scientific research.

[0053] 3. The present invention solves the problems of high operating cost, low personnel safety, and complex deployment process of existing manned aircraft lidar and manned sounding ships, and realizes the measurement and collection of high-precision and seamless coastal terrain and water depth data in a simple, fast, safe, efficient and low operating cost manner.

[0054] 4. The present invention solves the problems existing in the prior art, such as low water depth accuracy in nearshore shallow water areas, low spatial resolution of the constructed SBT-DEM, and complicated and cumbersome construction technical process, and realizes the simple, rapid and refined construction of SBT-DEM in the coastal zone. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] Figure 1 This is a schematic diagram of the principle of the inverse distance weighted DEM mosaic method;

[0056] Figure 2 A schematic diagram of a method flow of an embodiment of the present invention;

[0057] Figure 3The coastal zone SBT-DEM constructed for the embodiment of the present invention;

[0058] Figure 4 A three-dimensional terrain model generated by the SBT-DEM constructed in an embodiment of the present invention;

[0059] Figure 5 The SBT-DEM of the chart datum constructed for the embodiment of the present invention;

[0060] Figure 6 Comparison of the effects of the 1m resolution SBT-DEM constructed for the embodiment of the present invention and the medium resolution DEM (10 or 30m); DETAILED DESCRIPTION

[0061] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0062] The Galaxy No. 1 GNSS RTK used in the embodiment of the present invention is produced by Southern Surveying and Mapping Co., Ltd.; the SE40 unmanned boat used is produced by Zhuhai Yunzhou Co., Ltd. and is equipped with an SDE-18S single-beam echo sounder; the DV-LiDAR20 multi-rotor drone used is produced by Pegasus Robotics Co., Ltd. and is equipped with a RIEGL VUX-1UAV22 three-dimensional laser scanning system. In terms of offshore water depth measurement, the unmanned boat used in the present invention is equipped with a single-beam echo sounder, and the method can also be completed by carrying a multi-beam echo sounder, and the principle and technical process are similar.

[0063] Please refer to Figure 2 The present invention provides a method for constructing a coastal zone SBT-DEM based on an unmanned aerial vehicle and an unmanned ship, comprising the following steps:

[0064] Step S1: Use UAV laser radar and bathymetric unmanned boat to seamlessly measure coastal terrain and water depth, and obtain original land point cloud data and water depth point cloud data. Both the UAV and the unmanned boat adopt GNSS (Global Navigation Satellite System) network RTK (Real-Time Kinematics) measurement and positioning mode, and use handheld network RTK to measure terrain control points and verification points;

[0065] Step S2: error correction, coordinate calculation, datum conversion and other processing are performed on the land point cloud data measured by the UAV and the water depth point cloud data measured by the unmanned ship to obtain the land and seabed three-dimensional coordinate point data in the CGCS2000 Gaussian projection plane coordinate system and the 1985 national elevation datum;

[0066] Step S3: Use the spatial data processing tools of Point Cloud Cube (PCM) and ArcGIS software to first obtain the land and seabed DEMs respectively, and then use ArcGIS software to seamlessly mosaic them to obtain the coastal zone SBT-DEM;

[0067] Step S4: Based on the terrain verification points measured by RTK, the elevation accuracy of SBT-DEM is evaluated using MAE and RMSE indicators.

[0068] Preferably, in this embodiment, the step S1 is specifically:

[0069] Step S11: In this embodiment, the beach and nearshore waters of Muping District, Yantai City, Shandong Province are taken as the survey area. Before the survey operation, remote sensing images of the survey area are obtained and field surveys are conducted. The operation date and time period are selected according to the weather forecast information and the sea condition forecast data of the tidal software, and the standard data of the existing terrain control points in the survey area and its vicinity are collected (the standard coordinate point data published by the state);

[0070] Step S12: Collect the measured coordinate data of the three control points, and make a difference with the existing standard coordinate data in three dimensions, and then take the average to obtain the error correction values ​​(a, b, c) in three directions; Use a handheld GNSS RTK device to collect the coordinate data of the measuring point, and correct it according to the error correction value to obtain the coordinate data of the measuring point in the CGCS2000 Gaussian projection plane coordinate system and the 1985 national height datum after correction;

[0071] Step S13: October 29, 2021, 9:00-11:00 am is the low tide period of the day. Handheld GNSS RTK equipment is used in the survey area to collect coordinate data of standard measurement points in the intertidal zone. Part of the data is used as standard points for accuracy control of drone and unmanned boat measurement point data, and the other part is used as verification points for subsequent SBT-DEM accuracy verification.

[0072] Step S14: Nearshore water depth measurement using an unmanned ship: 7:00-12:00 on the morning of October 30, 2021 is the high tide period of the day. It is sunny, the wind force is level 1 (0.3-1.5 m / s), the wave height is 0.1-0.2 m, the ocean current velocity is 0-0.2 m / s, and there are no fishing nets and aquatic plants in the working sea area. Such hydrological and meteorological conditions and environmental conditions are conducive to the depth measurement operation of the unmanned ship. Based on the unmanned ship hydrological measurement software, the navigation path of the unmanned ship is planned. The main survey line is arranged perpendicular to the coastline with an interval of 8 m, and the inspection line is arranged parallel to the coastline with an interval of 50 m. The unmanned ship automatically navigates and measures along the planned path with a sampling interval of 1 m. The surveyors use manual remote control mode to operate the unmanned ship to navigate and measure in ultra-shallow waters. The seawater sound velocity value first uses the general empirical value of 1500 m / s. At the same time, a multi-parameter water quality meter is used to measure the temperature, salinity and depth parameters of seawater and calculate the actual seawater sound velocity value;

[0073] Step S15: Coastal land topography measurement using UAV lidar: October 29, 2021, 9:00-11:00 am is the low tide period of the day. It is sunny, the temperature is 22°C, and the wind force is level 3 (3.4-5.4m / s). Such meteorological conditions are very conducive to the measurement of UAVs. Based on the UAV butler software, 4 routes are planned parallel to the coastline. The route spacing is 112m, the mapping scale is 1:500, the flight altitude is 140m, the flight speed is 8m / s, the laser emission frequency is 400kHz, and the point cloud density is 34 points / m 2 The lateral overlap is 60%. The automatic cruise mode is used to carry out topographic survey along the trajectory line. The measurement data of the unmanned ship and the UAV have a certain overlapping area in the intertidal zone.

[0074] Preferably, in this embodiment, step S2 is specifically:

[0075] Step S21: Use the Inertial Explorer software to perform combined navigation solution on the static GNSS data of the base station and the POS (Position and Orientation System) (GNSS + Inertial Measurement Unit IMU) data of the UAV to obtain the track file of the UAV. After the solution is completed, check the attitude and position accuracy to ensure the accuracy of the track;

[0076] Step S22: using the drone manager software, based on the original laser data (original land point cloud data) and the track file, perform point cloud solution calculation to obtain the land laser point cloud, delete the deviation points, and finally output it as a land point cloud file in a standard format (LAS);

[0077] Step S23: Use the unmanned ship hydrographic survey software to filter out abnormal water depth points (the abnormal points are determined based on empirical thresholds) from the original sounding data of the echo sounder (the original water depth s is the distance from the bottom center of the transducer of the echo sounder to the seabed mud surface) and then use the actual seawater sound velocity to correct the water depth data. Finally, the water depth data is subjected to attitude correction using the real-time attitude angle data recorded by the attitude sensor (the attitude angle data includes the pitch angle and the roll angle), and the depth correction data z' of the echo sounder is obtained; the sound speed correction includes: using the measured actual seawater sound speed to calculate the sound speed correction number v of the water depth data point by point, and then adding the sound speed correction number (s+v) to the original water depth; the attitude correction includes: using the real-time attitude angle data to calculate the attitude correction number m of the water depth data after the sound speed correction point by point, and then adding the attitude correction number (s+v+m) to the water depth data after the sound speed correction, and obtaining the water depth correction data z': z'=s+v+m;

[0078] Step S24: using the unmanned ship hydrographic survey software, the three-dimensional coordinate point cloud data (x, y, zt-z') of the seabed is calculated based on the three-dimensional coordinate data (x, y, z) of the GNSS receiver carried by the unmanned ship, the depth correction data z' of the echo sounder, and the fixed height t (0.62m) from the phase center of the GNSS receiver antenna to the bottom center of the echo sounder transducer, and finally output as a coordinate point file in dat format;

[0079] Step S25: Perform benchmark conversion on the land point cloud and the seabed point cloud to obtain the land and seabed three-dimensional coordinate point clouds in the plane coordinate system of the CGCS2000 Gaussian three-dimensional zone projection and the 1985 national elevation benchmark.

[0080] Preferably, in this embodiment, step S3 is specifically:

[0081] Step S31: Based on the overlapping data of the seabed terrain point cloud and the land terrain point cloud in the intertidal zone, the coordinates of the terrain standard points collected by the handheld RTK in the intertidal zone are used to calculate the fixed errors of the seabed and land terrain point clouds respectively, and fixed error correction is performed on all seabed and land terrain point cloud data respectively; the calculation of the fixed error includes: randomly sampling at least 3 points, and calculating the average of the elevation difference with the standard point as the fixed error; the fixed error correction of the point cloud data includes: subtracting the fixed error from the elevation value of the point cloud data; the elevation value is the z value in (x, y, z).

[0082] Step S32: Based on the fixed error corrected seabed terrain point cloud, use the 3D analysis tool of ArcGIS software to perform spatial interpolation on the seabed terrain, use the Create TIN tool to generate an irregular triangulated network (TIN) based on the seabed terrain points, and use the natural neighbor interpolation method of the TIN to Raster tool to generate a seabed DEM based on the TIN, with a grid resolution of 1m;

[0083] Step S33: Based on the land terrain point cloud after fixed error correction, the PCM software is used to construct the coastal land terrain. First, the point cloud filter is used to separate the ground points and the non-ground points, and the land DEM is generated by the spatial interpolation method for the ground points; according to the boundary between the artificial construction land and the natural beach, the natural beach point cloud is cut out. There are a small number of fishing boats, vehicles and herbaceous plants on the natural beach. The cloth simulation filter algorithm is used to separate the ground points and the non-ground points. The cloth resolution is 2m, the maximum number of iterations is 200, the classification threshold is 0.5m, and the cloth hardness is hilly. After obtaining the ground point cloud, the inverse distance weighted interpolation method is used to construct the land DEM, the interpolation radius is 3m, and the grid resolution is 1m;

[0084] Step S34: Based on ArcGIS software, a buffer tool is used to generate a unilateral buffer with a radius of 3m from the sea side boundary of the sea-land DEM overlap area to the land direction. The inverse distance weighted mosaic method BLEND of the mosaic to new raster tool is used to perform DEM mosaic operation in the buffer. Only the land DEM with higher accuracy is retained as the output result in other areas in the overlapping area. The sea and land DEM in the non-overlapping area is directly output without processing. Python Arcpy is used to compile the above mosaic processing process into an automated program. After the program is run, the coastal zone SBT-DEM ( Figure 3 ), and then use ArcScene software to visualize the DEM in three dimensions ( Figure 4 ), the vertical exaggeration is 10, and finally the map is produced and output;

[0085] Furthermore, the inverse distance weighted mosaic algorithm in step S34 is specifically:

[0086]

[0087] Where Z is the elevation value of the output pixel in the overlapping area, and the elevation values ​​of the land and seabed DEM overlaps are Z Land and Z Seabed , D1 and D2 are the distances from pixel P to the edge in the overlap area ( Figure 1 ), the pixel is the grid cell P in the overlapping area.

[0088] Step S35: According to the tide station data of the Global Tide Forecast Service Platform (http: / / global-tide.nmdis.org.cn), based on the L values ​​of the Yantai and Weihai stations closest to the survey area, the vertical distance L value between the theoretical depth reference surface and the mean sea level of the survey area is calculated using the inverse distance weighted method, and then the vertical reference conversion is performed in ArcGIS software, and then the contour line tool is used to create 1m contour lines to obtain the SBT-DEM of the chart reference ( Figure 5 ).

[0089] Preferably, in this embodiment, step S4 is specifically as follows:

[0090] Based on the terrain verification points measured by RTK, MAE and RMSE are used as the elevation accuracy evaluation factors of SBT-DEM. Further, the step S4 is specifically as follows:

[0091] Based on the terrain verification points measured by handheld GNSS RTK, the elevation accuracy of SBT-DEM is evaluated using the mean absolute error (MAE) and root mean square error (RMSE):

[0092]

[0093]

[0094] In the formula, h i is the elevation value estimated by DEM, h i ' is the elevation value measured by handheld RTK, and n is the number of terrain verification points.

[0095] The evaluation results are as follows:

[0096] Table 1 SBT-DEM accuracy evaluation

[0097]

[0098] In summary, this embodiment achieves seamless measurement of coastal terrain and water depth. The accuracy of the constructed SBT-DEM is very high, with an elevation error of only 6.2 cm (RMSE). The accuracy of the land DEM based on the UAV lidar (RMSE = 4 cm) is higher than that of the seabed DEM based on the single beam of the unmanned ship (RMSE = 8.1 cm). Compared with the medium-resolution data in the past (10 and 30 m), the SBT-DEM constructed in this embodiment is highly refined, with a spatial resolution of up to 1 m. The ability to depict the micro-topographic features of geomorphic units such as coasts, intertidal zones, underwater sandbars, and submarine tidal channels is significantly improved with the improvement of the DEM spatial resolution ( Figure 6The resolution of (a) is significantly better than that of (b) and (c). Compared with the existing methods of directly using the mean method or the inverse distance weighted method for DEM mosaicking, the present invention combines the inverse distance weighted method with the buffer method to construct an SBT-DEM that simultaneously achieves seamless smooth splicing of land and sea DEMs and low elevation accuracy loss in overlapping areas. Therefore, the effectiveness and feasibility of this method in constructing fine-scale SBT-DEMs in the coastal zone are verified.

[0099] The above-mentioned specific implementation methods are used to explain the present invention and are only preferred embodiments of the present invention, rather than limiting the present invention. Any modifications, equivalent substitutions, improvements, etc. made to the present invention within the spirit of the present invention and the protection scope of the claims shall fall within the protection scope of the present invention.

Claims

1. The coastal zone SBT-DEM construction method based on drones and unmanned ships is characterized by: The steps include: Step S1: In the coastal zone survey area, the UAV laser radar and the depth measuring unmanned ship are used to measure the coastal zone topography and water depth to obtain the original land point cloud data and water depth point cloud data; the step S1 is specifically as follows: Step S11: Survey the survey area and collect remote sensing image maps, select the operation date and time according to the weather and sea condition forecast data, and select the control points and measurement points in the survey area; the survey area is the area where the coastal zone extends to the land and the sea respectively, including the land area and the sea area, and the two overlap to form the intertidal zone; the control points are the existing topographic survey points, and the measurement points are the topographic points of the target to be monitored, which are used for subsequent calculation and verification; Step S12: Calculate the error correction value according to the control point coordinates; Step S13: When the intertidal zone is exposed during low tide, the coordinate data of the measuring points of the intertidal zone are collected in the survey area by using a handheld GNSS RTK device, and corrected according to the error correction value to obtain the coordinate data of the standard measuring points in the required plane and elevation coordinate systems after correction; part of the standard data and standard points are used for the accuracy control of the measuring point data of the drone and the unmanned boat, and the other part of the standard data is used as verification points for the subsequent SBT-DEM accuracy verification; Step S14: During the high tide period, the unmanned boat is controlled in automatic cruise mode to measure the water depth in the sea area along the set trajectory to obtain the original water depth point cloud data; at the same time, the seawater temperature, salinity and depth parameters are measured to calculate the actual seawater sound velocity value; Step S15: During low tide, the UAV is controlled in automatic cruise mode to measure the land terrain along the set target track line to obtain original land point cloud data; Among them, the measurement data of the unmanned ship and the drone have overlapping areas in the intertidal zone; Step S2: error correction, coordinate calculation, and benchmark conversion are performed on the original land point cloud data and water depth data to obtain the three-dimensional coordinate point data of the land and seabed in the survey area in the same coordinate system; the step S2 is specifically as follows: Step S21: Combine the static GNSS data of the base station and the POS positioning and orientation data of the UAV during flight to perform navigation and calculation to obtain the track file of the UAV: ​​the real track line and real-time attitude angle of the UAV; the POS positioning and orientation data includes GNSS positioning and IMU attitude and orientation data; Step S22: performing point cloud solution based on the original land point cloud data and the track file of the UAV to obtain a land laser point cloud, deleting deviation points, and outputting a land point cloud file in LAS format; Step S23: a. Filter out abnormal depth points from the original depth data of the echo sounder; b. Use the actual seawater sound velocity calculated to correct the depth data; c. Finally, use the real-time attitude angle data recorded by the attitude sensor of the unmanned ship to correct the depth data, the attitude angle data includes the pitch angle and the roll angle, and obtain the depth correction data z' of the echo sounder; Step S24: Calculate the seabed three-dimensional coordinate point cloud data x, y, zt-z' based on the three-dimensional coordinate data (x, y, z) of the GNSS receiver carried by the unmanned ship, the depth correction data z' of the echo sounder, and the fixed height t from the phase center of the GNSS receiver antenna to the bottom center of the echo sounder transducer; Step S25: unifying the coordinate systems of the land point cloud and the seabed point cloud to obtain the three-dimensional coordinate point clouds of the land and the seabed in the same coordinate system; Step S3: Using the geographic information system spatial data processing method, obtain the DEM of the land and the seabed respectively, perform seamless mosaic processing, and obtain the coastal zone SBT-DEM; the step S3 is specifically as follows: Step S31: Based on the overlapping data of the submarine topography point cloud and the land topography point cloud in the intertidal zone, the fixed errors of the submarine topography point cloud and the land topography point cloud are calculated using the standard point coordinates, and the fixed error correction is performed on the elevation values ​​of all the submarine topography point cloud data and the land topography point cloud data; Step S32: Generate a seafloor DEM using a spatial interpolation method based on the seafloor topography point cloud after fixed error correction; Step S33: Based on the land point cloud after the fixed error correction, use point cloud filtering to separate ground points and non-ground points, and use a spatial interpolation method for the ground points to generate a land DEM; the use of point cloud filtering to separate ground points and non-ground points includes distinguishing ground points and non-ground points according to an empirical threshold in the elevation z direction; Step S34: Generate a one-sided buffer zone starting from the sea side boundary of the land-sea DEM overlap zone toward the land direction, perform DEM mosaic operation in the buffer zone using the inverse distance weighted mosaic method, retain the land DEM that meets the accuracy threshold requirement in the non-buffered area in the overlap zone as the output result; the land-sea DEM in the non-overlapping area is directly output without processing; and is used to obtain a coastal zone SBT-DEM that meets both seamless smooth splicing and low elevation accuracy loss; the coastal zone SBT-DEM includes the estimated elevation values ​​of each location; Step S35: Based on the vertical distance L from the theoretical depth reference plane to the mean sea level of the two nearest tide gauge stations in the measurement area A , L B and the plane distance D from the two stations to the survey area A , D B , use the inverse distance weighted method to calculate the L value of the survey area: L = (D B L A +D A L B ) / (D A +D B ), and then perform vertical datum conversion to obtain the SBT-DEM of the chart datum.

2. The coastal zone SBT-DEM construction method based on unmanned aerial vehicles and unmanned ships according to claim 1 is characterized in that: The calculation of the error correction value includes: collecting the measured coordinate data of at least three control points, and subtracting them from the existing standard coordinate data in three dimensions, and then taking the average to obtain the error correction values ​​a, b, and c in three directions.

3. The method for constructing coastal zone SBT-DEM based on unmanned aerial vehicles and unmanned ships according to claim 1 is characterized in that: The measurement trajectory of the unmanned ship is in two directions: the main measurement line is arranged perpendicular to the coast, and the inspection line is arranged parallel to the coast; the unmanned ship navigates and measures along the main measurement line and the inspection line; the measurement line of the drone is arranged parallel to the coast.

4. The coastal zone SBT-DEM construction method based on unmanned aerial vehicles and unmanned ships according to claim 1 is characterized in that: The controlling of the unmanned ship to perform water depth measurement in the sea area along the set trajectory is achieved by using a single-beam echo sounder or a multi-beam echo sounder carried by the unmanned ship; the controlling of the drone to perform topographic measurement in the land area along the set target track is achieved by using a lidar sensor device carried by the drone.

5. The method for constructing coastal zone SBT-DEM based on unmanned aerial vehicles and unmanned ships according to claim 1 is characterized in that: Step S35 also uses the following visualization method to draw: The SBT-DEM image of the chart datum is colored with different colors to distinguish the elevation data; Depth contours are drawn on the SBT-DEM image of the chart datum.

6. The method for constructing coastal zone SBT-DEM based on unmanned aerial vehicles and unmanned ships according to claim 1 is characterized in that: The inverse distance weighted mosaic algorithm in step S34 is specifically: Where Z is the elevation value of the output pixel in the overlapping area, and the elevation values ​​of the land and seabed DEM overlaps are Z Land and Z Seabed , D1 and D2 are the distances from pixel P to the edge in the overlapping area.

7. The method for constructing coastal zone SBT-DEM based on unmanned aerial vehicles and unmanned ships according to any one of claims 1 to 6, characterized in that: The step S4 of using the terrain verification points measured by RTK to evaluate the accuracy of SBT-DEM is as follows: Based on the terrain verification points collected by handheld GNSS RTK, the elevation accuracy of SBT-DEM is evaluated using the mean absolute error (MAE) and root mean square error (RMSE): In the formula, h i is the elevation value estimated by DEM, h i ' is the standard elevation value of the verification point measured by handheld RTK, and n is the number of terrain verification points.

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