A river section measurement method based on multi-source observation

Abstract

The application provides a river section measurement method based on multi-source observation, obtains the shape of the river water section through the unmanned aerial vehicle laser radar, obtains the shape of the river section through ICESAT-2, and obtains the shape of the underwater section through the unmanned aerial vehicle dragging underwater sonar, and finally splices the data of the water and underwater sections to realize comprehensive and accurate river section measurement. The measurement method can effectively improve the measurement accuracy, reduce the cost and workload, improve the efficiency and convenience of underwater section measurement, and further realize comprehensive river section measurement.

Description

Technical Field

[0001] The present invention relates to the field of earth science research services, and in particular to a river section measurement method based on multi-source observation. Background Art

[0002] River cross-section measurement is a crucial task in water conservancy projects and environmental monitoring. It is used to obtain data on the geometric shape and hydrological characteristics of river cross-sections. This data is crucial for river management, water resources planning, flood warning, and ecological and environmental assessments. Traditional river cross-section measurement methods rely primarily on ground-based and aerial surveying techniques, which have limitations such as low measurement accuracy, high costs, and a high workload. Therefore, it is necessary to develop a more accurate and cost-effective measurement method based on the development of existing measurement and control technologies to support water conservancy project planning and environmental management. Summary of the Invention

[0003] To address the above issues, this application proposes a river cross-section measurement method based on multi-source observation to improve the accuracy and efficiency of river cross-section measurement, providing important technical support for water conservancy projects, environmental management, and scientific research. The specific technical solution is as follows:

[0004] A river cross-section measurement method based on multi-source observation, the method comprising:

[0005] The above-water section of the river channel is measured by carrying a laser radar detector on a drone, and a digital elevation model of the section is established;

[0006] Obtaining cross-sectional data of the river channel based on ICESat-2 radar altimetry data;

[0007] By carrying a sonar detector on a UAV to measure the area below the water surface of the river channel, continuous riverbed elevation points are obtained;

[0008] The cross-sectional shape of the river channel is obtained based on the transit cross-sectional data, the cross-sectional shape above water and the continuous riverbed elevation points of the river channel.

[0009] Furthermore, the obtaining of the cross-sectional shape of the river channel based on the cross-sectional data of the river channel, the cross-sectional shape above water, and the continuous riverbed elevation points includes:

[0010] Determining the cross-sectional shape of the river channel above water based on the digital elevation model at the cross-section and the cross-sectional data of the river channel;

[0011] Determining the underwater cross-sectional shape of the river channel based on the continuous riverbed elevation points and the transit cross-sectional data of the river channel;

[0012] Splicing the water surface section shape and the underwater section shape of the river channel obtains the section shape of the river channel.

[0013] Further, the water surface section shape of the river channel is determined based on the section digital elevation model and the transit section data of the river channel, and the water surface section shape of the river channel is determined based on the section digital elevation model and the transit section data of the river channel.

[0014] The section digital elevation model is cross-verified with the transit section data of the river channel.

[0015] The section digital elevation model is orthographically projected along the vertical river direction with the transit section data of the river channel to determine the water surface section shape of the river channel.

[0016] The underwater section shape of the river channel is determined based on the continuous riverbed elevation points and the transit section data of the river channel.

[0017] The continuous riverbed elevation points are orthographically projected along the vertical river direction with the underwater section shape to determine the underwater section shape of the river channel.

[0018] Further, the water surface section of the river channel is measured by carrying a laser radar detector on the unmanned aerial vehicle to establish the section digital elevation model, and the water surface section of the river channel is measured by carrying a laser radar detector on the unmanned aerial vehicle to establish the section digital elevation model.

[0019] On-site survey of the river is performed, and a region around the river channel with little influence of surface coverage is selected as the address for section measurement.

[0020] Based on the address for section measurement, the flight height of the unmanned aerial vehicle and the scanning width of the laser radar are set to set the aerial photography path of the unmanned aerial vehicle, and the aerial photography path covers the entire river channel section position.

[0021] The laser point cloud data of the laser radar is acquired.

[0022] The section digital elevation model is established based on the laser point cloud data.

[0023] Further, the transit section data of the river channel is acquired based on the ICESat-2 radar altimetry data.

[0024] The transit route of ICESat-2 is selected as the section measurement position within the position range of the address for section measurement.

[0025] The transit cross-section data of the dry season is selected as the input data for section measurement.

[0026] The beam is selected.

[0027] Photons with a height H exceeding 5 meters in the Geoid ATL03 photon data set relative to the reference geoid are removed.

[0028] Remove outliers from the photon cloud and calculate the median height of the remaining photons , obtaining the water surface position of the river;

[0029] When the light beam can be projected onto the bottom of the river,

[0030] reserve photon point, The value range is 0.5-1 meter;

[0031] Correcting the retained photon point data;

[0032] Obtaining an underwater cross-sectional shape based on the corrected data;

[0033] When the light beam cannot be projected onto the bottom of the river channel, the water surface position of the river channel is interpolated to obtain the underwater cross-sectional shape.

[0034] Furthermore, the method of measuring the area below the water surface of the river channel by carrying a sonar detector on a drone to obtain continuous riverbed elevation points includes:

[0035] Determining the flight path of the sonar detector carried by the UAV based on the cross-sectional measurement position of the ICESat-2;

[0036] The UAV is equipped with a sonar detector and flies at a constant altitude and uniform speed. During the flight, the sonar detector is activated and operated to perform measurements and obtain sonar data;

[0037] Continuous riverbed elevation points are obtained based on the sonar data.

[0038] Furthermore, the obtaining of continuous riverbed elevation points based on the sonar data includes:

[0039] Sonar DCS positioning, the positioning formula is:

[0040] ;

[0041] ;

[0042] Where, and are the north and east coordinates of DCS respectively, and are the north and east coordinates of the drone, and are the offsets of DCS coordinates in the north and east directions respectively;

[0043] Vertical distance from the drone to the water surface The correction formula is:

[0044] ;

[0045] Where, is the distance from the drone to the water surface measured by the radar water level gauge, in meters; and denote the pitch angle and roll angle respectively;

[0046] Correction of riverbed elevation. The correction formula is:

[0047] ;

[0048] ;

[0049] Where, and Respectively represent the sampling points The river surface elevation at the sampling point and the altitude of the drone’s hovering position, It's the drone at the sampling point The vertical height from the water surface, Indicates that the riverbed is at the sampling point The elevation of Indicates sampling point The depth of water;

[0050] Sampling perpendicular to the river flow direction to obtain a certain sampling point The coordinates of , and obtain continuous riverbed elevation points.

[0051] Furthermore, the correction of the retained photon point data includes:

[0052] Refraction correction, the refraction correction formula is:

[0053] ;

[0054] Where, is the angle of incidence; is the angle of refraction; and are the refractive indices of air and water, respectively;

[0055] The slope distance correction of the photon from the water surface to the river bottom is calculated as follows:

[0056] ;

[0057] ;

[0058] Where, and respectively represent the slant distance of the photons from the water surface to the river bottom after and before correction, is the depth of the river from the water surface to the river bottom.

[0059] Further, the obtaining of the underwater section shape according to the corrected data comprises:

[0060] the slant side of the refraction slant right triangle is calculated as :

[0061] ;

[0062] the horizontal direction offset of the water bottom is calculated as and the vertical direction offset height is calculated as :

[0063] ;

[0064] ;

[0065] wherein, is the difference between the included angle of the refraction direction and the incident direction at the water bottom and the included angle of the refraction direction in water and the incident direction at the water bottom;

[0066] the horizontal offset is projected into the coordinate system of east and north directions based on the azimuth angle of the laser pointing:

[0067] ;

[0068] ;

[0069] the final water bottom position and elevation are obtained after correction in the original coordinate , and the underwater section shape is obtained:

[0070] ;

[0071] ;

[0072] .

[0073] Further, the formula for interpolating the river water surface position is:

[0074] ;

[0075] wherein, r1 is the interpolation coefficient, is the elevation of the submerged water bottom, is the river depth at low water level, is the river width, and x is the distance from the river center line. ​

[0076] This invention discloses a multi-source observation-based river cross-section measurement method. This method uses drone laser radar to obtain the above-water cross-sectional shape of the river, ICESAT-2 to obtain the river cross-sectional shape, and drone-towed underwater sonar to obtain the underwater cross-sectional shape. Ultimately, these above-water and underwater cross-sectional data are spliced ​​together to achieve comprehensive and accurate river cross-sectional measurement. This method can effectively improve measurement accuracy, reduce costs and workload, and increase the efficiency and convenience of underwater cross-sectional measurement, thereby achieving comprehensive river cross-sectional measurement. BRIEF DESCRIPTION OF THE DRAWINGS

[0077] To more clearly illustrate the technical solutions in the embodiments of the present application, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present application. Those skilled in the art can also derive other drawings based on these drawings without inventive effort.

[0078] In order to more completely understand the present application and its beneficial effects, the following description will be given in conjunction with the accompanying drawings. In the following description, the same reference numerals represent the same parts.

[0079] Figure 1 A schematic flow chart of a river cross-section measurement method based on multi-source observation according to the present invention;

[0080] Figure 2 Schematic diagram of refraction correction. DETAILED DESCRIPTION

[0081] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the embodiments described are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without making creative efforts are within the scope of protection of this application.

[0082] Traditional river channel cross-section measurement methods rely primarily on ground-based and aerial surveying techniques, which have limitations such as low measurement accuracy, high costs, and heavy workload. To obtain accurate river channel cross-section shape data, researchers are continuously exploring new measurement methods and technologies. With the development of remote sensing technologies such as UAV LiDAR and ICESAT-2, river channel cross-section measurement methods based on multi-source observations have gradually become a research hotspot. UAV LiDAR technology offers significant advantages in river channel cross-section measurement. Drones equipped with LiDAR can acquire high-precision three-dimensional point cloud data of locations above the water surface of a river channel. LiDAR emits a laser beam and receives the laser echo to calculate the distance between the river channel and the water surface, thereby determining the above-water channel shape. UAV LiDAR offers high spatial resolution and rapid data acquisition, providing accurate information on river channel cross-section shape. ICESAT-2 is a laser altimeter satellite launched by NASA in 2018. Using laser ranging technology, it can obtain elevation data of the Earth's surface and the water surface. For river cross-section measurements, ICESAT-2 provides highly accurate above-water elevation data, enabling the determination of river geometry. Cross-validation with above-water cross-section data obtained by drone-based LiDAR improves the reliability and accuracy of measurement results.

[0083] Furthermore, underwater cross-section measurement is a key task in river channel cross-section surveying. Traditional underwater cross-section measurements are typically performed using towed underwater sonar, which measures the time and distance sound waves travel underwater to infer the geometry of the underwater cross-section. However, conventional unmanned vessel surveying methods are prohibitively expensive. Using underwater sonar mounted on drones allows for rapid underwater cross-section measurement and the acquisition of underwater shape data corresponding to the surface cross-section.

[0084] This method uses drone-mounted lidar to obtain above-water cross-sectional geometry, ICESAT-2 to obtain above-water cross-sectional geometry, and drone-towed underwater sonar to obtain underwater cross-sectional geometry. Ultimately, these above-water and underwater cross-sectional data are spliced ​​together to achieve comprehensive and accurate river cross-sectional measurement. This multi-source observation method combines the advantages of lidar, satellite remote sensing, and underwater sonar technologies to provide comprehensive river cross-sectional information, providing important support for water conservancy project planning and environmental management.

[0085] Example 1, reference Figure 1 Based on the above ideas, the present invention provides a river section measurement method based on multi-source observation, which includes the following steps:

[0086] S10: measuring the above-water section of the river channel by carrying a laser radar detector on a drone, and establishing a digital elevation model of the section;

[0087] S20: Acquire the cross-section data of the river channel based on ICESat-2 radar altimetry data;

[0088] S30: measuring the area below the water surface of the river channel by carrying a sonar detector on the drone to obtain continuous riverbed elevation points;

[0089] S40: Obtaining the cross-sectional shape of the river channel based on the transit cross-sectional data of the river channel, the cross-sectional shape above water, and the continuous riverbed elevation points.

[0090] Step S10, wherein a laser radar detector is mounted on a drone to measure the above-water section of the river channel and establish a digital elevation model of the section, includes the following steps:

[0091] S101: Conduct an on-site survey of the river and select an area around the river that is less affected by surface cover as the location for cross-section measurement. Because drone laser radar is affected by the underlying surface, if there are trees on the underlying surface, the laser radar will measure the height of the trees instead of the height of the riverbank. This will affect the cross-section measurement and make the cross-section measurement less accurate. Therefore, when selecting drone cross-section measurement, the present invention tries to avoid the river being blocked by objects such as trees and houses. Select an area around the river that is less affected by surface cover, preferably an area without surface cover around the river, that is, an area without trees or other surface cover, as the location for cross-section measurement.

[0092] S102: Based on the address of the cross-section measurement, according to the flight altitude of the drone and the scanning width of the laser radar, setting the aerial photography path of the drone, wherein the aerial photography path covers the entire river cross-section position;

[0093] S103: Acquire laser point cloud data of the laser radar;

[0094] S104: Establishing a digital elevation model at the cross section based on the laser point cloud data.

[0095] In step S103, after the echo data received by the lidar is recorded, it is stored together with the laser device parameters (such as position, direction, and timestamp) to form the raw laser point cloud data. This raw laser point cloud data needs to be processed and optimized to improve data quality and usability. The specific processing steps include:

[0096] S1031: Remove stray points: Identify and remove outliers caused by interference or abnormal reflection to improve data accuracy.

[0097] S1032: Filtering: Apply filtering algorithms, such as Gaussian filtering and median filtering, to remove noise from the data and smooth the data, thereby obtaining clearer and more continuous point cloud surface data.

[0098] S1033: Segmentation: Segment point cloud data into different parts, such as ground and non-ground points, for further analysis and processing.

[0099] S1034: Registration: Register multiple scans or point cloud data from different locations so that they are aligned in the same coordinate system to obtain a more complete three-dimensional scene.

[0100] In step S104, the processed point cloud data is presented in a visual manner to establish a digital elevation model of the cross section. The specific processing steps include:

[0101] S1041: Sampling density adjustment: Adjust the sampling density of ground point cloud data according to application requirements and data characteristics to meet the requirements of DEM generation.

[0102] S1042: Gridding: Gridding the ground point cloud data and mapping the point cloud data into a two-dimensional grid.

[0103] S1043: Interpolation processing: interpolation calculation is performed on the data in each grid cell to generate the elevation value of each grid cell.

[0104] S1044: Filtering and smoothing: Filtering and smoothing the generated DEM to remove local noise and irregularities to obtain a smoother surface elevation model.

[0105] The drone platform used in the above steps is based on the DJI M300, equipped with a Yellow Scan LiDAR sensor payload to measure riverbank sections above the water surface. The drone is also equipped with a high-precision RTK GNSS base station and a ground control terminal. The tightly coupled RTK GNSS and IMU systems on the drone accurately obtain the drone's position and orientation system (POS) data, achieving centimeter-level positioning accuracy.

[0106] Regarding step S20, the process of obtaining the cross-section data of the river based on ICESat-2 radar altimetry data includes the following steps:

[0107] S201: Selecting the ICESat-2 transit route as the cross-section measurement location within the location range of the cross-section measurement address obtained in step S101; the along-track resolution of ICESat-2 radar altimetry is 0.7 meters, and the distance between adjacent tracks exceeds 91.6 kilometers. Using the ALT03 photon cloud product, the geometric shape of the river section can be very accurately mapped. For the measurement of river sections, each time ICESat-2 passes through, it can measure one section in the river section. After multiple passes, data from multiple sections of the river observation section can be obtained. Selecting the ICESat-2 transit route as the cross-section measurement location within the location range of the cross-section measurement address obtained in step S101 is sufficient to construct a hydrological and hydrodynamic model of the river section.

[0108] S202: Select the crossing data in the dry season as the input data for the measurement section; since more riverbeds are above the water surface in the dry season, more cross-sectional shapes above the water surface can be measured, and the measurement of cross-sectional shapes above the water surface is more accurate. Therefore, this embodiment preferably selects the crossing data in the dry season as the input data for the measurement section.

[0109] S203: Select beam. ICESat-2's lidar is equipped with three beams: Strong Beam, Middle Beam, and Weak Beam. Different beams have different signal strengths and coverages to meet the measurement requirements of different surface and terrain features. Therefore, it is necessary to select the appropriate beam based on the characteristics of the cross-section location. Specifically:

[0110] Strong Beam: Suitable for flat or smooth surface features and areas with small elevation changes. Strong beam has higher signal strength and can provide better measurement accuracy.

[0111] Middle Beam: Suitable for areas with moderate surface roughness and elevation changes. With a signal strength between strong and weak beams, the middle beam balances measurement accuracy and coverage.

[0112] Weak Beam: Suitable for areas with rough surfaces and large elevation changes. Weak beam provides wider coverage, but weaker signal strength may result in slightly lower measurement accuracy.

[0113] Choosing the right beam requires considering the following factors:

[0114] Surface characteristics: Select a beam with appropriate signal strength based on the smoothness or roughness of the surface. Smooth surfaces are generally suitable for strong beams, while rough surfaces may require weak beams to obtain sufficient reflected signals.

[0115] Elevation Variation: Consider elevation variations across the cross-section. If there are large elevation variations, you may need to select an intermediate or weak beam to ensure that data is captured across the entire elevation range.

[0116] Coverage requirements: Select a beam with appropriate coverage based on the width of the section being measured. Strong beams have narrower coverage, while weak beams have wider coverage.

[0117] By analyzing the surface characteristics, elevation changes, and coverage requirements of the cross-section location, appropriate beams are selected for data processing to ensure accurate elevation data is obtained to meet the measurement needs of different surface characteristics and terrain changes.

[0118] S204: Remove photons whose height H exceeds 5 meters relative to the reference geoid ATL03 photon data set. The reference surface for the concentration height H is the geoid. The above steps are used to remove the effects of reflections from land and water surfaces, making the measurement results more accurate.

[0119] S205: Remove outliers from the photon cloud and calculate the median height of the remaining photons , obtain the water surface position of the river; the water surface in the ALT03 data is characterized by a dense photon cloud, and the peak density of the Gaussian distribution can be used to identify the position of the water surface. By averaging the points within 20 cm within the peak range, the position of the water surface in the river section can be determined.

[0120] The specific method of removing outliers in the photon cloud is as follows: First, apply the Hampel filter to remove outliers, and filter the photons with the median absolute deviation (MAD) at every 3.5-meter ground track. If it exceeds MAD, it is considered as an outlier and removed.

[0121] The calculation method of MAD is as follows:

[0122] (1)

[0123] Where, .

[0124] After the Hampel filter removes outliers, median filtering is performed on the same 3.5-m ground track, and then a window sliding is performed until the entire ground track is determined.

[0125] S2061: When the light beam can be projected onto the bottom of the river, retain photon point, The value range of is 0.5-1 meter; the retained photon point data is corrected; and the underwater cross-sectional shape is obtained according to the corrected data.

[0126] Since the flow of river water will affect the photons, the present invention sets a buffer range Remove the influence of surface photons, according to different river conditions, The value range is between 0.5 meters and 1 meter.

[0127] In the above steps, the correction of the retained photon point data includes the following corrections:

[0128] First, refraction correction. Since ATLAS photons are refracted on the air-water surface, their travel speed and direction will change. Therefore, refraction correction is required for the remaining photon data. The refraction correction formula is:

[0129] ; (2)

[0130] Where, is the angle of incidence; is the angle of refraction; and are the refractive indices of air and water, respectively;

[0131] Correction of the slant distance of photons from the water surface to the bottom of the river. Due to the change in the speed of light between the air and water surface, the slant distance of photons from the water surface to the bottom of the river needs to be corrected. The formula for the slant distance correction is:

[0132] ; (3)

[0133] ; (4)

[0134] Where, and represent the slant distances of photons from the water surface to the river bottom before and after correction, It is the vertical depth from the river surface to the river bottom.

[0135] The step of obtaining an underwater cross-sectional shape based on the corrected data comprises:

[0136] like Figure 2 As shown, different angles are obtained through trigonometric conversion (the angle between the refraction direction and the incident direction at the bottom of the water), (the angle between the direction of refraction in the water and the direction of incidence at the bottom of the water) and ( and The difference between the two angles), R is the distance of the photon beam refracted in water, P is the distance between the incident direction to the water bottom and the actual refracted light line, The difference between the two angles), R is the distance of the photon beam refracted in water, P is the distance between the incident direction to the water bottom and the actual refracted light line, The difference between the two angles), R is the distance of the photon beam refracted in water, P is the distance between the incident direction to the water bottom and the actual refracted light line,

[0137] (5);

[0138] (6);

[0139] (7);

[0140] According to different angles , and , the hypotenuse of the refracted oblique right triangle is calculated as :

[0141] ; (8)

[0142] Further calculate the horizontal offset of the water bottom and the vertical offset height :

[0143] ; (9)

[0144] ; (10)

[0145] Based on the azimuth of the laser pointing , the horizontal offset is projected into the coordinate system of the east and north directions:

[0146] ; (11)

[0147] ; (12)

[0148] In the original coordinates, the final water bottom position and elevation are corrected , and the underwater section shape is obtained:

[0149] ; (13)

[0150] ; (14)

[0151] (15).

[0152] S2062: When the light beam cannot be projected to the river bottom, the river water surface position is interpolated to obtain the underwater section shape. The interpolation formula is:

[0153] ; (16)

[0154] Where r1 is the interpolation coefficient, is the elevation of the submerged bottom, is the river depth at low water level, is the width of the river, x is the distance from the center line of the river, and the shape of the cross section depends on the size of r1. If r1=1, the corresponding cross section shape is triangular, and r1 tends to positive infinity, the corresponding cross section shape is rectangular.

[0155] Regarding step S30, measuring the area below the water surface of the river channel by carrying a sonar detector on a drone to obtain continuous riverbed elevation points includes the following steps:

[0156] S301: Determine the route path of the sonar detector carried by the UAV according to the cross-section measurement position of the ICESat-2 obtained in step S201;

[0157] S302: The UAV is equipped with a sonar detector and flies at a constant altitude and uniform speed. During the flight, the sonar detector is activated and operated to perform measurements and obtain sonar data. The UAV platform equipped with the sonar device needs to have sufficient carrying capacity and stability to install and operate the sonar device. The sonar device usually includes a sensor and related data acquisition equipment. A sonar device with appropriate frequency, power and resolution is selected to meet the measurement requirements. During the flight, the sonar device is activated and operated to perform measurements. The sonar will emit sound wave signals and record the returned echo signals. By measuring the time delay and intensity of the echo signal, the characteristics of the underwater object or underwater terrain can be inferred. The sonar data is collected and stored in appropriate media or storage devices. Ensure the integrity and traceability of the data for subsequent data processing and analysis.

[0158] Specifically, the above-mentioned measurement system is based on the DJI M300 UAV platform, and its payloads include (1) UPK100 airborne GNSS / IMU system, which is used to record the positioning and orientation system (POS) data of the UAV; (2) 24-GHz radar water level meter, which is used to record the distance between the UAV and the water surface; (3) Deeper Chirp+ sonar (DCS), which is used for depth measurement; the DCS and the UAV are towed by a soft rope. The DCS is small and light, floating on the water surface, and can obtain depth measurement data when it touches the water surface, and can realize long-distance (100 meters) transmission of depth measurement data.

[0159] S303: Continuous riverbed elevation points are obtained based on the sonar data. Due to the position and angle differences between the drone and the towed sonar DCS, and the fact that the DCS sonar has a built-in global positioning system (GPS), the accuracy is relatively coarse. Water depth positioning requires the use of the drone's orthophoto image and the calculation of the drone's precise positioning to be assigned to the sonar DCS. Therefore, the sonar DCS data must be corrected, including:

[0160] Sonar DCS positioning, the positioning formula is:

[0161] ; (17)

[0162] ; (18)

[0163] Where, and are the north and east coordinates of DCS respectively, and are the north and east coordinates of the drone, and are the offsets of DCS coordinates in the north and east directions respectively;

[0164] Vertical distance from the drone to the water surface The correction formula is:

[0165] ; (19)

[0166] Where, is the distance from the drone to the water surface measured by the radar water level gauge, in meters; and denote the pitch angle and roll angle respectively;

[0167] Correction of riverbed elevation. The correction formula is:

[0168] ; (20)

[0169] ;(twenty one)

[0170] Where, and Respectively represent the sampling points The river surface elevation at the sampling point and the altitude of the drone’s hovering position, It's the drone at the sampling point The vertical height from the water surface, Indicates that the riverbed is at the sampling point The elevation of Indicates sampling point The depth of water;

[0171] Take samples perpendicular to the river flow and obtain a certain sampling point The coordinates of By sampling perpendicular to the river flow direction, continuous riverbed elevation points can be obtained, and the complete shape of the river section can be obtained.

[0172] After measuring the cross-sectional data, the cross-sectional shape above the water, and the continuous riverbed elevation points of the river channel, step S40 is executed to obtain the cross-sectional shape of the river channel based on the cross-sectional data, the cross-sectional shape above the water, and the continuous riverbed elevation points, including the following steps:

[0173] S401: Determine the cross-sectional shape of the river channel above water based on the digital elevation model at the cross-section and the cross-sectional data of the river channel;

[0174] S402: Determine the underwater cross-sectional shape of the river channel based on the continuous riverbed elevation points and the transit cross-sectional data of the river channel;

[0175] S403: splicing the above-water cross-sectional shape and the underwater cross-sectional shape of the river channel to obtain the cross-sectional shape of the river channel.

[0176] Wherein S401, determining the cross-sectional shape of the river channel above water based on the digital elevation model at the cross-section and the cross-sectional data of the river channel, includes:

[0177] Cross-validating the digital elevation model at the section with the crossing section data of the river;

[0178] orthographically projecting the digital elevation model at the section and the transit section data of the river along a direction perpendicular to the river channel to determine the cross-sectional shape of the river channel above water;

[0179] S402, determining the underwater cross-sectional shape of the river channel based on the continuous riverbed elevation points and the transit cross-sectional data of the river channel, includes:

[0180] Orthographic projection is performed on the continuous riverbed elevation points and the underwater cross-sectional shape along a direction perpendicular to the river channel to determine the underwater cross-sectional shape of the river channel.

[0181] Regarding step S403, since the coordinate projections of the above-water cross-sectional shape and the underwater cross-sectional shape of the river channel are unified and are both obtained based on the RTK-GNSS base station, they can be directly spliced ​​based on their coordinates, which will not be described in detail here.

[0182] The above measurement method has the following advantages:

[0183] First, improve measurement accuracy: By combining drone lidar and ICESAT-2 satellite data, as well as underwater sonar measurements, we achieve comprehensive, high-precision river cross-section measurements. By cross-validating measurement results from different data sources, we ensure the accuracy and reliability of the measurement data.

[0184] Second, it reduces costs and workload: Utilizing drone-based lidar and ICESAT-2 satellite data, we can quickly acquire river cross-section data over a wide area, reducing the manpower and time required for traditional ground-based surveys. Furthermore, drone-towed underwater sonar can improve the efficiency and convenience of underwater cross-section measurements.

[0185] Third, comprehensive river cross-section measurements will be achieved. By integrating both above-water and underwater cross-section measurements and stitching them together into complete river cross-sections, accurate river geometry and hydrological characteristics will be provided. This will provide a reliable basis for decision-making in areas such as water conservancy project planning, environmental monitoring, and flood warning.

[0186] Fourth, it promotes technological innovation and application: The multi-source observation-based river cross-section measurement method provided by this invention combines technologies such as drone lidar, ICESAT-2 satellite data, and underwater sonar, promoting innovation and application of remote sensing, laser measurement, and hydroacoustic technologies in river cross-section measurement. By resolving the technical issues existing in traditional river cross-section measurement methods and achieving the aforementioned objectives, this invention will provide an efficient and accurate river cross-section measurement method, providing important technical support for fields such as water conservancy projects, environmental management, and scientific research.

[0187] Other embodiments of the present invention will readily occur to those skilled in the art after considering the specification and practicing the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of the present invention that follow the general principles of the invention and include common knowledge or customary techniques in the art not disclosed herein. The description and examples are to be considered as exemplary only, with the true scope and spirit of the invention being indicated by the following claims.

[0188] It should be understood that the present invention is not limited to the exact construction described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present invention is limited only by the appended claims.

[0189] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A river section measurement method based on multi-source observation, characterized in that: include: The above-water section of the river channel is measured by carrying a laser radar detector on a drone, and a digital elevation model of the above-water section is established; Obtaining cross-sectional data of the river channel based on ICESat-2 radar altimetry data; By carrying a sonar detector on a UAV to measure the area below the water surface of the river channel, continuous riverbed elevation points are obtained; Obtaining the cross-sectional shape of the river channel based on the cross-sectional data of the river channel, the cross-sectional shape above water, and the continuous riverbed elevation points; The step of obtaining the cross-sectional shape of the river channel based on the cross-sectional data of the river channel, the cross-sectional shape above water, and the continuous riverbed elevation points includes: Determining the cross-sectional shape of the river channel above water based on the digital elevation model at the cross-sectional area above water and the cross-sectional data of the river channel; Determining the underwater cross-sectional shape of the river channel based on the continuous riverbed elevation points and the transit cross-sectional data of the river channel; splicing the above-water cross-sectional shape and the underwater cross-sectional shape of the river channel to obtain the cross-sectional shape of the river channel; The determining of the cross-sectional shape of the river channel above water based on the digital elevation model at the cross-sectional area above water and the cross-sectional data of the river channel includes: Cross-validating the digital elevation model at the water section with the transit section data of the river; orthographically projecting the digital elevation model at the water section and the transit section data of the river along a direction perpendicular to the river channel to determine the water section shape of the river channel; The step of determining the underwater cross-sectional shape of the river channel based on the continuous riverbed elevation points and the transit cross-sectional data of the river channel comprises: Orthographic projection is performed on the continuous riverbed elevation points and the underwater cross-sectional shape along a direction perpendicular to the river channel to determine the underwater cross-sectional shape of the river channel.

2. A river section measurement method based on multi-source observation according to claim 1, characterized in that: The method of measuring the above-water section of the river channel by carrying a laser radar detector on a drone and establishing a digital elevation model of the above-water section includes: Conduct on-site surveys of the river and select areas around the river that are less affected by surface cover as locations for cross-section measurements; Based on the address of the cross-section measurement, the drone's aerial photography path is set according to the drone's flight altitude and the laser radar's scanning width, and the aerial photography path covers the entire river section position; Acquire laser point cloud data of the laser radar; A digital elevation model of the above-water section is established based on the laser point cloud data.

3. A river section measurement method based on multi-source observation according to claim 2, characterized in that: The obtaining of the river channel cross-section data based on ICESat-2 radar altimetry data includes: Selecting the ICESat-2 transit route within the location range of the address of the cross-section measurement as the cross-section measurement location; The cross-border data in the dry season were selected as the input data for the measurement section; Select the beam; Remove photons whose height H is greater than 5 meters relative to the reference geoid Geoid ATL03 photon dataset; Remove outliers from the photon cloud and calculate the median height H of the remaining photons median , obtaining the water surface position of the river; When the light beam can be projected onto the bottom of the river, Keep H<(H median -H buffer ) photon point, H buffer The value range is 0.5-1 meter; Correcting the retained photon point data; Obtaining an underwater cross-sectional shape based on the corrected retained photon point data; When the light beam cannot be projected onto the bottom of the river channel, the water surface position of the river channel is interpolated to obtain the underwater cross-sectional shape.

4. A river section measurement method based on multi-source observation according to claim 3, characterized in that: The method of measuring the area below the water surface of the river channel by carrying a sonar detector on a drone to obtain continuous riverbed elevation points includes: Determining the flight path of the sonar detector carried by the UAV based on the cross-sectional measurement position of the ICESat-2; The UAV is equipped with a sonar detector and flies at a constant altitude and uniform speed. During the flight, the sonar detector is activated and operated to perform measurements and obtain sonar data; Continuous riverbed elevation points are obtained based on the sonar data.

5. A river section measurement method based on multi-source observation according to claim 4, characterized in that: The step of obtaining continuous riverbed elevation points based on the sonar data includes: Sonar DCS positioning, the positioning formula is: N s =N u -L y ; AND s =And u -THE x ; Where N s and E s are the north and east coordinates of DCS respectively, N u and E u are the north and east coordinates of the UAV, L y and L x are the offsets of DCS coordinates in the north and east directions respectively; Vertical distance H from the drone to the water surface z The correction formula is: Where SWE is the distance from the UAV to the water surface measured by the radar water level gauge, in meters; and ∈ represent the pitch angle and roll angle respectively; Correction of riverbed elevation. The correction formula is: H Mi =H Qi -H zi ; H Ni =H Mi -H ji ; Where H Mi and H Qi They represent the river surface elevation at sampling point i and the elevation of the drone’s hovering position at the sampling point, respectively. zi is the vertical height of the UAV from the water surface at sampling point i, H Ni represents the elevation of the riverbed at sampling point i, H ji represents the water depth at sampling point i; Sampling is done perpendicular to the river flow direction to obtain the coordinates of a sampling point i (N si ,E si ,H Ni ) to obtain continuous riverbed elevation points.

6. The method for river section measurement based on multi-source observation according to claim 3, characterized in that: The correcting of the retained photon point data comprises: Refraction correction, the refraction correction formula is: Where θ1 is the angle of incidence; θ2 is the angle of refraction; n1 and n2 are the refractive indices of air and water, respectively; The slope distance correction of the photon from the water surface to the river bottom is as follows: Where R and S represent the slant distances of photons from the water surface to the river bottom before and after correction, respectively, and D is the vertical depth from the river surface to the river bottom.

7. A river section measurement method based on multi-source observation according to claim 6, characterized in that: The step of obtaining the underwater cross-sectional shape based on the corrected retained photon point data comprises: Calculate the hypotenuse P of the refracted inclined right triangle: Calculate the horizontal offset ΔY and vertical offset height ΔZ of the bottom: ΔY=Pcosβ; ΔZ = Psinβ; Based on the azimuth angle k of the laser pointing, the horizontal offset is projected into the coordinate system in the east and north directions: ΔE=ΔYsink; ΔN=ΔYcosk; Correction is performed on the original coordinates to obtain the final bottom position and elevation (E′, N′, Z′), and the underwater cross-sectional shape is obtained: E′=E+ΔE; N′=N+ΔN; Z′=Z+ΔZ.

8. The method for river section measurement based on multi-source observation according to claim 3, characterized in that: The formula for interpolating the water surface position of the river is: Where r is the interpolation coefficient, Z′ is the elevation of the submerged bottom, is the river depth at low water level, W * is the width of the river, and x is the distance from the centerline of the river.

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