297results about "Measuring open water depth" patented technology

The invention discloses a deep and far sea unmanned aerial vehicle monitoring and management platform based on multi-sensor fusion, and relates to the technical field of unmanned aerial vehicle marine monitoring. The intelligent analysis module is used for receiving the fusion data after time-space alignment and the real-time ocean current data, optimizing the moving path of the unmanned aerial vehicle according to the received data, evaluating the resource development possibility, obtaining an analysis result and transmitting the analysis result; an anti-interference communication module; an energy management module; and dynamically adjusting an energy distribution strategy. The module combines the task priority weight and the environment energy consumption weight, optimizes the energy use efficiency, prolongs the endurance time of the unmanned aerial vehicle, and ensures the smooth completion of the task. Particularly in a complex marine environment, navigation errors are corrected in real time through a quantum navigation error compensation model, the positioning precision is improved, and the moving path of the unmanned aerial vehicle is optimized in combination with real-time ocean current data and an ocean flow field cost function.

The invention discloses a multi-source data-combined pit-pond water depth calculation and storage capacity calculation method, which comprises the following steps of: acquiring actually measured water depth data, performing data preprocessing, and dividing the data into a training sample point set and a test sample point set; acquiring a multispectral remote sensing image of the reckoning area, and executing image preprocessing; unifying to the same coordinate system; fractal dimensions of each wave band and the combined wave band are calculated, and a water body region is segmented; establishing a mapping relation between the water depth values of the training sample points and the standardized multispectral apparent reflectance; establishing a water depth inversion model, and verifying the water depth inversion model by using the test sample point set; calculating discrete water depth points of the pit pond by using the optimal water depth inversion model; and establishing a minimum energy curved surface to obtain the water storage amount of a single pit pond, and accumulating to generate the total water storage amount. According to the method, actual measurement and remote sensing data are fused, the energy minimization water depth inversion model is constructed, accurate calculation of the water storage capacity of the pit pond is achieved, and the method has the advantages of being high in precision and high in applicability.

The invention discloses a multi-field sensing fusion deep sea geological environment dynamic monitoring system and an application method. The system comprises a buoy measuring platform, a multi-beam sounding system, a high-precision marine gravimeter, an external camera, a GPS, a data acquisition and transmission control unit and a power supply system. By designing a modularized and integrated multi-sensor buoy platform, various sensors are fused and integrated. A plurality of sensors are connected to the data acquisition control terminal, the steps of sensor calibration, data synchronization and clock calibration, correction and compensation, data acquisition, real-time processing, fine post-processing, data transmission and the like are completed, and multi-sensor collaborative operation is realized, so that submarine topography and ocean gravity data of a deep sea ditch area are synchronously acquired in real time; and thus, diving erosion information experienced by the area can be accurately monitored. The method can provide important support for submarine topography and landform detection and application and marine geographic information system construction, and has application value in the aspects of geological disaster early warning, resource development and the like.

The invention relates to a sea area island remote sensing information change monitoring method and system, and relates to the technical field of remote sensing monitoring, and the method comprises the steps: obtaining a remote sensing image time sequence of a target sea area island, the remote sensing image time sequence comprises a plurality of remote sensing images, and each remote sensing image has an acquisition timestamp; collecting tide height information corresponding to the target sea area island at each collection timestamp, and water depth distribution information of the monitored sea area where the target sea area island is located; and performing correction processing on each remote sensing image according to the tidal height information and the water depth distribution information corresponding to each acquisition timestamp, and generating an island boundary contour change time sequence. The invention solves the problems that the traditional sea area island remote sensing monitoring adopts a single-moment image for analysis, the real coastline change and temporary boundary offset caused by tide cannot be distinguished, the boundary extraction precision is reduced due to shallow water area seabed reflection interference, the monitoring error is large, and the monitoring precision is low. The application precision requirements of sea area management, coastal zone protection and the like cannot be met.

The invention belongs to the technical field of hydraulic engineering measurement, and discloses a seawall measurement method and system based on multi-source data fusion, and the method comprises the steps: collecting geological data and hydrological data through a data collection module; the route planning module formulates a route; the overwater data acquisition equipment and the underwater data acquisition equipment are used for monitoring; the auxiliary equipment provides a high-precision positioning reference; the meteorological data module obtains meteorological data; the data processing module processes the data; the three-dimensional modeling module carries out point cloud registration and DEM model construction; the comprehensive analysis module performs comprehensive evaluation and predicts potential problems and risks; when an abnormal condition or a potential risk is monitored, the early warning module gives an alarm. Multi-source data acquisition equipment such as unmanned aerial vehicle aerial survey, a laser radar, a multi-beam depth finder, a side-scan sonar, a shallow profiler and a micro-motion exploration instrument are integrated, seawall overwater and underwater full-dimensional data acquisition, processing, modeling and volume calculation are realized, and high precision and reliability of measurement results are ensured.

The invention provides an ICESat-2 turbid water area sounding correction and water depth inversion method based on optical characteristics of a water body. The method comprises the following steps: S1, obtaining photon data and an optical remote sensing image of a near-shore turbid water research area, and carrying out preprocessing operation on the data; s2, performing spectral sensitivity analysis by acquiring an ICESat-2 photon error value and combining optical characteristics of a water body; s3, constructing an ICESat-2 turbid water area sounding compensation model based on water optical characteristics, and selecting the model preferentially according to evaluation indexes; s4, synthesizing a multi-temporal image, and realizing model adaptive adjustment of different space weight distribution based on the spectral sensitivity difference of the turbid water area; s5, constructing an ICESat-2 and remote sensing image joint inversion water depth model based on turbidity partitioning; s6, spatial interpolation is carried out on a water depth inversion result, residual noise and adjacent pixel differences possibly occurring in the image are suppressed, and continuous water depth is obtained; according to the invention, large-range water depth inversion without field actual measurement work can be realized.

The invention discloses a water environment monitoring method based on image vision, and relates to the technical field of water environments, and the method comprises the steps: continuously shooting water body images of different depths at preset intervals in the vertical direction through an underwater camera; calculating the color difference of two adjacent pictures, and determining a water quality mutation layer; when it is detected that the turbidity in the water quality abrupt change layer interval exceeds a preset threshold value, infrared spectral imaging and ultrasonic ranging cooperative work is switched, the penetrability characteristic of an infrared image and ultrasonic depth calibration data are combined, the layering positioning error is corrected, and the water quality abrupt change layer interval is obtained. Through vertical interval shooting, color difference analysis, infrared and ultrasonic collaborative correction and a dynamic sampling strategy, the precision and efficiency of water quality layered monitoring are improved.

The invention discloses an intelligent water depth measurement method for waterway maintenance of a water transportation project, and particularly relates to the technical field of water conservancy projects. Historical sounding data, meteorological and hydrological parameters, real-time sonar echo data and unmanned surveying ship path information of the target channel area are acquired; a multi-source sounding data fusion model is constructed, and heterogeneous data fusion is realized by adopting wavelet domain feature extraction, remote sensing delay compensation and a graph attention mechanism; constructing a water depth evolution characteristic spectrum based on multi-scale spatial domain characteristic extraction; modeling a water depth propagation relationship between the sounding units by using a graph neural network; projecting the evolution graph to a section grid, and outputting a continuous water depth prediction value in combination with residual error correction and a rolling prediction strategy; identifying a water depth deviation by comparing with a designed navigation depth, and constructing a risk map layer; the method has the advantages of high prediction precision, strong adaptability, good response real-time performance and the like, and can be widely applied to scenes of channel siltation monitoring, scouring early warning, shipping maintenance management and the like.

The invention discloses a water area and resource quantity monitoring and predicting method and system based on a remote sensing technology, and belongs to the technical field of water resource monitoring. The method comprises the following steps: determining a water area range according to historical data of a research area and an on-site survey condition, and determining a research area range; the method comprises the following steps: respectively acquiring ground data and water depth and water surface elevation data by using an unmanned aerial vehicle and an unmanned ship, respectively processing to obtain a land DEM and a water area DEM, and fusing to form an all-terrain DEM; downloading satellite image data of the research area, and performing geographical registration on the satellite image data; in the geographically registered satellite image data, describing the boundary of the water area through visual interpretation; superposing the water area boundary to an all-terrain DEM, obtaining the elevation of each point on the water area boundary line, calculating the average elevation of the water area boundary, and calculating the water area and the water resource amount to obtain the historical water area and the water resource amount; and on the basis of the obtained historical water area and water resource quantity, utilizing an ARIMA model to predict future water resource quantity and water area.

The invention relates to the field of laser water depth detection, in particular to a water surface fluctuation compensation method for laser sounding, and solves the problems of insufficient precision and water surface fluctuation interference in a traditional sounding technology in an extremely shallow water area. The measured water depth is corrected through the turbidity sensor, the IMU zero offset compensation sensor and the laser displacement sensor, and the purpose of improving the measurement accuracy is achieved. According to the scheme, the stability and precision of depth sounding of the extremely shallow water area are remarkably improved, and the method has high environmental adaptability and wide application prospects.

The invention provides a river sediment physical habitat evolution identification method, device and system and a medium. The method comprises the following steps: acquiring a multi-temporal remote sensing image and hydrological data (flow Q, water level Zw and slope S), screening and other hydrological condition image pairs; extracting a water surface range, and calculating the average width B of the main groove; deducing the average water depth h by using a Manning formula, and calculating the riverbed elevation zbed by combining the Zw; the difference value delta zbed of zbed in different periods is calculated, and the substrate state is judged according to the difference value delta zbed and a threshold value epsilon; and performing segment processing along the center line to output a spatial distribution result. On-site measurement is not needed by relying on conventional data, and consumption is reduced; water level interference is eliminated through equal hydrological condition matching, and comparability is ensured; water depth inversion and differential analysis directly reflect scour deposition and quantitatively reveal rules; long-distance automatic processing improves space-time coverage capability and precision, and provides a basis for river regulation, ecological restoration and drainage basin management.

The invention provides a water depth pressure dynamic data characteristic value real-time calculation method and system, electronic equipment and a storage medium, and relates to the technical field of water pressure monitoring. The method comprises the steps that voltage signals reflecting water depth changes of multiple channels are collected, the relevance of the voltage signals is analyzed, and the main fluctuation frequency of water flow is determined; setting a merging proportion, and fusing the multi-channel signals into a target signal; separating the target signal into a smooth trend part and an abrupt change part, and setting an abrupt change judgment threshold based on the energy change; detecting and marking a mutation time interval in the mutation part by using the threshold, and extracting the maximum fluctuation amplitude and duration in the interval as a first feature value; meanwhile, the smooth trend part is used for predicting and correcting the long-term reference offset of the voltage collecting device, the maximum value, the minimum value and the fluctuation range are output on the basis of the corrected signal to serve as second feature values, real-time feature extraction of the dynamic water depth pressure can be achieved, meanwhile, a sudden change event is accurately captured, and a stable extreme value range is output after drift is corrected.

The invention provides a laying tool, a laying method and a recovery method for a sailing type temperature-salinity-depth detector, and the tool comprises a tow fish which is provided with an attitude sensor on the surface of a housing and is used for detecting the pitch angle of the tow fish; the throwing frame is installed on the ship body and used for guiding the laying path of the tow fish; the winch is installed on a ship afterdeck or in a cabin, and the tow fish is hung through a mooring rope. Wherein an executing mechanism of the winch is in communication connection with the attitude sensor and is configured to respond to an attitude signal generated when the tow fish enters water and drive the tow fish to be adjusted to be in a vertical state; and driving the tow fish to be adjusted to be in a horizontal state in response to a posture signal when the tow fish is out of water. The laying tool provided by the invention is suitable for various laying scenes, realizes automatic posture adjustment of the tow fish when the tow fish enters and exits water, improves the automation degree and safety of operation, avoids human interference, and is beneficial to improving the measurement precision of the temperature-salinity-depth sensor.

The invention belongs to the technical field of underwater measurement, and discloses a test probe underwater depth automatic positioning method and system, and the method comprises the steps: collecting an absolute water pressure value of a current underwater environment, and carrying out the calculation of a hydrostatic pressure value through combining with water surface reference air pressure data; meanwhile, acoustic signals from the water surface base station are received, response is returned, and the round-trip propagation time of sound waves in the water body is measured and obtained; collecting water body temperature data and salinity change data, estimating density information of the current water body, and converting a hydrostatic pressure value into a pressure depth value; calculating an average sound wave propagation speed by adopting an empirical sound velocity model, and calculating an acoustic depth value of the probe in combination with back-and-forth propagation time of sound waves in the water body; the depth positioning precision and stability of the underwater probe in a complex environment are effectively improved, and high-reliability and high-precision underwater depth automatic positioning is realized.

The invention provides a river flow online measurement and calculation method based on multi-source data fusion, and belongs to the technical field of river flow measurement. A Bayesian neural network and active learning collaborative hydrological memory reconstruction model is adopted to carry out high-confidence data interpolation on a sensor failure period and quantify uncertainty, fractional calculus is introduced to model a river memory effect, and flow evolution is analyzed through a fractional order water balance equation. And selecting a steady-state or non-constant flow calculation mode according to the flow change rate, inverting an optimal flow field for the non-constant flow by adopting a four-dimensional variational data assimilation method in combination with regularization constraint and time smoothing constraint, and outputting a flow measurement result and an uncertainty quantitative index. The technical problems that flow measurement and calculation data are missing and accurate interpolation is difficult due to sensor failure under the extreme hydrological condition are solved.

The invention discloses a topographic change uncertainty analysis method based on time sequence sounding data, and relates to the technical field of marine surveying and mapping. According to the method, high-precision seabed deformation sequence data is acquired through time-space reference unification and data fusion correction processing based on multi-beam sounding data acquired by multiple periods and multiple platforms, and the influence of terrain gradient, seawater depth and the coupling effect of the terrain gradient and the seawater depth on the sounding uncertainty is systematically and quantitatively analyzed; comprehensively considering a coupling effect relationship between water depth and terrain gradient, combining horizontal uncertainty information obtained by the gradient-uncertainty statistical model with vertical uncertainty information obtained by the water depth-uncertainty statistical model based on an error propagation theory, and establishing a gradient-water depth joint probability statistical model under multi-period data constraint; the statistical separation capability of terrain deformation signals and measurement noise is remarkably improved, real and accurate seabed deformation information can be obtained, and precise detection and dynamic monitoring of seabed micro-landform changes in a complex deep sea environment are achieved.

The invention discloses a water depth inversion and coastal zone topographic surveying and mapping method based on a laser radar, and the method is applied to a surveying and mapping instrument mounted on a small unmanned helicopter, and achieves the quick and accurate measurement of the coastal zone topography. The surveying instrument comprises the following instruments: a laser radar, a camera, an inertial measurement unit and a global positioning unit. The method comprises the following steps: completing internal and external parameter calibration of each sensor on a surveying instrument; using the unmanned aerial vehicle to mount the surveying instrument to the to-be-measured area, and moving to obtain topographic data of the to-be-measured area; preliminarily constructing an odometer by using Kalman filtering, and constructing a land topographic map; the method comprises the following steps: recording motion characteristics of sea waves by using a laser radar point cloud elevation, obtaining a laser radar point cloud elevation program sequence, obtaining the water depth of an offshore sea area through a cBathy water depth estimation algorithm, and converting the water depth into a sea area topographic map; and combining the two topographic maps into a complete coastal zone topographic map based on the geographic coordinates.

The invention relates to the technical field of ecological monitoring, in particular to a resident-free island resource monitoring method based on a spatial three-dimensional model, and the method comprises the following steps: S1, building a remote sensing image interpretation information base; s2, based on the remote sensing image interpretation information base, generating an island space three-dimensional model containing island land terrain and shoreline distribution; s3, generating a total element three-dimensional dynamic map; s4, the interpretation result and the total element three-dimensional dynamic map in the S3 are superposed, and a reef area comprehensive distribution map is generated; s5, calculating the island resource development intensity and the ecological risk level, and outputting an island ecological assessment report; and S6, generating an island resource monitoring report. According to the invention, unmanned aerial vehicle aerial survey, GNSS measurement, depth sounding technology, image interpretation and ecological assessment are combined, a high-precision total-factor three-dimensional dynamic monitoring system is constructed, accurate analysis and visual expression of the current island resource utilization situation are realized, and scientific decision support is provided for island management and ecological protection.

The invention discloses a cross section water depth continuous measurement method and system based on millimeter waves, and relates to the technical field of hydrographic measurement. According to the invention, through a millimeter wave radar array and a multiple-input-multiple-output antenna, a frequency modulation continuous wave signal is transmitted and a mixed echo signal is received; extracting time-frequency characteristics by using wavelet transform and short-time Fourier transform, and classifying reflection peaks in combination with a Gaussian mixture model; calculating the thickness of an ice layer, the thickness of an air interlayer and an initial water level based on the delay inequality, and dynamically correcting an error through adaptive Kalman filtering; a dynamic focusing algorithm is adopted to synthesize water surface and riverbed reflection signals, and a sand content compensation and flow velocity correction model is introduced to optimize water depth and riverbed elevation inversion; the three-dimensional interpolation weight is optimized through an ant population algorithm, and a high-precision cross section continuous water depth distribution diagram is generated; according to the invention, the problems of poor penetrability, weak anti-interference capability and low continuous water depth precision are solved, and full-section dynamic monitoring of the ice layer thickness, the water level, the water depth and the riverbed form is realized.

The invention relates to an unmanned aerial vehicle towed body positioning attitude measurement method based on binocular vision positioning, and relates to the technical field of computer processing, and the method comprises the following steps: S01, constructing a measurement system which comprises an unmanned aerial vehicle and a towed body connected with the unmanned aerial vehicle through a cable; the unmanned aerial vehicle carries a GNSS module, an IMU module and a binocular camera, and the upper surface of the towed body is provided with a coding pattern and carries a sonar sensor; s02, establishing a towed body coordinate system by taking the acoustic center of the sonar sensor as an original point, obtaining three-dimensional coordinates of feature points on the towed body in the towed body coordinate system, and generating a three-dimensional space model operation simulation model of the towed body; and S03, the binocular camera is calibrated. According to the invention, the problem of underwater topographic survey of a near-shore high-flow-velocity turbid water area is solved, and high-efficiency, low-cost and high-precision surveying and mapping operation is realized.

An apparatus and method for predicting sea level fluctuations are disclosed. The method for predicting sea level fluctuations includes: acquiring past time-series data of past wind stress and past sea level height, determining an optimal length of a time lag of a response function representing a convolution relationship between the past wind stress and the past sea level height and a future sea level height, determining weighting factors of the past wind stress and the past sea level height in the response function to which the determined optimal length of the time lag is applied, and calculating the future sea level height using the response function to which the determined weighting factors are applied.

The invention discloses a dynamic isobath generation method combining super-resolution water depth and real-time water level, and belongs to the technical field of marine surveying and mapping. Extracting sparse production water depth data from a standard electronic chart product, and converting the sparse production water depth data into a low-resolution water depth digital elevation model under a unified coordinate system; performing super-resolution reconstruction on the low-resolution water depth digital elevation model by using a deep learning super-resolution model to generate a high-resolution water depth digital elevation model; acquiring real-time water level data; carrying out fusion calculation on the high-resolution water depth digital elevation model and the real-time water level data to obtain an actual water depth digital elevation model; and extracting a dynamic isobath from the actual water depth digital elevation model. According to the method, the problem that the static isobath in the existing electronic chart cannot respond to the real-time water level change is solved, full-automatic generation from sparse water depth data to the high-precision dynamic isobath is realized, and the water depth information accuracy and the navigation safety guarantee capability of the electronic chart are remarkably improved.

A system for determining minimum and maximum water depth value at a location on a body of water is provided. The system utilizes various data sources, including historical and community-sourced data, environmental data, geographical data, and sensor data, to provide an accurate and dynamic estimation of the minimum and maximum water depth value. By considering multiple factors affecting water depth, such as tides, and weather conditions, the system enables safer navigation. Users can input a location and receive the minimum and maximum water depth value, which is continuously updated based on the latest available data. The system also facilitates route planning by determining the minimum water depth values along a route and providing alerts when necessary, allowing users to make informed decisions and navigate safely. By leveraging diverse data sources, the system provides a comprehensive and reliable solution for determining minimum and maximum water depth values compared to existing systems.

Method, system, and non-transitory computer readable storage medium are provided for creating a shelf bathymetric map. In some embodiments, a satellite image with a shelf area and related altimeter data for at least a number of points of the shelf area are obtained. The shelf area in the satellite image and depth values for the shelf area from said altimeter data are selected. The selected depth values are associated with points of the shelf area based on geo-coordinates. A training dataset and a testing dataset are created from the associated points. A neural network is trained on the training dataset. The neural network is tested on the testing dataset. Inference of the neural network is adjusted based on testing results. A depth value for each satellite image pixel of the shelf area is predicted by the neural network.

The invention discloses a flood water depth estimation method based on deep learning and an FwDET model. The method is used for solving the problems that in a traditional method, multi-source data consistency is poor, change detection precision is low, water depth estimation is complex, and a structured result is lacked. According to the method, high-precision flood recognition is achieved through double-time-phase same-source SAR remote sensing images, the depth of the flood is rapidly estimated in combination with DEM data, an automatic processing flow is constructed, efficient, accurate and extensible flood disaster monitoring is achieved from pixel-level recognition to vectorization expression, and reliable data support is provided for disaster assessment and emergency response.

The invention provides a sparse Bayesian learning-based matched broadband modal phase velocity inversion earth sound parameter method and system, and the method comprises the steps: extracting a local mode through employing a receiving signal of a vertical array, and removing the narrowband limitation of block sparse Bayesian; the broadband modal phase velocity is used for matching inversion of the earth sound parameters, and decoupling of the earth sound parameters is achieved. The method has the advantages that seabed parameters do not need to be known priori, the depth range of the extraction mode is not limited by the aperture of the VLA, and the method can be applied to a non-uniform vertical array; when the earth sound parameters are inversed, the earth sound parameters are not influenced by the terrain on the propagation path, and the earth sound parameters of any terrain can be inversed; known sound source position information is not needed, and the problem of inaccurate inversion result caused by inaccurate sound source position is avoided; and meanwhile, multi-distance sound source signals are used for inversion, so that the inversion of the earth sound parameters is more robust and accurate.

The present invention relates to the technical field of marine hydrological monitoring, and in particular to an underwater profile density measurement system and method. The system comprises a survey vessel, a vessel anchor, a steel wire rope, rope guide devices, a parameter measurement device, a measurement and control transmission cable, and a data analysis system. The method comprises: connecting a vessel anchor to a steel wire rope, and then dropping the vessel anchor to a water bottom for anchoring and fixing; enabling a parameter measurement device to enter water along with a measurement and control transmission cable and to maintain movable connection with the steel wire rope; successively pulling the measurement and control transmission cable according to equally spaced markers to move upwards along the steel wire rope from an anchor point, and collecting two water pressure values at different depths and an attitude angle value measured by the parameter measurement device underwater; storing the collected data in a data analysis system, and on the basis of a built-in algorithm, obtaining the density of water around the parameter measurement device; and when the parameter measurement device moves upwards from the anchor point and leaves the water, performing integral processing on the measured data at all points to obtain the total water depth at the anchor point so as to obtain profile density values from the measurement device at different depths underwater, and drawing and generating a curve.

The invention discloses a seabed obstacle identification method based on multi-beam point cloud data and related equipment. The method comprises the following steps: acquiring the multi-beam point cloud data of a target area; performing statistics on the basis of the elevation difference between the adjacent sounding point clouds to obtain a frequency-based elevation difference histogram; fitting an attenuation model according to the elevation difference histogram, determining a noise threshold value based on the attenuation model, and dividing the multi-beam point cloud data into a real terrain point cloud and a noise point cloud by using the noise threshold value; a multi-beam real terrain point cloud is obtained through iterative denoising division; and based on the multi-beam real terrain point cloud, obstacle identification is carried out by using the elevation slope, and obstacle information of the target area is obtained. According to the method, through the automatic processes of determining the noise threshold value through the fitting attenuation model and iterative denoising, a traditional interactive filtering method depending on experience of technicians is replaced, the data processing efficiency is greatly improved, and the method can be widely applied to the technical field of data processing.

The invention discloses a self-adaptive water depth dual-channel conversion single-photon water depth laser radar and a working method thereof, and relates to the field of single-photon laser radars, in the laser radar, a blue-green laser emits laser to a laser scanning system through a perforated reflector; after a scanning light path of the laser scanning system is reflected by the water surface, an echo signal is returned to the receiving optical system; the receiving optical system divides the echo signal into a linear receiving channel and a single photon receiving channel according to a light splitting ratio, and respectively focuses the echo signal to a linear PMT module and a photon counting PMT module; the main control unit is connected with the data processing and storage module and used for receiving the water depth calculation result output by the data processing and storage module in real time and controlling a switch of the electric diaphragm. According to the invention, a water depth adaptive dual-mode measurement technology is realized, and the efficiency and accuracy of measurement work are improved.

The invention belongs to the technical field of underwater measurement systems, and particularly relates to a novel unmanned aerial vehicle mounting type water depth measurement system which comprises an unmanned aerial vehicle platform, a GPS-RTK module, a photographing lens, a detection host, a data transmission line, a depth measurement probe, a data recording trigger device and a ground control station. The GPS-RTK module, the photographing lens and the detection host are all mounted on the unmanned aerial vehicle platform; the detection host is connected with the sounding probe through a data transmission line. Through real-time differential positioning of the GPS-RTK module, centimeter-level positioning precision can be provided, the position accuracy of sounding data is ensured, compared with traditional shipborne GPS positioning, the precision is improved by one order of magnitude, the unmanned aerial vehicle platform is matched to reach water areas where traditional ships cannot reach, such as shoals, narrow riverways and upstream of reservoirs, and the unmanned aerial vehicle platform is matched with the unmanned aerial vehicle platform to reach the water areas where the traditional ships cannot reach. The application range of sounding is greatly expanded, and meanwhile, the hovering capability and the accurate controllability of the unmanned aerial vehicle enable the sounding operation to be more flexible and efficient.