A riverway monitoring system and method based on unmanned aerial vehicle aerial image

Abstract

This invention relates to the field of river management technology, specifically to a river monitoring system and method based on UAV aerial imagery, comprising: an upload module for uploading river distribution parameters and constructing a river distribution model based on these parameters; a selection module for traversing the river distribution model and selecting aerial photography points within it; and a sensing module for real-time sensing of solar pose information. In the process of acquiring river images based on aerial photography points, this invention ensures that the aerial photography point, the location information of the aerial photography equipment itself, and the position coordinates of the sun relative to the UAV aerial photography equipment are collinear. This guarantees, to the greatest extent possible, that there is no light reflection in the river images during the acquisition process, resulting in more reliable evaluation results when the acquired river images are used for river health assessment.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of river management, in particular to a river monitoring system and method based on unmanned aerial vehicle aerial image. BACKGROUND

[0002] River management is a key measure to improve water environment and maintain water ecological balance. It covers desilting and dredging, removing pollutants in river sediment; restoring water ecosystems, planting aquatic plants, and releasing aquatic animals; controlling source pollution and blocking sewage discharge. Through a series of measures, the water quality of the river is improved, and its ecological function is restored.

[0003] The invention patent with application number 202311339929.2 discloses a river water quality intelligent monitoring method, which comprises: acquiring water quality sensing data in the corresponding preset division area through self-moving sensors arranged in different preset division areas in the target river area; different preset division areas are separated by a screen; acquiring water quality sensing data and corresponding data parameters obtained by each self-moving sensor; the data parameters include at least two of acquisition time, acquisition position, acquisition time speed and acquisition time device parameters; the acquisition time device parameters include at least one of device type, device power, device health degree parameter and device wear degree parameter; according to the water quality sensing data and the corresponding data parameters obtained by each self-moving sensor, the water quality pollution parameters corresponding to each preset division area are determined; according to the water quality sensing data and the corresponding data parameters obtained by each self-moving sensor, the water quality pollution situation corresponding to each preset division area is determined, which comprises: for each preset division area, acquiring the water quality sensing data and the corresponding data parameters obtained by all self-moving sensors in the preset division area; for the water quality sensing data obtained by any self-moving sensor in the preset division area, determining the water quality pollution degree parameter corresponding to the water quality sensing data according to the neural network algorithm model; determining the accurate weight corresponding to the water quality sensing data according to the data type and the data parameters of the water quality sensing data.

[0004] The application aims to solve the problem that the existing water quality monitoring means basically rely on simple sensors and data determination rules to achieve, and in some areas where water pollution is serious and critical, the existing technology cannot achieve effective monitoring effect.

[0005] However, there is also a technology for monitoring the river by taking aerial images of the river by unmanned aerial vehicles, but this technology has a high demand for manual control in the application process, and the collected river images may have reflection, refraction and other problems due to environmental light, resulting in poor river image recognition and usability;

[0006] To this end, a river monitoring system and method based on aerial images of unmanned aerial vehicles are proposed. SUMMARY

[0007] In view of the above-mentioned shortcomings of the prior art, the present application provides a river monitoring system and method based on aerial images of unmanned aerial vehicles, which solves the technical problems raised in the background art.

[0008] To achieve the above-mentioned purposes, the present application is realized by the following technical solutions:

[0009] In a first aspect, a river monitoring system based on aerial images of unmanned aerial vehicles comprises:

[0010] An uploading module is configured to upload river distribution parameters and construct a river distribution model based on the river distribution parameters; a selection module is configured to traverse the river distribution model and select aerial points in the river distribution model; a perception module is configured to perceive real-time solar pose information; a control module is configured to set operation parameters of an unmanned aerial vehicle aerial device, control the unmanned aerial vehicle aerial device to run and execute a river image collection task; an evaluation module is configured to receive river images collected by the unmanned aerial vehicle aerial device and evaluate river health situations based on the river images; and a recording module is configured to record evaluation results of river health situations in historical operation of the evaluation module.

[0011] The uploading module is connected with a construction unit and a configuration unit through wireless network interaction, the uploading module is connected with a selection module through wireless network interaction, the selection module is connected with a self-defined unit, i.e., a pickup unit, through wireless network interaction, the selection module is connected with a perception module and a control module through wireless network interaction, the control module is connected with the uploading module and the selection module through wireless network interaction, the control module is connected with an evaluation module and a recording module through wireless network interaction, and the evaluation module is connected with a preprocessing unit through wireless network interaction.

[0012] Further, the uploaded river distribution parameters of the uploading module are coordinates of all bend nodes in the river and head and tail coordinates, and the uploading module uploads the river distribution parameters in sequence based on river directions when uploading the river distribution parameters.

[0013] The uploading module is connected with a sub-module, which comprises:

[0014] A construction unit is configured to receive river distribution parameters and construct a river distribution model based on the river distribution parameters and the sequence of uploading the river distribution parameters in the uploading module;

[0015] A configuration unit is configured to select a point on the contour of the river distribution model, configure real coordinates for the selected point, and synchronously configure a scale of the river distribution model.

[0016] In the construction unit running stage, the riverway distribution parameters are sequentially connected to construct a polyline representing a riverway path, the polyline representing the riverway path is translated by half of the riverway width to both sides respectively to obtain two polylines representing riverway boundaries, and the endpoints of the two polylines representing the riverway boundaries are connected to each other to construct a graph representing the riverway, which is recorded as a riverway distribution model. After the real coordinates and the scale are configured based on the configuration unit, the real coordinates of any point on the riverway distribution model are known.

[0017] Further, the selection module is further provided with a sub-module, including:

[0018] The custom unit is configured to customize the aerial photography point spacing on the system side, and select an aerial photography reference point on the centerline of the riverway distribution model based on the starting point of the riverway distribution model and the aerial photography point spacing.

[0019] The pickup unit is configured to capture the centerline nodes of the riverway distribution model, and capture the centerline nodes of the riverway distribution model as the aerial photography reference points.

[0020] Further, after the aerial photography reference points are determined, the aerial photography reference points are further subjected to repeated point identification, and the repeated aerial photography reference points are deleted to leave only one of the repeated aerial photography reference points.

[0021] Further, after the aerial photography reference points are determined, a perpendicular line of the centerline of the riverway distribution model is further selected based on each aerial photography reference point, and any two points on the perpendicular line are selected as aerial photography points. The vertical distance from each aerial photography point to the centerline of the riverway distribution model is not equal, and the distance between the aerial photography points on each perpendicular line is half of the length of the centerline of the riverway distribution model.

[0022] When the aerial photography point is used for aerial photography of the riverway image by the unmanned aerial vehicle, the aerial photography point is the center of the camera for photographing the riverway image.

[0023] Further, the perception module is integrated with a four-quadrant photoelectric detector, and the unmanned aerial vehicle aerial photography equipment is configured to perceive the position information of the unmanned aerial vehicle aerial photography equipment in real time. The perception module is configured to output the position coordinates of the sun relative to the unmanned aerial vehicle aerial photography equipment, i.e., the sun pose information, based on the position information of the unmanned aerial vehicle aerial photography equipment perceived by the unmanned aerial vehicle aerial photography equipment.

[0024] The control module runs a stage, a system end user customizes an unmanned aerial vehicle aerial photography equipment flight height interval, a uploading module and a selection module synchronously transmit a river distribution model and an aerial photography point to the control module, and the control module forwards the river distribution model and the aerial photography point to the unmanned aerial vehicle aerial photography equipment, controls the unmanned aerial vehicle aerial photography equipment to execute a flight task based on a predetermined flight height interval, the river distribution model and the aerial photography point, and collects river images at the aerial photography point.

[0025] Further, when the control module controls the unmanned aerial vehicle aerial photography equipment to execute a river image collection task, the unmanned aerial vehicle aerial photography equipment coordinates its position by means of translation flight and up-down movement flight, so that the aerial photography point, the position information of the unmanned aerial vehicle aerial photography equipment and the position coordinates of the sun relative to the unmanned aerial vehicle aerial photography equipment are collinear each time the river image is collected, the camera end of the unmanned aerial vehicle aerial photography equipment is opposite to the aerial photography point, and the river image is collected again.

[0026] The control module controls the river images collected by the unmanned aerial vehicle aerial photography equipment to be marked based on the aerial photography point information applied by the unmanned aerial vehicle aerial photography equipment in the collection stage.

[0027] Further, the evaluation module is internally provided with a sub-module, including:

[0028] A preprocessing unit is configured to acquire the river images received by the evaluation module, and convert the river images into gray scale images.

[0029] The preprocessing unit synchronously executes noise reduction processing before converting the river images into gray scale images.

[0030] Further, the river health situation evaluation logic in the evaluation module is expressed as:

[0031]

[0032] In the formula, S is a river health situation value, and a, β, γ and δ are weights. is a river water body color deviation degree; is a river water body texture complexity degree; A is a river image area determined after the water body boundary in the image is extracted by using an edge detection algorithm; P is a river image perimeter determined after the water body boundary in the image is extracted by using the edge detection algorithm; B dmin is a minimum possible value of the boundary definition degree customized by the system end user; A imp is a foreign matter area in the river image identified by using an image segmentation algorithm; A total is a river image area;

[0033] In the formula, A=A totalThe smaller S is, the healthier the river environment is, and vice versa, the worse the river environment is, the sum of alpha, beta, gamma and delta is 1, and all are positive numbers, based on the above formula, the maximum value in all calculation results is taken as the record module running record content;

[0034]

[0035] In the formula, H avg , S avg , V avg are the hue, saturation and lightness of the water body in the river image; H std , S std , V std are the standard hue, standard saturation and standard lightness of the river water body; is the preset maximum possible value of color deviation; CON, COR, ENE and ENT are the contrast, correlation, energy and entropy of the river image. is the preset highest value of texture complexity.

[0036] In the second aspect, a river monitoring method based on unmanned aerial vehicle aerial image includes the following steps:

[0037] Upload the river distribution parameters, construct a river distribution model based on the river distribution parameters, configure real coordinates for the river distribution model, set the aerial point selection logic, select the aerial point in the river distribution model based on the aerial point selection logic, set the unmanned aerial vehicle aerial equipment operation parameters, and collect the river image in combination with the aerial point, preprocess the collected river image, and execute the river health situation evaluation operation by applying the river image after preprocessing, and select the maximum river health situation evaluation result to execute the record operation according to the river health situation evaluation result of each river image.

[0038] Compared with the known public technology, the technical scheme provided by the present application has the following beneficial effects:

[0039] This invention provides a river monitoring system and method based on UAV aerial imagery. During execution, the system and method construct a river distribution model and configure real-world coordinates within it. Aerial photography points are selected within the model. Furthermore, based on the perception of solar pose information and the setting of operating parameters for the aerial photography equipment, it ensures that during river image acquisition, the aerial photography point, the equipment's own position, and the sun's position relative to the equipment are collinear. This minimizes light reflection in the river images during acquisition, resulting in more reliable and realistic assessments of river health when applied to river health evaluations. Moreover, the aforementioned control logic ensures a higher level of intelligent operation for the aerial photography equipment. Attached Figure Description

[0040] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the accompanying drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are merely some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without any creative effort.

[0041] Figure 1 This is a schematic diagram of a river monitoring system based on drone aerial imagery.

[0042] Figure 2 This is a flowchart illustrating a method for river monitoring based on drone aerial imagery. Detailed Implementation

[0043] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0044] The present invention will be further described below with reference to embodiments.

[0045] Example 1:

[0046] This embodiment presents a river monitoring system based on drone aerial imagery, such as... Figure 1 As shown, it includes:

[0047] Upload module 1 is used to upload river distribution parameters and construct a river distribution model based on the river distribution parameters;

[0048] The uploading module 1 uploads the river distribution parameters for all nodes of the bends in the river and the coordinates of the head and tail. The uploading module 1 uploads the river distribution parameters in sequence based on the river direction when uploading the river distribution parameters;

[0049] The uploading module 1 is provided with sub-modules, including:

[0050] The construction unit 11 is configured to receive the river distribution parameters and construct a river distribution model based on the sequence of uploading the river distribution parameters in the uploading module 1;

[0051] The configuration unit 12 is configured to select a point on the contour of the river distribution model, configure a real coordinate for the selected point, and synchronously configure a scale of the river distribution model;

[0052] In the construction unit 11, the river distribution parameters are sequentially connected to construct a polyline representing the river path, the polyline representing the river path is translated to both sides once by half of the river width, two polylines representing the river boundaries are obtained, the end points of the two polylines representing the river boundaries are connected to each other to construct a graph representing the river, and the graph is recorded as a river distribution model. After the real coordinate and the scale are configured by the configuration unit 12, the real coordinate of any point on the river distribution model is known;

[0053] The selection module 2 is configured to traverse the river distribution model and select a flight point in the river distribution model;

[0054] The selection module 2 is provided with sub-modules, including:

[0055] The self-defined unit 21 is configured to define the distance between flight points by the system, and select a flight reference point on the centerline of the river distribution model based on the starting point of the river distribution model and the distance between flight points;

[0056] The pickup unit 22 is configured to capture the centerline nodes of the river distribution model and take the captured centerline nodes of the river distribution model as the flight reference points;

[0057] After the flight reference points in the self-defined unit 21 and the pickup unit 22 are determined, the flight reference points are further subjected to repeated point recognition, and the repeated flight reference points are deleted to retain only one of each repeated flight reference point;

[0058] After the aerial reference points are determined, further vertical lines of the centerline of the river distribution model are made based on the aerial reference points, and any two points on the vertical lines are selected, and the two points selected on each vertical line are recorded as aerial point positions, the vertical distances from the points selected as the aerial point positions on each vertical line to the centerline of the river distribution model are not equal, and the interval between the points selected as the aerial point positions on each vertical line is half of the length of the centerline of the river distribution model;

[0059] The aerial point position is the center of the river image captured by the camera end when the unmanned aerial vehicle captures the river image by aerial photography.

[0060] The perception module 3 is used for real-time perception of the sun pose information.

[0061] The perception module 3 is integrated by a four-quadrant photoelectric detector, and the unmanned aerial vehicle aerial photography equipment perceives its own position information in real time during the running stage. The perception module 3 runs based on the self-position information perceived by the unmanned aerial vehicle aerial photography equipment, and outputs the position coordinates of the sun relative to the unmanned aerial vehicle aerial photography equipment, i.e. the sun pose information.

[0062] During the running stage of the control module 4, the system end user defines the flight height interval of the unmanned aerial vehicle aerial photography equipment, the uploading module 1 and the selection module 2 synchronously transmit the river distribution model and the aerial point position to the control module 4, and the control module 4 forwards the river distribution model and the aerial point position to the unmanned aerial vehicle aerial photography equipment, controls the unmanned aerial vehicle aerial photography equipment to execute the flight task based on the predetermined flight height interval, the river distribution model and the aerial point position, and collects the river image at the aerial point position.

[0063] The control module 4 is used for setting the running parameters of the unmanned aerial vehicle aerial photography equipment, and controlling the unmanned aerial vehicle aerial photography equipment to execute the collection task of the river image.

[0064] When the control module 4 controls the unmanned aerial vehicle aerial photography equipment to execute the collection task of the river image, the position of the unmanned aerial vehicle aerial photography equipment is coordinated by translation flight and up-down movement flight, so that the aerial point position, the self-position information and the position coordinates of the sun relative to the unmanned aerial vehicle aerial photography equipment are collinear when the river image is collected each time, the camera end on the unmanned aerial vehicle aerial photography equipment is opposite to the aerial point position, and the collection of the river image is then executed.

[0065] The control module 4 controls the unmanned aerial vehicle aerial photography equipment to collect the river image based on the aerial point position information applied by the unmanned aerial vehicle aerial photography equipment during the collection stage.

[0066] The evaluation module 5 is used for receiving the river image collected by the unmanned aerial vehicle aerial photography equipment, and evaluating the health situation of the river based on the river image.

[0067] The evaluation module 5 is internally provided with a sub-module, including:

[0068] The preprocessing unit 51 is used for obtaining the river image received by the evaluation module 5, and converting the river image into a gray image.

[0069] wherein the preprocessing unit 51 synchronously performs noise reduction processing before converting the river channel image into a grayscale image;

[0070] The river channel health situation evaluation logic in the evaluation module 5 is represented as:

[0071]

[0072] In the formula: S is the river channel health situation value; a, b, g, d are weights; is the river water color deviation degree; is the river water texture complexity degree; A is the river channel image area determined after extracting the water body boundary in the image using an edge detection algorithm; P is the river channel image perimeter determined after extracting the water body boundary in the image using an edge detection algorithm; B dmin is the minimum possible value of the boundary sharpness defined by the system end user; A imp is the impurity area in the river channel image identified through an image segmentation algorithm; A total is the river channel image area;

[0073] wherein A = A total The smaller S is, the healthier the river environment is, and vice versa. The sum of a, b, g, and d is 1, and they are all positive numbers. Based on the above formula, the maximum value of all calculation results is taken as the record module 6 running record content.

[0074]

[0075] In the formula: H avg , S avg , V avg are the hue, saturation, and lightness of the water body in the river channel image; H std , S std , V std are the standard hue, standard saturation, and standard lightness of the river water body; is the maximum possible value of the preset color deviation degree; CON, COR, ENE, and ENT are the contrast, correlation, energy, and entropy of the river channel image; is the highest value of the preset texture complexity;

[0076] Through the above formula, the river channel health situation is represented in a digital form, so that the system based on the continuous river channel health situation calculation result output monitors the river channel health situation.

[0077] The record module 6 is used to record the evaluation results of the historical running river channel health situation of the evaluation module 5.

[0078] The uploading module 1 is connected with the constructing unit 11 and the configuring unit 12 through the wireless network, the uploading module 1 is connected with the selecting module 2 through the wireless network, the selecting module 2 is connected with the self-defining unit 21 and the picking unit 22 through the wireless network, the selecting module 2 is connected with the sensing module 3 and the control module 4 through the wireless network, the control module 4 is connected with the uploading module 1 and the selecting module 2 through the wireless network, the control module 4 is connected with the evaluation module 5 and the recording module 6 through the wireless network, and the evaluation module 5 is connected with the preprocessing unit 51 through the wireless network.

[0079] In the embodiment, the uploading module 1 runs the uploading river distribution parameter, constructs the river distribution model based on the river distribution parameter, the constructing unit 11 synchronously receives the river distribution parameter, constructs the river distribution model based on the river distribution parameter and the sequence of the river distribution parameter uploaded by the uploading module 1, the configuring unit 12 selects a point on the contour of the river distribution model in real time, configures the real coordinates for the selected point, synchronously configures the scale of the river distribution model, the selecting module 2 runs the traversal of the river distribution model, selects the aerial photograph point in the river distribution model, the self-defining unit 21 synchronously defines the aerial photograph point interval through the system end, selects the aerial photograph reference point on the centerline of the river distribution model based on the starting point of the river distribution model and the aerial photograph point interval, the picking unit 22 captures the centerline node of the river distribution model in real time, takes the captured centerline node of the river distribution model as the aerial photograph reference point, the sensing module 3 further senses the sun pose information in real time, the control module 4 sets the running parameter of the unmanned aerial vehicle aerial photograph equipment, controls the unmanned aerial vehicle aerial photograph equipment to run and execute the collection task of the river image, the evaluation module 5 receives the river image collected by the unmanned aerial vehicle aerial photograph equipment, evaluates the river health situation based on the river image, the preprocessing unit 51 synchronously obtains the river image received by the evaluation module 5, converts the river image into a gray image, and finally records the evaluation result of the historical running river health situation of the evaluation module 5 through the recording module 6.

[0080] Through the system in the above embodiment, the unmanned aerial vehicle aerial photograph equipment applied to the river monitoring is provided with more intelligent control management, and through the historical record of the river health situation evaluation result, the river can be monitored for a long time, that is, the river health situation value continuously increases, indicating that the river environment is poor and needs to be maintained, and the river health situation value continuously decreases, indicating that the river environment tends to be healthy and has a certain self-healing ability.

[0081] Embodiment 2

[0082] In the specific implementation level, on the basis of embodiment 1, the embodiment refers to Figure 2 The embodiment 1 is further specifically described as follows:

[0083] A river monitoring method based on aerial images of unmanned aerial vehicles, comprising the following steps:

[0084] Step 1: upload river distribution parameters, build a river distribution model based on the river distribution parameters, and configure real coordinates for the river distribution model;

[0085] Step 2: set the aerial point selection logic, select the aerial point in the river distribution model based on the aerial point selection logic;

[0086] Step 3: set the unmanned aerial vehicle aerial equipment operation parameters, and combine the aerial point to collect river images;

[0087] Step 4: pre-process the collected river images, and apply the pre-processed river images to perform river health situation evaluation operation;

[0088] Step 5: according to the river health situation evaluation results of each river image, select the largest river health situation evaluation result to perform recording operation.

[0089] In summary, the method and system in the above embodiments ensure that the three points of the aerial point, the aerial equipment position information, and the position coordinates of the sun relative to the unmanned aerial vehicle aerial equipment are collinear during the river image collection process based on the aerial point, so as to ensure that there is no light reflection in the river image during the collection process. Therefore, when the collected river image is applied to river health evaluation, the evaluation result is more reliable, which can more truly reflect the real situation of the river water body. Based on the above control logic, the intelligent degree of the aerial equipment operation is higher.

[0090] The above embodiments are only used to illustrate the technical solutions of the present application, but not to limit them; although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that they can modify the technical solutions recorded in the foregoing embodiments, or make equivalent replacement for part of the technical features; and these modifications or replacements will not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A river monitoring system based on aerial images of unmanned aerial vehicles, characterized in that, The application relates to a river health state evaluation system, which comprises the following modules: An uploading module (1) is used for uploading river distribution parameters and constructing a river distribution model based on the river distribution parameters; A selection module (2) is used for traversing the river distribution model and selecting aerial photograph points in the river distribution model; A perception module (3) is used for real-time perception of sun position information; A control module (4) is used for setting the operation parameters of a UAV aerial photograph device, controlling the UAV aerial photograph device to run and execute a river image collection task; An evaluation module (5) is used for receiving the river images collected by the UAV aerial photograph device and evaluating the river health state based on the river images; A recording module (6) is used for recording the evaluation results of the historical operation of the river health state of the evaluation module (5); The uploading module (1) uploads the coordinates of all bend nodes in the river and the head and tail coordinates as the river distribution parameters, and the uploading module (1) uploads the river distribution parameters in sequence based on the river direction when uploading the river distribution parameters; The uploading module (1) is provided with a sub-module, which comprises: A construction unit (11) is used for receiving the river distribution parameters and constructing a river distribution model based on the sequence of the river distribution parameters and the uploading sequence of the river distribution parameters in the uploading module (1); A configuration unit (12) is used for selecting a point on the contour of the river distribution model, configuring the real coordinates of the selected point and synchronously configuring the scale of the river distribution model; In the running stage of the construction unit (11), the river distribution parameters are sequentially connected to construct a polyline representing a river path, the polyline representing the river path is translated to both sides once by applying one-half of the river width, two polylines representing the river boundaries are obtained, the end points of the two polylines representing the river boundaries are connected to each other to construct a graph representing the river, and the graph is recorded as a river distribution model. After the real coordinates and the scale of the river distribution model are configured by the configuration unit (12), the real coordinates of any point on the river distribution model are known; The selection module (2) is provided with a sub-module, which comprises: A self-defined unit (21) is used for defining the aerial photograph point distance on the system side, selecting aerial photograph reference points on the center line of the river distribution model based on the starting point of the river distribution model and the aerial photograph point distance; A pickup unit (22) is used for capturing the center line nodes of the river distribution model and taking the captured center line nodes of the river distribution model as the aerial photograph reference points; After the aerial photograph reference points in the self-defined unit (21) and the pickup unit (22) are determined, the repeated points of the aerial photograph reference points are further identified, the repeated aerial photograph reference points are deleted, and only one of the repeated aerial photograph reference points is reserved; The perception module (3) is integrated by four-quadrant photoelectric detectors, the position information of the UAV aerial photograph device is perceived in the running stage of the UAV aerial photograph device, the perception module (3) outputs the position coordinates of the sun relative to the UAV aerial photograph device based on the position information of the UAV aerial photograph device, and the position coordinates of the sun relative to the UAV aerial photograph device are the sun position information. The control module (4) runs a stage, and a system end user customizes a flight height interval of a UAV aerial photography device, the uploading module (1) and the selection module (2) synchronously transmit a river channel distribution model and a photography point to the control module (4), and the control module (4) forwards the river channel distribution model and the photography point to the UAV aerial photography device, controls the UAV aerial photography device to execute a flight task based on the predetermined flight height interval, the river channel distribution model and the photography point, and collects river channel images at the photography point; The evaluation module (5) is internally provided with a submodule, including: A preprocessing unit (51) is used for acquiring river channel images received by the evaluation module (5) and converting the river channel images into gray images; Wherein, the preprocessing unit (51) synchronously executes noise reduction processing before converting the river channel images into gray images; The evaluation logic of the river channel health situation in the evaluation module (5) is represented as: ； In the formula: is a river health situation value; is a weight; is a river water body color deviation degree; is a river water body texture complexity degree; is a river image area determined after using an edge detection algorithm to extract the water body boundary in the image; is a river image perimeter determined after using an edge detection algorithm to extract the water body boundary in the image; is a minimum possible value of boundary definition customized by a system end user; is a foreign matter area in the river image recognized through an image segmentation algorithm; is a river image area; wherein, = 0.5 , The smaller the value is, the healthier the river environment is, and vice versa. The sum of the two is 1, and both are positive numbers. Based on the above formula, calculate each river image, and take the maximum value of all calculation results as the record module (6) running record content. ； In the formula, is the hue, saturation, and lightness of the water body in the river image; is the standard hue, standard saturation, and standard lightness of the river water body; is the preset maximum possible value of the color deviation; is the contrast, correlation, energy, and entropy of the river image; is the preset highest value of the texture complexity. 2.The river monitoring system based on UAV aerial images according to claim 1, wherein, After the photography reference points are determined, a vertical line of a center line of the river channel distribution model is further made based on each photography reference point, and any two points on the vertical line are selected, and the two points selected on each vertical line are recorded as photography points, the vertical distances from the points selected as the photography points on each vertical line to the center line of the river channel distribution model are not equal, and the interval between the points selected as the photography points on each vertical line is one half of the length of the center line of the river channel distribution model; Wherein, the photography point is the center of the camera when the UAV photographs the river channel image. 3.The river monitoring system based on UAV aerial images according to claim 1, characterized in that, When the control module (4) controls the UAV aerial photography device to execute the collection task of the river channel image, the UAV aerial photography device coordinates its position by translating and moving up and down, so that the photography point, the position information and the position coordinates of the sun relative to the UAV aerial photography device are collinear each time the river channel image is collected, the camera end of the UAV aerial photography device is opposite to the photography point, and the collection of the river channel image is executed again. Wherein, the river channel images collected by the control module (4) are marked based on the photography point information applied in the collection stage. 4.The river monitoring system based on UAV aerial images according to claim 1, wherein, The subordinate of the uploading module (1) is interactively connected with a construction unit (11) and a configuration unit (12) through a wireless network, the uploading module (1) is interactively connected with a selection module (2) through a wireless network, the subordinate of the selection module (2) is interactively connected with a customizing unit (21) and a picking unit (22) through a wireless network, the selection module (2) is interactively connected with a sensing module (3) and a control module (4) through a wireless network, the control module (4) is interactively connected with the uploading module (1) and the selection module (2) through a wireless network, the control module (4) is interactively connected with an evaluation module (5) and a recording module (6) through a wireless network, and the subordinate of the evaluation module (5) is interactively connected with a preprocessing unit (51) through a wireless network.

5. A method for monitoring a river course based on aerial images taken by a UAV, the method being a method for implementing the system for monitoring a river course based on aerial images taken by a UAV according to any one of claims 1 to 4, characterized in that, The following steps are included: Step 1: upload river channel distribution parameters, construct a river channel distribution model based on the river channel distribution parameters, and configure real coordinates for the river channel distribution model; Step 2: set a photography point selection logic, select a photography point in the river channel distribution model based on the photography point selection logic; Step 3: set the operation parameters of the UAV aerial photography device, and collect the river channel image in combination with the photography point. Step4: pre-process the collected river images, and perform the river health situation evaluation operation on the pre-processed river images; Step5: according to the river health situation evaluation results of each river image, select the largest river health situation evaluation result to perform the recording operation.

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