River channel monitoring system and method based on aerial images of unmanned aerial vehicle

Abstract

The invention relates to the technical field of riverway treatment, in particular to a riverway monitoring system and method based on unmanned aerial vehicle aerial images, and the system comprises an uploading module which is used for uploading riverway distribution parameters and constructing a riverway distribution model based on the riverway distribution parameters; the selection module is used for traversing the riverway distribution model and selecting an aerial photography point location in the riverway distribution model; the sensing module is used for sensing sun pose information in real time; in the process of collecting the river channel image based on the aerial photography point location, the aerial photography point location, the position information of the aerial photography equipment and the position coordinate of the sun relative to the aerial photography equipment of the unmanned aerial vehicle are collinear, so that light reflection does not exist in the river channel image in the collecting process of the river channel image as far as possible, and the accuracy of the collection of the river channel image is ensured. When the acquired river channel image is applied to river channel health evaluation, the evaluation result is more reliable.

Description

Technical Field

[0001] The present invention relates to the technical field of river regulation, and particularly relates to a river monitoring system and method based on UAV aerial images. Background Art

[0002] River regulation is a key measure to improve the water environment and maintain the balance of the aquatic ecosystem. It includes dredging, removing pollutants in the river bottom mud; restoring the aquatic ecosystem, planting aquatic plants and releasing aquatic animals; controlling pollution sources and intercepting sewage, etc. Through a series of measures, the water quality of the river is improved and its ecological function is restored.

[0003] A patent for invention with the application number 202311339929.2 discloses a method for intelligent monitoring of river water quality. The method includes: obtaining water quality sensing data corresponding to a preset division area through an autonomous movable sensor arranged in different preset division areas in a target river area; separating different preset division areas by a partition net; obtaining the water quality sensing data and corresponding data parameters obtained by each autonomous movable sensor; the data parameters include at least two of the acquisition time, acquisition location, acquisition speed, and equipment parameters at the time of acquisition; the equipment parameters at the time of acquisition include at least one of the equipment type, equipment power, equipment health parameter, and equipment wear parameter; determining the water quality pollution parameter corresponding to each preset division area according to the water quality sensing data and corresponding data parameters obtained by each autonomous movable sensor; determining the water quality pollution situation corresponding to each preset division area according to the water quality sensing data and corresponding data parameters obtained by each autonomous movable sensor, including: for each preset division area, obtaining the water quality sensing data and corresponding data parameters obtained by all the autonomous movable sensors in the preset division area; for the water quality sensing data obtained by any one of the autonomous movable sensors in the preset division area, determining the water quality pollution degree parameter corresponding to the water quality sensing data according to a neural network algorithm model; and determining the accurate weight corresponding to the water quality sensing data according to the data type and the data parameters corresponding to the water quality sensing data.

[0004] This application aims to solve the problem of "existing water quality monitoring means basically rely on simple sensors and data determination rules to achieve, and in some areas with serious and critical water quality pollution problems, the prior art cannot achieve effective monitoring effects".

[0005] However, currently, there is also a technology for monitoring rivers by taking aerial images of rivers with UAVs. However, in the application process of this technology, the demand for manual control is relatively high, and affected by environmental light, the collected river images may have problems such as reflection and refraction, resulting in poor recognition and usability of the river images;

[0006] To this end, a river channel monitoring system and method based on UAV aerial images are proposed. Summary of the Invention

[0007] In view of the above-mentioned shortcomings of the prior art, the present invention provides a river channel monitoring system and method based on UAV aerial images, which solves the technical problems put forward in the above-mentioned background technology.

[0008] To achieve the above objectives, the present invention is realized through the following technical solutions:

[0009] In a first aspect, a river channel monitoring system based on UAV aerial images includes:

[0010] An upload module for uploading river channel distribution parameters and constructing a river channel distribution model based on the river channel distribution parameters; a selection module for traversing the river channel distribution model and selecting aerial photography points in the river channel distribution model; a perception module for real-time perceiving the sun's pose information; a control module for setting the operating parameters of the UAV aerial photography device and controlling the UAV aerial photography device to run and execute the task of collecting river channel images; an evaluation module for receiving the river channel images collected by the UAV aerial photography device and evaluating the health status of the river channel based on the river channel images; a recording module for recording the evaluation results of the health status of the river channel in the historical operation of the evaluation module;

[0011] The lower level of the upload module is connected to a construction unit and a configuration unit through wireless network interaction. The upload module is connected to the selection module through wireless network interaction. The lower level of the selection module is connected to a custom unit, namely a picking unit, through wireless network interaction. The selection module is connected to the perception module and the control module through wireless network interaction. The control module is connected to the upload module, namely the selection module, through wireless network interaction. The control module is connected to the evaluation module and the recording module through wireless network interaction. The lower level of the evaluation module is connected to a preprocessing unit through wireless network interaction.

[0012] Furthermore, the river channel distribution parameters uploaded by the upload module are the coordinates of all bend nodes in the river channel and the head and tail coordinates. When uploading the river channel distribution parameters, the upload module uploads the river channel distribution parameters in sequence based on the river flow direction;

[0013] The lower level of the upload module is provided with sub-modules, including:

[0014] A construction unit for receiving the river channel distribution parameters and constructing a river channel distribution model based on the river channel distribution parameters and the upload sequence of the river channel distribution parameters in the upload module;

[0015] A configuration unit for selecting a point on the contour of the river channel distribution model, configuring real-world coordinates for the selected point, and synchronously configuring the scale of the river channel distribution model;

[0016] During the operation stage of the building unit, the river channel distribution parameters are sequentially connected to construct a polyline representing the river channel path. By applying half of the river channel width, the polyline representing the river channel path is translated once to each side, resulting in two polylines representing the river channel boundaries. The endpoints of the two polylines representing the river channel boundaries are connected adjacent to each other to construct a graph representing the river channel, denoted as the river channel distribution model. After configuring the real coordinates and scale based on the configuration unit, the real coordinates of any point on the river channel distribution model are known.

[0017] Furthermore, a sub-module is provided under the selection module, including:

[0018] A custom unit for customizing the aerial photography point spacing at the system end, and selecting an aerial photography reference point on the midline of the river channel distribution model based on the starting point of the river channel distribution model and the aerial photography point spacing;

[0019] A picking unit for capturing the midline nodes of the river channel distribution model and using the captured midline nodes of the river channel distribution model as aerial photography reference points;

[0020] Among them, after the aerial photography reference points in the custom unit and the picking unit are determined, the recognition of duplicate points is further performed on the aerial photography reference points, and the recognized duplicate aerial photography reference points are deleted, so that only one of each duplicate aerial photography reference points is retained.

[0021] Furthermore, after the aerial photography reference points are determined, perpendicular lines to the midline of the river channel distribution model are made based on each aerial photography reference point. Any two points are selected on each perpendicular line, and the two points selected on each perpendicular line are both denoted as aerial photography points. The perpendicular distances from the points selected as aerial photography points on each perpendicular line to the midline of the river channel distribution model are not equal, and the distance between the points selected as aerial photography points on each perpendicular line is half of the length of the midline of the river channel distribution model;

[0022] Among them, the aerial photography point is the center of the river channel image captured by the camera end when the unmanned aerial vehicle takes an aerial photo of the river channel image.

[0023] Furthermore, the sensing module is integrated by a quadrant photodetector. During the operation stage of the unmanned aerial vehicle aerial photography device, the position information of the device itself is sensed in real time. The operation of the sensing module is based on the position information of the unmanned aerial vehicle aerial photography device sensed, and outputs the position coordinates of the sun relative to the unmanned aerial vehicle aerial photography device, that is, the sun pose information;

[0024] During the operation of the control module, the system-side user customizes the flight altitude range of the UAV aerial photography device. The upload module and the selection module synchronously transmit the river channel distribution model and the aerial photography points to the control module, and the control module forwards them to the UAV aerial photography device, controlling the UAV aerial photography device to execute the flight task based on the predetermined flight altitude range, the river channel distribution model and the aerial photography points, and collecting river channel images at the aerial photography points.

[0025] Furthermore, when the control module controls the UAV aerial photography device to execute the task of collecting river channel images, it coordinates its own position through translational flight and up-and-down movement flight, so that when collecting river channel images each time, the aerial photography point, its own position information, and the position coordinates of the sun relative to the UAV aerial photography device are collinear. The camera end on the UAV aerial photography device faces the aerial photography point, and then the collection of river channel images is executed;

[0026] Among them, the river channel images collected by the control module controlling the UAV aerial photography device are all marked based on the aerial photography point information applied during the collection stage.

[0027] Furthermore, there are sub-modules set inside the evaluation module, including:

[0028] The preprocessing unit is used to obtain the river channel images received during the operation of the evaluation module and convert the river channel images into grayscale images;

[0029] Among them, the preprocessing unit synchronously performs noise reduction processing before converting the river channel images into grayscale images.

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

[0031]

[0032] In the formula: S is the river channel health situation value; α, β, γ, δ are weights; is the deviation degree of the river channel water body color; is the complexity degree of the river channel water body texture; A is the area of the river channel image determined after using the edge detection algorithm to extract the water body boundary in the image; P is the perimeter of the river channel image determined after using the edge detection algorithm to extract the water body boundary in the image; B dmin is the minimum possible value of the boundary clarity customized by the system-side user; A imp is the impurity area in the river channel image identified by the image segmentation algorithm; A total is the area of the river channel image;

[0033] Among them, A = A total, the smaller the S, the healthier the river environment; on the contrary, the worse the river environment. The sum of α, β, γ, and δ is 1, and all are positive numbers. Based on the above formula, each river image is calculated, and the maximum value among all calculation results is taken as the content recorded by the recording module;

[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 maximum possible value of the preset color deviation; CON, COR, ENE, and ENT are the contrast, correlation, energy, and entropy of the river image; is the highest value of the preset texture complexity.

[0036] In the second aspect, a river monitoring method based on UAV aerial images includes the following steps:

[0037] Upload the river distribution parameters, construct a river distribution model based on the river distribution parameters, and configure real-world coordinates for the river distribution model; set the aerial photography point selection logic, and select aerial photography points in the river distribution model based on the aerial photography point selection logic; set the operating parameters of the UAV aerial photography equipment, and collect river images in combination with the aerial photography points; preprocess the collected river images, and perform an evaluation operation on the river health situation using the preprocessed river images; 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.

[0038] Adopting the technical solution provided by the present invention, compared with the known public technology, it has the following beneficial effects:

[0039] The present invention provides a river channel monitoring system and method based on UAV aerial images. During the execution of the system and method, by constructing a river channel distribution model and configuring real coordinates for the model, aerial photography points are selected in the river channel distribution model. Further, based on the perception of the sun's pose information and the setting of the operating parameters of the aerial photography equipment, it is ensured that during the process of the aerial photography equipment collecting river channel images based on the aerial photography points, the aerial photography points, the position information of the aerial photography equipment itself, and the position coordinates of the sun relative to the UAV aerial photography equipment are collinear. Thus, as much as possible, it is ensured that there is no light reflection in the river channel images during the collection process. When the collected river channel images are applied to the river channel health assessment, the assessment results are more reliable, and can more truly reflect the real situation of the river channel water body. And based on the above control logic, it is ensured that the operation of the aerial photography equipment has a higher degree of intelligence. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0041] Figure 1 It is a schematic structural diagram of a river channel monitoring system based on UAV aerial images;

[0042] Figure 2 It is a schematic flowchart of a river channel monitoring method based on UAV aerial images. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0043] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the drawings in the embodiments of the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts fall within the scope of protection of the present invention.

[0044] The following further describes the present invention with reference to the embodiments.

[0045] Embodiment 1:

[0046] A river channel monitoring system based on UAV aerial images in this embodiment, as Figure 1 shown, includes:

[0047] An upload module 1, configured to upload river channel distribution parameters and construct a river channel distribution model based on the river channel distribution parameters;

[0048] The uploaded river channel distribution parameters of the upload module 1 are the coordinates of all bend nodes and the start and end coordinates in the river channel. When the upload module 1 uploads the river channel distribution parameters, it uploads the river channel distribution parameters sequentially based on the river flow direction;

[0049] There are sub-modules set under the upload module 1, including:

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

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

[0052] Among them, during the operation stage of the construction unit 11, the river channel distribution parameters are sequentially connected to construct a polyline representing the river path. Applying half of the river channel width, the polyline representing the river path is translated once to each side to obtain two polylines representing the river channel boundaries. The endpoints of the two polylines representing the river channel boundaries are connected adjacent to each other to construct a graph representing the river channel, denoted as the river channel distribution model. After the real-world coordinates and scale are configured based on the configuration unit 12, the real-world coordinates of any point on the river channel distribution model are known;

[0053] The selection module 2 is used to traverse the river channel distribution model and select aerial photography points in the river channel distribution model;

[0054] There are sub-modules set under the selection module 2, including:

[0055] The customization unit 21 is used for the system side to customize the aerial photography point spacing, and select aerial photography reference points on the center line of the river channel distribution model based on the starting point of the river channel distribution model combined with the aerial photography point spacing;

[0056] The picking unit 22 is used to capture the center line nodes of the river channel distribution model and use the captured center line nodes of the river channel distribution model as aerial photography reference points;

[0057] Among them, after the aerial photography reference points in the customization unit 21 and the picking unit 22 are determined, the identification of duplicate points is further performed on the aerial photography reference points, and the identified duplicate aerial photography reference points are deleted, so that only one of each duplicate aerial photography reference point is retained;

[0058] After the aerial photography reference points are determined, perpendicular lines to the center line of the river channel distribution model are further drawn based on each aerial photography reference point. Any two points are selected on each perpendicular line, and the two points selected on each perpendicular line are both recorded as aerial photography points. The vertical distances from the points selected as aerial photography points on each perpendicular line to the center line of the river channel distribution model are not equal, and the distance between the points selected as aerial photography points on each perpendicular line is half of the length of the center line of the river channel distribution model;

[0059] Among them, the aerial photography point is the center of the river channel image captured by the camera end when the unmanned aerial vehicle (UAV) conducts aerial photography of the river channel;

[0060] The sensing module 3 is used to sense the sun's pose information in real time;

[0061] The sensing module 3 is integrated by a four-quadrant photodetector. During the operation of the UAV aerial photography equipment, it senses its own position information in real time. The operation of the sensing module 3 is based on the position information of the UAV aerial photography equipment sensed by itself, and outputs the position coordinates of the sun relative to the UAV aerial photography equipment, that is, the sun's pose information;

[0062] During the operation of the control module 4, the user of the system end customizes the flight altitude range of the UAV aerial photography equipment. The uploading module 1 and the selection module 2 synchronously transmit the river channel distribution model and the aerial photography points to the control module 4, and the control module 4 forwards them to the UAV aerial photography equipment, controlling the UAV aerial photography equipment to execute the flight task based on the predetermined flight altitude range, the river channel distribution model and the aerial photography points, and collecting the river channel images at the aerial photography points;

[0063] The control module 4 is used to set the operating parameters of the UAV aerial photography equipment and control the UAV aerial photography equipment to run and execute the task of collecting river channel images;

[0064] When the control module 4 controls the UAV aerial photography equipment to execute the task of collecting river channel images, it coordinates its own position through translational flight and up-and-down movement flight, so that when collecting river channel images each time, the aerial photography point, its own position information, and the position coordinates of the sun relative to the UAV aerial photography equipment are collinear. The camera end on the UAV aerial photography equipment faces the aerial photography point, and then the river channel images are collected;

[0065] Among them, the river channel images collected by the control module 4 controlling the UAV aerial photography equipment are all marked based on the aerial photography point information applied during the collection stage;

[0066] The evaluation module 5 is used to receive the river channel images collected by the UAV aerial photography equipment and evaluate the health status of the river channel based on the river channel images;

[0067] There are sub-modules set inside the evaluation module 5, including:

[0068] The preprocessing unit 51 is used to obtain the river channel images received by the evaluation module 5 during operation and convert the river channel images into grayscale images;

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

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

[0071]

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

[0073] Among them, A = A total , the smaller S is, the healthier the river channel environment is; conversely, the worse the river channel environment is. The sum of α, β, γ, δ is 1, and they are all positive numbers. Based on the above formula, each river channel image is calculated, and the maximum value among all calculation results is taken as the operation record content of the recording module 6;

[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 channel water body; is the maximum possible value of the preset color deviation degree; CON, COR, ENE, 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 - mentioned formula, the river channel health situation is represented in a digital form, so that this system monitors the river channel health situation based on the output of continuous river channel health situation calculation results.

[0077] The recording module 6 is used to record the evaluation results of the river channel health situation in the historical operation of the evaluation module 5;

[0078] The lower level of the upload module 1 is connected with a construction unit 11 and a configuration unit 12 through wireless network interaction. The upload module 1 is connected with a selection module 2 through wireless network interaction. The lower level of the selection module 2 is connected with a custom unit 21, i.e., a picking unit 22, through wireless network interaction. The selection module 2 is connected with a sensing module 3 and a control module 4 through wireless network interaction. The control module 4 is connected with the upload module 1, i.e., the selection module 2, through wireless network interaction. The control module 4 is connected with an evaluation module 5 and a recording module 6 through wireless network interaction. The lower level of the evaluation module 5 is connected with a preprocessing unit 51 through wireless network interaction.

[0079] In this embodiment, the upload module 1 runs to upload the river channel distribution parameters, constructs a river channel distribution model based on the river channel distribution parameters. The construction unit 11 synchronously receives the river channel distribution parameters and constructs the river channel distribution model based on the order of the river channel distribution parameters uploaded in the upload module 1. The configuration unit 12 selects a point on the contour of the river channel distribution model in real time, configures the real-world coordinates for the selected point, and synchronously configures the scale of the river channel distribution model. The selection module 2 runs later to traverse the river channel distribution model, selects aerial photography points in the river channel distribution model. The custom unit 21 synchronously customizes the spacing of the aerial photography points through the system end, selects an aerial photography reference point on the midline of the river channel distribution model based on the starting point of the river channel distribution model and the spacing of the aerial photography points. The picking unit 22 captures the midline nodes of the river channel distribution model in real time and uses the captured midline nodes of the river channel distribution model as the aerial photography reference points. The sensing module 3 further senses the sun pose information in real time, and then the control module 4 sets the operating parameters of the UAV aerial photography device, controls the UAV aerial photography device to run and execute the task of collecting river channel images. The evaluation module 5 receives the river channel images collected by the UAV aerial photography device, evaluates the health status of the river channel based on the river channel images. The preprocessing unit 51 synchronously obtains the river channel images received by the evaluation module 5 during operation, converts the river channel images into grayscale images, and finally records the evaluation results of the historical operation of the health status of the river channel by the recording module 6.

[0080] Through the system in the above embodiment, when the UAV aerial photography device is applied to river channel monitoring, it provides more intelligent control and management. And through the historical evaluation results of the health status of the river channel, long-term monitoring of the river channel can be implemented. That is, if the health status value of the river channel continues to increase, it means that the river channel environment deteriorates and needs maintenance. If the health status value of the river channel continues to decrease, the river channel environment tends to be healthy and has a certain "self-healing" ability.

[0081] Embodiment 2:

[0082] At the specific implementation level, on the basis of Embodiment 1, this embodiment refers to Figure 2 to further specifically describe a river channel monitoring system based on UAV aerial photography images in Embodiment 1:

[0083] A river channel monitoring method based on UAV aerial images, comprising the following steps:

[0084] Step1: Upload river channel distribution parameters, construct a river channel distribution model based on the river channel distribution parameters, and configure real-world coordinates for the river channel distribution model;

[0085] Step2: Set the aerial photography point selection logic, and select aerial photography points in the river channel distribution model based on the aerial photography point selection logic;

[0086] Step3: Set the operating parameters of the UAV aerial photography equipment, and collect river channel images in combination with the aerial photography points;

[0087] Step4: Preprocess the collected river channel images, and perform an evaluation operation on the river channel health situation by applying the preprocessed river channel images;

[0088] Step5: According to the evaluation results of the river channel health situation of each river channel image, select the largest river channel health situation evaluation result to perform a recording operation.

[0089] In summary, in the process of implementing the above method and system, by constructing a river channel distribution model and configuring real-world coordinates for the model, aerial photography points are selected in the river channel distribution model. Further, based on the perception of the solar pose information and the setting of the operating parameters of the aerial photography equipment, it is ensured that during the process of collecting river channel images based on the aerial photography points, the aerial photography points, the position information of the aerial photography equipment itself, and the position coordinates of the sun relative to the UAV aerial photography equipment are collinear. Thus, it is ensured as much as possible that there is no light reflection in the river channel images during the collection process. When the collected river channel images are applied to the evaluation of the river channel health, the evaluation results are more reliable, and can more truly reflect the real situation of the river channel water body. And based on the above control logic, it is ensured that the degree of intelligence of the operation of the aerial photography equipment is higher.

[0090] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements on some 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 invention.

Claims

1. A river channel monitoring system based on UAV aerial images, characterized in that, Including: An upload module (1) for uploading river channel distribution parameters and constructing a river channel distribution model based on the river channel distribution parameters; A selection module (2) for traversing the river channel distribution model and selecting aerial photography points in the river channel distribution model; A perception module (3) for real-time sensing of solar pose information; A control module (4) for setting the operating parameters of the UAV aerial photography device and controlling the UAV aerial photography device to run and execute the task of collecting river channel images; An evaluation module (5) for receiving the river channel images collected by the UAV aerial photography device and evaluating the river channel health status based on the river channel images; A recording module (6) for recording the evaluation results of the river channel health status of the historical operation of the evaluation module (5).

2. The river channel monitoring system based on UAV aerial images according to claim 1, wherein, The river channel distribution parameters uploaded by the upload module (1) are the coordinates of all bend nodes and the head and tail coordinates in the river channel. When uploading the river channel distribution parameters, the upload module (1) uploads the river channel distribution parameters sequentially based on the river flow direction; A sub-module is set under the upload module (1), including: A construction unit (11) for receiving the river channel distribution parameters and constructing a river channel distribution model based on the order of uploading the river channel distribution parameters in the upload module (1); A configuration unit (12) for selecting a point on the contour of the river channel distribution model, configuring real-world coordinates for the selected point, and synchronously configuring the scale of the river channel distribution model; Among them, during the operation stage of the construction unit (11), the river channel distribution parameters are sequentially connected to construct a polyline representing the river path. Applying half of the river channel width, the polyline representing the river path is translated once to each side to obtain two polylines representing the river channel boundaries. The endpoints of the two polylines representing the river channel boundaries are connected adjacent to each other to construct a graph representing the river channel, denoted as the river channel distribution model. After configuring the real-world coordinates and scale based on the configuration unit (12), the real-world coordinates of any point on the river channel distribution model are known.

3. The river channel monitoring system based on UAV aerial images according to claim 1, characterized in that, A sub-module is set under the selection module (2), including: A custom unit (21) for customizing the aerial photography point spacing at the system end and selecting aerial photography reference points on the midline of the river channel distribution model based on the starting point of the river channel distribution model and the aerial photography point spacing; A picking unit (22) for capturing the midline nodes of the river channel distribution model and using the captured midline nodes of the river channel distribution model as aerial photography reference points; Among them, after the aerial photography reference points in the custom unit (21) and the picking unit (22) are determined, the aerial photography reference points are further identified for duplicate points, and the identified duplicate aerial photography reference points are deleted, so that only one of each duplicate aerial photography reference point is retained.

4. The river channel monitoring system based on UAV aerial images according to claim 3, wherein, After the aerial photography reference points are determined, further perpendiculars to the midline of the river channel distribution model are made based on each aerial photography reference point. Arbitrary two points are selected on each perpendicular. The two points selected on each perpendicular are both denoted as aerial photography points. The perpendicular distances from the points selected as aerial photography points on each perpendicular to the midline of the river channel distribution model are not equal, and the distance between the points selected as aerial photography points on each perpendicular is half of the length of the midline of the river channel distribution model; Among them, the aerial photography point is the center of the camera when the UAV aerial photographs the river channel image.

5. The river channel monitoring system based on UAV aerial photography images according to claim 1, characterized in that, The perception module (3) is integrated by a quadrant photodetector, which senses its own position information in real time during the operation of the UAV aerial photography device. The perception module (3) operates based on the position information of the UAV aerial photography device it senses and outputs the position coordinates of the sun relative to the UAV aerial photography device, that is, the sun pose information; During the operation of the control module (4), the user at the system end customizes the flight altitude range of the UAV aerial photography device. The upload module (1) and the selection module (2) synchronously transmit the river channel distribution model and the aerial photography points to the control module (4), and the control module (4) forwards them to the UAV aerial photography device, controlling the UAV aerial photography device to execute the flight task based on the predetermined flight altitude range, the river channel distribution model and the aerial photography points, and collecting river channel images at the aerial photography points.

6. The river channel 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 task of collecting river channel images, it coordinates its own position through translational flight and vertical movement flight, so that when collecting river channel images each time, the aerial photography point, its own position information, and the position coordinates of the sun relative to the UAV aerial photography device are collinear. The camera end on the UAV aerial photography device faces the aerial photography point, and then the river channel images are collected; Among them, the river channel images collected by the control module (4) controlling the UAV aerial photography device are all marked based on the aerial photography point information applied during the collection stage.

7. The river channel monitoring system based on UAV aerial images according to claim 1, wherein, The evaluation module (5) is internally provided with sub-modules, including: A preprocessing unit (51) for obtaining the river channel images received during the operation of the evaluation module (5) and converting the river channel images into grayscale images; Among them, the preprocessing unit (51) performs noise reduction processing synchronously before converting the river channel images into grayscale images.

8. The river channel monitoring system based on UAV aerial photography images according to claim 1, wherein The river channel health status evaluation logic in the evaluation module (5) is expressed as: Where: S is the river channel health status value; α, β, γ, δ are weights; is the deviation degree of the river channel water body color; is the complexity of the river channel water body texture; A is the area of the river channel image determined after extracting the water body boundary in the image using an edge detection algorithm; P is the perimeter of the river channel image 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 clarity defined by the system-side user; A imp is the impurity area in the river channel image recognized by the image segmentation algorithm; A total is the area of the river channel image; where A = A total , the smaller the S, the healthier the river channel environment, and vice versa, the worse the river channel environment. The sum of α, β, γ, and δ is 1, and they are all positive numbers. Based on the above formula, each river channel image is calculated, and the maximum value among all calculation results is taken as the operation record content of the recording module (6); Where: H avg , S avg , V avg are the hue, saturation, and value of the water body in the river channel image; H std , S std , V std are the standard hue, standard saturation, and standard value of the river channel water body; is the maximum possible value of the preset color deviation; 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.

9. The river channel monitoring system based on UAV aerial photography images according to claim 1, characterized in that, The lower level of the upload module (1) is interconnected with a construction unit (11) and a configuration unit (12) through wireless network interaction. The upload module (1) is interconnected with a selection module (2) through wireless network interaction. The lower level of the selection module (2) is interconnected with a custom unit (21) and a picking unit (22) through wireless network interaction. The selection module (2) is interconnected with a perception module (3) and a control module (4) through wireless network interaction. The control module (4) is interconnected with the upload module (1) and the selection module (2) through wireless network interaction. The control module (4) is interconnected with an evaluation module (5) and a recording module (6) through wireless network interaction. The lower level of the evaluation module (5) is interconnected with a preprocessing unit (51) through wireless network interaction.

10. A river channel monitoring method based on UAV aerial images, which is an implementation method of a river channel monitoring system based on UAV aerial images according to any one of claims 1-9, characterized in that, Including the following steps: Step1: Upload the river channel distribution parameters, construct a river channel distribution model based on the river channel distribution parameters, and configure the real coordinates for the river channel distribution model; Step2: Set the aerial photography point selection logic, and select the aerial photography points in the river channel distribution model based on the aerial photography point selection logic; Step3: Set the operation parameters of the UAV aerial photography device, and collect river channel images in combination with the aerial photography points; Step4: Preprocess the collected river channel images, and perform the evaluation operation of the river channel health status by applying the preprocessed river channel images; Step 5: According to the river channel health status evaluation results of each river channel image, select the largest river channel health status evaluation result to perform the recording operation.

Images