Tree barrier hidden danger analysis method based on high-resolution remote sensing image

Abstract

The invention discloses a tree barrier hidden danger analysis method based on a high-resolution remote sensing image, and belongs to the technical field of intelligent monitoring of electric power facilities. The method comprises the following steps: acquiring and preprocessing a high-resolution satellite image of a power transmission channel; analyzing image metadata to extract azimuth angles and elevation angles of the sun and the satellite; establishing an object shadow length-height geometric model according to the position relationship between the sun and the satellite, and inverting the tree height by using the tree shadow length and generating a three-dimensional coordinate; determining a nearest power transmission line point in the image, measuring the shadow length of the nearest power transmission line point, calculating the height of the nearest power transmission line point, and generating three-dimensional coordinates of the nearest power transmission line point; calculating a line-tree horizontal distance and a space minimum distance; and performing tree obstacle risk grading according to a power transmission line safety distance standard. According to the invention, high-precision three-dimensional reconstruction is realized through a satellite shadow geometrical relationship, the problems of low efficiency and high cost of traditional inspection are solved, the coverage range is large, the cost is low, and the method is suitable for large-range power transmission channel tree obstacle monitoring.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of intelligent monitoring of power facilities, and particularly relates to a tree barrier hidden danger analysis method based on high-resolution remote sensing images. BACKGROUND

[0002] A power transmission line is the core of energy transmission of a power system, and its safe and stable operation is directly related to the power supply reliability of a power grid and the order of social production and life. With the continuous expansion of the power network in China, as of 2024, the total mileage of overhead power transmission lines in China has exceeded 1.75 million kilometers, of which more than 80% of the lines pass through complex terrains such as mountains, forests, and marshes. The trees in these areas grow extremely easily to form "tree barrier hidden dangers": when the height or horizontal distance of the trees breaks through the safety threshold of the power transmission line, it may cause line-to-ground discharge, inter-phase short circuit and other faults. According to the operation and maintenance data of State Grid, tree barriers have accounted for more than 35% of the causes of line tripping. However, the current mainstream tree barrier monitoring technology still has significant shortcomings and cannot meet the needs of large-scale, high-precision and low-cost operation and maintenance.

[0003] Manual inspection is the earliest tree barrier monitoring method, which relies on operation and maintenance personnel to carry range finders, telescopes and other equipment to patrol along the line on foot or by car, which is high in cost and low in efficiency. Unmanned aerial vehicle (UAV) inspection realizes tree barrier monitoring by carrying visible light cameras and laser ranging modules, which is more efficient than manual inspection, but is severely restricted by airspace and weather. Laser radar can generate high-precision three-dimensional point clouds by emitting laser beams to scan ground objects, and can realize millimeter-level measurement of tree height and line-tree distance, but the device is expensive and difficult to apply on a large scale.

[0004] Satellite remote sensing technology has been preliminarily applied to power line monitoring due to its advantages of "large range and no regional restrictions". Existing satellite image analysis is mostly limited to two-dimensional plane monitoring and cannot obtain three-dimensional information such as power line sag and spatial position. With the development of satellite remote sensing technology, the resolution of high-resolution satellite optical images has broken through 0.2 m, which can clearly distinguish power transmission lines, trees and their ground projections in the power transmission channel.

[0005] The patent with publication number CN 116256771 A provides a method for tree barrier safety detection using unmanned aerial vehicle laser point cloud, which obtains the spatial distribution information of power lines and surrounding environment in the power corridor by classifying and extracting power corridor power lines, ground models and vegetation information, and segmenting individual target point clouds, and finally realizes the analysis of dangerous tree barrier objects in the power corridor. However, this method requires obtaining unmanned aerial vehicle laser point cloud data, and cannot meet the demand of large-scale and high-frequency power transmission line inspection. The patent with publication number CN 119600470 A discloses a method for monitoring power transmission lines using satellites instead of unmanned aerial vehicles, which solves the problems of small monitoring area, long detection time and high limitation of unmanned aerial vehicles. This method only determines the ground hazard type through the frequency domain features of satellite image pixels, and cannot accurately calculate the height of trees and the spatial distribution state of power transmission lines, which cannot meet the fine inspection requirements of power transmission channels.

[0006] With the promotion of smart transformation of power grids, the operation and maintenance department puts forward the demand of "three high and one low" (high coverage, high precision, high frequency and low cost) for tree barrier monitoring, but the existing technologies cannot meet all the requirements at the same time. Especially under the "double carbon" goal, new energy stations (wind power, photovoltaic) supporting power transmission lines are mostly located in remote mountainous areas, and traditional monitoring methods are more difficult to adapt, so there is an urgent need for a tree barrier monitoring technology that can break through geographical restrictions, achieve three-dimensional accurate measurement, and have controllable cost. SUMMARY

[0007] The purpose of the present application is to solve the problems of "insufficient precision, limited range and high cost" in existing power transmission channel tree barrier monitoring, and to provide a tree barrier hazard analysis method based on high-resolution remote sensing images. By analyzing the azimuth and elevation angle parameters of the sun and the satellite, a shadow-height geometric model is constructed to realize three-dimensional coordinate reconstruction of trees and power lines, accurately calculate the line-tree safety distance, and meet the demand of large-scale, low-cost and high-precision tree barrier monitoring.

[0008] In order to achieve the above-mentioned purpose, the present application adopts the following technical solutions:

[0009] A tree barrier hazard analysis method based on high-resolution remote sensing images, through high-resolution satellite remote sensing images, combined with the spatial geometric relationship of sun-satellite-ground objects, the shadow length is used to inverse the height of trees and power lines, three-dimensional coordinates are generated, and based on the safety distance standard, tree barrier risk classification is realized, including the following steps:

[0010] S1, obtaining satellite remote sensing images of power transmission channels through remote sensing satellites, and performing geometric correction, fusion and inlay preprocessing;

[0011] S2, analyzing image metadata, extracting sun azimuth ω, sun elevation angle α, satellite azimuth β and satellite elevation angle θ;

[0012] S3. Based on the spatial relationship between the sun and the satellite, construct a geometric model of the measurable shadow length d and the object height H in the image. ;

[0013] S4. Measure the length d of the tree shadow along the direction of the sun's azimuth. t Based on the relationship between the satellite azimuth angle β and the solar azimuth angle ω, a geometric model is used. Calculate tree height and, combined with tree geographic location, generate three-dimensional coordinates of tree barrier points. ;

[0014] S5. Identify the nearest power line point to the tree obstruction point in the image as the nearest power line point, and record the two-dimensional coordinates of the nearest power line point. ;

[0015] S6. Starting from the nearest transmission line point, extend in the opposite direction along the solar azimuth angle to the transmission line projection point, and obtain the length from the nearest transmission line point to the transmission line projection point as the transmission line shadow length d. c Through geometric model Calculate the height H of the transmission line c Generate the three-dimensional coordinates of the nearest transmission line point.

[0016] S7. Calculate the horizontal distance d between the line and the tree based on the three-dimensional coordinates of the tree obstruction point and the nearest transmission line point. H and minimum spatial distance d M ;

[0017] S8. Classify tree obstruction points according to the safety distance standard for transmission lines and complete the tree obstruction analysis.

[0018] As a further description of the above technical solution, the resolution of the satellite remote sensing image in step S1 is not less than 0.5 meters, such as the image of Jilin-1 satellite.

[0019] As a further description of the above technical solution, the geometric model described in step S3 There are three scenarios:

[0020] when When using the formula ;

[0021] when When using the formula Where φ is the phase difference between the solar azimuth angle and the satellite azimuth angle. ;

[0022] when When using the formula .

[0023] As a further description of the above technical solution, the method for determining the nearest power line point in step S5 is: a perpendicular line is drawn from the tree barrier point to the straight line where the power line is located, and the intersection of the perpendicular line and the straight line where the power line is located is the nearest power line point.

[0024] As a further description of the above technical solution, the power line height H c The formula for calculating the power line height H is as follows:

[0025] As a further description of the above technical solution, in step S7, the line-tree horizontal distance d H is calculated according to the following formula:

[0026] ;

[0027] The formula for calculating the minimum spatial distance d M is as follows:

[0028] .

[0029] As a further description of the above technical solution, the power line route safety distance standard in step S8 is the "DL / T741-2021 Overhead Power Line Operation Regulation", and the minimum safety distance threshold is set according to the voltage level.

[0030] The method of the present application is based on high-resolution satellite remote sensing images, and by constructing a space geometric model of the sun-satellite-ground object, the three-dimensional state reconstruction and accurate analysis of tree barriers of the power line route are realized, and compared with the prior art, the following beneficial effects are obtained:

[0031] 1. Significantly improve the three-dimensional measurement accuracy and efficiency: traditional satellite image analysis can only obtain planar information, while the present application analyzes the geometric relationship between the shadow length and the sun / satellite azimuth / altitude angle, and for the first time realizes the sub-meter three-dimensional reconstruction of the conductor sag, spatial position and tree height, which meets the fine inspection requirements of the power industry for the clearance distance. Single satellite image has large coverage range and high coverage frequency, which is more than 20 times higher than unmanned aerial vehicle inspection, and is not limited by airspace control, and for trees growing at a faster rate, combined with rapidly updated satellite remote sensing images, large-scale and high-frequency monitoring can be realized.

[0032] 2. Greatly reduce the monitoring cost: the present application discards the expensive laser radar equipment and directly uses commercial high-resolution satellite images, so that the single monitoring cost is reduced to less than 1 / 10 of the laser radar scheme. And for remote or inconvenient transportation areas, there is no need for artificial on-site inspection or unmanned aerial vehicle scheduling, which reduces the labor input by 90%, and is especially suitable for mountainous areas, marshes and other difficult areas.

[0033] 3. Technical compatibility and scalability: The output three-dimensional coordinates of tree obstruction points can be directly imported into the power grid GIS system, supporting intelligent inspection decision-making; in addition, the method of this invention can also detect other hidden dangers in the transmission channel, such as safety hazards of buildings and crossings, ensuring the safe and stable operation of the transmission channel. Attached Figure Description

[0034] Figure 1 This is a flowchart of the tree obstacle hazard analysis method based on high-resolution remote sensing imagery of the present invention.

[0035] Figure 2 This is when the solar azimuth angle is the same as the satellite azimuth angle ( A schematic diagram showing the positional relationship between the satellite, the sun, and the object.

[0036] Figure 3 This is a schematic diagram showing the positional relationship between the satellite, the sun, and the object when the phase difference between the solar azimuth angle and the satellite azimuth angle is between 0 and 180°.

[0037] Figure 4 This is a schematic diagram showing the positional relationship between the satellite, the sun, and the object when the phase difference between the solar azimuth angle and the satellite azimuth angle is between 180° and 360°.

[0038] Figure 5 It refers to the positional relationship between tree obstruction points, power lines, and the nearest power line point in the image.

[0039] Figure 6 It is the positional relationship between the nearest transmission line point and the corresponding projection point in the image.

[0040] Figure 7 This is a schematic diagram showing the positional relationship between the horizontal distance between the line and the tree and the minimum spatial distance. Detailed Implementation

[0041] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments, but this does not constitute any limitation on the present invention. Any limited modifications made by any person within the scope of protection of the claims of the present invention are still within the scope of protection of the claims of the present invention.

[0042] A method for analyzing tree obstruction hazards based on high-resolution remote sensing imagery, the process of which is as follows: Figure 1 As shown, it includes the following steps:

[0043] S1. Acquire high-resolution (no less than 0.5 meters) satellite remote sensing images of the power transmission channel (e.g., images from Jilin-1 satellite) through remote sensing satellites, and perform geometric correction, fusion, and mosaicking preprocessing on the satellite remote sensing images;

[0044] S2, parse the metadata file of satellite remote sensing image, extract the sun azimuth angle ω, the sun elevation angle α, the satellite azimuth angle β and the satellite elevation angle θ;

[0045] S3, based on the spatial position relationship between the sun and the satellite, construct the geometric model of the shadow length d and the object height H that can be measured on the image , which is specifically divided into three cases:

[0046] When the satellite azimuth angle β is the same as the sun azimuth angle ω, that is , the position relationship between the satellite, the sun and the object is shown in Figure 2 , at this time the shadow of the object on the remote sensing image is partially blocked, the shadow length d of the object that can be measured in the remote sensing image can be calculated according to the pixel number and the pixel length of the satellite image, that is d = pixel number × pixel length, the geometric model at this time is , which is expressed as:

[0047] ;

[0048] When the phase difference between the sun azimuth angle and the satellite azimuth angle is located at 0~180°, that is , the position relationship between the satellite, the sun and the object is shown in Figure 3 , the shadow of the object on the remote sensing image is also partially blocked, assuming that E is the projection point of the highest point of the object on the ground, the straight line EO is a straight line passing through point E along the east-west direction, the intersection of the straight line connecting the satellite and the highest point A of the object with the ground is point C, the vertical line BE passing through point C is drawn, and the foot is point D, then the length of DE is the actual shadow length d of the object that can be measured in the remote sensing image;

[0049] According to the definition of the sun azimuth angle ω and the satellite azimuth angle β, the phase difference φ can be obtained as:

[0050] ;

[0051] In triangle ABC, the following geometric relationships exist:

[0052]

[0053] In triangle ABE, the following geometric relationships exist:

[0054] ;

[0055] In triangle BCE, according to the cosine formula, the following relationship is established:

[0056] ;

[0057] According to the sine theorem:

[0058]

[0059]

[0060] In the above formula, only the object height H is unknown; all others are known or can be indirectly calculated. This is the geometric model. Represented as:

[0061] ;

[0062] When the difference between the solar azimuth angle and the satellite azimuth angle is greater than 180°, that is... At that time, the positional relationship between the satellite, the sun, and the object is as follows: Figure 4 As shown, at this point, the object's shadow is fully visible, and the measurable shadow length d in the remote sensing image is equal to the actual shadow length. The geometric model at this point... Represented as:

[0063] ;

[0064] S4. Draw the tree shadow length vector along the sun's azimuth direction, and calculate the tree shadow length d based on the pixel length. t Based on the relationship between the satellite azimuth angle β and the solar azimuth angle ω, a suitable geometric model is selected. Calculate tree height H t Combined with the tree's accurate geographical location, using latitude and longitude as x and y coordinates, and the tree height H t Use the z-coordinate to generate the 3D coordinates of the tree obstacle point (the highest point of the tree). ;

[0065] S5. In the satellite remote sensing image, find the point on the straight line JK where the power transmission line is located that is closest to the tree obstacle point Q, and record the two-dimensional coordinates of the power transmission line point T. , specifically Figure 5 As shown: Draw a perpendicular line from the tree obstacle point Q to the line JK where the transmission line is located, intersecting the line JK at the foot of the perpendicular T. The foot of the perpendicular T is the nearest transmission line point T.

[0066] S6. Starting from the nearest transmission line point T found in step S5, extend the line in the opposite direction of the solar azimuth angle, intersecting the transmission line projection MN at point P, as shown. Figure 6 As shown, point P is the ground projection point of the nearest transmission line point. The length from the nearest transmission line point T to the ground projection point P is calculated by combining the pixel length, which is the shadow length d of the transmission line. c Substitute geometric relations Calculate the height H of the transmission line c Using the latitude and longitude of the nearest transmission line point T as the x and y coordinates, and the calculated transmission line height H... cz coordinate, construct the three-dimensional coordinates of the nearest power line point T , where the calculation of the power line height uses the formula .

[0067] S7, calculate the line-tree horizontal distance d according to the three-dimensional coordinates of the tree barrier point Q and the power line point T H and the minimum spatial distance d M , as shown in Figure 7 , where the line-tree horizontal distance is:

[0068] ;

[0069] The line-tree minimum spatial distance is:

[0070] ;

[0071] S8, according to the minimum safety distance specified in the different voltage grade power line regulations in the “DL / T 741-2021 Overhead Power Line Operation Regulations”, carry out tree barrier analysis on the tree point, set the minimum safety distance threshold according to the voltage grade, classify the tree barrier points, and complete the tree barrier analysis.

[0072] Application example:

[0073] The following takes the 500 kV power line tree barrier monitoring as an example to explain the implementation steps of the present application in detail:

[0074] 1, data acquisition and pretreatment (corresponding to step S1):

[0075] Satellite image source: Jilin No. 1 satellite image (resolution 0.5 m) is selected to cover a 100 km power transmission channel in a plain area. The pretreatment process includes: geometric correction - adopt RPC model combined with ground control points, positioning error ≤0.5 pixels; image fusion - fuse panchromatic and multispectral bands to enhance the edge features of ground objects; image inlay - color tone balancing treatment is performed on adjacent images to eliminate the joint.

[0076] 2, parameter extraction (corresponding to step S2):

[0077] Analyze the image metadata file (XML format) to obtain key parameters:

[0078] The sun azimuth ω=156.8°, the sun elevation angle α=52.4°, the satellite azimuth β=142.5°, and the satellite elevation angle θ=78.2°.

[0079] 3, tree height calculation (corresponding to steps S3 and S4):

[0080] Sun-satellite azimuth difference (0°~180° interval), the length of the tree shadow d = 8.2 m is taken along the solar azimuth angle 156.8°, and the formula is substituted :

[0081] The tree root point longitude and latitude are , the elevation is 0, and the tree highest point (tree barrier point) coordinates are , where z t = 14.4.

[0082] 4. Transmission line height calculation (corresponding to steps S5, S6):

[0083] First, the nearest transmission line point T is located, as shown in Figure 5 , the straight line JK where the transmission line is located is determined, the perpendicular to the straight line JK where the transmission line is located is drawn through the tree barrier point Q, and the intersection of the perpendicular to the straight line JK where the transmission line is located at point T, point T is the nearest transmission line point, and the transmission line shadow length d c = 4.1 m is taken along the reverse solar azimuth angle (156.8°+180°=336.8°);

[0084] Substitute the formula = 4.1 x 1.31 = 5.37 m; the three-dimensional coordinates of the transmission line point are , where z c = 5.37.

[0085] 5. Tree barrier distance analysis and classification (corresponding to steps S7, S8):

[0086] According to the three-dimensional coordinates of the tree barrier point and the nearest transmission line point, the line-tree horizontal distance d H is calculated:

[0087] = 6.8 m;

[0088] The minimum spatial distance d M :

[0089] = 11.3 m

[0090] According to the "DL / T 741-2021 Overhead Transmission Line Operation Regulations", the tree barrier point risk classification is divided, as shown in Table 1.

[0091] Table 1 Tree barrier point risk classification

[0092] Voltage class Minimum safety distance Risk class 500 kV 7.0 m d M = 11.3 m > 7.0 m → Grade II (general hidden trouble)

[0093] It should be noted that the object information (including but not limited to object device information, object personal information, etc.) and data (including but not limited to data for analysis, stored data, displayed data, etc.) involved in the present application are all information and data authorized by the object or fully authorized by all parties, and the collection, use and processing of related data need to comply with relevant laws, regulations and standards of relevant countries and regions.

[0094] It can be understood by those skilled in the art that all or part of the processes of the method of the present application can be completed by computer program instruction related hardware, and the computer program can be stored in a non-volatile computer readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above method. Among them, any reference to memory, database or other medium used in the embodiments provided by the present application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (Read-Only Memory, ROM), magnetic tape, floppy disk, flash memory, optical storage, high-density embedded non-volatile memory, resistive memory (ReRAM), magnetoresistive random access memory (Magnetoresistive Random Access Memory, MRAM), ferroelectric memory (Ferroelectric Random Access Memory, FRAM), phase change memory (Phase Change Memory, PCM), graphene memory, etc. Volatile memory can include random access memory (Random Access Memory, RAM) or external cache memory, etc. As an illustration of the present application rather than limitation, RAM can be in various forms, such as static random access memory (Static Random Access Memory, SRAM) or dynamic random access memory (Dynamic Random Access Memory, DRAM), etc. The database involved in the embodiments of the present application can include at least one of a relational database and a non-relational database. The non-relational database can include a distributed database based on blockchain, etc., without limitation. The processor involved in the embodiments of the present application can be a general-purpose processor, a central processing unit, a graphics processing unit, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., without limitation.

[0095] The technical features of the above embodiments can be combined arbitrarily. In order to make the description simple, not all possible combinations of the technical features in the above embodiments are described, but as long as the combination of the technical features does not exist contradictory, it should be considered as the scope of the present application.

[0096] The specific embodiments of the present application are only to illustrate the principles and technical means of the present application, and the description of the examples is only to help understand the method of the present application and its core idea; at the same time, for those skilled in the art, according to the idea of the present application, there will be changes in the specific embodiments and application scope. In view of the above, the content of the specification should not be understood as a limitation of the present application.

Claims

1. A method for analyzing tree obstruction hazards based on high-resolution remote sensing imagery, characterized in that, Includes the following steps: S1. Obtain satellite remote sensing images of the power transmission channel through remote sensing satellites, and perform geometric correction, fusion and mosaic preprocessing; S2. Parse image metadata and extract solar azimuth ω, solar altitude α, satellite azimuth β, and satellite altitude θ; S3. Based on the spatial relationship between the sun and the satellite, establish a geometric model of the measurable shadow length d and the object height H in the image. ; S4. Measure the length d of the tree shadow along the direction of the sun's azimuth. t Based on the relationship between the satellite azimuth angle β and the solar azimuth angle ω, a geometric model is used. Calculate tree height and, combined with tree geographic location, generate three-dimensional coordinates of tree barrier points. ; S5. Identify the nearest power line point to the tree obstruction point in the image as the nearest power line point, and record the two-dimensional coordinates of the nearest power line point. ; S6. Starting from the nearest transmission line point, extend in the opposite direction along the solar azimuth angle to the transmission line projection point, and obtain the length from the nearest transmission line point to the transmission line projection point as the transmission line shadow length d. c Through geometric model Calculate the height H of the transmission line c Generate the three-dimensional coordinates of the nearest transmission line point. ; S7. Calculate the horizontal distance d between the line and the tree based on the three-dimensional coordinates of the tree obstruction point and the nearest transmission line point. H and minimum spatial distance d M ; S8. Classify tree obstruction points according to the power transmission line safety distance standard and complete the tree obstruction analysis.

2. The method for analyzing tree obstruction hazards based on high-resolution remote sensing imagery according to claim 1, characterized in that: The resolution of the satellite remote sensing image described in step S1 is not less than 0.5 meters.

3. The method for analyzing tree obstruction hazards based on high-resolution remote sensing imagery according to claim 1, characterized in that, The geometric model described in step S3 There are three scenarios: when When using the formula ; when When using the formula Where φ is the phase difference between the solar azimuth angle and the satellite azimuth angle. ; when When using the formula .

4. The method for analyzing tree obstruction hazards based on high-resolution remote sensing imagery according to claim 1, characterized in that: The method for determining the nearest transmission line point in step S5 is as follows: draw a perpendicular line from the tree obstruction point to the straight line where the transmission line is located, and the intersection of the perpendicular line and the straight line where the transmission line is located is the nearest transmission line point.

5. The tree obstacle hazard analysis method based on high-resolution remote sensing imagery according to claim 3, characterized in that: In step S6, the height H of the transmission line c Using formula Perform the calculation.

6. The method for analyzing tree obstruction hazards based on high-resolution remote sensing imagery according to claim 1, characterized in that: In step S7, the horizontal distance d between the line and the tree is... H The calculation formula is: ； Minimum spatial distance d M The calculation formula is: 。 7. The method for analyzing tree obstruction hazards based on high-resolution remote sensing imagery according to claim 1, characterized in that: The safety distance standard for transmission lines mentioned in step S8 is the "DL / T 741-2021 Operation Regulations for Overhead Transmission Lines", and the minimum safety distance threshold is set according to the voltage level.

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