Geological disaster monitoring method and system based on unmanned aerial vehicle

Abstract

The invention provides a geological disaster monitoring method and system based on an unmanned aerial vehicle, and relates to the technical field of geological disaster monitoring, and the geological disaster monitoring method based on the unmanned aerial vehicle comprises the steps: respectively shooting initial image data and current image data of a to-be-monitored region through the unmanned aerial vehicle; preprocessing the initial image data to obtain a reference to-be-analyzed image, and preprocessing the current image data to obtain a current to-be-analyzed image; extracting to obtain a reference model and a current situation model; fusing the reference model and the current state model to obtain a monitoring model; the monitoring model is analyzed, the geological disaster condition of the to-be-monitored area is evaluated, and a geological disaster evaluation result is obtained; and outputting a geological disaster assessment report according to the geological disaster assessment result. According to the method, the limitation of complex terrains and severe working environments can be effectively overcome, the safety of patrol personnel can be effectively improved, and the patrol efficiency and accuracy can be effectively improved.

Description

Technical Field

[0001] The present application relates to the technical field of geological disaster monitoring, and specifically to a method and system for geological disaster monitoring based on unmanned aerial vehicles. Background Art

[0002] Geological disaster inspection is a vital task. It plays a very important role in timely discovering and assessing geological disaster risks, and then taking effective prevention and response measures to ensure the safety of people's lives and property. Usually, geological disaster inspection covers inspections of various types of disasters such as landslides, ground collapses and dangerous rock falls. During the inspection process, staff need to conduct detailed on-site surveys of geological disaster risk points and pay close attention to the signs and characteristics of geological disasters. In addition, it is necessary to conduct a comprehensive investigation of the environment around the disaster site to understand the basic conditions of topography, landforms, hydrogeology, and the potential impact of human activities on geological disasters.

[0003] At present, geological disaster inspections mainly rely on manual means, such as visual observation, tapping and touching. However, the geological and topographical conditions in most field environments are complex and changeable, which makes it extremely risky for inspectors to conduct manual inspections when facing steep slopes, large landslides, ground collapse areas and dangerous rockfalls. Especially in difficult-to-reach landslide areas, manual inspections often cannot fully and accurately reflect the true conditions of landslides, which brings certain challenges to geological disaster prevention and control work. Therefore, how to improve the safety, efficiency and accuracy of geological disaster inspections has become an urgent problem to be solved. Summary of the invention

[0004] In order to solve the technical problems in the related technologies, the present application provides a geological disaster monitoring method based on drones.

[0005] In order to achieve the above objectives, the technical solutions adopted in this application include:

[0006] According to the first aspect of the present application, a method for monitoring geological disasters based on a drone is provided, comprising the following steps:

[0007] Step S1: using a drone to capture initial image data and current image data of the area to be monitored;

[0008] Step S2: preprocessing the initial image data to obtain a reference image to be analyzed, and preprocessing the current image data to obtain a current image to be analyzed;

[0009] Step S3: extracting a reference model based on the reference image to be analyzed, and extracting a current model based on the current image to be analyzed;

[0010] Step S4: The baseline model and the current status model are integrated to obtain a monitoring model;

[0011] Step S5: Analyze the monitoring model, evaluate the geological disaster situation in the monitored area, and obtain the geological disaster assessment results;

[0012] Step S6: Output a geological disaster assessment report based on the geological disaster assessment results.

[0013] Optionally, the step S1 specifically includes:

[0014] Step S1-1: Select at least one reference point and several monitoring points in the area to be monitored.

[0015] Step S1-2: Control the UAV to obtain initial image data and current image data of the area to be monitored, wherein both the initial image data and the current image data contain all reference points and monitoring points.

[0016] Optionally, step S2 specifically includes the following steps performed in sequence:

[0017] Step S2-1: Check the overlap of images, and delete images whose spatial overlap is less than a first threshold and images whose front-to-back overlap is less than a second threshold;

[0018] Step S2-2: adjusting the white balance, contrast and brightness of the image;

[0019] Step S2-3: Correcting the barrel distortion and pincushion distortion of the image, and performing geometric correction on the image;

[0020] Step S2-4: resolution and size of the same image;

[0021] Step S2-5: Use a filter to remove random noise in the image;

[0022] Step S2-6: Enhance the edge information and texture information of the image.

[0023] Optionally, the first threshold A satisfies: 55%≤A≤75%; and / or,

[0024] The second threshold value B satisfies: 65%≤B≤85%.

[0025] Optionally, the step S4 specifically includes:

[0026] Step S4-1: taking the reference point and the plurality of monitoring points in the reference model as the center and the first spacing as the radius, respectively generating a plurality of reference spherical surfaces, and generating a reference curved surface based on the plurality of reference spherical surfaces, wherein the reference curved surface is set as a closed curved surface tangent to the plurality of reference spherical surfaces respectively; retaining the partial model data of the reference model included in the reference curved surface;

[0027] Step S4-2: taking the reference point and the plurality of monitoring points in the current model as the center and the second spacing as the radius, respectively generating a plurality of current spherical surfaces, and generating a current curved surface based on the plurality of current spherical surfaces, wherein the current curved surface is configured as a closed curved surface tangent to the plurality of current spherical surfaces respectively; retaining part of the model data in the current model that is included in the current curved surface;

[0028] Step S4-3: Taking the reference point as the fusion reference point, the reference model data retained in step S4-1 and the current status model data retained in step S4-2 are fused to generate a monitoring model.

[0029] Optionally, the step S5 specifically includes:

[0030] Step S5-1: In the monitoring model, the monitoring point of the reference model is used as the original position, and the relative displacement and movement direction of the corresponding monitoring point in the current status model are calculated;

[0031] Step S5-2: According to the relative displacement and moving direction obtained in step S5-1, the disaster type and disaster degree corresponding to the monitoring point are marked in the monitoring model, wherein the disaster type is determined according to the relative displacement and moving direction of one or more monitoring points, and the disaster types include landslide, ground collapse and dangerous rockfall; the disaster degree is determined according to the relative displacement, when the relative displacement is less than a first threshold, the disaster degree is marked as slight, when the relative displacement is greater than or equal to the first threshold and less than or equal to the second threshold, the disaster degree is marked as medium, and when the relative displacement is greater than a third threshold, the disaster degree is marked as severe.

[0032] Optionally, the step S6 specifically includes:

[0033] Step S6-1: Generate a corresponding disaster content report according to the marking result of step S5-2, the disaster content report includes the location of the corresponding monitoring point, the corresponding disaster type and disaster degree;

[0034] Step S6-2: Generate a corresponding disaster image report based on the annotation result of step S5-2, that is, perform visual annotation in the current status model, the annotation content includes annotation text and annotation color, wherein the annotation text is the disaster type marked in text form at the monitoring point, and the annotation color is the color of the annotation text, and the minor, moderate and severe annotation colors are different;

[0035] Step S6-3: Output a disaster assessment report, which includes the disaster content report in step S6-1 and the disaster image report in step S6-2.

[0036] According to the second aspect of the present application, a geological disaster monitoring system based on a drone is also provided, characterized in that it is applied to the geological disaster monitoring method based on a drone described in any technical solution in the first aspect of the present application, including:

[0037] The drone module is used to capture the initial image data and current image data of the area to be monitored;

[0038] An image preprocessing module, used for preprocessing the initial image data to obtain a reference image to be analyzed, and for preprocessing the current image data to obtain a current image to be analyzed;

[0039] A modeling module, used to extract a reference model based on a reference image to be analyzed, and to extract a current model based on a current image to be analyzed;

[0040] A fusion module is used to fuse the baseline model and the current status model to obtain a monitoring model;

[0041] The analysis module is used to analyze the monitoring model, evaluate the geological disaster situation in the monitored area, and obtain the geological disaster assessment results;

[0042] Output module, used to output geological disaster assessment report.

[0043] According to the third aspect of the present application, a computer device is also provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of the UAV-based geological disaster monitoring method described in any one of the technical solutions in the first aspect of the present application can be implemented.

[0044] According to the fourth aspect of the present application, a computer-readable storage medium is also provided, on which a computer program is stored, characterized in that when the computer program is executed by a processor, it can implement the steps of the drone-based geological disaster monitoring method described in any technical solution in the first aspect of the present application.

[0045] Beneficial effects:

[0046] 1. Through the above technical solution, first, drones are used to capture images of the monitored area, and inspectors do not need to enter the monitored area. This can not only overcome the limitations of complex terrain and harsh working environment, but also effectively improve the safety of inspectors.

[0047] Second, by processing the initial image data and current image data of the monitored area taken by the drone, the baseline model and the current model are obtained respectively. This not only enables relevant personnel to quickly and intuitively grasp the initial state and current state of the monitored area, but also enables the baseline model and the current state model to accurately and comprehensively verify the occurrence, potential dangers and development trends of geological disasters, providing more comprehensive and intuitive data reference for disaster reduction and prevention.

[0048] Third, after operations such as relevant software and algorithms, a comprehensive and reliable geological disaster assessment report for the monitored area can be directly output, which can not only effectively improve the efficiency of geological disaster inspections, but also help to ensure the accuracy of geological disaster inspections.

[0049] 2. Other beneficial effects or advantages of the present application will be described in detail in the specific implementation manner. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For those skilled in the art, other drawings can be obtained based on these drawings without paying any creative labor.

[0051] in:

[0052] Figure 1 It is a schematic diagram of the steps of a method for monitoring geological disasters based on a drone provided by an exemplary embodiment of the present application. DETAILED DESCRIPTION

[0053] In order to make the purpose, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below in combination with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments.

[0054] Therefore, the following detailed description of the embodiments of the present application provided in the accompanying drawings is not intended to limit the scope of the present application for which protection is sought, but merely represents selected embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in the field without creative work are within the scope of protection of the present application.

[0055] In addition, the terms "including" and "having" and any variations thereof mentioned in the description of the present application are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but optionally includes other steps or units that are not listed, or optionally includes other steps or units that are inherent to these processes, methods, products or devices. Among them, it should also be noted that in the embodiments of the present application, words such as "exemplary" or "for example" are used to represent examples, illustrations or explanations. Any embodiment or design described as "exemplary" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or design solutions. Specifically, the use of words such as "exemplary" or "for example" is intended to present related concepts in a specific way.

[0056] Taking large-scale landslides as an example, existing geological disaster inspections generally use contact-based, single-point survey methods. That is, geological inspectors are required to enter large-scale landslide areas and conduct on-site contact surveys of the approximate area and status of the landslide. This not only poses a great safety risk, but also, since some landslide areas are inaccessible to humans, manual inspections cannot fully and accurately reflect the true situation of the landslide.

[0057] Therefore, how to improve the personal safety, inspection efficiency and inspection accuracy of geological disaster inspection personnel has become an urgent problem to be solved.

[0058] In view of this, the present application provides a new solution, namely, a geological disaster monitoring method based on drones, which can not only effectively overcome the limitations of complex terrain and harsh working environment, but also effectively improve the safety of patrol personnel and effectively improve the efficiency and accuracy of patrols.

[0059] The technical solution of the present application is described in detail below with reference to the accompanying drawings.

[0060] Example 1

[0061] like Figure 1 As shown, this embodiment provides a method for monitoring geological disasters based on a drone, comprising the following steps:

[0062] Step S1: using a drone to capture initial image data and current image data of the area to be monitored;

[0063] Step S2: preprocessing the initial image data to obtain a reference image to be analyzed, and preprocessing the current image data to obtain a current image to be analyzed;

[0064] Step S3: extracting a reference model based on the reference image to be analyzed, and extracting a current model based on the current image to be analyzed;

[0065] Step S4: The baseline model and the current status model are integrated to obtain a monitoring model;

[0066] Step S5: Analyze the monitoring model, evaluate the geological disaster situation in the monitored area, and obtain the geological disaster assessment results;

[0067] Step S6: Output a geological disaster assessment report based on the geological disaster assessment results.

[0068] Through the above technical solution, firstly, drones are used to capture images of the monitored area, and inspectors do not need to enter the monitored area. This can not only overcome the limitations of complex terrain and harsh working environment, but also effectively improve the safety of inspectors.

[0069] Second, by processing the initial image data and current image data of the monitored area taken by the drone, the baseline model and the current model are obtained respectively. This not only enables relevant personnel to quickly and intuitively grasp the initial state and current state of the monitored area, but also enables the baseline model and the current state model to accurately and comprehensively verify the occurrence, potential dangers and development trends of geological disasters, providing more comprehensive and intuitive data reference for disaster reduction and prevention.

[0070] Third, after operations such as relevant software and algorithms, a comprehensive and reliable geological disaster assessment report for the monitored area can be directly output, which can not only effectively improve the efficiency of geological disaster inspections, but also help to ensure the accuracy of geological disaster inspections.

[0071] In one implementation of the present application, step S1 of the present application may specifically include:

[0072] Step S1-1: Select at least one reference point and several monitoring points in the area to be monitored.

[0073] Step S1-2: Control the UAV to obtain initial image data and current image data of the area to be monitored, wherein both the initial image data and the current image data contain all reference points and monitoring points.

[0074] In this way, the selected reference points can be used as a reference for changes in the entire monitored area, and the selected monitoring points can be selected according to actual needs. For example, for landslides, multiple monitoring points can be set, and multiple monitoring points can be selected as the edges and center positions of the landslide to fully reflect the changes in the landslide; for ground collapse, multiple monitoring points can also be set, and multiple monitoring points can be selected as the edges and center positions of the ground collapse area to fully reflect the changes in the landslide; for dangerous rock falls, one or more monitoring points can be set to reflect the state and position changes of the dangerous rock falls.

[0075] It is understandable that the selected reference point should not change as much as possible to ensure the accuracy of the reference. For example, the reference point can be selected as a certain location or object in the area to be monitored, or a single unchanging reference object can be set in the area to be monitored. This application does not make specific limitations on this.

[0076] In one implementation of the present application, step S2 of the present application may specifically include the following steps performed in sequence:

[0077] Step S2-1: Check the image overlap, delete images with spatial overlap less than a first threshold, and images with front-to-back overlap less than a second threshold; in this way, it is ensured that there is sufficient spatial overlap and front-to-back overlap between images to facilitate subsequent feature matching and three-dimensional reconstruction.

[0078] Step S2-2: Adjust the white balance, contrast and brightness of the image; thus, by adjusting the white balance of the image, the color difference can be eliminated, by adjusting the contrast of the image, the details in the image can be made clearer, and by adjusting the brightness of the image, the image can be made more suitable for modeling.

[0079] Step S2-3: Correct the barrel distortion and pincushion distortion of the image, and perform geometric correction on the image; in this way, the barrel distortion or pincushion distortion caused by the correction lens can be eliminated, and the geometric deformation of the image caused by the change of the UAV's flight posture can be corrected.

[0080] Step S2-4: The resolution and size of the same image; in this way, the amount of computation during processing can be reduced, and the efficiency of image processing and model generation can be improved.

[0081] Step S2-5: Use a filter to remove random noise in the image; for example, a filter (such as Gaussian filtering, median filtering) can be used to remove random noise in the image.

[0082] Step S2-6: Enhance the edge information and texture information of the image. In this way, enhancing the edge information in the image will help the subsequent feature matching. Enhancing the texture information in the image can improve the realism of the three-dimensional model.

[0083] In this way, the images processed by the above preprocessing steps can not only clearly and accurately reflect the actual situation of the monitored area, but also generate corresponding models more quickly and accurately, thereby improving the accuracy and comprehensiveness of geological disasters.

[0084] In one implementation of the present application, the first threshold value A of the present application may be set as: 55%≤A≤75%; and / or, the second threshold value B may be set as: 65%≤B≤85%.

[0085] It can be understood that the specific values ​​of the first threshold and the second threshold can be adjusted according to actual needs, and this application does not make any specific limitations on this.

[0086] In one implementation of the present application, step S4 of the present application may specifically include:

[0087] Step S4-1: taking the reference point and the plurality of monitoring points in the reference model as the center and the first spacing as the radius, respectively generating a plurality of reference spherical surfaces, and generating a reference curved surface based on the plurality of reference spherical surfaces, wherein the reference curved surface is set as a closed curved surface tangent to the plurality of reference spherical surfaces respectively; retaining the partial model data of the reference model included in the reference curved surface;

[0088] Step S4-2: With the reference point and the plurality of monitoring points in the current model as the center and the second spacing as the radius, a plurality of current spherical surfaces are respectively generated, and a current curved surface is generated based on the plurality of current spherical surfaces, wherein the current curved surface is configured as a closed curved surface tangent to the plurality of current spherical surfaces respectively; and part of the model data in the current model that is included in the current curved surface is retained;

[0089] Step S4-3: Taking the reference point as the fusion reference point, the reference model data retained in step S4-1 and the current status model data retained in step S4-2 are fused to generate a monitoring model.

[0090] Thus, in this embodiment, first, the reference surface set in this way can simplify the reference model sufficiently, and the current situation surface can simplify the current situation model sufficiently, retaining the model data necessary for analyzing disasters and deleting unnecessary model data, which can not only effectively improve the calculation efficiency and model fusion efficiency, but also improve the accuracy and efficiency of analyzing disaster types and disaster degrees based on the fusion model (i.e., the monitoring model).

[0091] In one implementation of the present application, step S5 of the present application may specifically include:

[0092] Step S5-1: In the monitoring model, the monitoring point of the reference model is used as the original position, and the relative displacement and moving direction of the corresponding monitoring point in the current status model are calculated;

[0093] Step S5-2: According to the relative displacement and moving direction obtained in step S5-1, the disaster type and disaster degree corresponding to the monitoring point are marked in the monitoring model, wherein the disaster type is determined according to the relative displacement and moving direction of one or more monitoring points, and the disaster types include landslide, ground collapse and dangerous rockfall; the disaster degree is determined according to the relative displacement, when the relative displacement is less than a first threshold, the disaster degree is marked as slight, when the relative displacement is greater than or equal to the first threshold and less than or equal to the second threshold, the disaster degree is marked as medium, and when the relative displacement is greater than a third threshold, the disaster degree is marked as severe.

[0094] In this way, through the relative displacement and movement direction of the monitoring points, the disaster type and degree corresponding to all monitoring points can be quickly and effectively determined, comprehensively and accurately reflecting the geological conditions in the monitored area.

[0095] In one implementation of the present application, step S6 of the present application may specifically include:

[0096] Step S6-1: Generate a corresponding disaster content report according to the marking result of step S5-2, the disaster content report includes the location of the corresponding monitoring point, the corresponding disaster type and disaster degree;

[0097] Step S6-2: Generate a corresponding disaster image report based on the annotation result of step S5-2, that is, perform visual annotation in the current status model, the annotation content includes annotation text and annotation color, wherein the annotation text is the disaster type marked in text form at the monitoring point, and the annotation color is the color of the annotation text, and the minor, moderate and severe annotation colors are different;

[0098] Step S6-3: Output a disaster assessment report, which includes the disaster content report in step S6-1 and the disaster image report in step S6-2.

[0099] In this way, relevant technical personnel can quickly and accurately grasp the original state and current situation of the geology in the entire monitored area, as well as the development trend of geological disasters, so that relevant technical personnel can quickly and accurately carry out corresponding disaster reduction and prevention work.

[0100] According to the second aspect of the present application, a geological disaster monitoring system based on a drone is also provided, characterized in that the geological disaster monitoring method based on a drone is applied in any technical solution in the first aspect of the present application, including:

[0101] The drone module is used to capture the initial image data and current image data of the area to be monitored;

[0102] An image preprocessing module, used for preprocessing the initial image data to obtain a reference image to be analyzed, and for preprocessing the current image data to obtain a current image to be analyzed;

[0103] A modeling module, used to extract a reference model based on a reference image to be analyzed, and to extract a current model based on a current image to be analyzed;

[0104] A fusion module is used to fuse the baseline model and the current status model to obtain a monitoring model;

[0105] The analysis module is used to analyze the monitoring model, evaluate the geological disaster situation in the monitored area, and obtain the geological disaster assessment results;

[0106] Output module, used to output geological disaster assessment report.

[0107] The drone-based geological disaster monitoring system of this application can not only effectively overcome the limitations of complex terrain and harsh working environment, but also effectively improve the safety of patrol personnel and effectively improve the efficiency and accuracy of patrols.

[0108] According to the third aspect of the present application, a computer device is also provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of the UAV-based geological disaster monitoring method in any technical solution in the first aspect of the present application can be implemented.

[0109] It is understood that in this embodiment, the memory may include a volatile memory, such as a random access memory; the memory may also include a non-volatile memory, such as a read-only memory, a flash memory, a hard disk or a solid state drive; in addition, the memory may also include a combination of the above-mentioned types of memory. This application does not specifically limit this.

[0110] Similarly, the processor may be a processor that implements or executes various exemplary logic steps described in conjunction with the disclosure of the present application. The processor may be a central processing unit, a general-purpose processor, a digital signal processor, an application-specific integrated circuit, a field programmable gate array or other programmable logic device, a transistor logic device, a hardware component, or any combination thereof. It may implement or execute various exemplary logic steps described in conjunction with the disclosure of the present application. The processor may also be a combination that implements computing functions, such as a combination of one or more microprocessors, a combination of a DSP and a microprocessor, and the like.

[0111] According to the fourth aspect of the present application, a computer-readable storage medium is also provided, on which a computer program is stored, characterized in that when the computer program is executed by a processor, it can implement the steps of the drone-based geological disaster monitoring method in any technical solution in the first aspect of the present application.

[0112] In this embodiment, the computer readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination thereof. More specific examples (non-exhaustive list) of computer readable storage media include: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM), a register, a hard disk, an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above, or any other form of computer readable storage medium known in the art. An exemplary storage medium is coupled to a processor so that the processor can read information from the storage medium and can write information to the storage medium. Of course, the storage medium may also be a component of the processor. The processor and the storage medium may be located in an application-specific integrated circuit (ASIC). In the embodiments of the present application, a computer-readable storage medium may be any tangible medium that contains or stores a program, which may be used by or in conjunction with an instruction execution system, apparatus, or device.

[0113] The above are only specific implementations of the present application, but the protection scope of the present application is not limited thereto. Any changes or substitutions within the technical scope disclosed in the present application should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A method for monitoring geological disasters based on drones, characterized in that: The steps include: Step S1: using a drone to capture initial image data and current image data of the area to be monitored; Step S2: preprocessing the initial image data to obtain a reference image to be analyzed, and preprocessing the current image data to obtain a current image to be analyzed; Step S3: extracting a reference model based on the reference image to be analyzed, and extracting a current model based on the current image to be analyzed; Step S4: The baseline model and the current status model are integrated to obtain a monitoring model; Step S5: Analyze the monitoring model, evaluate the geological disaster situation in the monitored area, and obtain the geological disaster assessment results; Step S6: Output a geological disaster assessment report based on the geological disaster assessment results.

2. The method for monitoring geological disasters based on an unmanned aerial vehicle according to claim 1, characterized in that: The step S1 specifically includes: Step S1-1: Select at least one reference point and several monitoring points in the area to be monitored. Step S1-2: Control the UAV to obtain initial image data and current image data of the area to be monitored, wherein both the initial image data and the current image data contain all reference points and monitoring points.

3. The method for monitoring geological disasters based on unmanned aerial vehicles according to claim 1, characterized in that: The step S2 specifically includes the following steps performed in sequence: Step S2-1: Check the overlap of images, and delete images whose spatial overlap is less than a first threshold and images whose front-to-back overlap is less than a second threshold; Step S2-2: adjusting the white balance, contrast and brightness of the image; Step S2-3: Correcting the barrel distortion and pincushion distortion of the image, and performing geometric correction on the image; Step S2-4: resolution and size of the same image; Step S2-5: Use a filter to remove random noise in the image; Step S2-6: Enhance the edge information and texture information of the image.

4. The method for monitoring geological disasters based on an unmanned aerial vehicle according to claim 3, characterized in that: The first threshold value A satisfies: 55%≤A≤75%; and / or, The second threshold value B satisfies: 65%≤B≤85%.

5. The method for monitoring geological disasters based on unmanned aerial vehicles according to claim 2, characterized in that: The step S4 specifically includes: Step S4-1: taking the reference point and the plurality of monitoring points in the reference model as the center and the first spacing as the radius, respectively generating a plurality of reference spherical surfaces, and generating a reference curved surface based on the plurality of reference spherical surfaces, wherein the reference curved surface is set as a closed curved surface tangent to the plurality of reference spherical surfaces respectively; retaining the partial model data of the reference model included in the reference curved surface; Step S4-2: taking the reference point and the plurality of monitoring points in the current model as the center and the second spacing as the radius, respectively generating a plurality of current spherical surfaces, and generating a current curved surface based on the plurality of current spherical surfaces, wherein the current curved surface is configured as a closed curved surface tangent to the plurality of current spherical surfaces respectively; retaining part of the model data in the current model that is included in the current curved surface; Step S4-3: Taking the reference point as the fusion reference point, the reference model data retained in step S4-1 and the current status model data retained in step S4-2 are fused to generate a monitoring model.

6. The method for monitoring geological disasters based on unmanned aerial vehicles according to claim 5, characterized in that: The step S5 specifically includes: Step S5-1: In the monitoring model, the monitoring point of the reference model is used as the original position, and the relative displacement and movement direction of the corresponding monitoring point in the current status model are calculated; Step S5-2: According to the relative displacement and moving direction obtained in step S5-1, the disaster type and disaster degree corresponding to the monitoring point are marked in the monitoring model, wherein the disaster type is determined according to the relative displacement and moving direction of one or more monitoring points, and the disaster types include landslide, ground collapse and dangerous rockfall; the disaster degree is determined according to the relative displacement, when the relative displacement is less than a first threshold, the disaster degree is marked as slight, when the relative displacement is greater than or equal to the first threshold and less than or equal to the second threshold, the disaster degree is marked as medium, and when the relative displacement is greater than a third threshold, the disaster degree is marked as severe.

7. The method for monitoring geological disasters based on an unmanned aerial vehicle according to claim 6, characterized in that: The step S6 specifically includes: Step S6-1: Generate a corresponding disaster content report according to the marking result of step S5-2, the disaster content report includes the location of the corresponding monitoring point, the corresponding disaster type and disaster degree; Step S6-2: Generate a corresponding disaster image report based on the annotation result of step S5-2, that is, perform visual annotation in the current status model, the annotation content includes annotation text and annotation color, wherein the annotation text is the disaster type marked in text form at the monitoring point, and the annotation color is the color of the annotation text, and the minor, moderate and severe annotation colors are different; Step S6-3: Output a disaster assessment report, which includes the disaster content report in step S6-1 and the disaster image report in step S6-2.

8. A geological disaster monitoring system based on drones, characterized in that: The method for monitoring geological disasters based on an unmanned aerial vehicle according to any one of claims 1 to 7 comprises: The drone module is used to capture the initial image data and current image data of the area to be monitored; An image preprocessing module, used for preprocessing the initial image data to obtain a reference image to be analyzed, and for preprocessing the current image data to obtain a current image to be analyzed; A modeling module, used to extract a reference model based on a reference image to be analyzed, and to extract a current model based on a current image to be analyzed; A fusion module is used to fuse the baseline model and the current status model to obtain a monitoring model; The analysis module is used to analyze the monitoring model, evaluate the geological disaster situation in the monitored area, and obtain the geological disaster assessment results; Output module, used to output geological disaster assessment report.

9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the steps of the geological disaster monitoring method based on a drone described in any one of claims 1 to 7 can be implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the geological disaster monitoring method based on a drone described in any one of claims 1 to 7 can be implemented.

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