Method and device for predicting and analyzing gully catchment surface disaster along railway based on three-dimensional geographic scene

Abstract

The invention belongs to the technical field of traffic geographical environment safety risk prediction, and particularly relates to a railway line gully catchment surface disaster prediction analysis method based on a three-dimensional geographical scene, and the method comprises the following steps: S1, preliminarily delineating a monitoring range; s2, environment monitoring sensing equipment is installed; s3, collecting key index information of the drainage system; s4, acquiring three-dimensional geographic model data; s5, processing the acquired data; s6, calculating and analyzing the ground elevation and area of the monitoring area; s7, simulating rainfall and calculating total rainfall; s8, calculating the total rainwater convergence amount; s9, performing active flooding analysis on the terrain elevation model; s10, calculating and analyzing the specific position of the catchment surface and catchment area and volume parameters changing along with time; and S11, predicting and evaluating possible catchment surface disasters. The technical problems of insufficient real-time performance, high data acquisition cost, complex operation and high calculation difficulty in the prior art can be solved, and the method has a relatively good market application prospect.

Description

Technical Field

[0001] The present invention belongs to the technical field of traffic geographical environment safety risk prediction, and specifically relates to a method and device for predicting and analyzing gully catchment surface disasters along railways based on a three-dimensional geographical scene. Background Art

[0002] In railway engineering, slope stability and watershed management are important factors to ensure the safe operation of railways. In recent years, with the rapid development of geographic information systems (GIS) and remote sensing technology, 3D geographic scene technology has gradually shown strong application potential in terrain analysis and disaster prediction. 3D geographic scene technology integrates multi-source data to generate realistic 3D terrain models, providing a new means for environmental monitoring and disaster prediction along the railway.

[0003] Traditional terrain analysis mainly relies on two-dimensional maps and ground surveys, which are difficult to fully reflect the three-dimensional structure and dynamic changes of complex terrain. Three-dimensional geographic scene technology uses high-precision digital elevation models (DEMs) and three-dimensional geographic information data to achieve a comprehensive and three-dimensional representation of terrain, which can more intuitively and accurately display terrain features and hydrological processes. Especially in complex terrain areas along railways, this technology provides important support for slope stability analysis and catchment area disaster prediction.

[0004] The existing prediction and analysis of rainfall catchment disasters can be roughly divided into two categories: one is the rainfall catchment calculation method analyzed by rainfall runoff estimation model, and the other is the analysis method by satellite imagery. The patent application publication number CN116628998A discloses a rainfall catchment calculation method suitable for mountainous areas. It constructs random raindrops on the terrain grid surface, increases the density and number of raindrops according to the actual rainfall, simulates the flow path of all rainwater on the terrain slope and the catchment model of the target area, and uses a visual programming language to analyze and process the rainfall catchment, forming a terrain point cloud and projecting it onto a plane map to calculate the catchment area, and finally obtain the total precipitation. The patent application with the publication number CN115796599A discloses a flash torrent risk analysis method and system based on the comprehensive characteristics of micro-watersheds. The method generates a stereoscopic image by acquiring ground model data and satellite data, extracts river sections and micro-watershed units that exceed the catchment area threshold, and extracts the confluence characteristics and calculates the rainstorm factor, runoff factor, confluence factor and risk-bearing body index based on the river section and micro-watershed unit data, thereby quantitatively assessing the risk of flash torrents.

[0005] Although the rainfall catchment calculation method based on terrain data can simulate the rainfall catchment in mountainous areas in detail, it has the following disadvantages:

[0006] 1) High complexity: This method involves constructing terrain grids, increasing the density of raindrops, simulating rainwater flow paths, and using visual programming languages ​​for analysis. The steps are complex and require high computing resources.

[0007] 2) Limited accuracy: The accuracy of simulation data depends on the terrain grid and rainfall model, which is greatly affected by the complexity of the terrain and the accuracy of the model, and may not fully and accurately reflect the actual situation;

[0008] 3) Insufficient real-time performance: When dealing with dynamic rainfall conditions and terrain changes, the real-time performance is poor, making it difficult to update and predict water catchment in a timely manner;

[0009] 4) Limited scope of application: This method has certain limitations in data acquisition and processing capabilities. It is suitable for specific regions, but its application is limited in remote or complex terrain areas.

[0010] In contrast, the flash flood gully risk analysis method based on the comprehensive characteristics of micro-watersheds, which generates stereoscopic images through satellite data collection to comprehensively evaluate watershed characteristics and risk factors, also has limitations such as high data acquisition cost and complex operation, making it difficult to achieve real-time monitoring and wide applicability.

[0011] The information disclosed in this background technology section is only intended to enhance the understanding of the overall background of the invention and should not be regarded as an acknowledgment or any form of suggestion that the information constitutes the prior art already known to a person skilled in the art. Summary of the invention

[0012] The purpose of the present invention is to provide a method and device for predicting and analyzing gully catchment surface disasters along railways based on three-dimensional geographical scenes, so as to solve the technical problems of insufficient real-time performance, high data acquisition cost, complex operation and high calculation difficulty in the prior art.

[0013] In order to achieve the above object, the present invention provides the following technical solutions:

[0014] A method for predicting and analyzing gully catchment surface disasters along a railway based on a three-dimensional geographic scene comprises the following steps:

[0015] S1. Preliminarily define the monitoring scope based on the given slopes and gullies along the railway where there may be a risk of watershed disasters;

[0016] S2. Scientifically install rain sensors, soil sensors and other sensing equipment within the monitoring range to monitor environmental parameters in real time, including: rainfall, soil moisture, soil saturation and water infiltration rate;

[0017] S3. Combined with the drainage system along the route, collect key indicator information of drainage ditches and pipelines in the monitoring area along the route from relevant design departments;

[0018] S4. Use drones and other equipment to obtain geographic model data such as digital elevation model DEM, digital surface model DSM, and three-dimensional tilt, image and other data to determine the terrain and environmental characteristics of the monitoring area;

[0019] S5. Perform data cleaning and correction, data interpolation and correction, spatial data integration, terrain analysis and modeling on the collected data to ensure the quality and integrity of the data, so as to facilitate the reliability of subsequent analysis and result presentation;

[0020] S6. Based on the digital elevation model (DEM) geographic model data obtained above, calculate the ground elevation, area and other key parameters of the monitoring area;

[0021] S7, simulating rainfall, rainfall area and rainfall time, and calculating the total rainfall in the monitoring area;

[0022] S8, combining the sensor data, taking into account the water absorption capacity and water infiltration rate of the soil and the drainage volume of the drainage ditch, and calculating the total amount of rainwater after the rainwater converges;

[0023] S9. Conduct active flooding analysis on the terrain elevation model;

[0024] S10, calculating and analyzing the specific location of the catchment surface, the catchment area and volume and other parameters that change with time;

[0025] S11. Analyze indicators such as the area of ​​the catchment area with different rainfall amounts and rainfall durations, the distance from the railway, and the relative railway elevation, so as to predict and evaluate possible catchment area disasters and provide a basis for prevention and response measures.

[0026] A gully catchment surface disaster prediction and analysis device along a railway based on a three-dimensional geographic scene, comprising:

[0027] Input module, used to input various sensor data, GIS spatial data and other key indicators required for analysis;

[0028] Preprocessing module: performs internal processing on spatial data to ensure data quality and integrity;

[0029] Calculation module: used to calculate total rainfall, catchment area, etc.;

[0030] Analysis module: used to perform active flooding analysis on digital elevation model DEM;

[0031] Display module: used to display the entire prediction process.

[0032] Preferably, the input module comprises:

[0033] The first input submodule is used to input and collect data sent back by various sensors in real time;

[0034] The second input submodule is used to input key indicators such as drainage volume of drainage ditches;

[0035] The third input submodule is used to collect geographic model data such as digital elevation model DEM, digital surface model DSM, and three-dimensional tilt, image and other data;

[0036] The fourth input submodule is used to input other parameter indicators for simulation prediction.

[0037] Preferably, the calculation module comprises:

[0038] The first calculation submodule is used to calculate the total rainfall;

[0039] The second calculation submodule is used to calculate and analyze the water seepage;

[0040] The third calculation submodule is used to calculate and analyze the drainage volume;

[0041] The fourth calculation submodule is used to calculate and analyze information such as the area of ​​the catchment area, the distance from the railway, and the relative railway elevation.

[0042] The gully catchment area disaster prediction and analysis device along the railway based on the three-dimensional geographical scene of the present invention also includes a processor and a storage medium; wherein,

[0043] The processor is used to execute each step of the above-mentioned method for predicting and analyzing gully catchment surface disasters along the railway based on the three-dimensional geographic scene;

[0044] The storage medium is used to store geographic data, including data collected by sensors, three-dimensional geographic scene data taken by drones, catchment area data obtained by calculation and analysis, etc. These data can be stored in a database, file system or other format for easy access and query at any time.

[0045] Compared with the prior art, the present invention has the following beneficial effects:

[0046] (1) The method for predicting and analyzing gully catchment area disasters along railways based on three-dimensional geographic scenes of the present invention can ensure the accuracy and real-time nature of the data by scientifically installing rainwater sensors, soil sensors and other equipment to monitor environmental parameters such as rainfall, soil moisture, soil saturation and water infiltration rate in real time, thereby providing reliable data support for subsequent analysis.

[0047] (2) The method for predicting and analyzing gully catchment area disasters along the railway based on three-dimensional geographic scenes of the present invention uses drones to obtain DEM, DSM and three-dimensional oblique image data, which can fully reflect the terrain and environmental characteristics of the monitoring area; through data cleaning, correction, interpolation and modification, the data quality and integrity can be ensured, making the terrain analysis more comprehensive, three-dimensional and intuitive.

[0048] (3) The three-dimensional geographic scene-based disaster prediction and analysis method for gully catchment areas along railways of the present invention is based on a high-precision three-dimensional terrain model and combined with GIS technology to simulate rainfall, rainfall area and rainfall time, so as to calculate the total rainfall in the monitoring area and the total amount of rainwater after confluence; through active flooding analysis, the specific location, area and volume of the catchment area and other parameters are calculated and analyzed, so as to provide accurate disaster prediction and assessment.

[0049] (4) The method for predicting and analyzing gully catchment area disasters along railways based on three-dimensional geographic scenes of the present invention predicts and evaluates catchment area disasters by analyzing indicators such as the area of ​​the catchment area, the distance from the railway, and the relative railway elevation, and provides a basis for prevention and response measures. It can effectively improve the level of environmental risk management along the railway, ensure the safety and reliability of railway operations, and have a positive impact on the railway industry and related stakeholders. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] Figure 1 It is a schematic flow chart of the method of the present invention;

[0051] Figure 2 is a schematic diagram of the analysis parameter configuration of the present invention;

[0052] Figure 3 It is a display diagram of the water catchment surface analysis effect of the present invention;

[0053] Figure 4 It is a schematic diagram of indicators of water catchment surface analysis results of the present invention. DETAILED DESCRIPTION

[0054] The following is a clear and complete description of the technical solution of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by technicians in this field without creative work are within the scope of protection of the present invention.

[0055] Example 1

[0056] Refer to the attached Figure 1 The present invention provides a method for predicting and analyzing gully catchment surface disasters along a railway based on a three-dimensional geographic scene, comprising the following steps:

[0057] Step 1: Preliminary definition of monitoring scope;

[0058] Based on historical data and expert assessment, initially identify the locations of slopes and gullies along the railway that may be at risk of watershed disasters; survey these areas, confirm the monitoring scope, and mark important locations; use geographic information system (GIS) software to draw the survey results into a monitoring scope map to ensure that all potential risk areas and confluence analysis areas are covered;

[0059] Step 2: Collect key indicator information of the drainage system;

[0060] Conduct field surveys of drainage systems along the route, including the layout and status of drainage ditches and pipes; collect drainage system design drawings and drainage data from relevant design and management departments, and integrate the collected data into the GIS system to form a complete drainage system information database;

[0061] Step 3: Install environmental monitoring sensor equipment;

[0062] Design a sensor deployment plan based on the terrain and risk assessment results to ensure representativeness of monitoring data; select rainwater sensors, soil moisture sensors, soil saturation sensors, and water infiltration rate sensors suitable for environmental monitoring, and install the sensors at predetermined locations to ensure that they are firmly installed and accurately positioned; set the sampling frequency and data transmission method of the sensors to ensure that real-time data can be transmitted stably;

[0063] Step 4: Obtain 3D geographic model data;

[0064] Develop UAV flight plans to cover the monitoring area, determine the flight altitude and route; check the UAV and its equipped cameras, GPS, IMU and other sensors to ensure the equipment is working properly; fly the UAV according to the plan to collect DEM, DSM and 3D oblique image data; download and check the data, perform preliminary processing to ensure the data is complete and correct;

[0065] 3D geographic scene technology uses multi-source remote sensing data (such as satellite images, aerial photography, laser radar, etc.) and geographic information system (GIS) to build a high-precision 3D terrain model; this technology can not only accurately reflect the elevation changes of the terrain, but also display information such as surface cover, buildings and vegetation, making terrain analysis more comprehensive, three-dimensional and intuitive; in the prediction of gully catchment disasters along the railway, GIS technology can process, analyze and visualize 3D geographic data, help engineers identify potential risk areas, conduct disaster simulation and formulate emergency plans;

[0066] Digital Elevation Model (DEM) is a digital surface elevation model commonly used in terrain analysis. It obtains surface elevation data through technologies such as laser radar and aerial photogrammetry, and uses mathematical interpolation methods to generate a continuous terrain surface. DEM is used as a basic data source in three-dimensional geographic scene technology to support analysis of terrain undulation, slope, flow direction, etc.

[0067] Step 5: Data processing;

[0068] Clean and correct the collected data, use professional software to clean the raw data, remove noise and outliers; at the same time, correct the data to ensure data accuracy; interpolate missing data, use reasonable interpolation methods to fill data gaps, and ensure data continuity and integrity; integrate data from different sources (such as DEM, DSM, image data, etc.), unify the coordinate system and resolution, and form a complete spatial data set; perform terrain analysis and modeling based on the integrated data, calculate terrain parameters (such as slope, slope aspect, watershed range, etc.), and provide a basis for subsequent analysis; perform quality checks on processed data to ensure that the errors in the data processing process are within an acceptable range and that the integrity and reliability of the data are guaranteed;

[0069] Step 6: Calculate and analyze key parameters such as ground elevation and area of ​​the monitoring area;

[0070] Use DEM data to calculate the ground elevation within the initially delineated monitoring area and generate an elevation distribution map; use GIS tools to calculate the total area of ​​the monitoring area and the area of ​​each sub-area to ensure the accuracy of the area calculation results; further analyze the terrain data, such as slope distribution, aspect distribution and watershed division, to obtain more terrain feature parameters;

[0071] Step 7: Simulate rainfall and calculate total rainfall;

[0072] Use rainfall simulation software to set different rainfall scenarios and perform rainfall simulation; input actual rainfall data and historical rainfall data collected by sensors to perform scenario simulation; based on the simulation results, calculate the total rainfall in the monitoring area under different scenarios; the total rainfall calculation formula is as follows:

[0073] ;

[0074] in: is the total rainfall (cubic meters); is the rainfall (meters); is the rainfall area (square meters);

[0075] Step 8: Calculate the total amount of rainwater collection;

[0076] Integrate the data of rainwater sensors and soil sensors to obtain real-time rainfall, soil moisture, soil saturation, and water infiltration rate data; combine the data of the drainage system to analyze the drainage capacity and efficiency of ditches and pipes; use the hydrological model to calculate the convergence process and total amount of rainwater, considering the influence of soil water absorption, infiltration, and drainage system; the total amount of water is calculated as follows:

[0077]

[0078] in: is the total catchment volume; It is the amount of water absorbed and infiltrated by the soil; is the displacement;

[0079] Step 9: Conduct active flooding analysis;

[0080] The seed point grid propagation algorithm is a computer vision algorithm for image segmentation and target detection. It mainly identifies objects or targets in images, especially targets with regular shapes and boundaries. The core of the seed point grid propagation algorithm is to select one or more seed points, which are located inside or near the image target and can be manually marked by the user or generated by automatic methods. The regional image is divided into a regular grid, each grid represents a pixel or a group of pixels, covering the potential target area of ​​the entire image. The propagation process starts from the seed point, and the algorithm determines the boundary of the target area based on pixel similarity metrics, such as color, texture, brightness and other features.

[0081] Specifically, the seed point grid propagation algorithm marks the grids around the seed point as part of the target area according to the similarity measurement and adds them to the queue to be processed; the propagation process follows a certain strategy, continuously spreading from the seed point to the surrounding eight neighborhoods to ensure that only areas similar to the target are added to the target area, which is controlled by thresholds or pixel similarity measurements; the propagation is iterative until there are no more grids to process or the stopping condition is reached, and the process can be iterated multiple times to improve the target boundary; after the propagation is completed, the algorithm extracts the boundary information of the target area to form the contour or segmentation result of the target;

[0082] Active flooding simulation based on seed point grid spreading algorithm is a method for simulating the flooding process under active flooding conditions. It combines the grid digital elevation model and performs special processing on individual pixels. The system automatically obtains spreading seed points through the catchment area of ​​the lowest point of the terrain, reads the network value and location information of the pixel points, and then compares these pixel points with the flooding elevation. If the grid value is less than the flooding elevation, it is placed in the flooding area buffer, otherwise it is placed in the non-flooding area buffer. Starting from the spreading seed point, the eight surrounding pixels are traversed, and the grid values ​​of these eight pixels are compared with the flooding elevation of the reservoir. If there is a grid point lower than the flooding elevation, the point is also set as a seed point and placed in the flooding area buffer, and the rest are placed in the non-flooding area buffer. The end condition of the flooding area analysis is when there are no flooding area grid points around all the seed points, that is, when no pixel value smaller than the flooding elevation can be found, which means that all the pixels of the digital elevation model have been calculated.

[0083] Step 10: Calculate the catchment area, volume, distance from the railway, and relative elevation to the railway;

[0084] The grid of the catchment area is vectorized to generate the vector graphics of the catchment surface; the catchment area can be obtained by using the method of calculating the vector surface area through GIS;

[0085] Calculate the water depth grid. For each grid cell, calculate the difference between the water level elevation and the terrain elevation, that is, the water depth. The specific formula is as follows:

[0086]

[0087] in, Is a grid cell The depth of water, is the determined water level elevation, Is a grid cell The terrain elevation of The function is to ensure that the water depth is positive, because if the water level elevation is lower than the terrain elevation, the water depth should be 0;

[0088] Calculate the volume of each grid cell. The volume calculation formula for each grid cell is:

[0089]

[0090] in, Is a grid cell The volume of Is a grid cell The depth of water, is the plane area of ​​each grid cell, usually the square of the grid resolution; for example, if the grid resolution is 1 meter × 1 meter, the area of ​​each grid cell is 1 square meter; if the resolution is 10 meters × 10 meters, the area is 100 square meters; add up the volumes of all grid cells, and add up the volumes of all grid cells to get the total water volume of the entire catchment area; the specific formula is as follows:

[0091]

[0092] in, is the total water volume of the catchment area, m and n are the number of rows and columns of the grid data respectively; by accumulating the volume of each grid cell, the total water volume of the entire catchment area can be obtained;

[0093] For each point on the vector plane, calculate its distance to the nearest railway line; the distance from the vector plane to the railway can be calculated using the Euclidean distance formula:

[0094]

[0095] in: is the coordinate of the point on the vector surface; is the coordinates of the point on the nearest railway line; is the distance between two points;

[0096] Determine the nearest point between the vector surface and the railway line. For each point on the vector surface, calculate its shortest distance to the railway line and determine the point on the railway line that is closest to it. Because the watershed surface and the railway line are already associated with the digital elevation model (DEM), the elevation values ​​of the watershed surface and the railway line can be directly obtained from the DEM. The formula for calculating the relative elevation difference is as follows:

[0097]

[0098] Among them, the point on the water surface is assumed to be , then its elevation is ; Let the point on the nearest railway line be , then its elevation is ; The relative elevation difference is d;

[0099] Finally, the water flow path and watershed range are analyzed, and the location of the catchment surface with different rainfall amounts and rainfall durations is calculated and analyzed. At the same time, the corresponding catchment surface area, volume, distance from the railway, relative elevation and other indicator information are calculated;

[0100] Step 11: Prediction and assessment of watershed disasters;

[0101] Comprehensively analyze key indicators such as the area of ​​the catchment area, distance from the railway and relative elevation; build a disaster prediction model, use the catchment area indicator data to predict, and determine the possible time and scope of disaster occurrence; formulate prevention and response measures based on the prediction results, including early warning systems, drainage improvements, emergency plans, etc.;

[0102] Risk analysis methods based on three-dimensional geographic scenarios integrate terrain data, rainfall data and hydrological models to simulate rainfall events and surface runoff paths, and quantitatively assess the risks of slope stability and catchment area formation. These methods can predict potential geological disasters such as debris flows and landslides, and provide a scientific basis for disaster prevention and emergency management along the railway.

[0103] The embodiment of the present invention also provides a device for predicting and analyzing gully catchment surface disasters along railways based on a three-dimensional geographical scene, which is used to execute each step of the method for predicting and analyzing gully catchment surface disasters along railways based on a three-dimensional geographical scene. The device specifically includes:

[0104] Input module: used to input various sensor data, GIS spatial data and other key indicators required for analysis;

[0105] Preprocessing module: performs internal processing on spatial data to ensure data quality and integrity;

[0106] Calculation module: used to calculate the total rainfall, catchment area, etc.;

[0107] Analysis module: used to perform active flooding analysis on the DEM elevation module;

[0108] Display module: used to display the entire prediction process.

[0109] The input module includes:

[0110] The first input submodule: used to input and collect data sent back by various sensors in real time;

[0111] The second input submodule: used to input key indicators such as drainage volume of drainage ditch;

[0112] The third input submodule is used to collect geographic model data such as DEM (digital elevation model), DSM (digital surface model), and three-dimensional tilt, image and other data;

[0113] The fourth input submodule is used to input other parameter indicators for simulation prediction.

[0114] The computing module includes:

[0115] The first calculation submodule: used to calculate the total rainfall;

[0116] The second calculation submodule is used to calculate and analyze the water seepage;

[0117] The third calculation submodule: used to calculate and analyze the drainage volume;

[0118] The fourth calculation submodule is used to calculate and analyze the area of ​​the catchment area, the distance from the railway, the relative railway elevation and other information.

[0119] The device for predicting and analyzing gully catchment surface disasters along railways based on three-dimensional geographic scenes provided in an embodiment of the present invention also includes a processor and a storage medium.

[0120] Processors are used for data conversion and calculation and geographic information system integration. The GIS data processor is responsible for processing the input monitoring range, track reference point and other information, performing the necessary mathematical calculations and coordinate conversion operations, and predicting and analyzing the gully catchment area disaster along the railway based on the three-dimensional geographic scene. This may involve executing coordinate conversion algorithms based on known geographic reference information, earth ellipsoid and other parameters. GIS data processors are usually able to integrate with geographic information systems (GIS) to access geospatial data, map projections, coordinate systems, etc. to ensure correct coordinate conversion and consistency of geographic data.

[0121] Storage media are used for geographic data storage, data backup and recovery, spatial indexing, and data management. The geographic data stored in the storage media include: the scope along the railway line, related three-dimensional geographic information data, etc. These data can be stored in a database, file system, or other format for access and query at any time. The data backup and recovery mechanism can prevent data loss or damage and ensure data security and availability. For large amounts of geographic data, the spatial index function can speed up data retrieval and query operations. The storage medium also provides data management functions, allowing operations such as classification, version control, and permission management of geographic data.

[0122] The method and device for predicting and analyzing gully and water surface disasters along the railway based on three-dimensional geographic scenes provided by the present invention are based on three-dimensional geographic scene technology and utilize high-precision digital elevation models and GIS technology to accurately predict and analyze gully and water surface disasters along the railway, providing strong technical support for the safe operation of the railway; by real-time monitoring of environmental parameters, comprehensive reflection of terrain environmental characteristics, and accurate simulation of rainfall and confluence processes, the scientificity and reliability of disaster prediction are significantly improved, which is conducive to ensuring that environmental risk management along the railway is more efficient and effective.

[0123] In the existing technology, high-resolution satellite remote sensing technology is often used to obtain terrain data and environmental parameters along the railway. By selecting appropriate remote sensing satellites, such as Sentinel-2, Landsat-8 or commercial satellites such as WorldView-3, images of the monitoring area are taken regularly; multispectral image data can analyze surface features and environmental parameters, and meteorological sensors on satellites can obtain data such as rainfall, surface temperature and humidity; the collected data is transmitted to the ground receiving station through the satellite communication system, and after receiving, it is pre-processed and analyzed using remote sensing image processing software; the processed data is integrated into the GIS system for terrain analysis and disaster prediction. However, this solution has limited acquisition frequency and cannot achieve real-time monitoring of rapidly changing environments. Although the spatial resolution of satellite data is high, it is greatly affected by weather and may not meet the accuracy requirements in complex terrain environments, especially the recognition of small-scale features. In addition, remote sensing image processing requires professional technology and software support, the processing process is complex, time and computing resources are high, the cost is very high, and weather and other conditions are also required.

[0124] Compared with the existing technology, the present invention solves the problems of insufficient real-time data collection, high data acquisition cost, complex operation, and high calculation difficulty. By scientifically installing sensor equipment on the slopes and gullies along the railway, real-time monitoring of environmental parameters, and using drones to obtain high-precision three-dimensional terrain data, the present invention combines GIS technology for data cleaning, correction, and multi-source data integration and analysis, thus achieving more accurate and scientific disaster prediction and assessment.

[0125] On the other hand, the present invention can also reduce complex manual operation steps through automated sensor network and drone data collection, making the entire monitoring and analysis process simpler and more efficient. Through these improvements, the method and device for predicting and analyzing gully catchment surface disasters along the railway based on three-dimensional geographic scenes provided by the present invention significantly improve the real-time nature of disaster management, the economy of data acquisition and the simplicity of operation, which is conducive to ensuring the safety and reliability of railway operation.

[0126] The foregoing description of specific exemplary embodiments of the present invention is for the purpose of illustration and demonstration. These descriptions are not intended to limit the present invention to the precise form disclosed, and it is clear that many changes and variations can be made based on the above teachings. The purpose of selecting and describing the exemplary embodiments is to explain the specific principles of the present invention and its practical application, so that those skilled in the art can realize and utilize various different exemplary embodiments of the present invention and various different selections and changes. The scope of the present invention is intended to be limited by the claims and their equivalents.

Claims

1. A method for predicting and analyzing gully catchment surface disasters along railways based on three-dimensional geographic scenes, characterized in that: The following steps are involved: S1. Preliminarily define the monitoring scope based on the given slopes and gullies along the railway where there may be a risk of watershed disasters; S2. Scientifically install rain sensors, soil sensors and other sensing equipment within the monitoring range to monitor environmental parameters in real time, including: rainfall, soil moisture, soil saturation and water infiltration rate; S3. Combined with the drainage system along the route, collect key indicator information of drainage ditches and pipelines in the monitoring area along the route from relevant design departments; S4. Use UAV equipment to obtain digital elevation model data, digital surface model data, and three-dimensional tilt and image data to determine the terrain and environmental characteristics of the monitoring area; S5. Perform data cleaning and correction, data interpolation and correction, spatial data integration, terrain analysis and modeling on the collected data to ensure the quality and integrity of the data, so as to facilitate the reliability of subsequent analysis and result presentation; S6. Calculate the ground elevation and area of ​​the monitoring area based on the digital elevation model (DEM) geographic model data obtained above; S7, simulating rainfall, rainfall area and rainfall time, and calculating the total rainfall in the monitoring area; S8, combining the sensor data, taking into account the water absorption capacity and water infiltration rate of the soil and the drainage volume of the drainage ditch, and calculating the total amount of rainwater after the rainwater converges; S9. Conduct active flooding analysis on the terrain elevation model; S10, calculating and analyzing the specific location of the catchment surface, and the catchment area and volume parameters changing over time; S11. Analyze the area of ​​the catchment area with different rainfall amounts and rainfall durations, the distance from the railway, and the relative elevation of the railway, predict and evaluate possible catchment area disasters, and provide a basis for prevention and response measures.

2. A device for predicting and analyzing gully catchment surface disasters along railways based on three-dimensional geographical scenes, characterized in that: include: Input module, used to input various sensor data, GIS spatial data and other key indicator data required for analysis; Preprocessing module: performs internal processing on spatial data to ensure data quality and integrity; Calculation module: used to calculate the total rainfall and catchment area; Analysis module: used for active flooding analysis of digital elevation models; Display module: used to display the entire prediction process.

3. The device for predicting and analyzing gully catchment surface disasters along railways based on three-dimensional geographic scenes according to claim 2 is characterized in that: The input module comprises: The first input submodule is used to input and collect data sent back by various sensors in real time; The second input submodule is used to input key indicators such as drainage volume of drainage ditches; The third input submodule is used to collect digital elevation model data, digital surface model data, and three-dimensional tilt and image data; The fourth input submodule is used to input other parameter indicators for simulation prediction.

4. The device for predicting and analyzing gully catchment surface disasters along railways based on three-dimensional geographic scenes according to claim 2, characterized in that: The calculation module comprises: The first calculation submodule is used to calculate the total rainfall; The second calculation submodule is used to calculate and analyze the water seepage; The third calculation submodule is used to calculate and analyze the drainage volume; The fourth calculation submodule is used to calculate and analyze the area of ​​the catchment area, the distance from the railway and the relative railway elevation information.

5. The device for predicting and analyzing gully catchment surface disasters along railways based on three-dimensional geographic scenes according to claim 2, characterized in that: Also includes a processor and a storage medium; wherein, The processor is used to execute each step of the method for predicting and analyzing gully catchment surface disasters along railways based on three-dimensional geographic scenes as described in claim 1; The storage medium is used to store geographic data, including data collected by sensors, three-dimensional geographic scene data taken by drones, and catchment area data obtained through calculation and analysis.

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