Geological disaster early warning method based on troposphere delay decoupling

Abstract

The invention discloses a geological disaster early warning method based on troposphere delay decoupling, and relates to the field of geological disaster monitoring and navigation positioning, and the method comprises the steps: carrying out the time-space synchronous collection of multi-modal data; geologically decoupling the troposphere delay component, and converting atmospheric noise into a geological signal; constructing delay-catastrophe parameter dynamic mapping; dynamically reconstructing a terrain adaptive reference station, and dynamically reconstructing a virtual GNSS reference point network with the same height as a monitoring point by using a digital elevation model (DEM); performing three-dimensional reconstruction on a disaster risk field, fusing the delay mapping factor and the earth surface deformation data, and generating a multi-dimensional risk field; constructing an early warning threshold self-evolution mechanism; and constructing a multi-stage joint control early warning decision. According to the invention, the accuracy of early warning of geological disasters can be improved, and intelligent technical support is provided for disaster prevention and reduction.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of geological disaster monitoring and navigation, and particularly relates to a geological disaster early warning method based on decoupling of troposphere delay. BACKGROUND

[0002] With the growing demand for remote sensing monitoring, geological disaster prevention and emergency management, how to achieve accurate monitoring and efficient early warning of geological disasters has become a technical problem to be solved. Traditional geological disaster monitoring methods rely on manual patrol, single sensor monitoring or data collection of fixed monitoring points. These methods often have limited monitoring coverage, delayed data updates and slow response speed in the face of complex terrain, changing climate and rapid disaster occurrence, and are difficult to meet the needs of modern disaster prevention and mitigation. In recent years, the development of multi-source remote sensing technology, GNSS deformation monitoring, meteorological and hydrological observation and unmanned aerial vehicle patrol has provided rich data sources for disaster monitoring. However, different data sources have differences in spatial resolution, temporal resolution and data accuracy, and a single data source cannot fully reflect the formation mechanism and evolution process of geological disasters. At the same time, static early warning threshold setting has obvious shortcomings in dealing with dynamic changing disaster risks, which can easily lead to false negatives or false positives.

[0003] At present, although the existing technology introduces a risk assessment model and a certain degree of data fusion algorithm, there are still great technical bottlenecks in how to integrate multi-source monitoring data in space and time, construct a three-dimensional dynamic model of disaster risk, and realize adaptive adjustment of the early warning threshold combined with real-time data. In addition, the disaster early warning system is mostly single-level triggered in the decision mechanism, lacks a dynamic response strategy of multi-level control, and is difficult to develop accurate and hierarchical control measures for different development stages of disasters. Therefore, an intelligent geological disaster early warning system that can integrate multi-source monitoring data, realize three-dimensional reconstruction of risk field, have a self-evolution mechanism of early warning threshold, and combine a multi-level control decision tree is needed to improve the accuracy, timeliness and reliability of monitoring, so as to effectively reduce the loss of personnel and property caused by disasters. SUMMARY

[0004] The purpose of the present application is to provide a geological disaster early warning method based on decoupling of troposphere delay, which can realize three-dimensional dynamic reconstruction of geological disaster risk, adaptive adjustment of early warning threshold, and multi-level control early warning response, thereby improving the accuracy, timeliness and reliability of geological disaster monitoring. To achieve the above purpose, the present application provides the following solutions:

[0005] In a first aspect, the present application provides an intelligent geological disaster risk assessment and early warning method based on multi-source data fusion, which comprises:

[0006] Obtaining multi-source monitoring data, the multi-source monitoring data including GNSS ZWD, ground deformation data, meteorological data, soil saturation and spatial gradient information thereof.

[0007] Performing spatio-temporal registration and signal preprocessing on the multi-source monitoring data to obtain preprocessed data in a unified format.

[0008] Based on the preprocessed data, an interpolation and inversion algorithm with geological parameter constraints is adopted to construct a three-dimensional disaster risk field model.

[0009] According to the change rate and spatial gradient of the three-dimensional risk field model, a self-evolution algorithm is used to dynamically adjust the early warning trigger threshold to obtain a real-time updated early warning threshold.

[0010] The three-dimensional risk field data and the dynamic early warning threshold are input into a multi-level control decision tree model to perform hierarchical judgment on the disaster risk, and a corresponding early warning response strategy is output, including an early warning level, a response measure and a resource scheduling scheme.

[0011] In a second aspect, the present application provides a computer device, comprising a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the above-mentioned early warning method for geological disasters based on the decoupling of the tropospheric delay.

[0012] In a third aspect, the present application provides a computer readable storage medium having a computer program stored thereon, wherein the computer program is executed by a processor to implement the above-mentioned early warning method for geological disasters based on the decoupling of the tropospheric delay.

[0013] In a fourth aspect, the present application provides a computer program product comprising a computer program, wherein the computer program is executed by a processor to implement the above-mentioned early warning method for geological disasters based on the decoupling of the tropospheric delay.

[0014] According to the specific embodiments provided by the present application, the following technical effects are disclosed:

[0015] The application provides a geological disaster early warning method based on troposphere delay decoupling. Through the spatio-temporal synchronous acquisition of multi-modal data, the GNSS observation, InSAR deformation, meteorological hydrology, soil moisture and DEM and other multi-source information are unified in seconds and consistent in spatial reference, laying a solid foundation for subsequent multi-source data fusion. Through the geological decoupling of the troposphere delay component, the ZTD is decomposed into ZHD and ZWD using the Saastamoinen model, and the wet delay is further decomposed into the surface water content change, the water level change coupling and the rock mass stress change component, so that the original atmospheric noise signal is converted into an effective parameter reflecting geological activity, greatly improving the availability and interpretation of deformation monitoring data. In the delay-disaster parameter dynamic mapping link, the application uses the matrix mapping relationship to establish a quantitative correlation between the delay component and the soil saturation, the crack expansion index, the rock mass stress change rate and other disaster sensitive factors, realizes the efficient conversion of the delay parameter to the actual disaster causing factor, and ensures that the risk assessment has more physical meaning and prediction ability. In view of the precision loss problem of the traditional reference station in the complex terrain with height difference, the application proposes a terrain adaptive reference station dynamic reconstruction method, generates a virtual GNSS reference network with the same height as the monitoring point based on DEM data, eliminates the system error caused by the height difference, and significantly improves the observation precision and stability. In the three-dimensional reconstruction of the disaster risk field, the application fuses the delay mapping factor and the surface deformation data, uses the spatial interpolation and volume rendering technology to construct a multi-dimensional risk field, which can present the distribution range, intensity gradient and spatial evolution trend of the potential geological disaster in a stereoscopic manner, providing visual and quantitative support for risk identification. In order to overcome the defect that the fixed early warning threshold is easy to produce false alarm or false alarm in the dynamic environment, the application introduces a self-evolution mechanism of the early warning threshold, adjusts the threshold in real time by combining the delay change rate, the soil saturation gradient and other factors through a dynamic adjustment function, so that the early warning system can adapt to different climate conditions, geological states and disaster development speed, thereby intervening in advance when the risk changes rapidly, improving the sensitivity and reliability of the early warning. Finally, in the multi-level control early warning decision, the application constructs a response system based on the risk field grading, divides the disaster risk into multiple levels, and links with the emergency dispatch, patrol dispatch and other links, forming a closed-loop management process from risk monitoring, threshold adjustment to emergency disposal. The method not only can trigger low-level early warning in the early stage of disaster, prompt attention and monitoring, but also can automatically upgrade to high-level early warning and issue disposal commands when the risk significantly improves, realizing the integration of early warning and response. Through the technical means of multi-modal data fusion, delay geological decoupling, dynamic threshold adjustment and multi-level response control, the application significantly improves the precision, real-time performance and reliability of geological disaster monitoring and early warning, and can be widely applied to the prevention and control scenes of landslides, debris flows, ground subsidence and other disasters, and has important engineering application value and popularization significance. BRIEF DESCRIPTION OF DRAWINGS

[0016] Fig. 1 This is a flowchart illustrating a geological disaster early warning method based on tropospheric delayed decoupling, as provided in an embodiment of this application.

[0017] Fig. 2 This is a flowchart illustrating the overall process of a geological disaster early warning method based on tropospheric delay decoupling, as provided in an embodiment of this application.

[0018] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used together with the embodiments of the invention to explain the invention and do not constitute a limitation thereof. Detailed Implementation

[0019] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0020] like Figs. 1-2 As shown, the geological disaster early warning method based on tropospheric delayed decoupling proposed in this invention includes the following steps:

[0021] Step 1: Spatiotemporal synchronous acquisition of multimodal data.

[0022] Step 2: Geological decoupling of the tropospheric delay component, converting atmospheric noise into geological signals.

[0023] Step 3: Construct a dynamic mapping of latency-catastrophic parameters;

[0024] Step 4: Dynamic reconstruction of terrain-adaptive reference stations. A virtual GNSS reference point network with the same elevation as the monitoring points is dynamically reconstructed using a digital elevation model (DEM).

[0025] Step 5: Three-dimensional reconstruction of the disaster risk field, integrating delay mapping factors and surface deformation data to generate a multi-dimensional risk field;

[0026] Step Six: Construct a self-evolutionary mechanism for early warning thresholds;

[0027] Step 7: Construct a multi-level joint control and early warning decision-making system.

[0028] Step one, "Multimodal Data Spatiotemporal Synchronous Acquisition," primarily ensures accurate temporal and spatial alignment of data from different sources, facilitating subsequent analysis and processing. First, a unified geodetic benchmark and projection system are used to process the spatial coordinates of different data sources, ensuring they are within the same coordinate reference frame. For time synchronization, GNSS time synchronization is used as the primary clock source, supplemented by network time synchronization, and clock drift monitoring of sampling equipment ensures high accuracy of data timestamps. Regarding the sampling strategy, sampling frequencies with different time resolutions are set based on the characteristics of disaster monitoring, while real-time quality control is performed to detect outliers and noise. Data transmission employs encryption protocols to ensure data security and reliability. Furthermore, all data undergoes standardization processing to generate a spatiotemporally consistent database, facilitating subsequent analysis and fusion.

[0029] Step two: The Saastamoinen model is used to separate the ZHD and ZWD components in the ZTD; the linear relationship between the wet delay hydrological component and soil moisture content, and the differential relationship between the deformation component and rock mass strain acceleration are established through field calibration; the terrain obscuring coefficient μ is calculated using the DEM, and satellite signal penetration path correction is performed on the mountain monitoring points, finally outputting the delay component parameters with geological and engineering significance. The GNSS ZWD is separated into three types of geological response components:

[0030] ZWD(t)=ZWD geo +ZWD hydro (t)+ZWD deform (t)

[0031] Among them, ZWD hydro To couple the components with surface water content and water level changes, ZWD deform ZWD represents the rock mass stress and slip movement components. geo This is the observation bias term caused by obstructed terrain.

[0032] Step three involves transforming the tropospheric delay characteristics obtained from geological decoupling in Step two into a parameter set that directly discriminates against geological catastrophic processes. Multiple features of the delay data are extracted and mapped to geological hazard parameters. By incorporating historical monitoring data and real-time observation data, a relationship model between delay and catastrophic parameters is established. Corrections for topography and geological conditions are added to the model to make the mapping more consistent with reality. Simultaneously, a dynamic update mechanism is used to continuously refine the model parameters using real-time data, ensuring that the mapping relationship remains effective and accurate despite environmental changes.

[0033] Step four effectively eliminates the delay differences caused by the different elevations of the base station and the monitoring point, ensuring that the virtual base station possesses the same terrain features as the monitoring point. This guarantees a more accurate correspondence between the delay data and geological parameters. Ultimately, the dynamically reconstructed virtual base station network not only improves the spatiotemporal accuracy of monitoring but also provides more reliable input data for subsequent risk field reconstruction and threshold setting. The ZTD correction formula is:

[0034]

[0035] Step five involves fusing the delay mapping factor with surface deformation data to achieve a three-dimensional reconstruction of the disaster risk field. The generated risk field expresses the disaster risk distribution characteristics in a three-dimensional manner in geographic space and, combined with time-series information, depicts the dynamic evolution of the risk. The constructed multidimensional risk field simultaneously includes spatial, temporal, and risk intensity dimensions, comprehensively characterizing the likelihood of disaster occurrence, its impact range, and potential destructiveness, providing support for subsequent early warning threshold setting and multi-level joint control and early warning decision-making. The expression for the three-dimensional disaster risk value R(x,y,z) is:

[0036] R(x,y,z)=f(S(x,y,z),σ'(x,y,z),C r (x,y,z))

[0037] Step six involves constructing a self-evolving early warning threshold mechanism. This mechanism introduces a dynamic adjustment function to adaptively correct the early warning trigger threshold. Based on statistical priors and expert experience, a baseline threshold is determined, and a spatiotemporally variable threshold field is generated according to deformation-driven factors and geomorphological characteristics. The threshold is updated in real time based on changes in monitoring data, deformation rate, and surface stability, and is further optimized through feedback from historical data. This mechanism ensures the smooth continuity of the threshold, avoids non-physical oscillations, and provides accurate early warning thresholds for different geographical regions and times. The dynamically adjusted threshold expression is:

[0038]

[0039] Among them, T alert (t) represents the early warning trigger threshold, T0 represents the initial early warning consistency, α represents the delayed change response factor, β represents the soil saturation influencing factor, and ▽ 2 S represents the soil saturation gradient.

[0040] Step seven involves establishing a multi-level joint control decision tree to classify and dynamically respond to disaster risks. This decision tree uses the risk value and its changing trend in the risk field as the core criterion, combined with risk level classification standards, to categorize disaster risks into different levels and set corresponding differentiated response measures. When the risk is at a low level, the system only monitors and records information; when the risk reaches a medium level, it initiates regional early warning and emergency preparedness; and when the risk enters a high level, it triggers comprehensive early warning and coordinated response, thus achieving tiered response and step-by-step joint control. This mechanism ensures the timeliness and accuracy of early warning results and forms a closed-loop chain from monitoring, assessment, early warning to response through multi-level decision paths, providing systematic and intelligent decision support for geological disaster prevention and control.

[0041] Compared with the prior art, the advantages of the present invention are:

[0042] The advantages of this invention lie in its innovative data fusion and dynamic modeling methods, which enhance the accuracy and response capabilities of real-time geological disaster early warning. First, by reconstructing a three-dimensional disaster risk field using multimodal data, comprehensive spatial and temporal coverage of risk assessment is achieved, providing higher accuracy for disaster prediction in complex geological environments. Second, the self-evolving early warning threshold mechanism dynamically adjusts the threshold based on real-time monitoring data, avoiding the limitations of fixed thresholds in traditional early warning models. This ensures greater flexibility and accuracy in threshold response, improving the adaptability and anti-interference capabilities of the early warning system. Furthermore, the constructed multi-level joint control decision-making mechanism intelligently generates corresponding response measures based on different risk levels, enabling refined management of disaster prevention and control, avoiding over-response or delayed response, and improving the timeliness and effectiveness of decision-making. Through these technical means, this invention significantly enhances the adaptability and stability of the disaster early warning system in complex environments, providing more systematic and intelligent support for the accurate monitoring and prevention of geological disasters, and possesses significant practical value and application prospects.

[0043] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0044] This document uses specific examples to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the methods and core ideas of this application. Furthermore, those skilled in the art will recognize that, based on the ideas of this application, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A geological disaster warning method based on a troposphere delay decoupling, characterized in that, Specifically comprising the following steps: (1) Multi-modal data space-time synchronous acquisition; (2) Tropospheric delay component geology decoupling, converting atmospheric noise into geological signals; (3) Delay-disaster parameter dynamic mapping; (4) Topographic self-adaptive base station dynamic reconstruction, using digital elevation model (DEM) to dynamically reconstruct and monitor virtual GNSS reference point network at the same height as the monitoring point; (5) Three-dimensional disaster risk field reconstruction, integrating delay mapping factors and surface deformation data to generate a multi-dimensional risk field; (6) Building an early warning threshold self-evolution mechanism; (7) Building a multi-level cascade control early warning decision. 2.The method for early warning of geological disasters based on the decoupling of the tropospheric delay according to claim 1, characterized in that, In step (1), the spatial reference is based on CGCS2000 / WGS84 as the horizontal reference and EGM2008 as the vertical reference, and the coordinates of data from different sources are converted, orthorectified and terrain corrected to ensure that all data fall into the same coordinate reference frame. In terms of time reference, GNSS time service (PPS) is used as the main clock source, IEEE-1588 PTP or NTP is configured as the redundant time service channel on the network side, and the edge device enables hardware time stamping and clock drift monitoring and automatic backhanding. All observations carry high-precision time stamps and clock health status markers. To solve the problem of inconsistent sampling frequency and transmission time delay of multi-source devices, the system sets a configurable synchronization time window Δt (seconds / minutes / hours) to perform unified resampling and alignment on asynchronous data within the window, and gives a missing data flag to avoid introducing false correlations for data outside the window. 3.The method of early warning of geological disasters based on the decoupling of the tropospheric delay according to claim 1, characterized in that, In step (2), the Saastamoinen model is used to separate the dry delay (ZHD) and wet delay (ZWD) components in the zenith tropospheric delay (ZTD). Through field calibration, a linear relationship between the hydrological component of the wet delay and the soil moisture content and a differential relationship between the deformation component and the rock mass strain acceleration are established. Combined with the digital elevation model (DEM), the terrain shielding coefficient μ is calculated to correct the satellite signal penetration path for mountain monitoring points. Finally, the delay component parameters with geological engineering significance are output, and the GNSS ZWD is separated into three types of geological response components. ZWD(t) = ZWD geo + ZWD hydro (t) + ZWD deform (t) where ZWD hydro is the coupling component with the surface water content and water level change, ZWD deform is the component of rock mass stress and sliding activity, ZWD geo is the observation bias term caused by the shielding topography. 4.The method of early warning of geological disasters based on the decoupling of the tropospheric delay according to claim 1, characterized in that, In step (3), the delay component is converted into actual geological disaster factors using matrix mapping relationship, and the mapping expression is: Where S is the soil saturation, σ' is the rock stress change rate, C r is the crack propagation exponent, and Φ is the hazard sensitive conversion matrix. 5.The method for early warning of geological disasters based on the decoupling of the tropospheric delay according to claim 1, characterized in that, In step (4), the correction formula for ZTD is: wherein ZTD corrected is the corrected total tropospheric delay value, ZTD obs is the original total delay value observed by the actual CORS base station, and Δh is the height difference between the current monitoring point and the reference station. 6.The method for early warning of geological disasters based on the decoupling of the tropospheric delay according to claim 1, characterized in that, In step (5), the expression of three-dimensional disaster risk value R(x, y, z) is: R(x,y,z) = f(S(x,y,z), σ'(x,y,z), C r (x,y,z)) 7.The method of early warning of geological disasters based on the decoupling of the tropospheric delay according to claim 1, characterized in that, In step (6), a dynamic adjustment function is introduced to automatically modify the early warning trigger threshold based on deformation and topographic factors. When the current risk value R(x, y, z) exceeds the dynamically adjusted threshold, the system will trigger an early warning response. The expression of the dynamically adjusted threshold is: Wherein, T alert (t) is the early warning trigger threshold, T0 is the initial early warning consistency, a is the delay change response factor, β is the soil saturation influence factor, and 2 S is the soil saturation gradient. 8.The method of early warning of geological disasters based on the decoupling of the tropospheric delay according to claim 1, characterized in that, In step (7), a multi-level cascade control decision tree is used to classify and respond to disaster risks, ensuring timely and accurate early warning decisions. Different early warning responses are taken according to different risk levels. The decision tree is based on disaster risk value R(x, y, z) and its change trend to form a decision-making mechanism to automatically generate early warning responses according to risk levels.

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