Geological disaster risk evaluation method based on INSAR dynamic deformation monitoring

Abstract

The invention provides a geological disaster risk evaluation method based on INSAR dynamic deformation monitoring, and the method comprises the following steps: S1, carrying out the evaluation of regional basic geological environment conditions, the method comprises the following steps: selecting landform, rock-soil body engineering geologic characteristic stratum lithology, geologic structure, meteorological and hydrological conditions, vegetation conditions, human engineering activities, land utilization status and the like as evaluation factors, and carrying out regional susceptibility evaluation with grid units by adopting an information amount model and an evidence weight model. The step S2 and the step S3 are carried out in sequence when the information amount model is adopted for judgment, and the step S4 and the step S5 are carried out in sequence when the evidence weight model is adopted for judgment; s2, factor information in a specific evaluation unit is collected, and a geological disaster information amount formula M.1 under various factor specific states is obtained; and S3, a plurality of influence factors are arranged in the evaluation unit, a plurality of states exist in each factor, and risk evaluation data of the total information amount of geological disaster occurrence under the condition of each state factor combination is obtained by using a formula M.2.

Description

Technical Field

[0001] This invention belongs to the field of disaster monitoring, and specifically relates to a geological disaster risk assessment method based on INSAR dynamic deformation monitoring. Background Technology

[0002] Geological hazards include landslides, mudslides, debris flows, ground subsidence, ground fissures, and ground settlement—all geological-related disasters that endanger people's lives and property, whether caused by natural factors or human activities. To prevent and mitigate geological hazards, protect people's lives and property, and promote sustainable economic and social development, geological hazard prevention and control work should adhere to the principles of prevention first, combining avoidance with remediation, and comprehensive planning with a focus on key areas. Based on a thorough collection of existing data, and using remote sensing, ground surveys, mapping, and engineering investigations as primary means, with residential areas as the main survey targets, detailed county-level geological hazard surveys and risk identification should be conducted. This aims to identify potential geological hazards and risk slopes to the greatest extent possible, conduct geological hazard risk assessments, and propose risk management countermeasures, providing a fundamental geological basis for disaster prevention and mitigation, land use planning, and government decision-making.

[0003] Existing geological hazard risk assessment technologies are limited and lack methods that combine dynamic factors such as InSAR deformation monitoring. As a result, the geological hazard risk assessment system lacks dynamic updating means, which is not conducive to long-term monitoring, identification and early warning of geological hazards.

[0004] Therefore, there is an urgent need for a geological hazard risk assessment method based on INSAR dynamic deformation monitoring. Summary of the Invention

[0005] This invention proposes a geological hazard risk assessment method based on INSAR dynamic deformation monitoring. Current assessment methods do not incorporate dynamic factor determination. After changes occur in the surface deformation state, current risk assessment methods cannot accurately assess geological hazard risks. A more accurate geological hazard risk assessment method is needed that can accurately reflect the geological risks in the region.

[0006] The technical solution of this invention is implemented as follows: a geological hazard risk assessment method based on INSAR dynamic deformation monitoring, the method comprising the following steps:

[0007] S1: Assess the basic geological environment conditions of the region, selecting factors such as topography, geomorphology, engineering geological characteristics of soil and rock, stratigraphy, geological structure, meteorology and hydrology, vegetation conditions, human engineering activities, and current land use as evaluation factors. Use the information content model and the evidence weight model to conduct regional susceptibility assessment using grid cells. When using the information content model, proceed to steps S2 and S3 sequentially; when using the evidence weight model, proceed to steps S4 and S5 sequentially.

[0008] S2: Collect factor information in a specific evaluation unit and obtain the geological hazard information quantity formula M.1 for various factors under specific conditions;

[0009] S3: Several influencing factors are listed in the evaluation unit. Each factor has several states. The total amount of information about the occurrence of geological disasters under the combination of factors in each state is obtained using the formula (M.2) to obtain risk assessment data.

[0010] S4: Overlay analysis is performed using the weight indices of influencing factors related to the formation of geological disasters; the weight of each evidence factor is calculated; and the contribution weight of all units in the evidence factor layer to the occurrence of geological disasters is calculated using conditional probability.

[0011] S5: The obtained contribution weights are optimized through the evidence layer, and risk assessment data is obtained based on the contribution weights and the tightness coefficient of the evidence factors in the evidence layer;

[0012] S6: Using weighted data from the integrated information content model and the evidence weight model, the susceptibility assessment results are classified into different levels.

[0013] S7: Based on the regional geological hazard susceptibility assessment, and incorporating assessment factors such as rainfall, earthquakes, and human engineering activities, a regional geological hazard risk assessment is conducted using the same model as the susceptibility assessment.

[0014] S8: The weighted data from the integrated model is used to classify the regional risk assessment results into different levels.

[0015] S9: Based on the collection of regional disaster-bearing body data, remote sensing interpretation, and field investigation, calculate the vulnerability of people and property in the region, and classify the vulnerability assessment results into levels.

[0016] S10: Based on the comprehensive assessment results of regional geological hazard risk and vulnerability, the preliminary results of the regional geological hazard risk assessment are determined.

[0017] S11: Regional time-series InSAR surface deformation monitoring data is periodically imported into the risk assessment model as a dynamic change factor. The model is then updated based on the weight parameters of the InSAR dynamic change factor to optimize and adjust the initially determined regional geological hazard risk results. The final regional geological hazard risk level is determined according to four levels: extremely high, high, medium, and low. This application discloses a geological hazard risk assessment method based on InSAR dynamic deformation monitoring. Based on geological environmental background conditions, topography, slope, structural development, network density, and rock and soil characteristics, it fully considers multi-source dynamic hazard-causing factors, such as rainfall, earthquakes, and human engineering activities. Combining current Internet of Things technology and SAR remote sensing satellite monitoring technology, it integrates real-time single-point GNSS surface deformation monitoring and wide-area long-term InSAR deformation data to establish a dynamic analysis model for analyzing geological hazard risk. Based on existing information technology, we will fully mine data, taking disaster-prone conditions as static background factors, rainfall, earthquakes, and human engineering activities as excitation variables, and single-point GNSS surface deformation monitoring and wide-area long-time InSAR deformation data as susceptibility characterization factors. We will use the above factors as inputs and outputs to target massive amounts of data.

[0018] A key element of any strategy or plan to reduce the risk of natural disasters is to conduct an objective and comprehensive assessment of disasters using useful and relevant scientific data. Geological hazard risk assessment is a highly relevant and important research topic and a crucial non-engineering measure for mitigating disaster losses. Geological hazard risk research is a newly emerging research field in recent years and is receiving increasing attention. While research on natural disasters has a long history both domestically and internationally, research on natural disaster risk is a relatively new field that has only emerged in recent decades. Along with the development of natural disaster risk assessment, geological hazard risk assessment has flourished in recent decades, but it is still not fully mature in both theory and practice.

[0019] Furthermore, the uploaded geological hazard information is obtained by using the synthetic aperture radar interferometry onboard the satellite to acquire geological information in the region, and the geological hazard information is determined and collected based on the topographic changes at different times before being uploaded.

[0020] Furthermore, the geological disaster information in step S1 includes regional surface deformation, regional weather, regional geology, and regional population heat map distribution modeling.

[0021] Furthermore, the regional surface deformation is observed using radar satellites, and the satellite-collected data is analyzed using InSAR technology.

[0022] Furthermore, the evaluation unit in step S2 is an independent region formed after the coverage area is divided when the satellite performs regional coverage.

[0023] Furthermore, the factor information in step S2 includes landslides, collapses, debris flows, ground subsidence, and ground fissures.

[0024] Furthermore, the information content formula M.1 is expressed as:

[0025]

[0026] Where IAj→B represents the amount of information about the occurrence of geological disaster B under the corresponding factor A, state j (or interval); N j S represents the number of units corresponding to the distribution of geological hazards under state (or interval) of factor A and j; N represents the total number of units in the survey area where geological hazards are known to exist; S j S represents the number of units in the distribution of state (or interval) of factor A and j; S represents the total number of units in the survey area.

[0027] Furthermore, the information content formula M.2 is expressed as:

[0028]

[0029] Where I represents the total information content corresponding to the occurrence of geological disasters in a specific unit, indicating the likelihood of geological disasters occurring, and can be used as a geological disaster susceptibility index; N i This refers to the area or number of geological hazards corresponding to specific factors and the i-th state (or interval); S i N represents the distribution area corresponding to a specific factor and the i-th state (or interval); N represents the total area of ​​geological hazards or the total number of geological hazard points in the survey area; and S represents the total area of ​​the survey area.

[0030] After adopting the above technical solution, the beneficial effects of the present invention are as follows: By incorporating dynamic factors, the geological hazard risk in a region is routinely assessed based on factors such as regional topography, geomorphology, engineering geological characteristics of soil and rock, strata lithology, geological structure, meteorology and hydrology, vegetation conditions, and human engineering activities. The actual surface deformation rate data is obtained by processing the data using the InSAR method. Based on the threshold range of surface deformation rate, multiple dynamic disaster-causing factors, such as rainfall, earthquakes, and human engineering activities, are fully considered. Combining current Internet of Things technology and SAR remote sensing satellite monitoring technology, and integrating real-time single-point GNSS surface deformation monitoring and wide-area long-term InSAR deformation data, a dynamic analysis model is established to dynamically analyze the geological hazard risk. Attached Figure Description

[0031] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0032] Figure 1 This is a flowchart of the method of the present invention. Detailed Implementation

[0033] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0034] Example:

[0035] like Figure 1 As shown, a geological hazard risk assessment method based on INSAR dynamic deformation monitoring is presented, the method comprising the following steps:

[0036] S1: Assess the basic geological environment conditions of the region, selecting factors such as topography, engineering geological characteristics of soil and rock, stratigraphy, geological structure, meteorology and hydrology, vegetation conditions, human engineering activities, and current land use as evaluation factors. Use the information content model and the weight of evidence model to conduct regional susceptibility assessment on a grid cell basis. When using the information content model, proceed to steps S2 and S3 sequentially; when using the weight of evidence model, proceed to steps S4 and S5 sequentially. Assess the basic geological environment conditions of the region, including factors such as topography, engineering geological characteristics of soil and rock, geological structure, meteorology and hydrology, vegetation conditions, human engineering activities, and current land use. Use the information content model and the weight of evidence model to conduct regional susceptibility assessment on a grid cell basis.

[0037] S2: Collect factor information in a specific evaluation unit and obtain the geological hazard information quantity formula M.1 for various factors under specific conditions; collect factor information in a specific evaluation unit. Obtain the geological hazard information quantity formula for various factors under specific conditions.

[0038] S3: Several influencing factors are listed in the evaluation unit. Each factor has several states. The total information amount of geological disaster occurrence under the combination of factors in each state is obtained using formula (M.2) to obtain risk assessment data. The influencing factors listed in the evaluation unit are combined according to state, and the corresponding information amount formula (M.2) is used to obtain the total information amount of geological disaster occurrence to form risk assessment data.

[0039] S4: Perform overlay analysis using the weight indices of influencing factors related to the formation of geological disasters; calculate the weight of each evidence factor; calculate the contribution weight of all units in the evidence factor layer to the occurrence of geological disasters using conditional probability; perform overlay analysis using the weight indices of influencing factors related to the formation of geological disasters. Calculate the weight of each evidence factor and calculate the contribution weight of all units in the evidence factor layer to the occurrence of geological disasters using conditional probability.

[0040] S5: The obtained contribution weights are optimized through the evidence layer, and risk assessment data is obtained based on the contribution weight size and evidence factor tightness coefficient in the evidence layer; The obtained contribution weights are optimized through the evidence layer, and risk assessment data is obtained by considering the contribution weight size and evidence factor tightness coefficient.

[0041] S6: Using weighted data from the integrated information content model and the evidence weight model, the susceptibility assessment results are classified into different levels.

[0042] S7: Based on the regional geological hazard susceptibility assessment, and incorporating assessment factors such as rainfall, earthquakes, and human engineering activities, a regional geological hazard risk assessment is conducted using the same model as the susceptibility assessment.

[0043] S8: The weighted data from the integrated model is used to classify the regional risk assessment results into different levels.

[0044] S9: Based on the collection of regional disaster-bearing body data, remote sensing interpretation, and field investigation, calculate the vulnerability of people and property in the region, and classify the vulnerability assessment results into levels.

[0045] S10: Based on the comprehensive assessment results of regional geological hazard risk and vulnerability, the preliminary results of the regional geological hazard risk assessment are determined.

[0046] S11: Import regional temporal InSAR surface deformation monitoring data as dynamic change factors into the risk assessment model at regular intervals, match and update according to the weight parameters of the INSAR dynamic change factors, optimize and adjust the preliminary regional geological disaster risk results, and determine the final regional geological disaster risk level according to four levels: extremely high, high, medium and low.

[0047] The working principle of the InSAR dynamic deformation monitoring-based geological hazard risk assessment method is to comprehensively analyze multiple factors within a region and combine them with surface deformation monitoring data to assess the risk level of geological hazards. This method comprehensively considers the influencing factors of natural conditions, human activities, and dynamic changes in the surface, using both information quantity models and evidence weight models to evaluate the susceptibility and danger of geological hazards, and combining this with the vulnerability of the affected body to ultimately determine the regional geological hazard risk level.

[0048] This application discloses a geological hazard risk assessment method based on INSAR dynamic deformation monitoring. Based on geological environmental background conditions, topography, slope, tectonic development, network density, and soil and rock characteristics, it fully considers multi-source dynamic hazard-causing factors, such as rainfall, earthquakes, and human engineering activities. Combining current IoT technology and SAR remote sensing satellite monitoring technology, it integrates real-time single-point GNSS surface deformation monitoring and wide-area long-term InSAR deformation data to establish a dynamic analysis model for analyzing geological hazard risk. Based on existing information technology, it fully conducts data mining, using hazard-causing conditions as static background factors, rainfall, earthquakes, and human engineering activities as excitation variables, and single-point GNSS surface deformation monitoring and wide-area long-term InSAR deformation data as susceptibility characterization factors. Using these factors as inputs and outputs, it addresses massive datasets.

[0049] The Synthetic Aperture Radar (SAR) dataset in this application is acquired using SAR interferometry. It utilizes radar to transmit microwaves towards a target area and then receives the echoes reflected from the target, obtaining SAR complex image pairs of the same target area. If there is coherence between the complex image pairs, conjugate multiplication of the SAR complex image pairs yields an interferogram. Based on the phase values ​​of the interferogram, the path difference of the microwaves in the two imaging processes is calculated, thereby determining the topography, geomorphology, and minute surface changes of the target area. Actual surface deformation rate data is obtained through InSAR processing. Based on the surface deformation rate threshold range, the data is classified into the same levels as the long-term geological state levels, i.e., five rate levels are also defined.

[0050] InSAR is a 3D imaging technology for the Earth from space. It marks a new stage in space remote sensing, moving from 2D to 3D information acquisition, and has brought about a revolution in geodesy. This technology provides a completely new tool for the study of geological hazards. Using InSAR technology for ground micro-displacement monitoring is a new method that has developed in recent years and gained increasing attention. This technology has been widely applied in topographic surveying, ground deformation monitoring, volcanic activity assessment and monitoring, and other geological hazard assessments, achieving many encouraging results.

[0051] The geological disaster interferometric radar model consists of models based on regional surface deformation, regional weather, regional geology, and regional population heat map distribution. The geological observation satellite uses basic radar operating parameters for modeling, including basic parameters such as operating frequency range, operating bandwidth, transmission power, and receiving sensitivity.

[0052] A key element of any strategy or plan to reduce the risk of natural disasters is to conduct an objective and comprehensive assessment of disasters using useful and relevant scientific data. Geological hazard risk assessment is a highly relevant and important research topic and a crucial non-engineering measure for mitigating disaster losses. Geological hazard risk research is a newly emerging research field in recent years and is receiving increasing attention. While research on natural disasters has a long history both domestically and internationally, research on natural disaster risk is a relatively new field that has only emerged in recent decades. Along with the development of natural disaster risk assessment, geological hazard risk assessment has flourished in recent decades, but it is still not fully mature in both theory and practice.

[0053] The geological disaster interferometric radar model consists of models based on regional surface deformation, regional weather, regional geology, and regional population heat map distribution. The geological observation satellite uses basic radar operating parameters for modeling, including basic parameters such as operating frequency range, operating bandwidth, transmission power, and receiving sensitivity.

[0054] The method employs satellite observation, collecting surface displacement data via satellite radar and simultaneously gathering regional data. It models the transmitted signal waveforms of the satellite radar, setting parameters such as frequency, repetition rate, pulse width, pulse count, and specific parameters for particular modulation types. Real-time data updates and simulation output are then performed. A synthetic aperture radar (SAR) dataset is generated, acquiring deformation components of ground points along the radar's line-of-sight. These deformation components are used to make a preliminary judgment on the type of geological hazard. Geological hazard types include landslides, collapses, debris flows, ground subsidence, and ground fissures. Deformation data includes coseismic displacement information, deformation trend information, and deformation displacement values. The changes in these three data points, combined with the deformation data, form a change curve. The curvature of this curve is used to conduct a risk assessment of the geological hazard.

[0055] The uploaded geological hazard information is obtained by acquiring surface deformation information within the region through synthetic aperture radar interferometry onboard a satellite. Geological hazard information is then assessed and collected based on topographic changes over different time periods before being uploaded. The geological hazard information in step S1 comprises regional topography, regional weather, regional geology, and a regional population heat map distribution model. The regional topography is observed using geological observation satellites, and data collected by these satellites is gathered via radar. The evaluation unit in step S2 is an independent area formed after dividing the covered area during satellite coverage. The factor information in step S2 includes landslides, collapses, debris flows, ground subsidence, and ground fissures.

[0056] Furthermore, the information content formula M.1 is expressed as:

[0057]

[0058] Where IAj→B represents the amount of information about the occurrence of geological disaster B under the corresponding factor A, state j (or interval); N j S represents the number of units corresponding to the distribution of geological hazards under state (or interval) of factor A and j; N represents the total number of units in the survey area where geological hazards are known to exist; S j Let S be the number of units distributed under the states (or intervals) of factors A and j; and S be the total number of units in the survey area. For ease of understanding, let's consider a scenario where, after rainfall (j) exceeds a threshold due to a factor like heavy rain (A), the probability of a landslide (B) occurring in the area is considered. The number of units is determined by topography or satellite scanning, dividing the surface of an area into several units, each with independent topographic features. INSAR can record changes in these topographic features, and the risk of disasters can be assessed based on these changes. For example, if an area already has some ground fissures, the occurrence of a specific geological disaster or a factor corresponding to that disaster may worsen the severity of the disaster, thus requiring adjustment of its risk level.

[0059] The information content formula M.2 is expressed as follows:

[0060]

[0061] Where I represents the total information content corresponding to the occurrence of geological disasters in a specific unit, indicating the likelihood of geological disasters occurring, and can be used as a geological disaster susceptibility index; N i This refers to the area or number of geological hazards corresponding to specific factors and the i-th state (or interval); S i N represents the distribution area corresponding to a specific factor and the i-th state (or interval); N represents the total area of ​​geological hazards or the total number of geological hazard points in the survey area; and S represents the total area of ​​the survey area.

[0062] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A geological hazard risk assessment method based on INSAR dynamic deformation monitoring, characterized in that, The method includes the following steps: S1: Assess the basic geological environment conditions of the region, selecting factors such as topography, geomorphology, engineering geological characteristics of soil and rock, stratigraphy, geological structure, meteorology and hydrology, vegetation conditions, human engineering activities, and current land use as evaluation factors. Use the information content model and the evidence weight model to conduct regional susceptibility assessment in grid cells. When using the information content model, proceed to steps S2 and S3 in sequence. When using the evidence weight model, proceed to steps S4 and S5 in sequence. S2: Collect factor information in a specific evaluation unit and obtain the geological hazard information quantity formula M.1 for various factors under specific conditions; S3: Several influencing factors are listed in the evaluation unit. Each factor has several states. The total amount of information about the occurrence of geological disasters under the combination of factors in each state is obtained using the formula M.2 to obtain risk assessment data. S4: Perform an overlay analysis using the weight indices of influencing factors related to the formation of geological disasters; calculate the weight of each evidence factor; The contribution weights of all cells in the evidence factor layer to the occurrence of geological disasters are calculated using conditional probability. S5: The obtained contribution weights are optimized through the evidence layer, and risk assessment data is obtained based on the contribution weights and the tightness coefficient of the evidence factors in the evidence layer; S6: Using weighted data from the integrated information content model and the evidence weight model, the susceptibility assessment results are graded. S7: Based on the regional geological hazard susceptibility assessment, and combined with rainfall, earthquake, and human engineering activity assessment factors, a regional geological hazard risk assessment is conducted using the same model as the susceptibility assessment. S8: Using weighted data from a comprehensive model, the regional risk assessment results are classified into different levels. S9: Based on the collection of regional disaster-bearing body data, remote sensing interpretation, and field investigation, calculate the vulnerability of people and property in the region, and classify the vulnerability assessment results into levels; S10: Based on the comprehensive assessment results of regional geological hazard risk and vulnerability, the preliminary results of the regional geological hazard risk assessment are determined; S11: Import regional temporal InSAR surface deformation monitoring data as dynamic change factors into the risk assessment model at regular intervals, match and update according to the weight parameters of the INSAR dynamic change factors, optimize and adjust the preliminary regional geological disaster risk results, and determine the final regional geological disaster risk level according to four levels: extremely high, high, medium and low.

2. The geological hazard risk assessment method based on INSAR dynamic deformation monitoring as described in claim 1, characterized in that: The uploaded temporal InSAR surface deformation monitoring data is obtained by using synthetic aperture radar interferometry on a satellite to acquire surface deformation information at different time intervals within the region. The impact of surface deformation at different time intervals on geological hazard information is determined and then uploaded.

3. The geological hazard risk assessment method based on INSAR dynamic deformation monitoring as described in claim 1, characterized in that: Regional surface deformation is observed using radar satellites, and the satellite-collected data is analyzed using InSAR technology.

4. The geological hazard risk assessment method based on INSAR dynamic deformation monitoring as described in claim 1, characterized in that: The factor information in step S2 includes collapse, landslide, debris flow, ground subsidence, and ground fissure.

5. The geological hazard risk assessment method based on INSAR dynamic deformation monitoring as described in claim 1, characterized in that: The information content formula M.1 is expressed as follows: Where IAj→B represents the amount of information about the occurrence of geological disaster B under the corresponding factor A, state j (or interval); N j S represents the number of units corresponding to the distribution of geological hazards under state (or interval) of factor A and j; N represents the total number of units in the survey area where geological hazards are known to exist; S j S represents the number of units in the distribution of state (or interval) of factor A and j; S represents the total number of units in the survey area.

6. The geological hazard risk assessment method based on INSAR dynamic deformation monitoring as described in claim 1, characterized in that: The information content formula M.2 is expressed as follows: Where I represents the total information content corresponding to the occurrence of geological disasters in a specific unit, indicating the likelihood of geological disasters occurring, and can be used as a geological disaster susceptibility index; N i This refers to the area or number of geological hazards corresponding to specific factors and the i-th state (or interval); S i N represents the distribution area corresponding to a specific factor and the i-th state (or interval); N represents the total area of ​​geological hazards or the total number of geological hazard points in the survey area; and S represents the total area of ​​the survey area.

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