Geological disaster monitoring and early warning system

Abstract

The invention relates to a geological disaster monitoring and early warning system applied to the field of disaster early warning. The system comprises a monitoring module for collecting rainfall conditions, vegetation development conditions, soil water content, ground seam development conditions and human activity data, an analysis and judgment module comprising a preliminary analysis and dynamic correction unit, an early warning module for sending an alarm and an escape path, and a simulation module for predicting a disaster path, vegetation monitoring not only considers a soil fixation effect, but also introduces a root system destruction effect; human activity monitoring distinguishes overground engineering and underground engineering, the dynamic correction unit solves the influence of historical early warning residual risks on current evaluation through time attenuation and main control factor superposition, the system innovatively integrates the two-way influence of engineering efficiency and natural factors, building impact resistance evaluation is introduced, the early warning accuracy is remarkably improved, and the early warning efficiency is improved. And the method is especially suitable for progressive disaster prediction in engineering activity dense areas.

Description

Technical Field

[0001] The present invention relates to a disaster monitoring and early warning system, in particular to a geological disaster monitoring and early warning system applied in the field of disaster early warning. Background Art

[0002] The primary purpose of geological disaster early warning monitoring is to reduce losses and protect lives. This includes the role of early warning, such as identifying potential hazards in advance and implementing measures to prevent casualties and property damage. It also includes the role of protecting the ecological environment and economic development, promoting sustainable development.

[0003] The specification of Chinese invention patent CN118114992B discloses a remote sensing satellite geological disaster early warning method. By analyzing multiple geological characteristics, it improves the accuracy of geological risk prediction, and by simulating water-soil interactions, it improves the understanding of soil erosion mechanisms and landslide risks, thereby optimizing the effectiveness of disaster warnings.

[0004] The specification of Chinese invention patent CN118298609B discloses a debris flow monitoring and early warning system, which uses a monitoring and acquisition module to comprehensively detect surface precipitation, soil fluidity, vegetation coverage, surface rock area, and slope conditions in the monitoring target area, and uses this as a data analysis block to comprehensively analyze the degree of debris flow hazard in the detection target area, thereby achieving comprehensive and integrated consideration.

[0005] In the existing geological disaster early warning system, the water storage capacity of the surface layer is usually judged by monitoring vegetation, thereby playing a positive role in weakening mudslides. However, when mudslides actually occur, some plants are deep-rooted plants or bamboo plants. When their roots grow, they spread over a wide range and will cause the soil surface to become looser. When plants with developed root systems are carried by mudslides, the pulling and traction of the roots will cause the soil to become further loose, thereby increasing the degree of harm caused by mudslides. In addition, the existing geological disaster early warning system will ignore the intervention of human activities. For example, the existence of platforms or gullies on the surface will play an interception and weakening role in the early stage of mudslides. Therefore, the early warning system needs to be improved. Summary of the Invention

[0006] In view of the above-mentioned prior art, the technical problem to be solved by the present invention is.

[0007] To solve the above problems, the present invention provides a geological disaster monitoring and early warning system, which includes a monitoring module, a history storage module, an analysis and judgment module, an early warning module, and a simulation module. The analysis and judgment module is used to collect data from the monitoring module to analyze the early warning level and notify the early warning level through the early warning module. The history storage module is used to store the monitoring data of the monitoring module. The simulation module is used to simulate the path and speed of debris flow disasters. The monitoring module is used to collect environmental parameters of the monitored warning area, including precipitation monitoring unit, vegetation monitoring unit, soil mobility monitoring unit, ground crack monitoring unit and human activity monitoring unit. The vegetation monitoring unit is used to monitor the vegetation type, distribution area and season corresponding to the monitoring time point in the monitored area. The analysis and judgment module includes a preliminary analysis unit and a risk dynamic correction unit. The preliminary analysis unit is used to perform a preliminary analysis of the warning level based on the data collected by the monitoring module, and the risk dynamic correction unit dynamically corrects the warning risk based on the previous warning. The human activity monitoring unit includes an above-ground engineering monitoring unit and an underground engineering monitoring unit. The above-ground engineering monitoring unit is used to monitor the types and distribution areas of buildings on the surface of the monitored warning area, and the underground engineering monitoring unit is used to monitor the types and distribution areas of underground construction projects in the monitored area.

[0008] In the above-mentioned geological disaster monitoring and early warning system, the overall plan and effect are summarized in one sentence.

[0009] As a further improvement of this application, the calculation formula of the preliminary analysis unit is as follows: R=R(p)*0.2+R(w)*0.4+R(g)*0.15+R(f)*0.1+R(h)*0.15, where R(p) is the risk coefficient corresponding to the vegetation monitoring unit, R(w) is the risk coefficient corresponding to the precipitation monitoring unit, R(g) is the risk coefficient corresponding to the soil mobility monitoring unit, R(f) is the risk coefficient corresponding to the ground fissure monitoring unit, and R(h) is the risk coefficient corresponding to the human activity monitoring unit. In the rainy season, the weight of R(w) increases to 0.5 and the weight of R(p) decreases to 0.1. In the dry season, the weight of R(h) increases to 0.3 and the weight of R(w) decreases to 0.25.

[0010] As a further improvement of this application, the calculation formula of R(p) is as follows: R(p)=E*(1-a*C*Rd*Rm*T)+b*C*Ra*max(0,τ-T 修) , T 修 =T0*(1-0.2*M), E represents the basic risk of debris flow without plant cover, a and b are calibration coefficients, C is the plant coverage rate of the area to be tested, R d is the root density of plants in the area to be detected, R m is the average root depth of the area to be tested, T0 is the initial root tensile strength of the area to be tested, Ra is the lateral distribution radius of the roots in the area to be tested, τ is the debris flow shear stress, and M is the soil saturation.

[0011] As a further improvement of this application, the calculation formula of R(h) is as follows: R(h)=1- + ,in represents the efficiency coefficient of the t-th type of ground engineering, At represents the coverage of the t-th type of ground engineering, represents the risk gain factor of the jth type of underground engineering, represents the disturbance intensity of the jth type of underground engineering, is the above-ground impact factor.

[0012] As a further improvement of this application, the calculation formula of R(w) is as follows: R(w)=w1*R w2 +w3, where w1, w2 and w3 are empirical parameters and R is the drought index; R(g)=σtanϕ+D*(1-S), where σ is the effective normal stress, ϕ is the internal friction angle, D is the soil cohesion, and S is the looseness index; R(f)=K*(1+F / Fmax)*∇h, where K is the matrix permeability (m / s), F is the fracture density in m / m², Fmax is the maximum fracture density threshold, and ∇h is the hydraulic gradient.

[0013] As a further improvement of the present application, the early warning module includes an early warning signal sending unit and a guidance avoidance unit, wherein the early warning signal sending unit is used to send an early warning prompt signal when the early warning risk level exceeds the safety threshold, and the guidance avoidance unit sends an escape avoidance path at the same time as sending the early warning prompt signal based on the simulated disaster path and speed.

[0014] As another improvement of the present application, the risk dynamic correction unit is used to perform dynamic correction when the previous warning signal was issued but no disaster occurred. When the warning risk level in the preliminary analysis unit does not exceed the safety threshold during the current warning monitoring, but the previous warning feature has not yet returned to zero, there is a potential superimposed threat. The calculation formula is as follows: R t修 =R t α*R t−1 + ; R t The risk value obtained by preliminary analysis and calculation at the current moment; R t修 is the revised comprehensive risk value at the current moment; α: time decay coefficient, α=e −λΔt , λ is the decay rate, Δt is the time interval; β i: The weight of the i-th main control factor, satisfying ∑β i =1); f(x i ): Normalized contribution function of the i-th main control factor f(x i )=(x i -L i ) / (U i -L i ), U i and L i are the lower and upper thresholds, respectively.

[0015] As another improved supplement of the present application, the monitoring module further includes a human activity correction unit, whose working steps are as follows: S1, the distance L between the above-ground buildings on the disaster path and the disaster site; S2. Calculate whether the energy carried by the debris flow will cause damage to the above-ground buildings when the disaster reaches the coordinates of the above-ground buildings; S3. If no damage is caused, is a positive value, otherwise Multiply by (-1).

[0016] As another improvement supplement of this application, the impact resistance of the above-ground building in S2 is N=ζ*(fc*Aw / Ek)*e -k*L , where ζ is the structural type correction coefficient, fc is the compressive strength of the main structure of the building, Aw is obtained through the BIM database or material testing, Aw is the effective shear area of the building's frontal surface, Ek is the kinetic energy of the debris flow disaster, L is the horizontal distance between the building and the starting point of the debris flow, and k is the terrain attenuation coefficient.

[0017] To summarize, the system includes a monitoring module for collecting data on precipitation, vegetation development, soil moisture content, ground fissure development, and human activities; an early warning module for sending alarms and escape routes; and a simulation module for predicting disaster routes. Vegetation monitoring not only considers the soil-fixing effect, but also introduces the root damage effect; human activity monitoring is divided into above-ground engineering and underground engineering. The dynamic correction unit solves the impact of the residual risk of historical warnings on the current assessment through time attenuation and the superposition of main control factors. The system innovatively integrates the two-way influence of engineering effectiveness and natural factors, and introduces building impact resistance assessment, which significantly improves the accuracy of early warnings and is particularly suitable for progressive disaster prediction in areas with intensive engineering activities. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 This is a schematic diagram of the system composition of the first embodiment of the present application; Figure 2 This is a schematic diagram of the working steps of the human activity correction unit of the first embodiment of the present application; Figure 3 This is a schematic diagram of the first embodiment of the present application showing that when the roots of plants are caught in a debris flow, the looseness of the soil surface increases. DETAILED DESCRIPTION

[0019] Two implementation modes of the present application are described in detail below with reference to the accompanying drawings.

[0020] The first implementation method: Figure 1 A geological disaster monitoring and early warning system is shown, which includes a monitoring module, a history storage module, an analysis and judgment module, an early warning module, and a simulation module. The analysis and judgment module is used to collect data from the monitoring module to analyze the early warning level and notify the early warning level through the early warning module. The history storage module is used to store the monitoring data of the monitoring module. The simulation module is used to simulate the path and speed of debris flow disasters. The monitoring module is used to collect environmental parameters of the monitored warning area, including precipitation monitoring unit, vegetation monitoring unit, soil mobility monitoring unit, ground crack monitoring unit and human activity monitoring unit. The vegetation monitoring unit is used to monitor the vegetation type, distribution area and season corresponding to the monitoring time point in the monitored area. The analysis and judgment module includes a preliminary analysis unit and a risk dynamic correction unit. The preliminary analysis unit is used to perform a preliminary analysis of the warning level based on the data collected by the monitoring module, and the risk dynamic correction unit dynamically corrects the warning risk based on the previous warning. The human activity monitoring unit includes an above-ground engineering monitoring unit and an underground engineering monitoring unit. The above-ground engineering monitoring unit is used to monitor the types and distribution areas of buildings on the surface of the monitored warning area, and the underground engineering monitoring unit is used to monitor the types and distribution areas of underground construction projects in the monitored area.

[0021] Specifically, in this application, the analysis and judgment module is used to calculate the disaster warning risk level of the monitored area that may be caused by the environmental parameters collected by the monitoring module, and the monitoring module will monitor the precipitation, soil fluidity, ground cracks, vegetation and human activities in the monitored area accordingly, so as to carry out corresponding disaster warning monitoring.

[0022] The calculation formula for the preliminary analysis unit is as follows: R=R(p)*0.2+R(w)*0.4+R(g)*0.15+R(f)*0.1+R(h)*0.15, where R(p) is the risk coefficient corresponding to the vegetation monitoring unit, R(w) is the risk coefficient corresponding to the precipitation monitoring unit, R(g) is the risk coefficient corresponding to the soil mobility monitoring unit, R(f) is the risk coefficient corresponding to the ground fissure monitoring unit, and R(h) is the risk coefficient corresponding to the human activity monitoring unit. In the rainy season, the weight of R(w) increases to 0.5 and the weight of R(p) decreases to 0.1. In the dry season, the weight of R(h) increases to 0.3 and the weight of R(w) decreases to 0.25.

[0023] The calculation formula of R(p) is as follows: R(p)=E*(1-a*C*Rd*Rm*T)+b*C*Ra*max(0,τ-T 修) , T 修 =T0*(1-0.2*M), E represents the basic risk of debris flow without plant cover, a and b are calibration coefficients, C is the plant coverage rate of the area to be tested, R d is the root density of plants in the area to be detected, R m is the average root depth of the area to be tested, T0 is the initial root tensile strength of the area to be tested, Ra is the lateral distribution radius of the roots in the area to be tested, τ is the debris flow shear stress, and M is the soil saturation.

[0024] Specifically, in the existing technology, vegetation plays a positive role in weakening the early warning disaster of mudslides (because the soil-fixing effect of plants can reduce the fluidity of the soil, thereby reducing the effect of mudslides). However, in actual practice, some plants are deep-rooted plants or bamboo plants. When they grow, their root systems spread over a wide range and will increase the looseness of the soil surface. When plants with developed root systems are followed by muds and rocks, the soil will be further loosened due to the pulling of the roots, thereby increasing the degree of harm caused by mudslides (because the underground stems reproduce rapidly, forming a dense root network, destroying the original consolidation state of the soil; when deep-rooted plants accelerate their growth in spring, the roots extend to all sides, squeezing the soil structure, especially in clay or soft strata, which can easily cause ground cracks; when bamboo shoots break out of the ground in spring, they grow very fast (some varieties can grow tens of centimeters a day), and their strong growth force will push the soil open, causing the ground to bulge and crack) (such as Figure 3 shown).

[0025] Based on the above explanation, the root system of the plant needs to be taken into consideration. When a debris flow or landslide disaster occurs, the loose soil area caused by the growth of the plant and the loose soil area caused by the root arrangement area when the plant is entrained and pulled out will both increase the degree of entrainment when the debris flow passes. Therefore, R (p) is designed to adjust the accuracy of the debris flow warning risk analysis.

[0026] The calculation formula of R(h) is as follows: R(h)=1- + ,in represents the efficiency coefficient of the t-th type of ground engineering, At represents the coverage of the t-th type of ground engineering, represents the risk gain factor of the jth type of underground engineering, represents the disturbance intensity of the jth type of underground engineering, is the above-ground impact factor.

[0027] Specifically, different types of above-ground buildings have different above-ground engineering efficiency coefficients and underground engineering risk gain factors. For example, η=0.2 in drainage ditches, η=0.15 in platforms, γ=0.3 in mines, and γ=0.25 in tunnels. The values are adjusted according to different types. Therefore, underground buildings will increase the risk of surface debris flows. Above-ground buildings can play a certain role in intercepting or diverting debris flows when they arrive (for example, drainage ditches will play a partial diversion role), thereby weakening the effect.

[0028] The calculation formula of R(w) is as follows: R(w)=w1*R w2 +w3, where w1, w2 and w3 are empirical parameters and R is the drought index; R(g)=σtanϕ+D*(1-S), where σ is the effective normal stress, ϕ is the internal friction angle, D is the soil cohesion, and S is the looseness index; R(f)=K*(1+F / Fmax)*∇h, where K is the matrix permeability (m / s), F is the fracture density in m / m², Fmax is the maximum fracture density threshold, and ∇h is the hydraulic gradient.

[0029] The early warning module includes an early warning signal sending unit and a guidance avoidance unit. The early warning signal sending unit is used to send an early warning prompt signal when the early warning risk level exceeds the safety threshold. The guidance avoidance unit sends an escape avoidance path at the same time as sending the early warning prompt signal based on the simulated disaster occurrence path and speed.

[0030] Specifically, the signal sending unit and the guidance avoidance unit can assist the early warning module in issuing effective early warning signals and corresponding escape routes.

[0031] Figure 2 As shown, the monitoring module also includes a human activity correction unit, whose working steps are as follows: S1, the distance L between the above-ground buildings on the disaster path and the disaster site; S2. Calculate whether the energy carried by the debris flow will cause damage to the above-ground buildings when the disaster reaches the coordinates of the above-ground buildings; S3. If no damage is caused, is a positive value, otherwise Multiply by (-1).

[0032] The impact resistance of the above-ground buildings in S2 is N=ζ*(fc*Aw / Ek)*e -k*L , where ζ is the structural type correction coefficient, fc is the compressive strength of the main structure of the building, Aw is obtained through the BIM database or material testing, Aw is the effective shear area of the building's frontal surface, Ek is the kinetic energy of the debris flow disaster, L is the horizontal distance between the building and the starting point of the debris flow, and k is the terrain attenuation coefficient.

[0033] Specifically, when a building is under construction (not yet completed) or the building is completed but not large in size, the N at the location of the building is not enough to resist the impact potential energy of the debris flow. The building will be destroyed by the subsequent debris flow and then swept into the debris flow, causing the debris flow to grow stronger and thus increase the harmfulness of the debris flow. Therefore, it needs to be a positive value at this time, increasing the value of R (h) (including during the immediate construction period, materials piled on the surface will also be swept into the subsequent debris flow, thereby increasing the risk level of debris flow warning).

[0034] The second implementation method: Figure 2 The risk dynamic correction unit is used to perform dynamic correction when the last warning signal was issued but no disaster occurred. During the current warning monitoring, the warning risk level in the preliminary analysis unit does not exceed the safety threshold, but the last warning feature has not returned to zero, and there is a potential superimposed threat. The calculation formula is as follows: R t修 =R t α*R t−1 + ; R t The risk value obtained by preliminary analysis and calculation at the current moment; R t修 is the revised comprehensive risk value at the current moment; α: time decay coefficient, α=e −λΔt , λ is the decay rate, Δt is the time interval; β i : The weight of the i-th main control factor, satisfying ∑βi =1); f(x i ): Normalized contribution function of the i-th main control factor f(x i )=(x i -L i ) / (U i -L i ), U i and L i are the lower and upper thresholds, respectively.

[0035] Unlike the first embodiment, in the first embodiment, the calculation of the debris flow warning risk is usually an independent single calculation, but in the actual process, the warning signal was issued in the previous round of warning analysis but no disaster actually occurred, but there is still a high possibility of debris flow disasters in the monitored area. If the next round of risk monitoring is in an independent risk monitoring operation, it will be affected by the residual threat of the previous warning (which has not yet been metabolized and decayed to a safe state). Even if the calculated risk level is lower than the safety threshold, there is still a possibility that the disaster warning exceeds the safety threshold.

[0036] Specifically, based on the fact that the previous round of disaster warning exceeded the safety threshold, if in the next round of disaster monitoring, some factors (such as rainfall intensity) are lower than the safety threshold, and other factors have the same values as in the previous round of monitoring, because the potential degree of disaster in the previous round was higher, the superimposed influencing factors at this time (for example, rainfall intensity, which would turn the originally precarious disaster threat from the previous round into reality) would also cause the potential occurrence of disasters.

[0037] Therefore, the design includes attenuation calculation and main control factors to avoid the continued impact of historical false alarms through time attenuation, and can adapt to different geological backgrounds, thereby improving the accuracy of disaster warnings.

[0038] In summary, accurate early warning is achieved through the collaboration of multiple modules. The system includes a monitoring module that collects data on precipitation, vegetation, soil, ground cracks and human activities, an analysis and judgment module that includes preliminary analysis and dynamic correction units, an early warning module for sending alarms and escape routes, and a simulation module for predicting disaster paths. Among them, vegetation monitoring not only takes into account the soil-fixing effect, but also introduces the root damage effect (deep-rooted plants may aggravate soil loosening); human activity monitoring distinguishes between above-ground projects (such as the risk of weakening drainage ditches) and underground projects (such as the increased risk of mines); the dynamic correction unit solves the impact of residual risks from historical warnings on current assessments through time attenuation and the superposition of main control factors. The system innovatively integrates the two-way influence of engineering effectiveness and natural factors, and introduces building impact resistance assessment, which significantly improves the accuracy of early warnings. It is particularly suitable for progressive disaster prediction in areas with intensive engineering activities.

[0039] In view of current actual needs, the protection scope of the above-mentioned implementation mode adopted in this application is not limited to this. Various changes made within the knowledge scope of technical personnel in this field without departing from the concept of this application still fall within the protection scope of the present invention.

Claims

1. A geological disaster monitoring and early warning system, characterized by: It includes a monitoring module, a history storage module, an analysis and judgment module, an early warning module and a simulation module. The analysis and judgment module is used to collect data from the monitoring module to analyze the early warning level and notify the early warning level through the early warning module. The history storage module is used to store the monitoring data of the monitoring module. The simulation module is used to simulate the path and speed of debris flow disasters. The monitoring module is used to collect environmental parameters of the monitored warning area, including a precipitation monitoring unit, a vegetation monitoring unit, a soil mobility monitoring unit, a ground crack monitoring unit and a human activity monitoring unit. The vegetation monitoring unit is used to monitor the vegetation type, distribution area and season corresponding to the monitoring time point in the monitored area; The analysis and judgment module includes a preliminary analysis unit and a risk dynamic correction unit, wherein the preliminary analysis unit is used to perform a preliminary analysis of the warning level based on the data collected by the monitoring module, and the risk dynamic correction unit dynamically corrects the warning risk based on the previous warning. The human activity monitoring unit includes an above-ground engineering monitoring unit and an underground engineering monitoring unit, wherein the above-ground engineering monitoring unit is used to monitor the types and distribution areas of buildings on the surface of the monitored warning area, and the underground engineering monitoring unit is used to monitor the types and distribution areas of underground construction projects in the monitored area.

2. A geological disaster monitoring and early warning system according to claim 1, characterized in that: The calculation formula of the preliminary analysis unit is as follows: R=R(p)*0.2+R(w)*0.4+R(g)*0.15+R(f)*0.1+R(h)*0.15, where R(p) is the risk coefficient corresponding to the vegetation monitoring unit, R(w) is the risk coefficient corresponding to the precipitation monitoring unit, R(g) is the risk coefficient corresponding to the soil mobility monitoring unit, R(f) is the risk coefficient corresponding to the ground fissure monitoring unit, and R(h) is the risk coefficient corresponding to the human activity monitoring unit. In the rainy season, the weight of R(w) increases to 0.5 and the weight of R(p) decreases to 0.

1. In the dry season, the weight of R(h) increases to 0.3 and the weight of R(w) decreases to 0.

25.

3. A geological disaster monitoring and early warning system according to claim 2, characterized in that: The calculation formula of R(p) is as follows: R(p)=E*(1-a*C*Rd*Rm*T)+b*C*Ra*max(0,τ-T 修) , T 修 =T0*(1-0.2*M), E represents the basic risk of debris flow without plant cover, a and b are calibration coefficients, C is the plant coverage rate of the area to be tested, R d is the root density of plants in the area to be detected, R m is the average root depth of the area to be tested, T0 is the initial root tensile strength of the area to be tested, Ra is the lateral distribution radius of the roots in the area to be tested, τ is the debris flow shear stress, and M is the soil saturation.

4. A geological disaster monitoring and early warning system according to claim 2, characterized in that: The calculation formula of R (h) is as follows: R(h)=1- + ,in represents the efficiency coefficient of the t-th type of ground engineering, At represents the coverage of the t-th type of ground engineering, represents the risk gain factor of the jth type of underground engineering, represents the disturbance intensity of the jth type of underground engineering, is the above-ground impact factor.

5. A geological disaster monitoring and early warning system according to claim 2, characterized in that: The calculation formula of R(w) is as follows: R(w)=w1*R w2 +w3, where w1, w2 and w3 are empirical parameters and R is the drought index; R(g)=σtanϕ+D*(1-S), where σ is the effective normal stress, ϕ is the internal friction angle, D is the soil cohesion, and S is the looseness index; R(f)=K*(1+F / Fmax)*∇h, where K is the matrix permeability (m / s), F is the fracture density in m / m², Fmax is the maximum fracture density threshold, and ∇h is the hydraulic gradient.

6. A geological disaster monitoring and early warning system according to claim 4, characterized in that: The early warning module includes an early warning signal sending unit and a guidance avoidance unit, wherein the early warning signal sending unit is used to send an early warning prompt signal when the early warning risk level exceeds a safety threshold, and the guidance avoidance unit sends an escape avoidance path at the same time as sending the early warning prompt signal based on the simulated disaster occurrence path and speed.

7. A geological disaster monitoring and early warning system according to claim 6, characterized in that: The risk dynamic correction unit is used to perform dynamic correction when the last warning signal was issued but no disaster occurred. During the current warning monitoring, the warning risk level in the preliminary analysis unit does not exceed the safety threshold, but the last warning feature has not yet returned to zero, and there is a potential superimposed threat. The calculation formula is as follows: R t修 =R t a*R t−1 + ; R t The risk value obtained by preliminary analysis and calculation at the current moment; R t修 is the revised comprehensive risk value at the current moment; α: time decay coefficient, α=e −λΔt , λ is the decay rate, Δt is the time interval; β i : The weight of the i-th main control factor, satisfying ∑β i =1); f(x i ): Normalized contribution function of the i-th main control factor f(x i )=(x i -L i ) / (U i -L i ), U i and L i are the lower and upper thresholds, respectively.

8. A geological disaster monitoring and early warning system according to claim 6, characterized in that: The monitoring module also includes a human activity correction unit, which works as follows: S1, the distance L between the above-ground buildings on the disaster path and the disaster site; S2. Calculate whether the energy carried by the debris flow will cause damage to the above-ground buildings when the disaster reaches the coordinates of the above-ground buildings; S3. If no damage is caused, is a positive value, otherwise Multiply by (-1).

9. A geological disaster monitoring and early warning system according to claim 8, characterized in that: The impact resistance of the above-ground buildings in S2 is N=ζ*(fc*Aw / Ek)*e -k*L , where ζ is the structural type correction coefficient, fc is the compressive strength of the main structure of the building, Aw is obtained through the BIM database or material testing, Aw is the effective shear area of the building's frontal surface, Ek is the kinetic energy of the debris flow disaster, L is the horizontal distance between the building and the starting point of the debris flow, and k is the terrain attenuation coefficient.

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