An intelligent regional landslide monitoring and management method

Abstract

The present invention belongs to the field of landslide monitoring and relates to data processing technology. It is used to solve the problem that existing landslide monitoring and management methods are unable to perform distribution analysis on landslide risk areas. Specifically, it is an intelligent regional landslide monitoring and management method, comprising the following steps: performing regional landslide monitoring and analysis on a monitoring area, setting a plurality of horizontal monitoring points, shift monitoring points and anti-slip monitoring points in the monitoring area, dividing the monitoring area into a plurality of sub-areas and calculating monitoring coefficients of the sub-areas, and judging whether the landslide monitoring results of the sub-areas are qualified by using the monitoring coefficients of the sub-areas; the present invention can perform regional landslide monitoring and analysis on the monitoring area through a regional monitoring module, and can monitor horizontal displacement, shift wall displacement and anti-slip rod displacement respectively through horizontal monitoring points, shift monitoring points and anti-slip monitoring points, thereby performing comprehensive analysis and processing on various displacement parameters to obtain monitoring coefficients.

Description

Technical Field

[0001] The invention belongs to the field of landslide monitoring, relates to data processing technology, and specifically is an intelligent regional landslide monitoring and management method. Background Art

[0002] Landslide monitoring falls under the discipline of natural disaster prevention and control. Key monitoring areas include: the development of various cracks in different parts of a slope; rock and soil relaxation, localized collapse, and subsidence and uplift; various underground and surface deformations and displacements; groundwater levels, volumes, and hydrochemical characteristics; tree leaning and building deformation; external environmental changes such as rainfall and earthquakes; and abnormal animal activity. These efforts generate relevant data and information, providing a basis for landslide prediction and disaster prevention.

[0003] Existing landslide monitoring and management methods can only observe and analyze various landslide precursor phenomena through landslide parameters and record various work in the landslide formation process; however, they lack the function of distributing and analyzing landslide risk areas, and thus cannot formulate targeted control plans based on the distribution characteristics of risk areas, resulting in low efficiency of landslide monitoring and control.

[0004] In response to the above technical problems, this application proposes a solution. Summary of the Invention

[0005] The purpose of the present invention is to provide an intelligent regional landslide monitoring and management method to solve the problem that existing landslide monitoring and management methods are unable to perform distribution analysis on landslide risk areas;

[0006] The technical problem to be solved by the present invention is: how to provide an intelligent regional landslide monitoring and management method that can perform distribution analysis on landslide risk areas.

[0007] The purpose of the present invention can be achieved through the following technical solutions:

[0008] An intelligent regional landslide monitoring and management method comprises the following steps:

[0009] Step 1: Conduct regional landslide monitoring analysis in the monitoring area: Set up several horizontal monitoring points, gear monitoring points, and anti-slip monitoring points in the monitoring area, divide the monitoring area into several sub-areas, and calculate the monitoring coefficients of the sub-areas. Use the monitoring coefficients of the sub-areas to determine whether the landslide monitoring results of the sub-areas are qualified;

[0010] Step 2: Monitor and analyze the overall landslide risk in the monitoring area: mark the ratio of the number of dangerous areas to the number of sub-areas as the hazard coefficient, establish a monitoring set based on the monitoring coefficients of all sub-areas, calculate the variance of the monitoring set to obtain the fluctuation coefficient, and determine whether the overall landslide risk in the monitoring area meets the requirements based on the numerical values of the hazard coefficient and the fluctuation coefficient;

[0011] Step 3: Obtain the center point position of the monitoring area and the center point position of all dangerous areas and mark them as monitoring points and dangerous points respectively, perform distribution simulation analysis on the dangerous points and obtain the dangerous characteristics of the monitoring area.

[0012] As a preferred embodiment of the present invention, in step one, the process of obtaining the monitoring coefficient of the sub-area includes: monitoring the horizontal displacement of the landslide at the horizontal monitoring point and obtaining the water displacement value, monitoring the displacement of the retaining wall at the shift monitoring point and obtaining the wall displacement value, monitoring the displacement of the anti-slip rod at the anti-slip monitoring point and obtaining the rod displacement value, summing up and averaging the water displacement values of all horizontal monitoring points in the sub-area and marking them as water displacement data, summing up and averaging the wall displacement values of all shift monitoring points in the sub-area and obtaining the wall displacement data, summing up and averaging the rod displacement values of all shift monitoring points in the sub-area and obtaining the rod displacement data, and performing numerical calculation on the water displacement data, wall displacement data and rod displacement data to obtain the monitoring coefficient of the sub-area.

[0013] As a preferred embodiment of the present invention, in step one, the specific process of determining whether the landslide monitoring result of the sub-area meets the requirements includes: obtaining the monitoring threshold through the storage module, and comparing the monitoring coefficient with the monitoring threshold: if the monitoring coefficient is less than the monitoring threshold, the landslide monitoring result of the sub-area is determined to be qualified, and the corresponding sub-area is marked as a safe area; if the monitoring coefficient is greater than or equal to the monitoring threshold, the landslide monitoring result of the sub-area is determined to be unqualified, and the corresponding sub-area is marked as a dangerous area, and the location information of the dangerous area is sent to the monitoring management platform, and the monitoring management platform sends the received location information of the dangerous area to the feature analysis module and the mobile phone terminal of the manager.

[0014] As a preferred embodiment of the present invention, in step 2, the specific process of determining whether the overall landslide risk of the monitoring area meets the requirements includes: obtaining the danger threshold and the fluctuation threshold through the storage module, and comparing the danger coefficient and the fluctuation coefficient with the danger threshold and the fluctuation threshold respectively: if the danger coefficient is less than the danger threshold, it is determined that the overall landslide risk of the monitoring area meets the requirements, and the overall monitoring module sends an overall qualified signal to the monitoring management platform; if the danger coefficient is greater than or equal to the danger threshold and the fluctuation coefficient is greater than or equal to the fluctuation threshold, it is determined that the overall landslide risk of the monitoring area does not meet the requirements and the risk factor is external force damage, and the overall monitoring module sends an external force damage signal to the monitoring management platform; if the danger coefficient is greater than or equal to the danger threshold and the fluctuation coefficient is less than the fluctuation threshold, it is determined that the overall landslide risk of the monitoring area does not meet the requirements and the risk factor is natural impact, and the overall monitoring module sends a natural impact signal to the monitoring management platform; after receiving the external force damage signal or the natural impact signal, the monitoring management platform generates a feature analysis signal and sends it to the feature analysis module.

[0015] As a preferred embodiment of the present invention, in step three, the process of obtaining the angle data JD of the dangerous point includes: connecting the dangerous point with the monitoring point in sequence to obtain several dangerous line segments, marking the dangerous line segment with the smallest length value as the standard line segment, and marking the angle value of the angle formed by the dangerous line segment and the standard line segment as angle data; the length data CD of the dangerous point is the length value of the dangerous line segment.

[0016] As a preferred embodiment of the present invention, in step three, the specific process of performing distribution simulation analysis on dangerous points includes: establishing a rectangular coordinate system with angle data JD as the X-axis and length data CD as the Y-axis, dividing the first quadrant in the rectangular coordinate system into several analysis panels, obtaining the number of dangerous points in the analysis panel and marking them as dangerous values, obtaining the dangerous threshold through the storage module, marking the analysis panel with a dangerous value not less than the dangerous threshold as a dangerous panel, connecting the center points of the dangerous panels in order from left to right and from bottom to top to obtain several associated line segments, obtaining the associated threshold through the storage module, comparing the length value of the associated line segment with the associated threshold, and marking the dangerous features of the monitoring area through the comparison results.

[0017] As a preferred embodiment of the present invention, in step three, the specific process of comparing the length value of the associated line segment with the associated threshold includes: if the length value of the associated line segment is less than the associated threshold, it is determined that the danger panels at both ends of the associated line segment have associated features, and the danger areas corresponding to the danger points in the danger panels with associated features are marked as associated areas; if the length value of the associated line segment is greater than or equal to the associated threshold, it is determined that the danger panels at both ends of the associated line segment do not have associated features; if the number of associated areas is zero, the danger features of the monitoring area are marked as dispersed, and the feature analysis module sends a dispersed governance signal to the monitoring management platform, which sends the dispersed governance signal to the mobile phone terminal of the manager after receiving the dispersed governance signal; if the number of associated areas is not zero, the danger features of the monitoring area are marked as concentrated, and the feature analysis module sends a concentrated governance signal to the monitoring management platform, which sends the concentrated governance signal to the mobile phone terminal of the manager after receiving the concentrated governance signal.

[0018] As a preferred embodiment of the present invention, it is applied to an intelligent regional landslide monitoring and management system, comprising a monitoring and management platform, wherein the monitoring and management platform is communicatively connected to a regional monitoring module, an overall monitoring module, a feature analysis module, and a storage module;

[0019] The regional monitoring module is used to perform regional landslide monitoring and analysis and send the location information of the dangerous area to the monitoring management platform when the monitoring result of the sub-area is unqualified. The monitoring management platform sends the received location information of the dangerous area to the feature analysis module;

[0020] The overall monitoring module is used to monitor and analyze the overall landslide risk in the monitoring area and send a feature analysis signal to the feature analysis module through the monitoring management platform when the overall landslide risk in the monitoring area does not meet the requirements;

[0021] The feature analysis module is used to perform governance feature analysis on the monitoring area and mark the dangerous features of the monitoring area after receiving the feature analysis signal, and send the dangerous features of the monitoring area to the mobile phone terminal of the manager through the monitoring management platform.

[0022] The present invention has the following beneficial effects:

[0023] 1. The regional monitoring module can be used to conduct regional landslide monitoring and analysis in the monitoring area. Horizontal displacement, retaining wall displacement, and anti-slide bar displacement can be monitored through horizontal monitoring points, retaining wall monitoring points, and anti-slide monitoring points, respectively. A comprehensive analysis of various displacement parameters is then performed to obtain a monitoring coefficient. The value of the monitoring coefficient provides intuitive feedback on the landslide risk in the sub-area, allowing for timely early warning and protection of dangerous areas with landslide risks.

[0024] 2. The overall monitoring module can monitor and analyze the overall landslide risk in the monitoring area. The overall landslide risk can be fed back through the proportion of dangerous areas in the monitoring area and the distribution of monitoring coefficients in sub-areas. In this way, feedback can be given when the overall landslide risk does not meet the requirements. At the same time, the risk factors of the landslide risk can be marked, which makes it easier for managers to formulate corresponding treatment plans based on the risk factors and improve the efficiency of landslide monitoring and treatment.

[0025] 3. The feature analysis module can be used to analyze the management characteristics of the monitoring area. The dangerous features of the monitoring area can be marked by extracting the geographical location of the dangerous area and performing distribution simulation analysis. In this way, targeted management plans can be formulated by combining the dangerous features with risk factors to further improve the efficiency of landslide monitoring and management. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0027] Figure 1 This is a system block diagram of Embodiment 1 of the present invention;

[0028] Figure 2 This is a flow chart of the method of embodiment 2 of the present invention. DETAILED DESCRIPTION

[0029] The technical solutions of the present invention will be clearly and completely described below with reference to the embodiments. Obviously, the embodiments described are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making any creative efforts shall fall within the scope of protection of the present invention.

[0030] Example 1

[0031] like Figure 1 As shown, an intelligent regional landslide monitoring and management system includes a monitoring and management platform, which is communicatively connected to a regional monitoring module, an overall monitoring module, a feature analysis module, and a storage module.

[0032] The regional monitoring module is used for regional landslide monitoring and analysis: a number of horizontal monitoring points, gear monitoring points and anti-slip monitoring points are set up in the monitoring area, and the horizontal displacement of the landslide is monitored at the horizontal monitoring points to obtain the water displacement value. The displacement monitoring can be carried out by a laser rangefinder. The laser rangefinder is an instrument that uses a certain parameter of the modulated laser to accurately measure the distance to the target. The pulsed laser rangefinder emits a beam or a series of short pulsed laser beams to the target when working. The photoelectric element receives the laser beam reflected by the target, and the timer measures the time from the laser beam emission to the reception, and calculates the distance from the rangefinder to the target; in the gear monitoring module, the timer measures the time from the laser beam emission to the reception, and calculates the distance from the rangefinder to the target. The displacement of the retaining wall is monitored at the position monitoring point and the wall displacement value is obtained. The displacement of the anti-slip rod is monitored at the anti-slip monitoring point and the rod displacement value is obtained. The monitoring area is divided into several sub-areas, and the water displacement values of all horizontal monitoring points in the sub-area are summed and averaged to be marked as water displacement data SY. The wall displacement values of all the shift monitoring points in the sub-area are summed and averaged to obtain wall displacement data QY. The rod displacement values of all the shift monitoring points in the sub-area are summed and averaged to obtain rod displacement data GY. The monitoring coefficient JC of the sub-area is obtained by the formula JC=α1*SY+α2*QY+α3*GY. The monitoring coefficient is a function that reflects the displacement of the shifting position. The value of the landslide risk level in the sub-area, the larger the value of the monitoring coefficient, the higher the landslide risk level in the sub-area; α1, α2 and α3 are all proportional coefficients, and α1>α2>α3>1; the monitoring threshold JCmax is obtained through the storage module, and the monitoring coefficient JC is compared with the monitoring threshold JCmax: if the monitoring coefficient JC is less than the monitoring threshold JCmax, the landslide monitoring result of the sub-area is determined to be qualified, and the corresponding sub-area is marked as a safe area; if the monitoring coefficient JC is greater than or equal to the monitoring threshold JCmax, the landslide monitoring result of the sub-area is determined to be unqualified, and the corresponding sub-area is marked as a safe area. The area is marked as a dangerous area, and the location information of the dangerous area is sent to the monitoring management platform. The monitoring management platform sends the received location information of the dangerous area to the feature analysis module and the mobile terminal of the manager; regional landslide monitoring and analysis is carried out on the monitoring area. The horizontal displacement, retaining wall displacement and anti-slip rod displacement can be monitored respectively through the horizontal monitoring points, retaining monitoring points and anti-slip monitoring points, so as to obtain the monitoring coefficient by comprehensively analyzing and processing the various displacement parameters. The landslide risk of the sub-area is intuitively fed back through the value of the monitoring coefficient, and early warning and protection are carried out in time for dangerous areas with landslide risks.

[0033] The overall monitoring module is used to monitor and analyze the overall landslide risk of the monitoring area: the ratio of the number of dangerous areas to the number of sub-areas is marked as the danger coefficient, a monitoring set is established for the monitoring coefficients of all sub-areas, the variance of the monitoring set is calculated to obtain the fluctuation coefficient, the danger threshold and the fluctuation threshold are obtained through the storage module, and the danger coefficient and the fluctuation coefficient are compared with the danger threshold and the fluctuation threshold respectively: if the danger coefficient is less than the danger threshold, it is determined that the overall landslide risk of the monitoring area meets the requirements, and the overall monitoring module sends an overall qualified signal to the monitoring management platform; if the danger coefficient is greater than or equal to the danger threshold and the fluctuation coefficient is greater than or equal to the fluctuation threshold, it is determined that the overall landslide risk of the monitoring area does not meet the requirements and the risk factor is external force damage, and the overall monitoring module sends a signal to the monitoring management platform. The platform sends an external force destruction signal; if the hazard coefficient is greater than or equal to the hazard threshold and the fluctuation coefficient is less than the fluctuation threshold, it is determined that the overall landslide risk in the monitoring area does not meet the requirements and the risk factor is natural impact, and the overall monitoring module sends a natural impact signal to the monitoring management platform; after receiving the external force destruction signal or the natural impact signal, the monitoring management platform generates a feature analysis signal and sends it to the feature analysis module; the overall landslide risk in the monitoring area is monitored and analyzed, and the overall landslide risk is fed back through the proportion of dangerous areas in the monitoring area and the distribution of monitoring coefficients in sub-areas, so as to provide feedback when the overall landslide risk does not meet the requirements, and at the same time mark the risk factors of the landslide risk, so that management personnel can formulate corresponding treatment plans based on risk factors and improve the efficiency of landslide monitoring and treatment.

[0034] The feature analysis module is used to perform governance feature analysis on the monitoring area after receiving the feature analysis signal: obtain the center point position of the monitoring area and the center point position of all dangerous areas and mark them as monitoring points and dangerous points respectively, obtain the angle data JD and length data CD of the dangerous point, and the acquisition process of the angle data JD of the dangerous point includes: connecting the dangerous points with the monitoring points in sequence to obtain several dangerous line segments, marking the dangerous line segment with the smallest length value as the standard line segment, and marking the angle value of the angle formed by the dangerous line segment and the standard line segment as angle data; the length data CD of the dangerous point is the length of the dangerous line segment. Length value; perform distribution simulation analysis on dangerous points: establish a rectangular coordinate system with angle data JD as X-axis and length data CD as Y-axis, divide the first quadrant in the rectangular coordinate system into several analysis panels, the analysis panel is a square with a side length of L1, obtain the number of dangerous points in the analysis panel and mark it as a dangerous value, obtain the dangerous threshold through the storage module, mark the analysis panel with a dangerous value not less than the dangerous threshold as a dangerous panel, connect the center points of the dangerous panel in the order from left to right and from bottom to top and obtain several associated line segments, obtain the associated threshold through the storage module, The length of the associated line segment is compared with the associated threshold: if the length of the associated line segment is less than the associated threshold, it is determined that the danger panels at both ends of the associated line segment have associated features, and the danger areas corresponding to the danger points in the danger panels with associated features are marked as associated areas; if the length of the associated line segment is greater than or equal to the associated threshold, it is determined that the danger panels at both ends of the associated line segment do not have associated features; if the number of associated areas is zero, the danger features of the monitored area are marked as dispersed, and the feature analysis module sends a dispersed governance signal to the monitoring and management platform. After receiving the dispersed governance signal, the monitoring and management platform sends the dispersed governance signal to the manager's mobile terminal; if the number of associated areas is not zero, the danger features of the monitored area are marked as concentrated, and the feature analysis module sends a concentrated governance signal to the monitoring and management platform. After receiving the concentrated governance signal, the monitoring and management platform sends the concentrated governance signal to the manager's mobile terminal; the governance features of the monitored area are analyzed, and the danger features of the monitored area are marked by extracting the geographical location of the danger area and performing distribution simulation analysis, so as to formulate targeted governance plans based on the hazard features and risk factors, and further improve the efficiency of landslide monitoring and governance.

[0035] Example 2

[0036] like Figure 2 As shown, an intelligent regional landslide monitoring and management method includes the following steps:

[0037] Step 1: Conduct regional landslide monitoring and analysis in the monitoring area: Set up several horizontal monitoring points, retaining wall monitoring points, and anti-slip monitoring points in the monitoring area. These monitoring points can monitor horizontal displacement, retaining wall displacement, and anti-slip bar displacement, respectively. Divide the monitoring area into several sub-areas and calculate the monitoring coefficients for each sub-area. The values of the monitoring coefficients provide intuitive feedback on the landslide risk of each sub-area.

[0038] Step 2: Monitor and analyze the overall landslide risk in the monitoring area: mark the ratio of the number of dangerous areas to the number of sub-areas as the hazard coefficient, establish a monitoring set based on the monitoring coefficients of all sub-areas, calculate the variance of the monitoring set to obtain the fluctuation coefficient, and determine whether the overall landslide risk in the monitoring area meets the requirements based on the values of the hazard coefficient and the fluctuation coefficient. Mark the risk factors of the landslide risk to facilitate management personnel to formulate corresponding control plans based on the risk factors.

[0039] Step 3: Obtain the center point location of the monitoring area and the center point location of all dangerous areas and mark them as monitoring points and dangerous points respectively. Perform distribution simulation analysis on the dangerous points and obtain the dangerous characteristics of the monitoring area; formulate targeted control plans based on the dangerous characteristics and risk factors to further improve the efficiency of landslide monitoring and control.

[0040] An intelligent regional landslide monitoring and management method performs regional landslide monitoring and analysis on the monitoring area during operation: a number of horizontal monitoring points, gear monitoring points, and anti-slip monitoring points are set in the monitoring area, and various displacement parameters are comprehensively analyzed and processed to obtain monitoring coefficients. The landslide risk of the sub-area is intuitively fed back through the numerical value of the monitoring coefficient; the overall landslide risk of the monitoring area is monitored and analyzed: the ratio of the number of dangerous areas to the number of sub-areas is marked as a dangerous coefficient, a monitoring set is established for the monitoring coefficients of all sub-areas, and the variance of the monitoring set is calculated to obtain a fluctuation coefficient. Whether the overall landslide risk of the monitoring area meets the requirements is determined by the numerical values of the dangerous coefficient and the fluctuation coefficient, and the risk factors of the landslide risk are marked to facilitate management personnel to formulate corresponding control plans based on the risk factors, thereby improving the efficiency of landslide monitoring and control; the center point position of the monitoring area and the center point positions of all dangerous areas are obtained and marked as monitoring points and dangerous points respectively, distribution simulation analysis is performed on the dangerous points to obtain the dangerous characteristics of the monitoring area; and targeted control plans are formulated in combination with the dangerous characteristics and risk factors to further improve the efficiency of landslide monitoring and control.

[0041] The above content is merely an example and explanation of the structure of the present invention. Those skilled in the art may make various modifications or additions to the described specific embodiments or replace them in a similar manner. As long as they do not deviate from the structure of the invention or exceed the scope defined by the claims, they should all fall within the scope of protection of the present invention.

[0042] The above formulas are all obtained by collecting a large amount of data and performing software simulation to obtain a formula close to the actual value. The coefficients in the formula are set by those skilled in the art based on actual conditions; for example: formula JC = α1*SY + α2*QY + α3*GY; those skilled in the art collect multiple groups of sample data and set corresponding monitoring coefficients for each group of sample data; the set monitoring coefficients and the collected sample data are substituted into the formula, and any three formulas form a system of three linear equations. The calculated coefficients are screened and averaged, and the values of α1, α2, and α3 are obtained as 5.38, 3.47, and 2.64, respectively;

[0043] The size of the coefficient is to quantify each parameter to obtain a specific numerical value, which is convenient for subsequent comparison. The size of the coefficient depends on the amount of sample data and the preliminary setting of the corresponding monitoring coefficient for each set of sample data by technical personnel in this field; as long as it does not affect the proportional relationship between the parameter and the quantified value, such as the monitoring coefficient is proportional to the value of the water transfer data.

[0044] Throughout this specification, references to terms such as "one embodiment," "example," or "specific example" indicate that the specific features, structures, materials, or characteristics described in conjunction with that embodiment or example are included in at least one embodiment or example of the present invention. In this specification, schematic representations of these terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.

[0045] The preferred embodiments of the present invention disclosed above are intended only to help illustrate the present invention. These preferred embodiments do not exhaustively describe all details, nor do they limit the present invention to specific embodiments. Obviously, many modifications and variations are possible based on the contents of this specification. These embodiments are selected and described in detail in this specification to better explain the principles and practical applications of the present invention, thereby enabling those skilled in the art to better understand and utilize the present invention. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. An intelligent regional landslide monitoring and management method, characterized in that: The following steps are involved: Step 1: Conduct regional landslide monitoring analysis in the monitoring area: Set up several horizontal monitoring points, gear monitoring points, and anti-slip monitoring points in the monitoring area, divide the monitoring area into several sub-areas, and calculate the monitoring coefficients of the sub-areas. Use the monitoring coefficients of the sub-areas to determine whether the landslide monitoring results of the sub-areas are qualified; The acquisition process of the monitoring coefficient of the sub-area includes: monitoring the horizontal displacement of the landslide at the horizontal monitoring point and obtaining the water displacement value, summing and averaging the water displacement values of all horizontal monitoring points in the sub-area and marking them as water displacement data SY, monitoring the displacement of the retaining wall at the gear monitoring point and obtaining the wall displacement value, summing and averaging the wall displacement values of all gear monitoring points in the sub-area and obtaining the wall displacement data QY, monitoring the displacement of the anti-slip rod at the anti-slip monitoring point and obtaining the rod displacement value, summing and averaging the rod displacement values of all gear monitoring points in the sub-area and obtaining the rod displacement data GY, and calculating the displacement data GY by the formula The monitoring coefficient JC of the sub-region is obtained. The monitoring coefficient is a value that reflects the landslide risk level in the sub-region. The larger the value of the monitoring coefficient, the higher the landslide risk level in the sub-region. α1, α2, and α3 are all proportional coefficients, and α1>α2>α3>1; Step 2: Compare the monitoring coefficient with the monitoring threshold: If the monitoring coefficient is greater than or equal to the monitoring threshold, the landslide monitoring result of the sub-region is judged to be unqualified, and the corresponding sub-region is marked as a dangerous area; Monitor and analyze the overall landslide risk in the monitoring area: mark the ratio of the number of dangerous areas to the number of sub-areas as the hazard coefficient, establish a monitoring set based on the monitoring coefficients of all sub-areas, calculate the variance of the monitoring set to obtain the fluctuation coefficient, and determine whether the overall landslide risk in the monitoring area meets the requirements based on the values of the hazard coefficient and the fluctuation coefficient; Step 3: Get the center point position of the monitoring area and the center point position of all dangerous areas and mark them as monitoring points and dangerous points respectively, get the angle data JD and length data CD of the dangerous points, the process of getting the angle data JD of the dangerous points includes: connecting the dangerous points with the monitoring points in turn to get several dangerous line segments, marking the dangerous line segment with the smallest length value as the standard line segment, marking the angle value of the angle formed by the dangerous line segment and the standard line segment as the angle data; the length data CD of the dangerous point is the length value of the dangerous line segment; perform distribution simulation analysis on the dangerous points: establish a rectangular coordinate system with the angle data JD as the X-axis and the length data CD as the Y-axis, divide the first quadrant in the rectangular coordinate system into several analysis panels, the analysis panel is a square with a side length of L1, get the number of dangerous points in the analysis panel and mark it as a dangerous value, get the dangerous threshold value through the storage module, mark the analysis panel with a dangerous value not less than the dangerous threshold value as a dangerous panel, and arrange the center points of the dangerous panels in order from left to right and from bottom to top. Connect the lines in sequence and obtain several associated line segments, obtain the associated threshold through the storage module, and compare the length value of the associated line segment with the associated threshold: if the length value of the associated line segment is less than the associated threshold, it is determined that the danger panels at both ends of the associated line segment have associated features, and the danger areas corresponding to the danger points in the danger panels with associated features are marked as associated areas; if the length value of the associated line segment is greater than or equal to the associated threshold, it is determined that the danger panels at both ends of the associated line segment do not have associated features; if the number of associated areas is zero, the danger features of the monitoring area are marked as dispersed, and the feature analysis module sends a dispersed governance signal to the monitoring management platform. After receiving the dispersed governance signal, the monitoring management platform sends the dispersed governance signal to the mobile phone terminal of the manager; if the number of associated areas is not zero, the danger features of the monitoring area are marked as concentrated, and the feature analysis module sends a concentrated governance signal to the monitoring management platform. After receiving the concentrated governance signal, the monitoring management platform sends the concentrated governance signal to the mobile phone terminal of the manager.

2. An intelligent regional landslide monitoring and management method according to claim 1, characterized in that: In step one, the specific process of determining whether the landslide monitoring result of the sub-area meets the requirements includes: obtaining the monitoring threshold through the storage module, and comparing the monitoring coefficient with the monitoring threshold: if the monitoring coefficient is less than the monitoring threshold, the landslide monitoring result of the sub-area is determined to be qualified, and the corresponding sub-area is marked as a safe area; if the monitoring coefficient is greater than or equal to the monitoring threshold, the landslide monitoring result of the sub-area is determined to be unqualified, and the corresponding sub-area is marked as a dangerous area, and the location information of the dangerous area is sent to the monitoring management platform, and the monitoring management platform sends the received location information of the dangerous area to the feature analysis module and the mobile phone terminal of the manager.

3. The intelligent regional landslide monitoring and management method according to claim 1 is characterized in that: In step 2, the specific process of determining whether the overall landslide risk of the monitoring area meets the requirements includes: obtaining the danger threshold and the fluctuation threshold through the storage module, and comparing the danger coefficient and the fluctuation coefficient with the danger threshold and the fluctuation threshold respectively: if the danger coefficient is less than the danger threshold, it is determined that the overall landslide risk of the monitoring area meets the requirements, and the overall monitoring module sends an overall qualified signal to the monitoring management platform; if the danger coefficient is greater than or equal to the danger threshold and the fluctuation coefficient is greater than or equal to the fluctuation threshold, it is determined that the overall landslide risk of the monitoring area does not meet the requirements and the risk factor is external force damage, and the overall monitoring module sends an external force damage signal to the monitoring management platform; if the danger coefficient is greater than or equal to the danger threshold and the fluctuation coefficient is less than the fluctuation threshold, it is determined that the overall landslide risk of the monitoring area does not meet the requirements and the risk factor is natural impact, and the overall monitoring module sends a natural impact signal to the monitoring management platform; after receiving the external force damage signal or the natural impact signal, the monitoring management platform generates a feature analysis signal and sends it to the feature analysis module.

4. The intelligent regional landslide monitoring and management method according to claim 1 is characterized in that: The system is applied to an intelligent regional landslide monitoring and management system, comprising a monitoring and management platform, wherein the monitoring and management platform is communicatively connected to a regional monitoring module, an overall monitoring module, a feature analysis module, and a storage module; The regional monitoring module is used to perform regional landslide monitoring and analysis and send the location information of the dangerous area to the monitoring management platform when the monitoring result of the sub-area is unqualified. The monitoring management platform sends the received location information of the dangerous area to the feature analysis module; The overall monitoring module is used to monitor and analyze the overall landslide risk in the monitoring area and send a feature analysis signal to the feature analysis module through the monitoring management platform when the overall landslide risk in the monitoring area does not meet the requirements; The feature analysis module is used to perform governance feature analysis on the monitoring area and mark the dangerous features of the monitoring area after receiving the feature analysis signal, and send the dangerous features of the monitoring area to the mobile phone terminal of the manager through the monitoring management platform.

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