A typhoon-induced geological disaster monitoring and early warning method based on multi-factor scenarios

Abstract

The present invention relates to the field of geological disaster early warning, and discloses a typhoon-induced geological disaster monitoring and early warning method based on a multi-factor scenario, comprising the following steps: S100, collecting multi-factor data related to typhoons in various regions; S200, spatially analyzing the collected multi-factor data to determine potential high-risk areas for geological disasters; S300, combining historical geological disaster data and real-time monitoring data, using data fusion technology to construct a risk assessment model for typhoon-induced geological disasters; S400, based on the results of the risk assessment model, issuing geological disaster early warning information through wireless communication technology. The present invention can more comprehensively assess the impact of typhoons on the geological environment by comprehensively collecting and analyzing multiple typhoon-related factor data, thereby significantly improving the accuracy of geological disaster early warnings.

Description

Technical Field

[0001] The present invention relates to the field of geological disaster early warning, and in particular to a typhoon-induced geological disaster monitoring and early warning method based on a multi-factor scenario. Background Art

[0002] Typhoons are one of the natural disasters that affect China and the rest of the world every year. The intensity and path of typhoons have a significant impact on the occurrence and development of geological disasters.

[0003] Geological disaster monitoring and early warning are of great significance for protecting the lives and property of the people. According to statistics, there are about 280,000 geological disaster monitoring points in the country, of which more than 16,000 are in Zhejiang Province. The existing geological disaster monitoring and early warning has gradually changed from relying on the masses without professional knowledge to relying on professional technicians and professional monitoring equipment, and from mainly manual monitoring and data collection to mainly automated monitoring and data collection. However, after the data is transmitted to the system, data management and analysis face a series of challenges.

[0004] On the one hand, due to the large number of monitoring equipment and data, and the remote installation location, it is difficult to send people to the site for 24-hour review. If there is no professional on-site inspection, it is not easy to determine whether the landslide body is deformed and harmful, which can easily lead to untimely disaster warning. On the other hand, some typhoon-induced geological disaster monitoring methods are mainly based on single factors, such as rainfall, wind speed, ground humidity, etc. However, these methods have certain limitations in the reliability and real-time prediction of typhoon-induced geological disasters. As the intensity of typhoons and the complexity of their paths increase, single-factor monitoring methods are difficult to meet the needs of typhoon-induced geological disaster monitoring and early warning.

[0005] Therefore, it is particularly important to develop a typhoon-induced geological disaster monitoring and early warning method based on multi-factor scenarios. Summary of the invention

[0006] The purpose of the present invention is to provide a typhoon-induced geological disaster monitoring and early warning method based on a multi-factor scenario to solve the technical problem that as the intensity and path complexity of typhoons increase, a single-factor monitoring method is difficult to meet the monitoring and early warning needs of typhoon-induced geological disasters.

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

[0008] A typhoon-induced geological disaster monitoring and early warning method based on multi-factor scenarios includes the following steps:

[0009] S100. Collect multi-factor data related to typhoons in various regions, including but not limited to rainfall, wind speed, topography, soil type, vegetation cover, groundwater level, surface temperature and humidity;

[0010] S200, spatially analyze the collected multi-factor data to identify potential high-risk areas for geological disasters;

[0011] S300, combining historical geological disaster data and real-time monitoring data, using data fusion technology to build a risk assessment model for typhoon-induced geological disasters;

[0012] S400. Based on the results of the risk assessment model, geological disaster warning information is issued through wireless communication technology.

[0013] As a further technical solution, the S200 includes:

[0014] S201, preprocessing the collected data, including data cleaning, format conversion, and coordinate system one;

[0015] S202, using GIS software to establish a spatial database, and importing the pre-processed data into the spatial database;

[0016] S203. Statistical analysis is performed on the factor data to calculate the frequency and intensity in the current area, and the disaster-causing coefficient of each factor is obtained, which is expressed as follows: ,in, is the total area of ​​the current region, is the total number of target areas contained in the current region, is the number of target regions where the current feature exists, The target area where the current feature exists;

[0017] S204. Based on the disaster-causing coefficient of each element calculated in the current area, the formula is: Calculate the geological disaster risk index of the current area ,in, is the total number of elements, For the The disaster coefficient of each factor, For the The weight coefficient corresponding to each element, For the Regions;

[0018] S205. Calculate the geological disaster risk index The preset geological disaster risk threshold interval To compare; if , then it is judged that the risk of geological disasters in the current area is high; if , then it is judged that the current area is at risk of geological disasters; if , then it is judged that the risk of geological disasters in the current area is low;

[0019] S205. Mark the areas judged to have high risk of geological disasters and identify them as potential high-risk areas for geological disasters.

[0020] As a further technical solution, the method for constructing a risk assessment model for typhoon-induced geological disasters is:

[0021] S301. Based on the historical geological disaster data of each target area, obtain the disaster index of each target area ;

[0022] S302, based on the disaster index and disaster risk factor Combined with the above, the disaster risk coefficient of each target area is calculated. ;

[0023] S303. Based on the population density, GDP, road density, and land use type of each target area, analyze and obtain the disaster vulnerability coefficient of each target area. ;

[0024] S304, based on the disaster risk factor and disaster vulnerability coefficient Construct a risk assessment model for typhoon-induced geological disasters; the expression is: , ;

[0025] in, is the preset weight coefficient, is the preset scale factor, is the reference value of the disaster risk factor, is the reference value of the disaster vulnerability coefficient, For the The risk assessment value of the target area, It is the overall risk assessment value of the current area.

[0026] As a further technical solution, the disaster index of each target area for:

[0027]

[0028]

[0029] like ,but ;otherwise ; The target area included in the current region is The number of typhoons affected;

[0030] in, For the The level of the typhoon, For the The minimum distance between the center of the target area affected by the typhoon and the center of the typhoon. , is the impact factor, is the exponential coefficient, It is the total number of times the current target area is affected by typhoons.

[0031] As a further technical solution, the disaster risk coefficient ; ; is the judgment function, when hour, ,otherwise ;

[0032] in, For the detection period, For the current moment, is the starting time, For the detection period The curve of the disaster coefficient of each factor changing with time, is the reference coefficient, As the reference change curve, is the reference value of the disaster index, is the coefficient of variation, is the reference value of the coefficient of deviation.

[0033] As a further technical solution, the method for risk assessment of the current area is:

[0034] Get the overall risk assessment value of the current area And with the overall risk assessment threshold range To compare:

[0035] like , then the overall risk of the current region is judged to be at a medium level;

[0036] like , then the overall risk of the current region is judged to be at a high level;

[0037] like , then the overall risk of the current region is judged to be at a low level.

[0038] As a further technical solution, according to the results of the risk assessment model, the steps of issuing geological disaster warning information through wireless communication technology are as follows:

[0039] If the overall risk in the current area is judged to be low and it is not a potential high-risk area for geological disasters, no geological disaster warning will be issued;

[0040] When the overall risk in the current area is judged to be low and it is a potential high-risk area for geological disasters, a blue geological disaster warning will be issued;

[0041] When the overall risk in the current area is judged to be at a medium level and it is not a potential high-risk area for geological disasters, a purple geological disaster warning will be issued;

[0042] When the overall risk in the current area is judged to be at a medium level and it is a potential high-risk area for geological disasters, a yellow geological disaster warning message will be issued;

[0043] When it is judged that the overall risk in the current area is at a high level and it is not a potential high-risk area for geological disasters, an orange geological disaster warning is issued;

[0044] When it is judged that the overall risk in the current area is at a high level and it is a potential high-risk area for geological disasters, a red geological disaster warning is issued.

[0045] As a further technical solution, the order of the levels of geological disaster warning from high to low is red>orange>yellow>purple>blue.

[0046] Beneficial effects of the present invention:

[0047] (1) The present invention can more comprehensively assess the impact of typhoons on the geological environment by comprehensively collecting and analyzing multiple typhoon-related factor data, including but not limited to rainfall, wind speed, topography, soil type, vegetation coverage, groundwater level, surface temperature and humidity, etc., thereby significantly improving the accuracy of geological disaster warnings. This multi-factor comprehensive analysis method can better reflect the complexity and diversity of geological disasters than single-factor analysis; and by using spatial analysis technology to determine potential high-risk areas for geological disasters, accurate warnings can be issued for specific areas, effectively reducing false alarms and missed alarms, which not only helps to reasonably allocate rescue resources, but also improves the public's trust in warning information and response efficiency;

[0048] (2) The risk assessment model constructed by the present invention, which combines historical geological disaster data and real-time monitoring data and adopts data fusion technology, can update the geological disaster risk status in real time and ensure the timeliness and effectiveness of early warning information, which is of great significance for reducing casualties and property losses caused by geological disasters. At the same time, the geological disaster early warning information is released through wireless communication technology, which can ensure that the early warning information is quickly transmitted to the residents and relevant departments in the threatened areas, providing them with sufficient time to take preventive measures or emergency evacuation, thereby effectively improving the emergency response capability and disaster response efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] The present invention will be further described below in conjunction with the accompanying drawings.

[0050] Figure 1 It is a diagram of the method steps of the present invention. DETAILED DESCRIPTION

[0051] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0052] See also Figure 1 As shown, the present invention is a typhoon-induced geological disaster monitoring and early warning method based on a multi-factor scenario, comprising the following steps:

[0053] S100. Collect multi-factor data related to typhoons in various regions, including but not limited to rainfall, wind speed, topography, soil type, vegetation cover, groundwater level, surface temperature and humidity;

[0054] S200, spatially analyze the collected multi-factor data to identify potential high-risk areas for geological disasters;

[0055] S300, combining historical geological disaster data and real-time monitoring data, using data fusion technology to build a risk assessment model for typhoon-induced geological disasters;

[0056] S400. Based on the results of the risk assessment model, geological disaster warning information is issued through wireless communication technology.

[0057] The S200 includes:

[0058] S201, preprocessing the collected data, including data cleaning, format conversion, and coordinate system one;

[0059] S202, using GIS software to establish a spatial database, and importing the pre-processed data into the spatial database;

[0060] S203. Statistical analysis is performed on the factor data to calculate the frequency and intensity in the current area, and the disaster-causing coefficient of each factor is obtained, which is expressed as follows: ,in, is the total area of ​​the current region, is the total number of target areas contained in the current region, is the number of target regions where the current feature exists, The target area where the current feature exists;

[0061] S204. Based on the disaster-causing coefficient of each element calculated in the current area, the formula is: Calculate the geological disaster risk index of the current area ,in, is the total number of elements, For the The disaster coefficient of each factor, For the The weight coefficient corresponding to each element, For the Regions;

[0062] S205. Calculate the geological disaster risk index The preset geological disaster risk threshold interval To compare; if , then it is judged that the risk of geological disasters in the current area is high; if , then it is judged that the current area is at risk of geological disasters; if , then it is judged that the risk of geological disasters in the current area is low;

[0063] S205. Mark the areas judged to have high risk of geological disasters and identify them as potential high-risk areas for geological disasters.

[0064] In this embodiment, by comprehensively collecting and analyzing multiple typhoon-related factor data, including but not limited to rainfall, wind speed, topography, soil type, vegetation coverage, groundwater level, surface temperature and humidity, etc., it is possible to more comprehensively evaluate the impact of typhoons on the geological environment, thereby significantly improving the accuracy of geological disaster warning. This multi-factor comprehensive analysis method can better reflect the complexity and diversity of geological disasters than single-factor analysis; the collected data is then preprocessed, including data cleaning, format conversion, and coordinate system one, and a spatial database is established using GIS software, and the preprocessed data is imported into the spatial database; then, the factor data is statistically analyzed, the frequency and intensity in the current area are calculated, and the disaster-causing coefficient of each factor is obtained, which is expressed as: , the above formula can be used to obtain the disaster coefficient of each factor in each region. The larger the disaster coefficient, the higher the frequency of geological disasters under given factor conditions, that is, the factor has a strong correlation with the occurrence of geological disasters; on the contrary, the smaller the disaster coefficient, the weaker the relationship between the factor and the geological disaster, and the lower the possibility of geological disasters. Then through the formula: Calculate the geological disaster risk index of the current area Obviously, by calculating the disaster coefficient of each element in the current area through cumulative summation, it can comprehensively reflect the geological disaster risk in the current area, and provide data support for the subsequent targeted monitoring of which element and the issuance of the danger warning of the element;

[0065] Finally, the obtained geological disaster risk index will be calculated Compare with the preset geological disaster risk threshold interval to divide the areas with high geological disaster risk, mark for subsequent early warning and key monitoring, and determine the potential high-risk areas of geological disasters through spatial analysis technology. The present invention can accurately warn specific areas and effectively reduce false alarms and missed alarms, which not only helps to reasonably allocate rescue resources, but also improves the public's trust in early warning information and response efficiency;

[0066] At the same time, combining historical geological disaster data and real-time monitoring data, the risk assessment model constructed using data fusion technology can update the geological disaster risk status in real time, ensuring the timeliness and effectiveness of early warning information, which is of great significance for reducing casualties and property losses caused by geological disasters; at the same time, issuing geological disaster early warning information through wireless communication technology can ensure that the early warning information is quickly transmitted to residents and relevant departments in the threatened areas, providing them with sufficient time to take preventive measures or emergency evacuation, thereby effectively improving emergency response capabilities and disaster response efficiency.

[0067] The method for constructing a risk assessment model for typhoon-induced geological disasters is:

[0068] S301. Based on the historical geological disaster data of each target area, obtain the disaster index of each target area ;

[0069] S302, based on the disaster index and disaster risk factor Combined with the above, the disaster risk coefficient of each target area is calculated. ;

[0070] S303. Based on the population density, GDP, road density, and land use type of each target area, analyze and obtain the disaster vulnerability coefficient of each target area. ;

[0071] S304, based on the disaster risk factor and disaster vulnerability coefficient Construct a risk assessment model for typhoon-induced geological disasters; the expression is: , ;

[0072] in, is the preset weight coefficient, is the preset scale factor, is the reference value of the disaster risk factor, is the reference value of the disaster vulnerability coefficient, For the The risk assessment value of the target area, It is the overall risk assessment value of the current area.

[0073] Disaster index for each target area for:

[0074]

[0075]

[0076] like ,but ;otherwise ; The target area included in the current region is The number of typhoons affected;

[0077] in, For the The level of the typhoon, For the The minimum distance between the center of the target area affected by the typhoon and the center of the typhoon. , is the impact factor, is the exponential coefficient, It is the total number of times the current target area is affected by typhoons.

[0078] The disaster risk factor ; ; is the judgment function, when hour, ,otherwise ;

[0079] in, For the detection period, For the current moment, is the starting time, For the detection period The curve of the disaster coefficient of each factor changing with time, is the reference coefficient, As the reference change curve, is the reference value of the disaster index, is the coefficient of variation, is the reference value of the coefficient of deviation.

[0080] In this embodiment, a method for constructing a risk assessment model for typhoon-induced geological disasters is provided. Specifically, detailed records of typhoon-induced geological disasters that have occurred in the past are first collected, including the type of disaster, time of occurrence, location, impact range, and loss situation. The data is then cleaned and sorted to remove duplicate, erroneous or invalid data. The disaster index of each target area is then calculated using a formula. , the specific expression is: ; From the above formula, it can be seen that the higher the current typhoon level, the more destructive it is to the current target area, and the greater the possibility of geological disasters. The disaster index of the current target area is The larger the distance, the smaller the minimum distance from the typhoon center. , it means that the greater the impact of the typhoon, the greater the possibility of geological disasters. The disaster index of the current target area is The larger the index is, the greater the impact of the current typhoon on the entire region. The exponential coefficient is calculated. Obviously, the larger the exponential coefficient is, the greater the impact on the target area is. Through the above process, the comprehensive typhoon level and the minimum distance from the typhoon center are achieved, while considering the impact of the current typhoon on the entire region, so as to establish a more accurate disaster index assessment model.

[0081] At the same time, based on the population density, GDP, road density, and land use type of each target area, the disaster vulnerability coefficient of each target area is analyzed and obtained. ;

[0082] The specific method is to input the population density, GDP, road density, and land use type data of each target area into the pre-trained composite neural network model of recurrent neural network and convolutional neural network, and output the disaster vulnerability coefficient. ; The establishment and training process of the above-mentioned composite neural network model are existing mature technologies and will not be elaborated here;

[0083] Then, according to the disaster risk factor and disaster vulnerability coefficient Construct a risk assessment model for typhoon-induced geological disasters; the expression is: and According to the above formula, the disaster risk coefficient of each target area is and disaster vulnerability coefficient The larger the value is, the higher the overall geological disaster risk in the area. Therefore, it is more necessary to conduct overall early warning and monitoring of the area to prevent potential geological disasters brought by typhoons to the current area. The above process is based on the disaster risk coefficient. By combining the impact of the typhoon itself, which is reflected by the risk factor, and the ability of the target area to withstand the impact of the typhoon, which is reflected by the disaster vulnerability coefficient, we can establish a more accurate risk assessment model for typhoon-induced geological disasters and improve the accuracy of geological disaster warnings.

[0084] The method for conducting risk assessment for the current area is:

[0085] Get the overall risk assessment value of the current area And with the overall risk assessment threshold range Row comparison:

[0086] like , then the overall risk of the current region is judged to be at a medium level;

[0087] like , then the overall risk of the current region is judged to be at a high level;

[0088] like , then the overall risk of the current region is judged to be at a low level.

[0089] According to the results of the risk assessment model, the steps for issuing geological disaster warning information through wireless communication technology are as follows:

[0090] If the overall risk in the current area is judged to be low and it is not a potential high-risk area for geological disasters, no geological disaster warning will be issued;

[0091] When the overall risk in the current area is judged to be low and it is a potential high-risk area for geological disasters, a blue geological disaster warning will be issued;

[0092] When the overall risk in the current area is judged to be at a medium level and it is not a potential high-risk area for geological disasters, a purple geological disaster warning will be issued;

[0093] When the overall risk in the current area is judged to be at a medium level and it is a potential high-risk area for geological disasters, a yellow geological disaster warning message will be issued;

[0094] When it is judged that the overall risk in the current area is at a high level and it is not a potential high-risk area for geological disasters, an orange geological disaster warning is issued;

[0095] When the overall risk in the current area is judged to be high and it is a potential high-risk area for geological disasters, a red geological disaster warning will be issued; the levels of geological disaster warnings are in the order of red > orange > yellow > purple > blue from high to low.

[0096] It should be noted that the calculation formulas and various parameters involved in the calculation in the present invention have been dimensionally processed in advance, and the process of dimensionless processing is well known in the industry and will not be described here.

[0097] The above is a detailed description of an embodiment of the present invention, but the content is only a preferred embodiment of the present invention and cannot be considered to limit the scope of implementation of the present invention. All equivalent changes and improvements made within the scope of the present invention should still fall within the scope of the patent coverage of the present invention.

Claims

1. A typhoon-induced geological disaster monitoring and early warning method based on multi-factor scenarios, characterized in that: The steps include: S100. Collect multi-factor data related to typhoons in various regions, including but not limited to rainfall, wind speed, topography, soil type, vegetation cover, groundwater level, surface temperature and humidity; S200, spatially analyze the collected multi-factor data to identify potential high-risk areas for geological disasters; S300, combining historical geological disaster data and real-time monitoring data, using data fusion technology to build a risk assessment model for typhoon-induced geological disasters; S400, issuing geological disaster warning information through wireless communication technology according to the results of the risk assessment model; The S200 includes: S201, preprocessing the collected data, including data cleaning, format conversion, and coordinate system one; S202, using GIS software to establish a spatial database, and importing the pre-processed data into the spatial database; S203. Statistical analysis is performed on the factor data to calculate the frequency and intensity in the current area, and the disaster-causing coefficient of each factor is obtained, which is expressed as follows: ,in, is the total area of ​​the current region, is the total number of target areas contained in the current region, is the number of target regions where the current feature exists, The target area where the current feature exists; S204. Based on the disaster-causing coefficient of each element calculated in the current area, the formula is: Calculate the geological disaster risk index of the current area ,in, is the total number of elements, For the The disaster coefficient of each factor, For the The weight coefficient corresponding to each element, For the Regions; S205. Calculate the geological disaster risk index The preset geological disaster risk threshold interval To compare; if , then it is judged that the risk of geological disasters in the current area is high; if , then it is judged that the current area is at risk of geological disasters; if , then it is judged that the risk of geological disasters in the current area is low; S205, marking the areas judged to have high risk of geological disasters and determining them as potential high-risk areas for geological disasters; The method for constructing a risk assessment model for typhoon-induced geological disasters is: S301. Based on the historical geological disaster data of each target area, obtain the disaster index of each target area ; S302, based on the disaster index and disaster risk factor Combined with the above, the disaster risk coefficient of each target area is calculated. ; S303. Based on the population density, GDP, road density, and land use type of each target area, analyze and obtain the disaster vulnerability coefficient of each target area. ; S304, based on the disaster risk factor and disaster vulnerability coefficient Construct a risk assessment model for typhoon-induced geological disasters; the expression is , ; in, , is the preset weight coefficient, , is the preset scale factor, is the reference value of the disaster risk factor, is the reference value of the disaster vulnerability coefficient, For the The risk assessment value of the target area, is the overall risk assessment value of the current area; Disaster severity index for each target area for: ； ； like ,but ;otherwise ; The target area included in the current region is The number of typhoons affected; in, For the The level of the typhoon, For the The minimum distance between the center of the target area affected by the typhoon and the center of the typhoon. , is the impact factor, is the exponential coefficient, is the total number of times the current target area is affected by typhoons; The disaster risk factor ; ; is the judgment function, when hour, ,otherwise ; in, For the detection period, For the current moment, is the starting time, For the detection period The curve of the disaster coefficient of each factor changing with time, is the reference coefficient, As the reference change curve, is the reference value of the disaster index, is the coefficient of variation, is the reference value of the coefficient of deviation.

2. The typhoon-induced geological disaster monitoring and early warning method based on multi-factor scenarios according to claim 1 is characterized in that: The method for conducting risk assessment for the current area is: Get the overall risk assessment value of the current area And with the overall risk assessment threshold range To compare: like , then the overall risk of the current region is judged to be at a medium level; like , then the overall risk of the current region is judged to be at a high level; like , then the overall risk of the current region is judged to be at a low level.

3. The typhoon-induced geological disaster monitoring and early warning method based on multi-factor scenarios according to claim 2 is characterized in that: According to the results of the risk assessment model, the steps for issuing geological disaster warning information through wireless communication technology are as follows: If the overall risk in the current area is judged to be low and it is not a potential high-risk area for geological disasters, no geological disaster warning will be issued; When the overall risk in the current area is judged to be low and it is a potential high-risk area for geological disasters, a blue geological disaster warning will be issued; When the overall risk in the current area is judged to be at a medium level and it is not a potential high-risk area for geological disasters, a purple geological disaster warning will be issued; When the overall risk in the current area is judged to be at a medium level and it is a potential high-risk area for geological disasters, a yellow geological disaster warning message will be issued; When it is judged that the overall risk in the current area is at a high level and it is not a potential high-risk area for geological disasters, an orange geological disaster warning is issued; When it is judged that the overall risk in the current area is at a high level and it is a potential high-risk area for geological disasters, a red geological disaster warning is issued.

4. The typhoon-induced geological disaster monitoring and early warning method based on multi-factor scenarios according to claim 3 is characterized in that: The order of the geological disaster warning levels from high to low is red > orange > yellow > purple > blue.

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