Geological disaster risk evaluation method, device, equipment, medium and product

Abstract

The invention discloses a geological disaster risk evaluation method, device and equipment, a medium and a product, and relates to the field of geological disaster evaluation, and the method comprises the steps: obtaining a historical optical remote sensing image time sequence, historical InSAR data and a historical geological disaster risk evaluation result of a to-be-researched region, the historical optical remote sensing image time sequence comprises a plurality of optical remote sensing images, and determining a geological disaster activity evaluation result by adopting an activity joint evaluation function based on the historical optical remote sensing image time sequence and historical InSAR data; based on each optical remote sensing image, determining a change intensity evaluation result of the geological disaster-bearing body by adopting a change intensity evaluation function; and based on the geological disaster activity evaluation result, the geological disaster-bearing body change intensity and the historical geological disaster risk evaluation result, determining a dynamic geological disaster risk evaluation result by adopting a geological disaster joint dynamic evaluation function. According to the invention, the accuracy of the geological disaster risk evaluation result is improved, and the geological disaster investigation cost is reduced.

Description

Technical Field

[0001] The present application relates to the field of geological disaster assessment, and particularly to a method, device, equipment, medium and product for geological disaster risk assessment. Background Art

[0002] Geological disaster risk assessment refers to the quantitative value of the probability and severity of the adverse impact of geological disasters on life, health, property or the environment, and is the basis of geological disaster risk management.

[0003] Although various geological disaster risk assessment methods emerge in an endless stream, from the perspective of the assessment method, the selected factors are static and will not change once assigned values; from the perspective of time, the assessment results only represent the static characteristics of geological disasters at the moment of assessment. However, the environment where geological disasters occur is always in a state of change, especially in a relatively long period of time, and the possibility of change is very high. Traditional assessment methods do not consider the dynamic change situation. Therefore, there is a problem of low assessment accuracy in the assessment methods of geological disasters in the related art.

[0004] In the areas where geological disasters have been investigated, geological disasters still occur every year. After several years, there is a question about whether these assessment results are still valid, and how to use these assessment results is also a difficult problem. Each round of investigation will cost a huge amount of manpower and material resources, and it is not realistic to achieve high-frequency round investigations. Therefore, how to reasonably reuse these previous investigation results is also a problem that needs to be solved. Summary of the Invention

[0005] The purpose of the present application is to provide a method, device, equipment, medium and product for geological disaster risk assessment, which considers the dynamic change situation of geological disasters and the previous assessment results, improves the accuracy of geological disaster risk assessment results, and reduces the cost of geological disaster investigation.

[0006] To achieve the above purpose, the present application provides the following solutions:

[0007] In the first aspect, the present application provides a method for geological disaster risk assessment, including:

[0008] Obtaining a time series of historical optical remote sensing images, historical InSAR data and historical geological disaster risk assessment results of the area to be studied, where the time series of historical optical remote sensing images includes multiple optical remote sensing images;

[0009] Based on the time series of historical optical remote sensing images and historical InSAR data, using a joint evaluation function for the activity of geological disasters to determine the activity evaluation result of geological disasters in the area to be studied; wherein, the activity evaluation result of geological disasters includes strong activity, medium activity and weak activity;

[0010] Based on each of the optical remote sensing images, the change intensity evaluation function of geological disaster-affected bodies is used to determine the evaluation result of the change intensity of geological disaster-affected bodies in the area to be studied; among them, the evaluation result of the change intensity of geological disaster-affected bodies includes strong deformation evaluation result, general deformation evaluation result and weak deformation evaluation result;

[0011] Based on the evaluation result of the geological disaster activity in the area to be studied, the change intensity of the geological disaster-affected bodies and the evaluation result of the historical geological disaster risk, the joint dynamic evaluation function of geological disasters is used to determine the dynamic geological disaster risk evaluation result of the area to be studied; among them, the dynamic geological disaster risk evaluation result includes extremely high risk, high risk, medium risk and low risk.

[0012] Further, the joint dynamic evaluation function of geological disasters is:

[0013]

[0014] The joint evaluation function of the geological disaster activity is:

[0015] K g =K L *K N ;

[0016] The change intensity evaluation function of the geological disaster-affected bodies is:

[0017] K v =[S G W] T ;

[0018] wherein, R n is the dynamic geological disaster risk evaluation result, R o is the historical geological disaster risk evaluation result, K g is the geological disaster activity evaluation result, K v is the change intensity evaluation result of the geological disaster-affected bodies, K L is the long-term change feature evaluation result, K N is the short-term surface deformation evaluation result, S is the strong deformation evaluation result, G is the general deformation evaluation result, W is the weak deformation evaluation result, and T is the transpose of the matrix.

[0019] Further, the joint evaluation function of the geological disaster activity includes a long-term change feature evaluation function and a short-term surface deformation evaluation function;

[0020] Based on the time series of the historical optical remote sensing images and the historical InSAR data, the joint evaluation function of the geological disaster activity is used to determine the evaluation result of the geological disaster activity in the area to be studied, including:

[0021] Extract the earliest geological disaster outline area and the latest geological disaster outline area of the area to be studied from the historical optical remote sensing image time series;

[0022] Based on the earliest geological disaster outline area and the latest geological disaster outline area, use the long-term change feature evaluation function to determine the long-term change feature evaluation result of the area to be studied; among them, the long-term change feature evaluation result includes the long-term active area and the non-long-term active area;

[0023] Obtain the surface deformation rate map of the area to be studied according to the historical InSAR data;

[0024] Based on the surface deformation rate map, use the short-term surface deformation evaluation function to determine the short-term surface deformation evaluation result of the area to be studied; among them, the short-term surface deformation evaluation result includes the surface strong deformation area, the surface medium deformation area, the surface weak deformation area and the surface non-deformation area;

[0025] Based on the long-term change feature evaluation result and the short-term surface deformation evaluation result, use the joint evaluation function of geological disaster activity to determine the geological disaster activity evaluation result of the area to be studied.

[0026] Further, based on each of the optical remote sensing images, use the change intensity evaluation function of geological disaster disaster-bearing bodies to determine the change intensity evaluation result of geological disaster disaster-bearing bodies in the area to be studied, including:

[0027] Extract the patches of geological disaster disaster-bearing bodies from each of the optical remote sensing images to obtain the time series of geological disaster disaster-bearing body patches;

[0028] Calculate the phased annual change rate of area according to two adjacent geological disaster disaster-bearing body patches in the time series of geological disaster disaster-bearing body patches;

[0029] Calculate the full-cycle average annual change rate of area according to the earliest geological disaster disaster-bearing body patch and the latest geological disaster disaster-bearing body patch in the time series of geological disaster disaster-bearing body patches; where the full cycle is the entire time from the start time to the end time of the time series of geological disaster disaster-bearing body patches;

[0030] Evaluate the change intensity of geological disaster disaster-bearing bodies according to the full-cycle average annual change rate and the phased annual change rate of area to obtain the change intensity evaluation result of geological disaster disaster-bearing bodies.

[0031] Further, calculating the phased annual change rate of area according to two adjacent geological disaster disaster-bearing body patches in the time series of geological disaster disaster-bearing body patches includes:

[0032] Evenly divide the geological disaster disaster-bearing body patches into multiple partition units;

[0033] Calculate the area increment of each partition unit according to the area of each partition unit in two adjacent geological disaster-affected body map patches.

[0034] Calculate the annual change rate of the phased area of each partition unit according to the area increment.

[0035] Furthermore, evaluate the change intensity of the geological disaster-affected body according to the annual average change rate of the full-cycle area and the annual change rate of the phased area, and obtain the evaluation result of the change intensity of the geological disaster-affected body, including:

[0036] Determine the degree of dispersion of the change rate of the geological disaster-affected body according to the annual change rate of the phased area and the annual average change rate of the full-cycle area of each partition unit.

[0037] Determine the mean value of the annual change rate of the area of each partition unit according to the annual change rate of the phased area of each partition unit.

[0038] Evaluate the change intensity of the geological disaster-affected body according to the degree of dispersion and the mean value, and obtain the evaluation result of the change intensity of the geological disaster-affected body.

[0039] In a second aspect, the present application provides a geological disaster risk assessment device, including:

[0040] An acquisition module for acquiring a time series of historical optical remote sensing images, historical InSAR data, and historical geological disaster risk assessment results of a region to be studied, where the time series of historical optical remote sensing images includes multiple optical remote sensing images;

[0041] An activity evaluation module for determining the geological disaster activity evaluation result of the region to be studied based on the time series of historical optical remote sensing images and historical InSAR data by using a joint activity evaluation function of geological disasters; wherein, the geological disaster activity evaluation result includes strong activity, medium activity, and weak activity;

[0042] A change intensity evaluation module for determining the geological disaster-affected body change intensity evaluation result of the region to be studied based on each of the optical remote sensing images by using a change intensity evaluation function of the geological disaster-affected body; wherein, the geological disaster-affected body change intensity evaluation result includes a strong deformation evaluation result, a general deformation evaluation result, and a weak deformation evaluation result;

[0043] A dynamic risk assessment module, which is used to determine the dynamic geological disaster risk assessment result of the area to be studied by using the joint dynamic assessment function of geological disasters based on the geological disaster activity assessment result of the area to be studied, the change intensity of geological disaster bearing bodies, and the historical geological disaster risk assessment result; the dynamic geological disaster risk assessment result includes extremely high risk, high risk, medium risk, and low risk.

[0044] In a third aspect, the present application provides a computer device, including: a memory, a processor, and a computer program stored on the memory and executable on the processor, where the processor executes the computer program to implement the above-mentioned geological disaster risk assessment method.

[0045] In a fourth aspect, the present application provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, it implements the above-mentioned geological disaster risk assessment method.

[0046] In a fifth aspect, the present application provides a computer program product, including a computer program, and when the computer program is executed by a processor, it implements the above-mentioned geological disaster risk assessment method.

[0047] According to the specific embodiments provided by the present application, the following technical effects are disclosed in the present application:

[0048] The present application provides a geological disaster risk assessment method, device, equipment, medium, and product. Based on the historical geological disaster risk assessment result, the joint dynamic assessment function of geological disasters is used to assess the geological disaster risk, so that the previous geological disaster risk assessment result can be reused, greatly reducing the investigation cost. At the same time, based on the historical optical remote sensing image time series and historical InSAR data, the activity joint assessment function and the change intensity assessment function of geological disaster bearing bodies are respectively used to determine the activity of geological disasters and the change intensity of geological disaster bearing bodies in the area to be studied, considering the dynamic changes in the environment where the geological disasters are located. Finally, the historical geological disaster risk assessment result and the dynamic changes in the environment where the geological disasters are located are combined to assess the geological disaster risk, and a dynamic geological disaster risk assessment result is obtained, greatly improving the accuracy of the geological disaster risk assessment result. Description of the Drawings

[0049] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings required in the embodiments. Obviously, the drawings in the following description are only some embodiments of the present application. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0050] Figure 1It is an application environment diagram of a geological disaster risk assessment method in an embodiment of the present application;

[0051] Figure 2 It is a schematic flowchart of a geological disaster risk assessment method provided in an embodiment of the present application;

[0052] Figure 3 is a schematic diagram comparing the geological disaster risk assessment results of a certain area provided by the present application at different times before and after. Among them, (a) is the historical geological disaster risk assessment result, and (b) is the dynamic geological disaster risk assessment result;

[0053] Figure 4 It is a schematic diagram of the functional modules of a geological disaster risk assessment device provided in an embodiment of the present application;

[0054] Figure 5 It is a schematic diagram of the structure of a computer device provided in an embodiment of the present application. Detailed implementation manners

[0055] Next, the technical solutions in the embodiments of the present application will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present application.

[0056] To make the purpose, features, and advantages of the present application more obvious and understandable, the present application will be further described in detail below in conjunction with the accompanying drawings and specific implementation manners.

[0057] The geological disaster risk assessment method provided in the embodiments of the present application can be applied, for example, as Figure 1In the application environment shown. Among them, the terminal 102 communicates with the server 104 through the network. The data storage system can store the data that the server 104 needs to process. The data storage system can be set separately, integrated on the server 104, placed on the cloud or other servers. The terminal 102 can send the historical optical remote sensing image time series, historical InSAR data, and historical geological disaster risk assessment results of the area to be studied to the server 104. After receiving the historical optical remote sensing image time series, historical InSAR data, and historical geological disaster risk assessment results of the area to be studied, the server 104 determines the geological disaster activity assessment result of the area to be studied by using the joint assessment function of geological disaster activity based on the historical optical remote sensing image time series and historical InSAR data; determines the change intensity assessment result of the geological disaster disaster-bearing body in the area to be studied by using the change intensity assessment function of the geological disaster disaster-bearing body based on each of the optical remote sensing images; and determines the dynamic geological disaster risk assessment result of the area to be studied by using the joint dynamic assessment function of geological disasters based on the geological disaster activity assessment result, the change intensity of the geological disaster disaster-bearing body, and the historical geological disaster risk assessment result in the area to be studied. The server 104 can feedback the obtained dynamic geological disaster risk assessment result to the terminal 102. In addition, in some embodiments, the geological disaster risk assessment method can also be implemented separately by the server 104 or the terminal 102. For example, the terminal 102 can directly process the historical optical remote sensing image time series, historical InSAR data, and historical geological disaster risk assessment results of the area to be studied, or the server 104 can obtain the historical optical remote sensing image time series, historical InSAR data, and historical geological disaster risk assessment results of the area to be studied from the data storage system and process the historical optical remote sensing image time series, historical InSAR data, and historical geological disaster risk assessment results of the area to be studied.

[0058] Among them, the terminal 102 can be, but is not limited to, various desktop computers, laptop computers, smart phones, tablet computers, Internet of Things devices, and portable wearable devices. The Internet of Things devices can be smart speakers, smart TVs, smart air conditioners, smart vehicle-mounted devices, etc. The portable wearable devices can be smart watches, smart bracelets, head-mounted devices, etc. The server 104 can be implemented by an independent server or a server cluster composed of multiple servers, and can also be a cloud server.

[0059] In an exemplary embodiment, as Figure 2 shown, a geological disaster risk assessment method is provided. This method is executed by a computer device, and can be specifically executed separately by a computer device such as a terminal or a server, or jointly executed by a terminal and a server. In the embodiments of the present application, this method is applied to Figure 1Taking server 104 in [the context] as an example for illustration, it includes the following steps 201 to 204. Among them:

[0060] Step 201, obtain the historical optical remote sensing image time series, historical InSAR data, and historical geological disaster risk assessment results of the area to be studied, where the historical optical remote sensing image time series includes multiple optical remote sensing images.

[0061] Step 202, based on the historical optical remote sensing image time series and historical InSAR data, use the joint evaluation function of geological disaster activity to determine the geological disaster activity evaluation result of the area to be studied; among them, the geological disaster activity evaluation result includes strong activity, medium activity, and weak activity.

[0062] Step 203, based on each of the optical remote sensing images, use the change intensity evaluation function of geological disaster bearing bodies to determine the change intensity evaluation result of geological disaster bearing bodies in the area to be studied; among them, the change intensity evaluation result of geological disaster bearing bodies includes strong deformation evaluation result, general deformation evaluation result, and weak deformation evaluation result.

[0063] Step 204, based on the geological disaster activity evaluation result, the change intensity of geological disaster bearing bodies, and the historical geological disaster risk assessment result of the area to be studied, use the joint dynamic evaluation function of geological disasters to determine the dynamic geological disaster risk assessment result of the area to be studied; the dynamic geological disaster risk assessment result includes extremely high risk V, high risk H, medium risk M, and low risk L.

[0064] The joint dynamic evaluation function of the geological disaster is:

[0065]

[0066] Among them, R n is the dynamic geological disaster risk assessment result, R o is the historical geological disaster risk assessment result, K g is the geological disaster activity evaluation result, K v is the change intensity evaluation result of geological disaster bearing bodies.

[0067] Implementing the above steps 201 to 204, based on the previous geological disaster assessment results, this application combines the dynamic changes of geological disasters to evaluate the geological disaster risk more accurately, and at the same time reduces the geological disaster investigation cost.

[0068] In an exemplary embodiment, step 201 specifically includes steps 101 - 103:

[0069] Step 101: Obtain multi-temporal optical remote sensing image data of the area to be studied and process it to obtain a time series of historical optical remote sensing images.

[0070] Optical remote sensing images mainly refer to remote sensing images that are imaged within the visible light range. There is a lot of optical remote sensing image data, such as WorldView satellite data, Sentinel data, high-resolution remote sensing satellite data, and resource satellite data, etc.

[0071] The time span between the earliest and the latest optical remote sensing image data in the multi-temporal optical remote sensing image data is more than 50 years, and the interval between adjacent two-phase optical remote sensing image data is about 5 - 10 years. Select one optical remote sensing image from each phase of optical remote sensing image data as a representative, which is used as the optical remote sensing image of this phase. Preprocess each optical remote sensing image to obtain an optical remote sensing image with accurate coordinates. Use the optical remote sensing image with accurate coordinates as the historical optical remote sensing image and apply it to analysis work such as land cover classification and land feature extraction. Finally, obtain a time series of historical optical remote sensing images. The time series of historical optical remote sensing images contains multiple optical remote sensing images, and the interval time between adjacent two optical remote sensing images is a preset time period. The preset time period can be about 5 - 10 years, or it can be other times.

[0072] The processing of optical remote sensing image data includes data preprocessing and image enhancement processing. Data preprocessing includes geometric correction, radiometric correction, and atmospheric correction. Image enhancement processing includes mosaicking, fusion, and cropping.

[0073] Step 102: Obtain InSAR data of the area to be studied and process it to obtain historical InSAR data.

[0074] InSAR (Interferometric Synthetic Aperture Radar) data mainly includes Sentinel-1 data, Sentinel-2 data, ALOS (Advanced Land Observing Satellite) data, RADARSAT-2 satellite data, HJ-1C (Environment-1) satellite data, and high-resolution 3 satellite 02 / 03 data. In this embodiment, the main InSAR data used is Sentinel-1 data.

[0075] The processing of InSAR data mainly includes: data preprocessing, interferometric processing, phase unwrapping, ellipsoid fitting, deformation calculation, error analysis, deformation interpretation, and result display, etc. Use the processed InSAR data as historical InSAR data.

[0076] Step 103: Obtain the historical geological disaster risk assessment results of the area to be studied.

[0077] Specifically, the historical geological disaster risk assessment results are the results of the preliminary geological disaster investigation and assessment of the area to be studied.

[0078] In an exemplary embodiment, step 202 specifically includes:

[0079] Step 21: Extract the earliest geological disaster outline area and the latest geological disaster outline area of the area to be studied from the historical optical remote sensing image time series.

[0080] Extract the earliest geological disaster outline area from the earliest historical optical remote sensing image in the historical optical remote sensing image time series, and extract the latest geological disaster outline area from the latest historical optical remote sensing image in the historical optical remote sensing image time series.

[0081] Step 22: Based on the earliest geological disaster outline area and the latest geological disaster outline area, use the long-term change feature evaluation function to determine the long-term change feature evaluation results of the area to be studied; wherein, the long-term change feature evaluation results include long-term active areas and non-long-term active areas.

[0082] Specifically, input the earliest geological disaster outline area and the latest geological disaster outline area into the long-term change feature evaluation function, perform spatial overlay analysis on the earliest geological disaster outline area and the latest geological disaster outline area, and obtain the change area vector of the area to be studied. Spatial overlay analysis is a spatial analysis method of geographic information systems. Spatial overlay analysis compares and analyzes the spatial relationships between the spatial information of different spatial data layers (such as vector data or raster data) by overlaying multiple spatial data layers together. The spatial data layers can include land cover types, terrain, climate, population distribution, and land use, etc.

[0083] Divide the area to be studied into long-term active area L T and non-long-term active area L N , and finally obtain the long-term change feature evaluation results of the area to be studied.

[0084] The long-term change feature evaluation function is:

[0085] K L =[L T L N .

[0086] Wherein, K L is the long-term change feature evaluation result.

[0087] Step 23: Obtain the surface deformation rate map of the area to be studied based on the historical InSAR data.

[0088] Based on the historical InSAR data, use the InSAR technology to obtain the surface deformation rate of the area to be studied, and perform interpolation processing on the surface deformation rate to obtain the morphological feature map of the scatter plot of the deformation rate, that is, the surface deformation rate map.

[0089] Step 24: Based on the surface deformation rate map, use the short-term surface deformation evaluation function to determine the short-term surface deformation evaluation result of the area to be studied.

[0090] Input the surface deformation rate map into the short-term surface deformation evaluation function, perform statistical analysis on each deformation rate scatter point in the surface deformation rate map to determine the break points of the deformation rate distribution, divide the deformation rate scatter points into four intervals according to the break points of the deformation rate distribution, and obtain the short-term surface deformation evaluation result of the area to be studied. The short-term surface deformation evaluation result includes the strong deformation area H of the surface m , the medium deformation area M of the surface m , the weak deformation area L of the surface m and the non-deformation area N of the surface m . In this embodiment, the determined break points of the deformation rate distribution are: -15 mm / y, -10 mm / y, and 0, where y is the year, the time unit.

[0091] The short-term surface deformation evaluation function is:

[0092]

[0093] where K N is the short-term surface deformation evaluation result.

[0094] Step 25: Based on the long-term change feature evaluation result and the short-term surface deformation evaluation result, use the activity evaluation function of geological disasters to determine the activity evaluation result of geological disasters in the area to be studied.

[0095] The activity evaluation function of the geological disaster is:

[0096] K g = K L * K N .

[0097] where K g is the activity evaluation result of geological disasters. The activity evaluation result of geological disasters includes strong activity W H , medium activity W M and weak activity W L .

[0098] In an exemplary embodiment, step 203 specifically includes steps 31 to 34:

[0099] Step 31: Extract patches of geological disaster affected bodies from each of the optical remote sensing images to obtain a time series of patches of geological disaster affected bodies.

[0100] Extract patches of geological disaster affected bodies from each optical remote sensing image to obtain a time series of patches of geological disaster affected bodies, where the geological disaster affected bodies are mainly artificial buildings.

[0101] Step 32: Calculate the annual change rate of the phased area based on two adjacent patches of geological disaster affected bodies in the time series of patches of geological disaster affected bodies.

[0102] Evenly divide the patches of geological disaster affected bodies into multiple partition units.

[0103] Calculate the area increment of each partition unit based on the areas of each partition unit in two adjacent patches of geological disaster affected bodies.

[0104] If the time interval between two adjacent optical remote sensing images is a preset time period, then the entire cycle of the optical remote sensing image time series includes multiple time periods, and the entire cycle is the entire time from the start time to the end time of the time series of patches of geological disaster affected bodies.

[0105] The calculation formula for the area increment of each partition unit within one time period is:

[0106] ΔA i，j =A i，j+1 -A i，j , i = 1, 2, 3......n; j = 1, 2, 3......m.

[0107] Where, ΔA i，j is the area increment of the i-th partition unit within the time period from the j-th time node to the j + 1-th time node; A i，j is the area of the i-th unit partition at the j-th time node; A i，j+1 is the area of the i-th unit partition at the j + 1-th time node.

[0108] Calculate the annual change rate of the phased area of each partition unit based on the area increment.

[0109] Y j =(D j+1 -D j ) / 365, j = 1, 2, 3......m.

[0110] V i，j =ΔA i，j / Y j, where \(i = 1, 2, 3, \cdots, n\) and \(j = 1, 2, 3, \cdots, m\).

[0111] Among them, \(Y\) j is the quantified annual time within the time period from the \(j\)-th time node to the \((j + 1)\)-th time node, \(D\) j is the quantified daily time at the \(j\)-th time node, \(D\) j+1 is the quantified daily time at the \((j + 1)\)-th time node, \(V\) i，j is the phased annual area change rate of the \(i\)-th partition unit within the time period from the \(j\)-th time node to the \((j + 1)\)-th time node.

[0112] Step 33: Calculate the full-cycle average annual area change rate based on the earliest geological disaster-affected body patch and the latest geological disaster-affected body patch in the time series of the geological disaster-affected body patches.

[0113] Fuse the geometric patch shapes of each partition unit in the region to obtain the fused area of each partition of the geological disaster-affected body patch.

[0114] The calculation formula for the fused area of each partition unit:

[0115] \(A\) wi = merge(\(\Delta A\) i,j ).

[0116] Among them, \(A\) wi is the fused area of the \(i\)-th partition unit within the time period from the \(j\)-th time node to the \((j + 1)\)-th time node, and merge is the merging and fusing function.

[0117] \(Y\) w = (\(D\) max - \(D\) min ) / 365.

[0118] Among them, \(Y\) w is the quantified annual time of the full cycle, \(D\) max is the quantified daily time of the earliest time node in the full cycle, \(D\) min is the quantified daily time of the latest time node in the full cycle.

[0119] \(V\) wi = \(A\) wi / \(Y\) w .

[0120] Among them, \(V\) wi is the full-cycle average annual area change rate of the \(i\)-th partition unit.

[0121] Obtain the full-cycle average annual area change rate by dividing the fused area of each partition unit in the full cycle by the quantified annual time of the full cycle.

[0122] Step 34: Evaluate the change intensity of the geological disaster-affected bodies based on the annual average change rate of the full-cycle area and the annual change rate of the phased area, and obtain the evaluation result of the change intensity of the geological disaster-affected bodies, which specifically includes steps 341 to 343:

[0123] Step 341: Determine the degree of dispersion of the change rate of the geological disaster-affected bodies according to the annual change rate of the phased area and the annual average change rate of the full-cycle area of each sub-region unit.

[0124] V Ri,j =(V i,j -V wi ) / V wi 。

[0125] Among them, V Ri,j is the degree of dispersion of the change rate within the time period from the j-th time node to the j + 1-th time node of the i-th sub-region unit; V i,j is the annual change rate of the phased area within the time period from the j-th time node to the j + 1-th time node of the i-th sub-region unit; V wi is the annual average change rate of the full-cycle area of the i-th sub-region unit.

[0126] Step 342: Determine the mean value of the annual change rate of the area of each sub-region unit according to the annual change rate of the phased area of each sub-region unit.

[0127]

[0128] Among them, V C is the mean value of the sum of the annual change rates of the area of a certain sub-region unit in each time period, that is, the mean value of the annual change rate of the area of a certain sub-region unit. This mean value represents the change intensity in the historical development process of this sub-region unit. M is the total number of time periods included in the full cycle.

[0129] Step 343: Evaluate the change intensity of the geological disaster-affected bodies according to the degree of dispersion and the mean value, and obtain the evaluation result of the change intensity of the geological disaster-affected bodies.

[0130] Determine the scatter distribution state of the change intensity of the geological disaster-affected bodies according to the mean value and the degree of dispersion. On this basis, determine the break point of the change intensity of the geological disaster-affected bodies. Classify the change intensity of the geological disaster-affected bodies in the area to be studied according to the break point of the change intensity of the geological disaster-affected bodies, and obtain the evaluation result of the change intensity of the geological disaster-affected bodies. The evaluation result of the change intensity of the geological disaster-affected bodies includes S as the evaluation result of strong deformation, G as the evaluation result of general deformation, and W as the evaluation result of weak deformation.

[0131] The change intensity evaluation function of the geological disaster is:

[0132] Kv = [SGW] T 。

[0133] Among them, K v is the evaluation result of the change intensity of geological disaster affected bodies, S is the evaluation result of strong deformation, G is the evaluation result of general deformation, W is the evaluation result of weak deformation, and T is the transpose of the matrix.

[0134] As shown in Figure 3, the geological disaster risk assessment method provided by this application was applied to a certain area for research, and the effect was obvious.

[0135] The geological disaster risk assessment method provided by this application fully considers the current cutting-edge technologies in geological disaster investigation and assessment, such as spatial analysis methods, and combines the previous geological disaster investigation and assessment results, which can save a large amount of investigation resources. At the same time, various data used in this application are easy to obtain, easy to operate, highly targeted, consider the impact of environmental changes, and improve the accuracy of geological disaster risk assessment results. As shown in Table 1, based on the historical geological disaster risk assessment results, the dynamic geological disaster risk assessment results of a certain area were obtained using the geological disaster risk assessment method of this application.

[0136] Table 1

[0137]

[0138]

[0139] Based on the same inventive concept, the embodiment of this application also provides a geological disaster risk assessment device for implementing the above-mentioned geological disaster risk assessment method. The solution provided by this device to solve problems is similar to the solution described in the above method. Therefore, the specific limitations in one or more embodiments of the following geological disaster risk assessment device can refer to the limitations of the geological disaster risk assessment method in the above text, and will not be repeated here.

[0140] In an exemplary embodiment, as Figure 4 shown, a geological disaster risk assessment device is provided, including:

[0141] An acquisition module 41, configured to acquire the historical optical remote sensing image time series, historical InSAR data, and historical geological disaster risk assessment results of the area to be studied. The historical optical remote sensing image time series includes multiple optical remote sensing images, and the time between two adjacent optical remote sensing images is a preset time period.

[0142] The activity evaluation module 42 is configured to determine the geological disaster activity evaluation result of the area to be studied based on the historical optical remote sensing image time series and historical InSAR data by using a joint activity evaluation function for geological disasters. Wherein, the joint activity evaluation function includes a long-term change feature evaluation function and a short-term surface deformation evaluation function, and the geological disaster activity evaluation result includes strong activity, medium activity, and weak activity.

[0143] The change intensity evaluation module 43 is configured to determine the change intensity evaluation result of the geological disaster affected bodies in the area to be studied based on each of the optical remote sensing images by using a change intensity evaluation function for geological disaster affected bodies. Wherein, the change intensity evaluation result of the geological disaster affected bodies includes a strong deformation evaluation result, a general deformation evaluation result, and a weak deformation evaluation result.

[0144] The dynamic risk evaluation module 44 is configured to determine the dynamic geological disaster risk evaluation result of the area to be studied based on the geological disaster activity evaluation result of the area to be studied, the change intensity of the geological disaster affected bodies, and the historical geological disaster risk evaluation result by using a joint dynamic evaluation function for geological disasters. The dynamic geological disaster risk evaluation result includes extremely high risk, high risk, medium risk, and low risk.

[0145] In an exemplary embodiment, a computer device is provided. The computer device can be a server or a terminal, and its internal structure diagram can be as Figure 5 shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, abbreviated as I / O), and a communication interface. Among them, the processor, the memory, and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store the historical optical remote sensing image time series, historical InSAR data, and historical geological disaster risk evaluation results obtained for the area to be studied. The input / output interface of the computer device is used to exchange information between the processor and external devices. The communication interface of the computer device is used to communicate with external terminals through a network connection. When the computer program is executed by the processor, it implements a geological disaster risk evaluation method.

[0146] Those skilled in the art can understand, Figure 5The structure shown is only a block diagram of some structures related to the solution of this application, and does not constitute a limitation on the computer device to which the solution of this application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine some components, or have different component arrangements.

[0147] In an exemplary embodiment, a computer device is further provided, including a memory and a processor. A computer program is stored in the memory, and when the processor executes the computer program, the steps in the above method embodiments are implemented.

[0148] In an exemplary embodiment, a computer-readable storage medium is provided, storing a computer program, and when the computer program is executed by a processor, the steps in the above method embodiments are implemented.

[0149] In an exemplary embodiment, a computer program product is provided, including a computer program, and when the computer program is executed by a processor, the steps in the above method embodiments are implemented.

[0150] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use, and processing of relevant data need to comply with relevant regulations.

[0151] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above methods. Among them, any reference to a memory, database, or other medium used in the embodiments provided in the present application can include at least one of non-volatile and volatile memories. Non-volatile memories can include read-only memory (ROM), magnetic tapes, floppy disks, flash memories, optical memories, high-density embedded non-volatile memories, resistive random access memories (ReRAMs), magnetoresistive random access memories (MRAMs), ferroelectric random access memories (FRAMs), phase change memories (PCMs), graphene memories, etc. Volatile memories can include random access memory (RAM) or external cache memories, etc. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc.

[0152] The databases involved in the embodiments provided in the present application can include at least one of relational databases and non-relational databases. Non-relational databases can include distributed databases based on blockchain, etc., without limitation. The processors involved in the embodiments provided in the present application can be general-purpose processors, central processors, graphics processors, digital signal processors, programmable logic devices, data processing logics based on quantum computing, etc., without limitation.

[0153] The technical features of the above embodiments can be combined arbitrarily. For the sake of brevity of description, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, it should be considered as the scope described in this specification.

[0154] In this article, specific examples are used to elaborate on the principles and implementation manners of the present application. The descriptions of the above embodiments are only used to help understand the method and its core idea of the present application; at the same time, for those of ordinary skill in the art, according to the idea of the present application, there will be changes in the specific implementation manners and application scopes. In summary, the content of this specification should not be construed as a limitation to the present application.

Claims

1. A geological disaster risk assessment method, characterized in that: The geological disaster risk assessment method comprises: Acquire a historical optical remote sensing image time series, historical InSAR data, and historical geological disaster risk assessment results for the area to be studied, wherein the historical optical remote sensing image time series includes multiple optical remote sensing images; Based on the historical optical remote sensing image time series and the historical InSAR data, a geological disaster activity joint evaluation function is used to determine the geological disaster activity evaluation result of the area to be studied; wherein the geological disaster activity evaluation result includes strong activity, medium activity and weak activity; Based on each of the optical remote sensing images, a change intensity evaluation function of the geological hazard-bearing body is used to determine a change intensity evaluation result of the geological hazard-bearing body in the area to be studied; wherein the change intensity evaluation result of the geological hazard-bearing body includes a strong deformation evaluation result, a general deformation evaluation result and a weak deformation evaluation result; Based on the geological hazard activity evaluation results of the area to be studied, the intensity of changes in the geological hazard-bearing body and the historical geological hazard risk evaluation results, a joint dynamic evaluation function of geological hazards is used to determine the dynamic geological hazard risk evaluation results of the area to be studied; wherein the dynamic geological hazard risk evaluation results include extremely high risk, high risk, medium risk and low risk.

2. The geological disaster risk assessment method according to claim 1, characterized in that: The joint dynamic evaluation function of the geological disasters is: The joint evaluation function of the activity of geological hazards is: K g =K L *K N ; The evaluation function of the change intensity of the geological disaster-bearing body is: K v =[S G W] T ; Among them, R n is the result of dynamic geological hazard risk assessment, R o is the historical geological disaster risk assessment result, K g is the result of geological hazard activity assessment, K v is the evaluation result of the change intensity of the geological hazard-bearing body, K L is the long-term change characteristic evaluation result, K N is the short-term surface deformation evaluation result, S is the strong deformation evaluation result, G is the general deformation evaluation result, W is the weak deformation evaluation result, and T is the transpose of the matrix.

3. The geological disaster risk assessment method according to claim 1, characterized in that: The joint evaluation function of the activity of geological hazards includes a long-term change characteristic evaluation function and a short-term surface deformation evaluation function; Based on the historical optical remote sensing image time series and the historical InSAR data, a geological hazard activity joint evaluation function is used to determine the geological hazard activity evaluation result of the area to be studied, including: Extracting the earliest geological disaster outer contour area and the latest geological disaster outer contour area of ​​the area to be studied from the historical optical remote sensing image time series; Based on the earliest geological disaster outer contour area and the latest geological disaster outer contour area, the long-term change characteristic evaluation function is used to determine the long-term change characteristic evaluation result of the area to be studied; wherein the long-term change characteristic evaluation result includes a long-term active area and a non-long-term active area; Obtaining a surface deformation rate map of the area to be studied based on the historical InSAR data; Based on the surface deformation rate map, a short-term surface deformation evaluation function is used to determine the short-term surface deformation evaluation result of the area to be studied; wherein the short-term surface deformation evaluation result includes a surface strong deformation area, a surface deformation area, a surface weak deformation area and a surface non-deformation area; Based on the long-term change characteristic evaluation results and the short-term surface deformation evaluation results, a geological hazard activity joint evaluation function is used to determine the geological hazard activity evaluation results of the area to be studied.

4. The geological disaster risk assessment method according to claim 1, characterized in that: Based on each of the optical remote sensing images, a change intensity evaluation function of the geological hazard-prone body is used to determine a change intensity evaluation result of the geological hazard-prone body in the area to be studied, including: Extracting the spots of geological disaster-prone bodies from each of the optical remote sensing images to obtain a time series of the spots of geological disaster-prone bodies; Calculate the annual change rate of the staged area based on two adjacent geological hazard prone body images in the time series of the geological hazard prone body images; The annual average change rate of the area during the whole cycle is calculated according to the earliest geological disaster prone body spot and the latest geological disaster prone body spot in the time series of the geological disaster prone body spots; wherein the whole cycle is the entire time from the start time to the end time of the time series of the geological disaster prone body spots; The intensity of changes in the geological disaster-prone body is evaluated based on the average annual change rate of the full-cycle area and the staged annual change rate of the area, and an evaluation result of the intensity of changes in the geological disaster-prone body is obtained.

5. The geological disaster risk assessment method according to claim 4, characterized in that: The annual change rate of the staged area is calculated based on two adjacent geological hazard prone body images in the time series of the geological hazard prone body images, including: Evenly divide the geological disaster-prone body map into a plurality of partition units; Calculate the area increment of each subdivision unit according to the area of ​​each subdivision unit in two adjacent geological hazard-bearing body maps; The annual rate of change of the area of ​​each partition unit is calculated based on the area increment.

6. The geological disaster risk assessment method according to claim 5, characterized in that: The intensity of the change of the geological disaster-bearing body is evaluated according to the annual average change rate of the whole-cycle area and the annual change rate of the staged area, and the evaluation results of the intensity of the change of the geological disaster-bearing body are obtained, including: Determine the degree of dispersion of the change rate of the geological hazard-bearing body according to the staged annual change rate of the area of ​​each sub-division unit and the average annual change rate of the area over the entire period; Determine the average annual area change rate of each sub-division unit according to the staged annual area change rate of each sub-division unit; The intensity of changes in the geological disaster-prone body is evaluated according to the discrete degree and the mean value to obtain an evaluation result of the intensity of changes in the geological disaster-prone body.

7. A geological disaster risk assessment device, characterized in that: The geological disaster risk assessment device comprises: An acquisition module is used to acquire a time series of historical optical remote sensing images, historical InSAR data, and historical geological disaster risk assessment results of the area to be studied, wherein the time series of historical optical remote sensing images includes multiple optical remote sensing images; An activity evaluation module is used to determine the activity evaluation result of the geological disasters in the area to be studied by using the activity joint evaluation function of the geological disasters based on the historical optical remote sensing image time series and the historical InSAR data; wherein the activity evaluation result of the geological disasters includes strong activity, medium activity and weak activity; A change intensity evaluation module is used to determine the change intensity evaluation result of the geological hazard-bearing body in the area to be studied by using the change intensity evaluation function of the geological hazard-bearing body based on each of the optical remote sensing images; wherein the change intensity evaluation result of the geological hazard-bearing body includes a strong deformation evaluation result, a general deformation evaluation result and a weak deformation evaluation result; The dynamic risk assessment module is used to determine the dynamic geological hazard risk assessment results of the area to be studied by using a joint dynamic assessment function of geological hazards based on the geological hazard activity assessment results of the area to be studied, the intensity of changes in the geological hazard-bearing body and the historical geological hazard risk assessment results; the dynamic geological hazard risk assessment results include extremely high risk, high risk, medium risk and low risk.

8. A computer device comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the geological hazard risk assessment method described in any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the geological hazard risk assessment method described in any one of claims 1 to 6 is implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the geological hazard risk assessment method described in any one of claims 1 to 6 is implemented.

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