A new-born landslide hazard identification method, system, computing device and medium

Abstract

This invention relates to a method, system, computing device, and medium for identifying newly formed landslide hazards. The method includes: acquiring the frequency of occurrence of different historical characteristic elements of the same geological environmental factor in multiple landslides within a region to be identified before the landslide occurred, and determining the first target characteristic elements corresponding to each geological environmental factor; acquiring all characteristic elements of each geological environmental factor corresponding to each rock mass within the region to be identified; matching all characteristic elements of each geological environmental factor corresponding to each rock mass with the corresponding first target characteristic element, and determining a first number of successful matches; acquiring the total number of the first number corresponding to each rock mass; if the total number is greater than a preset threshold, then the rock mass is a target rock mass, and the target rock mass is identified as a hazard point. This method can accurately identify newly formed bedding-parallel rock landslide hazards, thereby improving the effectiveness of early warning and prevention of landslide disasters.

Description

Technical Field

[0001] This invention relates to the field of geological disaster monitoring technology, specifically to a method, system, computing device, and medium for identifying potential new landslide hazards. Background Technology

[0002] A landslide is a natural disaster in which rock and soil on a slope slides downhill, either as a whole or in parts, under the influence of gravity, due to factors such as river erosion, groundwater activity, rainwater soaking, earthquakes, and artificial slope cutting.

[0003] Therefore, early warning and prevention of landslide disasters are of great significance. Traditional early warning and prevention methods usually involve monitoring potential landslide sites and issuing warnings based on the monitoring results. However, traditional investigation and identification methods are insufficient for identifying newly formed bedding rock landslide hazards, resulting in poor effectiveness of early warning and prevention of landslide disasters. Summary of the Invention

[0004] The present invention aims to solve, at least to some extent, the technical problems in the related technologies, and provides a method, system, computing device and medium for identifying potential new landslide hazards.

[0005] Firstly, in order to solve the above-mentioned technical problems, the present invention provides a method for identifying potential new landslide hazards, comprising:

[0006] The frequency of occurrence of different historical characteristic elements of the same geological environmental factors in multiple landslides within the area to be identified before the landslide occurred is obtained; the frequency of occurrence represents the number of times each historical characteristic element of the same geological environmental factor occurred within a preset time period before the landslide occurred.

[0007] Historical feature elements that occur more frequently than a preset frequency threshold in the same geological environmental factors are taken as the first target feature elements.

[0008] Obtain all characteristic elements of each geological environmental factor corresponding to each rock mass within the area to be identified;

[0009] For each rock mass, all feature elements of each geological environmental factor corresponding to the rock mass are matched with each of the first target feature elements of the same geological environmental factor, and a first number of feature elements of each geological environmental factor that are successfully matched with the first target feature elements are determined.

[0010] Obtain the total number of the first quantity corresponding to each rock mass. If the total number is greater than a preset quantity threshold, then the rock mass is a target rock mass and the target rock mass is identified as a potential hazard point.

[0011] Secondly, in order to solve the above-mentioned technical problems, the present invention provides a system for identifying potential new landslide hazards, comprising:

[0012] The first acquisition module is used to acquire the frequency of occurrence of different historical characteristic elements of the same geological environmental factors in multiple landslides in the area to be identified before the landslide occurred; the frequency of occurrence represents the number of times each historical characteristic element of the same geological environmental factor occurred within a preset time period before the landslide occurred.

[0013] The target module is used to select historical feature elements that occur more frequently than a preset frequency threshold in the same geological environmental factors as the first target feature elements.

[0014] The second acquisition module is used to acquire all feature elements of each geological environmental factor corresponding to each rock mass in the area to be identified;

[0015] The matching module is used to match all feature elements of each geological environmental factor corresponding to each rock mass with each first target feature element of the same geological environmental factor for each rock mass, and to determine the first number of feature elements of each geological environmental factor that are successfully matched with the first target feature elements.

[0016] The determination module is used to obtain the total number of the first quantity corresponding to each rock mass. If the total number is greater than a preset quantity threshold, the rock mass is a target rock mass and the target rock mass is determined as a potential hazard point.

[0017] Thirdly, in order to solve the above-mentioned technical problems, the present invention provides a computing device, including a memory, a processor, and a program stored in the memory and running on the processor, wherein the processor executes the program to implement the steps of the method for identifying new landslide hazards as described above.

[0018] Fourthly, in order to solve the above-mentioned technical problems, the present invention provides a computer-readable storage medium storing instructions that, when executed on a terminal device, cause the terminal device to perform the steps of the newly formed landslide hazard identification method described above.

[0019] The beneficial effects of the present invention are as follows: by obtaining the frequency of occurrence of different historical characteristic elements of the same geological environmental factors in multiple landslides in the area to be identified before the landslide, the historical characteristic elements of the same geological environmental factors with a frequency greater than a preset frequency threshold are taken as the first target characteristic elements, thereby determining the same characteristic elements among multiple landslides in the area to be identified, that is, the first target characteristic elements are characteristic elements that may lead to the occurrence of landslides.

[0020] Next, obtain all feature elements of each geological environmental factor corresponding to each rock mass in the area to be identified. For each rock mass, match all feature elements corresponding to each geological environmental factor with each first target feature element of the same geological environmental factor, determine the first number of feature elements in each geological environmental factor that successfully match the first target feature elements in the same geological environmental factor, and determine the number of feature elements in each rock mass that may cause landslides.

[0021] The total number of each rock mass is then compared with a preset threshold. Rock masses exceeding the preset threshold are identified as target rock masses. This means that the target rock mass contains a large number of characteristic elements that could lead to a landslide, making it highly likely that a landslide will occur. Therefore, this target rock mass is identified as a potential hazard point, specifically a newly formed bedding-parallel rock landslide hazard.

[0022] In this way, by analyzing the characteristic elements of multiple landslides that have occurred within the area to be identified, the primary target characteristic elements that may lead to landslides are determined. Then, the characteristic elements of the rock mass are matched with the primary target characteristic elements to determine the number of primary target characteristic elements within the rock mass that may lead to landslides. When there are a large number of characteristic elements within the rock mass that may lead to landslides, it indicates that the boundary constraints on the rock mass are weak, meaning the probability of a landslide is high and there is a significant landslide hazard. This allows for more accurate identification of hazard points or newly formed bedding rock landslide hazards, thereby improving the effectiveness of landslide disaster early warning and prevention. Attached Figure Description

[0023] Figure 1 A flowchart of a method for identifying potential new landslide hazards provided by the present invention;

[0024] Figure 2 This is a schematic diagram of the structure of a new landslide hazard identification system provided by the present invention. Detailed Implementation

[0025] The principles and features of the present invention are described below. The examples given are only for explaining the present invention and are not intended to limit the scope of the present invention.

[0026] The following describes, with reference to the accompanying drawings, a method, system, computing device, and medium for identifying potential new landslide hazards according to an embodiment of the present invention.

[0027] like Figure 1 As shown, this embodiment provides a method for identifying potential new landslide hazards, including:

[0028] Step S101: Obtain the frequency of occurrence of different historical characteristic elements of the same geological environmental factor in multiple landslides within the area to be identified before the landslide occurred. The frequency of occurrence represents the number of times each historical characteristic element of the same geological environmental factor occurred within a preset time period before the landslide occurred.

[0029] Before a landslide occurs, the rock mass is formed. This rock mass can be considered a "six-faceted rock mass" developed within a natural slope. Besides being free-floating above, this "six-faceted rock mass" is constrained by up to five rock faces before it can slide, including the anti-sliding force at the base, the resistive force at the leading edge, the tensile force at the trailing edge, and the shear resistance at the lateral boundaries. The fewer or weaker the boundary constraints on the "six-faceted rock mass," the more prone it is to landslides. The boundary constraints on each rock face are characterized by their specific features. Therefore, by determining the frequency of different historical characteristic features of the same geological environmental factors in multiple landslide-affected areas before the landslides, a higher frequency indicates a weaker boundary constraint effect of those geological environmental factors on the rock mass.

[0030] It is understood that a landslide has six rock faces: the surface, the bottom, the leading edge, the trailing edge, the left side, and the right side. Therefore, obtaining different historical characteristic elements of the same geological environmental factor in an existing landslide refers to obtaining different historical characteristic elements of at least one geological environmental factor corresponding to each rock face of the existing landslide. In this embodiment, multi-source data of existing landslides can be obtained, such as historical elevation data, historical geological image data, historical remote sensing data, historical rock strata occurrence data, geological survey data, and geological hazard investigation data. By analyzing and calculating through multi-source data, the different historical characteristic elements of the same geological environmental factor for each existing landslide can be determined. Since obtaining the historical characteristic elements of existing landslides is a relatively mature existing technology, it will not be elaborated further here.

[0031] In this embodiment, the area to be identified is an area prone to frequent landslides.

[0032] This embodiment uses Reservoir Area A as the study area, where extreme rainfall and reservoir water soaking induced newly formed bedding-parallel landslides. Therefore, this embodiment actually conducts a specific study on bedding-parallel landslides; that is, the newly formed landslide hazard in this embodiment refers to the newly formed bedding-parallel landslide hazard.

[0033] Step S102: Select historical feature elements with a frequency greater than a preset frequency threshold among the same geological environmental factors as the first target feature elements.

[0034] It is understandable that the number of primary target characteristic elements corresponding to the same geological environmental factor includes at least one. The higher the frequency of occurrence, the more likely that the primary target characteristic element corresponding to that geological environmental factor is the characteristic element that leads to a landslide. That is, when a landslide is about to occur, this characteristic element has a poor ability to restrict the boundary of the rock mass.

[0035] Step S103: Obtain all feature elements of each geological environmental factor corresponding to each rock mass in the area to be identified.

[0036] Step S104: For each rock mass, match all feature elements of each geological environmental factor corresponding to the rock mass with each first target feature element of the same geological environmental factor, and determine the first number of feature elements of each geological environmental factor that are successfully matched with the first target feature elements.

[0037] Step S105: Obtain the total number of the first quantity corresponding to each rock mass. If the total number is greater than the preset quantity threshold, the rock mass is the target rock mass and the target rock mass is identified as a hidden danger point.

[0038] This embodiment provides a method for identifying potential new landslide hazards. It obtains the frequency of occurrence of different historical characteristic elements of the same geological environmental factor in multiple landslides within a target area before the landslide. Historical characteristic elements with a frequency greater than a preset frequency threshold are designated as first target characteristic elements. This identifies common characteristic elements among multiple landslides within the target area, indicating that the first target characteristic elements are potential landslide-causing elements. Next, all characteristic elements corresponding to each geological environmental factor for each rock mass within the target area are obtained. For each rock mass, all characteristic elements corresponding to each geological environmental factor are matched with the first target characteristic elements of the same geological environmental factor. A first number of successful matches between characteristic elements of each geological environmental factor and the first target characteristic elements of the same geological environmental factor is determined, thus identifying the number of potential landslide-causing characteristic elements in each rock mass. The total number of these potential landslide-causing characteristic elements in each rock mass is then compared with a preset threshold. Rock masses with a number greater than the preset threshold are identified as target rock masses. In other words, target rock masses contain a large number of potential landslide-causing characteristic elements, making them highly likely to experience a landslide. Therefore, the target rock mass was identified as a potential hazard point, namely a newly formed bedding rock landslide hazard.

[0039] In this way, by analyzing the characteristic elements of multiple landslides that have occurred within the area to be identified, the primary target characteristic elements that may lead to landslides are determined. Then, the characteristic elements of the rock mass are matched with the primary target characteristic elements to determine the number of primary target characteristic elements within the rock mass that may lead to landslides. When there are a large number of characteristic elements within the rock mass that may lead to landslides, it indicates that the boundary constraints on the rock mass are weak, meaning the probability of a landslide is high and there is a significant landslide hazard. This allows for more accurate identification of hazard points or newly formed bedding rock landslide hazards, thereby improving the effectiveness of landslide disaster early warning and prevention.

[0040] Preferably, the types of geological environmental factors include topography, geological structure, slope structure, and stratigraphic lithology.

[0041] Landslides that have occurred usually have typical topographic features, such as semi-circular, tongue-shaped, or fan-shaped flat rock surfaces, steep cliffs with open rock surfaces at the front edge, large undulations in the slope rock surface, stepped drop-offs and water-collecting depressions at the rear edge, and gullies on both sides.

[0042] Geological structures have a wide-ranging impact. The non-uniform distribution of in-situ stress caused by these structures is the primary driving force behind landslides, and the vicinity of these structures is also a high-incidence area for landslides, especially near fault fracture zones and abrupt fold transition zones.

[0043] When a slope exhibits a distinct zigzag shape with a steep upper section and a gentler lower section, or a near-straight slope, with an elevation gradient and rock stratum dip angle exceeding 35°, the slope is more prone to initiation under gravity. The boundary cutting of a slope determines the amount of energy required to initiate sliding and the magnitude of resistance during movement. Slopes with multiple rock faces cut into relatively isolated structures are more susceptible to deformation due to external disturbances. Furthermore, the presence of joints and fissures intersecting the rock mass weakens the overall supporting capacity of the fractured rock mass. Therefore, slope structure significantly influences whether a landslide will occur.

[0044] Stratigraphic lithology includes both landslide-prone strata and lithology. Typically, landslides within the same area often share similar landslide-prone strata and lithologies. For example, if the area to be identified is a reservoir area (hereinafter referred to as Reservoir Area A), statistical data shows that 70% of existing landslides in Reservoir Area A are developed within "landslide-prone strata." Typical neo-landslides are also formed in Jurassic, Triassic, part of Permian, and Silurian sedimentary strata, with lithology primarily consisting of sandstone, mudstone, or sandy mudstone. The rock mass composition exhibits an alternating layered structure of soft and hard layers or alternating layers of unequal thickness. Relatively soft or thinner layers are easily disintegrated and broken by pressure from the overlying rock mass. Once these layers undergo mudification under long-term groundwater exposure, they form natural aquitards, which are detrimental to the stability of the overlying rock strata, easily leading to landslide disasters.

[0045] Therefore, topography, geological structure, slope structure, and lithology can influence the constraints on rock mass boundaries. When the rock mass boundaries are poorly constrained, the resistance to landslides is smaller, making them more prone to disaster. Thus, by identifying geological environmental factors as topography, geological structure, slope structure, and lithology, we can more accurately determine the geological environmental factors leading to landslides. This allows us to identify the historical and primary target characteristics of each geological environmental factor, thereby improving the accuracy of identifying potential hazard points, specifically newly formed bedding-parallel rock landslides.

[0046] In some embodiments, Table 1 is used as a first data table. Table 1 shows the correspondence between geological environmental factors and first target feature elements.

[0047] Table 1

[0048]

[0049] Furthermore, the frequency of occurrence of different historical characteristic elements of the same geological environmental factors in multiple landslides within the area to be identified before the landslides occurred is obtained. This includes: acquiring multi-source data within the area to be identified; determining, based on the multi-source data, at least one historical characteristic element when the geological environmental factor in each landslide within the area to be identified is topography, geological structure, slope structure, or stratigraphic lithology; and, based on all historical characteristic elements, determining the frequency of occurrence of different historical characteristic elements of the same geological environmental factors in multiple landslides within the area to be identified before the landslides occurred.

[0050] In this way, by using multi-source data in the area to be identified, it is possible to accurately determine at least one historical characteristic element when the geological environmental factors in multiple landslides are topography, geological structure, slope structure and stratigraphy, thus facilitating the determination of the frequency of occurrence of different historical characteristic elements of the same geological environmental factors.

[0051] For example, there are four geological environmental factors in the area to be identified: topography, geological structure, slope structure, and stratigraphy.

[0052] The geological environmental factors are topography and landforms. Different historical features before the landslide include monocline topography, exposed front edge, and deep gullies. Among them, monocline topography appeared twice, exposed front edge appeared five times, and deep gullies appeared three times, so the frequency of occurrence of the three is 2 / 10, 5 / 10, and 3 / 10, respectively.

[0053] The geological environmental factors are topography and landforms. Different historical characteristics before the landslide include regional fault fracture zones and regional fold abrupt transition zones. Among them, regional fault fracture occurred 5 times and regional fold abrupt transition zones occurred 3 times, so their occurrence frequencies are 5 / 10 and 5 / 10 respectively.

[0054] The geological environmental factor is the slope structure. Different historical characteristics before the landslide include longitudinal and oblique longitudinal structures. Among them, the longitudinal structure appeared 6 times and the oblique longitudinal structure appeared 4 times, so the frequency of occurrence of the two is 6 / 10 and 4 / 10 respectively.

[0055] The geological environmental factors are stratigraphy and lithology. Different historical characteristics before the landslide include slippery strata (Jurassic) and lithology (carbonaceous shale), and slippery strata (Triassic) and lithology (carbonaceous shale). Among them, slippery strata (Jurassic) and lithology (carbonaceous shale) appeared 6 times, and slippery strata (Triassic) and lithology (carbonaceous shale) appeared 4 times, so their occurrence frequencies are 6 / 10 and 4 / 10 respectively.

[0056] Preferably, all feature elements of each geological environmental factor corresponding to each rock mass within the area to be identified are obtained, including: obtaining the first distribution of the first target feature element within the area to be identified when the geological environmental factor is topography, and the second distribution of the first target feature element when the geological environmental factor is geological structure. Areas where both the first and second distributions are concentrated are designated as prone areas. All feature elements of each geological environmental factor corresponding to each rock mass within the prone areas are obtained. The first distribution includes both concentrated and sparse distributions. The second distribution includes both concentrated and sparse distributions.

[0057] For example, when the geological environmental factor is topography, the primary target characteristic element is a zigzag or monocline topography; when the geological environmental factor is geological structure, the primary target characteristic element is a regional fold abrupt change zone. A regional topographic and geomorphological analysis is performed on the area to be identified, and the first distribution when the primary target characteristic element is a zigzag topography is determined. A regional geological structure analysis is then performed on the area to be identified, and the second distribution when the primary target characteristic element is a regional fold abrupt change zone is determined. Areas where both the first and second distributions are concentrated are identified as high-risk areas.

[0058] Because the area to be identified is large and contains numerous rock masses, identifying each rock mass individually would be extremely time-consuming and inefficient in identifying potential hazard points, particularly newly formed bedding-parallel landslides. However, the wide distribution of topography and geological structures allows for efficient identification. Therefore, by acquiring the distribution of the first target feature elements corresponding to the topography and geological structures within the area to be identified, and noting that when both the first and second distributions within the same area are concentrated, it indicates that the feature elements in that area have minimal constraint on the rock mass boundaries, meaning that the rock masses in that area are highly prone to landslides and are considered a high-risk area. Thus, by identifying high-risk areas within the area to be identified and then identifying the individual rock masses within those areas, the number of rock masses to be identified can be reduced, improving identification efficiency, while also ensuring the accuracy of identifying potential hazard points.

[0059] In some embodiments, elevation data of the area to be identified is acquired, and multiple slope information and multiple relief information are calculated from the elevation data. These are then used to determine at least one feature element corresponding to the geological environmental factors within the area to be identified as topography. Based on each feature element corresponding to the geological environmental factors as topography, a first distribution is determined.

[0060] In some embodiments, geological images and remote sensing images of the area to be identified are acquired, the geological images are analyzed and the remote sensing images are interpreted, and at least one feature element of the geological environmental factors in the area to be identified is determined when the geological environmental factors are geological structures. Then, based on each of the first target feature elements when the geological environmental factors are geological structures, a second distribution is determined.

[0061] In some embodiments, when the area to be identified is Reservoir Area A, by analyzing the distribution of the first target feature elements corresponding to the geological structure and topography of Reservoir Area A, twelve prone areas, namely, bedding rock landslide prone areas, are identified.

[0062] As shown in Table 2, this is the second data table. Table 2 illustrates the correspondence between various landslide-prone areas and the first target characteristic elements when the geological environmental factors are geological structures and topography. The "first target characteristic elements" in Table 2 refer to the first target characteristic elements corresponding to geological structures and topography. Specifically, the first target characteristic elements when the geological environmental factor is a geological structure include regional fold abrupt change zones and abrupt changes in stratum attitude. The first target characteristic elements when the geological environmental factor is a topography include free front and zigzag topography, and monocline topography. Furthermore, since the area to be identified in this embodiment is Reservoir Area A, the reservoir water has an inducing effect on the rock mass. Therefore, Table 2 also introduces the relationship between landslide-prone areas and reservoir water, i.e., the first target characteristic element also includes the reservoir water level being above the potential slip surface or turning point, so that researchers can analyze the impact of reservoir water on bedding rock landslides. The "satisfied characteristic elements" in Table 2 are the characteristic elements within the landslide-prone areas that successfully match the first target characteristic elements.

[0063] Table 2

[0064]

[0065] As shown in Table 2, the more characteristic elements a prone area meets, the more likely it is to experience bedding-parallel landslides compared to other prone areas, requiring special attention. For example, the characteristic elements met by both banks of area L1 are: ① abrupt fold change zone; ② abrupt change in strata attitude; ③ open front; ④ zigzag or monoc topography; ⑤ reservoir water level above the potential slip surface or inflection point. Area L11, on the other hand, meets the same characteristic elements: ① abrupt fold change zone; ② abrupt change in strata attitude; ④ zigzag or monoc topography; ⑤ reservoir water level above the potential slip surface or inflection point. Therefore, area L1 meets 5 characteristic elements, while area L11 meets 4. Thus, area L1 is more prone to bedding-parallel landslides than area L11.

[0066] Preferably, all characteristic elements of each geological environmental factor corresponding to each rock mass within the prone area are obtained, including: obtaining the third distribution of the first target characteristic element corresponding to the slope structure geological environmental factor within the prone area, and the fourth distribution of the first target characteristic element corresponding to the stratigraphic lithology geological environmental factor. Areas where both the third and fourth distributions are concentrated are designated as potential hazard sections. All characteristic elements of each geological environmental factor corresponding to each rock mass within the potential hazard section are obtained. The third distribution includes both concentrated and sparse distributions. The fourth distribution includes both concentrated and sparse distributions.

[0067] For example, when the geological environmental factor is a slope structure, the first target characteristic element is a dip slope or a dipping slope; when the geological environmental factor is lithology, the first target characteristic element is a landslide-prone strata (Jurassic) and lithology (mudstone). Regional slope structure analysis is performed on the prone area to determine the third distribution when the first target characteristic element is a dip slope or a dipping slope. Stratigraphic lithology analysis is then performed on the prone area to determine the fourth distribution when the first target characteristic element is a landslide-prone strata (Jurassic) and (mudstone). Areas where both the third and fourth distributions are concentrated are designated as potential hazard sections within the prone area.

[0068] Because the areas covered by topography and geological structures are quite large, to further improve the efficiency of identifying potential landslide sites, specifically newly formed bedding-parallel landslides, it is necessary to identify high-risk areas and determine the regions within these areas where landslides may occur. Therefore, by acquiring the distribution of the first target characteristic elements corresponding to the slope structure and lithology within the high-risk area, when the third and fourth distributions within the same area are concentrated, it indicates that the characteristic elements in that area have relatively little constraint on the rock mass boundary, meaning that the rock mass in that area is highly prone to landslides, thus constituting a potential landslide zone. In this way, by identifying potential landslide zones within high-risk areas and then identifying the individual rock masses within those zones, we can further reduce the number of rock masses that need to be identified, thereby improving identification efficiency, while also ensuring the accuracy of identifying potential landslide sites.

[0069] In some embodiments, elevation data and stratum attitude data within the prone area are acquired. Based on this elevation data and stratum attitude data, the prone area is gridded, and at least one characteristic element is determined when the geological environmental factors within the prone area constitute a slope structure. A third distribution is then determined based on each characteristic element corresponding to the slope structure.

[0070] In some embodiments, based on geological survey data, the distribution area of ​​stratigraphic lithology is determined, and the fourth distribution is determined accordingly.

[0071] In some embodiments, multiple landslide-prone areas can be merged and reorganized into a new landslide-prone area based on the distribution of these areas and their actual geographical distribution. For example, among the twelve bedding rock landslide-prone areas mentioned above, three are located in the same basin, and clastic rock dip slopes (slope structures highly prone to landslides) are also relatively concentrated in the periphery of the basin. Therefore, based on the distribution of each landslide-prone area, this embodiment studies the basin where multiple landslide-prone areas are relatively concentrated as a new landslide-prone area, focusing on clastic rock dip slopes near water, especially dip slopes developed in landslide-prone strata and affected by geological structures. Potential landslide-prone sections, i.e., potential hazard sections, are delineated in the main stream and important tributaries.

[0072] As shown in Table 3, this is the third data table. Table 3 shows the correspondence between each potential hazard section and the first target characteristic element when the geological environmental factors are slope structure and stratum lithology. The "first target characteristic element" in Table 3 refers to the first target characteristic element when the geological environmental factors are slope structure and stratum lithology. Specifically, the first target characteristic element when the geological environmental factor is slope structure includes dip and diagonal slopes. The first target characteristic when the geological environmental factor is stratum lithology includes slippery strata and lithology. For ease of understanding, Table 3 does not show the specific slippery strata and specific lithology when the geological environmental factor is stratum lithology. Additionally, Table 3 also shows that the first target characteristic element when the geological environmental factor is topography includes zigzag topography and monoclinic topography. Since this embodiment studies Reservoir Area A, each potential hazard section is located near the main stream or tributary, and water flow can also induce landslides. Therefore, Table 3 also shows the positional relationship between the potential hazard section and the water bank, i.e., the first target characteristic element is the water-adjacent slope. In Table 3, “Satisfactory Feature Elements” refers to the feature elements within the hidden danger section that successfully match the first target feature elements.

[0073] Table 3

[0074]

[0075] As shown in Table 3, the more characteristic elements a potential hazard section meets, the more likely it is to experience a landslide compared to other potential hazard sections, and therefore it requires special attention.

[0076] Understandably, this implementation obtains the first distribution of the first target feature element corresponding to the geological environmental factor of topography within the area to be identified, and the second distribution of the first target feature element corresponding to the geological environmental factor of geological structure. Areas where both the first and second distributions are concentrated are then designated as prone areas for newly formed bedding-parallel landslides. Furthermore, by obtaining the third distribution of the first target feature element corresponding to the geological environmental factor of slope structure within the prone area, and the fourth distribution of the first target feature element corresponding to the geological environmental factor of stratigraphy, areas where both the third and fourth distributions are concentrated are designated as potential hazard sections for newly formed bedding-parallel landslides. Then, all feature elements corresponding to each geological environmental factor for each rock mass within the potential hazard section are matched with each first target feature element of the same geological environmental factor to obtain the total number. Rock masses with a total number exceeding a preset threshold are identified as potential hazard points. In this way, based on geological environmental factors, the area to be identified is narrowed down to prone areas, then to hazardous sections, and finally to hazardous points. This step-by-step approach achieves the identification of newly formed bedding rock landslide hazards, balancing identification efficiency and accuracy. This improves the effectiveness of landslide disaster early warning and prevention.

[0077] Preferably, the method involves acquiring all characteristic elements of each geological environmental factor corresponding to each rock mass within the area to be identified, including: dividing the rock mass into multiple rock faces and determining at least one geological environmental factor corresponding to each rock face. This involves acquiring all characteristic elements corresponding to at least one geological environmental factor for each rock face of each rock mass within the area to be identified.

[0078] In this embodiment, the rock mass can be considered as a "six-faceted rock mass" developed in a natural slope, meaning the rock mass has six faces: surface, bottom, leading edge, trailing edge, and sides. Each face of the rock mass is subject to different boundary constraints, such as anti-sliding at the bottom, resisting at the leading edge, tensile strength at the trailing edge, and shear strength at the side boundaries. While the surface of the rock mass does not directly restrict sliding, its corresponding topography also influences whether a landslide will occur. Therefore, by determining the geological environmental factors corresponding to each face of the rock mass based on its different faces, the rock mass can be identified from both the constraints and influences it faces when sliding, allowing for a more accurate identification of newly formed bedding rock landslide hazards, i.e., hazard points.

[0079] For example, a rock mass consists of six faces. The geological environmental factors corresponding to the surface are mainly topography and landforms. The geological environmental factors corresponding to the bottom are mainly slope structure, stratigraphic lithology, and geological structure. The geological environmental factors corresponding to the leading edge are mainly topography and landforms. The geological environmental factors corresponding to the trailing edge are mainly topography, landforms, and geological structure. The geological environmental factors corresponding to both sides are mainly topography, landforms, and geological structure.

[0080] Preferably, the rock mass is divided into multiple rock faces, and at least one geological environmental factor corresponding to each rock face is determined. This includes: dividing the rock mass into multiple rock faces; and performing a search operation from a preset data table based on each rock face to find at least one geological environmental factor corresponding to each rock face; wherein the preset data table stores the correspondence between rock faces and geological environmental factors.

[0081] In this way, by looking up the table, the geological environmental factors corresponding to each rock surface of the rock mass can be determined, so as to obtain the relevant characteristic elements based on the geological environmental factors corresponding to each rock surface.

[0082] In some embodiments, the rock mass is considered as a hexahedron, and each face of the hexahedron is one of the six rock faces, also known as the six rock faces. Referring to Table 4, which is the fourth data table, Table 4 shows the correspondence between rock faces and geological environmental factors, as follows.

[0083] Table 4

[0084]

[0085] Preferably, for each rock mass, all feature elements of each geological environmental factor corresponding to the rock mass are matched with each first target feature element of the same geological environmental factor to determine a first number of successful matches between feature elements of each geological environmental factor and the first target feature elements. This includes: for each rock mass, matching all feature elements corresponding to at least one geological environmental factor of the current rock surface with each first target feature element of the same geological environmental factor to determine a second number of successful matches between feature elements of each geological environmental factor of the current rock surface and the first target feature elements. For each rock mass, the total number of the second number is taken as the first number.

[0086] Each rock face of a rock mass has specific geological environmental factors. By acquiring the characteristic elements corresponding to these specific geological environmental factors for each rock face and matching them with the primary target characteristic elements of the same geological environmental factors, a successful match indicates the presence of characteristic elements within the rock mass that could potentially lead to a landslide, meaning the rock mass boundary is relatively weak. Thus, by determining the number of successful matches for each rock mass, the primary number of characteristic elements potentially leading to a landslide within that rock mass is determined. This determines the degree of rock mass boundary constraint. It is understandable that a larger primary number indicates a weaker rock mass boundary constraint, making a landslide more likely.

[0087] For example, when the current rock face is the rear edge of a rock mass, the geological environmental factors include topography and geological structure. Specifically, when the rock face is the rear edge, the characteristic element of topography as the geological environmental factor is a zigzag topography; when the geological environmental factor is geological structure, the characteristic elements are regional fold abrupt change zones and strata dip zones. Based on the analysis of historical characteristic elements of multiple landslides that have occurred in the area to be identified, the first target characteristic elements when the geological environmental factor is topography include zigzag topography, monocline topography, and frontal freefall. The first target characteristic elements when the geological environmental factor is geological structure include regional fault zones and regional fold abrupt change zones. Matching the characteristic element corresponding to topography when the rock face is the rear edge (zigzag topography) with the target characteristic elements of the same geological environmental factor (zigzag topography, monocline topography, and frontal freefall) results in a single successful match. The geological environmental factors are determined by matching the characteristic elements corresponding to the geological structure (regional fold abrupt change zones and rock strata abrupt change zones) with the target characteristic elements of the same geological environmental factors (regional fault zones and regional fold abrupt change zones). A successful match is counted as one. Therefore, the second number of successful matches based on the leading edge rock surface of this rock mass is two. The second number of successful matches is calculated sequentially for each of the six faces of the rock mass and summed to obtain the first number.

[0088] Furthermore, the process involves matching all feature elements corresponding to at least one geological environmental factor of the current rock surface with each first target feature element of the same geological environmental factor to determine a second number of successful matches between feature elements of each geological environmental factor on the current rock surface and the first target feature elements. This includes: identifying the geological environmental factor corresponding to each rock surface as the target geological environmental factor; acquiring various historical feature elements of each rock surface in multiple landslides based on the corresponding target geological environmental factor, and determining the various historical feature elements of the target geological environmental factor for each rock surface; identifying historical feature elements of the same target geological environmental factor in each rock surface with a frequency greater than a preset frequency threshold as second target feature elements; and matching all feature elements corresponding to at least one target geological environmental factor of the current rock surface with each second target feature element of the target geological environmental factor of the same rock surface to determine a second number of successful matches between feature elements of each target geological environmental factor on the current rock surface and the second target feature elements.

[0089] In this way, based on the rock surface as the grouping basis, the historical characteristic elements corresponding to the target geological environmental factors of each rock surface are grouped, and the historical characteristic elements of the same target geological environmental factor in each rock surface with a frequency greater than a preset frequency threshold are designated as the second target characteristic elements. The second target characteristic elements are the characteristic elements that may lead to landslides. Then, the characteristic elements corresponding to the target geological environmental factors of each rock surface are matched with the second target characteristic elements corresponding to the target geological environmental factors of the same rock surface, thereby determining the characteristic elements in each rock surface of the rock mass that may lead to landslides. This allows for the determination of the total number of characteristic elements in the rock mass that may lead to landslides, i.e., the total number, thus determining the degree of boundary constraint of the rock mass.

[0090] For example, when the rock face is the rear edge, the target geological environmental factors include topography and geological structure. Based on the analysis of historical feature elements of multiple landslides that have occurred in the area to be identified, it is determined that when the rock face is the rear edge, the second target feature element corresponding to the topography as the target geological environmental factor includes zigzag topography, monocline topography, and frontal freefall; the second target feature element corresponding to the geological structure as the target geological environmental factor includes regional fault zones and regional fold abrupt transition zones. When the current rock face is the rear edge, the feature element corresponding to the topography as the target geological environmental factor is zigzag topography, and the feature element corresponding to the geological structure as the target geological environmental factor is regional fold abrupt transition zone. Therefore, when the current rock face is the rear edge, the feature element corresponding to the topography as the geological environmental factor (zigzag topography) is matched with the feature elements corresponding to the same target geological environmental factor (topography) of the same type of rock face (zigzag topography, monocline topography, and frontal freefall), and the number of successful matches is 1. Furthermore, the geological environment factor is matched with the characteristic elements corresponding to the geological structure (regional fold abrupt change zone) and the characteristic elements corresponding to the same target geological environment factor (geological structure) of the same rock surface (regional fault zone and regional fold abrupt change zone). The number of successful matches is 1. Then, when the current rock surface is the trailing edge, the number of successful matches is 2.

[0091] In some embodiments, Table 5 is used in conjunction with the fifth data table. Table 5 shows the correspondence between the rock surface and the target geological environment factors, and the second target characteristic elements pointed to by the target geological environment factors.

[0092] Table 5

[0093]

[0094] In some embodiments, a detailed field investigation is conducted on potential hazard points within Reservoir Area A. A more detailed field investigation is carried out at potential hazard points where new bedding rock landslides may occur, and on-site verification is conducted. The investigation focuses on the spatial boundary constraints of the dip slope, including the front edge resistance, the rear edge tensile resistance, the shear resistance on both sides, and the bottom anti-sliding resistance. The long-term effects of reservoir water on the development of slope joints and fissures and their correlation with the initial deformation development process of the slope are also investigated.

[0095] As shown in Table 6, the sixth data table, Table 6 illustrates the correspondence between potential hazard points and various geological environmental factors. In this embodiment, "geological environmental factors" include topography, geological structure, slope structure, slippery strata, and lithology. For ease of understanding, this embodiment actually breaks down the geological environmental factor of strata lithology into slippery strata and lithology. That is, if both slippery strata and lithology are satisfied, then the potential hazard point satisfies the geological environmental factor of strata lithology. It is understandable that, since this embodiment focuses on the on-site investigation of potential hazard points within Reservoir Area A, reservoir water will also affect the stability of the potential hazard points. Therefore, Table 6 also includes the effects of reservoir water and initial slope deformation as geological environmental factors to show the long-term effects of reservoir water on the development of slope joints and fissures and their correlation with the initial slope deformation development process. In this embodiment, "satisfied geological environmental factors" refers to the characteristic elements within the potential hazard point that match the first target characteristic element among the geological environmental factors.

[0096] Table 6

[0097]

[0098] As shown in Table 6, the more geological environmental factors a potential hazard point meets, the weaker its boundary constraint capacity, and the more prone it is to landslides compared to other potential hazard points.

[0099] Preferably, a method for identifying potential new landslide hazards further includes issuing early warnings based on hazard points. Thus, when the total number of characteristic elements corresponding to a rock mass exceeds a preset threshold, it indicates that the rock mass contains a large number of characteristic elements that could potentially lead to landslides, meaning it is prone to landslide hazards. Therefore, this rock mass is considered a hazard point, and an early warning is issued so that staff can conduct on-site investigations and verifications of the hazard point and implement relevant early warning and prevention measures.

[0100] Combination Figure 2As shown, this embodiment provides a new landslide hazard identification system 100. The system includes: a first acquisition module 101, a target module 102, a second acquisition module 103, a matching module 104, and a determination module 105. The first acquisition module is used to acquire the frequency of occurrence of different historical characteristic elements of the same geological environmental factor in multiple landslides within the area to be identified, prior to the landslide; the frequency of occurrence represents the number of times each historical characteristic element of the same geological environmental factor appeared within a preset time period before the landslide. The target module is used to select historical characteristic elements of the same geological environmental factor whose frequency of occurrence is greater than a preset frequency threshold as first target characteristic elements. The second acquisition module is used to acquire all characteristic elements of each geological environmental factor corresponding to each rock mass within the area to be identified. The matching module is used to match all characteristic elements of each geological environmental factor corresponding to each rock mass with each of the first target characteristic elements of the same geological environmental factor for each rock mass, determining a first number of successful matches between characteristic elements of each geological environmental factor and the first target characteristic elements. The determination module is used to obtain the total number of the first quantity corresponding to each rock mass. If the total number is greater than the preset quantity threshold, the rock mass is the target rock mass and the target rock mass is determined as a hidden danger point.

[0101] This embodiment employs a newly developed landslide hazard identification system. It acquires the frequency of occurrence of different historical characteristic elements of the same geological environmental factor in multiple landslides within a target area before the landslides occurred. Historical characteristic elements with a frequency exceeding a preset frequency threshold are designated as first target characteristic elements. This identifies common characteristic elements among multiple landslides within the target area, indicating that the first target characteristic elements are potential landslide-causing elements. The system then acquires all characteristic elements corresponding to each geological environmental factor for each rock mass within the target area. For each rock mass, all characteristic elements corresponding to each geological environmental factor are matched with the first target characteristic elements of the same geological environmental factor. A first number of successful matches between characteristic elements of each geological environmental factor and the first target characteristic elements is determined, thus identifying the number of potential landslide-causing characteristic elements present in each rock mass. The total number of these potential landslide-causing characteristic elements in each rock mass is then compared to a preset threshold. Rock masses with a number exceeding the preset threshold are identified as target rock masses. In other words, target rock masses containing a large number of potential landslide-causing characteristic elements are highly likely to experience a landslide. Therefore, the target rock mass was identified as a potential hazard point, namely a newly formed bedding rock landslide hazard.

[0102] In this way, by analyzing the characteristic elements of multiple landslides that have occurred within the area to be identified, the primary target characteristic elements that may lead to landslides are determined. Then, the characteristic elements of the rock mass are matched with the primary target characteristic elements to determine the number of primary target characteristic elements within the rock mass that may lead to landslides. When there are a large number of characteristic elements within the rock mass that may lead to landslides, it indicates that the boundary constraints on the rock mass are weak, meaning the probability of a landslide is high and there is a significant landslide hazard. This allows for more accurate identification of hazard points or newly formed bedding rock landslide hazards, thereby improving the effectiveness of landslide disaster early warning and prevention.

[0103] Preferably, the types of geological environmental factors include topography, geological structure, slope structure, and stratigraphic lithology.

[0104] Preferably, the second acquisition module includes a first acquisition unit, a high-risk area unit, and a second acquisition unit. The first acquisition unit is used to acquire, within the area to be identified, the first distribution of the first target feature element corresponding to the geological environmental factor being topography, and the second distribution of the first target feature element corresponding to the geological environmental factor being geological structure; wherein the distribution includes concentrated distribution and sparse distribution. The high-risk area unit is used to designate areas where both the first and second distributions are concentrated as high-risk areas. The second acquisition unit is used to acquire all feature elements corresponding to each geological environmental factor for each rock mass within the high-risk area.

[0105] Preferably, the second acquisition unit includes a first acquisition subunit, a hidden danger segment subunit, and a second acquisition subunit. The first acquisition subunit is used to acquire the third distribution of the first target characteristic element corresponding to the geological environmental factor of a slope structure within the prone area, and the fourth distribution of the first target characteristic element corresponding to the geological environmental factor of stratigraphic lithology. The hidden danger segment subunit is used to define areas where both the third and fourth distributions are concentrated as hidden danger segments. The second acquisition subunit is used to acquire all characteristic elements of each geological environmental factor corresponding to each rock mass within the hidden danger segment.

[0106] Preferably, the second acquisition module further includes a geological environmental factor unit and a third acquisition unit. The geological environmental factor unit is used to divide the rock mass into multiple rock faces and determine at least one geological environmental factor corresponding to each rock face. The third acquisition unit is used to acquire all feature elements corresponding to at least one geological environmental factor for each rock face of each rock mass within the area to be identified.

[0107] Preferably, the geological environmental factor unit is specifically used to divide the rock mass into multiple rock surfaces; based on each rock surface, a search operation is performed from a preset data table to find at least one geological environmental factor corresponding to each rock surface; wherein, the preset data table stores the correspondence between rock surfaces and geological environmental factors.

[0108] Preferably, the matching module includes a matching unit and a quantity unit. The matching unit, for each rock mass, matches all feature elements corresponding to at least one geological environmental factor corresponding to the current rock surface with each first target feature element of the same geological environmental factor, determining a second quantity of feature elements on the current rock surface that successfully match the first target feature elements for each geological environmental factor. The quantity unit, for each rock mass, uses the total of the second quantity as the first quantity.

[0109] A computing device according to an embodiment of the present invention includes a memory, a processor, and a program stored in the memory and running on the processor. When the processor executes the program, it implements some or all of the steps of the newly emerging landslide hazard identification method described above.

[0110] The computing device can be a computer, and the corresponding program is computer software. The parameters and steps in the computing device of the present invention can be referred to the parameters and steps in the embodiment of the method for identifying new landslide hazards shown above, and will not be repeated here.

[0111] This invention provides a computer-readable storage medium storing instructions that, when executed, perform the steps of the aforementioned method for identifying potential new landslide hazards.

[0112] The computer-readable storage medium may be a transient computer-readable storage medium or a non-transitory computer-readable storage medium.

[0113] The technical solution of this embodiment can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes one or more instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the method of this embodiment. The aforementioned computer-readable storage medium can be a non-transitory computer-readable storage medium, including: USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks, and other media capable of storing program code. It can also be a transient computer-readable storage medium.

[0114] Those skilled in the art will recognize that this invention can be implemented as a system, method, or computer program product. Therefore, this disclosure can be implemented in the following forms: it can be entirely hardware, entirely software (including firmware, resident software, microcode, etc.), or a combination of hardware and software, generally referred to herein as a "circuit," "module," or "system." Furthermore, in some embodiments, the invention can also be implemented as a computer program product contained in one or more computer-readable media, which contains computer-readable program code. Computer-readable storage media can be, for example, but not limited to—electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatuses, or devices, or any combination thereof.

[0115] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the present invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0116] Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of the present invention.

Claims

1. A method for identifying potential new landslide hazards, characterized in that, include: The frequency of occurrence of different historical characteristic elements of the same geological environmental factors in multiple landslides within the area to be identified before the landslide occurred is obtained; the frequency of occurrence represents the number of times each historical characteristic element of the same geological environmental factor occurred within a preset time period before the landslide occurred. Historical feature elements that occur more frequently than a preset frequency threshold in the same geological environmental factors are taken as the first target feature elements. Obtain all characteristic elements of each geological environmental factor corresponding to each rock mass within the area to be identified; For each rock mass, all feature elements of each geological environmental factor corresponding to the rock mass are matched with each of the first target feature elements of the same geological environmental factor, and a first number of feature elements of each geological environmental factor that are successfully matched with the first target feature elements are determined. Obtain the total number of the first quantity corresponding to each rock mass. If the total number is greater than a preset quantity threshold, then the rock mass is a target rock mass and the target rock mass is identified as a potential hazard point. The types of geological environmental factors include topography, geological structure, slope structure, and stratigraphic lithology; The process of acquiring all feature elements of each geological environmental factor corresponding to each rock mass within the area to be identified includes: Within the area to be identified, obtain the first distribution of the first target feature element when the geological environmental factor is the topography, and the second distribution of the first target feature element when the geological environmental factor is the geological structure; The region where both the first and second distribution scenarios are concentrated is designated as the prone area; Obtain all characteristic elements of each geological environmental factor corresponding to each rock mass in the prone area.

2. The method according to claim 1, characterized in that, The acquisition of all characteristic elements of each geological environmental factor corresponding to each rock mass in the prone area includes: Within the prone area, obtain the third distribution of the first target feature element when the geological environmental factor is the slope structure, and the fourth distribution of the first target feature element when the geological environmental factor is the lithology of the strata; The areas where both the third and fourth distribution scenarios are concentrated are designated as potential hazard segments; Obtain all characteristic elements of each geological environmental factor corresponding to each rock mass within the aforementioned hazardous section.

3. The method according to claim 1, characterized in that, The process of acquiring all feature elements of each geological environmental factor corresponding to each rock mass within the area to be identified includes: The rock mass is divided into multiple rock faces, and at least one geological environmental factor corresponding to each rock face is determined. Obtain all feature elements corresponding to at least one geological environmental factor for each rock surface of each rock mass within the area to be identified.

4. The method according to claim 3, characterized in that, The step of dividing the rock mass into multiple rock faces and determining at least one geological environmental factor corresponding to each rock face includes: The rock mass is divided into multiple rock faces; Based on each of the rock surfaces, a search operation is performed from a preset data table to find at least one geological environmental factor corresponding to each of the rock surfaces; wherein, the preset data table stores the correspondence between the rock surfaces and the geological environmental factors.

5. The method according to claim 3, characterized in that, For each rock mass, the process involves matching all characteristic elements of each geological environmental factor corresponding to the rock mass with each of the first target characteristic elements of the same geological environmental factor, and determining a first number of characteristic elements in each geological environmental factor that successfully match the first target characteristic elements, including: For each rock mass, all feature elements corresponding to at least one geological environmental factor corresponding to the current rock surface of the rock mass are matched with each of the first target feature elements of the same geological environmental factor to determine the second number of feature elements of each geological environmental factor of the current rock surface that are successfully matched with the first target feature elements. For each of the rock masses, the total number of the second quantity is taken as the first quantity.

6. A system for identifying potential new landslide hazards, characterized in that, include: The first acquisition module is used to acquire the frequency of occurrence of different historical characteristic elements of the same geological environmental factors in multiple landslides in the area to be identified before the landslide occurred; the frequency of occurrence represents the number of times each historical characteristic element of the same geological environmental factor occurred within a preset time period before the landslide occurred. The target module is used to select historical feature elements that occur more frequently than a preset frequency threshold in the same geological environmental factors as the first target feature elements. The second acquisition module is used to acquire all feature elements of each geological environmental factor corresponding to each rock mass in the area to be identified; The matching module is used to match all feature elements of each geological environmental factor corresponding to each rock mass with each first target feature element of the same geological environmental factor for each rock mass, and to determine the first number of feature elements of each geological environmental factor that are successfully matched with the first target feature elements. The determination module is used to obtain the total number of the first quantity corresponding to each rock mass. If the total number is greater than a preset quantity threshold, the rock mass is a target rock mass and the target rock mass is determined as a hidden danger point. The types of geological environmental factors include topography, geological structure, slope structure, and stratigraphic lithology. The second acquisition module includes a first acquisition unit, a high-risk area unit, and a second acquisition unit. The first acquisition unit is used to acquire, within the area to be identified, the first distribution of the first target feature element corresponding to the geological environmental factor of topography and the second distribution of the first target feature element corresponding to the geological environmental factor of geological structure. The distribution includes concentrated and sparse distribution. The high-risk area unit is used to designate areas where both the first and second distributions are concentrated as high-risk areas. The second acquisition unit is used to acquire all feature elements corresponding to each geological environmental factor for each rock mass within the high-risk area.

7. A computing device comprising a memory, a processor, and a program stored in the memory and running on the processor, characterized in that, When the processor executes the program, it implements the steps of the method for identifying potential new landslide hazards as described in any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores instructions that, when executed on a terminal device, cause the terminal device to perform the steps of a method for identifying potential new landslide hazards as described in any one of claims 1 to 5.

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