Geological disaster short-term and temporary early warning method and system

Abstract

The invention provides a geological disaster short-term and temporary early warning method and system, and the method comprises the steps: obtaining a historical geological disaster case, and generating a corresponding geological disaster sample according to the historical geological disaster case; generating a corresponding target risk early warning model in real time according to the geological disaster sample based on a first preset rule, and obtaining a target early warning area input by a user in real time; obtaining target grid data corresponding to the target early warning area in real time based on a second preset rule, and extracting a plurality of grid points correspondingly contained in the target grid data in real time; and calculating a disaster-causing rainfall level corresponding to each grid point in real time, and matching geological disaster susceptibility degrees corresponding to the grid points so as to determine corresponding geological disaster risk levels. According to the invention, the meteorological disaster grade of each small region can be predicted quickly and effectively, and the working efficiency is correspondingly improved.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and in particular to a method and system for short-term warning of geological disasters. Background Art

[0002] With the advancement of science and technology and the rapid development of productivity, people's early warning technology for geological disasters has become increasingly mature, and corresponding early warning systems have been developed to generate corresponding early warning information in real time so that people can take corresponding preventive measures.

[0003] Among them, in the process of geological disaster early warning, most of the existing technologies will collect geological data, geological disaster data, meteorological data and other information in real time to determine the critical rainfall of geological disasters, and conduct a comprehensive analysis of meteorological forecast information and geological environment information to carry out risk warnings for geological disaster meteorology.

[0004] Furthermore, the warning period generated by the prior art through the above method is mostly 1 day or more, and the warning area is mostly a large county or city. However, the time and space resolutions corresponding to this warning method are not fine enough, that is, the predicted time period and prediction range are not fine enough, which is prone to false alarms and missed alarms, which will lead to unnecessary temporary avoidance, thereby reducing the efficiency of the warning work. Summary of the invention

[0005] Based on this, the purpose of the present invention is to provide a geological disaster short-term warning method and system to solve the problem that the existing technology has insufficient temporal and spatial resolution of geological disasters, which leads to false alarms and missed alarms.

[0006] The first aspect of the embodiment of the present invention proposes: A method for short-term early warning of geological disasters, wherein the method comprises: Obtain historical geological disaster cases, and generate corresponding geological disaster samples based on the historical geological disaster cases; Generate a corresponding target risk warning model in real time according to the geological disaster sample based on the first preset rule, and obtain the target warning area input by the user in real time; Based on the second preset rule, target grid data corresponding to the target warning area is acquired in real time, and a number of grid points corresponding to the target grid data are extracted in real time; The target risk warning model is used to calculate in real time the disaster-causing rainfall level corresponding to each of the grid points, and the geological disaster susceptibility corresponding to the grid points is matched in real time in a preset database, so as to determine the corresponding geological disaster risk level in real time according to the disaster-causing rainfall level and the geological disaster susceptibility and issue a real-time warning, and each of the grid points is unique.

[0007] The beneficial effect of the present invention is that by acquiring historical geological disaster cases, geological disaster samples for subsequent training can be generated accordingly. Based on this, the required target risk warning model can be further trained through the existing training method. Specifically, in order to automatically complete the subsequent identification, it is necessary to further receive the target warning area input by the user. Based on this, the disaster-causing rainfall level corresponding to each current grid point can be further detected in real time, so that the degree of meteorological disaster in the current target warning area can be obtained accordingly. Based on this, the corresponding disaster level can be finally generated according to the early warning platform constructed in real time, and the corresponding real-time early warning can be completed, so that the rapid early warning of each small area can be completed in a short time and quickly, which correspondingly improves work efficiency.

[0008] Furthermore, the step of acquiring target grid data corresponding to the target warning area in real time based on the second preset rule includes: When the target warning area is acquired in real time, the target warning area is fully scanned to match a target area map adapted to the target warning area in a preset map database in real time; Real-time detection of a first endpoint located at the northernmost end, a second endpoint located at the southernmost end, a third endpoint located at the easternmost end, and a fourth endpoint located at the westernmost end in the target area map; The target latitudes corresponding to the first endpoint and the second endpoint are detected respectively, and the target longitudes corresponding to the third endpoint and the fourth endpoint are detected in real time, so as to perform grid division processing on the target warning area according to the target latitude and the target longitude in real time, and generate the target grid data accordingly.

[0009] Furthermore, the step of performing grid division processing on the target warning area according to the target latitude and the target longitude in real time and correspondingly generating the target grid data includes: When the target latitude and the target longitude are respectively obtained, the target latitude and the target longitude are respectively used as corresponding grid division starting points; Performing a grid division process on the target warning area according to the grid division starting point at a preset division interval, so as to form a plurality of target grids correspondingly inside the target warning area; The target grids are analyzed and processed to generate the target grid data accordingly.

[0010] Furthermore, the step of performing parsing processing on the plurality of target grids to generate the target grid data accordingly includes: When a plurality of target grids are acquired in real time, a grid area corresponding to each target grid is detected in real time; Splitting the target grid into a plurality of grid points according to the grid area, each of the grid points having a size of one square kilometer; The precipitation information corresponding to each of the grid points is detected in real time in a preset meteorological database, and each of the grid points and the precipitation information corresponding thereto are integrated and processed to generate the target grid data accordingly.

[0011] Furthermore, the step of calculating the disaster-causing rainfall level corresponding to each of the grid points in real time through the target risk warning model includes: When the grid point is acquired in real time, the target precipitation information corresponding to the grid point is matched in real time in the target grid data; Extracting the actual precipitation and the forecast precipitation corresponding to the grid point in real time according to the target precipitation information; The disaster-causing rainfall level corresponding to the grid point is calculated in real time according to the actual precipitation and the forecast precipitation.

[0012] Furthermore, the step of calculating the disaster-causing rainfall level corresponding to the grid point in real time according to the actual precipitation and the forecast precipitation includes: When the actual precipitation and the forecast precipitation are respectively obtained, the corresponding preset algorithm is called out in real time; The effective rainfall corresponding to the grid point is calculated in real time according to the actual rainfall and the forecast rainfall by the preset algorithm, and the effective rainfall is compared with the preset disaster-causing rainfall in real time to determine the disaster-causing rainfall level corresponding to the grid point in real time; The disaster-causing rainfall level is matched accordingly in a preset risk level table according to the disaster-causing rainfall level, and the disaster-causing rainfall level is unique.

[0013] Furthermore, the expression of the preset algorithm is:

[0014] Among them, r a represents the effective rainfall, i represents the rainfall time, r i represents the rainfall on the i-th day, k represents the effective rainfall coefficient, and n represents the time of effective rainfall.

[0015] The second aspect of the embodiment of the present invention proposes: A geological disaster short-term warning system, wherein the system comprises: An acquisition module is used to acquire historical geological disaster cases and generate corresponding geological disaster samples according to the historical geological disaster cases; A first processing module is used to generate a corresponding target risk warning model according to the geological disaster sample in real time based on a first preset rule, and obtain a target warning area input by a user in real time; A second processing module is used to obtain target grid data corresponding to the target warning area in real time based on a second preset rule, and extract a number of corresponding grid points contained in the target grid data in real time; The early warning module is used to calculate the disaster-causing rainfall level corresponding to each of the grid points in real time through the target risk early warning model, and match the geological disaster susceptibility corresponding to the grid point in real time in a preset database, so as to determine the corresponding geological disaster risk level in real time according to the disaster-causing rainfall level and the geological disaster susceptibility and issue a real-time early warning, and each of the grid points is unique.

[0016] Furthermore, the second processing module is specifically used for: When the target warning area is acquired in real time, the target warning area is fully scanned to match a target area map adapted to the target warning area in a preset map database in real time; Real-time detection of a first endpoint located at the northernmost end, a second endpoint located at the southernmost end, a third endpoint located at the easternmost end, and a fourth endpoint located at the westernmost end in the target area map; The target latitudes corresponding to the first endpoint and the second endpoint are detected respectively, and the target longitudes corresponding to the third endpoint and the fourth endpoint are detected in real time, so as to perform grid division processing on the target warning area according to the target latitude and the target longitude in real time, and generate the target grid data accordingly.

[0017] Furthermore, the second processing module is specifically used for: When the target latitude and the target longitude are respectively obtained, the target latitude and the target longitude are respectively used as corresponding grid division starting points; Performing a grid division process on the target warning area according to the grid division starting point at a preset division interval, so as to form a plurality of target grids correspondingly inside the target warning area; The target grids are analyzed and processed to generate the target grid data accordingly.

[0018] Furthermore, the second processing module is specifically used for: When a plurality of target grids are acquired in real time, a grid area corresponding to each target grid is detected in real time; Splitting the target grid into a plurality of grid points according to the grid area, each of the grid points having a size of one square kilometer; The precipitation information corresponding to each of the grid points is detected in real time in a preset meteorological database, and each of the grid points and the precipitation information corresponding thereto are integrated and processed to generate the target grid data accordingly.

[0019] Furthermore, the early warning module is specifically used for: When the grid point is acquired in real time, the target precipitation information corresponding to the grid point is matched in real time in the target grid data; Extracting the actual precipitation and the forecast precipitation corresponding to the grid point in real time according to the target precipitation information; The disaster-causing rainfall level corresponding to the grid point is calculated in real time according to the actual precipitation and the forecast precipitation.

[0020] Furthermore, the early warning module is specifically used for: When the actual precipitation and the forecast precipitation are respectively obtained, the corresponding preset algorithm is called out in real time; The effective rainfall corresponding to the grid point is calculated in real time according to the actual rainfall and the forecast rainfall by the preset algorithm, and the effective rainfall is compared with the preset disaster-causing rainfall in real time to determine the disaster-causing rainfall level corresponding to the grid point in real time; The disaster-causing rainfall level is matched accordingly in a preset risk level table according to the disaster-causing rainfall level, and the disaster-causing rainfall level is unique.

[0021] Furthermore, the expression of the preset algorithm is:

[0022] Among them, r a represents the effective rainfall, i represents the rainfall time, r i represents the rainfall on the i-th day, k represents the effective rainfall coefficient, and n represents the time of effective rainfall.

[0023] The third aspect of the embodiment of the present invention proposes: A computer comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor implements the above-described short-term warning method for geological disasters when executing the computer program.

[0024] The fourth aspect of the embodiments of the present invention proposes: A readable storage medium stores a computer program, wherein when the program is executed by a processor, the method for short-term warning of geological disasters as described above is implemented.

[0025] Additional aspects and advantages of the present invention will be given in part in the following description and in part will be obvious from the following description, or will be learned through practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 A flow chart of a method for short-term early warning of geological disasters provided by a first embodiment of the present invention; Figure 2 This is a structural block diagram of a geological disaster short-term warning system provided in the third embodiment of the present invention.

[0027] The following specific implementation manner will further illustrate the present invention in conjunction with the above-mentioned drawings. DETAILED DESCRIPTION

[0028] In order to facilitate the understanding of the present invention, the present invention will be described more fully below with reference to the relevant drawings. Several embodiments of the present invention are given in the drawings. However, the present invention can be implemented in many different forms and is not limited to the embodiments described herein. On the contrary, the purpose of providing these embodiments is to make the disclosure of the present invention more thorough and comprehensive.

[0029] It should be noted that when an element is referred to as being "fixed to" another element, it may be directly on the other element or there may be a central element. When an element is considered to be "connected to" another element, it may be directly connected to the other element or there may be a central element at the same time. The terms "vertical", "horizontal", "left", "right" and similar expressions used herein are for illustrative purposes only.

[0030] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art to which the present invention belongs. The terms used herein in the specification of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention. The term "and / or" used herein includes any and all combinations of one or more of the related listed items.

[0031] See also Figure 1 , shown is a short-term warning method for geological disasters provided by the first embodiment of the present invention. The short-term warning method for geological disasters provided in this embodiment can quickly and effectively complete geological disaster warnings in small areas, correspondingly improving the warning accuracy and improving work efficiency.

[0032] Specifically, this embodiment provides: A method for short-term early warning of geological disasters specifically comprises the following steps: Step S10, obtaining historical geological disaster cases, and generating corresponding geological disaster samples according to the historical geological disaster cases; Step S20, generating a corresponding target risk warning model according to the geological disaster sample in real time based on the first preset rule, and obtaining the target warning area input by the user in real time; Step S30, acquiring target grid data corresponding to the target warning area in real time based on a second preset rule, and extracting a number of grid points corresponding to the target grid data in real time; Step S40, the target risk warning model is used to calculate in real time the disaster-causing rainfall level corresponding to each of the grid points, and the geological disaster susceptibility corresponding to the grid points is matched in real time in the preset database, so as to determine the corresponding geological disaster risk level in real time according to the disaster-causing rainfall level and the geological disaster susceptibility and make a real-time warning, and each of the grid points is unique.

[0033] Specifically, in this embodiment, it should be noted that in order to quickly and effectively provide real-time warnings for each small area, a warning platform needs to be created accordingly, wherein the meteorological information of each small area only needs to be input into the current warning platform, and the corresponding warning information can be automatically output, so that the staff can take corresponding preventive measures. It should be pointed out that the existing precipitation information can reflect the probability of geological disasters. Based on this, the geological disaster short-term warning method provided by the present invention is to complete the subsequent prediction by analyzing the rainfall data of each area in real time. Based on this, in order to facilitate subsequent implementation, the present invention will first screen out geological disaster cases caused by rainfall in real time in the existing meteorological database, and the geological disaster cases will retain accurate records of the time of disaster occurrence. At the same time, the present invention will further match the quantitative rainfall estimation data with a spatial resolution of one thousand meters that is adapted to the current geological disaster cases in real time in the above-mentioned meteorological database, and can integrate and process the current two types of data to further form the required geological disaster samples. It should be pointed out that the geological disaster samples contain clear date information and longitude and latitude information. At the same time, the present invention will also statistically analyze the cumulative frequency of geological disaster disaster samples in real time, and divide the corresponding disaster-causing rainfall levels according to the probability of effective rainfall causing disasters of 50%, 30%, 15% and 5%, for subsequent processing.

[0034] Further, after obtaining the required geological disaster samples in real time through the above steps, the subsequent training can be completed accordingly to further obtain the required target risk warning model. Based on this, subsequent prediction processing can be carried out. Specifically, a prediction target needs to be accurately determined, that is, the target warning area input by the user needs to be obtained in real time. At the same time, the target grid data corresponding to the current target warning area is obtained in real time according to the pre-set second preset rule, and a number of required grid points can be further extracted from the internal correspondence of the current target grid data. On this basis, the present invention will further calculate the disaster-causing rainfall level corresponding to each current grid point. At the same time, the current disaster-causing rainfall level and the current target risk warning model are immediately integrated and processed, and the required warning platform can be further constructed. Specifically, it should be pointed out that the warning platform is a cloud platform. In its daily work process, the warning platform can receive the corresponding meteorological data generated in each region in real time, and analyze the probability of geological disasters in correspondence to carry out subsequent warnings. In addition, it should be noted that, considering that the geological environment has small temporal and spatial changes, it can be used as a static background, while precipitation changes dynamically day by day and hour by hour. Therefore, the geological disaster-prone zoning and the possibility of dynamic precipitation inducing geological disasters are combined to calculate the geological disaster-causing rainfall level. Based on this, the present invention will take the geological disaster-prone areas as the basic prone areas, and the medium prone areas and low prone areas will decrease step by step. By comparing the disaster-causing rainfall level of the effective rainfall, the geological disaster-causing rainfall level can be finally determined, and corresponding warning information can be further generated according to the geological disaster-causing rainfall level, and sent to the user accordingly. Therefore, the present invention can accurately predict the geological disaster level within each kilometer, and can generate corresponding warning information every few hours, which correspondingly improves work efficiency.

[0035] Second embodiment Furthermore, the step of acquiring target grid data corresponding to the target warning area in real time based on the second preset rule includes: When the target warning area is acquired in real time, the target warning area is fully scanned to match a target area map adapted to the target warning area in a preset map database in real time; Real-time detection of a first endpoint located at the northernmost end, a second endpoint located at the southernmost end, a third endpoint located at the easternmost end, and a fourth endpoint located at the westernmost end in the target area map; The target latitudes corresponding to the first endpoint and the second endpoint are detected respectively, and the target longitudes corresponding to the third endpoint and the fourth endpoint are detected in real time, so as to perform grid division processing on the target warning area according to the target latitude and the target longitude in real time, and generate the target grid data accordingly.

[0036] Furthermore, the step of performing grid division processing on the target warning area according to the target latitude and the target longitude in real time and correspondingly generating the target grid data includes: When the target latitude and the target longitude are respectively obtained, the target latitude and the target longitude are respectively used as corresponding grid division starting points; Performing a grid division process on the target warning area according to the grid division starting point at a preset division interval, so as to form a plurality of target grids correspondingly inside the target warning area; The target grids are analyzed and processed to generate the target grid data accordingly.

[0037] Furthermore, the step of performing parsing processing on the plurality of target grids to generate the target grid data accordingly includes: When a plurality of target grids are acquired in real time, a grid area corresponding to each target grid is detected in real time; Splitting the target grid into a plurality of grid points according to the grid area, each of the grid points having a size of one square kilometer; The precipitation information corresponding to each of the grid points is detected in real time in a preset meteorological database, and each of the grid points and the precipitation information corresponding thereto are integrated and processed to generate the target grid data accordingly.

[0038] Furthermore, the step of calculating the disaster-causing rainfall level corresponding to each of the grid points in real time through the target risk warning model includes: When the grid point is acquired in real time, the target precipitation information corresponding to the grid point is matched in real time in the target grid data; Extracting the actual precipitation and the forecast precipitation corresponding to the grid point in real time according to the target precipitation information; The disaster-causing rainfall level corresponding to the grid point is calculated in real time according to the actual precipitation and the forecast precipitation.

[0039] Furthermore, the step of calculating the disaster-causing rainfall level corresponding to the grid point in real time according to the actual precipitation and the forecast precipitation includes: When the actual precipitation and the forecast precipitation are respectively obtained, the corresponding preset algorithm is called out in real time; The effective rainfall corresponding to the grid point is calculated in real time according to the actual rainfall and the forecast rainfall by the preset algorithm, and the effective rainfall is compared with the preset disaster-causing rainfall in real time to determine the disaster-causing rainfall level corresponding to the grid point in real time; The disaster-causing rainfall level is matched accordingly in a preset risk level table according to the disaster-causing rainfall level, and the disaster-causing rainfall level is unique.

[0040] Furthermore, the expression of the preset algorithm is:

[0041] Among them, r a represents the effective rainfall, i represents the rainfall time, r i represents the rainfall on the i-th day, k represents the effective rainfall coefficient, and n represents the time of effective rainfall.

[0042] In addition, in this embodiment, it is also necessary to explain that after the target prediction area is acquired in real time through the above steps, it is necessary to further parse and process the current target prediction area to further acquire the required target grid data. Preferably, the present invention will first perform a full scan of the current target prediction area, so as to determine the size and shape of the current target prediction area. Based on this, a target area map corresponding to the current target prediction area in a one-to-one ratio can be further matched in real time in the existing map database. Based on this, the northernmost, southernmost, easternmost and westernmost ends corresponding to the current target prediction area can be quickly detected according to the target area map, and the corresponding first endpoint, second endpoint, third endpoint and fourth endpoint can be detected respectively. At the same time, the current first endpoint and second endpoint are used as the starting latitude, and the current third endpoint and fourth endpoint are used as the starting longitude, and the current target is matched in real time according to the division interval of 0.01°. The target prediction area is gridded, so that a number of target grids can be formed in the current target prediction area. Based on this, in order to further obtain the target grid data corresponding to the current target prediction area, the present invention will further detect the grid area corresponding to the current target grid, and further split the current target grid into a number of grid points of only one square kilometer in size according to the size of the current grid area. At the same time, the precipitation information corresponding to each current grid point can be extracted in real time from the existing meteorological database, that is, the historical precipitation information of the current grid point. Based on this, it is only necessary to integrate each current grid point and the precipitation information corresponding to it, so as to generate the required target grid data in real time for subsequent processing.

[0043] Furthermore, after the required target grid data is acquired in real time through the above steps, a number of grid points corresponding to the current target grid data can be extracted. In order to determine the disaster-causing rainfall level corresponding to each grid point in real time, the present invention preferably further extracts the actual precipitation that has occurred in the past 6 hours and the forecast precipitation that will occur in the next 6 hours for the current grid point through the above meteorological database. Based on this, the present invention further inputs the current actual precipitation and the forecast precipitation into the above preset algorithm, and can further output the effective rainfall adapted to the current grid point in real time through the preset algorithm, that is, when The actual rainfall generated by the previous grid point is based on this, and the present invention will further compare the effective rainfall of the current grid point with the pre-set disaster-causing rainfall in real time, so as to determine the disaster-causing rainfall level corresponding to the effective rainfall of the current grid point. It should be noted that the disaster-causing rainfall level and the susceptibility of geological disasters at the current grid point can directly determine the disaster-causing rainfall level of geological disasters at the current grid point. Based on this, the present invention will further match the current disaster-causing rainfall level with the preset meteorological disaster level table in real time, and can finally match the disaster-causing rainfall level corresponding to each current grid point, so as to quickly and accurately complete the subsequent early warning, thereby correspondingly improving work efficiency.

[0044] See also Figure 2 , the third embodiment of the present invention provides: A geological disaster short-term warning system, wherein the system comprises: An acquisition module is used to acquire historical geological disaster cases and generate corresponding geological disaster samples according to the historical geological disaster cases; A first processing module is used to generate a corresponding target risk warning model according to the geological disaster sample in real time based on a first preset rule, and obtain a target warning area input by a user in real time; A second processing module is used to obtain target grid data corresponding to the target warning area in real time based on a second preset rule, and extract a number of corresponding grid points contained in the target grid data in real time; The early warning module is used to calculate the disaster-causing rainfall level corresponding to each of the grid points in real time through the target risk early warning model, and match the geological disaster susceptibility corresponding to the grid point in real time in a preset database, so as to determine the corresponding geological disaster risk level in real time according to the disaster-causing rainfall level and the geological disaster susceptibility and issue a real-time early warning, and each of the grid points is unique.

[0045] Furthermore, the second processing module is specifically used for: When the target warning area is acquired in real time, the target warning area is fully scanned to match a target area map adapted to the target warning area in a preset map database in real time; Real-time detection of a first endpoint located at the northernmost end, a second endpoint located at the southernmost end, a third endpoint located at the easternmost end, and a fourth endpoint located at the westernmost end in the target area map; The target latitudes corresponding to the first endpoint and the second endpoint are detected respectively, and the target longitudes corresponding to the third endpoint and the fourth endpoint are detected in real time, so as to perform grid division processing on the target warning area according to the target latitude and the target longitude in real time, and generate the target grid data accordingly.

[0046] Furthermore, the second processing module is specifically used for: When the target latitude and the target longitude are respectively obtained, the target latitude and the target longitude are respectively used as corresponding grid division starting points; Performing a grid division process on the target warning area according to the grid division starting point at a preset division interval, so as to form a plurality of target grids correspondingly inside the target warning area; The target grids are analyzed and processed to generate the target grid data accordingly.

[0047] Furthermore, the second processing module is specifically used for: When a plurality of target grids are acquired in real time, a grid area corresponding to each target grid is detected in real time; Splitting the target grid into a plurality of grid points according to the grid area, each of the grid points having a size of one square kilometer; The precipitation information corresponding to each of the grid points is detected in real time in a preset meteorological database, and each of the grid points and the precipitation information corresponding thereto are integrated and processed to generate the target grid data accordingly.

[0048] Furthermore, the early warning module is specifically used for: When the grid point is acquired in real time, the target precipitation information corresponding to the grid point is matched in real time in the target grid data; Extracting the actual precipitation and the forecast precipitation corresponding to the grid point in real time according to the target precipitation information; The disaster-causing rainfall level corresponding to the grid point is calculated in real time according to the actual precipitation and the forecast precipitation.

[0049] Furthermore, the early warning module is specifically used for: When the actual precipitation and the forecast precipitation are respectively obtained, the corresponding preset algorithm is called out in real time; The effective rainfall corresponding to the grid point is calculated in real time according to the actual rainfall and the forecast rainfall by the preset algorithm, and the effective rainfall is compared with the preset disaster-causing rainfall in real time to determine the disaster-causing rainfall level corresponding to the grid point in real time; The disaster-causing rainfall level is matched accordingly in a preset risk level table according to the disaster-causing rainfall level, and the disaster-causing rainfall level is unique.

[0050] Furthermore, the expression of the preset algorithm is:

[0051] Among them, r a represents the effective rainfall, i represents the rainfall time, r i represents the rainfall on the i-th day, k represents the effective rainfall coefficient, and n represents the time of effective rainfall.

[0052] The fourth embodiment of the present invention provides a computer, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the method for short-term warning of geological disasters as described above when executing the computer program.

[0053] The fifth embodiment of the present invention provides a readable storage medium having a computer program stored thereon, wherein the program, when executed by a processor, implements the method for short-term warning of geological disasters as described above.

[0054] In summary, the geological disaster short-term warning method and system provided by the above embodiments of the present invention can quickly and effectively complete disaster warnings in small areas, thereby correspondingly improving the warning accuracy and work efficiency.

[0055] It should be noted that the above modules can be functional modules or program modules, and can be implemented by software or hardware. For modules implemented by hardware, the above modules can be located in the same processor; or the above modules can be located in different processors in any combination.

[0056] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in conjunction with such instruction execution systems, devices or apparatuses. For the purposes of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in conjunction with such instruction execution systems, devices or apparatuses.

[0057] More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk case (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be a paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering or, if necessary, processing in another suitable manner, and then stored in a computer memory.

[0058] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0059] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0060] The above-described embodiments only express several implementation methods of the present invention, and the description thereof is relatively specific and detailed, but it cannot be understood as limiting the scope of the present invention. It should be pointed out that, for a person of ordinary skill in the art, several modifications and improvements can be made without departing from the concept of the present invention, and these all belong to the protection scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the attached claims.

Claims

1. A short-term early warning method for geological disasters, characterized in that: The method comprises: Obtain historical geological disaster cases, and generate corresponding geological disaster samples based on the historical geological disaster cases; Generate a corresponding target risk warning model in real time according to the geological disaster sample based on the first preset rule, and obtain the target warning area input by the user in real time; Based on the second preset rule, target grid data corresponding to the target warning area is acquired in real time, and a number of grid points corresponding to the target grid data are extracted in real time; The target risk warning model is used to calculate the disaster-causing rainfall level corresponding to each of the grid points in real time, and the geological disaster susceptibility corresponding to the grid points is matched in real time in a preset database, so as to determine the corresponding geological disaster risk level in real time according to the disaster-causing rainfall level and the geological disaster susceptibility and make a real-time warning, and each of the grid points is unique; The step of acquiring target grid data corresponding to the target warning area in real time based on the second preset rule comprises: When the target warning area is acquired in real time, the target warning area is fully scanned to match a target area map adapted to the target warning area in a preset map database in real time; Real-time detection of a first endpoint located at the northernmost end, a second endpoint located at the southernmost end, a third endpoint located at the easternmost end, and a fourth endpoint located at the westernmost end in the target area map; The target latitudes corresponding to the first endpoint and the second endpoint are detected respectively, and the target longitudes corresponding to the third endpoint and the fourth endpoint are detected in real time, so as to perform grid division processing on the target warning area according to the target latitude and the target longitude in real time, and generate the target grid data accordingly.

2. The method for short-term early warning of geological disasters according to claim 1 is characterized in that: The step of performing grid division processing on the target warning area according to the target latitude and the target longitude in real time and correspondingly generating the target grid data comprises: When the target latitude and the target longitude are respectively obtained, the target latitude and the target longitude are respectively used as corresponding grid division starting points; Performing a grid division process on the target warning area according to the grid division starting point at a preset division interval, so as to form a plurality of target grids correspondingly inside the target warning area; The target grids are analyzed and processed to generate the target grid data accordingly.

3. The method for short-term early warning of geological disasters according to claim 2 is characterized in that: The step of performing parsing processing on the plurality of target grids to generate the target grid data accordingly comprises: When a plurality of target grids are acquired in real time, a grid area corresponding to each target grid is detected in real time; Splitting the target grid into a plurality of grid points according to the grid area, each of the grid points having a size of one square kilometer; The precipitation information corresponding to each of the grid points is detected in real time in a preset meteorological database, and each of the grid points and the precipitation information corresponding thereto are integrated and processed to generate the target grid data accordingly.

4. The method for short-term early warning of geological disasters according to claim 3 is characterized in that: The step of calculating the disaster-causing rainfall level corresponding to each of the grid points in real time through the target risk warning model comprises: When the grid point is acquired in real time, the target precipitation information corresponding to the grid point is matched in real time in the target grid data; Extracting the actual precipitation and the forecast precipitation corresponding to the grid point in real time according to the target precipitation information; The disaster-causing rainfall level corresponding to the grid point is calculated in real time according to the actual precipitation and the forecast precipitation.

5. The method for short-term early warning of geological disasters according to claim 4 is characterized in that: The step of calculating the disaster-causing rainfall level corresponding to the grid point in real time according to the actual precipitation and the forecast precipitation comprises: When the actual precipitation and the forecast precipitation are respectively obtained, the corresponding preset algorithm is called out in real time; The effective rainfall corresponding to the grid point is calculated in real time according to the actual rainfall and the forecast rainfall by the preset algorithm, and the effective rainfall is compared with the preset disaster-causing rainfall in real time to determine the disaster-causing rainfall level corresponding to the grid point in real time; The disaster-causing rainfall level is matched accordingly in a preset risk level table according to the disaster-causing rainfall level, and the disaster-causing rainfall level is unique.

6. The method for short-term early warning of geological disasters according to claim 5 is characterized in that: The expression of the preset algorithm is: Among them, r a represents the effective rainfall, i represents the rainfall time, r i represents the rainfall on the i-th day, k represents the effective rainfall coefficient, and n represents the time of effective rainfall.

7. A geological disaster short-term warning system, characterized in that: Used to implement the geological disaster short-term warning method according to any one of claims 1 to 6, the system comprises: An acquisition module is used to acquire historical geological disaster cases and generate corresponding geological disaster samples according to the historical geological disaster cases; A first processing module is used to generate a corresponding target risk warning model according to the geological disaster sample in real time based on a first preset rule, and obtain a target warning area input by a user in real time; A second processing module is used to obtain target grid data corresponding to the target warning area in real time based on a second preset rule, and extract a number of corresponding grid points contained in the target grid data in real time; The early warning module is used to calculate the disaster-causing rainfall level corresponding to each of the grid points in real time through the target risk early warning model, and match the geological disaster susceptibility corresponding to the grid point in real time in a preset database, so as to determine the corresponding geological disaster risk level in real time according to the disaster-causing rainfall level and the geological disaster susceptibility and issue a real-time early warning, and each of the grid points is unique.

8. A computer comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the method for short-term warning of geological disasters as described in any one of claims 1 to 6 is implemented.

9. A readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the method for short-term warning of geological disasters as described in any one of claims 1 to 6 is implemented.

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