Satellite image feedback-based landslide monitoring apparatus and method, terminal, device, and medium

Abstract

A satellite image feedback-based landslide monitoring apparatus and method, a terminal, a device, and a medium, which relate to the technical field of geological disaster data monitoring. The monitoring method comprises: delineating a geological disaster investigation range selected in a satellite image, and on said basis, arranging a satellite image feedback-based landslide monitoring apparatus on site; monitoring deformation and stress in slope evolution, feeding back real-time data to an indoor satellite image interpretation terminal, carrying out repeated training on the established learning model, and establishing a relationship between a migration element of an on-site slope and pixel change in the satellite image; and monitoring and issuing early warning for an on-site landslide disaster on the basis of a preprogrammed safety threshold value. In the described monitoring method, information related to disaster-prone areas, including geological strata, geological structures, surface erosion, meteorological conditions, and groundwater is systematically monitored. Typical characteristics of the monitored disaster points are provided from an engineering geological perspective and such features are integrated into specific indicators such as strain and stress, thereby establishing a relationship between deformation and stress indicators and pixel change in the satellite image.

Description

Landslide monitoring device, method, terminal, equipment and medium based on satellite image feedback

[0001] This application claims priority to the Chinese patent application filed with the China Patent Office on May 16, 2022, with application number 202210526838.9 and invention name “Landslide monitoring device, method, terminal, equipment and medium based on satellite image feedback”, the entire contents of which are incorporated by reference into this application. Technical Field

[0002] The present invention belongs to the technical field of geological disaster data monitoring, and in particular relates to a landslide monitoring device, method, terminal, equipment and medium based on satellite image feedback. Background Art

[0003] Geological hazards in mountainous areas are primarily collapses, landslides, and debris flows. While systematic research has been conducted on the causal mechanisms and preventative measures for these hazards, early identification plays a crucial role in disaster prevention. Currently, the most commonly used method involves on-site monitoring of existing hazards to prevent their further expansion. The identification of potentially unstable hazard sites is primarily conducted through rough manual inspections. However, due to factors such as the complexity of the terrain and the accumulated experience of personnel, some potentially catastrophic sites are overlooked during manual inspections. Furthermore, manual inspections are prohibitively expensive for certain areas and do not cover them completely.

[0004] Some units use satellite photos for inspection. From a macro application perspective, the applicability of this method has been expanded. It only requires manual interpretation using satellite images, which greatly saves relative costs and greatly improves work efficiency. However, the interpretation of satellite images requires a certain amount of work experience, which greatly reduces its universality. Even experienced staff are very prone to errors in the interpretation process. This is mainly because different geological disasters have different host environments, and the host environment is always changing, which increases the complexity of geological disasters. In the existing technology, geological disasters in mountainous areas are identified through multi-source, multi-phase, high-resolution satellite data, geological disasters in mountainous areas are identified through the combination of drone images and DEM, geological disasters are identified through real-scene three-dimensional modeling methods using drone oblique photogrammetry, and the deformation of landslide disasters on site is measured and observed multiple times for identification.

[0005] Through the above analysis, the problems and defects of the existing technology are as follows: In the process of geological disaster identification using high-resolution satellites in the existing technology, the interpretation of geological disasters on satellite images is mainly carried out by combining on-site investigations with satellite images. The key problem of this method is that the geological disasters identified in the method are all geological disasters that have already occurred, and potential disasters such as unstable slopes and collapses cannot be distinguished, that is, only collapse and landslide disasters that have already caused disasters can be identified. In addition, since some areas cannot be reached by manual investigation, some disasters cannot be found and cannot be interpreted on satellite images. The learning model trained based on this also has great limitations in the interpretation of geological disasters on satellite images.

[0006] The key problem with using drone images to identify geological disasters is that they can only identify landslide disasters that have already occurred, but cannot identify potential disasters that are about to occur. In addition, drones can only identify single landslides. For geological disaster surveys in a certain area, the cost of using drones is high and the time consumption is greatly increased, which greatly increases the workload of later indoor image processing.

[0007] Summary of the Invention

[0008] To overcome the problems in related technologies, the present invention discloses a device, method, terminal, equipment, and medium for monitoring landslides based on satellite image feedback, which improves the accuracy and reliability of slope monitoring and saves costs.

[0009] The technical solution is as follows: a landslide monitoring device based on satellite image feedback includes: a composite monitoring box for monitoring groundwater chemical composition, pore water pressure, horizontal displacement, horizontal stress and vertical stress, and monitoring wall mineral composition change indicators to obtain relevant data at different depths of the geological body;

[0010] The data acquisition and control system is used to collect, aggregate and store on-site data. The data collected on-site is cached and then transmitted using a wireless transmission device. The data is aggregated and then transmitted to the indoor satellite image interpretation terminal.

[0011] The flow monitoring system is used to monitor surface water flow at different locations on the slope, as well as test and analyze the chemical composition and pH data of the surface water. The collected flow data is integrated with meteorological data to analyze flow and rainfall indicators at different locations.

[0012] The laser scanning monitoring system is used to monitor and analyze the scour pattern of the slope in real time, obtain scour pattern data at different locations on the slope, calculate the scour situation by comparing it with the original slope shape, monitor the water flow and water level at the bottom of the ditch, and issue early warnings for dangerous situations.

[0013] The water level monitoring system is used to monitor the water level and flow at the bottom of the ditch in real time. After transmitting the data to the data acquisition and control system, it is compared with the rainfall data. At the same time, it is compared and analyzed with the values ​​of the moisture sensor and pore pressure sensor inside the slope to obtain the relationship between rainfall, flow and pore water pressure.

[0014] Optionally, the landslide monitoring device based on satellite image feedback further includes: a power supply system consisting of two modules: a solar power supply module and a wind power supply module, which utilizes solar energy and wind energy to supplement power and supply power to the entire monitoring system;

[0015] The power supply system adopts variable frequency automatic control. When the parameter of the same sensor changes by ≤0.1% for one week in a row, the power supply of one-third of the common sensors is automatically cut off and the sensors are kept in the test state. When the fluctuating current is fed back to the power supply system, the power supply system starts to supply power again and the sensors return to normal.

[0016] Optionally, the landslide monitoring device based on satellite image feedback further includes:

[0017] Wireless transmission antenna, used for data transmission and command reception;

[0018] The meteorological monitoring station is used to monitor local rainfall, temperature, humidity, wind direction, wind speed, and air pressure meteorological indicators in real time, store and transmit the data, and finally transmit it to the data acquisition and control system.

[0019] Another object of the present invention is to provide a method for monitoring potential instability collapse and landslide disasters, comprising the following steps:

[0020] Step 1: Delineate the geological hazard investigation area selected from the satellite image, and deploy landslide monitoring equipment based on satellite image feedback on site.

[0021] Step 2: Monitor the deformation and stress of the evolving slope, feed the real-time data back to the indoor satellite image interpretation terminal, and repeatedly train the established learning model to link the movement elements of the on-site slope with the pixel changes in the satellite image.

[0022] Step three: Based on pre-programmed safety thresholds, monitor and warn of on-site landslide disasters.

[0023] In one embodiment, in step one, a satellite image interpretation learning model is trained using monitoring data of potential unstable landslide disasters, and the learning model is used to identify potential unstable slopes.

[0024] In step 2, machine learning involves repeatedly training the machine by setting up a dataset of changes in key indicators such as slope, aspect, altitude, and rainfall. This predicts and analyzes the occurrence of landslides based on a neural network method, and then identifies field landslide hazards. The learning model is: M = F(x1, x2, x3…), where x1, x2, and x3 are the key indicators of slope, aspect, and rainfall, respectively.

[0025] In step three, the setting of the safety threshold is determined in combination with the safety factor of the landslide disaster. The safety factor is the ratio of the anti-sliding force or torque to the sliding force or torque. The safety threshold is a function of the safety factor. The change law of the safety threshold is determined according to the change of the safety factor.

[0026] Another object of the present invention is to provide an indoor satellite image interpretation terminal for implementing the aforementioned method for monitoring potential instability, collapse and landslide disasters.

[0027] Another object of the present invention is to provide a storage medium for receiving user input programs, wherein the stored computer program enables an electronic device to execute the method for monitoring potential instability, collapse and landslide disasters.

[0028] Another object of the present invention is to provide a computer device, which includes a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the processor executes the method for monitoring potential instability and landslide disasters.

[0029] Combining all the above technical solutions, the advantages and positive effects of the present invention are as follows:

[0030] First, in view of the technical problems existing in the above-mentioned prior art and the difficulty of solving these problems, this paper closely combines the technical solutions to be protected by the present invention and the results and data during the research and development process, and analyzes in detail and in depth how the technical solutions of the present invention solve the technical problems and some creative technical effects brought about by solving the problems. The specific description is as follows:

[0031] The present invention provides a landslide monitoring device and technical method based on satellite image feedback. First, the geological disaster investigation range selected in the satellite image is delineated, and on this basis, monitoring equipment is deployed on site. The monitoring technical method of the present invention can monitor the core elements of engineering geology (stratum lithology, meteorology, geotechnical parameters, hydrology, etc.) in real time. On the one hand, it monitors the deformation and stress in the evolution of the slope, feeds back the real-time data to the indoor satellite image interpretation terminal, repeatedly trains the established learning model, and establishes a connection between the movement elements of the on-site slope and the pixel changes in the satellite image, thereby enhancing the accuracy of the satellite image interpretation; on the other hand, based on the pre-programmed safety threshold, it monitors and warns of on-site landslide disasters, provides local disaster prevention and mitigation services, deeply integrates transportation disaster prevention and mitigation with rural construction disaster prevention and mitigation, and reduces the cost of disaster prevention and mitigation.

[0032] The application of this technology can monitor potentially unstable slopes, which mainly solves the problem of being unable to identify impending geological disasters in satellite images. In addition, the technology provided in the present invention ultimately focuses on the application of big data artificial intelligence recognition methods. The establishment of this technology can provide important support for the identification of landslide geological disasters based on satellite images, improve work efficiency, and save the cost of geological disaster identification.

[0033] Second, considering the technical solution as a whole or from the perspective of the product, the technical effects and advantages of the technical solution to be protected by the present invention are described in detail as follows:

[0034] In response to the shortcomings of the above methods, the present invention proposes a landslide monitoring device and method based on satellite image feedback. Typical disaster points are selected through satellite images, and monitoring is carried out at the typical disaster points. The monitoring information is then fed back to an indoor interpretation terminal for interpretation, thereby improving the accuracy of the satellite image interpretation results.

[0035] On the one hand, the present invention promptly feeds back on-site information of typical disaster points to the indoor satellite image interpretation terminal, facilitating the smooth implementation of the interpretation work. On the other hand, the monitoring device of the present invention, in addition to monitoring the general displacement and stress change characteristics of the disaster, systematically monitors the stratum lithology, geological structure, surface scour, meteorology, groundwater and other information of the disaster, and gives the typical characteristics of the monitored disaster points from the perspective of engineering geology. These characteristics are integrated into specific indicators such as strain and stress, and the deformation and stress indicators are linked to the pixel changes in the satellite images, so that potential disaster points can be interpreted more accurately, effectively improving the accuracy and reliability of disaster investigation. In addition, based on the accurate monitoring information combined with artificial intelligence, the indoor interpretation method is machine-learned, and the artificial intelligence method is later used to interpret satellite images of typical disaster points, greatly improving work efficiency.

[0036] Third, as supporting evidence for the inventiveness of the present invention's claims, the technical solution of the present invention fills a technological gap in the industry, both domestically and internationally. The implementation of the present invention greatly facilitates geological hazard investigations, saving significant manpower and material resources. It also enables regional geological hazard investigations and inspections, providing important support for the safe construction and operation of highway and civil engineering projects. Furthermore, the present invention's technology facilitates integration into existing intelligent transportation information systems, filling this gap.

[0037] Figures in the specification

[0038] FIG1 is a flow chart of a method for monitoring potential instability, collapse and landslide disasters provided by an embodiment of the present invention;

[0039] FIG2 is a schematic diagram of a method for monitoring potential instability and landslide disasters provided by an embodiment of the present invention;

[0040] FIG3 is a schematic diagram of a landslide monitoring device based on satellite image feedback provided by an embodiment of the present invention;

[0041] FIG4 is a schematic diagram of a composite monitoring box provided in an embodiment of the present invention;

[0042] FIG5 is a schematic diagram of a flow monitoring system provided by an embodiment of the present invention.

[0043] In the figure: 1. Composite monitoring box; 1-1. Automatic shearing system; 1-2. Loading device; 1-3. Data collector; 1-4. Integrated monitor; 1-5. Water chemistry monitoring sensor; 1-6. Pore water pressure sensor; 1-7. Mineral composition monitoring sensor; 1-8. Moisture sensor; 1-9. Horizontal displacement monitoring sensor; 1-10. Vertical displacement monitoring system; 2. Data acquisition and control system; 3. Power supply system; 4. Slope top; 5. Ditch bottom; 6. Flow monitoring system; 6-1 , seepage solute test sensor; 6-2, water temperature monitoring sensor; 6-3, pH monitoring sensor; 6-4, anti-siltation and scouring system; 6-5, water tank inlet; 6-6, water inlet; 6-7, water outlet; 6-8, data storage device; 6-9, monitoring water tank; 6-10, water tank overflow channel; 6-11, flow monitoring sensor; 6-12, particle composition monitoring system; 7, laser scanning monitoring system; 8, wireless transmission antenna; 9, water level monitoring system; 10, meteorological monitoring station. DETAILED DESCRIPTION

[0044] To make the above-mentioned objects, features, and advantages of the present invention more readily apparent, specific embodiments of the present invention are described in detail below with reference to the accompanying drawings. The following description sets forth numerous specific details to facilitate a full understanding of the present invention. However, the present invention can be implemented in many other ways than those described herein, and those skilled in the art may make similar modifications without departing from the scope of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0045] 1. Explanation of the embodiment:

[0046] The monitoring method for potential instability collapse and landslide disasters provided by the embodiment of the present invention innovatively proposes a machine learning model training method based on potential instability collapse and landslide disaster monitoring.

[0047] At the same time, an innovative landslide monitoring device based on satellite image feedback was proposed. By analyzing factors such as changes in rock mechanical conditions, groundwater seepage, water chemistry, and mineral composition, the accuracy of landslide disaster identification was greatly improved.

[0048] The potential instability and collapse disaster monitoring method provided by the present invention analyzes geological deformation and regional meteorological data simultaneously during the learning process based on monitoring data. This method determines the critical conditions for geological instability from multiple perspectives, thereby improving the accuracy of the trained model in identifying dangerous geological bodies. This identification process is reverse-validated using existing geological disaster sites. By training multiple models, the universality of the present invention is enhanced.

[0049] Example 1

[0050] As shown in FIG1 , the method for monitoring potential instability and landslide disasters provided by an embodiment of the present invention includes the following steps:

[0051] S101: Delineate the geological disaster investigation area selected in the satellite image, and deploy landslide monitoring equipment based on satellite image feedback on site.

[0052] S102 conducts real-time monitoring of core engineering geological elements (stratum lithology, meteorology, geotechnical parameters, hydrology, etc.), monitors deformation and stress during slope evolution, feeds real-time data back to the indoor satellite image interpretation terminal, repeatedly trains the established learning model, and establishes a connection between the movement elements of the on-site slope and the pixel changes in the satellite image, thereby enhancing the accuracy of satellite image interpretation.

[0053] S103, based on pre-programmed safety thresholds, monitors and warns of on-site landslide disasters, provides local disaster prevention and mitigation services, deeply integrates transportation disaster prevention and mitigation with rural construction disaster prevention and mitigation, and reduces disaster prevention and mitigation costs.

[0054] In step S102, machine learning involves repeatedly training the machine by setting up a dataset of changes in key indicators such as slope, aspect, altitude, and rainfall. This predictive analysis of landslide hazards based on neural network methods is then used to identify field landslide hazards. The learning model is: M = F(x1, x2, x3…), where x1, x2, and x3 represent key indicators such as slope, aspect, and rainfall, respectively.

[0055] The prediction analysis of landslide disasters based on the neural network method and the identification of field landslide disasters based on the prediction analysis include:

[0056] Based on the specific changes in indicators such as slope, slope direction and rainfall obtained from on-site monitoring, the deformation state of the slope is judged in combination with the displacement in remote sensing satellite images. The specific stability of the landslide is analyzed based on the deformation state and deformation rate, and potential unstable slopes are accurately identified based on this.

[0057] Prediction process: Based on a large number of identifications in the early stage, continuous training is carried out, and repeated training is carried out based on the data set. The accuracy of recognition is improved through the combination of typical area identification and manual judgment. In the later stage, mature methods are used to identify potential geological disasters.

[0058] In step S103, the setting of the safety threshold is determined in combination with the safety factor of the landslide disaster. The safety factor is the ratio of the anti-sliding force or torque to the sliding force or torque. The safety threshold is a function of the safety factor. The change law of the safety threshold is determined according to the change of the safety factor.

[0059] F = N / T (F is generally the safety factor, N is the anti-slip force or anti-slip torque, KN; T is the sliding force or torque, KN).

[0060] In an embodiment of the present invention, a satellite image interpretation learning model is trained using monitoring data of potential unstable collapse and landslide disasters. This is completely different from the training basis of traditional learning models. The learning model can be used to accurately identify potential unstable slopes in the later stage, thereby improving the level of disaster prevention and mitigation, and breaking through the technical bottleneck of existing technologies that only identify existing disasters.

[0061] In the embodiments of the present invention, the proposed landslide monitoring device based on satellite imagery feedback improves upon traditional monitoring methods. In addition to sensors for displacement, stress, and pore pressure monitoring, it also incorporates monitoring systems for hydrology, hydrochemistry, and changes in mineral composition. This device reveals the underlying mechanisms of landslide disasters through the lens of changes in material composition and groundwater seepage, significantly surpassing existing landslide monitoring technologies in accuracy and reliability. The ultimate goal of this monitoring device and method is to provide early warning and monitoring of potential disasters, effectively contributing to local disaster prevention and mitigation efforts.

[0062] In the embodiments of the present invention, changes in material composition primarily focus on the content of clay minerals within geological bodies. Increased clay minerals are extremely detrimental to the stability of geological bodies and can easily lead to landslides and collapses under the influence of triggering factors such as groundwater or earthquakes, resulting in catastrophic effects. The formation of clay minerals is closely linked to changes in certain anions, cations, and mineral components in groundwater. Therefore, changes in material composition and groundwater can reveal the underlying mechanisms of geological disaster formation.

[0063] Example 2

[0064] As shown in FIG2 , the monitoring method for potential instability and landslide disasters provided by an embodiment of the present invention includes:

[0065] (1) Select the study area using satellite images. Use satellite images to select the study area where geological disaster investigation is to be carried out.

[0066] (2) On-site monitoring: several typical disaster sites are selected in the study area to deploy monitoring devices.

[0067] (3) Data collection: On-site monitoring obtains various types of data and transmits the data to the indoor satellite image interpretation terminal.

[0068] (4) Satellite image recognition: machine learning is performed based on monitoring data, and the learned model is used to use artificial intelligence to accurately identify and batch identify landslide disasters in the study area to serve disaster prevention and mitigation.

[0069] Figure 2 uses a potentially unstable geological body as the research object. Landslides or collapses can only occur after the geological body becomes unstable. In addition to repeatedly monitoring and processing the potentially unstable geological body using the on-site monitoring facilities developed in this invention, traditional monitoring data such as displacement, stress, and meteorological data are also key components of subsequent machine learning. Furthermore, the device proposed in this invention accurately monitors phenomena such as surface water flow and erosion of the geological body surface.

[0070] Example 3

[0071] As shown in FIG3 , the landslide monitoring device based on satellite image feedback provided by an embodiment of the present invention includes:

[0072] Composite monitoring box 1, this device contains many monitoring systems, which can monitor indicators such as groundwater chemical composition, pore water pressure, horizontal displacement, horizontal stress and vertical stress, and changes in the mineral composition of the monitoring wall. The integration of many sensors reduces the number of holes required for on-site monitoring. The high degree of integration can greatly improve the installation efficiency. At the same time, the monitoring box is laid out in a vertical form, which can obtain relevant data at different depths. When the parameters of adjacent layers change greatly, it is combined with other data to make a comprehensive judgment on whether the geological body will become unstable and damaged.

[0073] The data acquisition and control system 2 is mainly used for the collection and aggregation of on-site data, and also has the function of preliminary data storage. It can cache the data collected on-site and transmit it using a wireless transmission device, and transmit the data after aggregation to the indoor satellite image interpretation terminal. The indoor satellite image interpretation terminal repeatedly learns based on the collected data to realize artificial intelligence-based landslide disaster identification and improve the accuracy of disaster identification. In addition, the system's specific data fusion and processing functions can compare and analyze the data collected by underground sensors with the data collected by meteorological stations, and establish a connection through built-in algorithms for monitoring personnel to analyze and use.

[0074] The power supply system 3 mainly consists of two modules: solar power supply and wind power supply. It uses solar energy and wind energy to supplement electricity and has the function of electricity storage to supply power to the entire monitoring system. The power supply system 3 adopts variable frequency automatic control. When the parameter change of the same sensor is less than 0.1% for a week, the power supply system 3 will automatically cut off the power supply of one-third of the general sensors to keep them in the test state. Once there is a fluctuating current feedback to the power supply system 3, the power supply system 3 will immediately start to re-supply, and the sensor will fully return to normal. This process can reduce power loss during monitoring. The repeated collection of general data has limited significance for later analysis, and at the same time reduces the load on the memory. This is also set in the present invention, which is significantly innovative and different from the existing technology of turning on all sensors for monitoring at the same time.

[0075] Slope top 4, slope top 4 needs simple leveling during monitoring.

[0076] Ditch bottom 5, where the shady slope and the sunny slope meet.

[0077] The flow monitoring system 6 mainly monitors the surface water flow at different locations on the slope. At the same time, water storage tanks are arranged inside the monitoring system, and relevant sensors are used to test and analyze the chemical composition and pH data of the surface water. After the flow data is collected, it is integrated with meteorological data to analyze the relationship between the flow at different locations and indicators such as rainfall.

[0078] The laser scanning monitoring system 7 has the main function of real-time monitoring and analysis of the scouring pattern of the slope surface. It can obtain data such as the scouring pattern at different positions on the slope surface, calculate the scouring situation by comparing it with the original slope surface pattern, and at the same time perform simple monitoring of the water flow and water level at the bottom of the ditch 5. An early warning system is also deployed in the system, which mainly warns of dangerous situations. An alarm amplifier is set up to issue an alarm, and the instructions are issued by the data acquisition and control system 2.

[0079] The wireless transmission antenna 8 is mainly used in the process of data transmission and command reception.

[0080] The water level monitoring system 9 mainly monitors the water level and flow at the bottom of the ditch 5 in real time. After the data is transmitted to the data acquisition and control system 2, it will be compared with data such as rainfall. At the same time, it will be compared and analyzed with the values ​​of moisture sensors 1-8 and pore pressure sensors inside the slope. Based on this, the connection between rainfall, flow and pore water pressure can be established, laying the foundation for the instability judgment of potential unstable geological bodies.

[0081] The meteorological monitoring station 10 mainly monitors local meteorological indicators such as rainfall, temperature, humidity, wind direction, wind speed, and air pressure in real time, stores and transmits the data, and finally transmits it to the data acquisition and control system 2.

[0082] Example 4

[0083] According to the landslide monitoring device based on satellite image feedback provided in Example 3 of the present invention, as shown in FIG4 , the composite monitoring box 1 includes:

[0084] Automatic shearing system 1-1, the main function of this system is to measure the mechanical parameters of the rock and soil at a certain underground layer, mainly based on the principle of cross-plate shear instrument, and monitor and analyze the initial and changing shear strength parameters in real time, and transmit them to the data collector 1-3.

[0085] Loading device 1-2: The main function of this device is to provide loading function in the shear test, and at the same time it can control the depth of the shear plate into the soil. Since a new shear band will be formed each time shearing, the shear plate needs to be loaded into the unsheared soil for secondary shearing or multiple shearing in the later shearing to ensure accurate test results.

[0086] The main function of the data collectors 1-3 is to collect and store the data in the entire monitoring box and transmit the data to the data acquisition and control system 2.

[0087] The integrated monitors 1-4 have a box wall material with a certain rigidity and are waterproof, which is obtained through customized processing.

[0088] Water chemical monitoring sensors 1-5 are mainly used to monitor the water chemical characteristics of the layer. If the rock layer is below the groundwater level, the sensor can be directly tested. If the rock layer where the sensor is located is above the groundwater level, the sensor monitors the water chemical composition during the water migration process, including parameters such as anions, cations and pH values.

[0089] The pore water pressure sensors 1-6 are mainly used to monitor the pore water pressure in the rock and soil of the layer, and provide core parameters for the effective stress calculation of the entire rock and soil.

[0090] Mineral composition monitoring sensors 1-7 monitor and analyze the mineral composition of the layer, such as clay minerals, quartz, feldspar, etc.

[0091] Moisture sensors 1-8 are mainly used to monitor the moisture content of the layer and can reflect conditions such as moisture migration inside the rock and soil.

[0092] Horizontal displacement monitoring sensor 1-9, when the rock and soil body produces horizontal displacement, the monitoring box as a whole will be squeezed, and horizontal displacement monitoring is carried out based on this to obtain the horizontal displacement deformation index.

[0093] Vertical displacement monitoring system 1-10, when the rock and soil mass produces vertical settlement, this sensor can collect the vertical displacement in real time.

[0094] Example 5

[0095] According to the landslide monitoring device based on satellite image feedback provided in Example 3 of the present invention, as shown in FIG5 , the flow monitoring system 6 includes:

[0096] The seepage solute test sensor 6-1 is mainly used to monitor the chemical composition of surface water, including the types and contents of anions and cations in surface water.

[0097] The water temperature monitoring sensor 6-2 is mainly used to monitor the temperature of surface water in real time.

[0098] The pH monitoring sensor 6-3 is mainly used to monitor the pH of surface water and obtain data on changes in the chemical environment of surface water.

[0099] The anti-siltation and flushing system 6-4 has the main function of regularly flushing the monitoring water tank 6-9, using the flushing force to flush out the solid phase materials remaining at the bottom to ensure the normal use of the water tank.

[0100] The water inlet 6-5 of the water tank has the main function of allowing water to enter the water tank. It has a built-in electromagnetic valve that can automatically close or open the valve as needed.

[0101] The water inlet 6-6, the water inlet of the flow monitoring system 6, allows groundwater to enter the system channel.

[0102] Water outlet 6-7, water outlet in flow monitoring system 6.

[0103] The data storage 6 - 8 mainly collects and stores the data collected by the sensors in the flow monitoring system 6 , and finally transmits the data to the data acquisition and control system 2 in FIG. 3 .

[0104] Monitoring water tanks 6-9 mainly serve various surface water monitoring sensors. The sensors are fixedly installed and water is stored for testing to ensure good stability of the test results.

[0105] The water tank overflow channel 6-10 is used to monitor the water tank 6-9 so that excess water can be discharged through this channel.

[0106] Flow monitoring sensors 6-11 are mainly used to monitor the surface water flow at the monitoring location and provide basic data for the subsequent slope scour analysis.

[0107] Particle composition monitoring system 6-12, the main function of this system is to test the soil particles carried in the surface water at the monitoring location and obtain the particle size of the material components carried in the water. The system has an automatic flushing function. After each test, the system automatically flushes the particles remaining at the bottom to ensure the cleanliness of the flow channel.

[0108] In the above embodiments, the description of each embodiment has its own focus. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant description of other embodiments.

[0109] The information interaction, execution process, etc. between the above-mentioned devices / units are based on the same concept as the embodiment of the method of the present invention. Their specific functions and technical effects can be found in the method embodiment part and will not be repeated here.

[0110] Those skilled in the art can clearly understand that, for the convenience and brevity of description, only the division of the above-mentioned functional units and modules is used as an example for illustration. In actual applications, the above-mentioned functions can be distributed and completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiment can be integrated into one processing unit, or each unit can exist physically alone, or two or more units can be integrated into one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of software functional units. In addition, the specific names of the functional units and modules are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of the present invention. The specific working process of the units and modules in the above-mentioned system can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0111] 2. Application Examples

[0112] Application Example 1

[0113] The monitoring device provided by the embodiment of the present invention is used to investigate geological disasters in the Bailong River Basin. First, the Bailong River Basin is selected using satellite images, and several relatively typical disaster points are selected in this basin. On-site monitoring devices are deployed, and the on-site monitoring data are collected and organized and imported into indoor terminals. The critical values ​​of key indicators such as slope and rainfall are found based on the changes in slope stress, displacement and other data collected on-site. This data is input into the system, and the learning model is repeatedly trained. The landslide disaster here can be used as a typical disaster point. During the model training, key pixel points are extracted from the satellite images, and the pixel points are linked to the changes in displacement, stress and other indicators monitored on-site. The trained model is then used to identify other similar disaster points in the entire basin, which can greatly save manpower and material resources.

[0114] Application Example 2

[0115] The monitoring method provided in an embodiment of the present invention runs on a computer device, which includes: at least one processor, a memory, and a computer program stored in the memory and capable of running on the at least one processor. When the processor executes the computer program, the steps in any of the above-mentioned method embodiments are implemented.

[0116] Application Example 3

[0117] The monitoring method provided by the embodiment of the present invention runs on a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, the steps in the above-mentioned various method embodiments can be implemented.

[0118] Application Example 4

[0119] The monitoring method provided in an embodiment of the present invention runs on an information data processing terminal. When the information data processing terminal is implemented on an electronic device, it provides a user input interface to implement the steps in the above-mentioned method embodiments. The information data processing terminal is not limited to mobile phones, computers, and switches.

[0120] Application Example 5

[0121] The monitoring method provided in the embodiment of the present invention is run on a server. When the server is used to be executed on an electronic device, it provides a user input interface to implement the steps in the above-mentioned method embodiments.

[0122] Application Example 6

[0123] The monitoring method provided in the embodiment of the present invention is run on a computer program product. When the computer program product is run on an electronic device, the electronic device can implement the steps in the above-mentioned various method embodiments when executing the computer program product.

[0124] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present invention can implement all or part of the process of the above-mentioned method embodiment by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium. When executed by a processor, the computer program can implement the steps of each of the above-mentioned method embodiments. The computer program includes computer program code, which can be in source code form, object code form, executable file, or some intermediate form. The computer-readable medium can at least include: any entity or device capable of carrying computer program code to the camera / terminal device, recording medium, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signal, telecommunication signal, and software distribution medium. Examples include a USB flash drive, a mobile hard drive, a magnetic disk, or an optical disk.

[0125] III. Evidence of the relevant effects of the embodiments:

[0126] The monitoring device and method provided by the embodiments of the present invention utilize integrated air-space-ground-ground technology to monitor and identify landslide disasters. Landslide monitoring utilizes precise satellite positioning, combined with real-time ground-based monitoring for identification. Indoor terminals collect and aggregate data, learn from it, and issue identification commands, improving the accuracy of the entire identification technology. This process effectively integrates remote sensing geology, disaster geology, and sensing technology, achieving multidisciplinary cross-fertilization and mutual verification, significantly enhancing the functionality and efficiency of the entire monitoring system.

[0127] Satellite images were used to identify a landslide on site, preliminarily determine the scope of the landslide, and conduct on-site monitoring, focusing on analyzing changes in groundwater and material composition. The occurrence of a landslide is the result of the formation of a sliding zone, which is a macroscopic manifestation of the reduction of the mechanical indicators (cohesion and friction) of the rock and soil at a certain depth within the landslide body.

[0128] The above description is only a preferred specific implementation method of the present invention, but the scope of protection of the present invention is not limited thereto. Any modifications, equivalent substitutions and improvements made by any technician familiar with this technical field within the technical scope disclosed by the present invention and within the spirit and principles of the present invention should be covered by the scope of protection of the present invention.

Claims

1. A landslide monitoring device based on satellite image feedback, characterized in that: The landslide monitoring device based on satellite image feedback includes: The composite monitoring box (1) is used to monitor groundwater chemical composition, pore water pressure, horizontal displacement, horizontal stress and vertical stress, and monitoring wall mineral composition change indicators to obtain relevant data at different depths of the geological body; A data acquisition and control system (2) is used for collecting, aggregating and storing on-site data, caching the data collected on-site and transmitting it via a wireless transmission device, and aggregating the data and transmitting it to an indoor satellite image interpretation terminal; Flow monitoring system (6), used to monitor surface water flow at different locations on the slope, and to test and analyze the chemical composition and pH data of surface water. The collected flow data is integrated with meteorological data to analyze flow and rainfall indicators at different locations. A laser scanning monitoring system (7) is used to monitor and analyze the scour morphology of the slope in real time, obtain scour morphology data at different locations on the slope, calculate the scour situation by comparing it with the original slope morphology, monitor the water flow and water level at the bottom of the ditch (5), and issue early warnings for any dangerous situations; The water level monitoring system (9) is used to monitor the water level and flow rate at the bottom of the ditch (5) in real time, transmit the data to the data acquisition and control system (2), and compare it with the rainfall data. At the same time, it is compared and analyzed with the values ​​of the moisture sensors (1-8) and pore pressure sensors inside the slope to obtain the relationship between rainfall, flow rate and pore water pressure.

2. The landslide monitoring device based on satellite image feedback according to claim 1 is characterized in that: The landslide monitoring device based on satellite image feedback further includes: a power supply system (3), which is composed of two modules: solar power supply and wind power supply, and uses solar energy and wind energy to supplement electricity and supply power to the entire monitoring system; The power supply system (3) adopts variable frequency automatic control. When the parameter of the same sensor changes by ≤0.1% for one week in a row, the power supply of one-third of the sensors is automatically cut off to maintain the test state. After the fluctuating current is fed back to the power supply system (3), the power supply system (3) starts to supply power again and the sensor returns to normal.

3. The landslide monitoring device based on satellite image feedback according to claim 1 is characterized in that: The landslide monitoring device based on satellite image feedback further includes: A wireless transmission antenna (8) for data transmission and command reception; Meteorological monitoring station (10) is used to monitor local rainfall, temperature, humidity, wind direction, wind speed, The atmospheric pressure and meteorological indicators are monitored in real time, and the data are stored and transmitted, and finally transmitted to the data acquisition and control system (2).

4. The landslide monitoring device based on satellite image feedback according to claim 1 is characterized in that: The composite monitoring box (1) comprises: The automatic shearing system (1-1) is used to measure the mechanical parameters of the rock and soil at a certain underground layer, monitor and analyze the initial and changing shear strength parameters in real time, and transmit them to the data collector (1-3); A loading device (1-2) is used to provide loading in the shear test and also to control the depth of the shear plate into the soil; Data collectors (1-3) are used to collect and store data from the entire monitoring box and transmit the data to the data acquisition and control system (2); Comprehensive monitor (1-4) for waterproofing; Water chemistry monitoring sensors (1-5) are used to monitor the water chemistry of geological formations. If the formation is below the groundwater level, the sensors are used to directly test the water chemistry. If the formation is above the groundwater level, the sensors are used to monitor the water chemistry during water migration. Pore ​​water pressure sensors (1-6) are used to monitor the pore water pressure in the rock and soil of the geological layer and provide core parameters for the calculation of effective stress of the entire rock and soil; Mineral composition monitoring sensors (1-7) monitor and analyze the mineral composition of geological layers; Sub-sensors (1-8) are used to monitor the moisture content of the geological layer and reflect the moisture migration status within the rock and soil; Horizontal displacement monitoring sensors (1-9) are used to monitor horizontal displacement when rock and soil bodies produce horizontal displacement and obtain horizontal displacement deformation indicators; The vertical displacement monitoring system (1-10) is used to collect the vertical displacement in real time when the rock and soil mass produces vertical settlement.

5. The landslide monitoring device based on satellite image feedback according to claim 1 is characterized in that: The flow monitoring system (6) comprises: Seepage solute test sensor (6-1), used to monitor the chemical composition of surface water, including the types and contents of anions and cations in surface water; Water temperature monitoring sensor (6-2), used for real-time monitoring of surface water temperature; pH monitoring sensor (6-3) is used to monitor the pH of surface water to obtain surface Data on changes in water chemistry; Anti-siltation and flushing system (6-4), used for regularly flushing the monitoring water tank (6-9); The water inlet (6-5) of the water tank is used to allow water to enter the water tank, and has a built-in electromagnetic valve that automatically closes or opens the valve as needed; a water inlet (6-6) for the water inlet of the flow monitoring system (6) and a channel for groundwater to enter the system; a water outlet (6-7) for discharging water from the flow monitoring system (6); Data storage (6-8), for collecting and storing data collected by sensors in the flow monitoring system (6), and ultimately transmitting the data to the data acquisition and control system (2); Monitoring water tanks (6-9) are used to serve various surface water monitoring sensors, to fix the sensors, and to store water for testing; The water tank overflow channel (6-10) is used to monitor the water tank (6-9) and discharge the excess water; Flow monitoring sensors (6-11), used to monitor the surface water flow at the monitoring location; The particle composition monitoring system (6-12) is used to test the soil particles carried in the surface water at the monitoring location to obtain the particle size of the material components carried in the water.

6. A method for monitoring potential unstable landslide disasters using the landslide monitoring device based on satellite image feedback according to any one of claims 1 to 5, characterized in that: The method for monitoring potential instability and landslide disasters comprises the following steps: Step 1: Delineate the geological hazard investigation area selected from the satellite image, and deploy landslide monitoring equipment based on satellite image feedback on site. Step 2: Monitor the deformation and stress of the evolving slope, feed the real-time data back to the indoor satellite image interpretation terminal, and repeatedly train the established learning model to link the movement elements of the on-site slope with the pixel changes in the satellite image. Step three: Based on pre-programmed safety thresholds, monitor and warn of on-site landslide disasters.

7. The method for monitoring potential instability and landslide disasters according to claim 6, characterized in that: In step 1, the satellite image interpretation learning model is trained using the monitoring data of potential unstable landslide disasters, and the learning model is used to identify potential unstable slopes; In step 2, in machine learning, by setting up a data set of changes in key indicators such as slope, aspect, altitude and rainfall, the machine is repeatedly trained to predict the slope based on the neural network method. The occurrence of slope disasters is predicted and analyzed, and field landslide disasters are identified based on this; the learning model is: M = F(x1, x2, x3….), where x1, x2, and x3 are the key indicators of slope, slope direction, and rainfall respectively; The prediction analysis of landslide disasters based on the neural network method and the identification of field landslide disasters based on the prediction analysis include: Based on the changes in slope, aspect, and rainfall indicators obtained through on-site monitoring, combined with the displacement data from remote sensing satellite images, the deformation state of the slope is determined. The stability of the landslide is analyzed based on the deformation state and deformation rate, and potentially unstable slopes are identified. In step three, the setting of the safety threshold is determined in combination with the safety factor of the landslide disaster. The safety factor is the ratio of the anti-sliding force or torque to the sliding force or torque. The safety threshold is a function of the safety factor. The change pattern of the safety threshold is determined according to the change of the safety factor. Wherein, F=N / T, F is the safety factor, N is the anti-slip force or anti-slip torque, KN; T is the sliding force or torque, KN.

8. An indoor satellite image interpretation terminal, used to implement the monitoring method for potential instability, collapse and landslide disasters as described in claim 6.

9. A computer program storage medium for receiving user input, wherein the computer program stored in the medium causes an electronic device to execute the method for monitoring potential instability, collapse and landslide disasters as claimed in claim 6.

10. A computer device, characterized in that: The computer device includes a memory and a processor, the memory stores a computer program, and when the computer program is executed by the processor, the processor executes the method for monitoring potential instability and landslide disasters as described in claim 6.