197 results about "Geohazard" patented technology

The invention relates to the technical field of hydraulic engineering, geotechnical mechanics and geological disaster prevention and control engineering, and discloses a landslide surge physical and numerical hybrid model construction method and system and application. Analyzing the landslide instability evolution motion process, the landslide warehousing first wave height and the surge propagation process of the landslide surge; performing a numerical simulation test according to a second result of the landslide surge numerical model test; adjusting the particle size and the kernel function in the landslide surge numerical simulation test, so that the first wave height, the opposite-bank arrival height and the surge pressure distribution in the landslide surge numerical simulation test and the landslide surge physical model test are consistent; and taking the adjusted landslide surge numerical model as the obtained landslide surge hybrid model. The system comprises a first result acquisition module, a second result acquisition module, a test parameter adjustment module and a hybrid model acquisition module. According to the method, different calculation working conditions can be conveniently analyzed.

The invention discloses a seabed landslide simulation experiment device and method, and relates to the technical field of marine geological disaster simulation, the seabed landslide simulation experiment device comprises a closed test box, and at least one side of the test box is provided with a visual structure; the seabed simulation assembly is arranged at the bottom of the test box, the seabed simulation assembly comprises a bearing part, the gradient of the bearing part is adjustable, and a sediment layer, a trap layer and a storage layer which are sequentially arranged on the bearing part form a landslide mass; a seabed water pressure simulation assembly; a water flow simulation assembly; a pore water pressure simulation assembly; the measuring assembly comprises a camera module and a sensor module, the camera module obtains image information of the seabed simulation assembly through the visual structure, and the sensor module is used for obtaining the pressure condition in the test box and the pressure condition of the landslide mass. According to the seabed landslide simulation experiment device, a complex seabed environment can be truly simulated, so that the prediction accuracy of an experiment result on an actual seabed landslide condition is improved.

The invention relates to the cross technical field of artificial intelligence and geological disaster monitoring and early warning, in particular to a landslide recognition method and system based on staged feature adaptive transfer learning, and the method comprises the steps: constructing an initial landslide recognition model F1 with an encoder-decoder; a universal visual pre-training weight is migrated, and encoder parameters of the model F1 are finely adjusted by using a remote sensing image data set DS of a source domain, so that a landslide identification optimization model F2 adaptive to the field is obtained; inputting the remote sensing image data set DS of the source domain and the unmanned aerial vehicle image data set DT of the target domain into the model F2, and processing based on a covariance alignment mechanism to obtain a domain adaptive model F3; inputting a small amount of labeled target domain small sample data D 'T into the model F3, and finely adjusting specified parameters in the model F3 through a supervised learning mechanism to obtain a target domain adaptive model F4; and based on the target domain adaptation model F4, executing a landslide identification task on an input to-be-detected unmanned aerial vehicle image.

The invention discloses a novel anti-slide pile and an intelligent regional landslide monitoring and management method and system, relates to the technical field of landslide monitoring, combines the functions of real-time monitoring, early warning and prediction, structural stability evaluation, maintenance scheme analysis and the like, is beneficial to improving the scientificity, accuracy and efficiency of landslide control, reduces the geological disaster risk, and improves the safety of landslide management. Meanwhile, by combining elements such as the inclined piles in front of the piles, the anchor cables and the water guide pipes, the structure not only improves the stability of the slide-resistant piles, but also can effectively control deformation and drainage of landslides, so that geological disaster risks are reduced, casualties and economic losses are reduced, and the structure is composed of the slide-resistant piles, the anchor cables, the inclined piles in front of the piles, the water guide pipes and the drainage pipes; the anti-slide pile is a hollow pile, the anchor cable and the inclined pile in front of the pile are constructed in the hollow pile, the hollow pile part is filled with concrete after the anchor cable and the inclined pile are constructed, and the concept that the anchor cable cannot be constructed in a traditional embedded anti-slide pile is changed.

The invention relates to the technical field of slope reinforcement, and particularly discloses a slope reinforcement system and method for building municipal administration, slope rock mass strain time sequence data is collected through a distributed optical fiber sensing system, slope deformation monitoring data is obtained through a spaceborne interferometric synthetic aperture radar, and a three-dimensional deformation monitoring data set is constructed; an LSTM-rock constitutive model fusing a DFOS strain field and an InSAR deformation field is established, strain time sequence data and deformation data are input into the model for three-dimensional stress field inversion, and shear modulus degradation rate parameters, creep coefficient parameters and displacement increment prediction data are output; shear modulus degradation rate parameters, creep coefficient parameters and displacement increment prediction data are processed, regulation and control strategy codes of anchor rod tensioning force gradients and grouting pressure intervals are generated and uploaded to a control terminal, the precision and timeliness of slope stability analysis are remarkably improved, accurate intervention can be conducted in time according to potential risks of a slope, and the stability of the slope is improved. The probability of geological disasters such as landslide is reduced, and life and property safety of people is protected.

The invention discloses an active power distribution network fault risk assessment system and method, and relates to the technical field of power distribution network operation risk assessment, and the system comprises a natural environment data collection module, an environment risk assessment model construction module, and an environment risk assessment module. On the basis of historical data analysis and trend prediction functions, by analyzing historical meteorological data, geological disaster record data and historical fault records of the power distribution network, the current fault risk of the power distribution network can be accurately evaluated, and by predicting the change of environmental factors in a period of time in the future, the power distribution network fault risk can be accurately evaluated. And the prediction data are substituted into the risk calculation model to assess the possible fault risk of the power distribution network in the future according to the change trends of the rainfall, the wind speed, the temperature, the humidity and the water level. Therefore, the timeliness and accuracy of risk assessment are ensured, and more time is provided for the operation of the power grid to take preventive measures.

The invention provides a deep learning landslide identification method and system fusing optical and SAR remote sensing data, and relates to the field of geological disaster monitoring and identification, and the method comprises the steps: obtaining an optical image and an SAR image of a target region, carrying out the registration, generating an optical-SAR image pair, and generating a corresponding binary label map for the optical-SAR image pair; constructing a to-be-trained landslide recognition model, constructing a data set by the optical-SAR image pair and the corresponding binary label graph, and training the to-be-trained landslide recognition model by using the data set to obtain a trained landslide recognition model; and inputting an optical-SAR image pair of a to-be-identified area into the trained landslide identification model, and outputting a landslide identification result graph of the to-be-identified area. According to the invention, the limitation of a single remote sensing data source in landslide identification in the prior art is overcome, and the landslide identification precision in a complex environment is improved.

The invention discloses an air-space-ground landslide monitoring method and system based on deep learning, and relates to the technical field of landslide monitoring of mines. The system divides a mine area into a plurality of monitoring sub-areas by establishing a visual man-machine interaction platform and combining a digital geological disaster model; the multi-source data collection covers various sensing data of air-based, space-based and ground-based data, and the consistency and reliability of the data are ensured through standardization, time synchronization and space registration processing; a dynamic landslide monitoring model is constructed by adopting a convolutional neural network, multi-scale spatial-temporal characteristics of a landslide mass are extracted in real time, and accurate identification of landslide physical effect risks is realized; in combination with a geomechanical strain response index, a micro-seismic excitation response coefficient and a fluctuation disturbance abnormal index, a landslide risk is evaluated in multiple dimensions through a threshold judgment mechanism, a risk state and an early warning level are dynamically output, an early warning strategy is generated, mine safety management and emergency response are assisted, and life safety of mining personnel and environmental stability are guaranteed.

The invention relates to the technical field of early warning systems, and discloses a tunnel portal geological disaster early warning system which comprises a main beam, a supporting column is fixedly connected to the lower portion of the main beam, a supporting plate capable of moving up and down is arranged in the main beam, and a mounting plate is arranged below the main beam. The mounting plate is provided with an early warning assembly, the early warning assembly is connected with the supporting plate, a top plate is arranged above the main beam, the top plate is connected with the mounting plate, a pressure sensor is arranged between the top plate and the supporting plate, and an air bag detection assembly is arranged on one side of the mounting plate. The top plate can move downwards to cause numerical value change of the pressure sensor and the distance sensor, so that an alarm is triggered, in addition, the warning board can also turn over and fall down to further remind a driver, and in addition, when vibration and abnormal soil flow occur at the top of the tunnel, gas is transferred into the first gas bag from the second gas bag; the first air bag expands to push the sliding block to move and give an alarm.

The invention discloses an intelligent assessment method and system for regional geological disaster risk, and relates to the technical field of intelligent assessment. During operation of the system, various real-time data related to debris flow are acquired by integrating real-time sensors and satellite remote sensing data, original data are preprocessed and stored in a data storage system; based on the collected data, a physical model and a machine learning model are constructed, a debris flow disaster risk index MRI, a rainfall intensity coefficient RIC, a geological vulnerability coefficient GVC and a hydrodynamic pressure coefficient HPC are obtained after calculation, the probability of debris flow occurrence is predicted, and a result is output according to the model. The debris flow disaster risk index MRI is compared with a preset first safety threshold value M and a preset second safety threshold value N, the risk level of debris flow occurrence is evaluated, different areas are managed in a classified mode, debris flow early warning is given out according to real-time monitoring data and risk evaluation results, and automatic emergency response measures are supported.

The invention provides a method for determining the spontaneous combustion evolution process of end slope coal of a strip mine, and belongs to the field of geotechnical engineering geological disaster prevention and control and the field of mine safety and environmental protection. Updating the porosity, the permeability and the range of the combustion space area in the pre-established three-dimensional geologic model by adopting the three-dimensional distribution of the porosity of the bending subsidence zone, the permeability of the fissure zone, the permeability of the caving zone and the porosity of the caving zone in the combustion space area; performing coal fire evolution simulation again according to the updated pre-established three-dimensional geologic model to obtain a coal fire development range, an updated real-time temperature field range and a gas concentration field; and if the combustion cannot be continued, outputting a final coal fire development range and an updated real-time temperature field range. According to the method, the efficiency and accuracy of open-pit mine end slope coal fire treatment are effectively improved.

The embodiment of the utility model provides mountain geological disaster safety monitoring and early warning equipment applied to an unmanned vehicle. The safety monitoring and early warning equipment is fixedly installed on the unmanned vehicle. The safety monitoring and early warning equipment comprises a sensor module and a pitching adjusting piece, wherein the pitching adjusting piece is used for adjusting the pitching angle of the sensor module. According to the safety monitoring and early warning equipment, a large number of fixed equipment does not need to be deployed at multiple places of the mountain land, and the cost is saved; meanwhile, equipment can be installed on one vehicle, and people can patrol on mountains.

The invention relates to a spoil field three-dimensional form change analysis method, which comprises the following steps: constructing an air-space-ground collaborative multi-scale three-dimensional monitoring network by adopting an unmanned aerial vehicle carrying a laser radar system; dynamic construction of a multi-period digital elevation model and a digital terrain model is realized through a weighted fusion algorithm based on point cloud density difference and an improved progressive triangulation network encryption algorithm; performing time sequence alignment on the digital terrain models in different periods, and constructing a digital elevation difference model; and through a digital elevation difference model and a self-adaptive threshold change detection technology, the space-time differentiation characteristics and evolution rules of a slope curvature sudden change area, a surface roughness abnormal zone and a deformation rate of the spoil site are disclosed. According to the scheme provided by the invention, high-precision three-dimensional form dynamic modeling and deformation process precise monitoring of the spoil ground can be realized, and reliable technical support is provided for ecological safety situation assessment and geological disaster advanced early warning of the spoil ground.

The invention provides a soil body-structure interaction boundary damage quantitative testing device and method, and relates to the technical field of geotechnical engineering test.The soil body-structure interaction boundary damage quantitative testing device comprises a stress conduction boundary shear strength and rigidity combined testing structure and a testing system integrating a shaft confining pressure-temperature collaborative loading system and a monitoring collection and process control system; through an improved slurry sample preparation method, tight connection and constant contact area between the hollow columnar soil sample and the friction pile body are ensured, and the test sealing performance is enhanced through the elastic sealing design; the real-time measurement of the rigidity of different positions in the whole shearing process is realized by virtue of the excitation damage detection element capable of synchronously moving; according to the method, the constitutive model of the marine rock-soil stress conduction boundary domain is perfected, a reliable experimental basis is provided for foundation design of deep-sea engineering such as submarine pipelines and anchoring structures, and the method has important theoretical value and engineering significance for improving design scientificity and safety of deep-sea infrastructures and preventing and controlling submarine geological disasters.

The invention discloses an aerial or semi-aerial geophysical exploration CO2 monitoring system and method based on an unmanned aerial vehicle. A carbon dioxide gas sensor, an aerial three-component electromagnetic field sensor and an aerial horizontal controllable electromagnetic field transmitting coil are mounted at the lowest part of the unmanned aerial vehicle; the optical fiber CO2 modulation and demodulation instrument, the controllable electromagnetic source transmitter and the three-component electromagnetic field data acquisition instrument are carried in the unmanned aerial vehicle, and the electromagnetic field transmitting coil or the rectangular current source transmitting antenna and the controllable current transmitting source are laid around a CO2 injection well on the ground. The method comprises the following steps of: performing long-term safety monitoring on the migration of underground supercritical CO2 by using the CO2 concentration in equal-elevation air acquired at different stages and the processing result of real-time or time-shifting aviation or semi-aviation three-dimensional controllable source electromagnetic data; the geological disaster that the supercritical CO2 is leaked to the ground along the well wall of the injection well or the monitoring well or a shallow surface fault or a crack activated by the high-pressure supercritical CO2 injected underground is prevented.

The invention discloses a landslide early warning system and method based on modal decomposition and machine learning, and particularly relates to the field of artificial intelligence big data driving in geotechnical engineering and geological disaster prediction and early warning, a data transmission device transmits data monitored by a data monitoring and acquisition system to a monitoring station and a cloud storage server; the data monitoring and acquisition system comprises a displacement sensor, an underground water level sensor, a humidity sensor and a data transmission device; the displacement sensors are arranged on the surface and inside a mountain slope to monitor the displacement of the slope, the underground water level sensors are arranged at the slope top, the slope body and the slope toe to monitor the water level of the slope, and the humidity sensors are arranged on the surface of the slope to monitor weather conditions; the landslide displacement is predicted through a data analysis system, and the data analysis system comprises an SSA-VMD model and a CNN-BiLSTM-Attention model.

The invention relates to a method and a device for early intelligent identification of a large-area potential landslide, and belongs to the technical field of image target identification and geological disaster monitoring, and the method comprises the steps: collecting historical data of a landslide area, obtaining surface deformation rate and gradient data, and forming a sample data set; a potential landslide identification model composed of a data input layer, a feature coding network and an identification result output layer is constructed, the feature coding network is composed of nine cascaded feature learning modules, and each feature learning module is composed of a network hiding layer and a data normalization layer; training and verifying the potential landslide identification model to obtain a final potential landslide identification model; obtaining actual measurement data of the monitoring area; and inputting measured data into the final potential landslide identification model, and outputting a potential landslide identification result of the monitoring area. According to the method, potential landslide candidate points and non-hidden-danger points in a large-area range are distinguished, and reliable technical support is provided for landslide disaster prevention and control.

The invention provides an anchoring slope landslide instability risk evaluation method under a rainfall condition, and belongs to the technical field of geotechnical engineering and geological disaster prevention and control, and the method comprises the steps: constructing a theoretical calculation formula of a multilayer rock-soil body anchoring slope stability coefficient under a rainfall infiltration effect based on a segmented slip plane method; based on a Monte Carlo probability analysis framework, introducing a reliability index, and establishing a slope reliability integrated evaluation model; acquiring soil body, rainfall, support and geometric parameter data of the side slope; defining various parameters as random variables, and performing large-scale sampling calculation based on the theoretical formula; counting probability distribution of the stability coefficient, and solving a reliability index and a failure probability; establishing a risk monitoring criterion, and judging whether each index exceeds a permissible value or not; and implementing risk dynamic early warning based on a judgment result. According to the method, an integrated evaluation technology system for the reliability of the anchored side slope under rainfall suitable for the multi-layer rock-soil body is constructed, and efficient quantification of the reliability of the side slope under the multi-parameter coupling effect is achieved.

The invention relates to the technical field of geological disaster monitoring, in particular to a rock collapse accumulation body debris flow tendency intelligent evaluation system and method based on multi-parameter coupling. The method comprises the following steps: acquiring geological structure data of a rock collapse accumulation body; performing potential unconsolidated formation analysis according to the geological structure data to obtain potential unconsolidated formation data; performing rainfall infiltration analysis according to the potential unconsolidated formation data to obtain infiltration rate data; determining the water content state of the accumulation body according to the infiltration rate data; performing stability analysis according to the water-containing state of the accumulation body to obtain accumulation body stability data; identifying a potential sliding section based on the accumulation body stability data; detecting flow energy according to the potential sliding section to obtain sliding power data; and performing hydrological confluence analysis according to the geological structure data to obtain hydrological confluence data. According to the method, the accuracy of identifying and evaluating the debris flow tendency of the rock collapse accumulation body is improved based on a geological disaster monitoring technology.

The invention provides a drainage channel structure of a geological disaster control project and a construction method of the drainage channel structure, and relates to the technical field of drainage channels. The drainage channel structure of the geological disaster control project comprises an excavated U-shaped drainage channel body, a channel body supporting structure is arranged in the drainage channel body, and the channel body supporting structure comprises a first supporting layer and a second supporting layer arranged on the inner side of the first supporting layer; the first supporting layer comprises U-shaped supporting walls and a U-shaped concrete platform which are matched with the U-shaped drainage channel body, the U-shaped supporting walls are embedded in supporting wall setting cavities so as to form the first supporting layer with the U-shaped concrete platform, and the U-shaped supporting walls are formed by filling stone cages with broken stones; the second supporting layer is a concrete layer, and waterproof geotechnical cloth is arranged between the second supporting layer and the first supporting layer. The concrete layer of the second layer is not prone to cracking or damage, the canal body supporting structure is more stable, and the service life is longer.

The invention discloses a red clay excavation side slope collapse emergency disposal and treatment construction method, and belongs to the technical field of geological disaster prevention and side slope engineering. According to the method, through six-step integrated construction of monitoring, closing, reinforcing, back pressing, structure and slope protection, rapid emergency rescue and long-acting treatment of red clay slope collapse are achieved. The method has the advantages of being rapid in construction, small in traffic influence, low in cost, lasting in treatment effect and the like, and is suitable for comprehensive treatment of red clay slope slump in projects such as highways and railways.

The present application relates to geotechnical engineering and geological disaster prevention technical field, specifically disclose a kind of combined bedrock reconstruction and slope modification multi-cladding layer slope and its construction method, the present application is strengthened by constructing cemented rock-embedded groove the binding force of slope and bedrock, form anti-sliding "structure pile" effect, control bedrock seepage passage, significantly improve the overall collaborative stability of slope-bedrock;In the process of layered filling, embedded cemented soil and rock interlayer body, constitute continuous, multi-level interlayer structure, enhance the integrity of structure, overcome the problem of localization of traditional supporting structure;By being arranged between cemented soil and rock interlayer body and conventional soil and rock mixture embedded cemented layer gravel drainage groove, realize multi-channel grading drainage and anti-seepage function in slope, effectively reduce pore pressure;Through conventional drainage facilities and the drainage structure inside slope cooperation, form "upper cut, surface guide, lower discharge, buffer" four-in-one composite drainage system, improve the anti-sliding performance and seepage control ability of slope.

This application discloses a method and apparatus for identifying and imaging landslide geological bodies, comprising the following steps: constructing an initial model of the landslide geological body based on landslide disaster data of the target area; performing geophysical simulation based on the initial model to extract field data acquisition parameters of the target area; conducting natural and / or artificial electric field detection based on the field data acquisition parameters to obtain electric field observation data; inverting the electric field observation data to extract imaging data; and performing inversion imaging based on the imaging data to obtain a two-dimensional profile and a three-dimensional slice of the target area. The technical solution of this application can perform detailed identification and imaging of landslide geological disaster structures, providing crucial data information for subsequent landslide geological disaster early warning and engineering management. Its advantages of low cost, speed, high precision, and non-destructive green exploration are significant.

1. The name of this design product: Deformation detection radar. 2. Application of this product design: It is used for deformation monitoring in areas such as high and steep slopes, road / railway slopes, geological disaster risk points, tailings ponds (dams), open-pit mining areas, water conservancy projects, and geological disaster emergency rescue. It is especially suitable for field geological disaster emergency rescue monitoring and fixed monitoring equipment for slope construction. 3. The key point of the design of this product lies in its shape. 4. The picture or photo that best illustrates the design points: three-dimensional picture.

The invention relates to the technical field of ecological restoration monitoring, and discloses a landslide monitoring device and method for mine ecological restoration, and the device comprises a shell which comprises a cylindrical part shell and a moving part longitudinally connected to the part shell in a sliding manner, and a signal transmitting module is arranged at the top of the moving part; the inclination measuring piece is arranged at the bottom of the component shell; the conical head is arranged at the bottom of the inclination measuring piece; the spring rods are horizontally arrayed in the circumferential direction of the component shell, the protection plates are arranged at the ends of movable rods of the spring rods, and clamping rings are arranged on the spring rods; the installation ring is arranged on the inclination measuring piece in a sleeving mode, the arc-shaped plates and the connecting plates are arranged above the installation ring, sliding blocks are hinged to the tops of the arc-shaped plates, the connecting plates are connected with the sliding blocks in a sliding mode respectively, and connectors are arranged at the ends of the connecting plates; the device can be quickly and accurately arranged on a steep slope in a large scale, is damage-resistant, and improves the geological disaster monitoring capability and the safety guarantee level of a mine ecological restoration area.

The invention discloses a multi-mode intelligent interpretation method and system for collapse remote sensing monitoring. The method comprises the following steps: firstly, acquiring and preprocessing multi-source remote sensing data; the multi-source remote sensing data comprises a true color image RGB (Red-Green-Blue), a near infrared wave band NIR (Near-Infra) and a digital elevation model DEM (Digital Elevation Model), and the method comprises the following steps of: acquiring the multi-source remote sensing data; inputting the multi-source remote sensing data into a collapse remote sensing monitoring network, and outputting five types of collapse erosion bodies with preset scales; according to the method, the landform information represented by the high-resolution remote sensing image and the digital elevation model is comprehensively utilized, and various interactive prompts such as text description, voice instructions and geometric elements are combined, so that the precise, efficient and interactive intelligent recognition and boundary interpretation of the collapse hill are realized under the driving of the domain knowledge graph. The system is especially suitable for professional application scenes which require high precision, high flexibility and support natural interaction, such as natural resource investigation, geological disaster monitoring and the like.

The application discloses a kind of prediction methods of damming dam geometric form parameters, comprising: obtaining physical parameters and topography and geomorphology parameters to establish the calculation model of damming dam formation process;Analysis landslide volume, sliding surface inclination, landslide body natural repose angle and landslide speed influence on damming dam geometric form parameters obtain the fitting formula.Distribution position and volume of potential landslide body entering valley are obtained, based on the distribution position and the volume of potential landslide body entering valley, the volume of potential landslide body entering valley per unit time is obtained;Compare the volume of potential landslide body entering valley and river flow, to determine whether damming dam can be formed;Obtain the state parameters of potential landslide body and potential damming dam;Based on the geometric formula, the state parameters of potential landslide body and potential damming dam, the geometric form parameters of damming dam are predicted.The application can predict the geometric form of potential damming dam in advance, and provide a new method for the prediction and early warning of mountain damming dam geological disasters.

This invention relates to the field of mine geological disaster control and geotechnical engineering testing technology, and particularly to a device and method for simulating and testing the seepage and particle migration of glacial till under rainfall conditions. The device includes a rainfall simulation mechanism, a glacial till seepage simulation mechanism, a seepage monitoring system, and a migration and seepage monitoring system. The glacial till seepage simulation mechanism includes a cylinder, and the monitoring end of the seepage monitoring system is located inside the cylinder. By setting up a rainfall simulation mechanism and a cylinder, and placing the monitoring end of the seepage monitoring system inside the cylinder, this invention allows the seepage monitoring system to monitor the seepage and moisture content changes of glacial till samples at different depths in real time. The migration and seepage monitoring system collects infiltrated water and migrating fine particles, enabling researchers to determine the rainwater infiltration situation of this type of glacial till sample and the migration pattern of fine particles under infiltration conditions based on the amount of water and fine particles collected by the migration and seepage monitoring system.

A bedding landslide disaster risk evaluation method based on machine learning comprises the following steps: step 1, acquiring landform image data of a certain area, identifying different types of bedding landslide hidden danger points according to development features and landform features of bedding landslide, and constructing a bedding landslide feature sample library; and 2, under the condition that the bedding landslide feature sample library is constructed, carrying out bedding landslide hidden danger identification on an unknown region by utilizing machine learning, and further obtaining bedding landslide geological disaster data of the region. The method is used for solving the problems that an existing assessment method is limited by complexity and cost of data collection, and the processing capacity for multi-factor influence is limited, so that the risk assessment precision is not high.

The present invention discloses a method for simulating the three-dimensional morphological evolution of underground coal fire burnout areas, and belongs to the field of geotechnical engineering geological disaster prevention and control. Sentinel-1A image data is obtained, and the DS-InSAR technology is used to extract the cumulative surface deformation value and the ArcGIS software is used to extract the cumulative surface deformation contour line; according to the stratigraphic parameters, surface temperature, three-dimensional temperature field and cumulative surface deformation contour line data of the area recorded in the data, a three-dimensional morphological prediction model of the underground coal fire burnout area is constructed in a computer using numerical simulation and three-dimensional modeling technology, and the three-dimensional morphological evolution process of the underground coal fire burnout area is inverted, and the formation of the underground coal fire burnout area after the coal seam is burned is simulated, and the three-dimensional morphological inversion result of the underground coal fire burnout area is verified. The method realizes the description of the geometric structure of the underground coal fire burnout area, reveals the morphological changes of the underground coal fire burnout area and its relationship with factors such as surface deformation, and provides a new scientific basis for understanding the spatial characteristics and control factors of underground coal fires.