247 results about "Geologic hazards" patented technology

The invention relates to the technical field of side slope geological disaster monitoring, and discloses a side slope long-term monitoring early warning and threshold value dynamic adjustment method, which comprises the following steps: S1, deploying a plurality of sensors on a side slope; s2, preprocessing the collected original data; s3, setting an early warning threshold value for the key feature index; s4, dynamically evaluating and predicting the stable state of the slope in real time; s5, dynamically correcting and optimizing the initial early warning threshold value set in the step S3; s6, when the key characteristic index value exceeds the newest early warning threshold value, early warning is triggered; and S7, generating early warning information of different levels. The method solves the problems of tedious configuration of slope monitoring early warning threshold values and false alarm and missing alarm, achieves the adjustment and configuration of a unified threshold value through an efficient early warning trigger judgment disposal and threshold value dynamic adjustment mechanism, effectively improves the alarm success rate and early warning disposal efficiency, remarkably reduces the false alarm rate / missing alarm rate of slope early warning, and improves the safety of slope early warning. And the interference of the early warning system on residents is greatly reduced.

The invention relates to the field of coal mine geological disaster monitoring, in particular to a coal mine surface slope remote sensing data fusion monitoring method and system, and the method comprises the steps: collecting multi-source data through a satellite-unmanned aerial vehicle-ground three-stage network, and carrying out the cleaning, correction and standardization preprocessing; utilizing an improved LSTM model which introduces an attention mechanism and a geological parameter correction item to predict slope displacement and risk levels; distributing monitoring resources through a PSO (Particle Swarm Optimization) algorithm, dynamically adjusting an equipment state through a fuzzy PID (Proportion Integration Differentiation) algorithm, and fusing multi-source data through a Bayesian algorithm to generate a high-dimensional matrix; and finally, storing data based on the alliance chain and performing early warning based on a dynamic threshold value. The system correspondingly comprises six core modules. The problems of narrow coverage, poor timeliness and low data utilization rate of traditional monitoring are solved, millimeter-level precision monitoring is realized, the early warning response is less than or equal to 5 minutes, the cost is reduced by more than 40%, and the method is suitable for safety and ecological monitoring of various coal mine slopes.

The invention discloses a geological disaster risk evaluation method and system based on big data, and the method comprises the following steps: S1, obtaining multi-source geological disaster data, including geological structure data, landform data, meteorological and hydrological data, human activity data and historical disaster data; s2, performing space-time alignment and standardization processing on the multi-source geological disaster data, and constructing a geological disaster space-time data set; s3, constructing a geological disaster risk evaluation model based on the deep learning network, wherein the geological disaster risk evaluation model comprises a feature extraction module, a space-time correlation module and a risk prediction module; s4, calculating a weight coefficient of each evaluation index by adopting a dynamic weight distribution method; s5, calculating a geological disaster risk index through the geological disaster risk evaluation model, and generating a risk grade zoning map; according to the invention, more intelligent geological disaster risk evaluation of the urban area is realized.

The invention provides a method and system for analyzing a highway risk range based on geological disaster point data, and the method comprises the steps: obtaining geological disaster point data and highway network data, and storing the geological disaster point data and the highway network data; searching and determining a road section closest to each geological disaster point, determining a vertical point of each geological disaster point on the corresponding closest road section, and calculating a relative position of the vertical point on the road section; automatically determining a stake number corresponding to a vertical point according to a starting point stake number, a stopping point stake number and a relative position of a road section stored in the road network data; and generating a road risk range analysis result at least based on the stake number corresponding to the vertical point. According to the method, through rapid intelligent interpretation of geological disaster point space data, related units can be assisted to rapidly position a disaster risk range, then the potential threat range of the related units to a highway network is accurately defined, and the scientific and refined level of highway geological disaster prevention and engineering management is improved.

The invention relates to the technical field of geotechnical engineering and geological disaster monitoring, in particular to a rockburst tendency dynamic discrimination method, and aims to solve the limitation caused by the fact that a dynamic evolution process is simplified into a quasi-static attribute in traditional rockburst tendency evaluation. According to the method, rockburst tendency is defined as a hidden state variable evolved along with time, a physical constraint state space model containing a hidden state kinetic equation and a multi-modal observation equation is constructed, continuous stress-strain and discrete acoustic emission data are fused, hidden state probability distribution is estimated in real time through online Bayesian inference, and the probability distribution of the hidden state is estimated in real time. And in combination with adaptive information weight updating and physical consistency constraint, predicting a future state trajectory, calculating a risk probability exceeding a critical threshold, and outputting a dynamic rockburst tendency level. According to the scheme, continuous, dynamic and prospective judgment of the rockburst tendency is realized, and the accuracy and reliability of early warning are improved.

The invention discloses an extreme rainfall induced geological disaster chain risk evaluation method, and relates to the technical field of geological disaster risk evaluation. Comprising the steps of defining extreme rainfall induced geological disaster chain danger, selecting susceptibility evaluation indexes and grading, constructing a geological disaster susceptibility evaluation model based on a multi-element machine learning model, constructing a geological disaster susceptibility evaluation model based on a multi-element machine learning integrated model, and evaluating the susceptibility of an extreme rainfall induced geological disaster chain. And assessing the risk of the geological disaster chain induced by the extreme rainfall. According to the method, based on an optimal model, the comprehensive susceptibility and danger of extreme rainfall-collapse, extreme rainfall-landslide, extreme rainfall-debris flow and extreme rainfall induced geological disaster chains are evaluated respectively; the comprehensive risk assessment method for the extreme rainfall-collapse chain, the extreme rainfall-landslide chain, the extreme rainfall-debris flow chain and the extreme rainfall induced geological disaster chain is constructed, and a new thought is provided for risk assessment research of the extreme rainfall induced geological disaster chain.

According to the slope geological disaster risk assessment method and system provided by the invention, the feature information of the slope object can be accurately assessed by obtaining the non-natural vibration data and combining the hidden danger description factor information of the slope object, so that the adjacent slope objects around the target slope object are considered together in the slope object set, and the risk assessment accuracy is improved. Comprehensive analysis of a target slope object is formed through slope hidden danger data features in the slope object set, and then feature extraction of important hidden dangers is carried out on the target slope object set to obtain a description vector of the target slope object set; and according to the description vector regression of the target slope object set, whether the slope object attribute of the target slope object affects the slope geological disaster risk assessment result is analyzed, the slope object attribute is used for representing the attribute affecting the hidden danger of the slope object, and the regression analysis accuracy of the attribute change of the slope object is improved. And the accuracy and confidence of evaluation are ensured.

The invention discloses a landslide geological disaster deduction method and system based on an MPM method, and the method comprises the steps: collecting the multi-source data of a disaster scene, and synchronously constructing a digital twinborn model; a qualitative and quantitative two-stage inversion calibration model is adopted; a qualitative layer combines a monitored displacement direction and a deformation mode, and preliminarily inverts key parameters such as slip band cohesive force and an internal friction angle; the quantitative layer comparison model calculates the actual deformation range, collapse position and displacement, and parameters are optimized to match the actual landslide state; in landslide long-term evolution deduction, a rock-soil body aging characteristic model is embedded, an exponential function is used for describing annual scale parameter deterioration, prediction is divided into continuous analysis steps, MPM calculation is carried out based on a material point method, full-cycle simulation from the current year to the future years is completed, and deformation range, displacement and outburst risk results are output. And reliable decision support is provided for disaster prevention and reduction.

The invention provides a collapsed rockfall accurate identification and monitoring method and device based on AI and machine vision, and relates to the technical field of geological disaster monitoring, and the method comprises the steps: collecting the multi-modal visual data and environmental parameters of a collapse hidden danger region through a cooperative collection system; performing recognition, contour extraction and spatial parameter calculation on the multi-modal visual data through the recognition and positioning model to obtain a contour sequence, a volume sequence, a spatial coordinate sequence and a spatial attitude sequence of the collapsed rockfall; on the basis of the space coordinate sequence, the space attitude sequence and the multi-modal visual data, predicting the movement track and the speed sequence of the collapsed rockfall through a mixed time sequence AI model; inputting the environment parameters, the contour sequence, the volume sequence, the motion trail and the speed sequence into a kinetic energy calculation model, and calculating to obtain the impact energy of the collapsed rockfall; according to the contour sequence, the volume sequence, the motion trail, the speed sequence and the impact energy of the collapsed rockfall, the collapsed rockfall risk level is obtained through calculation.

The invention provides a debris flow risk assessment method and system based on debris flow parameter probability inversion calibration, and relates to the technical field of geological disaster risk assessment. According to the technical scheme provided by the embodiment of the invention, an effective means is provided for scientifically identifying debris flow parameters, and the method is particularly suitable for setting single gullies which are limited in detailed observation and cannot directly measure the parameters. A traditional method depends on statistical parameters or deterministic back analysis, the former introduces errors due to poor regional adaptability, and the latter has the problem of non-uniqueness of parameters; according to the scheme, the parameter posteriori distribution is updated by combining the Bayesian framework with historical observation data (debris flow influence areas), so that the standard deviation of key parameters is generally reduced. In the embodiment of the invention, the influence area is taken as core observation information, the practical limitation that the flow depth and the flow velocity are difficult to observe in real time in the debris flow event is avoided, the observation information can be obtained through post-event field investigation or satellite images, and the scheme is high in practicability.

The invention belongs to the field of geologic disaster prevention and control of geotechnical engineering, and provides a multi-scale numerical simulation method for a slope instability mechanism of a ductile shear zone, which comprises the following steps: acquiring physical and mechanical parameters of a rock-soil body material, and establishing a numerical model based on a particle flow discrete element method; a Johnson-Kendall-Robert contact model is adopted as a contact model between particles, the contact force between the particles is calculated, and meanwhile, a pressure interference parameter is defined to control the limit value of normal contact rigidity; performing dynamic modeling of the discrete element particle system based on a particle generator; static modeling of a discrete element particle system is carried out based on a Lagrange body continuous unit component; the acting force of discrete element particles is converted into equivalent grid node force through an equivalent node force conversion method, and surface attributes of all unit sets possibly involved in contact are defined in a solver.

The invention discloses a landslide hazard hidden danger point intelligent identification method based on unmanned aerial vehicle multispectral remote sensing, and relates to the technical field of geological disaster monitoring and unmanned aerial vehicle remote sensing intelligent identification. Comprising the following steps of (1) data acquisition and preprocessing, (2) trajectory disturbance feature mining, (3) spectral feature enhancement and space-time filtering, (4) bimodal coupling analysis and intelligent identification, and (5) closed-loop verification and route optimization. According to the method, the problem of data dimension splitting and error processing unidirectionality is solved by reserving the trajectory offset original value and constructing the fusion data set, and the data utilization rate is increased; through multi-disciplinary cross modeling and coupling knowledge base construction, a disciplinary blank is filled, and an unmanned aerial vehicle-environment-geology dynamic mutual feedback mechanism is established; by means of bimodal feature enhancement, anti-factual reasoning and route optimization, the recognition efficiency of the early hidden landslide hidden danger is effectively improved, the development stage of the hidden danger can be distinguished, and the high-precision and early recognition requirements are met.

The invention relates to the technical field of coal mine gas geological disaster prevention and control and intelligent identification, and discloses an underground coal mine gas geological abnormal body intelligent identification and grading early warning method and system, and the method comprises the steps: S1, collecting multi-source heterogeneous monitoring data in an underground coal mine target region, and carrying out the standardization processing and time-space reference unification; s2, constructing a multi-dimensional feature fingerprint database based on a historical or accumulated standardized data set; s3, acquiring real-time multi-source monitoring data for the current tunneling process or detection process, and extracting features of the real-time multi-source monitoring data; based on the multi-dimensional feature fingerprint database, adopting an evidence theory to carry out fusion calculation on a plurality of extracted real-time feature evidences to obtain a comprehensive confidence identification result of a specific type of gas geology anomalous body existing in a front unrevealed area; and S4, generating graded early warning information according to the comprehensive confidence identification result and a preset risk grade threshold. According to the invention, advanced identification, risk assessment and targeted early warning of geological disasters such as underground gas outburst are realized.

The invention discloses a method and device for evaluating the susceptibility of rainfall-induced landslide based on side slope geometrical characteristics, and belongs to the technical field of landslide geological disaster prevention and control. The method comprises the following steps: based on a side slope to be evaluated, establishing a standard three-dimensional side slope model, establishing simulated three-dimensional slope models with different gradients and different fluctuation degrees based on the standard three-dimensional slope model; the slope roughness coefficient of each simulated three-dimensional slope model and the safety coefficient of each simulated three-dimensional slope model in different rainfall stages are calculated, and the slope roughness coefficients are obtained based on slope geometric feature calculation and the standard three-dimensional slope model; and fitting the linear relationship between the slope roughness coefficient and the safety coefficient of each simulated three-dimensional slope model in the same rainfall stage to obtain the corresponding relationship between the slope roughness coefficient and the safety coefficient in different rainfall stages. According to the method, the rainfall-induced landslide susceptibility of the slope can be accurately and efficiently evaluated.

The invention provides a high-filling slope ecological protection construction method, and relates to the technical field of slope protection engineering. The construction method comprises the following implementation steps: step 1, slope pretreatment; the method comprises the following steps: firstly, shaping and trimming a high-filled side slope, cleaning surface topsoil, gravels and weeds, and synchronously presetting a through-type drainage system at the top, the waist and the toe of the side slope; comprising the four steps of anchor rod laying, grouting and anchoring, lattice beam pouring and geogrid laying, specifically, drilling is conducted on the trimmed slope surface of the side slope, anchor rods are laid, lattice beams fixedly connected with the anchor rods are formed through pouring, then the geogrids are flatly laid in the coverage area of the lattice beams, and double fixing is completed. The anti-sliding stability of the slope body is enhanced, the geogrids can disperse the load of the slope body, the shear strength of the surface soil body of the slope is improved, the overall stability of the high-filled slope is remarkably improved, and geological disasters such as landslide and collapse of the slope are effectively prevented.

The invention discloses a slope dangerous rock mass stability evaluation method and system based on kinetic parameters, and relates to the technical field of geological disaster risk evaluation, and the method comprises the steps: determining an instability mode based on the development characteristics and development environment of a to-be-evaluated slope dangerous rock mass; dangerous rock mass vibration characteristics and bed rock vibration characteristics of the slope dangerous rock mass to be evaluated are collected respectively; calculating dynamic characteristics of the slope dangerous rock mass to be evaluated based on the dangerous rock mass vibration characteristics and the bed rock vibration characteristics; based on a preset stability scoring table corresponding to the instability mode, scoring the development characteristics and the dynamic characteristics to obtain a scoring result; and carrying out stability evaluation on the to-be-evaluated slope dangerous rock mass based on the scoring result. According to the invention, the technical problems of insufficient evaluation result adaptability and low precision in the prior art are solved.

The invention belongs to the technical field of image processing, and particularly relates to a geological disaster risk area dynamic updating method based on slope unit automatic segmentation. Comprising the following steps: 1, acquiring digital elevation model raster data covering a target area and remote sensing image raster data spatially aligned with the digital elevation model raster data, and outputting slope unit vector data; 2, acquiring disaster-bearing body vector data, performing spatial superposition on the disaster-bearing body vector data and the slope unit vector data, and combining outer boundaries of slope units of all geological disaster risk areas to generate risk area vector boundary data; 3, generating new year risk area vector boundary data based on the new year data; and updating the risk area vector boundary data of the last year based on the risk area newly-added area and the risk area reduced area. According to the method, the slope unit division precision, the disaster-bearing body exposure description capability and the timeliness of risk area range updating are remarkably improved.

The invention provides a geotechnical engineering geological disaster prediction method and system for mining exploitation, and relates to the technical field of geotechnical engineering, and the method comprises the steps: S1, obtaining multi-dimensional data from different regions of a mining area in real time through a plurality of data collection devices, S2, carrying out the denoising, abnormal value correction, space-time alignment and missing value supplementation of the multi-dimensional data obtained in S1, and obtaining a prediction result; and the dynamic time window technology is adopted to process the time sequence data, so that the data under different time scales can be effectively synchronized, and accurate alignment and dynamic updating of the data are ensured. According to the geotechnical engineering geological disaster prediction method and system for mining exploitation, the fusion problem of multi-source heterogeneous data is effectively solved by combining the advantages of fuzzy logic and a neural network through an adaptive neural network-fuzzy hybrid algorithm. The fuzzy logic model carries out modeling on spatial and temporal changes of different data sources, and the influence degree of each data source on disaster prediction is accurately evaluated by dynamically adjusting parameters of a membership function.

The invention discloses a method for monitoring instability of a soil-rock interface slope under the action of water immersion, and belongs to the field of geological disaster monitoring and geotechnical engineering.The method comprises the following steps that a three-dimensional geological model containing a soil-rock interface is constructed based on a slope geological survey result; arranging a multi-type sensor monitoring network based on the three-dimensional geologic model to collect multi-source monitoring data; calculating a key stability index based on the multi-source monitoring data; on the basis of the key stability indexes, a comprehensive evaluation index is established by adopting a multi-parameter fusion method, a graded early warning threshold value is set, and real-time early warning of the slope stability state is achieved; meanwhile, constructing a multi-dimensional time sequence characteristic matrix based on historical and real-time monitoring data, and predicting the slope instability trend based on the multi-dimensional time sequence characteristic matrix by adopting a gating cycle unit GRU model to obtain advanced early warning data; and carrying out evaluation and graded early warning on the slope state based on real-time early warning and advanced early warning data.

The utility model relates to the technical field of mine geological disaster detection, in particular to a mine geological hidden disaster detection device which comprises a box body, and a detector is installed on the inner wall of the box body. The supporting mechanism capable of stably supporting the disaster detection device is arranged on the inner wall of the box body; through the arrangement of the supporting mechanism, when the disaster detection device is used, two supporting plates at the bottom of the box body can move downwards through second electric push rods to support the box body, the height of the box body can be adjusted through stretching and retracting of the second electric push rods, and when the disaster detection device encounters an uneven ground, the box body can be supported by the second electric push rods. The limiting bolt and the supporting plate are matched to move downwards to support the supporting plate, so that the disaster detection device is kept stable, the protective pad at the bottom of the limiting bolt can support the box body, the friction coefficient between the disaster detection device and the ground is increased, the disaster detection device can be stably supported, and the stability of the disaster detection device is improved.

The application discloses a geological disaster crack measuring device based on laser measurement and belongs to the technical field of laser ranging. The device comprises a bottom frame, an electrically connected sliding frame slidably arranged in a circular electric guide rail, a laser measuring device fixedly installed on one side of the sliding frame, an inner rod and a lower cylinder body slidably arranged in the fixed cylinder, a taper rod fixedly connected to the lower surface of the lower cylinder body, a push rod fixedly connected to the lower surface of the inner rod, a rotating support mechanism and a pressing lock mechanism arranged in the lower cylinder body, wherein the rotating support mechanism rotates and abuts against the inner walls on both sides of the crack when the rotating support mechanism descends, and the pressing lock mechanism enables the rotating handle to rotate synchronously when the rotating handle descends, and the pressing lock mechanism enables the rotating handle to be pressed and clamped and pressed and released along the limit multi-faces formed by the special-shaped guide plate and the special-shaped guide seat, so that the rotating handle can be quickly locked and unlocked in the crack before measurement. Through the cooperative design of the rotating support mechanism and the pressing lock mechanism, the stability, operation efficiency and environmental adaptability of the geological disaster crack measuring device are remarkably improved.

The application discloses a landslide susceptibility comprehensive evaluation method, system, device, medium and product, relates to the technical field of geological disaster prediction, and the method comprises the steps: taking the SBAS-InSAR deformation rate as a dynamic deformation factor, combining a static environmental factor, and constructing an original feature dataset; adopting a recursive feature elimination algorithm, performing importance sorting and iterative elimination on evaluation factors in the original feature dataset, determining an optimal feature subset, training an RFE-RF-XGBoost cascade integrated model; inputting the optimal feature subset corresponding to all grid units in the research area into the trained RFE-RF-XGBoost cascade integrated model, determining a landslide susceptibility spatial classification map, verifying and locally correcting different risk level regions divided in the landslide susceptibility spatial classification map, and determining a landslide susceptibility evaluation result, so that the timeliness and accuracy of the landslide susceptibility evaluation result are improved.

The application provides a method and device for correlatively characterizing stress drop and micro cracks of granite joints under multiple working conditions, computer equipment and a readable storage medium, relates to the technical field of deep hard rock engineering mechanics and geological disaster warning, and the method comprises the following steps: constructing a Voronoi-GBM numerical model; constructing a multi-objective optimization function for optimizing multiple micro mechanical parameters; optimizing the micro mechanical parameters of the Voronoi-GBM numerical model based on the multi-objective optimization function; simulating the operation of multiple granite shear working conditions by using the optimized Voronoi-GBM numerical model; and taking the micro crack characteristic parameters as input samples and the macro stress drop characteristic parameters as output samples, and training a target correlation characterization model. The scheme can effectively mine the correlation characterization of stress drop and micro cracks of granite joints, and realize the prediction of macro stress drop behavior from the micro crack characteristics.

The invention discloses a method, a system, a storage medium and equipment for determining the occurrence time and frequency of debris flow in an unmanned area based on the size of lichen, and relates to the technical field of geological disaster monitoring and dating, and the method comprises the steps of S1, condition setting, S2, lichen data acquisition, S3, lichen growth rate fitting, and S4, time and frequency determination. The method is characterized in that the exposure time of lichens is calculated according to the average diameter of ground clothes and the actual growth rate of the lichens in combination with the initial diameter of the lichens, the occurrence time of debris flow is determined according to the exposure time of the ground clothes, and the occurrence frequency of the debris flow is obtained according to the occurrence time of the debris flow. The technical problem that the time and frequency of debris flow events in depopulated areas are difficult to determine is effectively solved.

The invention discloses a green recovery ecological restoration method for a mine goaf, and relates to the technical field of ecological restoration. Rock surface treatment is firstly carried out, the exposed rock surface of a mine is cleaned, and broken stones are prevented from falling off during construction; then, regreening planting is carried out, and seedling transplanting is carried out on the reconditioned rock surface; and then vegetation maintenance is carried out, the planted seedlings and the sown grass seeds are maintained, and the vegetation can root and germinate. According to the method, through vegetation reconstruction and ecological restoration, surface coverage is rapidly restored, water and soil loss is reduced, geological disaster risks such as landslide and debris flow are effectively restrained, and the life and property safety of the mining area and surrounding residents is prevented from being threatened; the hyperaccumulator can also be used for purifying soil heavy metal pollution, and is matched with vegetation to adsorb dust and regulate microclimate, so that the regional air quality and ecological environment are remarkably improved; meanwhile, the regreening mining area can be transformed into an ecological park, a carbon sink forest or an agricultural base, and the land value is increased.

The application relates to the field of metal mine mining design, and particularly discloses a metal mine self-adaptive mining method based on geological-ground pressure response dynamic feedback, which comprises the following steps: obtaining geological exploration core and geophysical prospecting data of a metal mine area to be mined, determining target data according to the data, constructing a three-dimensional geological disaster model according to the target data, determining the ore body mining environment of each target point according to the model, and then obtaining a plurality of mining units; determining a target mining unit and a plurality of self-adaptive mining technical schemes from the units, calculating the mining ground pressure response and mining cost of surrounding rock in each scheme according to the model, determining a final mining scheme, mining the target mining unit based on the final mining scheme, monitoring the mining ground pressure response index of the surrounding rock, supporting the target mining unit according to the monitoring result, updating the model based on the target data indicated by the mining site after the mining is completed, returning to the step of determining the target mining unit until the mining is completed.

The invention discloses a grouting and filling mining ground surface deformation monitoring system and method, and belongs to the technical field of mine ground surface deformation monitoring, the system comprises a multi-source data monitoring module, a three-dimensional deformation resolving module, a data processing and early warning module, an integrated geological radar, a ground subsidence monitor, an unmanned aerial vehicle remote sensing device and a micro-nano sensor network, multi-source data collaborative collection of an underground stratum structure, earth surface three-dimensional deformation and stratum stress is achieved, and the three-dimensional deformation resolving module completes high-precision three-dimensional displacement resolving by dynamically adjusting a lateral pressure coefficient, improving a horizontal movement coefficient and fusing radar sight line direction deformation data and a constraint equation. And the data processing and early warning module triggers four-stage dynamic early warning and is linked with the mine production system through denoising, space-time registration, multi-scale fusion and neural network prediction. According to the invention, high-precision, large-range and real-time monitoring of real three-dimensional deformation of the earth surface is realized, and geological disasters such as earth surface settlement and collapse caused by grouting, filling and mining are effectively prevented.

This invention discloses a method for the exploration and analysis of karst collapse geological hazards, specifically relating to the field of geological hazard exploration and analysis. The method includes: after collecting current and historical images of a target area on a cloud-based collaborative platform, performing image pairing based on shooting location, shooting orientation, and coverage boundaries; dividing the overlapping areas of each image pair into land tables; and outputting image pairs and land table sequences. For land tables with the same sequence number in each image pair, extracting the boundaries of open water, wet soil, bare soil, vegetation, and shadow, and writing a single land surface marker based on the first digit of the enclosed area. This invention addresses the problem in existing technologies where inconsistent surface conditions between different exploration images are easily misjudged as collapse evolution changes by performing image pairing, land table division, single land surface marker generation, non-comparable grid re-sampling and backfilling, and comparable grid segment change determination.

The invention relates to the field of mine pit treatment, and particularly discloses a waste mine pit recovery treatment method which comprises the following steps: geological disaster prevention and treatment, one or more treatment of slope cutting, danger clearing, anchoring or retaining wall supporting on an unstable slope of a pit wall area to form waste slag and waste rocks, and stacking part of the waste slag and waste rocks in a slag top area; slope treatment is conducted, specifically, step-by-step slope making is conducted through the excavation slope ratio of 1: 1.25-1: 2, and step-by-step slope making is formed; performing land reclamation and construction to form a retaining wall, a drainage ditch and a slope safety isolation net; covering surface soil, and covering external soil with soil; vegetation recovery; and monitoring, managing and protecting. According to the scheme, when geological disaster prevention and treatment and side slope treatment are carried out, the pit wall area is sequentially constructed, comprehensive slope cutting and danger removing treatment can be carried out on the unstable side slope, stepped slope forming can be sequentially carried out, the final stepped slope forming strength is improved, and the follow-up collapse and landslide danger is reduced.