546 results about "Slope gradient" patented technology

The invention discloses a loess slope stability intelligent monitoring method and system, and the method comprises the steps: carrying out the regional differentiation modeling of multi-source data of a target region, and outputting slope change data; according to the period-by-period displacement time sequence data, a slope deformation trend is obtained through prediction based on an LSTM algorithm; and inputting the slope change data, the slope deformation trend and the meteorological rainfall data into a slope stability evaluation model to predict a safety coefficient, and if the safety coefficient is lower than a preset threshold value, issuing early warning information. According to the loess slope stability intelligent monitoring method and system provided by the invention, data such as gradient change and deformation trend are accurately extracted, multi-source data and meteorological rainfall data are fused by means of cross-modal attention, a random forest model is used for learning a multi-factor coupling rule, and finally multi-factor data prediction is integrated to obtain a safety coefficient for early warning. The problem of low early warning reliability caused by difficulty in accurately evaluating the slope stability by fusing multiple factors such as gradient, deformation and meteorological rainfall can be solved.

The invention discloses a grating dam safety evaluation and design method and structure based on debris flow blocking degree. Wherein the safety assessment method comprises the following steps: S100, calculating the safety of the debris flow on the basis of the solid matter concentration of a debris flow susceptible area, the particle size value corresponding to the accumulated content of 95% in a full particle size grading curve, the channel average gradient, the channel average width and the primary debris flow scale in the section range of the grating dam, the minimum particle size value of the maximum boulder in the drainage basin and the opening width of the grating dam; calculating a critical blocking judgment coefficient according to the correlation value of the height of the grating dam, the angle of the wedge-shaped structure and 60 degrees and the correlation value of the total amount of debris flow solid substances and the reservoir capacity of the wedge-shaped beam type grating dam; and S200, evaluating the safety of the grating dam based on the critical blocking discrimination coefficient. The evaluation and design method and structure incorporate the relative relation between the debris flow scale and the dam body storage capacity, meanwhile, the influence on active structure parameters such as wedge-shaped flow guide is quantified, and the blocking state prediction accuracy of the grating dam in actual operation is improved to a certain degree.

The invention relates to the technical field of marine surveying and mapping and submarine topography modeling, and discloses a submarine topography and landform construction method based on multi-source water depth data fusion, which comprises a multi-source data acquisition module, a data preprocessing module, a feature extraction module, a fusion algorithm matching module, a three-dimensional modeling module and an uncertainty evaluation module. A historical submarine topographic map is converted into grid data, namely, submarine topography is discretized into digital representation of regular grid units, water depths of other sources are converted into the grid data, the precision of the water depths of different sources is evaluated by adopting a superposition comparison method, and an error distribution model is established to reasonably correct and fuse the water depth data of various sources. The innovation of the method lies in that topographic feature parameters including the gradient, the curvature matrix and the bionic optimization algorithm are introduced, the defect that a single algorithm is preset in a traditional method is overcome, and the precision of coral reef and fault zone complex areas is improved.

The invention discloses a mountainous area wind field downscaling optimization method based on high-precision simulation, and relates to the technical field of meteorological numerical simulation, and the method comprises the steps: obtaining the terrain elevation data and meteorological monitoring data of a target mountainous area, recognizing slope abrupt change points, constructing a spiral sampling path, calculating a slope change value, determining the distance between sampling points, and generating target sampling data; performing orthogonal decomposition on the sampled data to obtain a frequency component, calculating a surface fluctuation coefficient, and constructing a boundary disturbance equation to obtain surface stress distribution; calculating an airflow motion state based on surface stress distribution, solving a vorticity equation to obtain vorticity characteristics of a leeward area, and calculating airflow motion correction parameters; and carrying out downscaling iterative operation on the corrected parameters and the meteorological monitoring data to generate target area wind field data with hectometer-magnitude spatial resolution. The simulation precision of the local wind field under the complex terrain condition is improved.

The invention relates to an earth surface deformation detection and classification method and system fusing CNN and SBAS-InSAR technologies, and the method comprises the steps: obtaining high-precision deformation data through a small baseline subset and an interference synthesis radar technology (SBAS-InSAR), constructing a CNN classification frame through combining PCA-enhanced optical satellite images, elevation, soil physical parameters, geological landform maps and other multi-source geographic information, and carrying out the detection and classification of the earth surface deformation through the CNN classification frame and the SBAS-InSAR technology. And identification of deformation types such as landslide, settlement and lifting is realized. The process comprises multi-source satellite data acquisition and preprocessing (including InSAR sight velocity decomposition and optical / topographic feature extraction), generation of a preliminary deformation label based on a classification algorithm of a gradient and a deformation velocity threshold, and recognition of a deformation type through a multilayer CNN model. According to the method, the deformation mode is automatically clustered and analyzed in a large-range area, the accuracy and detail performance of deformation type recognition are remarkably improved, the accuracy rate reaches 93%, the method is superior to a traditional method, a stable and extensible tool platform is provided for geological disaster monitoring, and positive risk management of landslide or land subsidence prone areas is assisted.

The invention relates to the technical field of construction resource scheduling, in particular to a water conservancy construction equipment scheduling method and system, and the method comprises the following steps: obtaining on-site point cloud and soil data to construct an environmental resistance field; calculating a dynamic work efficiency matrix by combining the equipment power parameters and the resistance field; generating an initial time sequence chain based on the work efficiency matrix, and calculating an overlapping volume of a three-dimensional space envelope body of the equipment; if there is overlap, the job time is adjusted according to the priority to generate a conflict-free scheduling instruction set. According to the method, the rated work efficiency parameters of different machine types in a specific operation area are corrected in real time by constructing the equipment passing resistance model fusing the terrain gradient and the soil moisture content, the problem that static scheduling cannot adapt to environmental changes is solved, and meanwhile space-time conflict detection logic based on the three-dimensional operation envelope surface is introduced; and when it is recognized that the multi-machine moving tracks are overlapped, avoiding or peak shifting instructions with priorities are automatically generated, and conflict-free collaborative operation of the equipment cluster in a complex water conservancy scene is achieved.

The invention provides an automatic digging method of an excavator based on image recognition, which is realized based on a material pool and the excavator, a laser radar and a binocular camera are arranged on the upper edge of the material pool, and the excavator comprises a digging arm, a double-bucket assembly and a control unit. The method comprises the following steps: determining a peak initial position by a laser radar material pile three-dimensional point cloud, and performing secondary calibration by a camera to obtain a peak final position and a slope angle; the control unit switches a first / second digging mode according to the distance between the wave crest and the excavator, the first mode controls the excavator bucket to conduct wall-attached digging and conduct bottoming detection through the pressure sensor, and the second mode adjusts the angle of the excavator bucket to conduct digging according to the slope angle; when no wave crest exists, a corresponding digging scheme exists, and the point cloud is updated after digging each time; the wave crest positioning precision and the environmental adaptability are improved, the digging efficiency is optimized, manual intervention is reduced, and the device is suitable for digging of materials such as cereals and gravels.

The invention discloses an SMAP soil hydrodynamic downscaling method based on a TOPMODEL theory, and the method comprises the steps: enabling original SMAP data to be matched with DEM data in spatial attributes through standardization processing, and obtaining standardized SMAP data; on the basis of DEM data, a confluence area and a gradient are calculated, and then a terrain index is calculated according to a TOPMODEL model; constructing a time sequence through the standardized SMAP data, and executing space-time stabilization processing to obtain a basic soil moisture field; based on the terrain index and the basic soil moisture field, preliminary soil moisture data is obtained through calculation by means of a downscaling model, and target soil water grating data with high resolution are obtained by optimizing the quality of the preliminary soil moisture data; according to the downscaling method, the structure is simple and clear, batch operation is facilitated, and low-resolution SMAP soil water data can be upgraded into high-resolution soil water data with the same resolution as DEM data in complex terrain areas such as mountainous areas, hills and river valleys.

The invention discloses an identification and treatment method for a water and soil loss priority treatment area of a small watershed slope in a hilly area. The method comprises the following steps: calculating a small watershed soil erosion modulus and a sediment connectivity index, and carrying out geospatial modeling to form a soil erosion and connectivity partition identification priority treatment area; determining the land utilization type and terrain status of water and soil loss, and dividing functional zones from the spatial angles of an upper slope, a middle slope and a lower slope; a water and soil conservation forest is built in a forest and grass vegetation area on the slope or an abandoned cultivated land above a reclamation prohibition slope and a water and soil loss treatment area on the barren mountain and slope according to the principle of suitable land and suitable trees, and water and soil loss is prevented and controlled through natural restoration; water and soil loss prevention and control measures of slope land reclamation-hydrological network optimization and node control-grassland soil fixation and fertility increasing are adopted in a slope water and soil loss treatment area below the reclamation forbidding gradient in the slope; the slope bottom is provided with a plant filter belt, a tail end grit chamber and an ecological ditch measure for desilting and pollution reduction; the problem that a water and soil conservation treatment system in a small watershed is low in treatment degree is solved.

The invention discloses a mountain torrent disaster danger area dynamic demarcation method based on multi-source data coupling, and the method comprises the steps: obtaining meteorological radar rainfall forecast data, surface deformation monitoring data and high-precision DEM topographic data in real time, carrying out the data preprocessing, and generating a fused multi-source data set; constructing a distributed hydrological model, and calculating the production and convergence flow of the sub-basins; training a Seq2Seq-LSTM model on the basis of rainfall-water level-swelling speed time sequence data, predicting danger areas in a future set time period, and dynamically dividing high / medium / low risk areas by adopting an SOM-CLARA clustering algorithm and taking rainfall intensity, earth surface deformation rate and gradient as feature vectors; and determining the early warning level of each risk area in combination with the critical rainfall threshold and the spatial heterogeneity index. Through the multi-source data dynamic coupling and self-adaptive demarcation algorithm, the dangerous area range is dynamically adjusted, and the accuracy and timeliness of mountain torrent disaster risk prevention and control are remarkably improved.

The invention provides a training method and application of a mountain torrent dangerous position prediction model. The training method comprises the following steps: acquiring digital elevation data, geological data, hydrological observation data, historical mountain torrent data and target rainfall intensity of a plurality of sub-basins; for any sub-drainage basin, according to the obtained data, simulating a submerged area and submerged water depth of the sub-drainage basin where the mountain torrent disaster occurs under the target rainfall intensity by using a hydrological hydrodynamic model, classifying the danger of the submerged area according to the submerged water depth, and setting a classification label; forming a plurality of mountain torrent inundation samples according to the inundation areas and the classification labels of the plurality of sub-basins, each mountain torrent inundation sample comprising three-band input data, the inundation area and the classification label of one sub-basin, and the three-band input data comprising digital elevation data, flow accumulation and gradient of the sub-basin; and training the initial mountain torrent dangerous position prediction model adopting the UNet network structure by taking the plurality of mountain torrent flooding samples as training data.

The invention provides an engineering investigation surveying and mapping intelligent management method and system based on a geographic feature processing technology. The method comprises the following steps: acquiring building distribution density, ground gradient and underground rock stratum distribution data of a target area, deploying a ground deformation monitoring radar at a selected position based on the building density and the rock stratum data, generating ground deformation data through radar images, and then separating ground subsidence change and original terrain characteristics to form a subsidence map; meanwhile, image reflection characteristics are analyzed to mark dangerous areas. And then integrating the ground gradient, the settlement trend and the rock stratum structure complexity to construct a land bearing evaluation model. The influence weight is further adjusted in combination with engineering requirements, and a bearing force evaluation result is generated after the model is input. Therefore, a scientific three-dimensional development planning scheme is generated, and optimized utilization and risk management and control of land resources are realized. According to the invention, through multi-source data fusion and model calculation, full-process analysis from land deformation monitoring to load bearing evaluation is realized.

The invention discloses a biomimetic anchor fluke type monitoring robot for a waste dump slope, and relates to the technical field of slope monitoring, the biomimetic anchor fluke type monitoring robot comprises a slope detector, a main body unit is arranged on the bottom surface of the slope detector, and a fixing unit for anchoring equipment at multiple angles is arranged on the bottom surface of the main body unit; the main body unit comprises a solar panel fixedly mounted on the bottom surface of the gradient detector and a base arranged on the bottom surface of the solar panel and playing a connecting role; after the fixed block is pushed to a certain depth, the anchoring telescopic rod drives the movable connecting rod to contract, the movable connecting rod drives the sliding block connected with the movable connecting rod to move, the inclination angle of the movable connecting rod is driven to change along with sliding of the sliding block in the limiting sliding groove, and it is ensured that the anchoring telescopic rod can always control the motion state of the sliding block; after the anchoring telescopic rod is completely contracted, the five soil breaking cones are unfolded from the contracted state and are unfolded in the soil in a lotus shape, and the stability of the equipment is further enhanced.

The invention discloses a ground monitoring method for water and soil loss and carbon loss of a road slope, and belongs to the field of ecological monitoring. The method comprises the following steps: setting an engineering disturbance area and a natural contrast area according to regional water and soil loss, vegetation coverage and altitude gradient, and arranging an erosion pile sample plot to form a contrast observation network; removing impurities on the surface layer of the sample plot, collecting a soil sample, obtaining volume-weight data, and recording environmental parameters such as geographic position, altitude and gradient; the method comprises the following steps: pretreating a soil sample, measuring organic carbon content and volume weight, and obtaining carbon components and physical parameters; the exposed height of the erosion pile is measured regularly, erosion / accumulation modulus is calculated, and a space-time database is established in combination with weather, disturbance events and the like; and based on the erosion / accumulation data and the physical and chemical parameters, constructing a model to quantify carbon loss and carbon sequestration caused by water and soil loss. According to the method, through contrast point distribution, high-frequency observation and multi-parameter analysis, whole-process dynamic monitoring of complex terrain carbon migration is achieved, and the method is suitable for accurate evaluation of water and soil loss induced carbon loss in the field of ecological monitoring.

The invention relates to the technical field of unmanned aerial vehicle remote sensing, in particular to a geological disaster monitoring method and system for unmanned aerial vehicle surveying and mapping, and the method comprises the following steps: extracting a terrain anomaly data set based on monitoring unit point cloud and texture, screening a behavior deviation region according to gradient and texture, and recognizing and matching an anomaly unit in combination with stress and slope direction. And calling a risk table comparison response to preferentially screen a monitoring unit needing to be adjusted according to the evaluation deviation calibration abnormity level, and outputting a geological monitoring intelligent collaborative scheduling instruction set. According to the method, a linkage identification path is constructed by extracting point cloud density sudden change and texture anomaly information in a monitoring unit on a space axis, the capture capability of fine earth surface changes is enhanced, the space identification accuracy of an abnormal area is improved, risk grade judgment is refined according to a terrain stability curve deviation trend, and the reliability of disaster assessment is enhanced. Corresponding calibration of the monitoring unit and the geological function diagram is achieved, the response range adjusting efficiency is improved, and it is ensured that the dispatching instruction has higher pertinence.

The invention discloses a DEM adaptive multi-algorithm fusion lifting method for a high-precision distributed hydrological model, and relates to the field of hydrological model basic data construction. The method comprises the following steps: acquiring original DEM data, land utilization data and soil type data; performing standardization processing on the original DEM data to obtain a unified grid DEM; calculating a basic terrain field based on the unified grid DEM; generating at least one enhanced topographic parameter (such as an enhanced gradient grid or topographic index) through a predetermined optimization pipeline based on the base topographic field; finally, hydrological response units are divided in combination with the at least one enhanced topographic parameter, the land utilization data, and the soil type data. Through the optimization assembly line, the problem that traditional filtering is insufficient in geomorphic feature reservation is solved, and the physical rationality of hydrological response unit division is improved.

The invention discloses a slope soil erosion prediction method, system, equipment and medium, and relates to the technical field of soil erosion, and the method comprises the following steps: taking slope soil with different grain composition as a research object, and carrying out a rainfall simulation experiment; constructing a production and construction project soil erosion prediction model according to the product of a subrainfall erosivity factor, a soil erodibility factor, a slope length factor, a slope factor and a slope surface area on the basis of the grain composition characteristic particle size; and predicting the soil erosion of the slope surface of the to-be-predicted production and construction project through the production and construction project soil erosion prediction model. According to the model disclosed by the invention, a direct quantitative relationship between the characteristic particle size and the erosion strength is established, so that an acquisition way of the soil erodibility factor is simplified, the dependence of the model on complex and expensive soil physical and chemical parameter analysis is greatly reduced, and the operability and the popularization efficiency of the model in a production field are greatly enhanced.

The invention relates to the technical field of ecological restoration of a coal mine in an arid region, and discloses an ecological restoration method for a waste dump of the coal mine in the arid region. According to the method, a multi-parameter environment sensing model containing soil humidity, soil components, surface temperature, vegetation indexes and regional gradient data is established, and whether ecological restoration is started or not is judged according to the model. And selecting at least one of water, a nutrient solution or a soil conditioner as a restoration medium, and quantitatively conveying the restoration medium to a predetermined area through an independent conveying path isolated from natural rainfall. The recovery area is composed of an independently-arranged conveying pipe network, the water flow direction is dynamically judged according to the gradient of the area, and natural diffusion advantage position pipe section conveying is preferentially started. During conveying, the operation time period is determined according to the medium absorption rate, intermittent conveying is executed on the selected pipe section, and the average flow in each cycle is controlled not to exceed the system reserve capacity. And when the reserve is insufficient, conveying is suspended, operation information is recorded, remaining operation continues to be completed after the reserve is recovered, and closed-loop recovery control is achieved.

The invention discloses a slope monitoring method and system based on an unmanned aerial vehicle, and relates to the technical field of intelligent geological disaster monitoring, and the method comprises the steps: carrying a magnetic gradient measurement unit and a laser radar through the unmanned aerial vehicle, and collecting magnetic gradient tensor collection and slope surface point cloud from multiple heights and multiple routes; on the basis of a gradient adaptive weighted total variation inversion method, slope gradient information extracted by a digital elevation model is introduced into regularization weight adjustment, so that an inversion result can be adaptively adjusted in different gradient areas; based on a magnetic susceptibility distribution model, a magnetic construction adaptive clustering and risk index calculation method is used, and through amplitude density index and gradient constraint search, clustering identification and risk quantitative partitioning of a high-gradient accumulation area are carried out. Therefore, expansion from surface slope deformation monitoring to deep concealed structure detection is realized, and concealed slip zones or fissure zones can be accurately revealed under complex terrain conditions.

A system and a method for defining and maintaining slope and cross-slope parameters during construction vehicle operations are provided. Data associated with an attachment positioned at reference points on the terrain and the corresponding location and elevation information from a location sensor are obtained. Based on this data, the processing unit calculates slope and cross-slope parameters by analyzing the differences in elevation and the horizontal distances between the reference points. As a result, guidance information is generated for real-time operator feedback or for the automatic adjustment of the attachment. The system includes a location sensor (e.g., GNSS) and optical sensors (e.g., LiDAR) for calculating the slope and cross-slope values, and for controlling operation of the attachment to ensure that the grading or earthmoving matches defined specifications.

The invention discloses a debris flow prediction method based on multi-source remote sensing, and the method comprises the following steps: 1, data acquisition and preprocessing: obtaining target region data through satellite remote sensing, and eliminating terrain shadow interference; step 2, feature extraction: extracting vegetation coverage and surface temperature from the optical image, extracting deformation magnitude and time sequence from InSAR data, and extracting gradient, slope direction, curvature and terrain humidity index from DEM terrain data; 3, performing multi-dimensional feature fusion, and constructing a multi-dimensional feature vector; 4, model construction: establishing a debris flow susceptible area identification model, and fusing the vegetation-terrain coupling characteristics of the optical image, the deformation dynamic characteristics of the InSAR and the terrain stability characteristics of the terrain data; 5, carrying out susceptibility partitioning and early warning, dividing risk grades based on probability values output by the model, and triggering graded early warning responses; according to the method, the multi-dimensional feature space is constructed through the collaborative interaction of the multi-source remote sensing data and the fused data.

The invention discloses a three-dimensional runoff water level prediction method based on DEM processing, PINN and reinforcement learning. The method comprises the following steps: firstly, extracting space and time characteristics including elevation, gradient, curvature, flow accumulation and river channel width from DEM data, and generating a self-adaptive computational grid; the PINN pre-trains a Navier-Stokes equation, then utilizes reinforcement learning optimized by a near-end strategy to optimize a roughness coefficient and a flow rate, and performs model refining through the optimized PINN to accurately predict a flow rate (u, v, w) and a water level. Generating a series of'total flow-flow velocity-water level 'data by using a trained PINN model, and constructing a prediction model of the three by using a deep learning method; and finally, when external input flow is received, acquiring water flow speeds corresponding to different moments by calling a PINN model, quickly acquiring corresponding water depths by using the fitted'total flow-flow speed-water level 'prediction model, and acquiring the water flow speeds and positions at different moments.

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 belongs to the technical field of municipal pipeline detection, and provides a municipal pipeline detection method and system based on nondestructive detection and artificial intelligence, and the method comprises the steps: carrying out the AI reconstruction through the pipe diameter point cloud data of different pipe sections, generating a continuous profile map, and recognizing the pipe sections with reduced pipe diameters; generating a slope curve by using the slope detection data to identify a slope change pipe section; calculating the overlapping mileage proportion of the pipe diameter reduction pipe section and the gradient change pipe section, performing linear fitting on the gradient curve of the overlapping pipe section, and judging the pipe diameter misjudgment risk pipe section according to the decision coefficient; determining a coupling relationship between gradient change and pipe diameter reduction based on historical data of pipe sections of the same type, establishing a coupling model, and judging whether the actual pipe diameter reduction amount and the theoretical pipe diameter reduction amount of the pipe section with the pipe diameter misjudgment risk conform to the coupling relationship or not; if not, the diameter of the oblique section is converted into the real inner diameter according to the gradient inclination angle by combining the RANSAC algorithm, the real inner diameter is compared with the designed inner diameter again to determine whether the pipe diameter is reduced or not, and it is ensured that the pipe diameter detection result is accurate.

This invention provides an indoor testing device and method for the surface impermeability and erosion resistance of ecological slope protection. It includes a slope simulation device with a rainfall simulation device mounted above it. The slope simulation device comprises an inclined soil-rock bearing device and a slope soil-rock layer, on which a vegetation layer is arranged. The slope simulation device is supported by a slope adjustment device. The erosion material collection device includes a mud-water collection tank, a collection trough, and a collection container. The mud-water collection tank collects surface runoff and erosion material from the vegetation layer; the collection trough collects seepage water between the vegetation layer and the slope soil-rock layer; and the collection container collects mud-water that has infiltrated below the slope soil-rock layer. This invention considers the runoff at the interface between the substrate and the slope, comprehensively analyzes the infiltration patterns of rainfall on the slope, and provides data and basis for numerical simulation and analysis processes. It provides a more accurate quantitative evaluation of the impermeability and erosion resistance of vegetation, and is more rigorous than existing testing methods.

The utility model provides a slope protection pile foundation pit supporting structure which comprises a first step supporting structure and a second step supporting structure, the slope protection piles are arranged on deep foundation pit slope protection piles, the gradient of an upper slope of a deep foundation pit is 1: 4, and double rows of supporting piles are arranged at the deep foundation pit and are arranged in a step shape. The first step supporting structure is connected with the upper portion of the deep foundation pit through a second top beam, the bottom of the second top beam is connected with a supporting pile, and the supporting pile is connected with the second step supporting structure through a slope bottom ground beam, a row pile connecting beam and the first top beam in sequence. Concrete waist beams, anchor cables and drainage holes are arranged on the side surfaces of the support piles in the first step support structure and the second step support structure; a hanging net is arranged on the surface, connected with the supporting piles, from the top beam of the first step supporting structure to the slope bottom ground beam, a hanging net is arranged on the surface, connected with the supporting piles, from the first top beam of the second step supporting structure to the foundation pit base, and concrete is sprayed to the hanging nets. The slope protection pile foundation pit supporting structure is high in erosion resistance, and the gradient and displacement of a foundation pit can be effectively controlled.

The invention belongs to the technical field of landslide identification and prediction, and particularly relates to a landslide distribution probability prediction method and system based on remote sensing data, and the prediction method comprises the following steps: step 1 to step 6, selecting a research area, capturing remote sensing data, describing a curved surface form of the research area, and constructing a digital elevation model; after screening, introducing elevation data into MATLAB software, and drawing a three-dimensional topographic map in a three-dimensional coordinate system; constructing a landslide probability model, simulating variables in the landslide, deducing seismic data, and deducing slope data; constructing a WGEN model, and deducing a precipitation density function of the research area based on GAMMA distribution to realize precipitation simulation; the prediction system comprises a web crawler module, a local database, a processor and a touch screen. According to the method, the elevation and rainfall of the plateau area are associated, multiple models are constructed, the landslide distribution probability accuracy is high, and risk early warning can be carried out within 3 hours after an earthquake.

The invention provides a protection method, device and equipment for power grid facilities under natural disasters and a medium. The method comprises the following steps: firstly, acquiring an initial data set, wherein the initial data set comprises a rainfall data set, a normalized vegetation index, land utilization data, road network data, soil type data, river network density data, elevation data, slope data, rock data and a surface deformation rate; and then, based on the initial data set, simulating a position point of a landslide barrier dam generated in a river after landslide is generated by rainfall, and geometric parameters of the landslide barrier dam. A first evolution law of outburst flood generated by the landslide barrier dam after outburst is then simulated based on the location points and the geometric parameters. And finally, based on the first evolution rule of the outburst flood, determining emergency protection measures of power grid facilities at the downstream of the landslide barrier dam. The protection accuracy of power grid facilities under natural disasters in the prior art is improved.

The invention discloses a quantitative calculation method of a soil erosion modulus background value, which comprises the following steps: S1, grading a rainfall erosion force factor and a soil erodibility factor in soil erosion factors according to unsupervised classification, and generating a contour map, S2, carrying out drainage basin analysis through DEM, calculating a slope length factor and a slope factor mean value according to a small drainage basin boundary, and calculating the background value of the soil erosion modulus according to the slope length factor and the slope factor mean value. S3, vegetation coverage and biological measure factors are measured and calculated according to a table look-up method and a linear interpolation method according to field investigation, and S4, water and soil conservation engineering measure factors and cultivation measure factors are measured and calculated according to land utilization, vegetation coverage and water and soil conservation measures of the field investigation and an assignment method. Corresponding soil erosion factor values can be rapidly matched according to areas where projects are located, adaptability is wide, and soil erosion modulus background values can be measured and calculated at any time according to conditions such as different areas and project types.

The invention discloses a foundation pit slope reinforcing method which comprises the following steps: inserting a plurality of grouting floral tubes on a ramp at intervals, and grouting to stabilize a ramp soil body; vertically driving a first row of timber piles at the position, relatively close to a slope toe, of the bottom of the ramp in the length direction of the ramp; grouting holes are formed in the road surface at the top of the ramp at intervals in the length direction of the ramp, compaction grouting is conducted, and the compactness of a soil body at the top of the ramp is improved; the surface soil of the ramp is removed, and the gradient of the ramp is slowed down; vertically driving a second row of timber piles in the middle of the ramp along the length direction of the ramp; concrete is poured on the ground at the bottom of the ramp in the length direction of the ramp, so that the concrete abuts against the toe of the ramp, and the slope reinforcing effect is improved through the reinforcing method.