1193 results about "Slope gradient" patented technology

The present invention discloses a method for dynamically assessing slope safety, and the method comprises the following steps: S1, carrying out geologic model generalization to the slope according to slope type, surface elevation, slope structure, stratum characteristics and a deformation failure mode to obtain a slope geologic model, creating a slope geometric model according to the said slope geologic model, carrying out the subdivision of computational grid, and selecting a reasonable numerical simulation method, mechanical constitutive and initial boundary value conditions to form a computational model; and S2, adjusting stratum parameters, structural plane parameters and activating factor strength based on the said computational model, carrying out a large amount of numerical simulation, summarizing results of the said numerical simulation, normalizing input quantities and output quantities to establish machine learning samples.

The invention provides a drainage basin digital twinning construction method and system based on multi-source data fusion. The method is applied to the technical field of drainage basin digital twinning construction, and comprises the following steps: acquiring water level monitoring data, surface flood routing path data, weather forecast rainfall data and terrain slope change data; rainfall and topographic slope data are fused to generate a runoff distribution relation, and a high-risk area is identified in combination with a water level sudden change amplitude. A digital twinning preliminary framework is established, and related characteristic parameters are generated by utilizing reverse feedback of a flood path and water level data. And inputting meteorological data, constructing a twinborn model based on the boundary condition of the catchment area, and simulating flood direction abnormity and flooding early warning signals. And according to the early warning space-time distribution and the terrain elevation data, generating emergency schemes such as flood dividing gate scheduling and flood storage and detention area starting, and realizing risk hierarchical management and control. According to the technical scheme provided by the invention, the flood inundation prediction precision and the emergency response efficiency are improved, and precise decision support is provided for flood control of a drainage basin.

The invention provides a water and soil loss dynamic monitoring method and system based on a remote sensing image, and the method comprises the steps: firstly obtaining a multi-temporal remote sensing image data set of a target region, which comprises a plurality of time period remote sensing image subsets and land surface coverage information, and then carrying out the land surface feature extraction of the multi-temporal remote sensing image data set, after vegetation coverage, terrain gradient and soil exposure features are obtained, a water and soil loss prediction model based on time-space correlation is constructed, the features are input for prediction, a water and soil loss grade distribution map is generated, a target loss risk area is identified according to the water and soil loss grade distribution map, and a treatment priority sequence and a vegetation recovery strategy are generated. And finally, the information is fed back to a monitoring platform to trigger regional governance task allocation operation, so that dynamic monitoring of water and soil loss is realized, and governance tasks are effectively planned.

The invention discloses a reservoir bank slope geological disaster risk identification method based on an unmanned aerial vehicle laser radar, and relates to the technical field of reservoir bank slope prevention and control, an unmanned aerial vehicle is used for carrying laser radar equipment, flight scanning is carried out on a reservoir bank slope area, and three-dimensional point cloud data is obtained. According to the reservoir bank slope identification method based on the unmanned aerial vehicle laser radar detection data, high-precision terrain and geological information of the reservoir bank slope is rapidly acquired in a non-contact manner by using the three-dimensional imaging capability of the unmanned aerial vehicle laser radar technology, so that the data acquisition efficiency and safety are greatly improved; the method also remarkably improves the precision and integrity of data, accurately captures key topographic factors such as topographic relief, gradient, slope direction and the like through laser radar scanning, and provides a solid foundation for the accurate recognition of bank slope types in combination with geological factors such as geological structures, lithology and the like, so that the prediction and evaluation of bank slope disasters are more accurate. Preventive measures can be taken in advance, and disaster risks are reduced.

The invention discloses a landslide monitoring method based on remote sensing data, and the method comprises the steps: obtaining a high-resolution optical remote sensing image and a synthetic aperture radar image of a research region, carrying out the registration processing of the optical and radar remote sensing images, and obtaining a remote sensing image with an accurate spatial position and an accurate geometric shape; generating a landslide area fusion image with high spectral resolution; the matched high-resolution DEM data is obtained; based on the matched high-resolution DEM data, gradient parameters of the research area are calculated, and a gradient threshold value is determined according to gradient distribution characteristics and prior knowledge; extracting slope direction parameters of the research area by adopting a slope direction algorithm based on grids and vectors, and screening out a landslide-prone area in combination with the slope threshold value; obtaining a landslide risk distribution map; and obtaining the occurrence possibility and danger level of the landslide, and obtaining the landslide condition according to the occurrence possibility and danger level of the landslide. According to the invention, precise identification and dynamic monitoring of landslide disasters are realized.

The present disclosure relates to the technical field of landslide hazard model tests, and in particular to a landslide model test method and device for realizing multi-variable synchronous monitoring. In the test device, a soil slope simulation unit is configured to pile up a soil slope and simulate different inclinations of the slope. A rainfall simulation unit is configured to simulate rainfall of different intensities and induce a landslide. A runoff-seepage separation unit is configured to realize separation of runoff from seepage of the slope under the effect of rainfall. A monitoring module is configured to monitor runoff and seepage flow rates of the slope, changes in water content and pore water pressure within the slope, and a morphological change of the slope under the effect of rainfall, to obtain a mechanism of rainfall-induced landslide deformation and damage based on changes in the flow rate.

The invention provides a multi-modal fusion sensing robot dog inspection slope disaster risk assessment method and device and a storage medium, and relates to the field of slope disaster assessment, and the method comprises the steps: obtaining multi-modal sensing data; performing space-time alignment processing on the multi-modal sensing data and then converting the multi-modal sensing data into a voxel coordinate system; performing feature extraction on the multi-modal sensing data after time-space alignment, and mapping each extracted feature to a unified voxel unit to form a three-dimensional voxel structure containing each extracted feature; constructing a three-dimensional multi-modal data fusion model; identifying disaster types based on the three-dimensional multi-modal data fusion model, wherein the disaster types comprise the ground surface crack length, the underground cavity volume, the water seepage point number, the local collapse and bulging area, the vegetation degradation area and the slope gradient; and calculating a risk index based on the identified disaster type in combination with the association degree of the disaster type. By adopting the evaluation method provided by the invention, rapid and efficient evaluation of slope disasters can be realized, and the method has relatively good accuracy.

The invention relates to the technical field of side slope deformation prediction, and discloses a side slope three-dimensional deformation prediction method, which comprises the following steps of: 1, carrying out InSAR three-dimensional time sequence deformation inversion to generate three-dimensional time sequence deformation of a side slope high-coherence point; 2, decomposing the three-dimensional time sequence deformation by using a grey wolf optimization algorithm and a variational mode decomposition model to obtain a trend term, a periodic term and a residual error; 3, establishing a deep learning network prediction model considering the environmental impact factors of the region where the slope is located; and step 4, generating a slope time sequence deformation prediction value. The method comprises the following steps: resolving a three-dimensional deformation sequence by using a synthetic aperture radar time sequence image; constructing a variational mode signal decomposition model based on a grey wolf optimization algorithm; and establishing a deep learning network prediction model considering the environmental impact factors. By means of the method, the difficult problem of the hydropower station dam area slope three-dimensional real-time deformation prediction technology can be solved, environmental physical factors such as the reservoir water level, the gradient and the direction are fully considered, and rapid, real-time and accurate three-dimensional deformation prediction of the slope can be achieved.

The invention relates to the technical field of risk analysis, in particular to a safety engineering comprehensive management system which comprises a geological parameter dynamic monitoring module, a risk threshold early warning module, a stability weight evaluation module and a risk comprehensive management and control module. According to the method, lithology data are extracted through a drilling profile to calculate the layer thickness sudden change rate and the strength attenuation rate, a lithology abnormal area is positioned through a variable coefficient method, lithology sudden change marks are analyzed through spatial clustering, a dynamic trend is captured through sliding window mean value comparison, and gradient amplitude and slope direction dispersion are calculated through a digital elevation model. Fusing the abnormal point density to generate a terrain instability index; establishing a multi-dimensional quantitative evaluation framework; carrying out fuzzy comprehensive evaluation and cross validation on the instability index and an engineering parameter trend; generating a dynamic priority sequence, carrying out stake number interval matching to construct a risk measure table, carrying out analytic hierarchy process dynamic resource allocation support drainage scheme, and carrying out real-time monitoring and prediction closed-loop iteration. And adaptively adjusting the control strategy.

A slope safety and stability analysis method based on an integrated sensor and an intelligent algorithm comprises the following steps: acquiring initial values of geometric parameters (including height, gradient and width) of a slope and basic physical parameters (weight, internal friction angle and cohesive force) of a soil body through a method of combining in-situ static sounding and an indoor test; an improved integrated sensor slope state monitoring device is adopted to continuously obtain state parameters such as water content, matrix suction, internal three-way displacement, an inclination angle and soil pressure of a slope soil body, and multi-dimensional dynamic monitoring is achieved; basic physical parameters of a soil body are updated in real time based on data collected by a sensor, and the slope stability safety coefficient is predicted through a semi-supervised learning model; safety early warning is triggered in a grading mode according to prediction results, model prediction values and measured values are recorded and analyzed, and the system evaluates the long-term stability and applicability of the model; through multi-source data fusion and intelligent analysis, theoretical support and technical guarantee are provided for safety monitoring and early warning of the loess slope.

The invention discloses a method for predicting the risk of a valley-type tailing pond being threatened by extra-small watershed flood, and the method comprises the steps: S1, obtaining the soil type, vegetation coverage and gradient of the extra-small watershed of the valley-type tailing pond, and the spatial distribution data of a valley, and building an underlying surface classification system; s2, non-linear key inducements in the rainfall-runoff process in the valley terrain extra-small watershed are extracted, dominant factors influencing runoff formation are recognized, and a non-linear confluence calculation numerical model is constructed; s3, constructing a distributed sensing monitoring network through a rainfall monitoring station and a runoff monitoring station; s4, constructing a layered three-dimensional hydrological hydrodynamic model of coupling rainfall runoff generation-slope confluence-shallow groundwater flow; and S5, establishing a risk assessment index system and a risk prediction model through a layered three-dimensional hydrological hydrodynamic model in combination with flood risk influence factors. According to the method, accurate prediction of the valley-type tailings pond under the flood threat in the extra-small watershed is realized, and the problem of poor predictability of the flood threat in the extra-small watershed is solved.

The utility model relates to the technical field of model tests, and discloses a landslide damage simulation test device which comprises a model test box, a rainfall frame, a hydraulic assembly, a plurality of spraying assemblies, a water tank assembly and a constant temperature system. The angle of the landslide model box can be adjusted through the hydraulic machine so as to change the slope of a model test landslide soil body; the multiple spraying assemblies are arranged at the top of the rainfall frame and located over the model test box, the output ends of the spraying assemblies aim at a test soil body in the model test box, the influence of rainfall on landslide slippage is simulated by adjusting the spraying size, and the constant temperature system is arranged at the top of the model test box and used for regulating and controlling the temperature of the test soil body. The constant temperature system is used for measuring the influence of the dry-wet cycle effect on the landslide soil body.

The invention belongs to the technical field of robot testing, and discloses a mobile robot slope dynamic and static stability test system and method, and the system comprises a ramp test device which is used for providing a horizontal slope and a slope surface which is connected with the horizontal slope and can adjust different slope values; the motion capture system is used for monitoring the motion state of the mobile robot on the ramp test device in real time; and the control system is electrically connected with the ramp test device and the motion capture system, and is used for controlling the slope value of the ramp test device in real time, receiving the detection result of the motion capture system, and judging whether to adjust and control the next slope value according to the detection result. According to the invention, the climbing and slope holding capabilities and the stability of the mobile robot can be tested.

The invention relates to the technical field of computer simulation, in particular to an earth surface two-dimensional calculation method based on a cellular automaton, which comprises the following steps of: analyzing topographic data of a plurality of areas based on topographic data acquisition records, recording elevation and gradient, processing the topographic data by using the cellular automaton, constructing a topographic model, and calculating the topographic model by using the cellular automaton. And obtaining regional terrain information. According to the method, through terrain data acquisition and terrain model construction, the basic data quality of the model is improved, accurate input data is provided for simulation, a key position is identified, the size and distribution of cells are adjusted, the simulation resolution of a key area is optimized, the local precision of simulation is improved, and the consumption of computing resources is reduced; the rainfall simulation parameters are adjusted according to the actual meteorological data, the prediction reliability is enhanced, the erosion effect and anti-erosion ability of various areas are evaluated by simulating soil erosion and surface runoff, and the prediction accuracy and practicability of surface two-dimensional calculation are improved.

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 side slope stability intelligent monitoring and supporting optimization method based on digital twinning, which comprises the following steps: extracting gradient, curvature and geological layering characteristics from a holographic terrain model, calculating a preliminary change trend of stress distribution of a rock-soil body in combination with a finite element analysis method, and determining spatial position distribution of a potential sliding surface of a side slope; according to the space coordinate set of the real-time monitoring point position, the data acquisition frequency of the sensor is adjusted through a time sequence analysis method, and a high-frequency monitoring data set reflecting dynamic changes of stress and underground water is obtained; extracting stress peak values and underground water level fluctuation characteristics from the high-frequency monitoring data set, and generating a multi-dimensional information matrix containing terrain, stress and water dynamics by combining spatial characteristics of the holographic terrain model and adopting a data fusion algorithm; according to the state parameters of the digital twinborn body, if it is judged that the stress distribution exceeds a preset threshold value, the stress distribution of the supporting structure is recalculated through finite element analysis, and an adjusted slope supporting design scheme is obtained.

The invention provides an intelligent early warning method and system for phosphorus tailing improved soil heavy metal migration, relates to the technical field of computers, and accurately predicts the main migration direction of heavy metal pollutants by combining factors such as terrain gradient, hydrological flow direction and soil structure heterogeneity. The method comprises the following steps: acquiring soil information of a to-be-detected area and soil potential information of a detection point in the to-be-detected area; determining heavy metal concentration information of the detection point according to the soil potential information; the heavy metal concentration information is used for reflecting heavy metal concentration distribution conditions corresponding to different soil depths of the detection points; determining migration direction information of the heavy metal at the detection point; the migration direction information is used for reflecting the corresponding heavy metal migration direction distribution condition of the heavy metal of the detection point in the three-dimensional space; and predicting a pollution diffusion area based on the migration direction information, the organic decomposition rate and the underground water level fluctuation information, and performing visual display.

The invention relates to the technical field of geological disaster detection, in particular to a geological disaster hidden danger point detection method and system. Comprising the following steps: S1, synchronously acquiring vegetation canopy penetration data, multispectral soil humidity spatial distribution data and lithology distribution data by adopting an unmanned aerial vehicle carried image data acquisition device and a multi-band laser radar, and generating an orthoimage and a three-dimensional point cloud data set; s2, fusing the orthoimage and the three-dimensional point cloud data through an aerial triangulation encryption algorithm to establish a three-dimensional model, loading the multispectral soil humidity spatial distribution data into the three-dimensional model to generate a dynamic digital elevation model, and generating a contour line topological structure through a TIN triangulation network algorithm; s3, extracting a slope factor, topographic relief, vegetation coverage, fracture distance and a lithologic factor based on the three-dimensional model to construct a geological disaster hidden danger system; according to the system, the geological disaster occurrence time can be estimated, and the rescue and protection treatment period can be effectively planned based on the geological disaster occurrence time.

The invention relates to the technical field of earthquakes, in particular to an optical remote sensing image feature landslide information extraction method. A double-time-phase NDVI time sequence analysis strategy is adopted, and landslide area recognition is achieved by constructing a vegetation index difference chart before and after an earthquake. A landslide mass area before an earthquake presents a high NDVI value due to complete vegetation coverage, and a vegetation index of the area in an image after a disaster is significantly attenuated due to surface disturbance, so that an obvious change response is formed. If the normalized vegetation index does not change, a non-landslide area can be determined, and the greater the change of the normalized vegetation index is, the greater the possibility of landslide occurrence is, and a landslide preselection area is determined; then Otsu threshold segmentation is carried out by combining cloud layer features and water body features, cloud layer and water body change parts are effectively eliminated, object-oriented geometric shape rule fine recognition is carried out on a preselected area, a DEM is adopted to calculate a slope value to constrain low-lying or flat earth surface changes, and efficient and accurate landslide information extraction is achieved.

The invention discloses a surface mine high and steep slope deformation monitoring method integrating gradient and slope direction factors, and relates to surface mine high and steep slope deformation monitoring. The method comprises the following steps: obtaining a one-dimensional deformation result of a radar sight line direction under lifting rail geometry; calculating the gradient and the slope direction value of the monitoring area; constructing a relation model of a radar sight line direction deformation result and a two-dimensional deformation result; and acquiring a deformation value of the monitoring area along the slope direction and a deformation value of the monitoring area vertical to the slope direction axis so as to monitor the deformation of the high and steep slope of the surface mine. According to the method, by calculating the deformation value of the monitored area in the slope direction and the deformation value of the monitored area perpendicular to the slope direction axis, more accurate real slope deformation can be obtained, the deformation conditions of the slope at different positions can be visually known, the slope degree of the slope can be quantified, and the slope direction can assist in judging the influence degree of natural conditions on the slope.

A method, system, medium and program product for measuring a volume based on elevation measurement, the method comprising: determining historical topographic feature data; elevation values of all positions in the mining area in different time periods are extracted; calculating a topographic relief change rule according to the elevation value, and establishing a topographic evolution model according to the topographic relief change rule; extracting terrain boundary feature points and ponding area contour lines from the unmanned aerial vehicle inclined image data; dividing a plurality of local terrain units according to the terrain boundary feature points, and calculating an elevation difference to obtain a gradient change coefficient; determining a terrain prediction model of each local terrain unit; splicing and reconstructing the terrain prediction model of each local terrain unit to obtain underwater terrain estimation data of the ponding area; constructing a mining area terrain model according to the underwater terrain estimation data and the terrain data; and calculating the earthwork excavation volume in the mining area according to the mining area terrain model. According to the invention, the accuracy of mining volume measurement is improved.

The invention belongs to the technical field of bridge safety evaluation, and particularly discloses a method and a system for evaluating local scouring of a bridge pile foundation based on a flow velocity strain rate. A calculation model of a local scouring pit form and a maximum scouring depth of a river-sea crossing bridge pile foundation is established, and a Reynolds stress tensor is converted into a flow velocity strain rate scalar; the method comprises the following steps: providing an erosion-deposition model, analyzing an erosion-deposition rate, establishing a scouring depth relationship, utilizing a sediment transportation model of grid unit storage parameters, simulating dynamic response of a water-sediment mixture, and triggering sediment sliding and updating a riverbed terrain when the dip angle of a scouring pit is at a supercritical slope by virtue of a slump model. All the models cooperate to achieve efficient simulation of local scouring of the pile foundation. According to the method, the form evolution and the maximum scouring depth of the local scouring pit of the single pile and the pile group can be efficiently and accurately calculated, and support is provided for bridge pile foundation design and anti-scouring structure optimization.

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 belongs to the technical field of mineral exploration, and particularly discloses a copper ore prospecting method based on three-dimensional geological modeling. The method comprises the following steps: acquiring geological data of a target area; after extreme values in the geological data are recognized and removed through a box plot, the geological data are mapped to an interval of [0, 1], and the geological data are divided into terrain data, stratum data and mineral resource data; adopting Kalman filtering to enable the data to form fusion data, and generating a thematic map comprising a geological map, a mineralization anomaly map and a topographic slope map; based on the data and the thematic map, constructing a three-dimensional geologic model by a finite element method, and performing mining path planning by adopting a specific path planning algorithm formula; exploring by the mining equipment according to the planned path, acquiring geological data, comparing the geological data with the predicted data, re-planning the path and continuing exploring if the path is blocked, the resource recovery is out of tolerance and new mineralization is abnormal, otherwise continuing exploring according to the planned path. The method has the advantages of being high in exploration efficiency and data precision, low in comprehensive cost and high in adaptability.

The invention relates to a spray-seeding process for quickly repairing vegetation in a slope area of a power transmission and transformation project, which comprises the following steps of: cleaning a slope of the power transmission and transformation project, and removing pumice stones, sundries and a loose soil layer on the slope surface; selecting a seed formula with a certain proportion for planting preparation; a matrix layer material and a seed layer biological matrix material are adopted as soil matrixes; adding a proper amount of organic fertilizer and long-acting slow-release compound fertilizer, and adding a proper amount of growth regulator; a spray-seeding device is adopted to evenly stir spray-seeding materials and then spray the spray-seeding materials to the slope surface, a certain distance and a certain angle are kept between a spray gun and the slope surface, and different spray-seeding modes are adopted for side slopes with different gradients; covering in time after spray-seeding is completed so as to maintain soil humidity and temperature and prevent seeds from being washed by rainwater and exposed to the sun; the spray-seeding technology is easy to operate, short in construction period, low in cost and suitable for large-scale popularization and application to rapid restoration of vegetation in the slope area of the power transmission and transformation project.

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 an MT-InSAR deformation monitoring method in combination with reservoir bank landslide deformation spatial-temporal characteristics. The method comprises the following steps: S1, selecting SAR data; step S2, constructing small baseline set InSAR data, including SAR image registration, interferogram combination, differential interference processing, phase filtering, coherence estimation and interferogram optimization combination; s3, based on the dual-polarized SAR intensity image, performing earth surface classification in combination with random forest classification, gradient and direction constraint and a deep neural network; then adaptive homogeneous filtering is carried out on the interferometric phase based on a secondary classification result; s4, combining a plurality of Sigmoid functions and a linear creep and periodic function to obtain an adaptive deformation model of the reservoir bank landslide; s5, performing deformation parameter nonlinear search by using a genetic algorithm to determine an optimal parameter set; on the basis of low-frequency deformation, atmospheric delay and decoherence noise are separated through low-pass filtering of a space domain and high-pass filtering of a time domain, and finally a deformation time sequence and an average deformation rate are recovered.

The present invention relates to the technical field of ecological suitability evaluation of agricultural land, and disclosed is a method for evaluating the ecological suitability of agricultural land. The present invention comprises: determining values of indicators of agricultural land, wherein the values of the indicators of the agricultural land comprise slope, elevation, slope length, profile curvature, soil thickness, plan curvature, the minimum number of days of continuous flooding, the maximum number of days of continuous flooding, the cumulative number of days of flooding, the average number of days of continuous flooding, minimum flooding depth, maximum flooding depth, cumulative flooding depth, and average flooding depth. In the present invention, the natural ecology of agricultural land, i.e., whether regional water, soil and climate conditions meet the ecological requirements of the agricultural land, is evaluated, so that it is ensured that the agricultural land can guarantee the sustainability of an ecosystem and environment; the ecological status thereof can be quickly and accurately identified, weights of indicators in an element layer can be determined, and finally, a system for evaluating the ecological suitability of agricultural land is constructed; the method can reflect the ecological suitability of agricultural land in a timely, macroscopic, and dynamic manner.

The invention discloses an RCBAM model construction method for remote sensing inversion of river flow. The method comprises the following steps: 1) collecting remote sensing image data; (2) high-precision DEM production; 3) obtaining a central line of a river channel; 4) river width and gradient acquisition; 5) river section shape extraction; 6) calculating an open-current area; and 7) estimating the river flow. According to the method, the section shape of the river channel is obtained based on a high-precision digital elevation model (DEM), and the section area of the river channel is dynamically calculated by combining instantaneous water surface information obtained by a remote sensing image, so that the problem that defects exist due to the fact that the overflowing area is obtained by depending on an empirical formula in a traditional BAM flow model is effectively solved, and river flow estimation considering the shape characteristics of the river channel is realized. And efficient and accurate river flow remote sensing inversion can be realized.

The invention relates to the technical field of water conservancy projects, in particular to a water conservancy earthwork dynamic monitoring method and system based on multi-source point cloud data fusion, and the method comprises the steps: carrying out the identification and standardization processing of airborne LiDAR, ground scanning and oblique photography point clouds, and generating a standard point cloud data set with uniform spatial positions and balanced density; dividing an abrupt slope area, a gentle slope area and a flat area based on topographic gradients, and constructing a grid framework adaptive to topographic features; carrying out weighted fusion by combining the point cloud coverage rate and the normalized terrain gradient to generate high-precision grid elevation data; calculating an earthwork variation distribution matrix by comparing historical elevation models; dynamically analyzing the change trend of the excavation and filling area, and synchronously evaluating the construction progress deviation and the geological disaster risk. According to the method, the problems of insufficient multi-source point cloud fusion precision, poor terrain adaptability and dynamic evaluation splitting in the prior art can be solved, and the monitoring precision and the engineering safety early warning efficiency under the complex terrain condition are remarkably improved.