A method and system for dynamically monitoring the amount of resources used in an open-pit mine

Abstract

The application discloses a kind of open-pit mine resource quantity dynamic monitoring method and system, it is related to mining monitoring technical field, the method: to time series SAR image data is carried out precision orbit correction and registration, based on the SAR image data after registration, extract initial annual digital elevation model;Compensate to get target annual digital elevation model for incoherence area;Target annual digital elevation model is converted into open-pit image three-dimensional surface model, and based on three-dimensional ore body model and open-pit image three-dimensional surface model, the three-dimensional ore body model of the part of ore body that has been used is determined;Based on three-dimensional ore body model, calculate resource use amount;Using earthwork quota method, calculate the volume of mined entity and as ore body quota earthwork amount;Based on the total volume of ore body quota earthwork amount and three-dimensional ore body model, confirm the reliability of resource use amount, complete the dynamic monitoring of use resource quantity.The application improves the precision and efficiency of open-pit mine resource quantity dynamic monitoring.

Description

Technical Field

[0001] This application relates to the field of mining monitoring technology, and in particular to a method and system for dynamic monitoring of resource utilization in open-pit mines. Background Technology

[0002] Currently, surveys of annual resource consumption in open-pit mines typically rely on high-resolution satellite remote sensing technology in the absence of annual UAV oblique photogrammetry data. However, this method has significant technical limitations: the quality of annual open-pit mine images acquired by high-resolution satellite remote sensing cannot be used for stereo image pair calculations. For example, excessive cloud cover prevents such calculations. This means that when the target area is covered by clouds, optical satellites cannot acquire clear stereo image pairs that can be used to generate 3D models, resulting in missing or invalid annual monitoring data. This makes it difficult to conduct continuous and reliable surveys and assessments of annual resource consumption in mines.

[0003] Therefore, there is an urgent need for a new method that can overcome the influence of weather and achieve stable and rapid investigation of the annual utilization of open-pit mines, in order to solve the problem of the difficulty in real-time investigation of the annual utilization of open-pit mines and provide a fast new method for the statistics and supervision of the annual consumption of national mineral resources. Summary of the Invention

[0004] The purpose of this application is to provide a method and system for dynamic monitoring of resource utilization in open-pit mines, thereby improving the accuracy and efficiency of dynamic monitoring of resource utilization in open-pit mines.

[0005] To achieve the above objectives, this application provides the following solution: Firstly, this application provides a method for dynamically monitoring the amount of resources utilized in an open-pit mine, the method comprising: Acquire time-series SAR image data of the target open-pit mine, and perform precise orbit correction and registration on the time-series SAR image data to obtain registered SAR image data; the registered SAR image data contains at least one pair of registered master and slave images; An initial annual digital elevation model was extracted using interferometric methods based on registered SAR image data. The incoherent regions in the initial annual digital elevation model are identified, and the elevation information of the incoherent regions is compensated using a stereo measurement method based on radar intensity images to obtain the target annual digital elevation model. An interpolation method was used to construct a three-dimensional ore body model of the target open-pit mine based on geological exploration data; The target annual digital elevation model is converted into a three-dimensional surface model of the open-pit image, and the three-dimensional ore body model of the target open-pit mine is spatially registered and Boolean operated with the three-dimensional surface model of the open-pit image to determine the three-dimensional ore body model of the ore body part that has been used. Based on the three-dimensional ore body model of the already utilized ore body, the resource utilization of the already utilized ore body is calculated. The earthwork quota method is used to calculate the volume of the mined entity of the already utilized ore body within the preset monitoring period, and the mined entity volume is used as the ore body quota earthwork volume. By comparing the earthwork volume of the ore body quota with the total volume of the three-dimensional ore body model of the ore body portion that has been utilized, and confirming the reliability of the resource utilization based on the comparison results, dynamic monitoring of the resource utilization of the target open-pit mine is completed.

[0006] Secondly, this application provides a dynamic monitoring system for the amount of resources utilized in an open-pit mine. This system is used to implement the aforementioned method for dynamic monitoring of resource utilization in an open-pit mine. The dynamic monitoring system includes: The registered SAR image data determination unit is used to acquire time-series SAR image data of the target open-pit mine, and to perform precise orbit correction and registration on the time-series SAR image data to obtain registered SAR image data; the registered SAR image data includes at least one pair of registered master image and slave image. The initial annual digital elevation model determination unit is used to extract the initial annual digital elevation model based on the registered SAR image data using interferometric methods. The target annual digital elevation model determination unit is used to identify the incoherent regions in the initial annual digital elevation model, and to use a stereo measurement method based on radar intensity images to compensate the incoherent regions for elevation information to obtain the target annual digital elevation model. The three-dimensional ore body model determination unit of the target open-pit mine is used to construct a three-dimensional ore body model of the target open-pit mine based on geological exploration data using interpolation methods. The three-dimensional ore body model determination unit for the already utilized ore body is used to convert the target annual digital elevation model into a three-dimensional surface model of the open-pit image, and to perform spatial registration and Boolean operation on the three-dimensional ore body model of the target open-pit mine and the three-dimensional surface model of the open-pit image to determine the three-dimensional ore body model for the already utilized ore body. The resource utilization determination unit for the utilized ore body is used to calculate the resource utilization of the utilized ore body based on the three-dimensional ore body model of the utilized ore body. The orebody quota earthwork volume determination unit is used to calculate the volume of the mined entity of the orebody that has been mobilized within a preset monitoring period using the earthwork quota method, and to use the mined entity volume as the orebody quota earthwork volume. The reliability verification unit is used to compare the earthwork volume of the ore body quota with the total volume of the three-dimensional ore body model of the ore body part that has been used, and to confirm the reliability of the resource utilization based on the comparison results, thereby completing the dynamic monitoring of the resource utilization of the target open-pit mine.

[0007] According to the specific embodiments provided in this application, this application has the following technical effects: This application discloses a method and system for dynamic monitoring of resource utilization in open-pit mines. By precisely registering the three-dimensional surface model of the open-pit mine image generated by InSAR with the three-dimensional ore body model in space, and by using Boolean operations, the utilized ore body portion is automatically and accurately cut out from the overall ore body model, ensuring that the calculation object is a pure ore body, eliminating the error caused by the mixing of ore and waste rock, and improving monitoring accuracy. Furthermore, by using the geometric volume calculated by earthwork quota to cross-validate the model results in real time, the calculation accuracy is locked, making the results verifiable and reliable. In addition, by using time-series SAR image data to achieve all-weather, periodic automated processing, and a real-time verification and feedback mechanism for utilization results, the traditional manual and time-consuming special monitoring is transformed into an efficient and batch-executable routine business process, significantly improving monitoring efficiency. Attached Figure Description

[0008] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0009] Figure 1 This is a schematic diagram of a method for dynamic monitoring of resource utilization in open-pit mines according to an embodiment of this application; Figure 2 This is a schematic diagram of the calibration of ground control points provided in an embodiment of this application; Figure 3 A schematic diagram of the geometric principle of InSAR measurement provided in an embodiment of this application; Figure 4 This is a schematic diagram of the positional relationship provided for an embodiment of this application. Detailed Implementation

[0010] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0011] To make the above-mentioned objectives, features and advantages of this application more apparent and understandable, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0012] In one exemplary embodiment, such as Figure 1 As shown, a method for dynamic monitoring of resource utilization in open-pit mines is provided, comprising the following steps: Wherein: Step S1: Acquire time-series SAR image data of the target open-pit mine, and perform precise orbit correction and registration on the time-series SAR image data to obtain registered SAR image data; the registered SAR image data includes at least one pair of registered master and slave images.

[0013] As an optional implementation, step S1 involves performing precise orbit correction and registration on the time-series SAR image data to obtain registered SAR image data, specifically including: Step S11: Download the precise orbit file that is spatiotemporally matched with the temporal and spatial information of the temporal SAR image data, and associate the precise orbit file with the main image and the secondary image in the temporal SAR image data to form an initial image pair with initial orbit information.

[0014] Specifically, you need to download a precise orbital file (such as GACOS orbital data) that matches the SAR image data in advance, and ensure that its time and sensor type are consistent with the SAR image data. The software will automatically select the matching orbital data, but it must be correctly stored in the designated folder.

[0015] Step S12: Based on the initial image pair, generate an initial interferogram, and select non-deformation areas on the initial interferogram as ground control points to generate corresponding ground control point files; the ground control point files contain the correspondence between the image coordinates and the actual geographic coordinates of each ground control point.

[0016] Specifically, flat areas are selected as control points (GCPs) in the initial interferogram, and these points are acquired using vector tools in remote sensing software. GCPs should avoid deformed areas to ensure the stability of orbit correction. Simultaneously, control points need to be evenly distributed and sufficient in number; typically, dozens to hundreds of points need to be acquired for each processing area to ensure the accuracy of orbit refinement. Figure 2 As shown, ground control points use two methods to control accuracy: calibration points and distance control points.

[0017] Step S13: Use the initial orbital parameter polynomial to perform coarse registration on the secondary images in the initial image pair to obtain the coarsely registered image pair.

[0018] Specifically, through the initial orbital parameter polynomial (e.g., X=a0+a1t+a2t) 2 Coarse registration is performed. Here, a0, a1, and a2 are coefficients, t is the motion time, and X is the compensation distance.

[0019] Step S14: Based on the ground control point file, optimize the orbital parameter model of the secondary image in the coarsely registered image pair to obtain the optimized orbital parameters.

[0020] Specifically, GCP is used to optimize orbital parameters, eliminate the influence of orbital errors on phase, and improve DEM accuracy.

[0021] Step S15: Based on the optimized orbit parameters, the orbit error is corrected on the coarsely registered image pair, and the image pair after error correction is re-flattened to obtain the re-flattened image pair.

[0022] Step S16: Re-register the corresponding master image and slave image in the image pair after deflating to obtain the registered SAR image data.

[0023] Specifically, the master and slave image orbits do not completely overlap, resulting in positional offsets. Therefore, registration is required. Coarse registration of the satellite orbits provides initial offset parameters. Then, a polynomial model is used to calculate the slant range and azimuth offsets. The expression for the polynomial model is as follows: (1) Where c0, c1, c2, b0, b1, and b2 are calculation coefficients, R0 is the distance offset in pixels, and A0 is the azimuth offset in pixels. For row indexes in the image; Use column indices in the image.

[0024] The process of acquiring time-series SAR image data of the target open-pit mine is as follows: obtain two or more SAR image data with short time intervals and small baselines. The master and slave images should be based on the intermediate date. The weather conditions, geological structure, land cover, seismic activity and other factors of the mine under study should be comprehensively considered. Generally, it is necessary to check the quality of SAR image data, try to avoid the rainy season and windy season, choose the autumn and winter seasons with less vegetation, no snow and no wind, and avoid earthquakes (data before and after earthquakes cannot be selected as master and slave images).

[0025] In addition, the band range needs to be considered. L-band (such as ALOS-2, wavelength ~23 cm): strong penetration, suitable for vegetated areas (such as forests and farmland); C-band (such as Sentinel-1, wavelength ~5.6 cm): balances resolution and coherence, widely used in urban areas and bare surfaces; X-band (such as TerraSAR-X, wavelength ~3 cm): high resolution, but easily affected by vegetation. In mountainous areas with large topographic relief, interferometric pairs with relatively long baselines should be selected.

[0026] Step S2: Using interferometry, an initial annual digital elevation model is extracted based on the registered SAR image data.

[0027] As an optional implementation method, step S2 specifically includes: Step S21: The registered master image and slave image are multiplied by complex conjugate as an interference pair to generate the corresponding interference phase map, and the interference phase difference of each pixel in the interference phase map is extracted.

[0028] Specifically, the geometric principles of InSAR measurements are as follows: Figure 3 As shown, where B is the baseline length, θ and α are the radar incident angle and baseline inclination angle, respectively, point P is the ground target, and S1 and S2 are the ground target reflection signals received at both ends of the baseline, it can be expressed as: (2) (3) in, Let S1 be the distance from the ground target P; Let S2 be the distance from the ground target P; The wavelength of the radar wave; i The imaginary unit; and This is a random phase caused by the scattering characteristics of the ground surface.

[0029] After master-slave image registration, according to the existing coherence model, the phase information of signals S1 and S2 can be considered as two parts: the phase determined by the round-trip path between the radar antenna and the ground target P, and the random phase caused by the different scattering characteristics of the scatterers within the resolution cell. (4) (5) in, , The random phase is caused by different scattering from the master and slave image resolution units; generally, they are the same. The interference phase obtained by multiplying the conjugates of S1 and S2 ΔS : (6) Phase difference of any pixel in the interferometric phase diagram for: (7) in, For interference complex signals, For the imaginary part of the interference complex signal; For the real part of the complex interference signal; The ambiguity is an integer.

[0030] Step S22: Calculate the parallel and vertical baselines of the corresponding interferometric pair based on the optimized orbital parameters, and establish a relationship model between the interferometric phase difference, terrain elevation change and flatland effect based on the parallel baseline, vertical baseline and the interferometric phase difference of the corresponding pixels.

[0031] Specifically, such as Figure 3 As shown, by projecting baseline B along the slant range direction and perpendicular to the slant range direction, we can obtain parallel baseline B1 and perpendicular baseline B2, whose geometric relationship is as follows: (8) (9) when hour: (10) Interference phase difference With parallel baseline The relationship is: (11) in, Wave number; Interference phase difference It is the radar incident angle. The function of the incident angle, which varies with the elevation h of the target point and the slant distance. The changes are as follows: (12) in, This refers to the altitude of the satellite platform.

[0032] To establish the relationship between elevation and phase, a reference point P is selected. ref Its slant distance is r 1ref Reference point P ref The path differences between the ground target P and the master and slave images are Δr and Δr, respectively. ref And Δr, the difference between the two is ΔΔr. From point P, respectively, the slope distance r 1ref and r 2ref Draw perpendicular lines in the direction of the angle, and Δr is approximately equal to the angle between the two perpendicular lines at the slope distance r. 1ref intercept on: (13) in, Let P be the displacement component of the ground object P relative to the reference point in the direction perpendicular to the line of sight.

[0033] The corresponding phase difference change is: (14) P2 can be decomposed into (15) in, Let P be the displacement component of the ground object P relative to the reference point in the line-of-sight direction.

[0034] Substituting equation (15) into equation (14) yields the relationship model between the interference phase difference and elevation and the flat terrain effect: (16) in, , , This indicates the topographic phase caused by changes in elevation. Terrain phase sensitivity; This indicates the flat-ground phase caused by changes in slant distance; For flat ground phase sensitivity.

[0035] Step S23: Remove the flat phase from the relation model to untangle the entangled interference phase and obtain the untangled terrain phase.

[0036] Specifically, the flat phase appears as periodically changing fringes on the interferogram, requiring the removal of the flat phase effect.

[0037] Step S24: Using geometric formulas, the unwrapped terrain phase is converted into the elevation value of each pixel to obtain the initial annual digital elevation model.

[0038] Specifically, the elevation h of the ground feature P can ultimately be calculated using the following formula based on geometric relationships: (17) Because the satellite's orbital position is uncertain, it is impossible to obtain the incident angle of each pixel precisely; usually, this is achieved by performing an interferometric phase calculation on h. The partial derivatives are used to establish the conversion relationship between phase and elevation: (18) After integration, the elevation calculation formula (i.e., the initial annual digital elevation model) is obtained as follows: (19) Step S3: Identify the incoherent regions in the initial annual digital elevation model, and use a stereo measurement method based on radar intensity images to compensate for the elevation information of the incoherent regions to obtain the target annual digital elevation model.

[0039] As an optional implementation, step S3 specifically includes: Step S31: Calculate the coherence of the interference pairs that generate the initial annual digital elevation model, and identify regions with coherence below a preset threshold as incoherent regions.

[0040] Specifically, the similarity between master and slave image signals and the quality of interference fringes are measured using coherence.

[0041] Within an estimation window region of m×n pixels, the coherence average is used. To estimate: (20) in, To estimate the row index of pixels within the window; To estimate the column index of the pixels within the window, Main image in pixels ( Complex observations at () To extract images from pixels ( Complex observations at () To extract images from pixels ( The complex conjugate of the complex observation at ().

[0042] The coherent portion of the master-slave image consists of interference signals and noise: (twenty one) (twenty two) in, Complex observations of the main image; ; The true coherent signal component that reflects the scattering characteristics of the Earth's surface; Noise in the main image; The noise in the image is mainly composed of noise caused by decoherence and thermal noise.

[0043] Based on this, the theoretical definition of the true coherence within the window is: (twenty three) in, The theoretical coherence coefficient; The average intensity of noise in the master and slave images.

[0044] Considering the residual phase fringes in the interferogram (mainly caused by terrain undulations), the true coherent signal components exhibit a phase difference between the master and slave images, i.e.: (twenty four) in, Pixels in the main image ( The true coherent signal components; To extract pixels from the image ( The true coherent signal components; f ( ) represents a pixel ( To accurately estimate coherence, the fringe rate of the image needs to be calculated by applying a topographic correction factor to the observations from the image before calculation. Therefore, the corrected coherence The estimation formula is: (25) Step S32: Using a stereo measurement method of radar intensity images, one or more sets of ascending-orbit SAR intensity images and descending-orbit SAR intensity images covering the decoherent region are obtained to form a stereo image pair.

[0045] Specifically, after decoherence, elevation cannot be extracted from the phase. Terrain can be reconstructed using radar intensity images and a stereo measurement method based on these images. This requires extracting the DEM from two pairs of SAR stereo images over a common coverage area. Using a range-Doppler model and measured ground control points as external GCP constraints, ascending and descending DEMs are extracted. Similar to photogrammetry, radar stereo measurement uses the geometric parallax of the same ground feature on SAR images from different viewpoints to calculate its 3D coordinates. Sufficiently overlapping SAR stereo images of the same target must be obtained using sensors from two different stations to generate the DEM through stereo intersection. Steps S33-S34 below implement this stereo calculation process.

[0046] Step S33: Match corresponding points between the stereo image pairs to establish a coordinate transformation relationship model for the corresponding points. The coordinate transformation relationship for ascending / descending SAR intensity images is established as follows: (26) in, These are the offsets in the distance and azimuth directions, respectively, for points of the same name. d 1. d 2. d 3. d 4. d 5 and d 6. e 1. e 2. e 3.e 4. e 5 and e 6 is the polynomial coefficient. l and p These are the pixel coordinates of the image.

[0047] Step S34: Using the range-Doppler model or collinear equations (Equations (27)-(30)), based on the image coordinates of corresponding points in the stereo image pair, the satellite orbit position vector, the velocity vector of the antenna phase center, and the Doppler centroid frequency, the three-dimensional coordinates (X, Y, Z) of the ground points in the decoherent region are calculated by spatial forward intersection.

[0048] Specifically, the coordinates of corresponding points in the image Coordinates of the corresponding ground point P(x,y,z) The relational model is represented as: (27) in, and For the master-slave image satellite orbital position vector of the stereo image pair, and These are the velocity vectors of the antenna phase centers, and These are the Doppler centroid frequencies. The collinearity equation is as follows: (29) (30) in, and The difference between the image coordinates and the principal point coordinates; , and For ground target points coordinates and For the antenna center at Location at any given moment and It is the equivalent focal length; , , , , , , , , For the antenna in Attitude Angle at Moment The coefficients of the direction covariance are used to form a matrix, which is used to transform vectors in the ground coordinate system to the camera (sensor) coordinate system. is a dimensionless scaling factor, representing the spatial distance correction factor between the ground target point and the center of the satellite antenna, used to determine the spatial geometric relationship between the ground target point and the center of the satellite antenna.

[0049] Step S35: Interpolate the calculated three-dimensional coordinates of the ground points to generate a local digital elevation model, and then merge the local digital elevation model with the initial annual digital elevation model to compensate for the elevation information of the incoherent areas in the initial annual digital elevation model, so as to obtain a complete target annual digital elevation model.

[0050] Furthermore, the method also includes: error analysis and accuracy control of elevation data. Specifically, during the SAR interferometry acquisition of the DEM, the influence of Earth's curvature is ignored, and the slant range r1 of the master and slave images and the interferometric phase are... The five parameters—horizontal baseline B1, vertical baseline B2, and satellite platform height H—are independent of each other. The total elevation error at point P is: (31) (32) Elevation error caused by slant distance Error in slope distance measurement Decide: (33) The elevation error caused by the interference phase is related to the vertical baseline, registration error, phase unwrapping error, etc.

[0051] (34) The elevation error caused by the satellite platform's altitude is related to the satellite platform's altitude error: (35) (36) The elevation error caused by the baseline is related to the baseline length and the angle of incidence.

[0052] in, The total elevation error of the ground feature target point P; The elevation error is caused by the satellite platform's altitude error; The elevation error is caused by the interferometric phase measurement error; Elevation error caused by horizontal baseline (parallel baseline) error; The elevation error is caused by the vertical baseline error; This is the error in the slope distance measurement; This is the error in the interferometric phase measurement; This is due to the error in the satellite platform's orbital altitude measurement. This represents the measurement error of the horizontal baseline; This represents the measurement error of the vertical baseline.

[0053] Step S4: Using interpolation methods, a three-dimensional ore body model of the target open-pit mine is constructed based on geological exploration data.

[0054] As an optional implementation, step S4 specifically includes: Step S41: Using a preset algorithm, based on geological exploration data, determine the pinch-out point and boundary of the ore body; the geological exploration data includes at least the grade value, ore body thickness value, and spatial location of each borehole.

[0055] Step S42: Using the ore body boundary as a constraint, a three-dimensional ore body model of the target open-pit mine is constructed based on the known thickness or grade values ​​of the borehole points using a preset spatial interpolation algorithm.

[0056] Specifically, estimating the amount of ore resources to be utilized first requires 3D docking of the ore body with the oblique photogrammetry 3D model. After aerial triangulation modeling, the obtained result is a 3D spatial coordinate in a coordinate system. Most mines use cross-sectional descriptions for their ore bodies, which require the creation of a 3D model. The oblique photogrammetry real-scene 3D model and the ore body 3D model are visually surface features. After docking, there are various relationships such as intersection, overlap, and inclusion. These relationships need to be interpreted before remodeling.

[0057] 1) Ore body modeling: First, determine the pinch-out point of the ore body using interpolation, finite inference, and infinite inference methods. Interpolation primarily involves obtaining the boundary reference points through interpolation; the specific formula is as follows: (37) In the formula, X d This is the distance from the ore-bearing borehole to the boundary of the ore body; C min Grade at the ore body boundary; C A C B The grade of the ore body is represented by industrial ore-bearing borehole A and non-industrial ore-bearing borehole B. L This is the distance between two boreholes. If the ore body thickness in a borehole without ore encounter is less than the minimum minable thickness but the grade meets the requirements, then: (38) In the formula, M A and M B M represents the ore body thickness of the ore-bearing borehole A and the non-industrial ore-bearing borehole B. min This is the minimum mineable thickness.

[0058] 2) Common interpolation methods for 3D modeling of ore bodies include the natural nearest neighbor method, the inverse power distance method, and the Kriging method. The natural nearest neighbor method uses a triangular mesh dual graph to interpolate arbitrary points, and the formula is as follows: (39) In the formula, Z(A) Z represents the estimated value of the point to be interpolated; D is the distance between the point to be interpolated and its naturally neighboring known points; D0 is the critical influence distance; n1 is the number of relevant known points; Z k1 (A) is the first Measured values ​​of known points.

[0059] The inverse power method of distance assumes that the closer the known point and the interpolation point are, the greater the correlation. The main calculation formula is as follows: (40) Among them, D k1 denoted as , where is the distance from the interpolation point to the known point, and μ is the exponent.

[0060] Kriging minimizes the interpolation points using linear regression, based on covariance.

[0061] (41) in, Given the point value, These are weights, which can be solved using a combination of functions. It represents the value of the distance model variable graph between points g1 and g2.

[0062] (42) in, It is a variation function. It is a Lagrange multiplier.

[0063] Step S5: Convert the target annual digital elevation model into a three-dimensional surface model of the open-pit image, and perform spatial registration and Boolean operation on the three-dimensional ore body model of the target open-pit mine and the three-dimensional surface model of the open-pit image to determine the three-dimensional ore body model of the ore body part that has been used.

[0064] As an optional implementation, in step S5, the three-dimensional ore body model of the target open-pit mine is spatially registered and Boolean-operated with the three-dimensional surface model of the open-pit image to determine the three-dimensional ore body model of the ore body portion that has been utilized. Specifically, this includes: Step S51: Using a seven-parameter spatial transformation model, the three-dimensional ore body model of the target open-pit mine and the three-dimensional surface model of the open-pit image are transformed to the same spatial coordinate system to complete the three-dimensional spatial registration.

[0065] Specifically, the ore body and the image need to be transformed into the same coordinate system. The two projected coordinate systems (X1, Y1, Z1) are transformed into (X2, Y2, Z2). The origins O1 and O2 of the two systems are different, and the coordinate axes are not parallel. During the transformation, in addition to the translation parameters (ΔX, ΔY, ΔZ), Euler angles are also required. εX , εY , εZ The corresponding rotation parameters (α, β, γ) are required, and the scale transformation parameter κ also needs to be set, for a total of 7 transformation parameters.

[0066] (43) in, The source coordinate system coordinate vector; The target coordinate system coordinate vector; , and These are the rotation matrices about the Z-axis, Y-axis, and X-axis, respectively. In the formula: (44) (45) (46) (47) The converted coordinates are consistent with the coordinates of the 3D model.

[0067] Step S52: Determine the spatial relationship between the 3D ore body model after 3D spatial registration and the 3D surface model of the open-pit image after 3D spatial registration. The spatial relationship is either intersecting or unrelated.

[0068] Specifically, the 3D ore body model registered in 3D space is docked with the 3D surface model of the open-pit image registered in 3D space. Figure 4 As shown, docking mainly includes intersection, inclusion, and irrelevance. Open-pit mine activity monitoring typically involves intersection or irrelevance. An intersection occurs when the ore body is not fully mined, while an irrelevance occurs when the ore body is fully mined. In an open-pit mine scenario, "intersection" means the current mining face (i.e., the 3D surface of the image) has cut into the ore body but has not been completely mined; "irrelevance" may indicate that the ore body has been completely mined out, or that the current mining activity has not yet reached the ore body.

[0069] To determine if they intersect, the intersection line L is calculated using the triangular mesh T1 of the image model and the triangular mesh T2 of the ore body model. The intersection line L intersects with the triangular meshes T1 and T2 at points A, B, C, and D, forming intervals [A, B] and [C, D]. If they overlap, they intersect; otherwise, they do not intersect.

[0070] Step S53: If the spatial positional relationship is intersecting, then perform Boolean operation on the three-dimensional ore body model registered in three-dimensional space and the three-dimensional surface model of the open-air image registered in three-dimensional space to calculate the intersection line of the corresponding triangular mesh, and cut the three-dimensional ore body model registered in three-dimensional space based on the intersection line to obtain the three-dimensional ore body model of the ore body part that has been used.

[0071] Step S54: If the spatial relationship is unrelated, then the entire three-dimensional ore body model after three-dimensional spatial registration is used as the three-dimensional ore body model of the utilized ore body portion. At this time, it is determined that the ore body has been completely mined, and the entire ore body model is directly used as the "three-dimensional ore body model of the utilized ore body portion".

[0072] Step S5 successfully and accurately extracted the three-dimensional spatial model of the portion of the ore body actually consumed by mining activities during the monitoring year from the complete ore body reserves, ensuring that the subsequent resource calculation object is the pure "utilized ore body", effectively avoiding the errors caused by the mixing of ore and waste rock in traditional methods.

[0073] Step S6: Based on the three-dimensional ore body model of the already utilized ore body, calculate the resource utilization of the already utilized ore body.

[0074] As an optional implementation, the resource utilization includes the utilization of ore and metal; therefore, step S6 specifically includes: Step S61: Divide the utilized ore body portion in the three-dimensional ore body model into multiple estimation blocks.

[0075] Step S62, using the formula Based on the volume and density of each estimated block, the amount of ore utilized in the already utilized orebody portion is calculated; among which, The amount of ore used in the already utilized portion of the ore body; To estimate the index of the block segment; To estimate the total number of blocks; For the first The estimated volume of each block segment; For the first The density of each estimated block segment.

[0076] Step S63, using the formula Based on the volume, density, and grade of each estimated block, the amount of metal utilized in the already utilized ore body is calculated; among which, The amount of metal utilized in the already utilized portion of the ore body; For the first The grade of each estimated block segment.

[0077] Specifically, for ore body A, which is unrelated to the 3D surface model of the open-air image registered in 3D space, a total of Each block segment has a volume of [number] segments. ,density ,grade The ore quantity dA and metal quantity mA directly incorporate the total resource quantity of the ore body into the utilization quantity.

[0078] For intersecting ore bodies, it is necessary to cut out the intersecting ore body portion and then calculate the resource utilization.

[0079] The intersection involves the line of intersection between the ore body and the ground of the 3D model image. The surface within the intersection line is used as the top surface of the ore body for modeling. The intersection line and the triangular mesh form a closed polygon, and triangular meshes are constructed for the vertices of the polygon. For the vertices of the formed polygon [V1,V2,V3,…,Vn], three points are taken sequentially to determine if they are collinear. If they are collinear, the intermediate points are deleted, and the above process is repeated until the end. The concavity and convexity of the vertices are determined using normal vectors. These triangular meshes are used to construct surfaces through TIN, which serve as the top surface of the docking 3D ore body model.

[0080] Step S7: Using the earthwork quota method, calculate the volume of the mined entity of the already utilized ore body within the preset monitoring period, and use the mined entity volume as the ore body quota earthwork volume.

[0081] As an optional implementation method, the preset monitoring period is two adjacent years; then step S7 specifically includes: Step S71: Based on the top surface of the pit constructed in the previous year, the top surface of the pit constructed in the current year, and the side surface of the ore body that has been utilized, determine a three-dimensional geometry bounded by the top surface of the pit constructed in the previous year, the top surface of the pit constructed in the current year, and the side surface of the ore body that has been utilized.

[0082] Step S72: Divide the three-dimensional geometry into multiple calculation segments along the mining direction, and calculate the cross-sectional area of ​​each calculation segment corresponding to the top surface of the mining pit constructed in the previous year and the cross-sectional area corresponding to the top surface of the mining pit constructed in the current year.

[0083] Step S73: Based on the cross-sectional area corresponding to the top surface of the mining pit constructed in the previous year and the cross-sectional area corresponding to the top surface of the mining pit constructed in the current year in all calculation segments, determine the volume of the mined entity of the ore body that has been utilized within the preset monitoring period.

[0084] Specifically, the "earthwork quota method" is introduced as a cross-validation tool to directly calculate the mining volume from the perspective of surface deformation. Open-pit mining involves not only the extraction of the ore body but also the surrounding rock; therefore, the earthwork quota refers to the earthwork of the ore body, and the calculation mainly focuses on the earthwork volume T of the mined portion of the ore body. Steps S71 to S73 assume the monitoring period is two adjacent years (e.g., the previous year and the current year). Assuming the top surface of the pit constructed in the previous year is S1 and the top surface of the pit constructed in the current year is S2, how do we combine the top surface of the current year's pit as the bottom surface, the top surface of the previous year's pit as the top surface, and the side surface of the ore body as the side surface to form a volume? This volume is the earthwork quota calculation quantity.

[0085] Each calculation segment consists of two cross-sections, D1 and D2, whose cross-sectional areas are calculated using a DTM network. The area of ​​a small triangular mesh, the area of ​​cross section D1 is... The cross-sectional area of ​​D2 is The corresponding calculation formula is: (48) (49) Each pair of cross sections forms a trapezoidal frustum. The volume of the extracted entity is calculated using the frustum volume formula (50): ） (50) in, V This refers to the earthwork volume allocated to the ore body. This represents the distance between every two cross sections.

[0086] Step S8: Compare the earthwork volume of the ore body quota with the total volume of the three-dimensional ore body model of the ore body part that has been used, and confirm the reliability of the resource utilization based on the comparison results, thereby completing the dynamic monitoring of the resource utilization of the target open-pit mine.

[0087] As an optional implementation, step S8 specifically includes: Step S81: The sum of the estimated volumes of all segments of the utilized ore body is used to determine the total volume of the three-dimensional ore body model of the utilized ore body.

[0088] Step S82: Calculate the absolute value of the difference between the total volume of the three-dimensional ore body model of the ore body portion that has been utilized and the earthwork volume of the ore body quota, and determine whether the absolute value is less than or equal to the preset allowable error threshold to obtain the comparison result.

[0089] Step S83: If the comparison result is yes, then the resource utilization is confirmed to be reliable.

[0090] Step S84: If the comparison result is negative, then the resource utilization is confirmed to be unreliable.

[0091] Specifically, resource estimation should be conducted, and the estimation parameters, methods, and block divisions for all resource quantities should be consistent with those in the exploration report. The industrial indicators for the deposit should be consistent with current industrial indicators; any inconsistencies between the industrial indicators in the report and current indicators should be corrected to reflect current indicators.

[0092] Basic parameters for resource estimation include the area, average thickness, dip angle, grade, and average weight of the ore body within the utilization range. Sometimes, ore moisture content and mineralization coefficient are also included. The most recent exploration report data should be used. Based on factors such as geological body occurrence, faults, and exploration projects, profile locations are selected. The vertical profile method is used to create the boundary lines of each profile, which are then projected onto the reserve estimation map. Connecting the boundary points of each profile line delineates the utilization range.

[0093] Depending on the scope of the impact, geometric methods (arithmetic mean method, geological block method, mining block method, cross-section method, contour line method, linear reserve method, trigonometric method, nearest area method, polygonal method), statistical analysis methods (distance-weighted method, kriging method), and SD method are used to calculate the amount of land covered. The geological block method and cross-section method are commonly used.

[0094] The resource utilization verification verifies whether the estimated volume of ore to be utilized is consistent with the calculated volume of earthwork quota. If the difference between the two is less than the given preset allowable error threshold ε, the calculation is considered valid; otherwise, the process starts from scratch.

[0095] (51) Furthermore, it also includes step S9: The optimized annual mobilization range vector is input, along with the bands R (red): 669.43 nm; G (green): 538.96 nm; B (blue): 479.25 nm from the oblique photography. These are used as inputs for the RGB (red, green, blue) color composite image. The composite color image is generated using points, lines, and surfaces with the same projection. The raster and vector are overlaid using coordinate layering.

[0096] vector x and y are the corresponding coordinates, and z is the eigenvalue. Vector values; raster , For the corresponding coordinates, This represents the raster grayscale value.

[0097] make Thus achieving a grid Grayscale values ​​and vectors The overlay process involves using corresponding coordinates to overlay raster and vector data, outputting a GIS vector and raster overlay image to create an image suitable for human visual perception.

[0098] Input oblique photographic images of the UAV and the annual operational range, and output a superimposed image (GIS) suitable for human visual observation. The final image can be output as a JPG or TIF format via software.

[0099] Based on the same inventive concept, this application also provides an open-pit mine resource utilization dynamic monitoring system for implementing the above-mentioned method for dynamic monitoring of open-pit mine resource utilization. The solution provided by this system is similar to the solution described in the above method. Therefore, the specific limitations of one or more embodiments of the open-pit mine resource utilization dynamic monitoring system provided below can be found in the limitations of the open-pit mine resource utilization dynamic monitoring method described above, and will not be repeated here.

[0100] In one exemplary embodiment, a dynamic monitoring system for resource utilization in an open-pit mine is provided, comprising: The registered SAR image data determination unit is used to acquire time-series SAR image data of the target open-pit mine, and to perform precise orbit correction and registration on the time-series SAR image data to obtain registered SAR image data; the registered SAR image data includes at least one pair of registered master image and slave image.

[0101] The initial annual digital elevation model determination unit is used to extract the initial annual digital elevation model based on the registered SAR image data using interferometric methods.

[0102] The target annual digital elevation model determination unit is used to identify incoherent regions in the initial annual digital elevation model and to compensate for the elevation information of the incoherent regions using a stereo measurement method based on radar intensity images, thereby obtaining the target annual digital elevation model.

[0103] The three-dimensional orebody model determination unit of the target open-pit mine is used to construct a three-dimensional orebody model of the target open-pit mine based on geological exploration data using interpolation methods.

[0104] The three-dimensional ore body model determination unit for the utilized ore body portion is used to convert the target annual digital elevation model into a three-dimensional surface model of the open-pit image, and to perform spatial registration and Boolean operation on the three-dimensional ore body model of the target open-pit mine and the three-dimensional surface model of the open-pit image to determine the three-dimensional ore body model for the utilized ore body portion.

[0105] The resource utilization determination unit for the utilized ore body is used to calculate the resource utilization of the utilized ore body based on the three-dimensional ore body model of the utilized ore body.

[0106] The orebody quota earthwork volume determination unit is used to calculate the volume of the mined orebody portion within a preset monitoring period using the earthwork quota method, and to use the mined volume as the orebody quota earthwork volume.

[0107] The reliability verification unit is used to compare the earthwork volume of the ore body quota with the total volume of the three-dimensional ore body model of the ore body part that has been used, and to confirm the reliability of the resource utilization based on the comparison results, thereby completing the dynamic monitoring of the resource utilization of the target open-pit mine.

[0108] Beneficial effects: 1) By accurately registering the three-dimensional surface model of the open-air image generated by InSAR with the three-dimensional ore body model in space, and by using Boolean operations, the ore body part that has been used is automatically and accurately cut out from the overall ore body model, ensuring that the calculation object is a pure ore body, eliminating the error caused by the mixing of ore and waste rock, and improving the monitoring accuracy. 2) By using the geometric volume calculated using earthwork quotas, the model results are cross-validated in real time to lock in the calculation accuracy and make the results verifiable and reliable.

[0109] 3) By utilizing time-series SAR imagery data to achieve all-weather, periodic automated processing and a real-time verification and feedback mechanism for motion data results, traditional manual and time-consuming specialized monitoring is transformed into a high-efficiency, batch-executable routine business process, significantly improving monitoring efficiency. It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of the relevant data must comply with relevant regulations.

[0110] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments described above. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM).

[0111] The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0112] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0113] This document uses specific examples to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the methods, systems, and core ideas of this application. Furthermore, those skilled in the art will recognize that, based on the ideas of this application, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A method for dynamic monitoring of resource utilization in open-pit mines, characterized in that, The method for dynamic monitoring of resource utilization in open-pit mines includes: Acquire time-series SAR image data of the target open-pit mine, and perform precise orbit correction and registration on the time-series SAR image data to obtain registered SAR image data; the registered SAR image data contains at least one pair of registered master and slave images; An initial annual digital elevation model was extracted using interferometric methods based on registered SAR image data. The incoherent regions in the initial annual digital elevation model are identified, and the elevation information of the incoherent regions is compensated using a stereo measurement method based on radar intensity images to obtain the target annual digital elevation model. An interpolation method was used to construct a three-dimensional ore body model of the target open-pit mine based on geological exploration data; The target annual digital elevation model is converted into a three-dimensional surface model of the open-pit image, and the three-dimensional ore body model of the target open-pit mine is spatially registered and Boolean operated with the three-dimensional surface model of the open-pit image to determine the three-dimensional ore body model of the ore body part that has been used. Based on the three-dimensional ore body model of the already utilized ore body, the resource utilization of the already utilized ore body is calculated. The earthwork quota method is used to calculate the volume of the mined entity of the already utilized ore body within the preset monitoring period, and the mined entity volume is used as the ore body quota earthwork volume. By comparing the earthwork volume of the ore body quota with the total volume of the three-dimensional ore body model of the ore body part that has been utilized, and confirming the reliability of the resource utilization based on the comparison results, dynamic monitoring of the resource utilization of the target open-pit mine is completed. Identify the incoherent regions in the initial annual digital elevation model (DEM), and use a stereo measurement method based on radar intensity images to compensate for the elevation information in the incoherent regions to obtain the target annual DEM, specifically including: The coherence of the interferometric pairs that generate the initial annual digital elevation model is calculated, and regions with coherence below a preset threshold are identified as incoherent regions. A stereo measurement method using radar intensity images is employed to acquire one or more sets of ascending-orbit SAR intensity images and descending-orbit SAR intensity images covering the decoherent region, forming a stereo image pair; Match corresponding points between the stereo image pairs and establish a coordinate transformation relationship model for the corresponding points. Using the range-Doppler model or collinear equation, based on the image coordinates of corresponding points in the stereo image pair, the satellite orbital position vector, the velocity vector of the antenna phase center, and the Doppler centroid frequency, the three-dimensional coordinates of ground points in the decoherent region are obtained through spatial forward intersection. The calculated three-dimensional coordinates of the ground points are interpolated to generate a local digital elevation model. The local digital elevation model is then merged with the initial annual digital elevation model to compensate for the elevation information of the incoherent areas in the initial annual digital elevation model, thus obtaining a complete target annual digital elevation model.

2. The method for dynamic monitoring of resource utilization in open-pit mines according to claim 1, characterized in that, The time-series SAR image data is subjected to precise orbit correction and registration to obtain registered SAR image data, specifically including: Download the precise orbit file that is spatiotemporally matched with the temporal and spatial information of the temporal SAR image data, and associate the precise orbit file with the master image and slave image in the temporal SAR image data to form an initial image pair with initial orbit information; Based on the initial image pair, an initial interferogram is generated, and non-deformation areas are selected on the initial interferogram as ground control points to generate corresponding ground control point files; the ground control point files contain the correspondence between the image coordinates and the actual geographic coordinates of each ground control point. The initial orbital parameter polynomial is used to perform coarse registration on the secondary images in the initial image pair to obtain the coarsely registered image pair. Based on the ground control point file, the orbit parameter model of the secondary image in the coarsely registered image pair is optimized to obtain the optimized orbit parameters; Based on the optimized orbit parameters, orbit error correction is performed on the coarsely registered image pairs, and the error-corrected image pairs are then subjected to re-flattening to obtain re-flattened image pairs. The corresponding master and slave images in the image pairs after deflating are re-registered to obtain the registered SAR image data.

3. The method for dynamic monitoring of resource utilization in open-pit mines according to claim 2, characterized in that, Using interferometric methods, an initial annual digital elevation model is extracted based on registered SAR image data, specifically including: The registered master image and slave image are multiplied together as an interference pair using complex conjugate multiplication to generate the corresponding interference phase map, and the interference phase difference of each pixel in the interference phase map is extracted. The parallel and vertical baselines of the corresponding interferometric pairs are calculated based on the optimized orbital parameters. Based on the parallel and vertical baselines and the interferometric phase difference of the corresponding pixels, a relationship model between the interferometric phase difference, the change in terrain elevation, and the flatland effect is established. Remove the flat terrain phase from the relation model to untangle the entangled interference phase and obtain the untangled terrain phase; Using geometric formulas, the unwrapped terrain phase is converted into the elevation value of each pixel to obtain the initial annual digital elevation model.

4. The method for dynamic monitoring of resource utilization in open-pit mines according to claim 1, characterized in that, Using interpolation methods and based on geological exploration data, a three-dimensional orebody model of the target open-pit mine is constructed, specifically including: Using a pre-defined algorithm and based on geological exploration data, the pinch-out point and boundary of the ore body are determined; the geological exploration data includes at least the grade value, ore body thickness value, and spatial location of each borehole. Using the ore body boundary as a constraint, a three-dimensional ore body model of the target open-pit mine is constructed based on the known thickness or grade values ​​of the borehole points using a preset spatial interpolation algorithm.

5. The method for dynamic monitoring of resource utilization in open-pit mines according to claim 4, characterized in that, Spatial registration and Boolean operations are performed between the 3D orebody model of the target open-pit mine and the 3D surface model of the open-pit image to determine the 3D orebody model of the utilized orebody portion, specifically including: A seven-parameter spatial transformation model was used to transform the three-dimensional ore body model of the target open-pit mine and the three-dimensional surface model of the open-pit image to the same spatial coordinate system, thus completing the three-dimensional spatial registration. Determine the spatial relationship between the 3D ore body model after 3D spatial registration and the 3D surface model of the open-pit image after 3D spatial registration; the spatial relationship is either intersecting or unrelated. If the spatial position relationship is intersecting, then perform Boolean operation on the three-dimensional ore body model after three-dimensional spatial registration and the three-dimensional surface model of the open-air image after three-dimensional spatial registration, calculate the intersection line of the corresponding triangular mesh, and cut the three-dimensional ore body model after three-dimensional spatial registration based on the intersection line to obtain the three-dimensional ore body model of the ore body part that has been used. If the spatial relationship is unrelated, then the three-dimensional ore body model after three-dimensional spatial registration is used as the three-dimensional ore body model of the ore body part that has been used.

6. The method for dynamic monitoring of resource utilization in open-pit mines according to claim 5, characterized in that, Resource utilization includes the amount of ore and the amount of metal utilized; Based on the three-dimensional orebody model of the already utilized portion of the orebody, the resource utilization of the already utilized portion is calculated, specifically including: The utilized ore body portion in the 3D ore body model is divided into multiple estimation blocks; Using formula Based on the volume and density of each estimated block, the amount of ore utilized in the already utilized orebody portion is calculated; among which, The amount of ore used in the already utilized portion of the ore body; To estimate the index of the block segment; To estimate the total number of blocks; For the first The estimated volume of each block segment; For the first The density of each estimated block segment; Using formula Based on the volume, density, and grade of each estimated block, the amount of metal utilized in the already utilized ore body is calculated; among which, The amount of metal utilized in the already utilized portion of the ore body; For the first The grade of each estimated block segment.

7. The method for dynamic monitoring of resource utilization in open-pit mines according to claim 6, characterized in that, The preset monitoring period is two consecutive years; The earthwork quota method is used to calculate the extracted volume of the utilized ore body within a preset monitoring period, and this extracted volume is used as the ore body quota earthwork volume, specifically including: Based on the top surface of the pit constructed in the previous year, the top surface of the pit constructed in the current year, and the side surface of the ore body that has been utilized, a three-dimensional geometry is defined, which is bounded by the top surface of the pit constructed in the previous year, the top surface of the pit constructed in the current year, and the side surface of the ore body that has been utilized. The three-dimensional geometry is divided into multiple calculation segments along the mining direction, and the cross-sectional area corresponding to the top surface of the mining pit constructed in the previous year and the cross-sectional area corresponding to the top surface of the mining pit constructed in the current year are calculated in each calculation segment. Based on the cross-sectional area corresponding to the top surface of the mining pit constructed in the previous year and the cross-sectional area corresponding to the top surface of the mining pit constructed in the current year in all calculation segments, the volume of the mined entity of the ore body that has been utilized is determined within the preset monitoring period.

8. The method for dynamic monitoring of resource utilization in open-pit mines according to claim 7, characterized in that, The reliability of the resource utilization amount is confirmed by comparing the allocated earthwork volume of the ore body with the total volume of the three-dimensional ore body model of the already utilized portion, and based on the comparison results: The sum of the estimated volumes of all segments of the utilized ore body is used to determine the total volume of the three-dimensional ore body model of the utilized ore body. Calculate the absolute value of the difference between the total volume of the three-dimensional ore body model of the ore body portion that has been utilized and the earthwork volume of the ore body quota, and determine whether the absolute value is less than or equal to a preset allowable error threshold to obtain the comparison result; If the comparison result is yes, then the resource mobilization is confirmed to be reliable; If the comparison result is negative, then the resource utilization is confirmed to be unreliable.

9. A dynamic monitoring system for resource utilization in open-pit mines, characterized in that, The open-pit mine resource utilization dynamic monitoring system is used to implement the open-pit mine resource utilization dynamic monitoring method according to any one of claims 1-8, and the open-pit mine resource utilization dynamic monitoring system includes: The registered SAR image data determination unit is used to acquire time-series SAR image data of the target open-pit mine, and to perform precise orbit correction and registration on the time-series SAR image data to obtain registered SAR image data; the registered SAR image data includes at least one pair of registered master image and slave image. The initial annual digital elevation model determination unit is used to extract the initial annual digital elevation model based on the registered SAR image data using interferometric methods. The target annual digital elevation model determination unit is used to identify the incoherent regions in the initial annual digital elevation model, and to use a stereo measurement method based on radar intensity images to compensate the incoherent regions for elevation information to obtain the target annual digital elevation model. The three-dimensional ore body model determination unit of the target open-pit mine is used to construct a three-dimensional ore body model of the target open-pit mine based on geological exploration data using interpolation methods. The three-dimensional ore body model determination unit for the already utilized ore body is used to convert the target annual digital elevation model into a three-dimensional surface model of the open-pit image, and to perform spatial registration and Boolean operation on the three-dimensional ore body model of the target open-pit mine and the three-dimensional surface model of the open-pit image to determine the three-dimensional ore body model for the already utilized ore body. The resource utilization determination unit for the utilized ore body is used to calculate the resource utilization of the utilized ore body based on the three-dimensional ore body model of the utilized ore body. The orebody quota earthwork volume determination unit is used to calculate the volume of the mined entity of the orebody that has been mobilized within a preset monitoring period using the earthwork quota method, and to use the mined entity volume as the orebody quota earthwork volume. The reliability verification unit is used to compare the earthwork volume of the ore body quota with the total volume of the three-dimensional ore body model of the ore body part that has been used, and to confirm the reliability of the resource utilization based on the comparison results, thereby completing the dynamic monitoring of the resource utilization of the target open-pit mine.

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