CN114199189A - Mining subsidence monitoring method combining unmanned aerial vehicle and DInSAR technology - Google Patents
Mining subsidence monitoring method combining unmanned aerial vehicle and DInSAR technology Download PDFInfo
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- CN114199189A CN114199189A CN202111499992.3A CN202111499992A CN114199189A CN 114199189 A CN114199189 A CN 114199189A CN 202111499992 A CN202111499992 A CN 202111499992A CN 114199189 A CN114199189 A CN 114199189A
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C5/00—Measuring height; Measuring distances transverse to line of sight; Levelling between separated points; Surveyors' levels
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
- G01S13/88—Radar or analogous systems specially adapted for specific applications
- G01S13/885—Radar or analogous systems specially adapted for specific applications for ground probing
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
- G01S13/88—Radar or analogous systems specially adapted for specific applications
- G01S13/89—Radar or analogous systems specially adapted for specific applications for mapping or imaging
- G01S13/90—Radar or analogous systems specially adapted for specific applications for mapping or imaging using synthetic aperture techniques, e.g. synthetic aperture radar [SAR] techniques
- G01S13/9004—SAR image acquisition techniques
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
- G01S19/38—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system
- G01S19/39—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system the satellite radio beacon positioning system transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
- G01S19/42—Determining position
- G01S19/45—Determining position by combining measurements of signals from the satellite radio beacon positioning system with a supplementary measurement
- G01S19/46—Determining position by combining measurements of signals from the satellite radio beacon positioning system with a supplementary measurement the supplementary measurement being of a radio-wave signal type
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Abstract
The invention relates to the technical field of mining subsidence monitoring, in particular to a mining subsidence monitoring method combining unmanned aerial vehicles and a DInSAR technology. The high precision of unmanned aerial vehicle data in the center of a subsidence area is utilized, the superiority of a DInSAR difference result in edge monitoring is reserved, and the shortcoming of the DInSAR means in the loss coherence of large-gradient deformation and the defect of the unmanned aerial vehicle technology in the aspect of edge micro-deformation monitoring are overcome. And the advantages of the two data are complemented, so that the high-precision monitoring of the mining subsidence area is realized.
Description
Technical Field
The invention relates to the technical field of mining subsidence monitoring, in particular to a mining subsidence monitoring method combining unmanned aerial vehicles and a DInSAR technology.
Background
The movement and deformation of the earth surface caused by mining are caused by the fact that after the mining layer of the mining area is mined, the original stress balance state of the surrounding rock mass is destroyed, and the stress is necessarily redistributed to achieve new balance. After the underground ore bed is mined out in a large area, the upper rock stratum loses support, the original stress balance condition is damaged, and the movement deformation is generated, so that the overlying rock stratum collapses, breaks and bends, and the ground surface sinks and deforms in a concave mode. The surface subsidence and surface subsidence caused by mining the mineral seam are collectively referred to herein as mining subsidence.
Mining subsidence is influenced by various factors, and complete surface deformation information needs to be monitored so as to provide scientific basis for safe mining and comprehensive environmental management of subsidence areas. The traditional mining subsidence monitoring method is leveling measurement and GPS measurement, but the traditional monitoring technologies such as leveling measurement and GPS measurement need a large amount of manpower and material resources, and continuous surface deformation information cannot be directly obtained. The unmanned aerial vehicle low-altitude photogrammetry technology and the synthetic aperture radar (DInSAR) differential interferometry technology are used as novel geodetic measurement means developed in recent years, and the defects of the traditional monitoring technology are made up to a certain extent. Mining subsidence is a large-deformation geological disaster, although an unmanned aerial vehicle monitors the mining subsidence and can obtain a central subsidence value of a subsidence area, subsidence data cannot reach the millimeter-level precision of traditional monitoring, the high-precision monitoring on the edge of a mining area is difficult, and the edge expression capability is poor; the DInSAR technology is affected by various factors such as orbit error and atmospheric delay, when the surface deformation gradient is too large, the loss coherence of an interference image pair is caused, and effective interference fringes cannot be obtained, so that the main value of mining subsidence cannot be obtained, and the precision of a subsidence area with large and fast settlement amount is low.
Because the respective limitations of the existing monitoring technologies make the monitoring process unable to accurately obtain the subsidence deformation information of the whole earth surface, it is urgently needed to provide a method for monitoring the mining subsidence deformation so as to obtain a more complete high-precision monitoring result.
Disclosure of Invention
The invention aims to provide a mining subsidence monitoring method combining unmanned aerial vehicles and the DInSAR technology, so that the problems in the prior art are solved.
In order to achieve the purpose, the technical scheme adopted by the invention is as follows:
a method of mining subsidence monitoring in conjunction with unmanned aerial vehicle and DInSAR techniques, the method comprising:
monitoring the marginal area of the mining subsidence through a DInSAR, determining a coherence threshold value monitored by the DInSAR according to SAR satellite parameters, and taking a monitoring point of the DInSAR which is smaller than the coherence threshold value and is closest to a mining subsidence center as the boundary of the DInSAR monitoring area;
monitoring a central area of the mining subsidence through an unmanned aerial vehicle, determining a monitoring threshold value monitored by the unmanned aerial vehicle according to a monitoring value of the unmanned aerial vehicle and a corresponding measured level value, and taking a monitoring point of which the monitoring value of the unmanned aerial vehicle is greater than the monitoring threshold value and which is farthest away from the mining subsidence center as a boundary of the monitoring area of the unmanned aerial vehicle;
and acquiring high-precision surface deformation information of the mining subsidence according to the coordinates of each monitoring point of the DInSAR monitoring area and the unmanned aerial vehicle monitoring area and the corresponding monitoring values thereof.
Preferably, the coherence threshold of the DInSAR monitoring is determined according to the SAR satellite parameters, specifically:
obtaining DInSAR detectable theoretical maximum deformation gradient d according to radar wavelength and pixel size of SAR satellitemaxSaid
The lambda is the radar wavelength, and the mu is the pixel size;
detectable maximum deformation gradient D according to preset DInSARmaxAnd d ismaxDetermining a coherence coefficient, said Dmax＝dmax+0.002(γ -1), said γ being the coherence coefficient;
and taking the obtained coherence coefficient as a coherence threshold value for screening the monitoring value of the DInSAR.
Preferably, the monitoring threshold value of unmanned aerial vehicle monitoring is determined according to the unmanned aerial vehicle monitoring value and the corresponding measured level value, and specifically:
according to the formula
Acquiring a monitoring threshold T;
wherein, the UiUnmanned aerial vehicle monitoring value W for ith monitoring pointiThe measured level value of the ith monitoring point is obtained, and n is the number of the monitoring points.
Preferably, if there are unmonitored points between the DInSAR monitoring area and the unmanned aerial vehicle monitoring area, determining a monitoring value of the unmonitored points by using an inverse distance weighting method, specifically:
according to the distance between the unmonitored point and the monitoring points around the unmonitored point, the distance is calculated according to a formula
Calculating the monitoring value of the unmonitored point;
wherein i is an unmonitored point, j is a monitored point around the unmonitored point, WiAnd WjRespectively representing the monitored values of the corresponding points, djIs the distance between the unmonitored point and its surrounding monitored points.
The invention has the beneficial effects that:
the invention provides a mining subsidence monitoring method combining unmanned aerial vehicle and DInSAR technologies, which fuses the unmanned aerial vehicle monitoring result of a mining subsidence area and the DInSAR differential settlement result. The high precision of unmanned aerial vehicle data in the center of a subsidence area is utilized, the superiority of a DInSAR difference result in edge monitoring is reserved, and the defects of loss coherence of a D-InSAR means in large gradient deformation and the defects of an unmanned aerial vehicle technology in the aspect of edge micro deformation monitoring are overcome. And the advantages of the two data are complemented, so that the high-precision monitoring of the mining subsidence area is realized.
Drawings
FIG. 1 is a schematic illustration of monitoring zones of a production subsidence area in an embodiment of the present invention;
in the figure, 1-mining area mining subsidence influence edge, 2-DInSAR monitoring area boundary and 3-unmanned aerial vehicle monitoring area boundary.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail below with reference to the accompanying drawings. It should be understood that the detailed description and specific examples, while indicating the invention, are intended for purposes of illustration only and are not intended to limit the scope of the invention.
The invention provides a mining subsidence monitoring method combining unmanned aerial vehicle and DInSAR technology, which comprises the following steps:
monitoring the marginal area of the mining subsidence through a DInSAR, determining a coherence threshold value monitored by the DInSAR according to SAR satellite parameters, and taking a monitoring point of the DInSAR which is smaller than the coherence threshold value and is closest to a mining subsidence center as the boundary of the DInSAR monitoring area;
monitoring a central area of the mining subsidence through an unmanned aerial vehicle, determining a monitoring threshold value monitored by the unmanned aerial vehicle according to a monitoring value of the unmanned aerial vehicle and a corresponding measured level value, and taking a monitoring point of which the monitoring value of the unmanned aerial vehicle is greater than the monitoring threshold value and which is farthest away from the mining subsidence center as a boundary of the monitoring area of the unmanned aerial vehicle;
and acquiring high-precision surface deformation information of the mining subsidence according to the coordinates of each monitoring point of the DInSAR monitoring area and the unmanned aerial vehicle monitoring area and the corresponding monitoring values thereof.
At present, different SAR satellites mainly adopt an L waveband, a C waveband and an X waveband. For example, ALOS-1 and JERS-1 satellites use the L band, with a wavelength of 23.5 cm; RADARSTA and a Sentinel satellite adopt a C wave band, and the wavelength is 5.6 cm; the Terras SAR-X and COSMO satellites adopt an X wave band, and the wavelength is 3 cm. In the DInSAR technology, the maximum deformation quantity of adjacent pixels of an SAR satellite which can be obtained by interferometry in an adjacent revisiting period is lambda/4. Therefore, the maximum deformation quantity of adjacent pixels which can be obtained by an L wave band is 5.87cm, the maximum deformation quantity of adjacent pixels which can be obtained by a C wave band is 1.4cm, and the maximum deformation quantity of adjacent pixels which can be obtained by an X wave band is 0.75 cm. In addition, the maximum sedimentation magnitude that can be monitored by the DInSAR technique during two imaging periods under ideal conditions is: w ═ r λ/4 μ, where: w represents the line-of-sight sedimentation amount, r represents the major influence radius of the mining area, and mu is the pixel size (ground resolution of the SAR sensor). The maximum settling amount in the vertical direction monitored by the InSAR is Δ Rmax ═ W/cos θ, where: Δ Rmax represents the maximum amount of settling in the vertical direction, and θ is the radar incident angle.
In practical application, the settlement gradient and the settlement amount which can be monitored by each wave band of the SAR satellite are smaller than theoretical values. For high-strength and large-gradient deformation, the DInSAR technology is also insufficient, so that the unmanned aerial vehicle data is adopted to monitor the large settlement gradient. According to experience, the root mean square error of unmanned aerial vehicle data and measured data is approximately 15cm-20cm, when the subsidence reaches the meter level, the unmanned aerial vehicle is adopted to monitor the deformation of the mining area, the accuracy requirement can be basically met, but for the subsidence edge area, the accuracy is relatively insufficient.
Therefore, the unmanned aerial vehicle and the DInSAR technology are combined to monitor the surface subsidence deformation, and the center of the mining subsidence area is monitored by utilizing the advantages that the unmanned aerial vehicle is flexible and is slightly limited by terrain and the like; the method can make up the defect of sparse measurement point positions in the traditional monitoring means by utilizing the DInSAR technology, has the characteristics and advantages of real time and high precision, and carries out deformation monitoring on the micro subsidence of the edge of the mining subsidence area. The unmanned aerial vehicle deformation monitoring result and the DInSAR result are fused, and the two data advantages are complemented to obtain a more accurate monitoring result. The distribution of the DInSAR monitoring area and the unmanned aerial vehicle monitoring area is shown in figure 1, wherein 1 is a mining area mining subsidence influence edge, 2 is a DInSAR monitoring area boundary, and 3 is an unmanned aerial vehicle monitoring area boundary; it should be noted that the schematic distribution of the monitoring area is only a specific implementation schematic provided by the present invention, and is only used for illustrating the present invention and not for limiting the scope of the present invention.
In this embodiment, a coherence threshold for DInSAR monitoring needs to be determined according to SAR satellite parameters, and a region with low coherence is removed to determine a DInSAR monitoring region. The coherence threshold is determined by the following equation:
Dmax＝dmax+0.002(γ-1)
in the formula, DmaxMaximum deformation gradient detectable for DInSAR; gamma is the coherence coefficient of the interferogram, ranging between 0 and 1; dmaxIs the maximum deformation gradient that can be theoretically detected by DInSAR, i.e.
(λ is the radar wavelength and μ is the pixel size). DmaxThe method can be preset according to a specific implementation scene to acquire a proper coherence coefficient as a coherence threshold. For example, for the image of Sentinel-1A using C-band and resolution of 20m, the maximum deformation gradient D detectable by DInSAR can be calculated by the formula when the coherence factor gamma is less than 0.3maxIs almost 0. Therefore, in order to ensure the correctness of the phase unwrapping result, the relative coefficient 0.3 is used as the screening threshold of the DInSAR monitoring value. By extracting the coherence coefficient of each monitoring point, the coherence threshold of the interference pair is set to 0.3 in the data processing process, so as to obtain a high coherence interferogram.
In this embodiment, the specific steps of determining the DInSAR monitoring region include: and processing the two SAR images, and performing two-rail method difference by combining an external DEM (Digital Elevation Model) to obtain a difference interference diagram. And (3) processing the differential interferogram by utilizing a function of extracting a value to a point of a 'Spatial analysis' tool in ArcGIS, and extracting the DInSAR monitoring value of each monitoring point on the working surface. And then screening the monitoring points by using the set threshold value of 0.3 coherence, opening a coherence map obtained in the process of the DInSAR processing by using ArcGIS to obtain the coherence coefficient of each monitoring point on the working face, screening the monitoring points by using the set coherence threshold value, taking the monitoring point with the coherence less than 0.3 and closest to the edge of the mining subsidence basin as the limit of the DInSAR monitoring, namely monitoring other monitoring points on one side of the monitoring point close to the edge of the mining subsidence basin by using the DInSAR.
In this embodiment, need confirm the monitoring threshold value of unmanned aerial vehicle monitoring according to unmanned aerial vehicle monitoring value and the actual measurement level value that corresponds to confirm unmanned aerial vehicle monitoring area. The monitoring threshold T is determined by the following formula:
wherein, the UiUnmanned aerial vehicle monitoring value W for ith monitoring pointiThe measured level value of the ith monitoring point is obtained, and n is the number of the monitoring points.
The specific steps for determining the unmanned aerial vehicle monitoring area in the embodiment are as follows: and obtaining two-stage DEM data corresponding to the DInSAR interference time by using an unmanned aerial vehicle technology. The two-phase DEM is then subtracted to obtain the condition of the subsurface subsidence basin caused by the mining of the research area within the two-phase time period. The unmanned aerial vehicle monitoring value of each monitoring point is extracted, then the monitoring value obtained by the unmanned aerial vehicle is screened by utilizing the monitoring threshold value T, the unmanned aerial vehicle monitoring value is selected to be larger than the monitoring threshold value T, the monitoring point farthest away from the mining subsidence basin center is the boundary of the unmanned aerial vehicle monitoring, and the unmanned aerial vehicle monitoring is adopted at other monitoring points close to one side of the mining subsidence basin center at the monitoring point.
In this embodiment, data fusion is performed on an exploitation subsidence edge area subjected to high-precision monitoring by a DInSAR and an exploitation subsidence center area subjected to high-precision monitoring by an unmanned aerial vehicle, if an unmonitored point exists between the DInSAR monitoring area and the unmanned aerial vehicle monitoring area (that is, an empty value exists between the DInSAR monitoring area after fusion and the boundary of the unmanned aerial vehicle monitoring area), a monitoring value of the unmonitored point is determined by using an inverse distance weighting method, and the specific steps are as follows:
according to the distance between the unmonitored point (xi, yi) and the monitoring points (xj, yj) around the unmonitored point, the monitoring value of the unmonitored point is calculated by the following formula:
wherein i is an unmonitored point and j isMonitoring points, W, around unmonitored pointsiAnd WjRespectively representing the monitored values of the corresponding points, djThe distance between the unmonitored point (xi, yi) and the monitoring point (xj, yj) around the unmonitored point, and the distance between the unmonitored point (xi, yi) and the monitoring point (xj, yj) around the unmonitored point
In this embodiment, if there is an overlap between the DInSAR monitoring region and the unmanned aerial vehicle monitoring region, since the monitoring error of the overlapping region is small, the monitoring value of any monitoring region may be adopted or the average of the two monitoring values may be taken.
In this embodiment, after the complete subsidence values (i.e., the monitoring values) of the monitoring points are obtained, a subsidence curve can be drawn by using the coordinates of the monitoring points and the corresponding subsidence values, so that the overall subsidence characteristics of the subsidence basin can be visually displayed.
By adopting the technical scheme disclosed by the invention, the following beneficial effects are obtained:
the invention provides a mining subsidence monitoring method combining unmanned aerial vehicle and DInSAR technologies, which fuses the unmanned aerial vehicle monitoring result of a mining subsidence area and the DInSAR differential settlement result. The high precision of unmanned aerial vehicle data in the center of a subsidence area is utilized, the superiority of a DInSAR difference result in edge monitoring is reserved, and the defects of loss coherence of a D-InSAR means in large gradient deformation and the defects of an unmanned aerial vehicle technology in the aspect of edge micro deformation monitoring are overcome. And the advantages of the two data are complemented, so that the high-precision monitoring of the mining subsidence area is realized.
The foregoing is only a preferred embodiment of the present invention, and it should be noted that, for those skilled in the art, various modifications and improvements can be made without departing from the principle of the present invention, and such modifications and improvements should also be considered within the scope of the present invention.
Claims (4)
1. A mining subsidence monitoring method combining unmanned aerial vehicle and DInSAR techniques, the method comprising:
monitoring the marginal area of the mining subsidence through a DInSAR, determining a coherence threshold value monitored by the DInSAR according to SAR satellite parameters, and taking a monitoring point of the DInSAR which is smaller than the coherence threshold value and is closest to a mining subsidence center as the boundary of the DInSAR monitoring area;
monitoring a central area of the mining subsidence through an unmanned aerial vehicle, determining a monitoring threshold value monitored by the unmanned aerial vehicle according to a monitoring value of the unmanned aerial vehicle and a corresponding measured level value, and taking a monitoring point of which the monitoring value of the unmanned aerial vehicle is greater than the monitoring threshold value and which is farthest away from the mining subsidence center as a boundary of the monitoring area of the unmanned aerial vehicle;
and acquiring high-precision surface deformation information of the mining subsidence according to the coordinates of each monitoring point of the DInSAR monitoring area and the unmanned aerial vehicle monitoring area and the corresponding monitoring values thereof.
2. The mining subsidence method of claim 1, wherein the coherence threshold for DInSAR monitoring is determined from SAR satellite parameters, specifically:
obtaining DInSAR detectable theoretical maximum deformation gradient d according to radar wavelength and pixel size of SAR satellitemaxSaid
The lambda is the radar wavelength, and the mu is the pixel size;
detectable maximum deformation gradient D according to preset DInSARmaxAnd d ismaxDetermining a coherence coefficient, said Dmax＝dmax+0.002(γ -1), said γ being the coherence coefficient;
and taking the obtained coherence coefficient as a coherence threshold value for screening the monitoring value of the DInSAR.
3. The mining subsidence method of claim 1, wherein the monitoring threshold value monitored by the unmanned aerial vehicle is determined according to the unmanned aerial vehicle monitoring value and the corresponding measured level value, and specifically:
according to the formula
Acquiring a monitoring threshold T;
wherein, the UiUnmanned aerial vehicle monitoring value W for ith monitoring pointiThe measured level value of the ith monitoring point is obtained, and n is the number of the monitoring points.
4. The mining subsidence method of claim 1, wherein if there are unmonitored points between the DInSAR monitored area and the unmanned aerial vehicle monitored area, determining a monitoring value of the unmonitored points by using a reverse distance weighting method, specifically:
according to the distance between the unmonitored point and the monitoring points around the unmonitored point, the distance is calculated according to a formula
Calculating the monitoring value of the unmonitored point;
wherein i is an unmonitored point, j is a monitored point around the unmonitored point, WiAnd WjRespectively representing the monitored values of the corresponding points, djIs the distance between the unmonitored point and its surrounding monitored points.
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