CN116448078A - Mine reserve estimation terrain profile method based on unmanned aerial vehicle oblique photography technology - Google Patents
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Abstract
The invention provides a mine reserve estimation topographic profile method based on unmanned aerial vehicle oblique photography technology, which comprises the steps of collecting field data of a mine, combining mine data, and arranging an unmanned aerial vehicle's route working scheme; laying image control points in a mine, and measuring coordinate information of the image control points by adopting RTK; acquiring oblique photography data of a mine by adopting an unmanned aerial vehicle, and acquiring a lens image and POS data; screening the lens images, and preprocessing the screened lens images to generate a mine digital surface model; converting the data of the mine digital surface model into mine point cloud data, filtering the mine point cloud data, and interpolating the filtered mine point cloud data to form a mine digital elevation model; and generating a two-dimensional geological profile by taking the mine digital elevation model as a base map, and judging whether the trend of the topographic profile meets the requirement. The influence of the surface structure and vegetation height on the unmanned aerial vehicle digital surface model is solved by adopting interpolation, and the drawing precision is improved.
Description
Technical Field
The invention relates to the technical field of mine reserve estimation, in particular to a mine reserve estimation topographic profile method based on unmanned aerial vehicle oblique photography technology.
Background
Mineral resources are taken as important material foundations for economic and social development and ecological civilization construction, and reasonable development and utilization of the mineral resources are one of important contents of the ecological civilization construction. However, the illegal exploitation of mineral resources not only damages the ecological environment and disturbs the normal safe production order of mines, but also threatens the life and property safety of people. Timely discovery and effective prevention of illegal mining behavior of mineral resources and maintenance of production safety are important responsibilities of supervision and management of natural resource authorities at all levels.
In the field inspection of mines, the estimation of mine reserves is mostly based on the plotting of terrain sections. The conventional topographic profile drawing method is to draw a profile base line by determining the direction of a topographic profile by taking a contour line as a data source in MAPGIS or CASS mapping software; determining a scale; determining an intersection point with the contour line; a plumb line; determining the height on the vertical line according to the vertical scale; the process of connecting each height point by using a smooth curve is used for realizing the manufacture of a terrain profile, and professional measuring equipment such as a total station, RTK and the like is required for carrying out measurement on the current situation of the mine terrain for the drawing of the terrain profile.
However, the process of drawing the topographic profile is complicated, field operators are required to use professional measuring tools such as total stations, RTKs and the like to carry out field topographic mapping, and the topographic profile can be drawn in a curve after developing an internal imaging, so that the drawing technology is relatively dependent on the capability level and experience of technicians, errors are easy to generate, the accuracy is not enough, and the aspects of reflecting the mine behavior and change are weaker; and although the emerging laser radar technology can rapidly acquire the topographic information, the measurement cost is high, the point cloud data contains noise points and a large amount of redundant information, the data processing difficulty is high, the specialization is strong, and the acquisition is difficult.
Therefore, the current mine reserve estimation adopts terrain profile drawing which is insufficient in accuracy and weak in reflecting mine behavior and change, and adopts a laser radar technology which is high in cost and difficult in data processing.
Disclosure of Invention
Aiming at the defects existing in the prior art, the invention provides a mine reserve estimation topographic profile method based on unmanned aerial vehicle oblique photography technology, which aims to solve the technical problems that the existing mine reserve estimation in the prior art adopts topographic profile drawing to be insufficient in accuracy and weak in reflecting mine behavior and change, and adopts a laser radar technology to face high cost and high data processing difficulty.
The invention provides a mine reserve estimation topographic profile method based on unmanned aerial vehicle oblique photography technology, which comprises the following steps:
s1, acquiring field data of the mine, and laying an unmanned aerial vehicle route working scheme by combining mine data;
s2, arranging image control points in the mine, and measuring coordinate information of the image control points by adopting RTK;
s3, acquiring oblique photographic data of the mine by adopting the unmanned aerial vehicle, and acquiring a lens image and POS data;
s4, screening the lens images, and preprocessing the screened lens images to generate a mine three-dimensional space model and a mine digital surface model;
s5, converting the data of the mine digital surface model into mine point cloud data, filtering the mine point cloud data, and interpolating the filtered mine point cloud data to form a mine digital elevation model;
s6, generating a two-dimensional geological section by taking the mine digital elevation model as a base map, and judging whether the two-dimensional geological section has the same topographic section trend as that of mine data.
Optionally, the acquiring the lens image and POS data includes:
the lens image data at least comprises an external azimuth element, an internal azimuth element and distortion parameter information of a camera, and the POS data at least comprises an image name and external azimuth element information.
Optionally, the screening the lens image includes:
screening the lens images, checking the overlapping degree of the photos, wherein the inclination angle of the photos is less than or equal to 12 degrees, the rotation deflection angle is less than or equal to 12 degrees, the altitude difference of the same course is not more than 30 meters, the course overlapping rate is 80%, the side overlapping rate is 70%, and the flying height is 100 meters.
Optionally, the preprocessing the screened lens image includes:
the preprocessing at least comprises the steps of puncturing a control point of lens image data, setting a plane of check point verification image, high elevation precision, space three encryption and data optimization.
Optionally, the converting the data of the mine digital surface model into mine point cloud data includes:
and converting the data of the mine digital surface model into mine point cloud data, and removing surface structures and vegetation information in the mine point cloud data in an automatic classification and manual classification mode.
Optionally, the interpolating the filtered mine point cloud data includes:
and exporting and storing the filtered mine point cloud data, and carrying out high Cheng Chazhi on the mine point cloud data by adopting a kriging interpolation variation function model.
Optionally, the kriging interpolation includes:
the calculation formula of the kriging interpolation is as follows:
wherein the method comprises the steps ofIs the point (x) o ,y o ) Where the estimation is z o ＝z(x o ,y o )，λ i Is a weight coefficient lambda i Also, the value of the unknown point is estimated by the weighted summation of the data of all the known points in space, lambda i Is capable of satisfying the point (x o ,y o ) Estimate of where->And the true value z o A set of optimal coefficients with the smallest difference, i.e. +.>At the same time, satisfies the condition of unbiased estimation, i.e
Optionally, the generating a two-dimensional geological profile by using the mine digital elevation model as a base map, and determining whether the two-dimensional geological profile has the same topographic profile trend as the mine data includes:
and generating a two-dimensional geological profile by taking the mine digital elevation model as a base map, reading elevation values on profile lines to complete the drawing of the terrain profile, comparing the elevation values with mine profile data of the mine data, and judging whether the tendency of the terrain profile is the same.
Compared with the prior art, the invention has the following beneficial effects:
1. the surface mine is drawn by adopting the unmanned aerial vehicle oblique photography technology, three-dimensional space information of the mine can be obtained, and the real appearance, position, height and other information of the ground feature can be intuitively reflected, and meanwhile, the surveying and mapping precision can be achieved.
2. The influence of the surface structure and vegetation height on the unmanned aerial vehicle digital surface model is solved by adopting interpolation, and the drawing precision is improved.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and together with the description, serve to explain the principles of the invention.
In order to more clearly illustrate the embodiments of the invention or the technical solutions of the prior art, the drawings which are used in the description of the embodiments or the prior art will be briefly described, and it will be obvious to a person skilled in the art that other drawings can be obtained from these drawings without inventive effort.
FIG. 1 is a schematic flow chart of the method of the present invention;
FIG. 2 is a schematic diagram of field image control point layout measurement in the present invention;
FIG. 3 is a schematic view of a mine stope and an industrial plaza of the present invention;
FIG. 4 is a schematic diagram of the result of the three-dimensional model of the mine in the invention;
FIG. 5 is a schematic view of a mine numerical surface model in accordance with the present invention;
FIG. 6 is a schematic diagram of the invention before and after filtration of the mine digital surface model;
FIG. 7 is a schematic view of a digital elevation model of a mine in the present invention;
FIG. 8 is a schematic view of the present situation of a mine in the present invention.
Detailed Description
For the purposes of making the objects, technical solutions and advantages of the embodiments of the present application more clear, the technical solutions of the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is apparent that the described embodiments are some embodiments of the present application, but not all embodiments. All other embodiments, which can be made by one of ordinary skill in the art without undue burden from the present disclosure, are within the scope of the present application based on the embodiments herein. The functional units of the same reference numerals in the examples of the present invention have the same and similar structures and functions.
Referring to fig. 1, the invention provides a mine reserve estimating topographic profile method based on unmanned aerial vehicle oblique photography technology, comprising the following steps:
s1, acquiring field data of the mine, and laying an unmanned aerial vehicle route working scheme by combining mine data;
s2, arranging image control points in the mine, and measuring coordinate information of the image control points by adopting RTK;
s3, acquiring oblique photographic data of the mine by adopting the unmanned aerial vehicle, and acquiring a lens image and POS data;
s4, screening the lens images, and preprocessing the screened lens images to generate a mine three-dimensional space model and a mine digital surface model;
s5, converting the data of the mine digital surface model into mine point cloud data, filtering the mine point cloud data, and interpolating the filtered mine point cloud data to form a mine digital elevation model;
s6, generating a two-dimensional geological section by taking the mine digital elevation model as a base map, and judging whether the two-dimensional geological section has the same topographic section trend as that of mine data.
S1, field data acquisition of mines is performed, and an unmanned aerial vehicle route working scheme is laid by combining mine data.
Firstly, preparing in advance, checking the condition of unmanned aerial vehicle equipment before carrying out mine field data acquisition, carrying out on-site survey on a mine, and laying a reasonable route working scheme by combining mine ore right related data.
S2, arranging image control points in the mine, and measuring coordinate information of the image control points by adopting RTK.
Referring to fig. 2 and 3, image control points are distributed on the mine ground, and coordinate information of field image control points is measured by using an RTK; it should be noted that, the coordinate information of the image control point needs to be processed by the CORS system after being processed by the high Cheng Jie algorithm for the unmanned aerial vehicle internal industry.
S3, adopting the unmanned aerial vehicle to acquire oblique photography data of the mine, and acquiring a lens image and POS data.
The unmanned aerial vehicle can adopt the model of the Xingjiang longitude and latitude M300, and acquire the lens image and POS data of the mine by utilizing the unmanned aerial vehicle to acquire oblique photographing data of the mine, wherein the lens image data at least comprises information such as external azimuth elements, internal azimuth elements, distortion parameters of cameras and the like, and the POS data at least comprises image name and external azimuth element information.
S4, screening the lens images, and preprocessing the screened lens images to generate a mine three-dimensional space model and a mine digital surface model.
Screening the lens images, checking the overlapping degree of the photos, wherein the inclination angle of the photos is less than or equal to 12 degrees, the rotation deflection angle is less than or equal to 12 degrees, the altitude difference of the same course is not more than 30 meters, the course overlapping rate is 80%, the side overlapping rate is 70%, and the flying height is 100 meters;
referring to fig. 4 and 5, preprocessing the screened lens image, specifically, importing the mine image with qualified inspection quality into intelligent map software in Xinjiang for internal processing, and generating a mine three-dimensional space model (OSGB format) and a mine digital surface model (tif format) through the processes of preprocessing image data, image control point stabbing, setting plane and elevation precision of check point verification image, air-to-air encryption, data optimization and the like
S5, converting the data of the mine digital surface model into mine point cloud data, filtering the mine point cloud data, and interpolating the filtered mine point cloud data to form a mine digital elevation model.
The data of the mine digital surface model contains non-ground information such as vegetation, surface buildings, moving objects and the like, and in the process of analyzing the mine exploitation profile, the height of the vegetation can enable the indicated elevation to be higher than the whole real ground elevation in the vegetation coverage area, and the error can seriously affect the analysis precision of the mine profile, so that inaccurate mine reserve estimation is caused. And carrying out mine surface structure and vegetation filtering on the digital surface model in the original landform range to generate an accurate mine digital elevation model, so that more real terrain information can be obtained.
Importing the mine digital surface model into global mapper software, and converting the data into mine point cloud data in the las format; and classifying mine point cloud data, classifying ground points by adopting automatic classification and manual classification functions, and filtering mine surface structures and vegetation by using classification results to obtain filtered raster data (see fig. 6 for details). In order to truly express the ground surface information of the mine, the filtered mine ground surface structure and vegetation information need to be recalculated and assigned, and the high Cheng Chazhi is carried out on the removed area by adopting the Kriging interpolation variation function model to generate a mine digital elevation model.
The method is based on variation function theory and structural analysis, and performs unbiased optimal estimation on variables in a range in a limited area, and takes spatial correlation properties in a calculation area into consideration in a gridding process, so that an interpolation result is more scientific and is closer to an actual situation, and a calculation formula of the kriging interpolation method is as follows:
wherein the method comprises the steps ofIs the point (x) o ,y o ) Where the estimation is z o ＝z(x o ,y o )。
Here, lambda i Is a weight coefficient that is also a weighted sum of the data of all known points in space to estimate the value of the unknown point. However, the weight coefficient is not the inverse of the distance, but can satisfy the point (x o ,y o ) Estimated value of the positionAnd the true value z o A set of optimal coefficients with the smallest difference, i.e. +.>At the same time satisfying the condition of unbiased estimation, i.e. +.>
The kriging interpolation variation function model construction comprises exploratory statistical analysis of data, heterofunctional model modeling and surface creation. The calculation steps are as follows:
1. calculating the distance between any null positions in the filtered raster data;
2. the distance grouping, namely sorting the distance values obtained by the first step from small to large, and then grouping the distance values, wherein each group comprises a certain number of distance values;
3. calculating average distance according to each group of distance values, calculating variation function estimated value of each group according to a formula, selecting a certain variation function theoretical model, performing function fitting, and calculating model parameters so as to obtain an expression of a variation function;
4. and calculating an estimated value of the point to be inserted.
Specifically, the filtered raster data is exported and stored as a Csv format, the data contains longitude, latitude and elevation information, a common kriging interpolation method is adopted, a linear variation function model is selected and constructed, a search radius is set as a variable in a limited area, the number of points in the search radius is set to be 10, the kriging estimation range is consistent with a base map (filtered raster data), and the gridding mask analysis is also selected to be consistent with the base map, so that a mine digital elevation model (see fig. 7 in particular) is obtained.
S6, generating a two-dimensional geological section by taking the mine digital elevation model as a base map, and judging whether the two-dimensional geological section has the same topographic section trend as that of mine data.
The method is characterized in that a mine digital elevation model is used as a base map, a 3D Path is added to an estimated topographic section line of the mine field check reserve according to a Path section mode, elevation/horizontal parameters of the section are set, a two-dimensional geological section map is generated, section data are stored as CSV files, derived distance and high Cheng Geshi section data are calculated and compared with the existing mine section data to verify, and under the condition that the section lines are consistent, geological section trends are approximately the same, so that the mine field check requirements are completely met.
In another embodiment, the three-dimensional space model of the mine is imported into three-dimensional visualization software, the current mining situation of the mine is visually displayed, the mining situation and recovery treatment situation are mastered, the three-dimensional space models of the mine in different time phases are overlapped, the mining change situation, mining position, mining amount and other information of the mine in a period of time can be known, and powerful data support is provided for fine supervision of the mine.
The mine plane and elevation boundary crossing condition is monitored by taking a mine digital orthographic image and a mine digital elevation model as base charts, superposing a mine range and combining elevation information (see in particular FIG. 8).
It should be noted that in this document, relational terms such as "first" and "second" and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
The foregoing is only a specific embodiment of the invention to enable those skilled in the art to understand or practice the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the invention. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (8)
1. A method for estimating a terrain profile of a mine reserve based on unmanned aerial vehicle oblique photography, comprising:
s1, acquiring field data of the mine, and laying an unmanned aerial vehicle route working scheme by combining mine data;
s2, arranging image control points in the mine, and measuring coordinate information of the image control points by adopting RTK;
s3, acquiring oblique photographic data of the mine by adopting the unmanned aerial vehicle, and acquiring a lens image and POS data;
s4, screening the lens images, and preprocessing the screened lens images to generate a mine three-dimensional space model and a mine digital surface model;
s5, converting the data of the mine digital surface model into mine point cloud data, filtering the mine point cloud data, and interpolating the filtered mine point cloud data to form a mine digital elevation model;
s6, generating a two-dimensional geological section by taking the mine digital elevation model as a base map, and judging whether the two-dimensional geological section has the same topographic section trend as that of mine data.
2. The method for estimating a topographic profile of a mine reserve based on unmanned aerial vehicle oblique photography as claimed in claim 1, wherein said acquiring lens images and POS data comprises:
the lens image data at least comprises an external azimuth element, an internal azimuth element and distortion parameter information of a camera, and the POS data at least comprises an image name and external azimuth element information.
3. The method for estimating a topographic profile of a mine reserve based on unmanned aerial vehicle oblique photography as claimed in claim 1, wherein said screening said lens images comprises:
screening the lens images, checking the overlapping degree of the photos, wherein the inclination angle of the photos is less than or equal to 12 degrees, the rotation deflection angle is less than or equal to 12 degrees, the altitude difference of the same course is not more than 30 meters, the course overlapping rate is 80%, the side overlapping rate is 70%, and the flying height is 100 meters.
4. The method for estimating a topographic profile of a mine reserve based on unmanned aerial vehicle oblique photography as set forth in claim 1, wherein the pre-processing the screened lens image includes:
the preprocessing at least comprises the steps of puncturing a control point of lens image data, setting a plane of check point verification image, high elevation precision, space three encryption and data optimization.
5. The unmanned aerial vehicle tilt photography based mine reserve estimation terrain profile method of claim 1, wherein the converting the data of the mine digital surface model to mine point cloud data comprises:
and converting the data of the mine digital surface model into mine point cloud data, and removing surface structures and vegetation information in the mine point cloud data in an automatic classification and manual classification mode.
6. The unmanned aerial vehicle tilt photography based mine reserve estimation terrain profile method of claim 1, wherein the and interpolating the filtered mine point cloud data comprises:
and exporting and storing the filtered mine point cloud data, and carrying out high Cheng Chazhi on the mine point cloud data by adopting a kriging interpolation variation function model.
7. The unmanned aerial vehicle tilt photography based mine reserve estimation terrain profile method of claim 6, wherein the kriging interpolation comprises:
the calculation formula of the kriging interpolation is as follows:
wherein the method comprises the steps ofIs the point (x) o ,y o ) Where the estimation is z o ＝z(x o ,y o )，λ i Is a weight coefficient lambda i Also, the value of the unknown point is estimated by the weighted summation of the data of all the known points in space, lambda i Is capable of satisfying the point (x o ,y o ) Estimate of where->And the true value z o A set of optimal coefficients with the smallest difference, i.e. +.>At the same time, satisfies the condition of unbiased estimation, i.e
8. The method for estimating a topographic profile of a mine reserve based on the unmanned aerial vehicle oblique photography technique as set forth in any one of claims 1 to 7, wherein the generating a two-dimensional geological profile based on the mine digital elevation model, determining whether the two-dimensional geological profile has the same topographic profile trend as the mine data, includes:
and generating a two-dimensional geological profile by taking the mine digital elevation model as a base map, reading elevation values on profile lines to complete the drawing of the terrain profile, comparing the elevation values with mine profile data of the mine data, and judging whether the tendency of the terrain profile is the same.
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| CN117029804A (en) * | 2023-08-07 | 2023-11-10 | 自然资源部重庆测绘院 | Mining area topography automatic updating method based on vehicle positioning information |
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| CN117029804A (en) * | 2023-08-07 | 2023-11-10 | 自然资源部重庆测绘院 | Mining area topography automatic updating method based on vehicle positioning information |
| CN117029804B (en) * | 2023-08-07 | 2024-04-26 | 自然资源部重庆测绘院 | Mining area topography automatic updating method based on vehicle positioning information |
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