A method for generating geological profiles based on SfM-MVS point clouds

Abstract

This invention discloses a method for generating geological profiles based on SfM-MVS point clouds, involving the field of geological attribute information extraction, including three important stages: geological outcrop image acquisition and 3D point cloud modeling; extraction of geospatial information and geological attribute information; and data processing and mapping. Geospatial information includes the acquisition of attitude and geometric parameter data, while geological attribute information includes lithology and tectonic properties. This method represents a breakthrough in 3D remote sensing research at the outcrop scale, inheriting the non-contact, macroscopic, comprehensive, and multi-temporal characteristics of remote sensing. It transforms the subjective field recording process into data acquisition and information extraction, avoiding the drawbacks of inaccessibility, discrete information observation, and inconsistent understanding. This enables the digital preservation of geological outcrops and provides methodological support for the construction of a global outcrop database.

Description

Technical Field

[0001] This invention relates to the field of geological attribute information extraction technology, and in particular to a method for generating geological profiles based on SfM-MVS point clouds. Background Technology

[0002] Outcrop geological profile mapping is a fundamental task in geological science. Geological profile surveying refers to the process of actually measuring and compiling geological profile maps along a certain orientation within a selected area after reconnaissance. It is a process of studying and dissecting key issues of strata, structures, igneous rocks, and ore bodies in the survey area. It serves as the basis for controlling the stratigraphic framework of the survey area, representing the geological structural framework, and dividing mapping units, and is a crucial prerequisite for mapping quality. Geological profiles mainly include cross-section maps, columnar sections, orthogonal sections, and balanced sections. The traditional surveying method is the traverse method, which relies on tools and data such as compasses, measuring ropes, and topographic maps. This method is a contact survey and is often limited by factors such as inaccessibility, visibility conditions, traverse curvature, and human measurement errors. The point coordinate method uses ground-based RTK-GPS to replace measuring ropes, overcoming the limitation of visibility conditions. However, it still requires the preparation of topographic maps in advance, the use of compasses to measure the attitude, and the use of rulers to measure the geometric characteristics of geological bodies. It remains at the technical stage of contact surveying, resulting in a large amount of time and labor intensity in the field, making it relatively time-consuming and labor-intensive. Furthermore, contact measurements rely on visual observation of rocks and structures, which is a discrete sampling survey and subjective judgment process. It cannot obtain comprehensive, macroscopic, and objective data on outcrops, and the measurements are one-time results, making it impossible to achieve the goal of digitizing and intelligently generating geological profiles from data.

[0003] Currently, remote sensing, a non-contact measurement method, is widely used in the Earth sciences due to its unique advantages in terms of periodicity, macroscopicity, and systems. Therefore, remote sensing-driven geological surveys have the potential to replace contact-based measurements, especially with the recent development of UAV-based SfM-MVS (Structure from Motion with Multi-view Stereo) 3D point cloud technology, which offers an opportunity to fundamentally change the status quo of contact-based measurements. It can not only acquire topographic information but also provide an immersive experience of outcrops. For example, thanks to advancements in laser scanning or photogrammetry, high-resolution and ultra-high-resolution (centimeter to millimeter) reproductions of geological outcrops (digital outcrop models) are possible. These technologies, combined with inexpensive and easy-to-use UAV technology, make it possible to acquire topographic data with millimeter to centimeter resolution over an area of ​​several square kilometers, providing an objective method for rapidly collecting detailed 3D information on geological structures. Once data is acquired, indoor mapping is automated, making geological research using outcrop point clouds a highly promising development direction. Summary of the Invention

[0004] The purpose of this invention is to provide a geological profile generation method based on SfM-MVS point clouds. This SfM-MVS point cloud-based geological profile mapping method represents a breakthrough in 3D remote sensing research at the outcrop scale. It inherits the non-contact, macroscopic, comprehensive, and multi-temporal characteristics of remote sensing. More importantly, it transforms the subjective field recording process into two main components: data acquisition and information extraction. This avoids the drawbacks of inaccessibility by humans, discrete information observation, and inconsistent understanding, enabling the digital preservation of geological outcrops. It provides methodological support for the construction of outcrop big data, is easy to operate, highly adaptable to different working environments, more convenient and flexible, highly repeatable, and applicable to geological mapping and scientific research.

[0005] This invention provides a method for generating geological profiles based on SfM-MVS point clouds, comprising the following steps:

[0006] Select the outcrops to be measured in the geological profile, collect images of the outcrops from multiple angles, and form an image set.

[0007] Import the image set into the point cloud modeling software to generate sparse point clouds and dense point clouds;

[0008] For point clouds with relative geographic coordinate control, the control surface method is used to perform attitude and size correction to obtain a corrected outcrop point cloud model.

[0009] The outcrop point cloud model is classified and layered, geological boundary points and topographic control points are marked, the 3D coordinates of geological boundary points and topographic control points are extracted, geological attribute information is assigned to the coordinates of geological boundary points, and the dense point cloud is exported in point cloud data format with the extension .las.

[0010] Import the exported dense point cloud into the point cloud processing software, use a virtual compass to determine the attitude of the structural surface that has reached the set value, or use the three-point method to calculate the attitude of the structural surface that has not reached the set value.

[0011] The occurrence data and geological attribute information are integrated into a two-dimensional relational data table in Excel, and after projection calculation, the data is imported into the data mapping software;

[0012] Digital mapping software is used to generate a cross-sectional grid, which is then further refined and filled with geological lithology and structural national standard patterns to form a geological cross-section map.

[0013] Preferably, when acquiring images of the exposed object from multiple angles:

[0014] If there is no RTK-GNSS signal in the outcrop area to be measured, a ground control surface is placed in the scene to be photographed as a reference surface. The dip and tilt angle of the ground control surface are measured with a compass, and the measured dip and tilt angle are converted into NED coordinates to obtain the true attitude and size parameters of the reference object.

[0015] If there is an RTK-GNSS signal in the outcrop area to be measured, then use an RTK-GNSS drone to directly take pictures, or use an RTK-GNSS base station to set up ground control points and measure the coordinates of the control points in the outcrop to be measured.

[0016] Preferably, if there is no RTK-GNSS signal in the outcrop area to be measured, the attitude and size correction of the dense point cloud is performed using the control surface method.

[0017] Preferably, when acquiring images of the outcrop object from multiple angles, the remote sensing platform moves, and the overlap between consecutive images is not less than 60%.

[0018] Preferably, before generating sparse and dense point clouds, images that do not meet the quality requirements are removed based on the image quality estimation function of the point cloud modeling software, and the remaining images are used to generate sparse and dense point clouds.

[0019] Preferably, for point clouds controlled by absolute geographic coordinates, sparse point clouds and dense point clouds are directly classified and layered.

[0020] Preferably, the geological profile includes a horizontal rock strata columnar section, an inclined rock strata cross section, and a combined horizontal and vertical cross section of folded rock strata.

[0021] Preferably, the horizontal rock strata columnar section and the inclined rock strata cross section require one data mapping process, while the folded rock strata combined cross and longitudinal cross section requires at least three combined cross section generation processes.

[0022] The geological profile generation method based on SfM-MVS point cloud provided by this invention has the following beneficial effects:

[0023] (I) This invention utilizes the non-contact nature of remote sensing, reducing labor intensity. This method eliminates the need for prior surveyors to travel back and forth to discuss geological survey content, and does not require consideration of the line-of-sight between surveyors. Furthermore, it can combine lithological contact and dip data to accurately measure the thickness of large strata, reducing limitations imposed by human intervention. Because it only requires obtaining image data of outcrops, various camera mounts are available, including handheld devices, selfie sticks, drones, and vehicle-mounted cameras. This is advantageous for mapping in special areas such as deeply dissected loess-covered areas and forest-covered areas.

[0024] (ii) This method inherits the advantages of remote sensing in terms of its macroscopic, comprehensive, and systematic nature. Another advantage of this method compared to traditional geological mapping is its ability to extract occurrence data from any part of the model, providing good coverage within the mapped area without any spatial data gaps.

[0025] (III) This method achieves instrumentation and quantification in geological profile mapping. The entire process relies on instrumental data collection, eliminating the need for manual readings and improving accuracy. While field sampling still requires labor, the entire workflow introduces 3D remote sensing technology into outcrop geological profile mapping. This not only overcomes the shortcomings of contact measurement but also transforms visual observation and manual recording into instrumental observation and computer data processing, allowing this work to inherit the advantages of remote sensing, such as non-contact, comprehensive, macroscopic, and timely processing. The use of drones and close-range photography equipment enables profile measurements even in areas inaccessible by humans. This significantly reduces the labor intensity and field hazards for geologists, breaking through the limitations of manual measurement and sampling surveys.

[0026] (iv) This method allows for multiple measurements and optimized mapping. As long as an outcrop can be observed, any outcrop point cloud data volume can be used as a candidate point for profile mapping. Therefore, according to this method, profile measurement actually only requires a single high-density multi-outcrop observation to ultimately select the optimal outcrop for mapping.

[0027] (V) This method achieves an immersive and digitally preserved effect. Because it obtains a three-dimensional outcrop model, it provides an immersive experience, allowing for extensive indoor analysis and repeated access to and sharing of outcrop data without additional fieldwork—a stark contrast to manual profiling methods. Repeatability and reproducibility of field observations are effortless, enabling new observations or testing of previous ones. Measurements can be conducted at multiple scales, from point measurements (similar to a handheld compass) to larger areas. Simultaneously, it provides the ability to quickly and accurately measure irregular or weathered surfaces. Furthermore, the application of this method offers an invaluable digital preservation of a region at a specific time phase, as geological outcrops are not permanent in some locations. Attached Figure Description

[0028] Figure 1 A detailed flowchart of the geological profile generation method based on SfM-MVS point cloud provided in the embodiments of the present invention;

[0029] Figure 2 A schematic diagram of point selection, projection, and orientation calculation on an outcrop point cloud model;

[0030] Figure 3 This is a combined transverse and longitudinal cross-section of the folded rock strata;

[0031] Figure 4A flowchart illustrating the geological profile generation method based on SfM-MVS point cloud provided in this embodiment of the invention. Detailed Implementation

[0032] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0033] This invention provides a method for generating geological profiles based on SfM-MVS point clouds, replacing the traditional traverse method and ground-based GPS point coordinate method, thus transforming contact measurement into non-contact measurement. (Refer to...) Figure 1 and Figure 4 The geological profile generation method in this invention is completed through three main steps: image acquisition and 3D modeling, extraction of geospatial data and geological attribute data, and geological profile generation. Specifically, it includes the following steps:

[0034] S1: Select the outcrop object for geological profile measurement, perform image acquisition required by SfM-MVS, and obtain a multi-directional image set of the outcrop to be measured;

[0035] Ensure that the overlap between consecutive images is not less than 60%, and that the remote sensing platform moves to ensure the smooth operation of the SfM algorithm;

[0036] If there is no RTK-GNSS signal in the outcrop area to be measured, a ground control surface is placed in the scene to be photographed, and the dip and tilt angle of the control surface are measured using a compass. The measured dip and tilt angle are then converted into NED coordinates to obtain the true attitude and size parameters of the reference object.

[0037] If there is an RTK-GNSS signal in the outcrop area to be measured, then use an RTK-GNSS UAV to directly capture suitable images, or use an RTK-GNSS base station to deploy ground control points and measure the coordinates of the control points in the outcrop to be measured for attitude and size correction.

[0038] Furthermore, UAV RTK-GNSS signal reception utilizes network location services, while base station RTK-GNSS signal reception only utilizes satellite location services.

[0039] S2: Remove problematic photos, import the remaining image set into point cloud modeling software, and generate sparse and dense point clouds through a fixed process;

[0040] S3: For point clouds with absolute geographic coordinate control, proceed directly to the next step; for point clouds with relative geographic coordinate control, the attitude and size should be corrected using the control surface method. The corrected outcrop point cloud model proceeds to the next step. Note that the point cloud corrected by the control surface method uses a custom coordinate system. Different shooting distances can be set for the measured point cloud to obtain multi-scale point clouds and perform multi-scale fusion. High-density point clouds are mainly targeted at the location of interest.

[0041] S4: Combining the knowledge and experience of geological experts on lithology and structural properties, classify and layer the outcrop point cloud model, mark geological boundary points, and visually mark topographic control points;

[0042] S5: In point cloud data processing software such as Metashape and LiDAR360, extract the 3D coordinates of geological boundary points and terrain control points, assign geological attribute information to the coordinates of geological boundary points, and export the dense point cloud in a point cloud data format with the extension .las.

[0043] S6: Import the 3D point cloud into attitude calculation software (such as CloudCompare), use a virtual compass to determine the attitude of well exposed structural surfaces, or use the three-point method to calculate the attitude of poorly exposed structural surfaces. These attitudes are one of the parameters in the geospatial data.

[0044] S7: Integrate the above spatial data and geological attribute data into a two-dimensional relational data table in Excel, perform projection calculations, and then import the data into mapping software such as MapGIS.

[0045] S8: Use digital mapping software such as MapGIS to generate a profile grid, and further refine and fill it with geological lithology and structural national standard patterns to form a geological profile map.

[0046] In this embodiment, the geological profile map includes a horizontal rock stratum columnar section, an inclined rock stratum cross section, and a combined cross and longitudinal section of folded rock strata. The first two types only require one data mapping process, while the latter requires more than two combined cross section generation processes.

[0047] In this embodiment, the three-dimensional, colored, multi-scale fused SfM-MVS point cloud allows geological experts to identify and locate geological phenomena of interest, such as lithology and structural properties, in step 4, thereby ensuring the coupling and simultaneous extraction of subsequent spatial data and geological attribute data.

[0048] Steps S1 to S3, as follows Figure 1 As shown in step one, outcrop image acquisition and 3D point cloud modeling are performed.

[0049] Steps S4 to S6, as follows Figure 1As shown in step two, geospatial and geological attribute information of the outcrops is extracted, especially the identification and occurrence of various structural planes, and the outcrops are layered, such as... Figure 2 and 3 The lithology and structure of the different strata shown have been determined by observation.

[0050] Step S7, as follows Figure 1 Step 3 and Figure 2 As shown in Figure a, the coordinates of geological points with different elevations and locations in space are projected onto the same horizontal plane.

[0051] Step S7, as follows Figure 1 Step 3 and Figure 2 As shown in c, the coordinates of these non-collinear geological points in space are projected onto a unified baseline, which is determined by connecting the beginning and end of the points.

[0052] Step S7, as follows Figure 1 Step 3 and Figure 2 As shown in d, the coordinates of these geological points with different elevations and locations are used to calculate spatial parameters such as azimuth, slope angle, and horizontal distance between each point through trigonometric functions.

[0053] Step S7, as follows Figure 1 As shown in step three, the spatial parameters such as attitude, azimuth, slope angle, and horizontal distance obtained above are processed and imported into MapGIS software to generate a geological profile grid map containing only topographic profile lines and geological boundaries, as shown in step three. Figure 1 The initial profile shown in step three and Figure 2 c is the cross-sectional grid.

[0054] Step S8, as follows Figure 1 As shown in step three, the cross-sectional grid is filled with patterns according to the national lithology standards to generate a pattern as shown in step three. Figure 1 Step 3 final profile or Figure 3 A geological profile with a grid pattern background.

[0055] This invention is primarily based on 3D point cloud modeling software and data mapping software (such as MapGIS). Examples utilize 3D reconstruction software (such as Agisoft Metashape) and open-source 3D point cloud processing software (such as CloudCompare). First, 3D scene reconstruction is completed using 3D modeling software such as Agisoft Metashape. Then, software such as Metashape and CloudCompare are used to determine geological boundary points and terrain control points, extracting spatial coordinates and attitude. Finally, software such as Excel and MapGIS are used for projection calculations and data mapping.

[0056] This invention achieves the goal of generating geological profile maps using the SfM-MVS outcrop point cloud model and projection conversion formula. This method realizes non-contact measurement, inheriting the advantages of remote sensing—non-contact, macroscopic, comprehensive, and timely—and will greatly improve the quality and efficiency of field geological surveys.

[0057] Compared with existing technologies, the geological profile generation method based on SfM-MVS point clouds provided by this invention has the following significant advantages:

[0058] (I) This invention provides a geological profile generation method based on SfM-MVS point clouds, utilizing the non-contact nature of remote sensing to reduce labor intensity. This method eliminates the need for prior surveyors to travel back and forth to discuss geological survey content, and does not require consideration of the line-of-sight between surveyors. Furthermore, it can combine lithological contact and dip data to accurately measure the thickness of large strata, reducing limitations imposed by human intervention. Because it only requires image data of outcrops, it can be implemented using various camera mounts, including handheld devices, selfie sticks, drones, and vehicle-mounted cameras. This is beneficial for mapping in deeply dissected loess-covered areas, forest-covered areas, and other special regions.

[0059] (ii) This method inherits the advantages of remote sensing in terms of its macroscopic, comprehensive, and systematic nature. Another advantage of this method compared to traditional geological mapping is its ability to extract occurrence data from any part of the model, providing good coverage within the mapped area without any spatial data gaps.

[0060] (III) This method achieves instrumentation and quantification in geological profile mapping. The entire process relies on instrumental data collection, eliminating the need for manual readings and improving accuracy. While field sampling still requires labor, the entire workflow introduces 3D remote sensing technology into outcrop geological profile mapping. This not only overcomes the shortcomings of contact measurement but also transforms visual observation and manual recording into instrumental observation and computer data processing, allowing this work to inherit the advantages of remote sensing, such as non-contact, comprehensive, macroscopic, and timely processing. The use of drones and close-range photography equipment enables profile measurements even in areas inaccessible by humans. This significantly reduces the labor intensity and field hazards for geologists, breaking through the limitations of manual measurement and sampling surveys.

[0061] (iv) This method allows for multiple measurements and optimized mapping. As long as an outcrop can be observed, any outcrop point cloud data volume can be used as a candidate point for profile mapping. Therefore, according to this method, profile measurement actually only requires a single high-density multi-outcrop observation to ultimately select the optimal outcrop for mapping.

[0062] (V) This method achieves an immersive and digitally preserved effect. Because it obtains a three-dimensional outcrop model, it provides an immersive experience, allowing for extensive indoor analysis and repeated access to and sharing of outcrop data without additional fieldwork—a stark contrast to manual profiling methods. Repeatability and reproducibility of field observations are effortless, enabling new observations or testing of previous ones. Measurements can be conducted at multiple scales, from point measurements (similar to a handheld compass) to larger areas. Simultaneously, it provides the ability to quickly and accurately measure irregular or weathered surfaces. The application of this method also provides an invaluable digital preservation of a region at a specific time, as geological outcrops are not permanent in some places. For example, geological outcrops may be covered or removed by civil engineering projects or mining excavations, and recent fault fractures may be erased by weathering or human activity.

[0063] This invention revolutionizes the working method, eliminating the need for traverse lines and various measuring tools to measure slope distances and stratigraphic thickness, and replacing the use of compasses for attitude measurements. Instead, it employs multi-scale photogrammetry applicable to different remote sensing platforms, 3D point cloud modeling, and point cloud geological information extraction. The principle involves developing a set of trigonometric function conversion formulas to extract the spatial and geological attribute data required for geological profile mapping from multi-scale SfM-MVS point cloud data. This method will enable the direct use of consumer-grade cameras, lightweight drones, and personal computers for geological profile mapping, thus inheriting the advantages of remote sensing such as macroscopic scope, timeliness, and non-contact operation. It significantly reduces the intensity of fieldwork, substantially improves the quality and efficiency of outcrop geological work, and lowers the safety risks for field personnel. Most importantly, this method, leveraging remote sensing principles, transforms visual observation into instrumental observation, representing a completely new approach that promises to achieve the instrumentation, digitization, and intelligentization of field geological work.

[0064] The above-disclosed embodiments are merely a few specific examples of the present invention. However, the embodiments of the present invention are not limited thereto, and any variations that can be conceived by those skilled in the art should fall within the protection scope of the present invention.

Claims

1. A method for generating geological profiles based on SfM-MVS point clouds, characterized in that, Includes the following steps: Select the outcrops to be measured in the geological profile, collect images of the outcrops from multiple angles, and form an image set. Import the image set into the point cloud modeling software to generate sparse point clouds and dense point clouds; For point clouds with relative geographic coordinate control, the control surface method is used to perform attitude and size correction to obtain a corrected outcrop point cloud model. The outcrop point cloud model is classified and layered, geological boundary points and topographic control points are marked, the 3D coordinates of geological boundary points and topographic control points are extracted, geological attribute information is assigned to the coordinates of geological boundary points, and the dense point cloud is exported in point cloud data format with the extension .las. Import the exported dense point cloud into the point cloud processing software, use a virtual compass to determine the attitude of the structural surface that has reached the set value, or use the three-point method to calculate the attitude of the structural surface that has not reached the set value. The occurrence data and geological attribute information are integrated into a two-dimensional relational data table in Excel, and after projection calculation, the data is imported into the data mapping software; Digital mapping software is used to generate a cross-sectional grid, which is then further refined and filled with geological lithology and structural national standard patterns to form a geological cross-section map. When acquiring multi-directional images of the exposed object to be tested: If there is no RTK-GNSS signal in the outcrop area to be measured, a ground control surface is placed in the scene to be photographed as a reference surface. The dip and tilt angle of the ground control surface are measured with a compass, and the measured dip and tilt angle are converted into NED coordinates to obtain the true attitude and size parameters of the reference object. If there is an RTK-GNSS signal in the outcrop area to be measured, then use an RTK-GNSS drone to directly take pictures, or use an RTK-GNSS base station to set up ground control points and measure the coordinates of the control points in the outcrop to be measured.

2. The geological profile generation method based on SfM-MVS point cloud as described in claim 1, characterized in that, If there is no RTK-GNSS signal in the outcrop area to be measured, the attitude and size correction of the dense point cloud is performed using the control surface method.

3. The geological profile generation method based on SfM-MVS point cloud as described in claim 1, characterized in that, When acquiring images of the outcrop object from multiple angles, the remote sensing platform moves, and the overlap between consecutive images is not less than 60%.

4. The geological profile generation method based on SfM-MVS point cloud as described in claim 1, characterized in that, Before generating sparse and dense point clouds, images that do not meet the quality requirements are removed based on the image quality estimation function of the point cloud modeling software, and the remaining images are used to generate sparse and dense point clouds.

5. The geological profile generation method based on SfM-MVS point cloud as described in claim 1, characterized in that, For point clouds with absolute geographic coordinate control, sparse point clouds and dense point clouds are directly classified and layered.

6. The geological profile generation method based on SfM-MVS point cloud as described in claim 1, characterized in that, The geological profile includes a horizontal stratum columnar section, an inclined stratum cross section, and a combined horizontal and vertical stratum cross section.

7. The geological profile generation method based on SfM-MVS point cloud as described in claim 6, characterized in that, The horizontal strata columnar section and the inclined strata cross section require one data mapping process, while the folded strata combined transverse and longitudinal cross section requires at least three combined cross section generation processes.

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