CN115166800A

CN115166800A - Landslide monitoring data processing method combining GNSS and three-dimensional laser scanning

Info

Publication number: CN115166800A
Application number: CN202210629510.XA
Authority: CN
Inventors: 韩冬卿; 杨舒涵; 苏丽娜; 朱斌; 周彤; 王德军; 杨景丽; 冯琦; 张亚林
Original assignee: Hebei University of Technology
Current assignee: Zhongdian Jianjijiao Expressway Investment Development Co ltd; Hebei University of Technology
Priority date: 2022-06-01
Filing date: 2022-06-01
Publication date: 2022-10-11

Abstract

The invention discloses a method for processing landslide monitoring data by combining GNSS and three-dimensional laser scanning, which specifically comprises the following steps: s1, a GNSS continuity monitoring station is arranged to keep all-weather monitoring on a landslide body; s2, a GNSS periodic monitoring station is arranged to periodically monitor the landslide body; s3, resolving coordinates of the GNSS reference point and the monitoring point; s4, distributing a three-dimensional laser scanner to scan the whole landslide body to obtain point cloud data; s5, extracting and processing point cloud feature points of the enforcement area; and S6, comparing and analyzing the GNSS and three-dimensional laser scanning point cloud data accuracy, and proving the reliability of the monitoring data. The method can accurately monitor the landslide body and provide a more comprehensive data base for deformation analysis by combining the GNSS and the three-dimensional laser scanning technology, and improves the economy of measurement operation and the comprehensiveness and reliability of measurement data.

Description

Landslide monitoring data processing method combining GNSS and three-dimensional laser scanning

Technical Field

The invention relates to the technical field of surveying and mapping science, in particular to a landslide monitoring data processing method combining GNSS and three-dimensional laser scanning technology.

Background

China is a country with a large area and a complex geological environment, geological disasters frequently occur, landslide is one of the most frequent geological disasters, and once the landslide occurs, heavy casualties and huge economic losses are often caused. Therefore, long-term monitoring and early warning of potential landslide areas are necessary.

At present, the landslide mass monitoring technology can be divided into a traditional landslide mass monitoring technology and an intelligent landslide mass monitoring technology. The traditional landslide monitoring technology mainly depends on equipment such as a total station and the like to carry out on-site survey; the intelligent landslide mass monitoring technology mainly comprises the following steps: optical fiber sensing technology, digital close-range photogrammetry technology, three-dimensional laser scanning technology and Global Navigation Satellite System (GNSS) monitoring technology.

The primary objective of deformation monitoring of the landslide body is to acquire timely and accurate deformation data, and then the data information needs to be researched and analyzed to find the inherent law, the deformation mechanism and the external influence of landslide deformation, so that the aim of early warning of landslide deformation influence is finally achieved. However, to accurately predict landslide monitoring in time, the monitoring technology is required to not only realize high-precision data acquisition but also achieve real-time monitoring. The GNSS technology is a technology capable of realizing high-precision, all-weather and automatic monitoring, and is very suitable for geological disaster monitoring. However, the GNSS technology can only carry out high-precision single-point measurement, and a large number of monitoring points are usually needed to obtain the whole deformation information of the landslide body to realize effective deformation analysis of the landslide body, so that the cost is high and unnecessary resource waste is caused by arrangement of a large number of monitoring points, and the single use of the GNSS technology for monitoring the landslide body has no economy and environmental protection.

Disclosure of Invention

The invention aims to provide a landslide monitoring data processing method combining GNSS and three-dimensional laser scanning, which can be used for monitoring the integral deformation of a landslide body and simultaneously ensuring the accuracy and reliability of monitoring data.

In order to achieve the purpose, the technical scheme adopted by the invention is as follows:

a landslide monitoring data processing method combining GNSS and three-dimensional laser scanning comprises the following steps:

s1, a GNSS continuity monitoring station is arranged to keep all-weather monitoring on a landslide body;

s2, arranging a GNSS periodic monitoring station, and periodically monitoring the landslide body;

s3, resolving coordinates of the GNSS reference point and the monitoring point;

s4, distributing a three-dimensional laser scanner to scan the whole landslide body to obtain point cloud data;

s5, extracting and processing point cloud feature points of the enforcement area;

and S6, comparing and analyzing the GNSS and three-dimensional laser scanning point cloud data accuracy, and proving the reliability of the monitoring data.

Preferably, the GNSS continuous monitoring station in S1 includes: the GNSS continuous monitoring station collects data of the landslide body for a long time, the monitoring is continuous, the time resolution is high, the key parts and the key parts are selected to be provided with permanent GNSS observation stations, and uninterrupted observation is carried out on the stations.

Preferably, the S2 GNSS periodic monitoring station includes: the GNSS periodic station regularly monitors the landslide mass in a static measurement mode, the deformation condition of the landslide mass is analyzed through the change of the position of the monitoring point in each period, and the monitoring period can be determined according to the characteristics and the hazard degree of the landslide mass.

Preferably, the S3 includes: the reference point and the monitoring points form a GNSS control network, the coordinates of the reference point are known, and the coordinates of the monitoring points can be calculated according to the space geometric relationship;

preferably, in S3, the reference points include: evenly distributed in whole monitoring area, lay in the external stable and open view department of ground of landslide, follow the nearest principle of distance monitoring point simultaneously, detect its stability when follow-up every phase is exerted.

Preferably, the S4 includes: the three-dimensional laser scanners monitor the deformation of the landslide body through the acquired three-dimensional point cloud data, the three-dimensional laser scanners are erected at the stable position of the foundation of the opposite surface of the landslide body, the condition of looking through the landslide body is guaranteed to be good, data are collected as much as possible, the point cloud data acquired by the three-dimensional laser scanners are spliced through targets, and the space point location information of the whole landslide body is obtained.

Preferably, the S5 includes: in order to ensure that the same points are monitored in each period, feature points in a measuring area need to be extracted, a point cloud scanned on a GNSS permanent observation pier by using a three-dimensional laser scanner is used for fitting a circle center (point cloud fitting circle center) of the point cloud to be used as the feature points, and the landslide body deformation is judged according to the positions of the feature points in each period.

Preferably, in S5, the point cloud fitting circle center includes:

the GNSS continuity monitoring point is a permanent GNSS observation pillar, the outer surface of the permanent GNSS observation pillar is a cylinder, the upper side part of the upright post is a GNSS radome, the horizontal tangent plane of the permanent GNSS observation pillar is a circle, a plurality of discrete points obtained by taking specific heights as the tangent plane are fitted at the GNSS radome by adopting a least square algorithm to obtain the circle center and the radius of the discrete points;

under the condition of considering the quantity and quality of point clouds of tangent planes, a plurality of tangent planes can be made according to the height of the antenna housing and a certain distance, circle center coordinates with different heights are obtained through fitting, errors in the circle center coordinates at different heights are fitted according to the adjustment, further weighting processing is carried out, and high-precision circle center coordinates are obtained.

Preferably, the S6 includes: firstly, comparing the spatial distance difference and the height difference of data acquired by different three-dimensional laser scanners from monitoring points, inspecting the internal fitting precision of three-dimensional laser scanning, further comparing the spatial distance difference and the height difference of the data acquired by the GNSS, and comparing the precision of the data acquired by different modes.

Compared with the prior art, the invention has the beneficial effects that: on one hand, the accuracy of data acquired by the GNSS technology can reach millimeter level, but the GNSS is a single-point measurement which is not beneficial to monitoring large-area targets such as a landslide body, the three-dimensional laser scanning technology can be used for integrally monitoring the large-area monitored targets, the overall change trend of the landslide body can be better mastered, and the two monitoring technologies are combined, so that the accurate monitoring of the landslide body can be realized at low cost and high efficiency, the overall deformation information of the landslide body can also be mastered, the monitoring data can be better analyzed, and disaster early warning can be carried out; on the other hand, the precision of data acquisition through the GNSS and the three-dimensional laser scanner is attached, the precision and the reliability of the data monitored in each period can be ensured, and a more reliable data basis is provided for the subsequent comparative analysis of the deformation data of the landslide body in each period.

Drawings

FIG. 1 is a flow chart of a method for processing landslide monitoring data by combining GNSS and three-dimensional laser scanning according to the present invention;

FIG. 2 is a plot of the point locations;

FIG. 3 is a GNSS control network diagram;

FIG. 4 is a point cloud fitting circle diagram;

wherein, p001, p 002-GNSS continuity monitoring station; c001, c 002-periodic monitoring station; c003, c004 — reference station; s001, s 002-three-dimensional laser scanner.

Detailed Description

The technical solution of the present invention is further described below with reference to the following detailed description and the accompanying drawings, but the scope of the present invention is not limited thereto.

The invention provides a landslide monitoring data processing method combining GNSS and three-dimensional laser scanning, wherein point distribution of each instrument, monitoring point and datum point is shown in figure 1, and the method comprises the following steps:

s1: two GNSS continuity monitoring stations (p 001, p 002) are arranged to keep all-weather monitoring on the landslide body;

specifically, a permanent GNSS observation pier is arranged at a key position of the landslide body with potential safety hazard according to the terrain condition of the landslide body, and the landslide body is continuously observed.

S2: two periodic monitoring points (c 001, c 002) are arranged to regularly monitor the landslide body;

specifically, two periodic monitoring points are arranged at the position where the potential safety hazard exists, GNSS receivers are placed at the positions of the periodic monitoring points, and a static measurement mode is adopted to periodically monitor the landslide body.

S3: calculating the coordinates of the GNSS monitoring points by utilizing a GNSS monitoring control network formed by the reference points (c 003 and c 004) and the monitoring points (c 001 and c 002);

the two datum points (c 003 and c 004) are uniformly distributed in the whole monitoring area, are distributed at the stable and wide visual field position of the foundation outside the landslide body, and follow the principle of being closest to the monitoring point, and the stability of the landslide body is detected in the follow-up each-stage application process;

specifically, a space rectangular coordinate of the reference point c003 under the CGCS2000 is solved by using a precision single-point positioning (PPP) resolving mode through China survey on-line resolving software, the result is shown in table 1, the coordinate system of the control network is subjected to joint measurement with the CGCS2000 through the position of the c003, and the subsequent monitoring analysis adopts positioning relative to the reference point;

TABLE 1 fiducial c003 three-dimensional space rectangular coordinates/m

Roll call

Coordinate frame

Reference epoch

X

Y

Z

StdX

StdY

StdZ

c003

CGCS2000

2000

-2081166.2152

4675456.3983

3794568.3749

0.0152

0.0237

0.015

Fixing the coordinate of the reference point c003, resolving the coordinate of the reference point c004 under the CGCS2000 by adopting a relative positioning mode through long-time static observation, and obtaining the relative positioning precision of 0.2mm as shown in Table 2;

TABLE 2 fiducial c004 three-dimensional space rectangular coordinates/m

Roll call

Coordinate frame

Reference epoch

X

Y

Z

Plane accuracy

Elevation accuracy

c004

CGCS2000

2000

-2081172.3523

4675359.3312

3794678.8188

0.0001

0.0002

Adopting a CGCS2000 reference ellipsoid to perform Gaussian projection on the spatial rectangular coordinates of the two reference points (c 003 and c 004) to obtain a plane rectangular coordinate and a geodetic height, wherein the result is shown in Table 3;

TABLE 3 Gaussian plane rectangular coordinate and geodetic height/m of reference point

Roll call	x	y	h	B	L
						c003	4067930.9415	500007.1083	493.5167	036°44′22.493906″N	113°59′42.286492″E
c004	4068071.0025	500052.1889	490.5199	036°44′27.037179″N	113°59′44.103452″E

In the HGO software, the two periodic monitor points (c 001, c 002) and the two reference points (c 003, c 004) form two synchronous observation rings, and as shown in fig. 2, the coordinates of the periodic monitor points (c 001, c 002) are resolved by the fixed reference points (c 003, c 004), and the results are shown in table 4.

TABLE 4 Gaussian plane rectangular coordinates and geodetic height/m of monitoring points

Roll call	x	y	h	Error in x (mm)	y middle error _ E (mm)	h error _ U (mm)
							c001	4068010.4399	499977.8055	504.8849	1.2	0.8	1.2
c002	4068035.9565	499984.6807	504.6125	0.8	0.6	1.2

S4: erecting two three-dimensional laser scanners (S001 and S002) at the stable position of the foundation on the opposite surface of the landslide body, scanning the landslide body by the two three-dimensional laser scanners to obtain point cloud data of a monitoring target, transmitting the point cloud data between the two three-dimensional laser scanners into Cyclone software, and performing coordinate conversion on the data of the two scanners by taking c001 and c002 as same-name targets to complete splicing.

S5: in order to ensure that the same points are monitored in each period, feature points in a measuring area need to be extracted, the two distributed continuous GNSS monitoring points (p 001 and p 002) are permanent GNSS observation piers, the outer surface of each permanent GNSS monitoring point is a cylinder, the upper side part of each vertical column is provided with a GNSS antenna housing, the horizontal section of each vertical column is a circle, point cloud scanned on the observation piers by a three-dimensional laser scanner is utilized, and the center of the circle is fitted by adopting a least square algorithm to be used as the feature points;

specifically, at the p001 radome, with a cut surface of h =507.000m and a slice thickness of 2mm, 22 discrete points are obtained, and as shown in fig. 3, fitting is performed using a least squares algorithm such that f = ∑ (((x) = s = _i -x _c ) ² +(y _i -y _c ) ² -R ² ) ² Obtaining the circle center and the radius of the circle with minimum, wherein dy and dx are deviation values of discrete points and the circumference in Y and X directions as shown in Table 5;

table 5 p001 continuous monitoring station radome slice point cloud fitting circle (h =507.000 m)

The height of the radome is about 21cm, under the condition of considering the point cloud number and quality of tangent planes, 6 tangent planes are made according to the distance of 2.5cm, the information of the circle obtained by fitting is shown in table 6, the maximum difference of the circle center can be seen to be 9mm in the y direction and 1mm in the x direction, under the condition of ensuring the consistency of the centers of the radomes, the difference can be mainly caused by accidental errors of observation, and further weighting treatment is carried out subsequently according to errors in the circle center coordinates at different elevations during adjustment fitting so as to obtain the high-precision circle center coordinates;

TABLE 6 p001 continuous monitoring station antenna housing slice point cloud fitting circles/m at different heights

Similarly, the radome at the p002 monitoring station has 7 tangent planes at intervals of 2.5cm, the circle information obtained by fitting is shown in table 7, the maximum difference between the circle centers of different tangent planes is 8mm in the y direction, and the maximum difference is 2mm in the x direction.

TABLE 7 p002 continuous monitoring station radome section point cloud fitting circles/m at different heights

S6: comparing and analyzing the GNSS and three-dimensional laser scanning point cloud data accuracy, and proving the reliability of the monitoring data;

specifically, when the accuracy of data of two different acquisition modes is compared, periodic monitoring points (c 001 and c 002) are aimed at, and the GNSS continuity monitoring station can continuously monitor the landslide body for a long time, but the monitoring accuracy is inferior to the periodic monitoring;

specifically, the spatial distance difference and the height difference of the coordinates of the monitoring points acquired by two different scanning stations (s 001 and s 002) are compared, so as to examine the internal attachment accuracy of the three-dimensional laser scanning, and then the spatial distance difference and the height difference of the three-dimensional laser scanning are compared with the spatial distance difference and the height difference of the GNSS acquired data, as shown in table 8, as can be seen from table 8, the spatial distance difference between the different scanning stations is 4mm, the height difference is 2mm, which indicates that the internal attachment accuracy of the three-dimensional laser scanning is higher, the spatial distance difference with the GNSS is 2mm, and the height difference is 2mm, which indicates that the accuracy with the GNSS is basically consistent, and certainly, the internal attachment accuracy is attenuated with the increase of the scanning distance, and further checking needs to be performed in the subsequent measurement.

TABLE 8 precision comparison/m for different acquisition modes

It should be emphasized that the described embodiments of the present invention are illustrative rather than restrictive, and thus the present invention includes embodiments that are not limited to the embodiments described in the detailed description, and that other embodiments derived from the technical solutions of the present invention by those skilled in the art are also within the scope of the claims of the present application. The invention is applicable to the prior art where nothing is said.

Claims

1. A landslide monitoring data processing method combining GNSS and three-dimensional laser scanning is characterized by comprising the following steps:

s3, resolving coordinates of the GNSS reference point and the monitoring point;

and S6, comparing and analyzing the GNSS and three-dimensional laser scanning point cloud data accuracy, and demonstrating the reliability of the monitoring data.

2. The method for processing landslide monitoring data combining GNSS and three-dimensional laser scanning as claimed in claim 1, wherein the S1 specifically comprises GNSS continuity monitoring stations performing long-time data collection on a landslide body, selecting key points and key parts to lay permanent GNSS observation stations, and performing uninterrupted observation on these stations.

3. The method as claimed in claim 1, wherein the step S2 includes the step of periodically monitoring the landslide body by the GNSS periodic station in a static measurement manner, analyzing deformation of the landslide body according to changes in positions of the monitoring points at each period, and determining the monitoring period according to characteristics and hazard of the landslide body.

4. The method for processing landslide monitoring data combining GNSS and three-dimensional laser scanning as claimed in claim 1, wherein S3 specifically comprises forming a GNSS control network by the reference point and the monitoring point, wherein coordinates of the reference point are known, and coordinates of the monitoring point can be calculated according to a spatial geometric relationship.

5. The method of claim 4, wherein the reference points are distributed uniformly throughout the monitoring area and distributed at locations outside the landslide body where the ground is stable and the field of view is wide, and the stability of the landslide is detected during each application period.

6. The landslide monitoring data processing method combining GNSS and three-dimensional laser scanning as claimed in claim 1, wherein S4 specifically comprises the steps that the three-dimensional laser scanners perform landslide body deformation monitoring through the acquired three-dimensional point cloud data, the positions are erected at the stable positions of foundations on opposite surfaces of the landslide body, and the point cloud data acquired by the three-dimensional laser scanners are spliced through targets to obtain the space point location information of the whole landslide body.

7. The method for processing landslide monitoring data combining GNSS and three-dimensional laser scanning as claimed in claim 1, wherein S5 specifically comprises extracting feature points in a measured area, fitting a point cloud scanned on a GNSS permanent observation pier by using a three-dimensional laser scanner to obtain a point cloud fitting circle center as a feature point, and judging landslide body deformation according to the position of each stage of feature point.

8. The method of claim 7, wherein fitting a circle center to the point cloud comprises:

the GNSS continuity monitoring points are permanent GNSS observation piers, the outer surface of each GNSS continuity monitoring point is a cylinder, the upper side part of each upright post is provided with a GNSS radome, the horizontal tangent plane of each GNSS radome is a circle, a plurality of discrete points obtained by taking specific heights as the tangent planes are fitted at the GNSS radomes by adopting a least square algorithm to obtain the circle centers and the radiuses of the discrete points;

and (3) making a plurality of tangent planes according to the height of the antenna housing at certain intervals, fitting to obtain circle center coordinates at different heights, fitting errors in the circle center coordinates at different heights according to the adjustment, and performing further weighting processing to obtain high-precision circle center coordinates.

9. The method for processing landslide monitoring data combining GNSS and three-dimensional laser scanning as claimed in claim 1, wherein the step S6 comprises comparing spatial distance differences and height differences of data acquired by different three-dimensional laser scanners at monitoring points, and examining internal coherent accuracy of three-dimensional laser scanning, and further comparing the spatial distance differences and height differences of data acquired by GNSS to compare accuracy of data acquired by different methods.