CN116819525A - InSAR landslide monitoring and evaluating method and system for high steep side slope - Google Patents

InSAR landslide monitoring and evaluating method and system for high steep side slope Download PDF

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CN116819525A
CN116819525A CN202310571937.3A CN202310571937A CN116819525A CN 116819525 A CN116819525 A CN 116819525A CN 202310571937 A CN202310571937 A CN 202310571937A CN 116819525 A CN116819525 A CN 116819525A
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insar
monitoring
sensitivity index
landslide
slope
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CN116819525B (en
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贺黎明
裴攀科
刘渝
蔡久扬
秦增辉
毛亚纯
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东北大学
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/10—Complex mathematical operations
    • 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
    • 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
    • G01S19/01—Satellite radio beacon positioning systems transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
    • G01S19/13—Receivers
    • G01S19/35—Constructional details or hardware or software details of the signal processing chain
    • G01S19/37—Hardware or software details of the signal processing chain
    • 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
    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
    • G01S7/41—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00 using analysis of echo signal for target characterisation; Target signature; Target cross-section

Abstract

The invention discloses an InSAR landslide monitoring and evaluating method and system for a high steep side slope, and relates to the technical field of landslide monitoring, wherein the method comprises the following steps: according to the topographic information of the target area and the SAR satellite geometric information covering the target area, an InSAR monitoring landslide sensitivity index model is constructed; identifying an InSAR geometric distortion region according to the InSAR monitoring landslide sensitivity index model, and drawing a terrain sensitivity index distribution map of the target region; and constructing InSAR monitoring theory and actual sensitivity index models according to the InSAR monitoring data and the GNSS monitoring data of the target area, and determining the credibility of the InSAR monitoring data according to the InSAR monitoring theory and the actual sensitivity index models. The method realizes the credibility evaluation of the InSAR monitoring result of the high and steep side slope.

Description

InSAR landslide monitoring and evaluating method and system for high steep side slope
Technical Field
The invention relates to the technical field of landslide identification, in particular to an InSAR landslide monitoring and evaluating method and system for a high and steep side slope.
Background
Strip mine landslide is a typical geological disaster caused by mining activities, and the strip mine is developed and utilized with high strength for a long time due to the advantage of easy mining, and along with the continuous increase of excavation depth and slope angle, a plurality of unstable high-steep slopes of the strip mine become important potential safety hazards for landslide event. Once the high and steep side slope slides, huge casualties and environmental damages are easily caused. Therefore, the method is particularly important for identifying, monitoring and early warning landslide of high and steep side slopes of surface mines, the traditional landslide geological investigation method is mainly developed for small-scale single landslide, and has limited capability in identifying and monitoring disaster hidden dangers of the landslide of the high and steep side slopes of the mines, so that the method is difficult to implement in a large scale and high efficiency.
The synthetic aperture interferometry radar (Interferometric Synthetic Aperture Radar, inSAR) is used as a novel space earth observation technology, has the typical characteristics of high-precision, high-resolution and all-weather operation, and is one of the best means for monitoring landslide on a large scale at present. However, this method also has some limitations, such as the unique north-south flight direction of synthetic aperture radar (Synthetic Aperture Radar, SAR) satellites and the observation mode of side-looking radar (InSAR can only measure the projection value of the surface deformation along the Line of Sight (LOS)), which limit the ability of InSAR to detect landslides, especially high steep landslides in mining areas, greatly. Meanwhile, as the SAR satellites are gradually increased, a plurality of orbits cover a target area within the same research time range, and different orbits often have obvious differences on mining area monitoring results due to different sensibilities of the different orbits to large-scale strip mine high-steep slope displacement monitoring. Therefore, in early identification of a large-scale high-steep slope landslide, it is very important to quantitatively evaluate sensitivity and reliability of rising and falling track SAR data in slope displacement monitoring.
The existing time sequence InSAR landslide monitoring reliability evaluation method (CN 113534154B-a SAR line-of-sight deformation and gradient slope sensitivity calculation method) is realized based on the identification of geometric distortion of radar satellites, and has the following two defects: 1. the identification precision of the geometric distortion model of the radar satellite is low and quite wide, the specific numerical value of the credibility cannot be accurately identified, and the monitoring data of a global navigation satellite system (Global Navigation Satellite System, GNSS) is not introduced for credibility evaluation; 2. the InSAR monitoring sensitivity and reliability evaluation effect of the high and steep side slopes of the large-scale mining areas is poor.
Disclosure of Invention
The invention aims to provide an InSAR landslide monitoring and evaluating method and system for a high and steep side slope, which realize the credibility evaluation of the InSAR monitoring result of the high and steep side slope.
In order to achieve the above object, the present invention provides the following solutions:
the invention discloses an InSAR landslide monitoring and evaluating method facing a high steep side slope, which comprises the following steps:
according to the topographic information of the target area and the SAR satellite geometric information covering the target area, an InSAR monitoring landslide sensitivity index model is constructed;
identifying an InSAR geometric distortion region according to the InSAR monitoring landslide sensitivity index model, and drawing a terrain sensitivity index distribution map of the target region;
and constructing InSAR monitoring theory and actual sensitivity index models according to the InSAR monitoring data and the GNSS monitoring data of the target area, and determining the credibility of the InSAR monitoring data according to the InSAR monitoring theory and the actual sensitivity index models.
Optionally, the terrain information includes a slope and a direction of the slope; the SAR satellite geometry information includes satellite incidence angles including an up-track satellite incidence angle and a down-track satellite incidence angle, and satellite heading angles including an up-track satellite heading angle and a down-track satellite heading angle.
Optionally, the InSAR monitoring landslide sensitivity index model is expressed as:
wherein ,represents the topographic sensitivity index in elevated rail conditions, < +.>Represents the topography sensitivity index in derailment conditions, < +.>Represents gradient, alpha represents gradient direction, theta A Represents the incidence angle theta of the orbiting satellite D Representing the incidence angle of the orbital reduction satellite, gamma A Indicating course angle of orbiting satellite, gamma D Representing the heading angle of the down-track satellite.
Optionally, the InSAR monitoring theory and actual sensitivity index model is expressed as:
wherein ,for the theoretically solved GNSS's line of sight projection deformation vector under elevated rail conditions, +.>The deformation vector is projected for the line of sight of the GNSS obtained by theoretical calculation under the rail descending condition; />For the up-track visual line deformation vector obtained from InSAR monitoring data, < + >>For the derailment visual line direction deformation vector obtained from InSAR monitoring data, S Slope For calculating the extracted deformation along the side slope by combining GNSS monitoring data and topographic information, < + >>For slope monitoring of the theoretical sensitivity index of the lifting rail, +.>For slope monitoring derailment theoretical sensibility index +.>For slope monitoring of the actual sensitivity index of the lifting rail, +.>The actual sensitivity index of derailment is monitored for the side slope.
Alternatively, the process may be carried out in a single-stage, and />Expressed as:
S Slope expressed as:
wherein ,is the projection vector of the sight line vector in the north-south direction under the track lifting condition, +.>For lifting the railProjection vector of sight line vector in east-west direction under condition,/->Is the projection vector of the sight line vector in the vertical direction under the track lifting condition, < + >>For the projection vector of the line-of-sight vector in the north-south direction under the derailment condition, +.>For the projection vector of the sight line vector in the east-west direction under the rail descending condition, +.>For the projection vector of the line of sight vector in the vertical direction under the rail lowering condition, +.>Representing east-west ground displacement vector, +.>Representing the north-south ground displacement vector, ++>Represents a vertical ground displacement vector,>represents gradient, and α represents gradient.
The invention also discloses an InSAR landslide monitoring and evaluating system facing the high and steep side slope, which comprises the following steps:
the InSAR monitoring landslide sensitivity index model construction module is used for constructing an InSAR monitoring landslide sensitivity index model according to the terrain information of a target area and SAR satellite geometric information covering the target area;
the InSAR geometric distortion region identification module is used for identifying an InSAR geometric distortion region according to the InSAR monitoring landslide sensitivity index model and drawing a terrain sensitivity index distribution map of the target region;
the InSAR monitoring data credibility determining module is used for constructing an InSAR monitoring theory and actual sensitivity index model according to the InSAR monitoring data and the GNSS monitoring data of the target area, and determining the credibility of the InSAR monitoring data according to the InSAR monitoring theory and the actual sensitivity index model.
The invention also discloses electronic equipment, which comprises a memory and a processor, wherein the memory is used for storing a computer program, and the processor runs the computer program to enable the electronic equipment to execute the InSAR landslide monitoring and evaluating method facing the high and steep slopes.
The invention also discloses a computer readable storage medium which stores a computer program, and the computer program realizes the InSAR landslide monitoring and evaluating method facing the high and steep slopes when being executed by a processor.
According to the specific embodiment provided by the invention, the invention discloses the following technical effects:
according to the invention, GNSS monitoring data are introduced, inSAR monitoring theory and actual sensitivity index model are constructed according to InSAR monitoring data and GNSS monitoring data of a target area, the credibility of the InSAR monitoring data is determined according to the InSAR monitoring theory and the actual sensitivity index model, the credibility evaluation of the InSAR monitoring result of the high-steep slope is realized, and in addition, the invention adopts the InSAR technology to realize the large-scale monitoring of the landslide of the high-steep slope.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions of the prior art, the drawings that are needed in the embodiments will be briefly described below, it being obvious that the drawings in the following description are only some embodiments of the present invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a schematic flow chart of an InSAR landslide monitoring and evaluating method for a steep slope, which is provided by the embodiment of the invention;
FIG. 2 is a schematic diagram of an imaging geometry model of an up-track satellite for a given point of a high steep slope according to an embodiment of the invention;
FIG. 3 is a geometric schematic of SAR imaging provided in an embodiment of the present invention;
fig. 4 is a schematic flow chart of an InSAR landslide monitoring and evaluating method for a steep slope, which is provided by the embodiment of the invention;
FIG. 5 is a graph showing the pattern of the sensitivity index of the high-steep slope terrains of a dumb-kaolin mine area provided by the embodiment of the invention;
fig. 6 is a schematic structural diagram of an InSAR landslide monitoring and evaluating system for a steep slope according to an embodiment of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The invention aims to provide an InSAR landslide monitoring and evaluating method and system for a high and steep side slope, which realize the credibility evaluation of the InSAR monitoring result of the high and steep side slope.
In order that the above-recited objects, features and advantages of the present invention will become more readily apparent, a more particular description of the invention will be rendered by reference to the appended drawings and appended detailed description.
Example 1
As shown in fig. 1, the embodiment provides an InSAR landslide monitoring and evaluating method for a steep slope, which specifically includes the following steps.
Step 101: and constructing an InSAR monitoring landslide sensitivity index model according to the topographic information of the target area and the SAR satellite geometric information covering the target area.
Wherein, in step 101, the topographic information is determined according to the digital elevation model (Digital Elevation Model, DEM) of the target area, the high-precision DEM data of the target area is imported into ArcGIS software, and the surface analysis function in the software space analysis tool is used to calculate the targetSlope of areaAnd a slope direction alpha. After preprocessing the InSAR image provided by the Sentinel-1 satellite, the SAR satellite geometric information can be extracted from the data file.
The topographic information includes gradient and slope direction; the SAR satellite geometry information includes satellite incidence angles including an up-track satellite incidence angle and a down-track satellite incidence angle, and satellite heading angles including an up-track satellite heading angle and a down-track satellite heading angle.
The method for constructing the InSAR monitoring landslide sensitivity index model specifically comprises the following steps:
step 1011: decomposing the side slope vector: the left and right panels in FIG. 2 show the imaging geometry of an up-track satellite for a given point on a high steep slope, whereinIs the slope gradient, alpha is the slope direction, beta is the slope direction vector +.>Vector with line of sight (LOS)>Included angle D between R Is the ground displacement direction. Slope direction vector +.>Is decomposed into north and southEast and west (east and west)>And vertical->The vectors in three directions, the decomposition result is expressed as a matrix:
step 1012: the displacement component of the GNSS along the LOS direction is calculated.
From the geometric diagram of SAR imaging (FIG. 3), the deformation directly observed by InSAR is the deformation of the ground along the line of sight (LOS), namely the sum of displacement vectors of high-steep slopes along the north-south (N), east-west (E) and vertical (U), so that the displacement component of GNSS along the line of sight (LOS) can be obtainedBy means of ground displacement vectors->And ground vertical vector +.>To represent:
upper corner marks a and D represent the calculated satellite flight modes of Ascending and Descending orbits (satellites), respectively, with the angle of incidence θ A The incidence angle of the orbit-reducing satellite is theta D Course angle of the orbit-raising satellite is gamma A Course angle of the orbit-reducing satellite is gamma D Sin is a sine function and cos is a cosine function.
Ground displacement vector under conditions of lifting rail and lowering railThe east-west displacement vector can be used>And a north-south displacement vector->Representation ofThe following are provided:
the displacement component of GNSS along LOS direction under the condition of ascending and descending rail can be obtained by combining the four equation relational expressionsDisplacement vector of the ground along the three directions of north and south, east and west and vertical> and />The relation between them is:
step 1013: construction of a terrain sensitivity index model
From the calculations of steps 1011 and 1012, the topography sensitivity index under the elevated and lowered rail conditions can be derived and />The expression of (2) the slope gradient of a specific section +.>And slope directionAlpha can cause the radar image to be shaded, and when the shade exists in the radar image, the InSAR monitoring result is not credible, so that the corresponding terrain sensitivity index value is 0.
The InSAR monitoring landslide sensitivity index model is expressed as follows:
wherein ,represents the topographic sensitivity index in elevated rail conditions, < +.>Represents the topography sensitivity index in derailment conditions, < +.>Represents gradient, alpha represents gradient direction, theta A Represents the incidence angle theta of the orbiting satellite D Representing the incidence angle of the orbital reduction satellite, gamma A Indicating course angle of orbiting satellite, gamma D Representing the heading angle of the down-track satellite.
Step 102: and identifying an InSAR geometric distortion region according to the InSAR monitoring landslide sensitivity index model, and drawing a terrain sensitivity index distribution map of the target region.
The step 102 specifically includes:
step 1021: and identifying an InSAR geometric distortion region according to the InSAR monitoring landslide sensitivity index model, wherein the identification rule is as follows:
if H terrain Greater than or equal toThe monitoring sensitivity of the InSAR in the area is higher, and the monitoring performance is good; if H terrain At 0 and->Between (I)>The region monitorability is general and belongs to the perspective shortening region; if H terrain Equal to 0 (H) terrain =0), the region is a monitoring blind region, belonging to a shadow region; if H terrain Less than 0 (H) terrain < 0), the region is less monitorable and belongs to the overlap region. Wherein->Is a slope grade.
Step 1022: drawing a target area terrain sensitivity index distribution map, which specifically comprises the following steps: and calculating the SAR image terrain sensitivity index of the target area by using a grid calculator function under a map algebra function set in the ArcGIS software space analysis tool, and then storing the calculation result in a tiff format for drawing.
Step 103: and constructing InSAR monitoring theory and actual sensitivity index models according to the InSAR monitoring data and the GNSS monitoring data of the target area, and determining the credibility of the InSAR monitoring data according to the InSAR monitoring theory and the actual sensitivity index models.
The InSAR monitoring theory and actual sensitivity index model is expressed as follows:
wherein ,for the theoretically solved GNSS's line of sight projection deformation vector under elevated rail conditions, +.>To be solved theoretically toThe deformation vector is projected to the sight line of the GNSS under the rail descending condition; />For the up-track visual line deformation vector obtained from InSAR monitoring data, < + >>For the derailment visual line direction deformation vector obtained from InSAR monitoring data, S Slope For combining GNSS monitoring data and topographic information to calculate the extracted deformation along the side slope direction, ++>For slope monitoring of the theoretical sensitivity index of the lifting rail, +.>For slope monitoring derailment theoretical sensibility index +.>For slope monitoring of the actual sensitivity index of the lifting rail, +.>The actual sensitivity index of derailment is monitored for the side slope.
and SSlope Expressed as:
wherein ,is the projection vector of the sight line vector in the north-south direction under the track lifting condition, +.>Is the projection vector of the sight line vector in the east-west direction under the track lifting condition, < + >>Is the projection vector of the sight line vector in the vertical direction under the track lifting condition, < + >>For the projection vector of the line-of-sight vector in the north-south direction under the derailment condition, +.>For the projection vector of the sight line vector in the east-west direction under the rail descending condition, +.>For the projection vector of the line of sight vector in the vertical direction under the rail lowering condition, +.>Representing east-west ground displacement vector, +.>Representing the north-south ground displacement vector, ++>Represents a vertical ground displacement vector,>represents gradient, and α represents gradient.
Example 2
As shown in fig. 4, the embodiment provides an InSAR landslide monitoring and evaluating method for a steep slope, which specifically includes the following steps.
S1, collecting satellite geometric information, DEM information, inSAR and GNSS monitoring data of a coverage target area Sentinel-1A, and acquiring gradient slope and satellite geometric parameters.
The InSAR monitoring data only has a displacement result in one direction (LOS direction) of the ground, and the GNSS monitoring data has a ground deformation displacement result in three directions (three-dimensional direction) of the ground.
S2, constructing an InSAR monitoring landslide sensitivity index model by combining satellite geometry and terrain information.
S3, identifying an InSAR geometric distortion region according to the sensitivity index, and drawing a terrain sensitivity index distribution map of the target region.
S4, constructing an InSAR monitoring theory and actual sensitivity index model according to the InSAR and GNSS monitoring values, and evaluating the reliability of the InSAR monitoring landslide.
If the reliability of the InSAR monitoring landslide is low, discarding the InSAR monitoring result using the track, and selecting the rest track monitoring results with high reliability.
The step S1 specifically comprises the following steps:
s11, collecting Sentinel satellite data and high-precision DEM data of a coverage target area, and InSAR deformation monitoring result data and GNSS monitoring result data.
S12, calculating gradient and slope direction information of the target area, importing high-precision DEM data of the target area into ArcGIS software, and calculating the gradient of the target area by using a surface analysis function in a software space analysis toolAnd a slope direction alpha.
S13, SAR satellite geometric information including satellite incidence angle theta (wherein the incidence angle of the orbit-raising satellite is theta) can be extracted from the data file by preprocessing SAR images provided by the Sentinel satellite A The incidence angle of the orbit-reducing satellite is theta D ) Satellite heading angle γ (where the orbiting satellite heading angle is γ A Course angle of the orbit-reducing satellite is gamma D )。
The step S2 specifically comprises the following steps:
s21, decomposing the side slope direction vector.
FIG. 2 shows an imaging geometry of an up-track satellite for a given point of a high steep slope, whereinIs the slope gradient, alpha is the slope direction, beta is the slope direction vector +.>Vector with line of sight (LOS)>An included angle between the two. Vector the direction of the side slopeIs decomposed into north and south->East and west (east and west)>And vertical->The vectors in three directions, the decomposition result is expressed as a matrix:
s22, calculating displacement components of the GNSS along the LOS direction.
From the geometric diagrams of SAR imaging (fig. 3 a and b), it can be known that the deformation directly observed by InSAR is the deformation of the ground along the line of sight (LOS), namely the sum of displacement vectors of high-steep slopes along the three directions of north and south (N), east and west (E) and vertical (U), the displacement component of GNSS along the line of sight (LOS) can be obtainedBy means of ground displacement vectors->Vector perpendicular to groundTo represent:
upper corner marks a and D represent the calculated satellite flight modes of Ascending and Descending orbits (satellites), respectively, with the angle of incidence θ A The incidence angle of the orbit-reducing satellite is theta D Course angle of the orbit-raising satellite is gamma A Course angle of the orbit-reducing satellite is gamma D Sin is a sine function and cos is a cosine function.
Ground displacement vector under conditions of lifting rail and lowering railThe east-west displacement vector can be used>And a north-south displacement vector->The expression is as follows:
the displacement component of GNSS along LOS direction under the condition of ascending and descending rail can be obtained by combining the four equation relational expressionsDisplacement vector of the ground along the three directions of north and south, east and west and vertical> and />The relation between them is：
S23, constructing a terrain sensitivity index model
The topographic sensitivity index under the condition of ascending and descending the rail can be obtained according to the calculation results of the steps S21 and S22 and />Is the expression of (1) for the slope gradient of a specific section +.>And the slope direction alpha of the side slope can cause the radar image to be shaded, and when the shade exists in the radar image, the InSAR monitoring result is not credible, so that the corresponding terrain sensitivity index value is 0.
The step S3 specifically comprises the following steps:
s31, according to the topographic sensitivity index H calculated in the step S2 terrain To identify the SAR geometric distortion region, the identification rules are as follows:
if H terrain Greater than or equal toThe monitoring sensitivity of the InSAR in the area is higher, and the monitoring performance is good; if H terrain At 0 and->Between (I)>The region monitorability is general and belongs to the perspective shortening region; if H terrain Equal to 0 (H) terrain =0), the region is a monitoring blind region, belonging to a shadow region; if H terrain Less than 0 (H) terrain < 0), the area is less monitorable and belongs to the overlap area. Wherein->Is a slope grade.
S32, drawing a terrain sensitivity index distribution map of the target area
And calculating the SAR image terrain sensitivity index of the target area by using a grid calculator function under a map algebra function set in the ArcGIS software space analysis tool, and then storing the calculation result in a tiff format for drawing.
Examples: taking the high steep side slope of the dumb baolin strip mine in the city of Anshan of Liaoning as an example, 29 scenery Sentinel-1 (sentry) satellite C wave band radar images (a group of track ascending images and a group of track descending images) are selected, and the selected data information is shown in table 1:
TABLE 1 detailed data parameter Table for high and steep side slopes of dumb Kaolin
And (3) obtaining the gradient and slope information of the high and steep side slope of the dummy strip mine by using the ArcGIS software and using the DEM, wherein the gradient and slope information are named as slope and aspect.
Calculating the terrain sensitivity index in the ascending and descending modes by using the formula in step S23:
opening a grid calculator in ArcGIS software, and inputting the following formula in a dialog box: 0.778 x Sin (3.14159/180 x "slope") +0.610 x Cos (3.14159/180 x "slope")) Sin (3.14159/180 x "aspect") +0.146 x Cos (3.14159/180 x "aspect")) Cos (3.14159/180 x "slope"), and the topographic sensitivity index profile in the ascending track mode is obtained after selecting the output path; the following formula is input: 0.777 x Sin (3.14159/180 x "slope") -0.612 x Cos (3.14159/180 x "slope") -Sin (3.14159/180 x "aspect") +0.147 x Cos (3.14159/180 x "aspect") -Cos (3.14159/180 x "slope"), and the topographic sensitivity index profile in the down-track mode is obtained after the output path is selected.
And identifying the SAR image distortion region based on the sensitivity index distribution map by utilizing the step S31.
And (3) drawing a high and steep slope SAR image distortion region of the dumb kaolin mining area by utilizing the step (S32).
The final results are shown in fig. 5 below: wherein (a) in fig. 5 shows a satellite map of a small scale of a dumb kaolin mine; FIGS. 5 (b) and (c) are slope and direction information obtained from a 12.5 m DEM provided by ALOS satellites, respectively; fig. 5 (d) shows a high-steep side slope SAR image distortion region of a dumb ridge mine of an up-take satellite; fig. 5 (e) shows a dead-space mine high steep slope SAR image distortion region of the orbiting satellite.
The step S4 specifically comprises the following steps:
s41, matrixing the displacement components of the GNSS along the line of sight (LOS).
Based on the displacement component expression of the GNSS along the line of sight (LOS) calculated in the step S22, settingAt this time-> and />Is the projection vector of the line of sight (LOS) vector in the three-dimensional directions of north-south (N), east-west (E) and vertical (U). Thus, the displacement component of GNSS along the line of sight (LOS)And->This can be represented by the following matrix:
upper and lower corner marks a and D represent the calculated radar satellite flight patterns as Ascending and Descending (derating), respectively.
S42, constructing an InSAR monitoring theory and actual sensitivity index model
In order to quantitatively evaluate the credibility of the InSAR deformation monitoring result in the high-steep slope monitoring of the strip mine in the ascending and descending track time sequence, a slope monitoring theoretical sensibility index T is defined GNSS And an actual sensitivity index P GNSS ：
wherein , and />The deformation vectors are respectively projected in the line of sight (LOS) under the conditions of ascending and descending of the rail by the GNSS obtained by theoretical calculation; s is S Slope Is the actual deformation of the slope direction (obtained from GNSS monitoring values), +.> and />The deformation vectors of the ascending track and the descending track vision Line (LOS) obtained from InSAR monitoring results are respectively +.> and />And the theoretical sensitivity indexes of the slope monitoring track lifting and track lowering are respectively shown. /> and />And the actual sensitivity indexes of the slope monitoring lifting rail and the slope lowering rail are respectively shown.
Examples: the method comprises the steps of taking a high-steep side slope of the mountain iron mine in the Anshan city of Liaoning province as a research case, selecting three GNSS monitoring stations (QK 01, QK02 and QK 03) located on the high-steep side slope, respectively calculating the ascending and descending theories and actual sensibility indexes of the three monitoring stations, wherein the calculation results are shown in table 2, and the monitoring results obtained by the descending track data set are more theoretically reliable than the monitoring results obtained by the ascending track data set. Further, the actual sensitivity index calculation of the high and steep slope is carried out by using the real InSAR visual Line (LOS) to deformation monitoring result, so that the derailment monitoring result is obviously better than the derailment monitoring result, and the derailment monitoring result is consistent with the theoretical calculation result, and can obtain the slope sliding quantity of about 40% even under the condition that the high and steep slope of the strip mine slides at a large angle. Therefore, the larger the slope sensitivity index is, the higher the reliability of the monitoring result is, and the highest reliability is achieved by monitoring the high and steep slope of Ji Da mountain iron ore by using the derailment data set.
TABLE 2 calculation of high-steep side slope theory and actual sensitivity index of high-mountain iron ore
The method has the technical effects that the topography sensitivity index can be accurately calculated, the geometric distortion area can be identified, and the problem that the reliability of the InSAR monitoring landslide cannot be evaluated in the traditional method is solved. By combining two research cases, the method provided by the invention can also be used for carrying out sensitivity prediction and credibility evaluation on the 'pain point' high steep slope monitored by the InSAR in the past, and the construction of a sensitivity index model has more reference significance for the identification and monitoring of the landslide of the strip mine, and can be used as reference data for monitoring and early warning of the landslide of the local area slope.
Example 3
As shown in fig. 6, this embodiment provides an InSAR landslide monitoring and evaluating system for a steep slope, including:
the InSAR monitoring landslide sensitivity index model construction module 201 is configured to construct an InSAR monitoring landslide sensitivity index model according to the topographic information of the target area and the geometric information of SAR satellites covering the target area.
The InSAR geometric distortion region identification module 202 is configured to identify an InSAR geometric distortion region according to the InSAR monitoring landslide sensitivity index model, and draw a topography sensitivity index distribution map of the target region.
The InSAR monitoring data credibility determining module 203 is configured to construct an InSAR monitoring theory and actual sensitivity index model according to the InSAR monitoring data and GNSS monitoring data of the target area, and determine the credibility of the InSAR monitoring data according to the InSAR monitoring theory and actual sensitivity index model.
Example 4
The embodiment provides an electronic device, which comprises a memory and a processor, wherein the memory is used for storing a computer program, and the processor runs the computer program to enable the electronic device to execute the InSAR landslide monitoring and evaluating method facing the high steep slope according to the embodiment 1.
The present embodiment also provides a computer-readable storage medium storing a computer program which, when executed by a processor, implements the InSAR landslide monitoring and evaluating method for a steep slope as described in embodiment 1.
In the present specification, each embodiment is described in a progressive manner, and each embodiment is mainly described in a different point from other embodiments, and identical and similar parts between the embodiments are all enough to refer to each other. For the system disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant points refer to the description of the method section.
The principles and embodiments of the present invention have been described herein with reference to specific examples, the description of which is intended only to assist in understanding the methods of the present invention and the core ideas thereof; also, it is within the scope of the present invention to be modified by those of ordinary skill in the art in light of the present teachings. In view of the foregoing, this description should not be construed as limiting the invention.

Claims (8)

1. An InSAR landslide monitoring and evaluating method for a high steep side slope is characterized by comprising the following steps:
according to the topographic information of the target area and the SAR satellite geometric information covering the target area, an InSAR monitoring landslide sensitivity index model is constructed;
identifying an InSAR geometric distortion region according to the InSAR monitoring landslide sensitivity index model, and drawing a terrain sensitivity index distribution map of the target region;
and constructing InSAR monitoring theory and actual sensitivity index models according to the InSAR monitoring data and the GNSS monitoring data of the target area, and determining the credibility of the InSAR monitoring data according to the InSAR monitoring theory and the actual sensitivity index models.
2. The method for monitoring and evaluating the InSAR landslide facing a steep slope according to claim 1, wherein the terrain information comprises a gradient and a slope direction; the SAR satellite geometry information includes satellite incidence angles including an up-track satellite incidence angle and a down-track satellite incidence angle, and satellite heading angles including an up-track satellite heading angle and a down-track satellite heading angle.
3. The method for monitoring and evaluating the InSAR landslide facing the high and steep slope according to claim 2, wherein the InSAR monitoring landslide sensitivity index model is expressed as:
wherein ,represents the topographic sensitivity index in elevated rail conditions, < +.>Represents the topography sensitivity index in derailment conditions, < +.>Represents gradient, alpha represents gradient direction, theta A Represents the incidence angle theta of the orbiting satellite D Representing the incidence angle of the orbital reduction satellite, gamma A Indicating course angle of orbiting satellite, gamma D Representing the heading angle of the down-track satellite.
4. The method for monitoring and evaluating the InSAR landslide facing the high and steep slope according to claim 1, wherein the InSAR monitoring theory and actual sensitivity index model is expressed as:
wherein ,for the theoretically solved GNSS's line of sight projection deformation vector under elevated rail conditions, +.>The deformation vector is projected for the line of sight of the GNSS obtained by theoretical calculation under the rail descending condition; />For the up-track visual line deformation vector obtained from InSAR monitoring data, < + >>For the derailment visual line direction deformation vector obtained from InSAR monitoring data, S Slope For calculating the deformation along the side slope by combining GNSS monitoring data and topographic information>For slope monitoring of the theoretical sensitivity index of the lifting rail, +.>For slope monitoring derailment theoretical sensibility index +.>For slope monitoring of the actual sensitivity index of the lifting rail, +.>The actual sensitivity index of derailment is monitored for the side slope.
5. The InSAR landslide monitoring and evaluating method for high and steep slopes as set forth in claim 4, wherein,andexpressed as:
S Slope expressed as:
wherein ,is the projection vector of the sight line vector in the north-south direction under the track lifting condition, +.>Is the projection vector of the sight line vector in the east-west direction under the track lifting condition, < + >>Is a projection vector of a sight line vector in a vertical direction under the track lifting condition,for the projection vector of the line-of-sight vector in the north-south direction under the derailment condition, +.>For the projection vector of the sight line vector in the east-west direction under the rail descending condition, +.>For the projection vector of the line of sight vector in the vertical direction under the rail lowering condition, +.>Representing east-west ground displacement vector, +.>Representing the north-south ground displacement vector, ++>Represents a vertical ground displacement vector,>represents gradient, and α represents gradient.
6. An InSAR landslide monitoring and evaluating system for a high steep side slope is characterized by comprising:
the InSAR monitoring landslide sensitivity index model construction module is used for constructing an InSAR monitoring landslide sensitivity index model according to the terrain information of a target area and SAR satellite geometric information covering the target area;
the InSAR geometric distortion region identification module is used for identifying an InSAR geometric distortion region according to the InSAR monitoring landslide sensitivity index model and drawing a terrain sensitivity index distribution map of the target region;
the InSAR monitoring data credibility determining module is used for constructing an InSAR monitoring theory and actual sensitivity index model according to the InSAR monitoring data and the GNSS monitoring data of the target area, and determining the credibility of the InSAR monitoring data according to the InSAR monitoring theory and the actual sensitivity index model.
7. An electronic device comprising a memory for storing a computer program and a processor that runs the computer program to cause the electronic device to perform the high and steep slope-oriented InSAR landslide monitoring evaluation method according to any one of claims 1 to 5.
8. A computer-readable storage medium, characterized in that it stores a computer program which, when executed by a processor, implements the InSAR landslide monitoring and evaluation method for steep slopes according to any one of claims 1 to 5.
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Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN106250667A (en) * 2016-06-29 2016-12-21 中国地质大学（武汉） The monitoring method of a kind of landslide transition between states of paddling and device
CN112288308A (en) * 2020-11-11 2021-01-29 华能澜沧江水电股份有限公司 DS evidence theory landslide evaluation method based on multiple coefficient of variation weighting
CN112540369A (en) * 2020-11-27 2021-03-23 武汉大学 Landslide three-dimensional deformation resolving method and system integrating GNSS and lifting rail time sequence InSAR
CN114201922A (en) * 2021-12-22 2022-03-18 云南大学 Dynamic landslide sensitivity prediction method and system based on InSAR technology
KR102387940B1 (en) * 2020-11-17 2022-04-18 이화여자대학교 산학협력단 Landslide prediction apparatus and method to undestand the geo-environmental characteristics related to landslide
CN115935640A (en) * 2022-12-02 2023-04-07 国家基础地理信息中心 Landslide sensitivity prediction model establishment method and landslide sensitivity evaluation method

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN106250667A (en) * 2016-06-29 2016-12-21 中国地质大学（武汉） The monitoring method of a kind of landslide transition between states of paddling and device
CN112288308A (en) * 2020-11-11 2021-01-29 华能澜沧江水电股份有限公司 DS evidence theory landslide evaluation method based on multiple coefficient of variation weighting
KR102387940B1 (en) * 2020-11-17 2022-04-18 이화여자대학교 산학협력단 Landslide prediction apparatus and method to undestand the geo-environmental characteristics related to landslide
CN112540369A (en) * 2020-11-27 2021-03-23 武汉大学 Landslide three-dimensional deformation resolving method and system integrating GNSS and lifting rail time sequence InSAR
CN114201922A (en) * 2021-12-22 2022-03-18 云南大学 Dynamic landslide sensitivity prediction method and system based on InSAR technology
CN115935640A (en) * 2022-12-02 2023-04-07 国家基础地理信息中心 Landslide sensitivity prediction model establishment method and landslide sensitivity evaluation method

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