CN114187521B - Boundary identification and extraction method for loess filling settlement area - Google Patents

Boundary identification and extraction method for loess filling settlement area Download PDF

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CN114187521B
CN114187521B CN202111540024.2A CN202111540024A CN114187521B CN 114187521 B CN114187521 B CN 114187521B CN 202111540024 A CN202111540024 A CN 202111540024A CN 114187521 B CN114187521 B CN 114187521B
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张瑞
廖明杰
谢凌霄
李松
余斌
王晓文
李涛
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Southwest Jiaotong University
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Abstract

The invention discloses a boundary identification and extraction method facing a loess filling settlement area, which comprises the following steps: acquiring uneven ground surface settlement data of a loess filling area within an image coverage range; establishing a ground settlement point database; counting settlement observation points with the same or similar settlement rates in each settlement area, and connecting all the equivalence points in different areas to form an isoline; setting a settlement rate and an accumulated settlement threshold, regarding settlement points larger than a certain threshold as settlement points in the soil filling area, and regarding contour lines formed by the corresponding settlement points as the boundary of the soil filling area in the area. This application carries out classification management to the settlement funnel through establishing the settlement observation point database in settlement zone, has formed the discernment extraction technology system on a complete loess fill settlement zone boundary, is showing the discernment extraction ability that has improved loess fill settlement zone boundary, can carry out scientific effectual prevention and cure to fill the soil settlement zone, and in time the discovery is bad, reduces resident and architectural loss.

Description

Boundary identification and extraction method for loess filling settlement area
Technical Field
The invention relates to the technical field of plateau surface deformation monitoring and boundary identification of loess filled areas, in particular to a boundary identification and extraction method for loess filled settlement areas.
Background
With the rapid expansion of modern cities, many cities on loess plateau solve the problem of urban land shortage by cutting mountains and filling ditches. In recent years, in order to effectively solve the problem that urban population is rapidly expanded but urban land is in short supply, many cities on the loess plateau in China adopt a mountain cutting and ditch filling mode to increase urban land, such as Yanan, lanzhou and the like. Because newly-built city is located fill regional top basically, the loess foundation is weak, can inevitably take place the condition such as loess collapsible, and then appear serious ground settlement problem, especially there is great potential safety hazard in uneven ground settlement. Therefore, in order to guarantee the safety of newly-built buildings and residents and ensure the stability of the ground, it is necessary to identify, extract and scientifically manage and plan the boundary information of the loess soil filling area in time.
At present, boundary identification methods of filled and subsided areas mainly comprise a point target-based Global Positioning System (GPS) method and a traditional population exploration method. The traditional method needs a large amount of manpower and material resources, is time-consuming and labor-consuming, and has obvious defects particularly for areas with large areas and complex terrains.
Therefore, it is necessary to develop a boundary identification and extraction method for a loess-filled settlement area to solve the above problems.
Disclosure of Invention
The invention aims to solve the problems and designs a boundary identification and extraction method facing a loess filling settlement area.
The invention realizes the purpose through the following technical scheme:
a boundary identification and extraction method facing a loess filling settlement area comprises the following steps:
s1, acquiring original SAR image data and preprocessing the data, and acquiring surface differential settlement data of a loess soil filling area in an image coverage range by using a time series InSAR technology;
s2, dividing the settlement area into m areas according to the obtained ground settlement space distribution result, wherein m is the number of the settlement funnels; then, deriving a basic attribute table of the settlement points of the settlement area according to the divided areas, establishing a ground settlement point database according to the basic attribute table, and performing classified management on the settlement area;
s3, on the basis of a foundation surface deformation database of the filled soil settlement area, counting settlement observation points with the same or similar settlement rate in each settlement area, and connecting all equivalence points in different areas to form an equivalence line;
s4, setting a settlement rate and an accumulated settlement threshold, regarding settlement points larger than a certain threshold as settlement points in the soil filling area, and regarding the contour lines formed by the corresponding settlement points as the boundary of the soil filling area in the area.
Specifically, step S1 includes:
in the image preprocessing stage, firstly, external precise orbit data are utilized to finish orbit correction; secondly, after the main image is selected, the terrain correction is completed by using external digital elevation model data; and registering the secondary image to the geometry of the primary image, and generating an interference pattern through interference.
Further, step S1 further includes:
the loess filling area ground settlement distribution condition in the image coverage range is obtained: firstly, setting a space-time baseline threshold, forming an interference pair baseline network by an interference pattern obtained by preprocessing, and then setting a space-time coherence threshold to screen a coherent point target so as to remove points with poor coherence; and finally, obtaining an interference phase time sequence result through phase unwrapping, and obtaining corresponding settlement result information in the research area through network inversion.
Preferably, the basic attribute table includes a deformation rate table and an accumulated deformation table; the deformation rate table comprises coordinates of the settlement observation points and corresponding deformation rate information; the accumulated deformation table comprises the coordinates of the settlement observation points and accumulated deformation information of each time period in the SAR image time sequence.
Specifically, the settlement observation point of each time segment is given a unique ID for storage.
The invention has the beneficial effects that:
the method comprises the steps of establishing a settlement observation point database of a settlement area, and carrying out classification management on settlement funnels to form a complete loess filling settlement area boundary identification and extraction technology system; manpower and materials, the time that this application drops into are showing and are being less than prior art, and actual maneuverability is strong, are showing the discernment extraction ability that has improved loess fill settlement zone boundary, can carry out scientific and effective prevention and cure to fill settlement zone, and in time the discovery problem reduces resident and building loss.
Drawings
FIG. 1 is a block flow diagram of the present application;
FIG. 2 is the average deformation rate over the study time in the examples of the present application;
FIG. 3 is a diagram of a basic ground settlement database in an embodiment of the present application;
FIG. 4 is a schematic diagram illustrating the boundary recognition and extraction results of the filled soil settlement region in the embodiment of the present application;
FIG. 5 is a graph of discrimination comparison verification of optical history images.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention. It is to be understood that the embodiments described are only a few embodiments of the present invention, and not all embodiments. The components of embodiments of the present invention generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations.
Thus, the following detailed description of the embodiments of the present invention, presented in the figures, is not intended to limit the scope of the invention, as claimed, but is merely representative of selected embodiments of the invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, it need not be further defined and explained in subsequent figures.
In the description of the present invention, it is to be understood that the terms "upper", "lower", "inner", "outer", "left", "right", and the like indicate orientations or positional relationships based on orientations or positional relationships shown in the drawings, or orientations or positional relationships conventionally placed when the product of the present invention is used, or orientations or positional relationships conventionally understood by those skilled in the art, which are merely for convenience of description and simplification of description, and do not indicate or imply that the device or element referred to must have a particular orientation, be constructed and operated in a particular orientation, and therefore, should not be construed as limiting the present invention.
Furthermore, the terms "first," "second," and the like are used solely to distinguish one from another, and are not to be construed as indicating or implying relative importance.
In the description of the present invention, it is also to be noted that, unless otherwise explicitly stated or limited, the terms "disposed" and "connected" are to be interpreted broadly, and for example, "connected" may be a fixed connection, a detachable connection, or an integral connection; can be mechanically or electrically connected; the connection may be direct or indirect via an intermediate medium, and may be a communication between the two elements. The specific meanings of the above terms in the present invention can be understood according to specific situations by those of ordinary skill in the art.
The following detailed description of embodiments of the invention refers to the accompanying drawings.
As shown in fig. 1, a boundary identification and extraction method facing a loess fill settlement zone includes the following steps:
s1, acquiring and preprocessing original SAR image data, and acquiring earth surface differential settlement data of a loess soil filling area in an image coverage area by using a time series InSAR technology (TS-InSAR).
In the image preprocessing stage, track correction is completed by using external precise track data, terrain correction is completed by using external Digital Elevation Model (DEM) data after a main image is selected, then a secondary image is registered to the geometry of the main image, and an interferogram is generated through interference.
In order to obtain the ground settlement distribution condition of a research area in an image coverage range, a space-time baseline threshold value is set firstly, an interference pair baseline network is formed by an interference pattern obtained by preprocessing, and then a space-time coherence threshold value is set to screen a coherent point target so as to remove points with poor coherence. And finally, obtaining an interference phase time sequence result through phase unwrapping, and obtaining corresponding settlement result information in the research area through network inversion.
And S2, dividing the settlement area into m areas according to the obtained ground settlement space distribution result, wherein m is the number of the settlement funnels, deriving a basic attribute table of the settlement points of the settlement area according to the divided areas, establishing a ground settlement point database according to the basic attribute table, and performing classified management on the settlement areas.
The information of the ground subsidence points of the soil filling area is stored in a database, the database is composed of a plurality of data tables, all attribute tables are respectively arranged according to the divided subsidence areas, and the data tables are mainly composed of two attribute tables, namely a deformation rate table and an accumulated deformation rate table. The deformation rate table mainly comprises information such as coordinates of settlement observation points and corresponding deformation rates; the integrated deformation table mainly includes information such as coordinates of a settlement observation point and an integrated deformation amount of each time slot in the SAR image time series, and the settlement observation point of each time slot is assigned with a unique ID and stored.
And S3, on the basis of a foundation surface deformation database of the filled soil settlement area, counting settlement observation points with the same or similar settlement rate in each settlement area, and connecting all the equivalence points in different areas to form an equivalence line.
S4, setting a settlement rate and an accumulated settlement threshold, regarding settlement points larger than a certain threshold as settlement points in the soil filling area, and regarding contour lines formed by the corresponding settlement points as the boundary of the soil filling area in the area.
Examples
In this embodiment, 89 scene Sentinel-1A SAR image data from 6 th 12 th month in 2017 to 26 th 12 th month in 2020 is used, and a new region of yangan in shanxi is selected as a research region. In 2012, the project of the Yangan new district (the north district) is formally started, the construction period is 4 years, and the project of the north district is located in the bridge ditch town of the pagoda district; and a high house ditch and the like are subsequently expanded, and the scale of the day is gradually formed. Since most houses and infrastructures in the new delay area are built on foundations in different periods, and uneven deformation of the ground surface is easy to occur, the development of ground surface deformation research of the new delay area and the identification and extraction of the filled soil area are very important for evaluating the overall stability and safety of the whole new delay area.
Specifically, the loess filling settlement area boundary identification and extraction method comprises the following steps:
acquiring a time sequence SAR image covering a research area, completing orbit correction by using external precise orbit data to remove a reference ellipsoid phase, completing terrain correction by using external Digital Elevation Model (DEM) data after selecting a main image to remove a terrain phase, and registering a secondary image to the geometry of the main image. In the time series InSAR, all SAR images need to be paired and combined to carry out interference network construction. Registering all the images together to the main image mountain of N +1 scene SAR images covering the same region arranged in a specific time sequence (t 0, t1, \8230;, tN) should satisfy the following condition
Figure DEST_PATH_IMAGE002
（1）
Wherein M is the number of interference pairs;
and performing interference processing on all paired images to generate corresponding interference patterns, and performing phase unwrapping and other steps to obtain the deformation rate of each settlement observation point (see fig. 2).
Suppose that the interferogram j is represented by a line at time t A And t B （t A <t B ) The interference of two imaged SAR images is generated, and then the interference phase at the pixel point (l, r) in the interference image j can be expressed as
Figure DEST_PATH_IMAGE004
（2）
The above equation can also be expressed as:
Figure DEST_PATH_IMAGE006
（3）
in the formula
Figure DEST_PATH_IMAGE008
And
Figure DEST_PATH_IMAGE010
respectively represent t at pixel points (l, r) B And t A The phase value of the time of day,
Figure DEST_PATH_IMAGE012
the deformation phase during the two images is the phase of the deformation,
Figure DEST_PATH_IMAGE014
in order to be the phase of the terrain,
Figure DEST_PATH_IMAGE016
for phase delay errors caused by atmospheric effects,
Figure DEST_PATH_IMAGE018
phase information generated for random noise.
The components in the formula (3) can be represented as follows:
Figure DEST_PATH_IMAGE020
（4）
Figure DEST_PATH_IMAGE022
（5）
Figure DEST_PATH_IMAGE024
（6）
lambda is the wavelength of the radar,
Figure DEST_PATH_IMAGE026
and
Figure DEST_PATH_IMAGE028
represents t A 、t B LOS direction accumulated deformation information of the time relative to the initial time;
Figure DEST_PATH_IMAGE030
represents a vertical baseline value;
Figure DEST_PATH_IMAGE032
is DEM elevation difference; γ is the distance from the radar line of sight to the ground observation, and θ represents the radar incident angle. After removing the various interference phases, the phase information for each interferogram can be represented by the following model:
Figure DEST_PATH_IMAGE034
（7）
wherein the content of the first and second substances,
Figure DEST_PATH_IMAGE036
representing the interference phase of each interferogram;
Figure DEST_PATH_IMAGE038
is the time interference phase of the other image relative to the reference image (assuming that the phase of the reference image is
Figure DEST_PATH_IMAGE040
），
Figure DEST_PATH_IMAGE042
Is the residual interference phase error, and A is an M N matrix representing the combined interferogram, consisting of 1, 0, and-1, where-1 represents the master image and 1 represents the slave image. The best estimate of the interference phase of the time series is calculated using the least squares method.
Figure DEST_PATH_IMAGE044
（8）
Wherein the content of the first and second substances,
Figure DEST_PATH_IMAGE046
is the best estimate of the time series interference phase, and W is the Fisher Information Matrix (FIM) diagonal weight Matrix. Equation 9 represents a model for calculating Temporal Coherence (TC), whichCan be used to select a coherence point with high coherence. Subsequently, a high-precision time series deformation result of coherent points in the research area can be obtained through Weighted Least Squares (WLS) estimation of a small baseline network.
Figure DEST_PATH_IMAGE048
（9）
Where k is an imaginary unit.
The all-weather monitoring can be carried out all day long through the InSAR technology, the monitoring efficiency can be greatly improved, the manual wide-area monitoring can be replaced, and the method has strong adaptability.
And 3, dividing the sedimentation area into three areas, namely SHQ, YZD and JSQ, according to the distribution of the sedimentation funnel, and then calculating the average deformation rate and the accumulated sedimentation amount of each area. Different land conditions can lead to different settlement types, and the method is favorable for distinguishing filling areas in different periods and carrying out different settlement factor analysis.
With reference to fig. 2, from 12 months 2017 to 12 months 2020, the new area of Yanan remains relatively stable in most areas, and the deformation rate is mainly concentrated in-10 to 15 mm/yr. However, there are three regions in the figure where ground distortion is significant, namely the SHQ, YZD and JSQ regions. All three settlement areas are distributed in a band shape and are overlapped with a planned filling area of the delay new area, and the maximum settlement rate reaches-50 mm/yr. There are many construction projects in the SHQ area. The YZD area is the area along the traffic key way. JSQ areas are currently building land. The time series deformation space distribution diagram also shows that the deformation range of the earth surface of the Yangan new area is gradually reduced and the speed is reduced from 2017 to 2020, because the Pingshan city building project is basically completed in 2017, and the settlement recovery work is gradually completed.
And 4, establishing a basic ground deformation database based on the three divided areas, so that the data can be classified and managed uniformly.
With reference to fig. 3, the basic ground settlement database is composed of three data tables, and the number of the data tables is determined by the number of the divided areas. Each dataform includes two attribute tables, a sedimentation rate table and a cumulative sedimentation table.
And 5, analyzing the settlement trends of the three settlement areas, making different settlement rate and accumulated settlement threshold schemes according to the filling conditions of the areas, and making different early warning schemes for areas with different settlement conditions.
And connecting the settlement observation points with the same or similar values into a contour line by combining with the figure 4, finally identifying and extracting the boundary of the filled settlement area according to a set threshold value, and carrying out discrimination verification on the extraction result by combining with the optical historical image of the figure 5.

Claims (2)

1. A boundary identification and extraction method for a loess fill settlement area is characterized by comprising the following steps:
s1, acquiring original SAR image data and preprocessing the data, and acquiring surface differential settlement data of a loess soil filling area in an image coverage range by using a time series InSAR technology;
s2, dividing the settlement area into m areas according to the obtained ground settlement space distribution result, wherein m is the number of the settlement funnels; then, deriving a basic attribute table of the settlement points of the settlement area according to the divided areas, establishing a ground settlement point database according to the basic attribute table, and performing classified management on the settlement area; the basic attribute table comprises a deformation rate table and an accumulated deformation table; the deformation rate table comprises coordinates of the settlement observation points and corresponding deformation rate information; the accumulated deformation table comprises the coordinates of the settlement observation points and accumulated deformation information of each time period in the SAR image time sequence;
s3, on the basis of a foundation surface deformation database of the filled soil settlement area, counting settlement observation points with the same or similar settlement rate in each settlement area, and connecting all equivalence points in different areas to form an equivalence line;
s4, setting a settlement rate and an accumulated settlement threshold, regarding settlement points larger than a certain threshold as settlement points in the soil filling area, and regarding contour lines formed by the corresponding settlement points as the boundary of the soil filling area in the area;
the step S1 comprises the following steps:
in the image preprocessing stage, firstly, external precise orbit data is utilized to complete orbit correction; secondly, after the main image is selected, the terrain correction is completed by using external digital elevation model data; registering the secondary image to the geometry of the primary image, and generating an interference pattern through interference;
the step S1 further includes:
the loess fill area ground settlement distribution condition in the image coverage range is obtained: firstly, setting a space-time baseline threshold, forming an interference pair baseline network by an interference pattern obtained by preprocessing, and then setting a space-time coherence threshold to screen a coherent point target so as to remove points with poor coherence; and finally, obtaining an interference phase time sequence result through phase unwrapping, and obtaining corresponding settlement result information in the research area through network inversion.
2. The boundary identification and extraction method for a loess-filled sedimentary region according to claim 1, wherein the sedimentation observation points for each time period are assigned unique IDs to be stored.
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