CN116047518B - Potential geological disaster identification method and equipment based on radar satellite - Google Patents

Potential geological disaster identification method and equipment based on radar satellite Download PDF

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CN116047518B
CN116047518B CN202310318209.1A CN202310318209A CN116047518B CN 116047518 B CN116047518 B CN 116047518B CN 202310318209 A CN202310318209 A CN 202310318209A CN 116047518 B CN116047518 B CN 116047518B
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target point
point
unit
slope
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CN116047518A (en
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于淼
谭遵泉
商胜波
赵宏杰
陆川
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Chengdu Guoxing Aerospace Technology Co ltd
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    • 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
    • G01S13/9021—SAR image post-processing techniques
    • G01S13/9023—SAR image post-processing techniques combined with interferometric 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
    • 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

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  • Remote Sensing (AREA)
  • Radar, Positioning & Navigation (AREA)
  • Physics & Mathematics (AREA)
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  • General Physics & Mathematics (AREA)
  • Electromagnetism (AREA)
  • Pit Excavations, Shoring, Fill Or Stabilisation Of Slopes (AREA)

Abstract

The application discloses a potential geological disaster identification method and equipment based on radar satellites, and relates to the technical field of geological disaster identification. The method has the advantages that the slope units are used for screening, the actual situation of geological disaster occurrence is met, the screening efficiency and accuracy can be improved, meanwhile, multi-source geographic information data are combined in the screening process, the occurrence of geological disasters is considered, the possible consequences of the occurrence of the geological disasters on targets are considered, and the identification accuracy is further improved; and the geological disaster hidden danger area is determined according to the position relation between the target point and the slope unit, so that the recognition efficiency can be remarkably improved compared with the conventional recognition which does not consider the slope unit and takes the target point as an object.

Description

Potential geological disaster identification method and equipment based on radar satellite
Technical Field
The application relates to the technical field of geological disaster prediction, in particular to a method and equipment for identifying potential geological disasters based on radar satellites.
Background
In the geological disaster monitoring technology, in order to obtain the earth surface deformation observation with high precision, the influence of a coherence factor is avoided as much as possible, and interference items are effectively separated. At present, a multi-time phase InSAR (MT-InSAR) technology is mainly applied, and the MT-InSAR technology with more applications mainly comprises the following steps: a PS-InSAR method that selects a permanent scatterer (Persistent Scatterer, PS) target based on the stability of amplitude and/or phase information over time sequence; the SBAS-InSAR method is based on interference pairs of multiple primary images, and the time sequence deformation information of a research area is restored based on high coherence points; unlike the physical properties of PS targets, the DS-InSAR (Distributed Scatterer, DS) method refers to point targets where no backscatter of any scatterers dominates within the radar resolution cell.
However, different parameter combinations of different MT-InSAR methods can affect the number and the precision of target points, and when the number of the target points reaches tens of millions or even hundreds of millions, the referential of the InSAR technology to geological disaster risk assessment can be reduced. Therefore, the current geological disaster identification method based on the time sequence InSAR technology is low in identification accuracy.
Disclosure of Invention
The main purpose of the application is to provide a radar satellite-based potential geological disaster identification method and equipment, and aims to solve the technical problem that the identification accuracy of the existing geological disaster identification method based on the time sequence InSAR technology is low.
In order to solve the above technical problems, the embodiments of the present application provide: a potential geological disaster identification method based on radar satellites comprises the following steps:
acquiring digital elevation model data of a target research area and a target point accumulated deformation time sequence in the target research area, wherein the target point accumulated deformation time sequence is acquired based on time sequence data acquired by a radar satellite;
generating slope unit data corresponding to a plurality of slope units in the target research area based on the digital elevation model data of the target research area;
screening a plurality of ramp units in the target research area based on ramp unit data in the target research area and multi-source geographic data in the target research area to obtain a first ramp unit set;
acquiring a target point set in the target research area based on the target point accumulated deformation time sequence in the target research area;
And determining a geological disaster hidden danger area in the target research area based on the position relation between the target point in the target point set and each slope unit in the first slope unit set.
Optionally, the screening the plurality of ramp units in the target study area based on the ramp unit data in the target study area and the multi-source geographic data in the target study area to obtain a first ramp unit set includes:
obtaining the planar vector centroid of each ramp unit in the target research area based on the ramp unit data in the target research area;
calculating the minimum Euclidean distance from the centroid of the planar vector of each slope unit to each type of data in the multi-source geographic data;
and screening slope units with the minimum Euclidean distance smaller than a distance threshold value to form the first slope unit set.
Optionally, before determining the geological disaster hidden danger area in the target research area based on the position relationship between the target point in the target point set and each slope unit in the first slope unit set, the method further includes:
acquiring gradient data of the target research area based on the digital elevation model data of the target research area;
Obtaining an average gradient of each ramp unit in the first ramp unit set based on gradient data of the first ramp unit set and the target study area;
screening slope units with average gradient larger than a gradient threshold value to form a second slope unit set;
the determining a geological disaster hidden danger zone in the target research zone based on the position relation between the target point in the target point set and each slope unit in the first slope unit set comprises the following steps:
and determining a geological disaster hidden danger area in the target research area based on the position relation between the target point in the target point set and each slope unit in the second slope unit set.
Optionally, the determining, based on the positional relationship between the target point in the target point set and each slope unit in the first slope unit set, a geological disaster hidden danger area in the target research area includes:
judging whether the number of target points in the target point set is larger than a threshold value or not;
if yes, screening a plurality of target points in the same slope unit from the target point set to form a closed vector surface;
and determining a geological disaster hidden danger zone in the target research zone based on the closed vector surface.
Optionally, the determining, based on the closed vector surface, a geological disaster hidden danger zone in the target research area includes:
calculating the centroid of the vector surface and Euclidean distances between a plurality of target points forming the vector surface and the centroid;
judging whether an outlier exists on the vector surface according to the Euclidean distance between a plurality of target points forming the vector surface and the centroid and the magnitude relation between the Euclidean distance and a preset radius threshold;
if the vector surface does not have outliers, the area where the vector surface is located is a geological disaster hidden danger area.
Optionally, the screening the multiple target points located in the same slope unit from the target point set to form a closed vector surface includes:
determining a starting point according to the longitude and latitude of each target point in the target point set
Figure SMS_1
；
At the starting point
Figure SMS_2
As a starting point, obtaining the starting point +.>
Figure SMS_3
Is located in the ramp unit at the target point +_with the T-th largest angle>
Figure SMS_4
；
At the target point
Figure SMS_5
As starting point, obtain the target point +.>
Figure SMS_6
Is located in the ramp unitTarget point with the t-th small polar angle +.>
Figure SMS_7
；
At the target point
Figure SMS_8
Circularly executing the above-mentioned acquisition of the target point with the t-th small polar angle as the starting point +. >
Figure SMS_9
Until the starting point is again acquired +.>
Figure SMS_10
Obtaining a plurality of target points positioned in the same slope unit;
based on a plurality of target points located in the same ramp unit, a closed vector surface is obtained.
Optionally, the starting point is
Figure SMS_11
As a starting point, obtaining the starting point +.>
Figure SMS_12
Is located in the ramp unit at the target point +_with the T-th largest angle>
Figure SMS_13
Comprising: />
Acquiring a target point with a T-th maximum polar angle in polar coordinates in the target point set
Figure SMS_14
And obtain the target point
Figure SMS_15
Is +_with the starting point>
Figure SMS_16
Is a first linear vector of (a); wherein the polar coordinates are +.>
Figure SMS_17
As a starting point;
if the first linear vector does not intersect the first ramp unit set of ramp units, obtaining a starting point
Figure SMS_18
Is located in the ramp unit at the target point +_with the T-th largest angle>
Figure SMS_19
；
If the first linear vector intersects the first ramp unit set of ramp units, eliminating the target point from the target point set
Figure SMS_20
Obtaining a target point set after being removed;
judging whether the number of target points in the target point set after the elimination is greater than the threshold value, if so, returning to acquire the target point with the T maximum polar angle under the polar coordinates based on the target point set after the elimination
Figure SMS_21
And obtain the target point +.>
Figure SMS_22
Is +_with the starting point>
Figure SMS_23
Is looped to obtain the first linear vector of +.A.A. with the starting point>
Figure SMS_24
Is located in the ramp unit at the target point +_with the T-th largest angle>
Figure SMS_25
。
Optionally, the target point is
Figure SMS_26
As a starting point, acquiring the target point and the target point in the target point set/>
Figure SMS_27
Is located in the ramp unit at the target point +.>
Figure SMS_28
Comprising:
acquiring a target point with a t-th small polar angle in polar coordinates in the target point set
Figure SMS_29
And obtain the target point
Figure SMS_30
Is->
Figure SMS_31
Is defined by a first linear vector of (a); wherein the polar coordinates are +.>
Figure SMS_32
As a starting point;
if the second linear vector does not intersect the first ramp unit set of ramp units, obtaining a target point
Figure SMS_33
Is located in the ramp unit at the target point +.>
Figure SMS_34
；
If the second linear vector intersects the first slope unit set of slope units, eliminating the target point from the target point set
Figure SMS_35
Obtaining a target point set after being removed;
judging whether the number of target points in the target point set after the elimination is greater than the threshold value, if so, returning to acquire the target point with the t-th small polar angle under the polar coordinates based on the target point set after the elimination
Figure SMS_36
And obtain the target point +.>
Figure SMS_37
Is->
Figure SMS_38
Is looped to obtain the second line vector of the target point +.>
Figure SMS_39
Is located in the ramp unit at the target point +.>
Figure SMS_40
。
Optionally, the obtaining the target point set in the target research area based on the target point accumulated deformation time sequence in the target research area includes:
carrying out trend test on the accumulated deformation time sequence of the target point in the target research area by utilizing a Mann-Kendall algorithm so as to obtain trend test data;
denoising the target point accumulated deformation time sequence in the target research area based on the trend test data so as to obtain a target point set in the target research area.
Optionally, the multi-source geographic data includes: river water system data, road data and residential point data.
In order to solve the above technical problems, the embodiment of the present application further provides: an electronic device comprising a memory in which a computer program is stored and a processor executing the computer program to implement the method as described above.
Compared with the prior art, the method and the device for identifying the potential geological disaster based on the radar satellite, provided by the embodiment of the application, are characterized in that the digital elevation model data of a target research area and the target point accumulated deformation time sequence in the target research area are obtained, and the target point accumulated deformation time sequence is obtained based on the time sequence data acquired by the radar satellite; generating slope unit data corresponding to a plurality of slope units in the target research area based on the digital elevation model data of the target research area; screening a plurality of ramp units in the target research area based on ramp unit data in the target research area and multi-source geographic data in the target research area to obtain a first ramp unit set; acquiring a target point set in the target research area based on the target point accumulated deformation time sequence in the target research area; and determining a geological disaster hidden danger area in the target research area based on the position relation between the target point in the target point set and each slope unit in the first slope unit set. In other words, in the method, a slope unit is introduced as a basic analysis unit in the data processing process, multi-source geographic information data are synthesized, the slope unit is analyzed and removed, and a geological disaster hidden danger area is determined according to the position relation between a target point and the slope unit. On one hand, the screening is carried out by taking the slope unit as a unit, so that the screening efficiency and accuracy can be improved, meanwhile, the multi-source geographic information data are combined in the screening process, the occurrence of the geological disasters is considered, the possible consequences of the occurrence of the geological disasters on the targets are considered, and the identification accuracy is further improved; on the other hand, the geological disaster hidden danger area is determined according to the position relation between the target point and the slope unit, so that the spatial association of the deformation target point can be enhanced, and compared with the existing method for identifying the target point without considering the slope unit, the identification efficiency can be remarkably improved.
Drawings
FIG. 1 is a flow chart of a method for identifying potential geological disasters based on radar satellites according to an embodiment of the present application;
FIG. 2 is a flow chart of a specific implementation of step S40 in the embodiment of the present application;
FIG. 3 is a flow chart of a grade unit screening process in an embodiment of the present application;
fig. 4 is a flow chart illustrating a specific implementation procedure of step S100 in the embodiment of the present application.
Detailed Description
It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the present application.
Geological disasters refer to a series of disaster events caused by geological processes due to natural actions in the earth or human activities, such as earthquakes, debris flows, landslides, collapse, etc., which may cause casualties, property loss, and damage to the ecological environment. These geological disasters are closely related to the earth's structure, topography, geological conditions, climate, human activities, etc., and need to be scientifically predicted, prevented and controlled to reduce their harmfulness.
In some areas with large relief, the traditional ground measurement means are limited by cost and coverage, and large-scale disaster census is difficult to realize. The synthetic aperture radar interferometry (InSAR) technology has the capability of being free from cloud and fog, large in coverage range and capable of monitoring tiny earth surface deformation, and can provide important support for geological disaster screening. The InSAR technology can measure tiny deformation of the earth surface, but due to the influences of time decoherence and space decoherence, interference components such as orbit errors, digital elevation model errors, atmospheric propagation delays and the like are contained in interference phases, and the application and measurement accuracy of the InSAR technology are limited. In order to obtain the surface deformation observation with high precision, the influence of a coherence factor should be avoided as much as possible, and the interference item is effectively separated. Multi-temporal InSAR (MT-InSAR) technology has been developed in this background.
The existing MT-InSAR method generates a large number of deformation interest points, including real deformation and noise deformation, how to extract effective deformation information of hidden geological disasters from the deformation information, and extracts geological disaster hidden danger areas conforming to the inoculation and disaster development rules of the geological disasters according to the effective deformation information to become the current technical difficulty. Effective deformation information is extracted by using a certain analysis processing algorithm and combined with geological disaster association factors to generate auxiliary data which can be used for assisting in verifying the hidden trouble of geological disasters in field.
The embodiment of the application provides a method and equipment for identifying potential geological disasters based on radar satellites, so as to solve the problems in the prior art.
Noun interpretation:
InSAR, english is fully: synthetic Aperture Radar Interferometry, chinese translation is: synthetic aperture radar interferometry.
MT-InSAR, english full name: multi-temporal Synthetic Aperture Radar Interferometry, chinese translation is: multi-time phase synthetic aperture radar interferometry.
In one implementation, the method of the present embodiment may be executed based on an existing computer device running a program, where the computer device may be a mobile phone, a tablet, a desktop computer, etc., and the computer device may include a processor, a storage medium, etc., where the storage medium is used to store the program for executing the method of the present embodiment, and the processor is used to run the program to execute the method of the present embodiment.
Referring to fig. 1, based on the computer device of the foregoing embodiment, an embodiment of the present application provides a method for identifying a potential geological disaster based on a radar satellite, including the following steps:
and S20, acquiring digital elevation model data of a target research area and a target point accumulated deformation time sequence in the target research area, wherein the target point accumulated deformation time sequence is acquired based on time sequence data acquired by a radar satellite.
In the implementation process, the target research area refers to a region where a possible geological disaster occurs, and the digital elevation model data (Digital Elevation Model), abbreviated as DEM, is obtained by implementing digital simulation of ground topography (i.e. digital expression of topography surface morphology) through limited topography elevation data, and is an entity ground model which represents ground elevation in the form of a group of ordered value arrays and can be obtained by photogrammetry, ground measurement, digitization of an existing topography and extraction from an existing DEM library.
In this embodiment, the time series of the target point accumulated deformation amount generally refers to the time series of the target point accumulated deformation amount (unit: mm) with longitude and latitude coordinates. The MT-InSAR method can be used for acquiring time series data in the same image frame based on radar satellites (space-borne synthetic aperture radar).
And step S40, acquiring a target point set in the target research area based on the target point accumulated deformation time sequence in the target research area.
In the implementation process, the target point accumulated deformation time sequence comprises a plurality of target points, and the target point accumulated deformation time sequence is traversed to obtain a target point set. In this embodiment, the target point is a deformation interest point generated by the MT-InSAR method.
As an alternative embodiment, referring to fig. 2, the obtaining the target point set in the target study area based on the time sequence of accumulated deformation of the target point in the target study area includes:
s402, carrying out trend test on the time sequence of the accumulated deformation of the target point in the target research area by utilizing a Mann-Kendall algorithm so as to obtain trend test data;
in the implementation process, the accumulated deformation time sequence of the target point is recorded as
Figure SMS_41
。
In the trend test process, according to the existing Mann-Kendall algorithm, firstly, the following assumption is made on the time sequence of the accumulated deformation of the target point:
Figure SMS_42
assume that: the data in the sequence is assumed to be independent random samples distributed in the same way, namely no significant trend exists;
Figure SMS_43
assume that: assuming that the sequence has a monotonic trend of rising or falling;
At the position of
Figure SMS_44
Assuming that test statistic S is defined as: />
S =
Figure SMS_45
Wherein, the liquid crystal display device comprises a liquid crystal display device,
Figure SMS_46
、/>
Figure SMS_47
respectively the observed values corresponding to the ith and the jth time sequences, and i<j, sgn is a sign function, sgn (θ) = = -j->
Figure SMS_48
，/>
Figure SMS_49
=/>
Figure SMS_50
-/>
Figure SMS_51
；
When n > =10, the statistic S approximately follows a normal distribution. And (3) normalizing the S to obtain Z, and performing significance test by using a statistical test value Z, wherein the formula is as follows:
Z =
Figure SMS_52
wherein var (S) = (n (n-1) (2n+5) room = (n-1) (2n+5) room
Figure SMS_53
Wherein: n is the number of data in the accumulated deformation time sequence; m is the number of knots (repeated data sets) in the sequence;
Figure SMS_54
is the width of the junction (the repeated data format in the ith repeated data set).
With the bilateral trend test, given a significance level (confidence level) α=0.05, when |z|<=
Figure SMS_55
When receiving +.>
Figure SMS_56
Assuming that the trend is not obvious; otherwise accept->
Figure SMS_57
Suppose, i.e. Z>=/>
Figure SMS_58
Indicating a significant increase in sequence and a significant decrease in sequence.
On the basis, the time sequence of the accumulated deformation amount of the target points with obvious descending trend is marked as forward deformation target points, and the target points are selected to enter the next analysis.
S404, denoising the target point accumulated deformation time sequence in the target research area based on the trend test data so as to obtain a target point set in the target research area.
In the specific implementation process, the target points with significant upward trend and no significant trend in the data of the trend test are considered to be interfered by larger noise and removed. Thereby obtaining a set of target points within the target study area.
Step S60, generating slope unit data corresponding to a plurality of slope units in the target research area based on the digital elevation model data of the target research area.
In the specific implementation process, the slope unit is a unit type in a geological disaster dangerous area, and the slope unit is a basic unit for development of geological disasters such as landslide, collapse and the like. The ramp unit data refers to data generated by the ramp unit division. The digital elevation model data can be input into three-dimensional analysis tools such as ArcGIS and the like to generate slope unit data corresponding to a plurality of slope units in the target research area. Specifically, on the digital elevation model data, ridge lines and valley lines (corresponding to water distribution lines and catchment lines respectively) can be respectively extracted by utilizing positive and negative terrains without depressions, the generated water collection basin is fused with the reverse water collection basin, unreasonable units are manually repaired and compiled in the later period, and finally the obtained area divided by the catchment lines and the water distribution lines is the slope unit.
Step S80, screening a plurality of slope units in the target research area based on the slope unit data in the target research area and the multi-source geographic data in the target research area to obtain a first slope unit set.
In the implementation process, the multi-source geographic data refers to various different types of geographic object data such as river water system data, road data, resident point data and the like.
It will be appreciated that by a ramp unit based geological disaster study, a prediction of the geological disaster of the region where the ramp unit is located can be obtained, but because not all geological anomalies can cause geological disasters. For example, in an unmanned area, geological disasters occur in time, and casualties cannot be caused, so that the prediction of the situation is of little significance. For example, when a geological disaster occurs, a barrier lake is likely to be generated in a place where a river water system exists, a road break is likely to be caused in a place where a road exists, and casualties are likely to be caused in a place where a resident point exists. In the embodiment, the slope units are screened by combining the multi-source geographic data, and some slope units without threat objects can be removed, so that on one hand, the data calculation amount is reduced, and the efficiency is improved; on the other hand, some interference can be eliminated, and the prediction accuracy is improved.
Specifically, whether the slope unit can be removed or not can be judged according to the position relation between the object corresponding to each geographic object data in the multi-source geographic data and the slope unit. For example, if a river system, road, or residential site is present in the slope unit or at a position closer to the slope unit, it is determined that there is a risk, and if the river system, road, or residential site is not present, it is possible to consider culling.
As an optional implementation manner, based on the ramp unit data in the target research area and the multisource geographic data in the target research area, a plurality of ramp units in the target research area are screened to obtain a first ramp unit set, which specifically includes:
obtaining the planar vector centroid of each ramp unit in the target research area based on the ramp unit data in the target research area; calculating the minimum Euclidean distance from the centroid of the planar vector of each slope unit to each type of data in the multi-source geographic data; and screening slope units with the minimum Euclidean distance smaller than a distance threshold value to form the first slope unit set.
In the implementation process, the slope units can be converted into planar vectors, so that the centroid of the planar vectors can be calculated according to a centroid calculation method, and then the minimum Euclidean distance from the centroid of the planar vectors of each slope unit to various types of objects in the multi-source geographic data is calculated.
In this embodiment, the distance threshold may be set according to the severity of the criterion, and it is understood that the further the object is from the centroid of the planar vector, the less the threat of the ramp unit. In this embodiment, the distance threshold may be set to 3km, and if the minimum euclidean distance between all surrounding objects and the centroid of the planar vector is greater than 3km, the ramp unit is considered to have no threat object, and may be eliminated. According to the method, the slope units with the minimum Euclidean distance smaller than the distance threshold value can be screened out to form the first slope unit set.
And step S100, determining a geological disaster hidden danger area in the target research area based on the position relation between the target point in the target point set and each slope unit in the first slope unit set.
In the implementation process, the position relationship refers to the relative position relationship between the target point and the slope units, and because the target point is a point with ground deformation and the slope units are basic units for development of common geological disasters (landslide, collapse and the like), the hidden danger area of the geological disasters can be determined according to the position relationship between the target point in the target point set and each slope unit in the first slope unit set.
In summary, compared with the prior art, the radar satellite-based potential geological disaster identification method provided by the embodiment introduces the slope unit as the basic analysis unit in the data processing process, synthesizes the multi-source geographic information data, analyzes and eliminates the slope unit, and determines the geological disaster hidden danger area according to the position relation between the target point and the slope unit. On one hand, the screening is carried out by taking the slope unit as a unit, so that the screening efficiency and accuracy can be improved, meanwhile, the multi-source geographic information data are combined in the screening process, the occurrence of the geological disasters is considered, the possible consequences of the occurrence of the geological disasters on the targets are considered, and the identification accuracy is further improved; on the other hand, the geological disaster hidden danger area is determined according to the position relation between the target point and the slope unit, so that the spatial association of the deformation target point can be enhanced, and compared with the existing method for identifying the target point without considering the slope unit, the identification efficiency can be remarkably improved.
As an optional implementation manner, referring to fig. 3, before determining the geological disaster hidden danger area in the target research area based on the position relationship between the target point in the target point set and each slope unit in the first slope unit set, the method further includes:
S902, acquiring gradient data of the target research area based on the digital elevation model data of the target research area;
in the implementation process, the gradient data can be obtained by taking the digital elevation model data as input and calculating the gradient in the research area by using software or a program and stored in a TIFF format.
S904, obtaining the average gradient of each slope unit in the first slope unit set based on the gradient data of the first slope unit set and the target research area;
in the implementation process, the slope units and gradient data in the first slope unit set are taken as input, the attribute of average gradient of the slope units is added, the average value of the gradient data in the slope units is calculated one by one and recorded as
Figure SMS_59
Wherein I is the index of the slope unit, the value range of I is 1-N, and N is the total number of the slope units in the research area.
S906, screening slope units with average gradient larger than a gradient threshold value to form a second slope unit set;
in a specific implementation process, the gradient threshold value can be set according to needs, and it can be understood that the larger the gradient is, the greater the possibility of sending geological disasters such as landslide, collapse, mud-rock flow and the like is. Therefore, a gradient threshold value is set, if the average gradient of the slope unit is larger than the threshold value, geological disasters such as landslide, collapse and debris flow are considered to exist in the slope unit, and if the average gradient is smaller than the threshold value, the geological disasters are removed, so that a second slope unit set is obtained.
Correspondingly, the determining the geological disaster hidden danger area in the target research area based on the position relation between the target point in the target point set and each slope unit in the first slope unit set includes:
and determining a geological disaster hidden danger area in the target research area based on the position relation between the target point in the target point set and each slope unit in the second slope unit set.
It can be appreciated that in this embodiment, by performing rescreening on the slope units in the slope unit set through the inherent relationship between the gradient and the geological disaster, subsequent calculation and evaluation of the slope units with lower part of risks can be further reduced, so that the efficiency of the whole recognition process and the recognition accuracy rate are further improved.
As an optional implementation manner, referring to fig. 4, the determining, based on the positional relationship between the target point in the target point set and each slope unit in the first slope unit set, a geological disaster hidden danger area in the target research area includes:
s1002, judging whether the number of target points in the target point set is larger than a threshold value;
in a specific implementation, in this embodiment, the target point set may be expressed as
Figure SMS_60
Wherein h is the number of target points in the target point set, < ->
Figure SMS_61
Is expressed as +.>
Figure SMS_62
，/>
Figure SMS_63
Representing the longitude of the i-th target point,
Figure SMS_64
representing the longitude of the i-th target point.
In this embodiment, the number of target points in the target point set is firstly determined, because the number of target points in the ramp unit is related to the risk of geological disasters, and if the number of target points in the ramp unit is smaller, the number of target points in the area is considered to be low, the density is low, the reference is not available, and the risk of geological disasters can be eliminated. Otherwise, the risk of geological disasters is considered.
In this embodiment, the threshold may also be set as required, for example, to 3.
S1004, if yes, screening a plurality of target points located in the same slope unit from the target point set to form a closed vector surface;
in the implementation process, if the number of target points in the target point set is greater than a threshold value, the risk of geological disasters is considered to exist. At this time, a plurality of target points located in the same slope unit are screened out from the target point set to form a closed vector surface. Specifically, multiple target points located in the same slope unit can be screened from the target point set by traversing the target point set and the first slope unit set.
Specifically, the screening the multiple target points located in the same slope unit from the target point set to form a closed vector surface includes:
determining a starting point according to the longitude and latitude of each target point in the target point set
Figure SMS_65
；
At the starting point
Figure SMS_66
As a starting point, obtaining the starting point +.>
Figure SMS_67
Is located in the ramp unit at the target point +_with the T-th largest angle>
Figure SMS_68
T is a positive integer;
at the target point
Figure SMS_69
As starting point, obtain the target point +.>
Figure SMS_70
Is located in the ramp unit at the target point +.>
Figure SMS_71
T is a positive integer;
at the target point
Figure SMS_72
Circularly executing the above-mentioned acquisition of the target point with the t-th small polar angle as the starting point +.>
Figure SMS_73
Until the starting point is again acquired +.>
Figure SMS_74
Obtaining a plurality of target points positioned in the same slope unit;
based on a plurality of target points located in the same ramp unit, a closed vector surface is obtained.
Specifically, the starting point is
Figure SMS_75
As a starting point, obtaining the starting point +.>
Figure SMS_76
Is located in the ramp unitTarget point +.>
Figure SMS_77
Comprising:
acquiring a target point with a T-th maximum polar angle in polar coordinates in the target point set
Figure SMS_78
And obtain the target point
Figure SMS_79
Is +_with the starting point>
Figure SMS_80
Is a first linear vector of (a); wherein the polar coordinates are +.>
Figure SMS_81
As a starting point;
if the first linear vector does not intersect the first ramp unit set of ramp units, obtaining a starting point
Figure SMS_82
Is located in the ramp unit at the target point +_with the T-th largest angle>
Figure SMS_83
；
If the first linear vector intersects the first ramp unit set of ramp units, eliminating the target point from the target point set
Figure SMS_84
Obtaining a target point set after being removed;
judging whether the number of target points in the target point set after the elimination is greater than the threshold value, if so, returning to acquire the target point with the T maximum polar angle under the polar coordinates based on the target point set after the elimination
Figure SMS_85
And obtain the target point +.>
Figure SMS_86
Is +_with the starting point>
Figure SMS_87
Is looped to obtain the first linear vector of +.A.A. with the starting point>
Figure SMS_88
Is located in the ramp unit at the target point +_with the T-th largest angle>
Figure SMS_89
。
Specifically, the target point is
Figure SMS_90
As starting point, obtain the target point +.>
Figure SMS_91
Is located in the ramp unit at the target point +.>
Figure SMS_92
Comprising:
acquiring a target point with a t-th small polar angle in polar coordinates in the target point set
Figure SMS_93
And obtain the target point
Figure SMS_94
Is->
Figure SMS_95
Is defined by a first linear vector of (a); wherein the polar coordinates are +.>
Figure SMS_96
As a starting point;
if the second linear vector does not intersect the first ramp unit set of ramp units, obtaining a target point
Figure SMS_97
Is located in the ramp unit at the target point +.>
Figure SMS_98
；
If the second linear vector intersects the first slope unit set of slope units, eliminating the target point from the target point set
Figure SMS_99
Obtaining a target point set after being removed;
judging whether the number of target points in the target point set after the elimination is greater than the threshold value, if so, returning to acquire the target point with the t-th small polar angle under the polar coordinates based on the target point set after the elimination
Figure SMS_100
And obtain the target point +.>
Figure SMS_101
Is->
Figure SMS_102
Is looped to obtain the second line vector of the target point +.>
Figure SMS_103
Is located in the ramp unit at the target point +.>
Figure SMS_104
。
Therefore, in the implementation process, the method of the embodiment screens out a plurality of target points located in the same slope unit from the target point set by traversing the target point set and the first slope unit set, and the implementation process can be summarized as follows:
First, a starting point is calculated
Figure SMS_105
The calculation mode is as follows:
Figure SMS_106
that is, the target point having the smallest longitude is selected as the start point.
If it is
Figure SMS_107
The number is greater than 1, update->
Figure SMS_108
The following are provided:
Figure SMS_109
that is, when there are a plurality of minimum longitude target points, a target point having the smallest latitude therein is selected as a start point.
Then, by
Figure SMS_110
As a starting point O, a horizontal direction is a polar axis X, and a polar coordinate system is constructed; calculating the polar coordinates of the remaining target point in the polar coordinate system>
Figure SMS_111
Wherein->
Figure SMS_112
Is of the polar diameter>
Figure SMS_113
Is the polar angle;
according to the order from large to small, the target point with the largest maximum angle is firstly acquired
Figure SMS_114
If a plurality of target points with the maximum polar angles exist, selecting the target point with the longest polar diameter, and connecting the starting point with the target point to form a linear vector; judging whether the linear vector intersects with the ramp unit, if the linear vector intersects with the ramp unit, discarding the target point +.>
Figure SMS_115
The target point set is updated (at this time, the updated target point set does not already contain the target point +.>
Figure SMS_116
) And then, judging the number again, and if the number of the target point sets is smaller than a threshold (for example, the threshold is 3, and the following is taken as 3 as an example directly), discarding the calculation, and considering that no geological disaster hidden danger area exists. Otherwise, if the number of the target point sets is greater than the threshold value, continuing to acquire the target point with the second largest maximum angle +. >
Figure SMS_117
Connecting the initial point with the point to form a linear vector; if the line vector intersects the ramp unit, the target point is rejected +.>
Figure SMS_118
Updating the target point set, entering quantity judgment, and if the number of the target point set is less than 3, abandoning calculation. Repeating the above steps until finding the target point +.f with the T-th maximum angle satisfying the spatial relationship>
Figure SMS_119
So that the starting point is +.>
Figure SMS_120
If the linear vector is formed in the slope unit (i.e. the linear vector does not intersect with the slope unit), the linear vector point pair is reserved, and the coordinates of the target point pair forming the linear vector are stored in the list. If the target points meeting the spatial relationship do not exist, the risk of geological disasters does not exist.
At the time of obtaining the target point with the T-th maximum angle
Figure SMS_121
After that, use +.>
Figure SMS_122
The point is newStarting point, constructing a polar coordinate system by taking the horizontal direction as a polar axis, and calculating the polar coordinates of the residual target point under the polar coordinate system>
Figure SMS_123
Wherein->
Figure SMS_124
Is of the polar diameter>
Figure SMS_125
Is the polar angle;
the target point with the smallest polar angle is firstly acquired according to the order from small to large
Figure SMS_126
If a plurality of minimum polar angle target points exist, selecting the target point with the longest polar diameter, and connecting a new starting point with the target point to form a linear vector; finding a target point with a T-th small polar angle which meets the spatial relationship by referring to the calculation and judgment logic in the step of finding the target point with the T-th large polar angle >
Figure SMS_127
I.e. start point and target point with minimum polar angle t +.>
Figure SMS_128
If the linear vector is formed in the slope unit (i.e. the linear vector does not intersect with the slope unit), the linear vector point pair is reserved, and the coordinates of the target point pair forming the linear vector are stored in the list. />
At the time of obtaining the target point with the t-th minimum polar angle
Figure SMS_131
After that, use +.>
Figure SMS_133
The point is a new starting point, a polar coordinate system is constructed by taking the horizontal direction as a polar axis, and the polar coordinates of the residual target point under the polar coordinate system are calculated>
Figure SMS_136
(/>
Figure SMS_129
,/>
Figure SMS_132
) Wherein, the method comprises the steps of, wherein,
Figure SMS_134
is of the polar diameter>
Figure SMS_137
The steps of traversing from small to large are repeated for polar angles until the list contains a starting point
Figure SMS_130
(i.e. go through again to start point +.>
Figure SMS_135
) To this end, a closed vector surface is formed, which is entirely inside the ramp unit.
It will be appreciated that, in the iterative manner described above, one can traverse again to the starting point
Figure SMS_138
Thereby forming a closed loop and obtaining a closed vector surface.
S1006, determining a geological disaster hidden danger area in the target research area based on the closed vector surface.
In the implementation process, whether the closed vector surface is defined as a geological disaster hidden danger area can be judged by judging whether the closed vector surface has an outlier target point. Specifically, if an outlier exists, the existence of a target point with poor spatial relevance with the deformation region is indicated, and the target point can be selected and removed.
As an optional implementation manner, the determining the geological disaster hidden danger zone in the target research area based on the closed vector surface includes:
calculating the centroid of the vector surface and Euclidean distances between a plurality of target points forming the vector surface and the centroid;
judging whether an outlier exists on the vector surface according to the Euclidean distance between a plurality of target points forming the vector surface and the centroid and the magnitude relation between the Euclidean distance and a preset radius threshold;
if the vector surface does not have outliers, the area where the vector surface is located is a geological disaster hidden danger area.
In the specific implementation process, the preset radius threshold may also be set as required, for example, set to 2km, and it may be understood that the principle of performing the slope unit screening according to the multi-source geographic data in the foregoing embodiment may be referred to for judging whether the outlier exists on the vector surface through the centroid and the euclidean distance, which is not described herein. Specifically, when euclidean distances between a plurality of target points forming the vector surface and the centroid are smaller than a preset radius threshold value, no outlier exists on the vector surface.
As another case, if euclidean distances between the plurality of target points forming the vector surface and the centroid are all greater than a preset radius threshold, an outlier exists on the vector surface, and the outlier has poor spatial correlation with the deformation region, and the target point is discarded.
It can be appreciated that in this embodiment, the spatial association of the deformation target points is enhanced by the recognition of the area units, such as the vector surface and the ramp unit, and the recognition efficiency can be significantly improved compared with the existing recognition of the geological disaster hidden danger area by the single target point.
In some embodiments, embodiments of the present application also provide a computer readable storage medium storing a computer program which, when executed by a processor, can perform the radar satellite-based potential geological disaster identification method of the previous embodiments.
The computer readable storage medium may be FRAM, ROM, PROM, EPROM, EEPROM, flash memory, magnetic surface memory, optical disk or CD-ROM; but may be a variety of devices including one or any combination of the above memories. The computer may be a variety of computing devices including smart terminals and servers.
In some embodiments, the executable instructions may be in the form of programs, software modules, scripts, or code, written in any form of programming language (including compiled or interpreted languages, or declarative or procedural languages), and they may be deployed in any form, including as stand-alone programs or as modules, components, subroutines, or other units suitable for use in a computing environment.
As an example, the executable instructions may, but need not, correspond to files in a file system, may be stored as part of a file that holds other programs or data, for example, in one or more scripts in a hypertext markup language (HTML, hyper Text Markup Language) document, in a single file dedicated to the program in question, or in multiple coordinated files (e.g., files that store one or more modules, sub-programs, or portions of code).
As an example, executable instructions may be deployed to be executed on one computing device or on multiple computing devices located at one site or, alternatively, distributed across multiple sites and interconnected by a communication network.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or system. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or system that comprises the element.
The foregoing order of embodiments of the present application is merely for illustration, and does not represent the advantages or disadvantages of the embodiments.
From the above description of embodiments, it will be clear to a person skilled in the art that the above embodiment method may be implemented by means of software plus a necessary general hardware platform, but may of course also be implemented by means of hardware, but in many cases the former is a preferred embodiment. Based on such understanding, the technical solution of the present application may be embodied essentially or in a part contributing to the prior art in the form of a software product stored in a storage medium (e.g. read-only memory/random-access memory, magnetic disk, optical disk), comprising several instructions for causing a multimedia terminal device (which may be a mobile phone, a computer, a television receiver or a network device, etc.) to perform the method of the embodiments of the present application.
The foregoing description of the preferred embodiments of the present application is not intended to limit the invention to the particular embodiments of the present application, but to limit the scope of the invention to the particular embodiments of the present application.

Claims (8)

1. A method for identifying potential geological disasters based on radar satellites, comprising:
Acquiring digital elevation model data of a target research area and a target point accumulated deformation time sequence in the target research area, wherein the target point accumulated deformation time sequence is acquired based on time sequence data acquired by a radar satellite;
acquiring a target point set in the target research area based on the target point accumulated deformation time sequence in the target research area;
generating slope unit data corresponding to a plurality of slope units in the target research area based on the digital elevation model data of the target research area;
screening a plurality of ramp units in the target research area based on ramp unit data in the target research area and multi-source geographic data in the target research area to obtain a first ramp unit set;
judging whether the number of target points in the target point set is larger than a threshold value or not;
if yes, determining a starting point according to the longitude and latitude of each target point in the target point set
Figure QLYQS_1
The method comprises the steps of carrying out a first treatment on the surface of the With start point->
Figure QLYQS_6
As a starting point, obtaining the starting point +.>
Figure QLYQS_9
Is located in the ramp unit at the target point +_with the T-th largest angle>
Figure QLYQS_2
T is a positive integer; with target point->
Figure QLYQS_5
As a starting point, acquiring the target point and the target point in the target point set
Figure QLYQS_8
Is located in the ramp unit at the target point +.>
Figure QLYQS_11
T is a positive integer; at the target point
Figure QLYQS_3
Circularly executing the above-mentioned acquisition of the target point with the t-th small polar angle as the starting point +.>
Figure QLYQS_4
Until the starting point is again acquired +.>
Figure QLYQS_7
Obtaining a plurality of target points positioned in the same slope unit; acquiring a closed vector surface based on a plurality of target points positioned in the same slope unit; wherein the start point->
Figure QLYQS_10
A target point of the set of target points having a minimum longitude; the linear vector is positioned on the slope sheetIn-element means that the linear vector does not intersect the ramp unit;
and determining a geological disaster hidden danger zone in the target research zone based on the closed vector surface.
2. The method of claim 1, wherein the screening the plurality of ramp units within the target study area to obtain the first set of ramp units based on the ramp unit data within the target study area and the multi-source geographic data within the target study area comprises:
obtaining the planar vector centroid of each ramp unit in the target research area based on the ramp unit data in the target research area;
Calculating the minimum Euclidean distance from the centroid of the planar vector of each slope unit to each type of data in the multi-source geographic data;
and screening slope units with the minimum Euclidean distance smaller than a distance threshold value to form the first slope unit set.
3. The method of claim 1, wherein prior to determining the geological disaster area within the target study area based on the positional relationship of the target point in the set of target points and each of the first set of ramp units, further comprising:
acquiring gradient data of the target research area based on the digital elevation model data of the target research area;
obtaining an average gradient of each ramp unit in the first ramp unit set based on gradient data of the first ramp unit set and the target study area;
screening slope units with average gradient larger than a gradient threshold value to form a second slope unit set;
the determining a geological disaster hidden danger zone in the target research zone based on the position relation between the target point in the target point set and each slope unit in the first slope unit set comprises the following steps:
and determining a geological disaster hidden danger area in the target research area based on the position relation between the target point in the target point set and each slope unit in the second slope unit set.
4. The method of claim 1, wherein the determining a geological disaster area within the target study area based on the closed vector surface comprises:
calculating the centroid of the vector surface and Euclidean distances between a plurality of target points forming the vector surface and the centroid;
judging whether an outlier exists on the vector surface according to the Euclidean distance between a plurality of target points forming the vector surface and the centroid and the magnitude relation between the Euclidean distance and a preset radius threshold;
if the vector surface does not have outliers, the area where the vector surface is located is a geological disaster hidden danger area.
5. The method according to claim 1, wherein the starting point is
Figure QLYQS_12
As a starting point, obtaining the starting point +.>
Figure QLYQS_13
Is located in the ramp unit at the target point +_with the T-th largest angle>
Figure QLYQS_14
Comprising:
acquiring a target point with a T-th maximum polar angle in polar coordinates in the target point set
Figure QLYQS_15
And obtain the target point
Figure QLYQS_16
Is +_with the starting point>
Figure QLYQS_17
Is a first linear vector of (a); wherein the polar coordinates are +.>
Figure QLYQS_18
As a starting point;
if the first linear vector does not intersect the first ramp unit set of ramp units, obtaining a starting point
Figure QLYQS_19
Is located in the ramp unit at the target point +_with the T-th largest angle>
Figure QLYQS_20
；
If the first linear vector intersects the first ramp unit set of ramp units, eliminating the target point from the target point set
Figure QLYQS_21
Obtaining a target point set after being removed;
judging whether the number of target points in the target point set after the elimination is greater than the threshold value, if so, returning to acquire the target point with the T maximum polar angle under the polar coordinates based on the target point set after the elimination
Figure QLYQS_22
And obtain the target point
Figure QLYQS_23
Is +_with the starting point>
Figure QLYQS_24
Is looped to obtain the first linear vector of +.A.A. with the starting point>
Figure QLYQS_25
Is located in the ramp unit at the target point +_with the T-th largest angle>
Figure QLYQS_26
。
6. The method according to claim 1, wherein the target point is
Figure QLYQS_27
As starting point, obtain the target point +.>
Figure QLYQS_28
Is located in the ramp unit at the target point +.>
Figure QLYQS_29
Comprising:
acquiring a target point with a t-th small polar angle in polar coordinates in the target point set
Figure QLYQS_30
And obtain the target point
Figure QLYQS_31
Is->
Figure QLYQS_32
Is defined by a first linear vector of (a); wherein the polar coordinates are +.>
Figure QLYQS_33
As a starting point;
if the second linear vector does not intersect the first ramp unit set of ramp units, obtaining a target point
Figure QLYQS_34
Is located in the ramp unit at the target point +.>
Figure QLYQS_35
；
If the second linear vector is equal to the first linear vectorThe first slope units are intersected with the slope units, and then the target point is eliminated from the target point set
Figure QLYQS_36
Obtaining a target point set after being removed;
judging whether the number of target points in the target point set after the elimination is greater than the threshold value, if so, returning to acquire the target point with the t-th small polar angle under the polar coordinates based on the target point set after the elimination
Figure QLYQS_37
And obtain the target point
Figure QLYQS_38
Is->
Figure QLYQS_39
Is looped to obtain the second line vector of the target point +.>
Figure QLYQS_40
Is located in the ramp unit at the target point +.>
Figure QLYQS_41
。
7. The method of claim 1, wherein the obtaining the set of target points within the target study area based on the time series of accumulated deformation of the target points within the target study area comprises:
carrying out trend test on the accumulated deformation time sequence of the target point in the target research area by utilizing a Mann-Kendall algorithm so as to obtain trend test data;
denoising the target point accumulated deformation time sequence in the target research area based on the trend test data so as to obtain a target point set in the target research area.
8. An electronic device comprising a memory and a processor, the memory having stored therein a computer program, the processor executing the computer program to implement the method of any of claims 1-7.
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