Permafrost region linear engineering line selection reconnaissance method, equipment and medium

Abstract

The invention discloses a permafrost region linear engineering line selection reconnaissance method and device and a medium, and relates to the technical field of permafrost exploration, and the method comprises the steps: obtaining a synthetic aperture radar image of a research region; resolving the synthetic aperture radar image to obtain an earth surface deformation rate field of the research area; dividing earth surface deformation grades based on the earth surface deformation rate field, and carrying out geological plotting and geological drilling to obtain comprehensive characteristics of permafrost; correcting the earth surface deformation grade based on the comprehensive features of the permafrost, and obtaining a permafrost distribution range according to the corrected earth surface deformation grade; and performing engineering line selection based on the frozen soil distribution range. The defects of permafrost point-shaped investigation and linear investigation can be overcome, and the investment cost is reduced while the accuracy and efficiency of engineering line selection investigation are improved.

Description

Technical Field

[0001] The present application relates to the technical field of permafrost exploration, and in particular to a linear engineering line selection and exploration method, equipment and medium in permafrost areas. Background Art

[0002] Permafrost is a multiphase rock and soil body containing ice. Under negative temperature conditions, it has good engineering properties. However, as the ground temperature rises, the engineering properties of permafrost change rapidly. When the permafrost in the foundation melts, it will cause a large amount of deformation or even damage to the building. A large amount of engineering practice experience shows that in permafrost areas, many serious engineering problems are caused by the degradation and formation of permafrost with high ice content. The melting of permafrost with high ice content in the foundation will cause the foundation to lose its bearing capacity, causing deformation and damage to the building. The formation of permafrost with high ice content in the foundation will cause serious deformation of the building. Especially under the background of warming and humidification, for linear projects that cross permafrost areas over long distances, in order to avoid the impact of thawing and settlement of permafrost, it is required to avoid areas with high ice content and unfavorable permafrost phenomena as much as possible when selecting the route. This requires that the plane distribution range of high ice content and unfavorable permafrost phenomena be determined through surveys during the route selection stage.

[0003] The development and distribution of permafrost is greatly affected by local factors. In addition to temperature factors, topography, ground conditions, stratum lithology, water supply, snow cover, etc. all significantly affect the existence and state of permafrost. Sometimes local factors even dominate the impact of permafrost on small time and spatial scales, which also determines the complexity of permafrost distribution. Traditional geological survey, geophysical exploration, geological drilling and other exploration technologies have certain limitations in large-scale line selection and exploration. For example, geological survey can only investigate the surface phenomenon of frozen soil, and large-scale geological survey has low efficiency and poor accuracy. Although geophysical exploration and geological drilling can obtain detailed characteristic indicators of permafrost, the investment cost is huge and the efficiency is low. In recent years, there are more and more engineering constructions in permafrost areas, such as railway projects, highway projects, energy oil and gas pipeline projects, etc. Due to the complexity of permafrost distribution and the limitations of traditional exploration methods, it is urgent to study a low-cost and efficient exploration method to improve the quality and efficiency of line selection in permafrost areas. Summary of the invention

[0004] The purpose of this application is to provide a linear engineering route selection survey method, equipment and medium in permafrost areas, which can overcome the shortcomings of permafrost point survey and linear survey, improve the accuracy and efficiency of engineering route selection survey, and reduce investment costs.

[0005] To achieve the above objectives, this application provides the following solutions: In a first aspect, the present application provides a method for linear engineering route selection and survey in permafrost regions, comprising: Acquire synthetic aperture radar images of the study area; The synthetic aperture radar image is processed to obtain the surface deformation rate field of the study area; Based on the surface deformation rate field, the surface deformation level is divided, and geological mapping and geological drilling are carried out to obtain the comprehensive characteristics of permafrost; the comprehensive characteristics of permafrost include the stratigraphic lithology of different surface deformation zones, the upper limit depth of permafrost, the total water content, the ice content characteristics of frozen soil and the type of frozen soil; Correcting the surface deformation level based on the comprehensive characteristics of permafrost, and obtaining the distribution range of permafrost according to the corrected surface deformation level; The engineering route is selected based on the distribution range of the frozen soil.

[0006] Optionally, obtain synthetic aperture radar imagery of the study area, including: Obtaining the direction of the engineering line, and based on the direction of the line, determining the working scope, and taking the working scope as the study area; According to the terrain undulation, vegetation coverage and slope orientation of the study area, satellite radar images of different phases are selected, and terrain data, satellite orbit data and atmospheric correction data corresponding to the selected satellite radar images are obtained, and the synthetic aperture radar image is obtained by fusion.

[0007] Optionally, the synthetic aperture radar image is processed to obtain a surface deformation rate field of the study area, including: Preprocessing the synthetic aperture radar image to obtain preprocessed image data; Performing differential interference processing on the pre-processed image data to obtain interference processing data; Performing surface deformation calculation processing on the interference processing data to obtain surface cumulative deformation data; The surface deformation rate field of the study area is obtained based on the surface accumulated deformation data.

[0008] Optionally, performing surface deformation solution processing on the interference processed data to obtain surface cumulative deformation data includes: The surface cumulative deformation data is obtained based on the interference processing data using a small baseline set interferometry algorithm or a permanent scatterer interferometry algorithm.

[0009] Optionally, preprocessing the synthetic aperture radar image to obtain preprocessed image data includes: generating a single-view complex image based on the synthetic aperture radar image; The single-view complex image is subjected to image cropping and track error elimination to obtain the preprocessed image data.

[0010] Optionally, the surface deformation level is corrected based on the comprehensive characteristics of permafrost, and the distribution range of frozen soil is obtained according to the corrected surface deformation level, including: Based on the comprehensive characteristics of permafrost, frozen soil is classified to obtain frozen soil types; the frozen soil types include high ice content frozen soil and low ice content frozen soil; The surface deformation level boundaries are corrected according to the field investigation results, the range values ​​of the surface deformation levels corresponding to each frozen soil type are obtained, and the spatial distribution range of each frozen soil type is obtained based on the range values.

[0011] Optionally, in the process of engineering route selection based on the frozen soil distribution range, the frozen soil distribution range where the surface deformation rate is less than a set value is avoided.

[0012] Optionally, the surface deformation level is divided based on the surface deformation rate field, including: The sinusoidal deformation decomposition model is used to decompose the surface deformation rate field to obtain the interannual linear deformation rate and seasonal periodic deformation amplitude. The interannual linear deformation rate and the seasonal periodic deformation amplitude are fitted by the least square method to generate a result graph; Calculate the mean and standard deviation of the interannual linear deformation rate and the seasonal periodic deformation amplitude in the result graph; Based on the multiple relationship between the mean and the standard deviation, the surface deformation level is divided in combination with the interannual linear deformation rate and the seasonal periodic deformation amplitude in different intervals.

[0013] In a second aspect, the present application provides a computer device, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the above-mentioned method for linear engineering line selection and survey in permafrost areas.

[0014] In a third aspect, the present application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the above-mentioned method for linear engineering line selection and survey in permafrost areas.

[0015] According to the specific embodiments provided in this application, this application has the following technical effects: The present application provides a linear engineering route selection and survey method, equipment and medium in permafrost areas. In view of the complexity of permafrost distribution and the limitations of traditional survey methods, the synthetic aperture radar image is solved and processed to obtain the surface deformation rate field of the study area, and a small amount of geological mapping and geological drilling data are integrated to obtain the distribution range of frozen soil, complete the engineering route selection, and thus overcome the shortcomings of permafrost point survey and linear survey, while improving the accuracy and efficiency of engineering route selection and survey, reducing investment costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0017] Figure 1 A schematic diagram of a process flow of a linear engineering route selection and survey method in permafrost regions provided in one embodiment of the present application; Figure 2 A schematic diagram of the structure of a computer device provided in one embodiment of the present application. DETAILED DESCRIPTION

[0018] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0019] In order to make the above-mentioned objects, features and advantages of the present application more obvious and easy to understand, the present application is further described in detail below in conjunction with the accompanying drawings and specific implementation methods.

[0020] In an exemplary embodiment, the present application provides a method for linear engineering route selection and survey in permafrost areas. The method is executed by a computer device, specifically, it can be executed by a computer device such as a terminal or a server alone, or it can be executed by a terminal and a server together. In the embodiment of the present application, the method is applied to a server as an example for explanation. Figure 1 As shown, the method includes: Step 100: Acquire a synthetic aperture radar image of the study area.

[0021] Step 101: Process the synthetic aperture radar image to obtain the surface deformation rate field of the study area.

[0022] Step 102: Based on the surface deformation rate field, the surface deformation level is divided, and geological mapping and geological drilling are carried out to obtain the comprehensive characteristics of permafrost. The comprehensive characteristics of permafrost include the stratigraphic lithology of different surface deformation zones, the upper limit depth of permafrost, the total water content, the ice content characteristics of frozen soil, and the type of frozen soil.

[0023] Step 103: Correct the surface deformation level based on the comprehensive characteristics of permafrost, and obtain the distribution range of permafrost according to the corrected surface deformation level.

[0024] Step 104: Select the engineering route based on the distribution range of frozen soil.

[0025] In another exemplary embodiment of the present application, the implementation process of step 100 includes: Step 1001: Obtain the direction of the project line, and determine the working scope based on the direction of the line, and use the working scope as the study area. For example, based on geological maps and optical satellite image data, a buffer zone with a radius of not less than 2 km around the railway line is defined as the radar data acquisition area.

[0026] Step 1002: According to the terrain undulation, vegetation coverage and slope orientation of the study area, appropriate satellite radar images of different phases are selected, and terrain data, satellite orbit data and atmospheric correction data corresponding to the selected satellite radar images are obtained, and synthetic aperture radar images are obtained by fusion. For example, according to the terrain undulation and slope orientation of the study area, C-band or longer-band ascending and descending satellite synthetic aperture radar images of more than 3 years are preferred, ensuring that the sampling interval is at least 1 scene / month, that is, at least 72 scenes of data are interferometrically processed. At the same time, terrain data, precise orbit data and atmospheric correction data of the corresponding area are collected.

[0027] In another exemplary embodiment of the present application, the implementation process of step 101 includes: Step 1011, preprocess the Synthetic Aperture Radar (SAR) image (including generating single-view complex images, image cropping and orbit error elimination, etc.) to obtain preprocessed image data. For example, an image located in the middle of the SAR image data is selected as a common main image to provide a unified coordinate reference system for all data, and a single main image is obtained to realize the processing of single-view complex images.

[0028] Step 1012: Perform differential interferometry processing (including registration, construction of interference combination, removal of reference ellipsoid phase and terrain phase, filtering and phase unwrapping, etc.) on the pre-processed image data to obtain interferometry processing data. Registration mainly refers to image registration, for example, precise registration based on correlation coefficient matching method, searching for the same-name points of the data to be registered using the intensity information of the public main image data, and correcting the offset using a quadratic function polynomial. The iteration ends when the accuracy meets the 1% pixel threshold standard.

[0029] Furthermore, the vegetation coverage and the optimal principle of time and space baselines are comprehensively considered to construct an interference pair combination. Among them, the time baseline is generally not more than 90 days, and the space baseline is not more than 180 meters. The interference phase map of every two time nodes is obtained by conjugate multiplication to remove the systematic errors of the reference ellipsoid phase and terrain phase that are not related to the surface deformation. Then filtering and phase unwrapping are carried out to reduce the influence of noise and restore the ambiguity of the interference phase.

[0030] Step 1013: Perform surface deformation solution processing on the interference processing data to obtain surface solution data. Among them, through human-computer interaction, the combination with poor interference effect is eliminated, and the small baseline set interferometry algorithm or permanent scatterer interferometry algorithm is used to carry out high coherence point combination and identification, remove terrain error, atmospheric error, deformation phase extraction and other processing to obtain surface cumulative deformation data.

[0031] Step 1014: Obtain the surface deformation rate field of the study area based on the surface cumulative deformation data. For example, set a coherence coefficient threshold to exclude low reliability areas, obtain the cumulative deformation of the project area in the past three years or more, and obtain the annual average surface deformation rate field of the study area to accurately identify the scope of the severe melting and subsidence area.

[0032] In another exemplary embodiment of the present application, the process of dividing the surface deformation level based on the surface deformation rate field in step 102 can be described as follows: After obtaining the surface deformation rate field (surface deformation data), the sinusoidal deformation decomposition model is introduced for deformation decomposition. Among them, the sinusoidal deformation decomposition model is a very effective way to decompose deformation, especially for surface deformation with obvious periodic characteristics, such as surface movement affected by temperature, precipitation or groundwater level changes. In other words, the sinusoidal deformation decomposition model is suitable for describing periodic seasonal oscillations, that is, the deformation characteristics of the surface uplift during the freezing period and the surface sinking during the melting period in permafrost areas. In this decomposition method, the actual total surface deformation is decomposed into long-term changes and periodic changes, namely, interannual linear trends and seasonal periodic deformations, so as to more accurately describe the dynamic characteristics of the actual surface deformation. The sinusoidal deformation decomposition model is usually expressed as a linear function and a sinusoidal function whose amplitude and phase change with time, as follows: .

[0033] In the formula, is the linear deformation part, a represents the interannual linear deformation rate, a∈(- ), b is the bias. represents the periodic deformation part, A represents the seasonal periodic deformation amplitude, A∈[0 ), represents the amplitude of seasonal periodic deformation, and determines the amplitude of periodic deformation fluctuation. is the frequency, which reflects the length of the cycle. For the freeze-thaw deformation of the frozen soil in the annual cycle, the frequency Usually the countdown of 1 year. is the phase offset, which is used to adjust the alignment of the waveform with the time axis. y(t) represents the output of the sinusoidal deformation decomposition model. t represents time.

[0034] The sinusoidal deformation decomposition model can extract periodic components by mathematically decomposing the surface deformation rate field, and can simplify complex deformation patterns into the superposition of linear trends and periodic fluctuations. When decomposing, the least squares fitting method is generally used to extract periodic changes from the data in the form of sine waves and separate them from long-term trends. This method can better capture the inherent periodic characteristics in the data by analyzing the temporal characteristics of the data and decomposing the deformation at each time point into its seasonal and interannual changes. In addition, the sinusoidal model parameters (interannual linear deformation rate a, bias b, seasonal periodic deformation amplitude A and phase offset ) are less, and the fitting process is simpler and the computational cost is lower than other complex models. By adjusting a small number of parameters, the sinusoidal deformation decomposition model can accurately fit seasonal changes of different amplitudes and periods, and is suitable for various types of surface deformation data.

[0035] After decomposing all surface deformation rate fields (i.e. deformation time series) using the above sinusoidal deformation decomposition model, the interannual linear deformation rate V and seasonal periodic deformation amplitude A of each pixel are obtained, and the results are plotted separately. The interannual linear deformation rate and seasonal deformation amplitude in the buffer zone are obtained by inverting ascending and descending orbit data, which reflect the long-term linear deformation trend and periodic deformation amplitude of the surface, respectively.

[0036] The mean and standard deviation of the interannual linear deformation rate V and seasonal periodic deformation amplitude A in the statistical results are respectively expressed as Indicates. Through the multiple relationship between the mean and the standard deviation, the interannual linear deformation rate and seasonal periodic deformation amplitude in different intervals are combined to classify the surface deformation engineering. When grading, the surface deformation level in the buffer zone can be divided according to the rules shown in Table 1. Among them, level one represents a weak deformation zone, and level six represents a strong deformation zone.

[0037] In another exemplary embodiment of the present application, the three to six levels of severe deformation areas obtained above are analyzed in combination with the topography and geological conditions of the site. After the scope of geological survey is determined, the distribution range of undesirable frozen soil phenomena such as ice cones, thermal melt subsidence, and thermal melt landslides visible to the naked eye on the surface is obtained when conducting on-site geological survey and verification in step 102. According to the surface deformation level and the survey results, the scope requiring geological drilling is determined, the drilling holes are arranged to determine the drilling hole positions, drilling is carried out, and frozen samples are taken for geotechnical tests. Among them, for areas with obvious deformation funnels but no obvious undesirable frozen soil phenomena are seen by the naked eye in on-site surveys, large-scale regional thawing settlement may also occur, so such areas also need to be verified by geological drilling.

[0038] Based on the above description, in practical application, the process of geological mapping based on deformation level may include: ① Areas with deformation levels 3 to 6 will be the focus of geological survey.

[0039] ② Carry out on-site geological surveys and mapping, combine high-resolution images and terrain data, and through on-site verification, exclude non-frozen soil deformation areas due to building settlement, exposed bedrock, or terrain slopes exceeding 20°.

[0040] ③ Integrate the surface deformation level and geological mapping results to determine the distribution range of adverse permafrost phenomena such as ice cones, thermal melt subsidence, and thermal melt landslides, and confirm the permafrost deformation funnel.

[0041] Based on the above description, in actual application, the process of geological drilling based on deformation level may include: ① Carry out hole layout design for the obtained deformation funnel. The holes should be arranged perpendicular to the deformation level boundary, and there should be holes in the center and outer edge of the deformation funnel. The holes can be appropriately increased in the middle to ensure that there are holes in different deformation level areas as much as possible.

[0042] ② Carry out drilling and sampling for geotechnical tests. Sampling shall be carried out layer by layer starting from 0.5m below the ground surface. When the soil layer thickness is less than 1.0m, one sample shall be taken. When the soil layer thickness is greater than 1.0m, one sample shall be taken for every meter. Sampling shall be increased near the upper limit of frozen soil or when the moisture content changes.

[0043] Based on the drilling and test results, the stratigraphic lithology, upper limit depth of permafrost, total water content, ice content characteristics of permafrost and permafrost type in different deformation grade areas are obtained.

[0044] For example, the name of the soil is determined based on the drilling core catalog and indoor geotechnical tests. The upper limit of permafrost is determined based on the drilling core catalog. The total moisture content is obtained based on the moisture content test. Based on the determined soil name and the obtained total moisture content, the ice content and permafrost type (little ice permafrost, more ice permafrost, rich ice permafrost, saturated ice permafrost, soil-containing ice layer and pure ice layer) are determined.

[0045] Among them, because the water is easily lost after the frozen soil melts, an electronic balance can be set up at the drilling site to weigh the drilled core in a frozen state in time to obtain the sample mass in the frozen state. m 0 , send the sample to the laboratory for drying to obtain the dry mass of the sample m d , and then determine the total moisture content is w A : w A =( m 0 / m d -1) × 100%.

[0046] In another exemplary embodiment of the present application, based on the distribution range of the above-obtained unfavorable frozen soil phenomena such as ice cones, thermal melt subsidence, thermal melt landslides, etc. visible to the naked eye, the plane distribution range of the unfavorable frozen soil phenomena can be further obtained. Based on this, the implementation process of step 103 may include: Step 1: Verify and analyze the ice content characteristics and frozen soil types of the acquired frozen soil and the surface deformation grade at the location of the borehole, and correct the surface deformation grade boundary according to the field investigation results to obtain a corrected surface deformation grade division map.

[0047] For example, the permafrost revealed by drilling is further divided into low-ice content permafrost (LI) and high-ice content permafrost (HI) as shown in Table 2 according to the "Railway Engineering Geotechnical Classification Standard".

[0048] Among them, low-ice-content frozen soil includes less-ice frozen soil (S) and more-ice frozen soil (D), and high-ice-content frozen soil includes rich-ice frozen soil (F), saturated-ice frozen soil (B), soil-containing ice layer (H) and pure ice layer (ICE).

[0049] In Table 2, the total water content includes ice and unfrozen water. Thawed saline soil, thawed peat soil, humus soil, and highly plastic clay are not listed. wP is the plastic limit water content.

[0050] Step 2: Based on the corrected surface deformation grade of the study area, the deformation grade is matched with the permafrost type for analysis. According to the surface deformation grade corresponding to the high-ice content permafrost, the plane distribution range of the high-ice content permafrost is delineated for engineering route selection.

[0051] Among them, the strength of surface deformation is proportional to the ice content in the soil layer. Areas with strong surface deformation are generally distributed with high ice content permafrost.

[0052] The permafrost types revealed by drilling at different locations in the deformation funnel were correlated with the deformation grades, and a matching table was established (as shown in Table 3) to obtain the surface deformation grades corresponding to each permafrost type, especially the range of surface deformation grades corresponding to permafrost areas with high ice content.

[0053] Table 3 Matching table of frozen soil types and surface deformation levels

[0054] In another exemplary embodiment of the present application, in the process of selecting the engineering route based on the distribution range of frozen soil, the area with higher surface deformation level is avoided. For example, according to the surface deformation level classification map, the distribution range of high ice content frozen soil with surface deformation level of level 3 or above is delineated.

[0055] Based on the above description, this application provides a linear engineering route selection survey method for permafrost areas based on Synthetic Aperture Radar Interferometry (InSAR) technology. In view of the complexity of permafrost distribution and the limitations of traditional survey methods, this application uses satellite synthetic aperture radar remote sensing technology to obtain the deformation rate field of the study area, and integrates a small amount of drilling data to obtain the plane distribution range of high ice content permafrost and unfavorable frozen soil phenomena, overcoming the shortcomings of permafrost point survey and line survey, and realizing large-scale surface survey, providing an efficient, accurate and economical survey method for large-area geological route selection of linear engineering in multi-frozen areas.

[0056] In an exemplary embodiment, a computer device is provided. The computer device may be a server or a terminal. The internal structure diagram thereof may be as follows: Figure 2 As shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, referred to as I / O) and a communication interface. Among them, the processor, the memory and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store linear engineering line selection and survey data in permafrost areas. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a linear engineering line selection and survey method for permafrost areas is implemented.

[0057] Those skilled in the art will understand that Figure 2 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components. In an exemplary embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the steps in the above-mentioned method embodiments when executing the computer program.

[0058] In an exemplary embodiment, a computer-readable storage medium is provided, storing a computer program, and when the computer program is executed by a processor, the steps in the above method embodiments are implemented.

[0059] In an exemplary embodiment, a computer program product is provided, including a computer program, and when the computer program is executed by a processor, the steps in the above method embodiments are implemented.

[0060] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.

[0061] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM may be in various forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM).

[0062] The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. The non-relational database may include a distributed database based on blockchain, etc., but is not limited thereto. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but is not limited thereto.

[0063] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0064] This article uses specific examples to illustrate the principles and implementation methods of this application. The description of the above embodiments is only used to help understand the method and core ideas of this application. At the same time, for those skilled in the art, according to the ideas of this application, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting this application.

Claims

1. A method for selecting and surveying linear engineering lines in permafrost areas, characterized in that: The linear engineering route selection survey method in permafrost areas includes: Acquire synthetic aperture radar images of the study area; The synthetic aperture radar image is processed to obtain the surface deformation rate field of the study area; Based on the surface deformation rate field, the surface deformation level is divided, and geological mapping and geological drilling are carried out to obtain the comprehensive characteristics of permafrost; the comprehensive characteristics of permafrost include the stratigraphic lithology of different surface deformation zones, the upper limit depth of permafrost, the total water content, the ice content characteristics of frozen soil and the type of frozen soil; Correcting the surface deformation level based on the comprehensive characteristics of permafrost, and obtaining the distribution range of permafrost according to the corrected surface deformation level; The engineering route is selected based on the distribution range of the frozen soil.

2. The method for selecting and surveying linear engineering lines in permafrost regions according to claim 1, characterized in that: Acquire synthetic aperture radar images of the study area, including: Obtaining the direction of the engineering line, and based on the direction of the engineering line, determining the working scope, and taking the working scope as the research area; According to the terrain undulation, vegetation coverage and slope orientation of the study area, satellite radar images of different phases are selected, and terrain data, satellite orbit data and atmospheric correction data corresponding to the selected satellite radar images are obtained, and the synthetic aperture radar image is obtained by fusion.

3. The method for selecting and surveying linear engineering routes in permafrost regions according to claim 1, characterized in that: The synthetic aperture radar image is processed to obtain the surface deformation rate field of the study area, including: Preprocessing the synthetic aperture radar image to obtain preprocessed image data; Performing differential interference processing on the pre-processed image data to obtain interference processing data; Performing surface deformation calculation processing on the interference processing data to obtain surface cumulative deformation data; The surface deformation rate field of the study area is obtained based on the surface accumulated deformation data.

4. The method for selecting and surveying linear engineering lines in permafrost regions according to claim 3, characterized in that: The interference processed data is subjected to surface deformation solution processing to obtain surface cumulative deformation data, including: The surface cumulative deformation data is obtained based on the interference processing data using a small baseline set interferometry algorithm or a permanent scatterer interferometry algorithm.

5. The method for selecting and surveying linear engineering lines in permafrost regions according to claim 3, characterized in that: Preprocessing the synthetic aperture radar image to obtain preprocessed image data includes: generating a single-view complex image based on the synthetic aperture radar image; The single-view complex image is subjected to image cropping and track error elimination to obtain the preprocessed image data.

6. The method for selecting and surveying linear engineering lines in permafrost regions according to claim 1, characterized in that: Based on the comprehensive characteristics of permafrost, the surface deformation level is corrected, and the distribution range of permafrost is obtained according to the corrected surface deformation level, including: Based on the comprehensive characteristics of permafrost, frozen soil is classified to obtain frozen soil types; the frozen soil types include high ice content frozen soil and low ice content frozen soil; The surface deformation level boundaries are corrected according to the field investigation results, the range values ​​of the surface deformation levels corresponding to each frozen soil type are obtained, and the spatial distribution range of each frozen soil type is obtained based on the range values.

7. The method for selecting and surveying linear engineering routes in permafrost regions according to claim 1, characterized in that: In the process of engineering route selection based on the frozen soil distribution range, the frozen soil distribution range where the surface deformation rate is less than the set value is avoided.

8. The method for selecting and surveying linear engineering lines in permafrost regions according to claim 1, characterized in that: The surface deformation levels are divided based on the surface deformation rate field, including: The sinusoidal deformation decomposition model is used to decompose the surface deformation rate field to obtain the interannual linear deformation rate and seasonal periodic deformation amplitude. The interannual linear deformation rate and the seasonal periodic deformation amplitude are fitted by the least square method to generate a result graph; Calculate the mean and standard deviation of the interannual linear deformation rate and the seasonal periodic deformation amplitude in the result graph; Based on the multiple relationship between the mean and the standard deviation, the surface deformation level is divided in combination with the interannual linear deformation rate and the seasonal periodic deformation amplitude in different intervals.

9. A computer device comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the linear engineering route selection and survey method for permafrost areas according to any one of claims 1 to 8.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method for linear engineering route selection and survey in permafrost areas described in any one of claims 1 to 8 is implemented.

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