A linear engineering route selection and exploration method, device and medium in permafrost regions

Abstract

The present application discloses a method, device and medium for route selection and investigation of linear projects in permafrost regions, relating to the technical field of permafrost exploration. The method includes: obtaining synthetic aperture radar images of the study area; performing resolution processing on the synthetic aperture radar images to obtain the surface deformation rate field of the study area; dividing the surface deformation levels based on the surface deformation rate field, conducting geological mapping and geological drilling to obtain the comprehensive characteristics of permafrost; correcting the surface deformation levels based on the comprehensive characteristics of permafrost, and obtaining the permafrost distribution range according to the corrected surface deformation levels; and performing engineering route selection based on the permafrost distribution range. The present application can overcome the deficiencies of point exploration and line exploration of permafrost, improve the accuracy and efficiency of engineering route selection and investigation, and reduce the input cost at the same time.

Description

Technical Field

[0001] This application relates to the technical field of permafrost exploration, and particularly to a route selection survey method, equipment and medium for linear projects in permafrost regions. Background Technique

[0002] Permafrost is a multiphase rock and soil mass containing ice. Under negative temperature conditions, it has good engineering properties. However, with the increase in ground temperature, the engineering properties of permafrost change rapidly. When the permafrost in the foundation melts, it will cause a large amount of deformation and even damage to buildings. A large number of engineering practice experiences show that in permafrost regions, many serious engineering problems are caused by the degradation and formation of high-ice-content permafrost. The melting of high-ice-content permafrost in the foundation will cause the foundation to lose its bearing capacity, resulting in the deformation and damage of buildings, and the formation of high-ice-content permafrost in the foundation will cause serious deformation of buildings. Especially under the background of warming and humidification, for linear projects that cross permafrost regions over long distances, in order to avoid the settlement effect of permafrost thawing, it is required to avoid areas with high-ice-content permafrost and poor permafrost phenomena as much as possible during route selection. This requires determining the planar distribution range of high-ice-content permafrost and poor permafrost phenomena through surveys during the route selection stage.

[0003] The development and distribution of permafrost are greatly affected by local factors. In addition to temperature factors, topography, ground conditions, formation lithology, water source recharge, snow cover, etc. all significantly affect the survival and state of permafrost. Sometimes local factors play a dominant role in the small time scale and space scale of permafrost, which also determines the complexity of permafrost distribution. Traditional survey techniques such as geological mapping, geophysical exploration, and geological drilling have certain limitations in large-scale route selection surveys. For example, geological mapping can only investigate the surface phenomena of permafrost, and the efficiency of large-area geological mapping is low and the accuracy is poor. 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 have been more and more engineering constructions in permafrost regions, such as railway projects, highway projects, energy and oil and gas pipeline projects, etc. Due to the complexity of permafrost distribution and the limitations of traditional survey methods, there is an urgent need to study a survey method with low cost investment and high efficiency to improve the quality and efficiency of route selection in permafrost regions. Summary of the Invention

[0004] The purpose of this application is to provide a route selection survey method, equipment and medium for linear projects in permafrost regions, which can overcome the deficiencies of point and line surveys of permafrost, and while improving the accuracy and efficiency of engineering route selection surveys, reduce the input cost.

[0005] To achieve the above purpose, this application provides the following solutions:

[0006] In the first aspect, this application provides a route selection survey method for linear projects in permafrost regions, including:

[0007] Obtain synthetic aperture radar images of the study area;

[0008] Perform resolution processing on the synthetic aperture radar images to obtain the ground surface deformation rate field of the study area;

[0009] Based on the ground surface deformation rate field, divide the ground surface deformation levels, conduct geological mapping and geological drilling to obtain the comprehensive characteristics of permafrost; the comprehensive characteristics of permafrost include the formation lithology, permafrost upper limit depth, total water content, ice content characteristics of frozen soil, and frozen soil types in different ground surface deformation areas;

[0010] Correct the ground surface deformation levels based on the comprehensive characteristics of permafrost, and obtain the permafrost distribution range according to the corrected ground surface deformation levels;

[0011] Based on the permafrost distribution range, conduct engineering route selection.

[0012] Optionally, obtaining synthetic aperture radar images of the study area includes:

[0013] Obtain the engineering route direction, and based on the route direction, determine the working range, and use the working range as the study area;

[0014] According to the terrain undulation, vegetation coverage, and slope aspect of the study area, select satellite radar images of different time phases, and obtain terrain data, satellite orbit data, and atmospheric correction data corresponding to the selected satellite radar images, and fuse them to obtain the synthetic aperture radar images.

[0015] Optionally, performing resolution processing on the synthetic aperture radar images to obtain the ground surface deformation rate field of the study area includes:

[0016] Perform preprocessing on the synthetic aperture radar images to obtain preprocessed image data;

[0017] Perform differential interferometric processing on the preprocessed image data to obtain interferometric processing data;<>

[0018] Perform ground surface deformation resolution processing on the interferometric processing data to obtain ground surface cumulative deformation amount data;

[0019] Based on the ground surface cumulative deformation amount data, obtain the ground surface deformation rate field of the study area.

[0020] Optionally, performing ground surface deformation resolution processing on the interferometric processing data to obtain ground surface cumulative deformation amount data includes:

[0021] Adopt the small baseline set interferometric measurement algorithm or the permanent scatterer interferometric algorithm to obtain the ground surface cumulative deformation amount data according to the interferometric processing data.

[0022] Optionally, preprocess the synthetic aperture radar image to obtain preprocessed image data, including:

[0023] Generate a single-look complex image based on the synthetic aperture radar image;

[0024] Perform image cropping and orbit error elimination on the single-look complex image to obtain the preprocessed image data.

[0025] Optionally, correct the surface deformation level based on the comprehensive characteristics of permafrost, and obtain the permafrost distribution range according to the corrected surface deformation level, including:

[0026] Classify permafrost based on the comprehensive characteristics of permafrost to obtain permafrost types; the permafrost types include permafrost with high ice content and permafrost with low ice content;

[0027] Correct the boundary of the surface deformation level according to the on-site investigation results, obtain the range values of the surface deformation levels corresponding to each permafrost type, and obtain the spatial distribution range of each permafrost type based on the range values.

[0028] Optionally, during the process of route selection for the project based on the permafrost distribution range, avoid the permafrost distribution range where the surface deformation rate is less than the set value.

[0029] Optionally, divide the surface deformation level based on the surface deformation rate field, including:

[0030] Decompose the surface deformation rate field using a sine deformation decomposition model to obtain the annual linear deformation rate and the seasonal periodic deformation amplitude;

[0031] Use the least squares method to fit the annual linear deformation rate and the seasonal periodic deformation amplitude to generate a result map;

[0032] Statistically calculate the mean and standard deviation of the annual linear deformation rate and the seasonal periodic deformation amplitude in the result map;

[0033] Based on the multiple relationship between the mean and the standard deviation, combine the annual linear deformation rate and the seasonal periodic deformation amplitude in different intervals to divide the surface deformation level.

[0034] In a second aspect, the present application provides a computer device, including: a memory, a processor, and a computer program stored on the memory and executable on the processor, where the processor executes the computer program to implement the steps of the above-provided linear engineering route selection and exploration method in permafrost regions.

[0035] In a third aspect, the present application provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the above-provided linear engineering route selection survey method in permafrost regions are implemented.

[0036] According to the specific embodiments provided by the present application, the present application has the following technical effects:

[0037] The present application provides a linear engineering route selection survey method, device and medium in permafrost regions. In view of the complexity of permafrost distribution and the limitations of traditional survey methods, by performing resolution processing on synthetic aperture radar images, a surface deformation rate field of the study area is obtained, and the permafrost distribution range is obtained by integrating a small amount of geological mapping and geological drilling data to complete engineering route selection. Furthermore, it can overcome the deficiencies of point and line surveys of permafrost, improve the accuracy and efficiency of engineering route selection surveys, and reduce the input cost at the same time. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings required for use in the embodiments. Obviously, the drawings in the following description are only some embodiments of the present application. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0039] Figure 1 It is a schematic flowchart of a linear engineering route selection survey method in permafrost regions provided by an embodiment of the present application;

[0040] Figure 2 It is a schematic structural diagram of a computer device provided by an embodiment of the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0041] The following will clearly and completely describe the technical solutions in the embodiments of the present application in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only some embodiments of the present application, rather than all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present application.

[0042] To make the above objects, features and advantages of the present application more obvious and understandable, the present application will be further described in detail below in conjunction with the drawings and specific embodiments.

[0043] In an exemplary embodiment, the present application provides a route selection survey method for linear projects in permafrost regions. This method is executed by a computer device, which can be specifically executed alone by a computer device such as a terminal or a server, or jointly executed by a terminal and a server. In the embodiments of the present application, this method is described by taking its application to a server as an example. As Figure 1 shown, this method includes:

[0044] Step 100: Obtain synthetic aperture radar images of the study area.

[0045] Step 101: Perform resolution processing on the synthetic aperture radar images to obtain the surface deformation rate field of the study area.

[0046] Step 102: Divide the surface deformation level based on the surface deformation rate field, conduct geological mapping and geological drilling to obtain the comprehensive characteristics of permafrost. Among them, the comprehensive characteristics of permafrost include the formation lithology, permafrost table depth, total moisture content, ice content characteristics of frozen soil, and frozen soil type in different surface deformation areas.

[0047] Step 103: Correct the surface deformation level based on the comprehensive characteristics of permafrost, and obtain the permafrost distribution range according to the corrected surface deformation level.

[0048] Step 104: Conduct route selection for the project based on the permafrost distribution range.

[0049] In another exemplary embodiment of the present application, the implementation process of step 100 includes:

[0050] Step 1001: Obtain the route direction of the project, and based on the route direction, determine the working range, and use the working range as the study area. For example, according to the geological map and optical satellite image data, delineate a buffer zone with a radius of not less than 2 km around the railway line position as the radar data acquisition area.

[0051] Step 1002: Select appropriate satellite radar images of different time phases according to the terrain undulation, vegetation coverage, and slope aspect of the study area, and obtain the corresponding terrain data, satellite orbit data, and atmospheric correction data for the selected satellite radar images, and fuse them to obtain synthetic aperture radar images. For example, according to the terrain undulation and slope aspect of the study area, preferably select ascending and descending orbit satellite synthetic aperture radar images with a C-band or longer wavelength for more than 3 years, ensure that the sampling interval is at least 1 scene / month, that is, at least 72 scenes of data are processed by interferometry. At the same time, collect the corresponding terrain data, precise orbit data, and atmospheric correction data for the area.

[0052] In another exemplary embodiment of the present application, the implementation process of step 101 includes:

[0053] Step 1011: Preprocess the Synthetic Aperture Radar (SAR) image (including generating a single-view complex image, image cropping, and orbit error removal) to obtain preprocessed image data. For example, an image located in the middle of the SAR image data is selected as a common master image to provide a unified coordinate reference system for all data, thereby obtaining a single master image and implementing single-view complex image processing.

[0054] Step 1012: Perform differential interferometry processing (including registration, interferometric combination construction, reference ellipsoid phase and terrain phase removal, filtering, and phase unwrapping) on the preprocessed image data to obtain interferometric processed data. Registration primarily refers to image registration. For example, precise registration is performed based on correlation coefficient matching. The intensity information of the common master image data is used to search for points of the same name in the data to be registered. Offset correction is performed using a quadratic polynomial. The iteration ends when the accuracy meets the 1% pixel threshold.

[0055] Furthermore, an interferometric pair combination is constructed by comprehensively considering vegetation cover and optimal temporal and spatial baselines. The temporal baseline is generally no longer than 90 days, and the spatial baseline is no longer than 180 meters. Conjugate multiplication is performed to obtain the interferometric phase map for each two time nodes, removing systematic errors in the reference ellipsoid phase and terrain phase that are unrelated to surface deformation. Filtering and phase unwrapping are then performed to reduce the effects of noise and restore the ambiguity of the interferometric phase.

[0056] Step 1013: Surface deformation calculation is performed on the interferometric data to obtain surface solution data. This involves eliminating combinations with poor interferometric effects through human-computer interaction. A small baseline set interferometry algorithm or a permanent scatterer interferometry algorithm is then used to perform high-coherence point combination and identification, remove terrain errors, remove atmospheric errors, and extract deformation phases to obtain cumulative surface deformation data.

[0057] Step 1014: Calculate the surface deformation rate field for the study area based on the accumulated surface deformation data. For example, set a coherence coefficient threshold to exclude low-reliability areas, obtain the cumulative deformation of the project area over the past three years or more, and statistically calculate the annual average surface deformation rate field for the study area, thereby accurately identifying the area with severe thaw subsidence.

[0058] In another exemplary embodiment of the present application, the process of classifying the surface deformation level based on the surface deformation rate field in step 102 can be described as follows:

[0059] After obtaining the surface deformation rate field (surface deformation data), a sine deformation decomposition model is introduced for deformation decomposition. Among them, the sine deformation decomposition model is a very effective way for deformation decomposition, especially suitable for surface deformations with obvious periodic characteristics, such as surface movements affected by temperature, precipitation, or groundwater level changes. That is to say, the sine deformation decomposition model is suitable for describing periodic seasonal oscillations, that is, the deformation characteristics of surface uplift during the general freezing period and surface subsidence during the melting period in permafrost regions. In this decomposition method, the actual total surface deformation amount is disassembled into long-term changes and periodic changes, that is, two parts: interannual linear trends and seasonal periodic deformations, so as to be able to more accurately describe the dynamic characteristics of the actual surface deformation. The sine deformation decomposition model is usually expressed as a linear function and a sine function with amplitudes and phases varying with time, and there is:

[0060] .

[0061] In the formula, is the linear deformation part, a represents the interannual linear deformation rate, a ∈ (- ), and b is the offset. represents the periodic deformation part, A represents the amplitude of the seasonal periodic deformation, A ∈ [0 ), represents the amplitude of the seasonal periodic deformation, and determines the amplitude of the periodic deformation amount fluctuation. is the frequency, reflecting the length of the period. For the freeze-thaw deformation of the permafrost annual cycle, the frequency is generally the reciprocal of 1 year. is the phase offset, used to adjust the alignment position of the waveform with the time axis. y(t) represents the output result of the sine deformation decomposition model. t represents time.

[0062] By mathematically decomposing the surface deformation rate field, the sine deformation decomposition model can extract the periodic components, and can simplify the complex deformation mode into the superposition of linear trends and periodic fluctuations. When decomposing, the least squares method is generally used for fitting, and the periodic changes are extracted from the data in the form of sine waves and separated from the long-term trends. This method analyzes the time characteristics of the data, decomposes the deformation amount at each time point into its seasonal and interannual change amounts, and can better capture the inherent periodic characteristics in the data. And the sine model has fewer parameters (interannual linear deformation rate a, offset b, amplitude A of seasonal periodic deformation, and phase offset ). Compared with other complex models, the fitting process is more concise and the calculation cost is lower. By adjusting a small number of parameters, the sine deformation decomposition model can accurately fit seasonal changes with different amplitudes and periods, and is applicable to various types of surface deformation data.

[0063] After decomposing all the ground surface deformation rate fields (i.e., deformation time series) using the above sine deformation decomposition model, the annual linear deformation rate V and seasonal periodic deformation amplitude A of each pixel are obtained, and the resulting diagrams are respectively plotted. The annual linear deformation rate and seasonal deformation amplitude in the buffer zone are obtained by inverting the ascending and descending orbit data, which respectively reflect the long-term linear deformation trend and periodic deformation amplitude of the ground surface.

[0064] Statistics are made on the mean values and standard deviations of the annual linear deformation rate V and seasonal periodic deformation amplitude A in the resulting diagrams, and are respectively represented by . Through the multiple relationship between the mean value and the standard deviation, the annual linear deformation rate and seasonal periodic deformation amplitude in different intervals are combined to conduct ground surface deformation engineering grading. When grading, the ground surface deformation levels in the buffer zone can be divided according to the rules shown in Table 1. Among them, level 1 represents a weak deformation area, and level 6 represents a strong deformation area.

[0065]

[0066] In another exemplary embodiment of the present application, in combination with the topographic and geological conditions of the site, the severely deformed areas of level 3 to level 6 obtained above are analyzed. After determining the geological mapping range, when conducting on-site geological mapping and verification in step 102, the distribution ranges of visible ground ice wedges, thermokarst subsidence, thermokarst slumps and other adverse frozen soil phenomena on the ground surface are obtained. According to the ground surface deformation level and mapping results, the range that needs geological drilling is determined, boreholes are arranged to determine the drilling hole positions, and drilling is implemented and frozen soil samples are taken for geotechnical tests. Among them, for areas with obvious deformation funnels but no obvious adverse frozen soil phenomena visible to the naked eye during on-site mapping, large-area regional thaw settlement may also occur, so geological drilling verification is also required for such areas.

[0067] Based on the above description, in practical applications, the process of conducting geological mapping based on the deformation level may include:

[0068] ① Taking the areas of deformation levels 3 to 6 as the key geological mapping range.

[0069] ② Conduct on-site geological mapping, combine high-resolution images and topographic data, and through on-site verification, exclude non-frozen soil deformation areas caused by building settlement, bedrock exposure or terrain slope exceeding 20°.

[0070] ③ Integrate the ground surface deformation level and geological mapping results, determine the distribution ranges of adverse frozen soil phenomena such as ice wedges, thermokarst subsidence, thermokarst slumps, and confirm the frozen soil deformation funnels.

[0071] Based on the above description, in practical applications, the process of conducting geological drilling based on the deformation level may include:

[0072] ①For the obtained deformation funnel, carry out borehole layout design. The boreholes should be arranged perpendicular to the deformation grade boundary. There should be boreholes at the center and the outer edge of the deformation funnel, and the boreholes can be appropriately densified in the middle to ensure that there are boreholes in different deformation grade areas as much as possible.

[0073] ②Implement drilling and take samples for geotechnical tests. Start sampling layer by layer from 0.5 m below the ground surface. When the soil layer thickness is less than 1.0 m, take 1 sample. When the soil layer thickness is greater than 1.0 m, take 1 sample per meter. Sampling should be densified near the permafrost table or when the water content changes.

[0074] According to the drilling and test results, obtain the formation lithology, permafrost table depth, total water content, ice content characteristics of permafrost, and permafrost type in different deformation grade areas.

[0075] For example, determine the name of the soil according to the drilling core logging and indoor geotechnical tests. Determine the permafrost table according to the drilling core logging. Obtain the total water content according to the water content test. According to the determined name of the soil and the obtained total water content, determine the ice content of permafrost and permafrost type (low-ice-content permafrost, multi-ice-content permafrost, rich-ice-content permafrost, saturated-ice-content permafrost, soil-containing ice layer, and pure ice layer).

[0076] Among them, because water is easy to lose after permafrost melts, an electronic balance can be set at the drilling site to weigh the drilled core in the frozen state in time to obtain the mass of the sample 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 that the total water content is w A :

[0077] w A = ( m 0 / m d - 1) × 100%.

[0078] In another exemplary embodiment of the present application, based on the distribution ranges of the above-mentioned visible ground ice cones, thermokarst subsidence, thermokarst slides and other permafrost hazards obtained, the planar distribution range of permafrost hazards can be further obtained. Based on this, the implementation process of step 103 may include:

[0079] Step 1: Verify and analyze the ice content characteristics and permafrost type of the obtained permafrost with the ground deformation grade at the location of the borehole, and correct the ground deformation grade boundary according to the on-site investigation results to obtain the corrected ground deformation grade division map.

[0080] For example, the permafrost revealed by drilling is further classified into low-ice-content permafrost (LI) and high-ice-content permafrost (HI) as shown in Table 2 according to the "Classification Standard for Rock and Soil in Railway Engineering".

[0081] Among them, low-ice-content permafrost includes slightly frozen soil (S) and moderately frozen soil (D), and high-ice-content permafrost includes richly frozen soil (F), saturated frozen soil (B), soil-ice layer (H) and pure ice layer (ICE).

[0082]

[0083] In Table 2, the total water content includes ice and unfrozen water. Salinized permafrost, peaty permafrost, humus soil, and highly plastic clay are not listed. wP is the plastic limit water content.

[0084] Step 2: On the basis of obtaining the corrected surface deformation grade of the study area, perform a matching analysis between the deformation grade and the permafrost type, and delineate the planar distribution range of high-ice-content permafrost according to the surface deformation grade corresponding to the high-ice-content permafrost for engineering route selection.

[0085] Among them, the strength of the surface deformation grade is proportional to the ice content in the soil layer, and high-ice-content permafrost generally distributes in areas with a strong surface deformation grade.

[0086] Perform a correlation analysis between the permafrost type revealed by drilling at different positions of the deformation funnel and the deformation grade, and establish a matching table (as shown in Table 3) to obtain the surface deformation grade corresponding to each permafrost type, especially the range of the surface deformation grade corresponding to the high-ice-content permafrost area.

[0087] Table 3 Matching Table of Permafrost Type and Surface Deformation Grade

[0088]

[0089] In another exemplary embodiment of the present application, during the process of engineering route selection based on the permafrost distribution range, avoid the area with a higher surface deformation grade. For example, according to the surface deformation grade division map, delineate the distribution range of high-ice-content permafrost with a surface deformation grade of three or above.

[0090] Based on the above description, the present application provides a linear engineering route selection survey method for permafrost regions based on Synthetic Aperture Radar Interferometry (InSAR) technology. Aiming at the complexity of permafrost distribution and the limitations of traditional survey methods, the present 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 planar distribution range of high-ice-content permafrost and adverse permafrost phenomena, overcoming the deficiencies of point and line surveys of permafrost, achieving large-scale area surveys, and providing an efficient, accurate and economical survey method for large-area geological route selection of linear projects in permafrost regions.

[0091] In an exemplary embodiment, a computer device is provided. The computer device can be a server or a terminal, and its internal structure diagram can be as Figure 2 shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, abbreviated 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 route selection survey data for permafrost regions. The input / output interface of the computer device is used to exchange information between the processor and external devices. The communication interface of the computer device is used to communicate with external terminals through a network connection. When the computer program is executed by the processor, it implements a linear engineering route selection survey method for permafrost regions.

[0092] Those skilled in the art can understand that Figure 2 the structure shown in

[0093] is only a block diagram of some structures 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 some components, or have different component arrangements. In an exemplary embodiment, a computer device is provided, including a memory and a processor. A computer program is stored in the memory, and when the processor executes the computer program, it implements the steps in the above method embodiments.

[0094] In an exemplary embodiment, a computer program product is provided, including a computer program which, when executed by a processor, implements the steps in the above method embodiments.

[0095] 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 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 need to comply with relevant regulations.

[0096] Those of ordinary skill in the art can understand that all or part of the processes in the above method embodiments can be completed by instructing relevant hardware through a computer program. 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 above method embodiments. Among them, any reference to a memory, database, or other medium used in the embodiments provided in this application can include at least one of non-volatile and volatile memories. 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 can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc.

[0097] The database involved in the embodiments provided in this application can include at least one of a relational database and a non-relational database. The non-relational database can include a distributed database based on blockchain, etc., and is not limited thereto. The processor involved in the embodiments provided in this application can be a general-purpose processor, a central processing unit, a graphics processing unit, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., and is not limited thereto.

[0098] The technical features of the above embodiments can be combined arbitrarily. For the sake of concise description, 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, it should be considered as the scope described in this specification.

[0099] Specific examples are used in this article to elaborate on the principles and implementation manners of the present application. The description of the above embodiments is only used to help understand the method of the present application and its core idea; at the same time, for those of ordinary skill in the art, according to the idea of the present application, there will be changes in the specific implementation manners and application scopes. In summary, the content of this specification should not be construed as a limitation on the present application.

Claims

1. A method for surveying linear engineering routes in permafrost regions, characterized in that: include: 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, upper permafrost depth, total moisture content, ice content characteristics of frozen soil and frozen soil type in different surface deformation zones; wherein, the surface deformation level is divided based on the surface deformation rate field, including: using the sinusoidal deformation decomposition model to decompose the surface deformation rate field to obtain the interannual linear deformation rate and seasonal periodic deformation amplitude; using the least squares method to fit the interannual linear deformation rate and the seasonal periodic deformation amplitude to generate a result map; statistically calculating the mean and standard deviation of the interannual linear deformation rate and the seasonal periodic deformation amplitude in the result map; based on the multiple relationship of the mean and 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; wherein, the interannual linear deformation rate and seasonal deformation amplitude in the buffer zone are obtained by inverting ascending and descending orbit data; Correcting the surface deformation level based on the comprehensive characteristics of permafrost, and obtaining the distribution range of frozen soil based on the corrected surface deformation level, including: classifying frozen soil based on the comprehensive characteristics of permafrost to obtain frozen soil types; the frozen soil types include high ice content frozen soil and low ice content frozen soil; correcting the surface deformation level boundaries based on field survey results, obtaining range values of the surface deformation level corresponding to each frozen soil type, and obtaining the spatial distribution range of each frozen soil type based on the range values; The engineering route is selected based on the permafrost distribution range.

2. The method for selecting and surveying linear engineering routes 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 determining a working scope based on the direction of the engineering line, and using 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 fused to obtain the synthetic aperture radar image.

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 interferometry processing on the pre-processed image data to obtain interferometry processing data; Performing surface deformation calculation on the interference processed data to obtain surface cumulative deformation data; The surface deformation rate field of the study area is obtained based on the surface cumulative deformation data.

4. The method for selecting and surveying linear engineering routes 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: A small baseline set interferometry algorithm or a permanent scatterer interferometry algorithm is used to obtain the surface cumulative deformation data based on the interference processing data.

5. The method for selecting and surveying linear engineering routes 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; Image cropping and track error elimination are performed on the single-view complex image to obtain the preprocessed image data.

6. 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 permafrost distribution range, the permafrost distribution range where the surface deformation rate is less than the set value is avoided.

7. 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 method for linear engineering line selection and investigation in permafrost areas according to any one of claims 1 to 6.

8. 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 selecting and surveying linear engineering routes in permafrost areas according to any one of claims 1 to 6 is implemented.

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