Building engineering surveying and mapping method and system based on remote sensing image

Abstract

The invention relates to the technical field of artificial intelligence, in particular to a building engineering surveying and mapping method and system based on a remote sensing image, and the method comprises the following steps: obtaining a multi-temporal remote sensing image, calculating the surface height change of a building region, extracting a settlement rate in a time sequence, screening a settlement rate change region, and calculating a local settlement gradient value. And obtaining ground surface settlement characteristic parameters. According to the method, the physical characteristics of the pipeline and the soil density are combined, the deformation quantity of the pipeline is accurately calculated, the accuracy of stress monitoring of the pipeline structure is improved, on the basis of water spectral feature analysis, the water diffusion rate and the flow direction deviation are integrated, accurate identification of a water flow abnormal area is achieved, and the water flow abnormal area is identified by utilizing SAR image data. The inclination angle and the stress deformation of the building foundation are evaluated, so that the monitoring of the settlement of the building foundation has more spatial relevance, the comprehensiveness and the prediction precision of building deformation monitoring are improved through a multi-data source fusion method, and stronger data support is provided for building safety.

Description

Technical Field

[0001] The present invention relates to the technical field of artificial intelligence, and particularly to a building engineering surveying and mapping method and system based on remote sensing images. Background Art

[0002] The technical field of artificial intelligence includes technologies that use computer algorithms to analyze, learn, and reason about data to achieve automated decision-making and pattern recognition. The core content of this technical field includes deep learning, computer vision, natural language processing, and expert systems, etc., involving multiple links such as data acquisition, feature extraction, model training, and prediction and reasoning. As an important branch of artificial intelligence, computer vision identifies, classifies, and detects visual data through image processing and analysis technologies, and is widely used in multiple fields such as autonomous driving, medical image analysis, and remote sensing surveying and mapping. Relying on computer vision technology, remote sensing surveying and mapping combines remote sensing images to obtain surface information to achieve target recognition, ground object classification, and spatial data extraction.

[0003] Among them, the building engineering surveying and mapping method based on remote sensing images refers to a technical method that uses remote sensing image data to survey and map the building engineering area. This method covers the preprocessing of high-resolution remote sensing image data, the extraction of building outlines, the calculation of building feature parameters, and the reconstruction of building spatial information. Specifically, image registration is used to spatially align multi-temporal or multi-sensor remote sensing data, the building boundary is obtained through edge detection and segmentation algorithms, and the height, volume, and morphological features of the building are calculated based on 3D reconstruction technology. Further combined with geographic information system data, the spatial positioning of the building and the update of surveying and mapping data are realized to support building engineering planning and management.

[0004] In the prior art during the surveying and mapping of construction projects, the spatial information of building structures is mainly concerned, but the impacts of ground settlement, water flow diffusion, and high-stress areas of pipelines on building deformation are not fully considered, resulting in a lack of complete environmental coupling analysis for building deformation monitoring. In terms of ground settlement analysis, the changing trends of multi-temporal settlement rates and local settlement gradients are not effectively calculated, making it difficult to accurately depict the local settlement differences and the development trends of regional deformations. The pipeline safety assessment relies on static parameters and is not combined with the dynamic changes of ground settlement, leading to insufficient identification of high-stress areas of pipelines caused by ground settlement and making it difficult to timely detect the risk of pipeline damage caused by changes in settlement gradients. The water flow diffusion monitoring uses a single spectral analysis method and fails to conduct a joint analysis with ground settlement and pipeline high-stress data, restricting the identification accuracy of water flow offsets and abnormal water accumulation areas and making it difficult to accurately reflect the long-term impact of underground water flow on building structures. In terms of the assessment of building foundation deformation, the single deformation data is not comprehensively calculated with water flow anomalies, changes in settlement rates, and high-stress areas of pipelines, making the analysis of the force conditions of building foundations lack three-dimensionality and affecting the accuracy of building structure safety assessment. These limitations result in insufficient integrity in building deformation monitoring, pipeline stress analysis, and water flow anomaly detection, affecting the comprehensiveness and predictive ability of construction project surveying and mapping. Summary of the Invention

[0005] The objective of the present invention is to address the deficiencies in the prior art and propose a method and system for construction project surveying and mapping based on remote sensing images.

[0006] To achieve the above objective, the present invention adopts the following technical solutions: A method for construction project surveying and mapping based on remote sensing images, comprising the following steps:

[0007] S1: Obtain multi-temporal remote sensing images, calculate the change in the ground surface height of the building area, extract the settlement rate within the time series, screen the areas with changing settlement rates, calculate the local settlement gradient value, and obtain the ground settlement characteristic parameters;

[0008] S2: Invoke the ground settlement characteristic parameters, combine the pipeline burial depth, pipe diameter, material properties, and the density of the surrounding soil, calculate the deformation amount of the pipeline, screen the areas where the deformation amount exceeds the set deformation threshold, analyze the stress distribution of the pipeline, extract the local stress concentration characteristics, and obtain the high-stress areas of the pipeline;

[0009] S3: Invoke the high-stress areas of the pipeline, analyze the water body spectral characteristics of the regional remote sensing images, screen the areas with abnormal spectral reflections, calculate the water diffusion rate, analyze the water flow offset in combination with the flow direction distribution, screen the areas where the water flow offset exceeds the threshold, and obtain the abnormal water flow diffusion areas on the ground surface;

[0010] S4: Call the surface abnormal water flow diffusion area, combine with the millimeter-level building foundation deformation data of the SAR image, calculate the building foundation inclination angle and the local force deformation condition, extract the area with abnormal building foundation settlement rate, analyze the degree of uneven building force, calculate the structure damage index, and obtain the building foundation deformation trend.

[0011] As a further solution of the present invention, the surface settlement characteristic parameters include the settlement rate change amplitude, the settlement gradient value distribution, and the settlement difference range. The pipeline high-stress area includes the stress concentration point distribution, the high-stress area boundary, and the area with deformation amount exceeding the threshold. The surface abnormal water flow diffusion area includes the abnormal water accumulation point, the water flow deviation direction, and the spectral reflection abnormal area. The building foundation deformation trend includes the foundation inclination angle distribution, the abnormal value of the settlement rate, and the degree of uneven force.

[0012] As a further solution of the present invention, the specific steps for obtaining multi-temporal remote sensing images, calculating the surface height change of the building area, extracting the settlement rate within the time series, screening the area with settlement rate change, and calculating the local settlement gradient value to obtain the surface settlement characteristic parameters are as follows:

[0013] S101: Obtain multi-temporal remote sensing images, perform time matching and coordinate registration on the images, call the registered remote sensing images, calculate the optical and radar interference phase change values between the images, extract the elevation change information of the building area, and calculate the time change amount of the surface height of the building area based on the corresponding relationship between the elevation change information and the time series to obtain the surface height change value of the building area;

[0014] S102: Based on the surface height change value of the building area, calculate the height change rate per unit time in the order of the time series. For the calculated height change rate, use the regional statistical method to screen the change areas where the rate value exceeds the set reference value, call the rate values of the screened change areas, perform spatial distribution analysis, and obtain the area with settlement rate change;

[0015] S103: Call the area with settlement rate change, calculate the settlement rate difference between adjacent building areas within the local space range, calculate the local area settlement gradient value based on the spatial distribution of the rate difference, and extract the spatial difference value of the settlement rate within the area to obtain the surface settlement characteristic parameters.

[0016] As a further solution of the present invention, the specific steps for calling the surface settlement characteristic parameters, combining with the pipeline burial depth, pipe diameter, material properties, and the surrounding soil density, calculating the deformation amount of the pipeline, screening the areas where the deformation amount exceeds the set deformation threshold, analyzing the stress distribution of the pipeline, and extracting the local stress concentration characteristics to obtain the pipeline high-stress area are as follows:

[0017] S201: Call the surface settlement characteristic parameters, combine the buried depth, pipe diameter, material properties of the water supply pipeline and the surrounding soil density, and calculate the axial deformation of the pipeline under different settlement gradients based on the pipe force balance relationship. For the deformation data, extract the deformation values in each region, compare them with the set deformation threshold, and screen the regions where the deformation exceeds the threshold to obtain the regions with excessive deformation;

[0018] S202: Call the regions with excessive deformation, calculate the axial tensile stress, circumferential stress and shear stress for the pipe force state, and analyze the spatial distribution characteristics of the differential stress components of the pipeline in combination with the settlement direction distribution. Extract the stress concentration areas in the local area to obtain the local stress concentration characteristics of the pipeline;

[0019] S203: Call the local stress concentration characteristics of the pipeline, combine the surface settlement gradient, calculate the stress peak index of the high-stress area, and conduct spatial statistical analysis on the stress gradient values of the differential areas to obtain the high-stress areas of the pipeline.

[0020] As a further solution of the present invention, the specific steps for calling the high-stress areas of the pipeline, analyzing the water body spectral characteristics of the regional remote sensing images, screening the areas with abnormal spectral reflection, calculating the water diffusion rate, analyzing the water flow deviation in combination with the flow direction distribution, and screening the areas where the water flow deviation exceeds the threshold to obtain the areas with abnormal surface water flow diffusion are as follows:

[0021] S301: Call the high-stress areas of the pipeline, obtain the remote sensing image data in the area, detect the spectral reflection characteristics of the image, extract the water body spectral reflection signal, calculate the spectral reflectance of the differential area, and screen the areas where the spectral reflectance deviates from the typical range of the water body to obtain the areas with abnormal spectral reflection;

[0022] S302: Call the areas with abnormal spectral reflection, calculate the water diffusion rate in the area, extract the water concentration change value, and analyze the water flow movement trend of the differential area based on the spatial distribution of the diffusion rate. Screen the areas where the water flow deviation exceeds the set deviation threshold to obtain the areas with excessive water flow deviation;

[0023] S303: Call the areas with excessive water flow deviation, calculate the water accumulation index in the area, analyze the spatial variation characteristics of the water accumulation amount, screen the areas with higher water accumulation amount, and extract the areas with abnormal water flow diffusion to obtain the areas with abnormal surface water flow diffusion.

[0024] As a further solution of the present invention, the formula for the water accumulation index in the area:

[0025]

[0026] where, M w represents the water accumulation index in the area, Wi represents the moisture concentration of the i-th grid cell, A i represents the area of the i-th grid cell, H i represents the elevation value of the i-th grid cell, H i-1 represents the elevation value of the previous grid adjacent to the i-th grid. v is a tiny positive number to prevent the denominator from being zero, and n represents the total number of grid cells in the study area.

[0027] As a further solution of the present invention, the specific steps to call the surface abnormal water flow diffusion area, combine the millimeter-level building foundation deformation data of the SAR image, calculate the building foundation tilt angle and local stress deformation conditions, extract the abnormal area of the building foundation settlement rate, analyze the degree of uneven building stress, calculate the structure damage index, and obtain the building foundation deformation trend are as follows:

[0028] S401: Call the surface abnormal water flow diffusion area, combine the millimeter-level building foundation deformation data of the SAR image, calculate the tilt angle of the building foundation point position, analyze the tilt angle distribution of the differential area, extract the area where the tilt angle change rate exceeds the set reference value, and determine the spatial range of the tilt angle abnormal area to obtain the building foundation tilt abnormal area;

[0029] S402: Call the building foundation tilt abnormal area, calculate the stress deformation index of the local building foundation, extract the deformation amount of the differential building foundation, and based on the spatial distribution of the deformation amount, analyze the change of the building foundation settlement rate, screen the abnormal area of the settlement rate, and calculate the settlement rate difference of the differential area to obtain the abnormal area of the building foundation settlement rate;

[0030] S403: Call the abnormal area of the building foundation settlement rate, analyze the degree of uneven building stress, calculate the stress deviation value of the building structure, and combine the settlement rate difference of the differential area to calculate the damage trend of the building structure, extract the area where the damage trend changes significantly, and obtain the building foundation deformation trend.

[0031] As a further solution of the present invention, the specific calculation formula of the building foundation deformation amount index is:

[0032]

[0033] where D b represents the building foundation deformation amount index, Z j represents the settlement amount of the building foundation at the j-th moment, Z j-1 represents the settlement amount of the building foundation at the previous moment, T j represents the monitoring time at the j-th moment, T j-1 represents the monitoring time at the previous moment, L j represents the building foundation length of the j-th monitoring point, Φj represents the basic tilt angle of the j-th monitoring point, Φ j-1 represents the basic tilt angle of the previous monitoring point, ε is a tiny positive number to prevent the denominator from being zero, and m represents the total number of monitoring points in the study area.

[0034] As a further solution of the present invention, the method further includes;

[0035] S5: Call the deformation trend of the building foundation, combine the data of surface settlement characteristics, water flow diffusion area and pipeline high-stress area, calculate the overall deformation distribution index of the building area, screen the areas where the deformation amount exceeds the threshold, construct the building deformation mapping data, and obtain the building engineering deformation mapping result;

[0036] The building engineering deformation mapping result includes deformation distribution data, areas where the deformation amount exceeds the threshold, and building structure deformation mapping diagrams;

[0037] S501: Call the deformation trend of the building foundation, combine the data of surface settlement characteristics, water flow diffusion area and pipeline high-stress area, calculate the deformation amount of each area, and based on the spatial distribution of the deformation amount, analyze the influence of foundation settlement, pipeline stress and water flow diffusion on the building structure deformation in the building area, extract the deformation amount values of each area, and obtain the building area deformation distribution index;

[0038] S502: Call the building area deformation distribution index, screen the areas where the deformation amount exceeds the set deformation threshold, analyze the change trend of the deformation amount, calculate the deformation diffusion range of the areas exceeding the threshold, extract the building foundation stress conditions in the deformation diffusion area, and combine the deformation rate of change of the differential area to obtain the areas where the building deformation amount exceeds the limit;

[0039] S503: Call the areas where the building deformation amount exceeds the limit, calculate the spatial distribution characteristics of the deformation amount, construct the building deformation spatial mapping data, extract the deformation change trend of each building structure, integrate the deformation amount, settlement characteristics and stress influence data, establish the mapping data set of the building deformation, and obtain the building engineering deformation mapping result.

[0040] A building engineering mapping system based on remote sensing images includes:

[0041] The surface settlement characteristic extraction module obtains multi-temporal remote sensing images, calculates the surface height difference of the building area, screens the areas where the height difference exceeds the surface settlement threshold, extracts the height change rate within the time series, calculates the surface settlement rate, screens the areas where the settlement rate exceeds the surface settlement rate threshold, calculates the local settlement gradient value, screens the areas where the settlement gradient exceeds the surface settlement gradient threshold, extracts the settlement rate difference between adjacent areas, calculates the settlement difference distribution, and obtains the surface settlement characteristic parameters;

[0042] The pipeline stress assessment module calls the above-mentioned surface settlement characteristic parameters, combines the buried depth, pipe diameter, material properties of the water supply pipeline and the surrounding soil density, calculates the pipeline deformation amount, screens the areas where the deformation amount exceeds the pipeline deformation threshold, calculates the stress distribution of the pipeline, extracts the local stress concentration characteristics, calculates the areas where the local stress exceeds the pipeline stress threshold, and obtains the high-stress areas of the pipeline;

[0043] The water flow diffusion analysis module calls the above-mentioned high-stress areas of the pipeline, analyzes the water body spectral reflection characteristics of the regional remote sensing images, screens the areas with abnormal spectral reflection, calculates the water diffusion rate, screens the areas where the water diffusion rate exceeds the water flow diffusion threshold, combines the flow direction distribution to calculate the water flow offset, and screens the areas where the water flow offset exceeds the water flow offset threshold, and obtains the surface abnormal water flow diffusion area;

[0044] The building foundation deformation assessment module calls the above-mentioned surface abnormal water flow diffusion area, combines the millimeter-level building foundation deformation data of the SAR image, calculates the building foundation tilt angle, screens the areas where the tilt angle exceeds the building foundation tilt threshold, calculates the local force deformation amount, screens the areas where the local force deformation amount exceeds the building force deformation threshold, extracts the area with abnormal building foundation settlement rate, calculates the building force imbalance degree, and obtains the building foundation deformation trend;

[0045] The building deformation mapping module calls the above-mentioned building foundation deformation trend, combines the surface settlement characteristic parameters, the surface abnormal water flow diffusion area and the high-stress area of the pipeline, calculates the overall deformation distribution index of the building area, screens the areas where the deformation amount exceeds the building deformation threshold, establishes a building deformation data set, and obtains the building engineering deformation mapping result.

[0046] Compared with the prior art, the advantages and positive effects of the present invention are as follows:

[0047] In the present invention, by combining the physical characteristics of the pipeline and the soil density, the pipeline deformation amount is accurately calculated, the accuracy of pipeline structure stress monitoring is improved. Based on the analysis of water body spectral characteristics, the water diffusion rate and flow direction offset are comprehensively considered to accurately identify the abnormal water flow area. Using the data of the SAR image, the tilt angle and force deformation of the building foundation are evaluated, making the monitoring of building foundation settlement more spatially relevant. Through the multi-data source fusion method, the comprehensiveness and prediction accuracy of building deformation monitoring are improved, providing stronger data support for building safety. Description of the Drawings

[0048] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0049] Figure 1 is a schematic diagram of the step process of the present invention;

[0050] Figure 2 is a system module diagram of the present invention. Specific embodiments

[0051] The technical solutions in the present invention will be described below with reference to the accompanying drawings.

[0052] In the embodiments of the present invention, words such as "exemplarily" and "for example" are used to represent examples, illustrations or explanations. Any embodiment or design solution described as an "example" in the present invention should not be construed as being more preferred or having more advantages than other embodiments or design solutions. Rather, the use of the word "example" is intended to present concepts in a specific manner. In addition, in the embodiments of the present invention, the meaning expressed by "and / or" can be both, or either one of the two can be selected.

[0053] In the embodiments of the present invention, "image" and "picture" can sometimes be used interchangeably. It should be noted that when the difference is not emphasized, the meanings they express are the same. "(of)", "corresponding", and "corresponding" can sometimes be used interchangeably. It should be noted that when the difference is not emphasized, the meanings they express are the same.

[0054] In the embodiments of the present invention, sometimes subscripts such as W 1 may be written in a non-subscript form such as W1. When the difference is not emphasized, the meanings they express are the same.

[0055] To make the technical problems, technical solutions and advantages to be solved by the present invention clearer, the following will be described in detail with reference to the accompanying drawings and specific embodiments.

[0056] Please refer to Figure 1 , a building engineering surveying and mapping method based on remote sensing images, including the following steps:

[0057] S1: Obtain multi-temporal remote sensing images, calculate the surface height change of the building area, extract the settlement rate within the time series, screen the areas with settlement rate changes, calculate the local settlement gradient value, and extract the settlement difference to obtain the surface settlement characteristic parameters;

[0058] S2: Invoke the surface settlement characteristic parameters, combine the buried depth, pipe diameter, material properties of the water supply pipeline and the surrounding soil density, calculate the deformation of the pipeline, screen the areas where the deformation exceeds the set deformation threshold, analyze the stress distribution of the pipeline, extract the local stress concentration characteristics, and calculate the high stress data in combination with the surface settlement gradient to obtain the high stress area of the pipeline;

[0059] S3: Call the high-stress area of the pipeline, analyze the water body spectral characteristics of the remote sensing images of the area, screen the areas with abnormal spectral reflection, calculate the water diffusion rate, analyze the water flow deviation in combination with the flow direction distribution, screen the areas where the water flow deviation exceeds the set threshold, and extract the areas with abnormal water accumulation to obtain the surface abnormal water flow diffusion area;

[0060] S4: Call the surface abnormal water flow diffusion area, combine with the millimeter-level building foundation deformation data of the SAR image, calculate the building foundation tilt angle and the local stress deformation condition, extract the areas with abnormal building foundation settlement rate, and analyze the degree of uneven building stress, calculate the structural damage trend to obtain the building foundation deformation trend;

[0061] S5: Call the building foundation deformation trend, combine with the surface settlement characteristics, water flow diffusion area and pipeline high-stress area data, calculate the overall deformation distribution index of the building area, screen the areas where the deformation amount exceeds the set deformation threshold, construct the building deformation mapping data to obtain the building engineering deformation mapping result.

[0062] The surface settlement characteristic parameters include the change range of the settlement rate, the distribution of the settlement gradient value and the range of the settlement difference. The pipeline high-stress area includes the distribution of stress concentration points, the boundary of the high-stress area and the area with deformation amount exceeding the threshold. The surface abnormal water flow diffusion area includes the abnormal water accumulation points, the water flow deviation direction and the area with abnormal spectral reflection. The building foundation deformation trend includes the distribution of the foundation tilt angle, the abnormal value of the settlement rate and the degree of uneven stress. The building engineering deformation mapping result includes the deformation distribution data, the area with deformation amount exceeding the threshold and the building structure deformation mapping diagram.

[0063] The specific steps of S1 are as follows:

[0064] S101: Obtain multi-temporal remote sensing images, perform time matching and coordinate registration on the images, call the registered remote sensing images, calculate the optical and radar interference phase change values between the images, extract the elevation change information of the building area, and calculate the time change amount of the surface height of the building area based on the corresponding relationship between the elevation change information and the time series to obtain the surface height change value of the building area;

[0065] First, call the image data of different time phases, arrange them in chronological order, and establish an index to ensure the temporal continuity of the data. During this process, extract the time information of each image, calculate the time interval between images. If the time interval between adjacent images exceeds the set maximum time span, then eliminate this image to avoid the large time difference in data affecting the accuracy of analysis. Subsequently, perform coordinate registration on the images, call the georeference information of the images, including projection coordinate system parameters, datum plane, central meridian, etc., check the coordinate consistency of each image. If there are deviations, then use affine transformation to adjust the position, rotation angle, and scale of the image, and perform resampling to align the spatial coordinates of each time-phase image. Next, call the optical and radar data of the images, and separately process the optical changes and radar interferometric phase changes between images. For optical images, extract the feature points of the images and calculate the feature matching degree between images to evaluate the image registration quality. For radar images, extract the phase information of the images and calculate the phase difference between adjacent time-phase images. Subsequently, for the building areas in the images, use edge detection methods combined with set segmentation thresholds to extract the boundaries of the building areas, call the contrast information of the images to determine the optimal threshold, and perform elevation analysis on the extracted areas. Through the calculation of the phase difference, combined with the incident angle information of the radar images, convert to obtain the elevation change data of the building areas, and finally obtain the change value of the surface height of the building areas.

[0066] S102: Based on the change value of the surface height of the building area, calculate the height change rate per unit time in the order of the time series. For the calculated height change rate, use the regional statistical method to screen the change areas where the rate value exceeds the set reference value, call the rate values of the screened change areas, and perform spatial distribution analysis to obtain the settlement rate change areas;

[0067] First, extract the height change data of the building areas in all time-phase images, calculate the height change amount between adjacent time-phase images, and at the same time obtain the corresponding time interval, calculate the height change rate within each time interval. Subsequently, perform regional statistical analysis on the calculated rate data, set the reference rate value, and calculate the average rate and standard deviation of all building areas in the study area to determine the threshold of the reference rate, and screen out the change areas where the rate value exceeds this reference value. For the screened change areas, call their rate data and perform spatial distribution analysis. First, divide the study area spatially according to the set grid size, and count the distribution of rate values within each grid, calculate the average rate and rate fluctuation within the grid, and judge whether the rate change in a certain area significantly deviates from the surrounding areas. If the degree of rate deviation exceeds the set relative change threshold, then determine that this area belongs to the settlement rate change area, and finally obtain the distribution of this area.

[0068] S103: Invoke the settlement rate change area, calculate the settlement rate difference between adjacent building areas within a local spatial range, calculate the settlement gradient value of the local area based on the spatial distribution of the rate difference, and extract the spatial difference value of the settlement rate within the area to obtain the surface settlement characteristic parameters;

[0069] First, set the spatial range of local analysis, extract the settlement rate data of all building areas within this range, calculate the rate difference between adjacent building areas, and calculate the settlement gradient value within the local area based on the spatial distribution of the rate difference. During this process, invoke the geographical coordinate information of each building area and calculate the relative position relationship between building areas. For each group of adjacent building areas, calculate its settlement rate change trend, count the rate difference situation within the local area, analyze the distribution characteristics of the rate change within the area, and then calculate the spatial difference value of the settlement rate within the area. Finally, obtain the surface settlement characteristic parameters.

[0070] The specific steps of S2 are as follows:

[0071] S201: Invoke the surface settlement characteristic parameters, combine the buried depth, pipe diameter, material properties of the water supply pipeline and the surrounding soil density, and calculate the axial deformation of the pipeline under different differential settlement gradients based on the pipe force balance relationship. For the deformation data, extract the deformation values within each area and compare them with the set deformation threshold to screen the areas where the deformation exceeds the threshold to obtain the areas with excessive deformation;

[0072] Obtain the settlement gradient data, and analyze the force conditions of the pipeline under different settlement gradients by combining factors such as the buried depth, pipe diameter, material properties of the water supply pipeline and the surrounding soil density. First, extract the buried depth data of the pipeline, determine the soil layer type where the pipeline is located according to the buried depth information, and combine the soil density data to calculate the binding force of the soil around the pipeline. Invoke the pipe diameter data of the pipeline and combine the material characteristic parameters, including elastic modulus, yield strength, Poisson's ratio, etc., to calculate the deformation response of the pipeline under different axial force states. For the calculation of the deformation under different differential settlement gradients, extract the settlement rate difference between adjacent pipeline segments, calculate the relative displacement of the pipeline along the axis, and further obtain the axial strain of the pipeline. Calculate the deformation according to the strain value. Subsequently, extract the deformation values within each area and set the deformation threshold. The deformation threshold is set based on the elastic limit of the pipeline material. By statistically analyzing the historical deformation data, the deformation threshold is set to 80% of the maximum allowable deformation before the pipeline yields. Calculate the deformation within each area and compare it with this threshold to screen the areas where the deformation exceeds the threshold. Finally, obtain the areas with excessive deformation.

[0073] S202: Call the over-limit deformation variable region, calculate the axial tensile stress, hoop stress and shear stress for the stress state of the pipeline, and analyze the spatial distribution characteristics of the differential stress components of the pipeline in combination with the settlement direction distribution, extract the stress concentration areas in the local area, and obtain the local stress concentration characteristics of the pipeline;

[0074] For the stress state of the pipeline, calculate the axial tensile stress, hoop stress and shear stress. First, obtain the axial deformation of the pipeline, and calculate the axial tensile stress of the pipeline in combination with the elastic modulus of the material. Extract the hoop stress state of the pipeline, call the pipe diameter and wall thickness data, and calculate the hoop stress in combination with the internal and external load pressures. Subsequently, for the settlement environment where the pipeline is located, analyze the shear stress of the pipeline, extract the surface settlement direction distribution data, calculate the axial settlement gradient of the pipeline, and calculate the shear stress component in combination with the lateral displacement of the pipeline. For the calculated stress data, conduct spatial distribution analysis, extract the stress concentration areas in the local area, set the stress concentration judgment threshold, calculate the mean and standard deviation of the stress values in the local area, and screen out the areas where the stress is greater than the mean plus twice the standard deviation, and finally obtain the local stress concentration characteristics of the pipeline.

[0075] S203: Call the local stress concentration characteristics of the pipeline, calculate the stress peak index of the high-stress area in combination with the surface settlement gradient, and conduct spatial statistical analysis on the stress gradient values in the differential area to obtain the high-stress area of the pipeline;

[0076] Calculate the stress peak index of the high-stress area in combination with the surface settlement gradient. First, extract the maximum stress value in the stress concentration characteristic area and compare it with the yield stress of the pipeline material. Set the judgment standard for the high-stress area as the stress value exceeding 60% of the yield stress. Conduct spatial statistical analysis on the stress gradient values in the differential area, extract the stress change trend in the local area, calculate the stress change rate of adjacent areas, and count the stress gradient difference in the area. Use the grid division method to divide the pipeline along the line into equally spaced areas, calculate the stress distribution in each grid, and analyze the spatial distribution law of the stress peak, and finally obtain the high-stress area of the pipeline.

[0077] The specific steps of S3 are as follows:

[0078] S301: Call the high-stress area of the pipeline, obtain the remote sensing image data in the area, detect the spectral reflection characteristics of the image, extract the water body spectral reflection signal, calculate the spectral reflectance of the differential area, and screen out the areas where the spectral reflectance deviates from the typical range of the water body to obtain the spectral reflection abnormal area;

[0079] Obtain the remote sensing image data of the area, call the multi-spectral band information of the image, and extract the spectral reflectance characteristic data within the area. First, for the image data, select specific bands applicable to water body identification, such as visible light, near-infrared, and short-wave infrared bands, and calculate the spectral reflectance values of each pixel in the image. Subsequently, perform water body area identification on the image. Adopt the spectral threshold method. According to the spectral reflectance characteristics of typical water bodies, set the reflectance thresholds for different bands, and screen the pixel areas that conform to the water body characteristics to extract the water body spectral reflection signal. Call the extracted spectral data, calculate the spectral reflectance of different regions, analyze the spectral reflectance change trend of the differentiated regions, and compare it with the spectral reflectance range of typical water bodies. Set the typical spectral reflectance range of the water body, and screen out the regions where the spectral reflectance deviates from this range. The spectral deviation is determined based on the mean and standard deviation of the spectral reflectance. Set the deviation threshold, screen out the pixel points where the spectral reflectance deviates from the typical water body range, and aggregate them into regions to finally obtain the spectral reflectance abnormal region.

[0080] S302: Call the spectral reflectance abnormal region, calculate the moisture diffusion rate within the region, extract the moisture concentration change value, and based on the spatial distribution of the diffusion rate, analyze the water flow movement trend of the differentiated regions, and screen out the regions where the water flow deviation exceeds the set deviation threshold to obtain the water flow deviation over-limit region;

[0081] First, extract the pixel information of the spectral reflectance abnormal region, and combine with multi-temporal images to calculate the time difference of the water body spectral change. Call the water body reflectance change data, analyze the water body spectral change trend, and combine with the humidity information of the surrounding soil to infer the moisture diffusion range. For the calculation of the diffusion rate, extract the water body boundary change data, and calculate the moving distance of the water body boundary in adjacent temporal images. Combine with the time interval data to calculate the diffusion speed of the water body per unit time. Subsequently, extract the moisture concentration information of the water body region, call the thermal infrared band data in the remote sensing image, and calculate the water body evaporation rate. Combine with the evaporation effect to correct the moisture concentration change value, analyze the spatial distribution of the diffusion rate, obtain the water flow movement trend of different regions, calculate the water flow offset amount, and set the determination threshold for the water flow offset. Extract the regions where the water flow deviation exceeds the set deviation threshold to finally obtain the water flow deviation over-limit region.

[0082] S303: Call the water flow deviation over-limit region, calculate the moisture aggregation index within the region, analyze the spatial change characteristics of the moisture accumulation amount, screen out the regions with higher moisture accumulation amount, and extract the water flow diffusion abnormal region to obtain the surface abnormal water flow diffusion region;

[0083] The formula for the moisture aggregation index within the region:

[0084]

[0085] Among them, M wRepresents the moisture aggregation index in the representative area, W i Represents the moisture concentration of the i-th grid cell, A i Represents the area of the i-th grid cell, H i Represents the elevation value of the i-th grid cell, H i-1 Represents the elevation value of the previous grid adjacent to the i-th grid. v is a small positive number to prevent the denominator from being zero, and n represents the total number of grid cells in the study area:

[0086] This formula is used to calculate the moisture aggregation index M in the area w , which includes the moisture concentration W i , the area A of each region i , and the elevation difference between adjacent grids. This formula takes into account the influence of moisture concentration and regional area in the area through the form of weighted average. At the same time, the influence weight of each region is adjusted through the elevation difference to reflect the influence of terrain on the water flow distribution.

[0087] Set a specific example. Assume a simplified situation where the area consists of 3 grid cells, and the moisture concentration W, area A, and elevation H of each grid are as follows: - Grid 1: W 1 = 150 mg / L, A 1 = 500 m2, H 1 = 10 m - Grid 2: W 2 = 180 mg / L, A 2 = 600 m2, H 2 = 15 m - Grid 3: W 3 = 200 mg / L, A 3 = 550 m2, H 3 = 20 m

[0088] Set ∈ as a small value of 0.01 to avoid division by zero errors and perform the following calculations:

[0089] Calculate the contribution of the moisture aggregation index in the area between Grid 1 and Grid 2:

[0090]

[0091] Calculate the contribution of the moisture aggregation index in the area between Grid 2 and Grid 3:

[0092]

[0093] Calculate the contribution of the moisture aggregation index in the area between Grid 3 and Grid 1 (assuming periodic boundary conditions):

[0094]

[0095] Add up the above calculation results to obtain the total moisture aggregation index in the area:

[0096] M w = 14970 + 21557 + 10989 = 47516;

[0097] This result indicates that the moisture aggregation index within the given area is 47516. This value reflects the combined effect between the total moisture amount and topographic changes within the area. The larger this value, the more obvious the moisture aggregation within the area, and it may be necessary to further analyze the specific impacts of topography or other environmental factors on water flow diffusion. In addition, the association between the numerical result and the step result lies in that it directly indicates the abnormal areas of water flow diffusion that require further attention and analysis.

[0098] The specific steps of S4 are as follows:

[0099] S401: Invoke the surface abnormal water flow diffusion area, combine with the millimeter-level building foundation deformation data of the SAR image, calculate the inclination angle of the building foundation points, analyze the inclination angle distribution of the differential area, extract the areas where the inclination angle change rate exceeds the set reference value, and determine the spatial range of the inclination angle abnormal area to obtain the building foundation inclination abnormal area;

[0100] Obtain the SAR image data of this area, extract the millimeter-level deformation information of the building foundation points, invoke the deformation displacement data of the building foundation points, calculate the deformation amounts of each foundation point in the horizontal and vertical directions, and combine with the geographic coordinate information to calculate the inclination angle of the building foundation points. For the calculation of the inclination angle, extract the elevation change value and horizontal displacement value of the foundation points, and calculate the inclination angle change situation of the foundation points in different directions. Subsequently, analyze the inclination angle distribution of the differential area, extract the inclination angle data of all building foundation points, calculate the average value and standard deviation of the inclination angles within the area, set the reference inclination angle threshold, use the regional statistics method to screen out the building foundation points where the inclination angle change rate exceeds the set reference value, and aggregate them into continuous spatial areas. Finally, determine the spatial range of the inclination angle abnormal area and obtain the building foundation inclination abnormal area.

[0101] S402: Invoke the building foundation inclination abnormal area, calculate the stress and deformation index of the local building foundation, extract the deformation amounts of the differential building foundations, and based on the spatial distribution of the deformation amounts, analyze the change situation of the building foundation settlement rate, screen out the areas with abnormal settlement rates, and calculate the settlement rate difference of the differential area to obtain the building foundation settlement rate abnormal area;

[0102] The specific calculation formula for the building foundation deformation amount index is:

[0103]

[0104] where D b represents the building foundation deformation amount index, Zj represents the settlement of the building foundation at the j-th moment, Z j-1 represents the settlement of the building foundation at the previous moment, T j represents the monitoring time at the j-th moment, T j-1 represents the monitoring time at the previous moment, L j represents the length of the building foundation at the j-th monitoring point, Φ j represents the foundation inclination angle at the j-th monitoring point, Φ j-1 represents the foundation inclination angle at the previous monitoring point, ε is a small positive number to prevent the denominator from being zero, and m represents the total number of monitoring points in the research area:

[0105] This formula is used to calculate the building foundation deformation index D b , and this index is estimated by considering the combined effect of the building foundation settlement rate and the change in the inclination angle. The constituent factors of each term include the rate of change of settlement, the building length, and the change in the inclination angle, which includes the stabilization parameter ε to reduce measurement errors.

[0106] Set a specific example, considering the data of three monitoring points in an area as follows: - Monitoring point 1: settlement Z 1 = 0mm, time T 1 = 0 days, inclination angle Φ 1 = 0 degrees, length L 1 = 20m - Monitoring point 2: settlement Z 2 = 5mm, time T 2 = 10 days, inclination angle Φ 2 = 0.5 degrees, length L 2 = 20m - Monitoring point 3: settlement Z 3 = 10mm, time T 3 = 20 days, inclination angle Φ 3 = 1.0 degrees, length L 3 = 20m

[0107] To calculate the building foundation deformation index, ε = 0.01 will be set to avoid the denominator being zero.

[0108] Perform the following calculations:

[0109] Contribution from monitoring point 1 to monitoring point 2:

[0110]

[0111] Contribution from monitoring point 2 to monitoring point 3:

[0112]

[0113] Sum these contributions to obtain D b = 12.97 + 12.97 = 25.94.

[0114] This result indicates that the building foundation deformation index in the monitoring area is 25.94. This value represents the overall trend of foundation deformation, and a higher value may indicate more significant structural risks. This numerical result is directly related to the determination of the abnormal building foundation settlement rate area, indicating areas that may require attention or further structural safety assessment.

[0115] S403: Invoke the abnormal building foundation settlement rate area, analyze the degree of uneven building stress, calculate the stress deviation value of the building structure, and combine the settlement rate difference in the differentiated area to calculate the damaged trend of the building structure, extract the areas with significant changes in the damaged trend, and obtain the building foundation deformation trend;

[0116] First, extract the stress data of the building structure, calculate the stress deviation value of each building foundation point, obtain the stress distribution of the building foundation points, calculate the stress difference between adjacent points, analyze the uneven settlement of the building foundation, combine the settlement rate difference in the differentiated area, calculate the stress offset of the building structure, judge the damaged trend of the building structure, extract the areas with significant changes in the damaged trend, set the damaged trend determination threshold, and screen out the areas where the stress change exceeds the threshold, and finally obtain the building foundation deformation trend.

[0117] The specific steps of S5 are as follows:

[0118] S501: Invoke the building foundation deformation trend, combine the surface settlement characteristics, water flow diffusion area and pipeline high-stress area data, calculate the deformation amount of each area, and based on the spatial distribution of the deformation amount, analyze the influence of foundation settlement, pipeline stress and water flow diffusion on the building structure deformation in the building area, extract the deformation amount value of each area, and obtain the building area deformation distribution index;

[0119] Obtain the foundation settlement characteristic data within the building area, and combine it with the distribution of the water flow diffusion area and the pipeline high-stress area to extract the deformation data of each area. For the foundation settlement characteristics, call the surface settlement rate data, and calculate the settlement deformation of different building points. Obtain the moisture concentration change information of the water flow diffusion area, and calculate the soil moisture change caused by the water flow. Extract the force data of the pipeline high-stress area, and calculate the pipeline deformation. Subsequently, based on the spatial distribution of the deformation, call the coordinate information of the building foundation points, and calculate the deformation difference between different building foundation points, judge the continuity of the deformation in space, and analyze the influence of foundation settlement, pipeline force, and water flow diffusion on the building structure deformation within the building area. Calculate the contribution value of different factors to the building foundation deformation, and perform normalization processing to obtain the proportion weight of the influence of each factor on the deformation. Extract the deformation values of each point within the building area, and construct a deformation spatial distribution matrix, and finally obtain the building area deformation distribution index.

[0120] S502: Call the building area deformation distribution index, screen the areas where the deformation exceeds the set deformation threshold, analyze the change trend of the deformation, and calculate the deformation diffusion range of the area exceeding the threshold. Extract the building foundation force conditions within the deformation diffusion area, and combine with the deformation change rate of the differential area to obtain the building deformation over-limit area.

[0121] First, calculate the mean and standard deviation of the deformation, and set the deformation threshold. The threshold is set as the mean plus twice the standard deviation to screen the areas with abnormal deformation. Subsequently, analyze the change trend of the deformation, extract the deformation data from the images at different times, and calculate the time change rate of the deformation. For the area exceeding the threshold, calculate the deformation diffusion range, extract the deformation data of the adjacent areas, and calculate the spatial gradient value of the deformation. Screen the areas where the deformation diffusion rate exceeds the set reference value, and obtain the boundary range of the diffusion area. Extract the building foundation force conditions within the deformation diffusion area, call the foundation force data, and calculate the foundation force change rate. Analyze the areas with abnormal foundation force, and combine with the deformation change rate of the differential area to screen the areas where the deformation change rate exceeds the set threshold, and finally obtain the building deformation over-limit area.

[0122] S503: Call the building deformation over-limit area, calculate the spatial distribution characteristics of the deformation, construct the building deformation spatial mapping data, and extract the deformation change trend of each building structure. Integrate the deformation, settlement characteristics, and force influence data to establish a mapping data set of building deformation, and obtain the building engineering deformation mapping result.

[0123] First, extract the building coordinate data of the region with excessive deformation quantity, and construct a spatial interpolation model of the deformation quantity to obtain the complete spatial distribution of the deformation quantity. Subsequently, construct the spatial mapping data of the building deformation, call the deformation quantity information of the building structure points, calculate the change trend of the deformation quantity of each building structure, extract the change rate of the deformation quantity of the building structure, calculate the gradient difference of the deformation quantity between different building structures, integrate the deformation quantity, settlement characteristics and force influence data, call the historical deformation data of the building foundation, calculate the long-term settlement trend, analyze the change of the settlement rate over time, and combine the force analysis to calculate the overall stability index of the building structure. Finally, establish the mapping data set of the building deformation and obtain the mapping result of the building engineering deformation.

[0124] Please refer to Figure 2 , a building engineering surveying and mapping system based on remote sensing images, including:

[0125] The surface settlement feature extraction module obtains multi-temporal remote sensing images, calculates the surface height difference of the building area, filters out the areas where the height difference exceeds the surface settlement threshold, extracts the height change rate within the time series, calculates the surface settlement rate, filters out the areas where the settlement rate exceeds the surface settlement rate threshold, calculates the local settlement gradient value, filters out the areas where the settlement gradient exceeds the surface settlement gradient threshold, extracts the settlement rate difference between adjacent areas, calculates the settlement difference distribution, and obtains the surface settlement feature parameters;

[0126] The pipeline stress assessment module calls the surface settlement feature parameters, combines the buried depth, pipe diameter, material properties of the water supply pipeline and the surrounding soil density, calculates the pipeline deformation quantity, filters out the areas where the deformation quantity exceeds the pipeline deformation threshold, calculates the stress distribution of the pipeline, extracts the local stress concentration characteristics, calculates the areas where the local stress exceeds the pipeline stress threshold, and obtains the high-stress areas of the pipeline;

[0127] The water flow diffusion analysis module calls the high-stress areas of the pipeline, analyzes the water body spectral reflection characteristics of the regional remote sensing images, filters out the areas with abnormal spectral reflection, calculates the water diffusion rate, filters out the areas where the water diffusion rate exceeds the water flow diffusion threshold, calculates the water flow offset in combination with the flow direction distribution, filters out the areas where the water flow offset exceeds the water flow offset threshold, and obtains the surface abnormal water flow diffusion areas;

[0128] The building foundation deformation assessment module calls the surface abnormal water flow diffusion areas, combines the millimeter-level building foundation deformation data of the SAR image, calculates the building foundation inclination angle, filters out the areas where the inclination angle exceeds the building foundation inclination threshold, calculates the local force deformation quantity, filters out the areas where the local force deformation quantity exceeds the building force deformation threshold, extracts the areas with abnormal building foundation settlement rate, calculates the building force imbalance degree, and obtains the building foundation deformation trend;

[0129] The building deformation surveying and mapping module calls the deformation trend of the building foundation, combines the surface settlement characteristic parameters, the surface abnormal water flow diffusion area and the pipeline high stress area, calculates the overall deformation distribution index of the building area, screens the areas where the deformation amount exceeds the building deformation threshold, establishes a building deformation data set, and obtains the building engineering deformation surveying and mapping result.

[0130] As described above, it is only the specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present invention can easily think of changes or substitutions, which should all be covered within the protection scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claimed rights.

Claims

1. A construction engineering surveying and mapping method based on remote sensing images, characterized in that: The following steps are involved: S1: Obtain multi-temporal remote sensing images, calculate the change in the surface height of the building area, extract the settlement rate in the time series, screen the area with sedimentation rate changes, calculate the local settlement gradient value, and obtain the surface settlement characteristic parameters; S2: calling the surface settlement characteristic parameters, combining the pipeline burial depth, pipe diameter, material properties and surrounding soil density, calculating the deformation of the pipeline, screening the area where the deformation exceeds the set deformation threshold, analyzing the stress distribution of the pipeline, extracting the local stress concentration characteristics, and obtaining the high stress area of ​​the pipeline; S3: calling the high stress area of ​​the pipeline, analyzing the spectral characteristics of the water body in the regional remote sensing image, screening the spectral reflection abnormal area, calculating the water diffusion rate, analyzing the water flow deviation in combination with the flow direction distribution, screening the water flow deviation exceeding the threshold area, and obtaining the abnormal water flow diffusion area on the surface; S4: Call the abnormal surface water flow diffusion area, combine the millimeter-level building foundation deformation data of SAR images, calculate the building foundation inclination angle and local stress deformation, extract the abnormal area of ​​building foundation settlement rate, analyze the degree of building stress imbalance, calculate the structural damage index, and obtain the building foundation deformation trend.

2. The construction engineering surveying and mapping method based on remote sensing images according to claim 1 is characterized in that: The surface settlement characteristic parameters include the amplitude of change of settlement rate, the distribution of settlement gradient values ​​and the range of settlement difference; the pipeline high stress area includes the distribution of stress concentration points, the boundary of high stress area and the area of ​​super-threshold deformation; the surface abnormal water flow diffusion area includes abnormal moisture accumulation points, water flow deviation direction and spectral reflection abnormality area; the building foundation deformation trend includes the distribution of foundation inclination angle, abnormal settlement rate value and degree of force imbalance.

3. The construction engineering surveying and mapping method based on remote sensing images according to claim 1 is characterized in that: The specific steps of obtaining multi-temporal remote sensing images, calculating the change of surface height in the building area, extracting the settlement rate in the time series, screening the area of ​​settlement rate change, calculating the local settlement gradient value, and obtaining the surface settlement characteristic parameters are as follows: S101: Acquire multi-temporal remote sensing images, perform time matching and coordinate registration on the images, call the registered remote sensing images, calculate the optical and radar interference phase change values ​​between the images, extract the elevation change information of the building area, calculate the time change of the surface height of the building area based on the corresponding relationship between the elevation change information and the time series, and obtain the surface height change value of the building area; S102: Based on the surface height change value of the building area, the height change rate per unit time is calculated in a time series order, and the change area whose rate value exceeds the set reference value is screened by using a regional statistical method for the calculated height change rate, and the rate value of the screened change area is called to perform spatial distribution analysis to obtain the settlement rate change area; S103: Call the settlement rate change area, calculate the settlement rate difference between adjacent building areas within the local spatial range, calculate the settlement gradient value of the local area based on the spatial distribution of the rate difference, and extract the spatial difference value of the settlement rate in the area to obtain the surface settlement characteristic parameters.

4. The construction engineering surveying and mapping method based on remote sensing images according to claim 1 is characterized in that: The specific steps of calling the surface settlement characteristic parameters, combining the pipeline burial depth, pipe diameter, material properties and surrounding soil density, calculating the deformation of the pipeline, screening the area where the deformation exceeds the set deformation threshold, analyzing the stress distribution of the pipeline, extracting the local stress concentration characteristics, and obtaining the high stress area of ​​the pipeline are as follows: S201: calling the surface settlement characteristic parameters, combining the buried depth, pipe diameter, material properties and surrounding soil density of the water supply pipe, and based on the pipe force balance relationship, calculating the deformation of the pipe along the axial direction under the differentiated settlement gradient, extracting the deformation value in each area for the deformation data, and comparing it with the set deformation threshold, screening the area where the deformation exceeds the threshold, and obtaining the over-limit deformation area; S202: calling the over-limit deformation region, calculating the axial tensile stress, hoop stress and shear stress according to the stress state of the pipeline, and analyzing the spatial distribution characteristics of the differential stress components of the pipeline in combination with the settlement direction distribution, extracting the stress concentration area in the local area, and obtaining the local stress concentration characteristics of the pipeline; S203: Invoking the local stress concentration characteristics of the pipeline, combining with the surface settlement gradient, calculating the stress peak index of the high stress area, and performing spatial statistical analysis on the stress gradient values ​​of the differentiated areas to obtain the pipeline high stress area.

5. The construction engineering surveying and mapping method based on remote sensing images according to claim 1, characterized in that: The specific steps of calling the high stress area of ​​the pipeline, analyzing the spectral characteristics of the water body in the regional remote sensing image, screening the spectral reflection abnormal area, calculating the water diffusion rate, analyzing the water flow deviation in combination with the flow direction distribution, screening the water flow deviation exceeding the threshold area, and obtaining the abnormal surface water flow diffusion area are as follows: S301: calling the pipeline high stress area, obtaining remote sensing image data in the area, detecting the spectral reflection characteristics of the image, extracting the spectral reflection signal of the water body, calculating the spectral reflectance of the differentiated area, screening the area where the spectral reflectance deviates from the typical range of the water body, and obtaining the spectral reflection abnormality area; S302: calling the spectral reflection anomaly area, calculating the water diffusion rate in the area, extracting the water concentration change value, and analyzing the water flow movement trend in the differentiated area based on the spatial distribution of the diffusion rate, screening the area where the water flow deviation exceeds the set deviation threshold, and obtaining the water flow deviation exceeding limit area; S303: Call the water flow deviation exceeding limit area, calculate the water concentration index in the area, analyze the spatial variation characteristics of water accumulation, screen the area with higher water accumulation, and extract the water flow diffusion abnormal area to obtain the surface abnormal water flow diffusion area.

6. The construction engineering surveying and mapping method based on remote sensing images according to claim 5 is characterized in that: The moisture accumulation index formula in the area is: Among them, M w Represents the moisture accumulation index in the region, W i represents the moisture concentration of the ith grid cell, A i represents the area of ​​the ith grid cell, H i represents the elevation value of the i-th grid cell, H i-1 represents the elevation value of the previous grid adjacent to the i-th grid, ∈ is a small positive number to prevent the denominator from being zero, and n represents the total number of grids in the study area.

7. The construction engineering surveying and mapping method based on remote sensing images according to claim 1 is characterized in that: The specific steps of calling the abnormal surface water flow diffusion area, combining the millimeter-level building foundation deformation data of SAR images, calculating the building foundation inclination angle and local stress deformation, extracting the abnormal area of ​​building foundation settlement rate, analyzing the degree of building stress imbalance, calculating the structural damage index, and obtaining the building foundation deformation trend are as follows: S401: calling the abnormal surface water flow diffusion area, combining the millimeter-level building foundation deformation data of the SAR image, calculating the inclination angle of the building foundation point, analyzing the inclination angle distribution of the differentiated area, extracting the area where the inclination angle change rate exceeds the set reference value, and determining the spatial range of the inclination angle abnormal area, and obtaining the building foundation inclination abnormal area; S402: calling the abnormal area of ​​building foundation inclination, calculating the stress deformation index of the local building foundation, extracting the deformation of the differentiated building foundation, and analyzing the change of the settlement rate of the building foundation based on the spatial distribution of the deformation, screening the abnormal area of ​​settlement rate, and calculating the settlement rate difference of the differentiated area to obtain the abnormal area of ​​building foundation settlement rate; S403: calling the abnormal settlement rate area of ​​the building foundation, analyzing the degree of imbalanced force on the building, calculating the force deviation value of the building structure, and combining the settlement rate difference of the differentiated area to calculate the damage trend of the building structure, extracting the area with significant changes in the damage trend, and obtaining the deformation trend of the building foundation.

8. The construction engineering surveying and mapping method based on remote sensing images according to claim 7 is characterized in that: The specific calculation formula of the building foundation deformation index is: Among them, D b Represents the building foundation deformation index, Z j represents the settlement of the building foundation at the jth moment, Z j-1 Represents the building foundation settlement at the previous moment, T j represents the monitoring time at the jth moment, T j-1 Represents the monitoring time of the previous moment, L j represents the length of the building foundation at the jth monitoring point, Φ j represents the basic tilt angle of the jth monitoring point, Φ j-1 represents the base tilt angle of the previous monitoring point, ε is a small positive number to prevent the denominator from being zero, and m represents the total number of monitoring points in the study area.

9. The construction engineering surveying and mapping method based on remote sensing images according to claim 1, characterized in that: The method further comprises: S5: calling the deformation trend of the building foundation, combining the surface settlement characteristics, water flow diffusion area and pipeline high stress area data, calculating the overall deformation distribution index of the building area, screening the area where the deformation value exceeds the threshold, constructing the building deformation mapping data, and obtaining the deformation mapping result of the building project; The deformation mapping results of the construction project include deformation distribution data, deformation variable over-threshold area and building structure deformation mapping map; S501: calling the deformation trend of the building foundation, combining the surface settlement characteristics, water flow diffusion area and pipeline high stress area data, calculating the deformation of each area, and based on the spatial distribution of the deformation, analyzing the influence of foundation settlement, pipeline force and water flow diffusion in the building area on the deformation of the building structure, extracting the deformation value of each area, and obtaining the deformation distribution index of the building area; S502: calling the deformation distribution index of the building area, screening the area where the deformation exceeds the set deformation threshold, analyzing the change trend of the deformation, and calculating the deformation diffusion range of the area exceeding the threshold, extracting the stress condition of the building foundation in the deformation diffusion area, and combining the deformation change rate of the differentiated area to obtain the area where the building deformation exceeds the limit; S503: calling the area where the building deformation exceeds the limit, calculating the spatial distribution characteristics of the deformation, constructing the spatial mapping data of the building deformation, and extracting the deformation change trend of each building structure, integrating the deformation, settlement characteristics and force influence data, establishing the mapping data set of the building deformation, and obtaining the deformation mapping result of the construction project.

10. The construction engineering surveying and mapping system based on remote sensing images is characterized by: According to the construction engineering surveying and mapping method based on remote sensing images according to any one of claims 1 to 9, the system comprises: The surface settlement feature extraction module obtains multi-temporal remote sensing images, calculates the surface height difference of the building area, screens the area where the height difference exceeds the surface settlement threshold, extracts the height change rate in the time series, calculates the surface settlement rate, screens the area where the settlement rate exceeds the surface settlement rate threshold, calculates the local settlement gradient value, screens the area where the settlement gradient exceeds the surface settlement gradient threshold, extracts the settlement rate difference of adjacent areas, calculates the settlement difference distribution, and obtains the surface settlement feature parameters; The pipeline stress assessment module calls the surface settlement characteristic parameters, combines the buried depth, diameter, material properties and surrounding soil density of the water supply pipeline, calculates the pipeline deformation, screens the area where the deformation exceeds the pipeline deformation threshold, calculates the stress distribution of the pipeline, extracts the local stress concentration characteristics, calculates the area where the local stress exceeds the pipeline stress threshold, and obtains the pipeline high stress area; The water flow diffusion analysis module calls the high stress area of ​​the pipeline, analyzes the spectral reflection characteristics of the water body in the regional remote sensing image, screens the spectral reflection abnormal area, calculates the water diffusion rate, screens the area where the water diffusion rate exceeds the water flow diffusion threshold, calculates the water flow offset in combination with the flow direction distribution, screens the area where the water flow offset exceeds the water flow offset threshold, and obtains the abnormal water flow diffusion area on the surface; The building foundation deformation assessment module calls the abnormal surface water flow diffusion area, combines the millimeter-level building foundation deformation data of the SAR image, calculates the building foundation inclination angle, screens the area where the inclination angle exceeds the building foundation inclination threshold, calculates the local force deformation, screens the area where the local force deformation exceeds the building force deformation threshold, extracts the abnormal building foundation settlement rate area, calculates the building force imbalance, and obtains the building foundation deformation trend; The building deformation mapping module calls the deformation trend of the building foundation, combines the surface settlement characteristic parameters, the surface abnormal water flow diffusion area and the pipeline high stress area, calculates the overall deformation distribution index of the building area, screens the area where the deformation value exceeds the building deformation threshold, establishes the building deformation data set, and obtains the deformation mapping result of the construction project.

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