Building functional damage assessment method based on lifting rail InSAR (Interferometric Synthetic Aperture Radar)

Abstract

The invention belongs to the technical field of remote sensing monitoring and disaster assessment, and particularly relates to a building functional damage assessment method based on a lifting rail InSAR, which comprises the following steps: step 1, obtaining lifting rail InSAR data before and after damage and collecting damage information; 2, reconstructing and fusing a digital surface model DSM before and after damage; step 3, building change detection and quantification based on differential DSM; 4, building damage characteristic parameters are quantitatively extracted; step 5, building functionality evaluation and classification based on multi-dimensional features; and step 6, generating a building function damage assessment report. According to the method, evaluation upgrading from two-dimensional change to three-dimensional refined structure change is realized, the extracted three-dimensional geometric change characteristics are mapped to direct influence on core functions of the building, the problem of mapping from deformation to function is effectively solved, and the automation degree and objectivity of evaluation are improved.

Description

Technical Field

[0001] This invention belongs to the field of remote sensing monitoring and disaster assessment technology, specifically relating to a method for assessing the functional damage of buildings based on rising-falling orbit InSAR. Background Technology

[0002] Following disasters such as earthquakes and explosions, rapid and accurate assessment of building damage is crucial for post-disaster emergency response and reconstruction. Traditional field surveys are inefficient, dangerous, and unable to quickly grasp the overall disaster situation on a macro scale. In recent years, with the development of remote sensing technology, optical remote sensing imagery has become an important tool for disaster monitoring; however, it is susceptible to weather conditions, often failing to acquire effective data due to cloud cover and smoke during disasters.

[0003] Spaceborne synthetic aperture radar interferometry (InSAR) technology offers all-weather, 24 / 7 operation, providing a new technical approach for building damage monitoring. However, this technology currently suffers from the following limitations:

[0004] Existing methods mostly rely on SAR data from a single orbit (ascending or descending), which can only acquire damage information along the radar line of sight, making it difficult to comprehensively reflect the overall damage characteristics of buildings, especially in terms of effectively monitoring functional damage to buildings. Traditional optical remote sensing or single-dimensional deformation monitoring cannot accurately quantify the three-dimensional structural damage of buildings, especially lacking the ability to capture key information such as roof collapse and facade tilting.

[0005] Traditional methods primarily focus on monitoring surface deformation, lacking assessment models that correlate deformation information with functional damage to buildings. Existing technologies typically only provide deformation values, failing to directly translate them into an assessment of their impact on building functionality. Current methods largely remain at the level of outputting physical deformation values ​​(such as settlement), unable to directly answer core questions such as whether a building is "safe" or "usable."

[0006] Therefore, there is an urgent need in this field for an assessment method that can overcome the above-mentioned shortcomings. This method should be able to comprehensively utilize multi-source remote sensing data to achieve accurate identification and functional assessment of building damage, and provide reliable technical support for post-disaster emergency decision-making. Summary of the Invention

[0007] The purpose of this invention is to provide a building functional damage assessment method based on rising-rail InSAR. This method upgrades the assessment from two-dimensional changes to three-dimensional refined structural changes, maps the extracted three-dimensional geometric change features to the direct impact on the core functions of the building, effectively solves the mapping problem from "deformation" to "function", and improves the automation and objectivity of the assessment.

[0008] Technical solution to achieve the purpose of this invention:

[0009] A method for assessing the functional damage of buildings based on lift-orbit InSAR includes:

[0010] Step 1: Acquisition of InSAR data and collection of damage information for the elevator rails before and after damage;

[0011] Step 2: Reconstruction and fusion of digital surface models (DSM) before and after damage;

[0012] Step 3: Building change detection and quantification based on differential DSM;

[0013] Step 4: Quantitative extraction of building damage characteristic parameters;

[0014] Step 5: Functional assessment and classification of buildings based on multi-dimensional characteristics;

[0015] Step 6: Generate a building functional damage assessment report.

[0016] Further, step 1 includes:

[0017] Step 1.1, Spaceborne SAR Data Acquisition: Select satellite system data sources and choose multi-temporal SAR image data covering the target area, including: at least one ascending and one descending SAR image in the pre-disaster phase, and at least one ascending and one descending SAR image in the post-disaster phase.

[0018] Step 1.2, Data Quality Inspection and Control: Check the spatiotemporal baseline parameters of the SAR image data to ensure that they meet the requirements of interferometry; evaluate the signal-to-noise ratio and coherence of the SAR image data to ensure that the average coherence coefficient of the study area is greater than 0.3 and the signal-to-noise ratio is greater than 25dB.

[0019] Step 1.3, Damage Background Information Collection: Collect basic information about the disaster event, including the precise time of the event, the geographical coordinates of the center point, the radius of the affected area, and the type of disaster; obtain on-site investigation reports and disaster reports; and collect basic geographic information such as topographic maps and building distribution maps of the relevant areas.

[0020] Further, step 2 includes:

[0021] Step 2.1: Select a pair of spaceborne SAR images, perform interferometric processing, and obtain initial single DSM data;

[0022] Step 2.2: Small vulnerabilities in a single DSM are replaced using a triangulation interpolation algorithm;

[0023] Step 2.3: Replace the vulnerability using the riser-faller fusion method. Schematic diagram of the shadow overlay area of ​​the riser-faller DSM replacing the fallr-faller DSM.

[0024] Further, step 3 includes:

[0025] Step 3.1, Pre-disaster and post-disaster DSM accurate registration: Using the pre-disaster fused DSM as the spatial reference benchmark, a polynomial transformation model based on the least squares method is used to calculate the translation, rotation, and scaling parameters of the post-disaster DSM relative to the benchmark; the bilinear interpolation algorithm is used to resample the post-disaster DSM to ensure that the registration error between the pre-disaster DSM and the post-disaster DSM is better than 0.3 pixels.

[0026] Step 3.2, DSM Differential Calculation and Change Area Extraction: After registration is completed, perform pre-disaster and post-disaster DSM differential calculation, set a change detection threshold. If the pre-disaster and post-disaster DSM differential calculation result of a region exceeds the set change detection threshold, the region is identified as a potential change area.

[0027] Step 3.3, Post-processing optimization of differential results: Morphological filtering optimization is performed on the initially extracted change regions to obtain the optimized change detection map.

[0028] Furthermore, step 4 specifically includes:

[0029] Based on the optimized change detection map, feature parameters are extracted for each building unit, and the change information of the feature parameters is statistically analyzed and quantified. The feature parameters include: damaged area, average height change, maximum collapse depth, volume change, and roof damage rate.

[0030] Further, step 5 includes:

[0031] Step 5.1, Load-bearing function assessment: Based on the average height change ΔH_avg and the maximum collapse depth ΔH_max, assess the overall and local structural stability of the building;

[0032] Step 5.2, Envelope Function Assessment: Using the roof damage rate R_damage as the core indicator, assess the integrity and effectiveness of the roof and facade envelope system;

[0033] Step 5.3, Vertical passage function assessment: Combining the two parameters of average height change ΔH_avg and maximum collapse depth ΔH_max, focus on analyzing the deformation data of vertical traffic core areas such as staircases and elevator shafts to assess the vertical passage function of the building;

[0034] Step 5.4, Comprehensive Assessment and Grade Decision: Based on the assessment results of steps 5.1-5.3, the worst functional level is used as the final damage assessment level for the building.

[0035] Furthermore, the load-bearing function evaluation criteria in step 5.1 are as follows:

[0036] Function intact: When |ΔH_avg| ≤ 0.1 m and |ΔH_max| ≤ 0.3 m, it is determined that the overall settlement and local deformation of the building structure are within the safety allowable range, the bearing function is not significantly affected, and the structure is stable;

[0037] Function partially damaged: When 0.1 m < |ΔH_avg| ≤ 0.3 m or 0.3 m < |ΔH_max| ≤ 0.8 m, it is determined that visible damage has occurred to the main structure of the building, there may be potential safety hazards, and professional maintenance is required;

[0038] Function severely damaged: When 0.3 m < |ΔH_avg| ≤ 0.5 m or 0.8 m < |ΔH_max| ≤ 1.5 m, it is determined that serious damage has occurred to the building's bearing structure, some components may have failed, and there are significant safety hazards;

[0039] Function lost: When |ΔH_avg| > 0.5 m or |ΔH_max| > 1.5 m, it is determined that the building's bearing system has been destroyed, and the structure may collapse as a whole or locally at any time.

[0040] Furthermore, the evaluation criterion for the enclosure function in step 5.2 is as follows:

[0041] Function intact: When R_damage ≤ 5%, it is determined that the enclosure structure is basically intact, only slightly damaged, and does not affect normal use;

[0042] Function partially damaged: When 5% < R_damage ≤ 20%, it is determined that local damage has occurred to the enclosure structure, which may cause rain leakage and a decline in insulation performance, and local repair is required;

[0043] Function severely damaged: When 20% < R_damage ≤ 50%, it is determined that the enclosure structure is damaged on a large scale, its shielding and insulation functions are basically lost, and there are serious safety hazards;

[0044] Function lost: When R_damage > 50%, it is determined that the enclosure system has been completely destroyed and cannot provide any shielding function.

[0045] Furthermore, the evaluation criterion for the vertical passage function in step 5.3 is as follows:

[0046] Function intact: In the vertical transportation core area, |ΔH_avg| ≤ 0.05 m and |ΔH_max| ≤ 0.15 m, and the passage is unobstructed;

[0047] Function partially damaged: In the vertical transportation core area, 0.05 m < |ΔH_avg| ≤ 0.15 m or 0.15 m < |ΔH_max| ≤ 0.3 m, the passage is deformed, the passage is blocked, and it needs to be restricted for use after maintenance;

[0048] Severely impaired function: In the vertical transportation core area, if 0.15 meters < |ΔH_avg| ≤ 0.25 meters or 0.3 meters < |ΔH_max| ≤ 0.6 meters, the passage is severely damaged and passage is prohibited.

[0049] Loss of function: When the vertical transportation core area |ΔH_avg|>0.25 meters or |ΔH_max|>0.6 meters, the passage is completely blocked or collapsed and cannot be repaired.

[0050] Further, step 6 includes:

[0051] Step 6.1, Generation of thematic map for building damage assessment: Spatially correlate the optimized change detection map obtained in Step 3 with the damage assessment level results obtained in Step 5, use a four-color rendering system to overlay and visualize it on the post-disaster high-resolution remote sensing base map to generate a thematic map for building damage assessment.

[0052] Step 6.2, Generation of Building Damage Assessment Details: Using each building unit as a recording unit, the system integrates the quantitative feature parameters extracted in Step 4 with the damage assessment level results in Step 5 to generate a building damage assessment details table.

[0053] Step 6.3, Statistical Analysis and Conclusion of Damage in Study Area: For all buildings in the area, the number, proportion, total damaged area and average damage rate of buildings at each damage assessment level are calculated; high-risk areas are identified through cross-analysis; the overall damage level, spatial distribution characteristics and main damage patterns are summarized, and based on the statistical results, priority treatment areas, resource allocation suggestions and long-term monitoring priorities are proposed, forming a statistical analysis chapter;

[0054] Step 6.4: Generate an assessment report by integrating the thematic map of building damage assessment, detailed tables, statistical analysis of damage in the study area, and conclusions.

[0055] The beneficial technical effects of this invention are as follows:

[0056] 1. The present invention provides a building functional damage assessment method based on rising-rail InSAR, which realizes the upgrade of assessment from two-dimensional change to three-dimensional refined structural change; effectively solves the problem of single assessment dimension: traditional optical remote sensing or single-dimensional deformation monitoring is difficult to accurately quantify the three-dimensional structural damage of buildings, especially the ability to capture key information such as roof collapse and facade tilt.

[0057] 2. This invention provides a method for assessing the functional damage of buildings based on InSAR with a rising rail. It establishes an assessment model that maps the extracted three-dimensional geometric change features (such as average height change and maximum collapse depth) to the direct impact on the core functions of the building (such as load-bearing, enclosure, and vertical passage). It effectively solves the problem of mapping "deformation" to "function": existing methods mostly stop at outputting physical deformation values ​​(such as settlement) and cannot directly answer core questions such as whether the building is "safe" and "usable".

[0058] 3. The present invention provides a building functional damage assessment method based on ascending and descending orbit InSAR, which has a more comprehensive assessment dimension and higher accuracy: by fusing ascending and descending orbit InSAR data, it effectively obtains the fine change information of the building in three-dimensional space (especially in the vertical direction), overcomes the bottleneck of traditional technologies (such as optical images or single line-of-sight SAR) in the lack of height dimension information, and makes the detection of damage modes such as roof collapse and overall building settlement more accurate and reliable.

[0059] 4. This invention provides a building functional damage assessment method based on rising-rail InSAR, whose assessment conclusions offer greater decision support value: it innovatively achieves a leap from "physical deformation monitoring" to "structural functional assessment." The output is no longer an abstract deformation variable, but an intuitive functional availability conclusion (such as "no entry" or "restricted use"), directly answering the most critical questions in post-disaster emergency response and reconstruction decisions, greatly enhancing the practicality and guiding significance of the assessment results.

[0060] 5. The present invention provides a building functional damage assessment method based on rising-rail InSAR, which has a high degree of automation and significantly improved assessment efficiency: The method realizes the fully automated processing and quantitative output of the entire process from raw data to the final functional assessment report. It can quickly and in batches assess all buildings in a large area, improve efficiency, reduce risks, greatly reduce reliance on field surveys, and change the traditional mode of relying on manual on-site surveys and strong subjective judgment. It can quickly generate a global disaster map during the "golden rescue period" after a disaster, providing a scientific basis for resource allocation.

[0061] 6. The present invention provides a building functional damage assessment method based on rising-falling rail InSAR, which is highly objective and avoids subjective bias: the entire assessment process is based on quantitative algorithms and models, avoiding subjective judgment differences and uncertainties caused by factors such as experience and fatigue in traditional manual interpretation, and ensuring the consistency and objectivity of the assessment results. Attached Figure Description

[0062] Figure 1A flowchart of a building functional damage assessment method based on lift-rail InSAR provided by the present invention;

[0063] Figure 2 This invention generates a digital surface model of a building before it is damaged.

[0064] Figure 3 This is a digital surface model of a building after damage, generated by the present invention. Detailed Implementation

[0065] The present invention will now be described in further detail with reference to the accompanying drawings and embodiments.

[0066] This invention utilizes pre- and post-disaster satellite-borne SAR data from rising and falling orbits, and employs techniques such as digital surface model (DSM) calculation, rising and falling orbit DSM fusion, building three-dimensional change detection, and functional assessment to achieve automated monitoring and quantitative assessment of building damage.

[0067] like Figure 1 As shown, this invention provides a method for assessing the functional damage of buildings based on lift-orbit InSAR, specifically including the following steps:

[0068] Step 1: Acquisition of InSAR data and collection of damage information for the elevator rail before and after damage

[0069] This step mainly involves collecting the basic data required for building damage assessment. The specific implementation process is as follows:

[0070] Step 1.1: Spaceborne SAR (InSAR) Data Acquisition

[0071] (1) Select multi-temporal SAR image data covering the target area, including:

[0072] At least one up-orbit and one down-orbit SAR image from the pre-disaster phase.

[0073] At least one image each from the ascending and descending SAR images during the post-disaster phase.

[0074] (2) Data sources should preferentially be selected from satellite systems such as Sentinel-1, TerraSAR-X, and COSMO-SkyMed.

[0075] (3) Data parameter requirements:

[0076] Imaging modes: Interferometric wide-swath (IW) or stripmap mode

[0077] Polarization mode: VV polarization or dual polarization (VV+VH)

[0078] Spatial resolution: better than 10 meters

[0079] Incident angle range: 20°-45°

[0080] Data format: Single-view complex (SLC) data

[0081] Step 1.2: Data Quality Inspection and Control

[0082] (1) Check the spatiotemporal baseline parameters of the SAR image data to ensure that they meet the requirements of interferometry.

[0083] Time baseline: Pre-disaster and post-disaster data should each be controlled within 30 days.

[0084] Spatial baseline: Image pairs with a minimum distance of 200 meters are preferred.

[0085] (2) Evaluate the signal-to-noise ratio (SNR) and coherence of SAR image data

[0086] Image quality is tested using the amplitude dispersion index method.

[0087] Ensure that the average coherence coefficient of the study area is greater than 0.3 and the signal-to-noise ratio is greater than 25 dB.

[0088] Step 1.3: Collection of damage background information

[0089] (1) Collect basic information about the disaster event:

[0090] Precise time of the event (year-month-day hour:minute)

[0091] Geographic coordinates of the center point (latitude and longitude, accuracy 0.001°)

[0092] Radius of influence (unit: kilometers)

[0093] Disaster types (such as explosions, earthquakes, fires, etc.)

[0094] (2) Obtain on-site investigation reports and disaster reports

[0095] (3) Collect basic geographic information such as topographic maps and building distribution maps of the relevant areas.

[0096] Step 2: Reconstruction and Fusion of Digital Surface Models (DSM) Before and After Damage

[0097] This step mainly involves reconstructing the digital surface model of the building before and after the damage, and performing data fusion for elevation changes. The specific implementation process is as follows:

[0098] Step 2.1: Select a suitable pair of spaceborne SAR images (one main image and one auxiliary image), perform interferometric processing, and obtain the initial single DSM data.

[0099] Step 2.2: Small vulnerabilities in a single DSM are replaced using the triangulation interpolation algorithm. For vulnerabilities smaller than a certain area, the size of the small vulnerability can be set by selecting parameters. It is recommended that the selected parameters be 5 pixels in diameter in flat areas and 3 pixels in diameter in mountainous areas. Vulnerabilities with a diameter of 3 pixels in flat areas will be automatically replaced by the triangulation interpolation algorithm.

[0100] Step 2.3: Replace vulnerabilities using the ascending-orbit fusion method. This involves using the ascending-orbit data to produce a DSM supplemented with smaller vulnerabilities as a base, and replacing the vulnerabilities in the overlay areas with the descending-orbit DSM data. A schematic diagram illustrating the replacement of the shaded overlay areas of the ascending-orbit DSM with the descending-orbit DSM.

[0101] Step 3: Building Change Detection and Quantification Based on Differential DSM

[0102] This step aims to automatically identify and quantitatively assess changes in building areas by accurately comparing and analyzing the digital surface models (DSM) before and after damage. The specific implementation process includes the following four core steps:

[0103] Step 3.1 Pre- and post-disaster DSM precise registration

[0104] First, sub-pixel-level precise registration is performed on the generated pre-disaster fused DSM and post-disaster fused DSM. Using the pre-disaster fused DSM as the spatial reference, a polynomial transformation model based on the least squares method is employed. By uniformly selecting no fewer than 50 salient feature points as control points throughout the entire target area, the translation, rotation, and scaling parameters of the post-disaster DSM relative to the reference are calculated. The post-disaster DSM is then resampled using a bilinear interpolation algorithm to ensure that the registration error between the pre-disaster and post-disaster DSMs is better than 0.3 pixels, providing a precise spatial alignment basis for subsequent difference calculations.

[0105] Step 3.2: DSM Differential Calculation and Variation Region Extraction

[0106] After registration, DSM differential calculation is performed: dDSM = DSM_post - DSM_pre. Here, DSM_post represents the post-disaster DSM, and DSM_pre represents the pre-disaster DSM. In the differential result dDSM, negative values ​​indicate areas of decreased elevation (e.g., building collapse or demolition), positive values ​​indicate areas of increased elevation (e.g., new buildings or debris), and areas close to zero represent no significant change. To initially separate actual changes from noise, a change detection threshold of ±0.5 meters is set; areas where |dDSM| > 0.5 meters are identified as potential change areas.

[0107] Step 3.3: Post-processing optimization of difference results

[0108] Morphological filtering optimization was performed on the initially extracted change regions to eliminate noise and improve their morphology. First, a 3×3 circular structuring element was used for opening operations to eliminate isolated noise points with an area smaller than 9 square meters. Then, a 5×5 circular structuring element was used for closing operations to fill the internal holes of the change regions and connect fracture boundaries. To further improve the reliability of the results, a minimum change patch area of ​​30 square meters was set, filtering out pseudo-change regions smaller than this area, ultimately obtaining the optimized binarized change detection map.

[0109] Step 4: Quantitative extraction of building damage characteristic parameters

[0110] Based on the optimized change detection map, feature parameters are extracted for each individual building, and statistical and quantitative analysis of change information is performed. The feature parameters include:

[0111] Damaged area: Calculate the projected area of ​​the changing region within the outline of each building;

[0112] Mean height change: the arithmetic mean of dDSM values ​​within the statistically varying area;

[0113] Maximum collapse depth: Identifies the minimum value of dDSM within the changed area;

[0114] Volume change: The volume of elevation change in each region is calculated by integration, using the following formula: Where dDSM_i is the elevation change value of the i-th pixel, A is the ground area represented by a single pixel, and n is the number of pixels;

[0115] Roof damage rate: This is the ratio of the damaged area to the total roof area of ​​the building, expressed by the formula:

[0116] Where -0.3 meters is the threshold for roof damage, R damage is the roof damage rate; Area(dDSM<-0.3m) is the area of ​​the damaged area; Area(total) is the total area of ​​the building's roof.

[0117] Step 5: Functional assessment and classification of buildings based on multi-dimensional characteristics

[0118] This step aims to transform the quantitative damage characteristic parameters extracted in Step 4 (average height change ΔH_avg, maximum collapse depth ΔH_max, roof damage rate R_damage) into a graded assessment result of the building's key functions by evaluating the building's load-bearing function, enclosure function, and vertical passage function respectively. This directly correlates physical deformation data with the functional behavior of the building structure, ultimately outputting a damage assessment grade with clear guiding significance. The specific implementation process includes the following three core parts:

[0119] Step 5.1, Bearing capacity function assessment

[0120] The bearing capacity function is fundamental to ensuring the safety of buildings. This invention mainly evaluates the overall and local structural stability of buildings based on the average height change (ΔH_avg) and the maximum collapse depth (ΔH_max). The evaluation criteria are as follows:

[0121] Function intact: When |ΔH_avg| ≤ 0.1 m and |ΔH_max| ≤ 0.3 m, it is determined that the overall settlement and local deformation of the building structure are within the safety allowable range, the bearing capacity function is not significantly affected, and the structure is stable.

[0122] Function partially damaged: When 0.1 m < |ΔH_avg| ≤ 0.3 m or 0.3 m < |ΔH_max| ≤ 0.8 m, it is determined that visible damage has occurred to the main structure of the building, there may be potential safety hazards, and professional inspection and repair are required.

[0123] Function severely damaged: When 0.3 m < |ΔH_avg| ≤ 0.5 m or 0.8 m < |ΔH_max| ≤ 1.5 m, it is determined that serious damage has occurred to the building's bearing structure, some components may have failed, and there are significant safety hazards.

[0124] Function lost: When |ΔH_avg| > 0.5 m or |ΔH_max| > 1.5 m, it is determined that the building's bearing system has been destroyed, and the structure may collapse as a whole or locally at any time.

[0125] Step 5.2, Enclosure function assessment

[0126] The enclosure function is related to the shielding performance and use comfort of buildings. This invention uses the roof damage rate (R_damage) as the core index to evaluate the integrity and effectiveness of the roof and facade enclosure systems. The evaluation criteria are as follows:

[0127] Function intact: When R_damage ≤ 5%, it is determined that the enclosure structure is basically intact, only slightly damaged, and does not affect normal use.

[0128] Function partially damaged: When 5% < R_damage ≤ 20%, it is determined that local damage has occurred to the enclosure structure, which may cause rain leakage and a decrease in insulation performance, and local repair is required.

[0129] Function severely damaged: When 20% < R_damage ≤ 50%, it is determined that the enclosure structure is damaged on a large scale, its shielding and insulation functions are basically lost, and there are serious safety hazards.

[0130] Function lost: When R_damage > 50%, it is determined that the enclosure system has been completely destroyed and cannot provide any shielding function.

[0131] Step 5.3, Vertical Passage Function Assessment

[0132] Vertical passage functionality is crucial for ensuring the connectivity of interior spaces within a building. The evaluation of this function requires a comprehensive analysis of two parameters: average height variation (ΔH_avg) and maximum collapse depth (ΔH_max), with a focus on deformation data in core vertical circulation areas such as staircases and elevator shafts. The evaluation criteria are as follows:

[0133] Fully functional: The vertical transportation core area has |ΔH_avg|≤0.05 meters and |ΔH_max|≤0.15 meters, ensuring unobstructed passage.

[0134] Functional damage: In the vertical transportation core area, if 0.05m <|ΔH_avg|≤0.15m or 0.15m <|ΔH_max|≤0.3m, the passageway is deformed, obstructing passage. It needs to be inspected and its use restricted.

[0135] Severely impaired function: In the vertical transportation core area, if 0.15 meters < |ΔH_avg| ≤ 0.25 meters or 0.3 meters < |ΔH_max| ≤ 0.6 meters, the passage is severely damaged and passage is prohibited.

[0136] Loss of function: When the vertical transportation core area |ΔH_avg|>0.25 meters or |ΔH_max|>0.6 meters, the passage is completely blocked or collapsed and cannot be repaired.

[0137] Step 5.4: Comprehensive Assessment and Tiered Decision-Making

[0138] After independently assessing the three functions mentioned above, a conservative approach (choosing the highest possible level) is adopted for a comprehensive decision, with the worst functional level being used as the final damage assessment level for the building. The decision matrix and final output results are as follows:

[0139] Fully functional and usable: The assessment results for the three functions of load-bearing, enclosure, and vertical passage are all "fully functional".

[0140] Functional components are partially damaged and require repair before use is restricted: at least one function is assessed as "partially damaged" and no function is assessed as "severely damaged" or "lost".

[0141] Severely Impaired Function, Dangerous, No Entry: At least one function is assessed as "severely impaired," but none is assessed as "loss of function."

[0142] Functional loss, removal recommended: At least one function has been assessed as "functional loss".

[0143] Step 6: Generation of Building Functional Damage Assessment Report

[0144] This step is the final output of the workflow of this invention. Its purpose is to systematically integrate, visualize, and comprehensively interpret all the data processing, analysis, and evaluation results obtained in the preceding steps (steps 1 to 5), generating a comprehensive building functional damage assessment report that is detailed, has clear conclusions, and can directly serve post-disaster emergency command and reconstruction planning. This report is not only a summary of the condition of a single building, but also a macro-level understanding of the disaster situation in the entire assessment area. The specific implementation process includes the generation of the following three core components:

[0145] Step 6.1, Thematic Map for Building Damage Assessment

[0146] Based on the pre-disaster and post-disaster digital surface models (DSMs) obtained in step 3, the changes in building areas are automatically identified through precise registration and differential calculation (dDSM = post-disaster DSM - pre-disaster DSM). First, the differential results are thresholded (e.g., |dDSM|>0.5 meters is set as a significant change area), and the boundaries of the changed patches are optimized through morphological filtering (opening operation for noise reduction and closing operation for filling). Subsequently, the optimized changed areas are spatially correlated with the damage assessment results (functional integrity, partial damage, severe damage, and loss of function) obtained in step 5. This involves converting the optimized changed areas into planar vector files, where each polygon represents a significant changed area identified on the differential DSM, and its attribute table contains at least one unique identifier. The damage assessment results are also presented as planar vector files, with each polygon representing an independent building outline. Their attribute table contains the building's unique identifier, as well as the assessment results from step 5: independent assessment levels for load-bearing function, enclosure function, and vertical passage function, and the final comprehensive damage level. The unique identifier corresponding to each polygon in both planar vector files is used as a common attribute field, linking the contents of the two attribute tables together. Four-color rendering (e.g., green for functional integrity, yellow for partial damage, orange for severe damage, and red for loss of function) is then used to overlay and visualize the polygonal patches on a high-resolution post-disaster remote sensing base map. Finally, a thematic map is generated, including a scale bar, legend, coordinate system, and damage level description, visually displaying the spatial distribution pattern of the damage.

[0147] Step 6.2, Building Damage Assessment Details

[0148] The detailed table uses each building as a record unit, integrating the quantitative feature parameters extracted in step 4 (such as average height change ΔH_avg, maximum collapse depth ΔH_max, and roof damage rate R_damage) with the damage assessment level results from step 5. The table details include: the building's unique identifier, geographic coordinates, feature parameter values, sub-assessment results for load-bearing capacity, enclosure, and vertical access functions, the overall damage assessment level (determined based on the highest possible value), and corresponding usage recommendations (such as "fully functional and usable," "partially damaged requiring repair and restricted use," "severely damaged and hazardous, entry prohibited," and "functionally lost, demolition recommended"). All data is automatically generated through database association, ensuring consistency with spatial data, and supports filtering and exporting by damage assessment level.

[0149] Step 6.3, Statistical Analysis and Conclusion of Damage in the Study Area

[0150] A macro-level statistical analysis of the assessment results for all buildings within the region is conducted: This includes calculating the number, percentage, total damaged area, and average damage rate of buildings at each damage assessment level. High-risk areas are identified through cross-analysis (e.g., the relationship between different building structure types and damage levels). The overall damage severity, spatial distribution characteristics (e.g., damage clusters), and main damage patterns (e.g., roof collapse or facade damage as the primary cause) are summarized. Based on the statistical results, priority areas for treatment, resource allocation recommendations, and long-term monitoring priorities are proposed. The final analysis section includes data charts (e.g., pie charts, bar charts) and written conclusions.

[0151] Step 6.4: Based on the thematic map of building damage assessment, detailed tables, statistical analysis of damage in the study area, and conclusions, generate an assessment report.

[0152] The three deliverables from steps 6.1-6.3 above should be integrated into a complete assessment report, output in PDF and GIS-compatible formats. The report must include an abstract, a brief description of the methodology, thematic maps, detailed tables, statistical conclusions, and recommendations, ensuring that the content is traceable and verifiable, providing comprehensive and quantifiable scientific evidence for post-disaster decision-making.

[0153] The present invention has been described in detail above with reference to the accompanying drawings and embodiments. However, the present invention is not limited to the above embodiments, and various changes can be made within the scope of knowledge possessed by those skilled in the art without departing from the spirit of the present invention. All contents not described in detail in the present invention can be derived from existing technologies.

Claims

1. A method for assessing the functional damage of buildings based on lift-orbit InSAR, characterized in that, include: Step 1: Acquisition of InSAR data and collection of damage information for the elevator rails before and after damage; Step 2: Reconstruction and fusion of digital surface models (DSM) before and after damage; Step 3: Building change detection and quantification based on differential DSM; Step 4: Quantitative extraction of building damage characteristic parameters; Step 5: Functional assessment and classification of buildings based on multi-dimensional characteristics; Step 6: Generate a building functional damage assessment report.

2. The method for assessing functional damage to buildings based on lift-rail InSAR according to claim 1, characterized in that, Step 1 includes: Step 1.1, Spaceborne SAR Data Acquisition: Select satellite system data sources and choose multi-temporal SAR image data covering the target area, including: at least one ascending and one descending SAR image in the pre-disaster phase, and at least one ascending and one descending SAR image in the post-disaster phase. Step 1.2, Data Quality Inspection and Control: Check the spatiotemporal baseline parameters of the SAR image data to ensure that they meet the requirements of interferometry; evaluate the signal-to-noise ratio and coherence of the SAR image data to ensure that the average coherence coefficient of the study area is greater than 0.3 and the signal-to-noise ratio is greater than 25dB. Step 1.3, Collection of damage background information: Collect basic information about the disaster event, including the precise time of the event, the geographical coordinates of the center point, the radius of the affected area, and the type of disaster; obtain on-site investigation reports and disaster reports; and collect basic geographic information such as topographic maps and building distribution maps of the relevant areas.

3. The method for assessing functional damage to buildings based on lift-orbit InSAR according to claim 2, characterized in that, Step 2 includes: Step 2.1: Select a pair of spaceborne SAR images, perform interferometric processing, and obtain initial single DSM data; Step 2.2: Small vulnerabilities in a single DSM are replaced using a triangulation interpolation algorithm; Step 2.3: Replace the vulnerability using the riser-faller fusion method. Schematic diagram of the shadow overlay area of ​​the riser-faller DSM replacing the fallr-faller DSM.

4. The method for assessing functional damage to buildings based on lift-orbit InSAR according to claim 3, characterized in that, Step 3 includes: Step 3.1, Pre-disaster and post-disaster DSM accurate registration: Using the pre-disaster fused DSM as the spatial reference benchmark, a polynomial transformation model based on the least squares method is used to calculate the translation, rotation, and scaling parameters of the post-disaster DSM relative to the benchmark; the bilinear interpolation algorithm is used to resample the post-disaster DSM to ensure that the registration error between the pre-disaster DSM and the post-disaster DSM is better than 0.3 pixels. Step 3.2, DSM Differential Calculation and Change Area Extraction: After registration is completed, perform pre-disaster and post-disaster DSM differential calculation, set a change detection threshold. If the pre-disaster and post-disaster DSM differential calculation result of a region exceeds the set change detection threshold, the region is identified as a potential change area. Step 3.3, Post-processing optimization of differential results: Morphological filtering optimization is performed on the initially extracted change regions to obtain the optimized change detection map.

5. The method for assessing functional damage to buildings based on lift-rail InSAR according to claim 4, characterized in that, Step 4 specifically involves: Based on the optimized change detection map, feature parameters are extracted for each building unit, and the change information of the feature parameters is statistically analyzed and quantified. The feature parameters include: damaged area, average height change, maximum collapse depth, volume change, and roof damage rate.

6. The method for assessing functional damage to buildings based on lift-orbit InSAR according to claim 5, characterized in that, Step 5 includes: Step 5.1, Load-bearing function assessment: Based on the average height change ΔH_avg and the maximum collapse depth ΔH_max, assess the overall and local structural stability of the building; Step 5.2, Enclosure Function Assessment: Using the roof damage rate R_damage as the core index, evaluate the integrity and effectiveness of the roof and facade enclosure systems; Step 5.3, Vertical Passage Function Assessment: Considering two parameters, the comprehensive average height change ΔH_avg and the maximum collapse depth ΔH_max, focus on analyzing the deformation data of vertical traffic core areas such as stairwells and elevator shafts to evaluate the vertical passage function of the building; Step 5.4, Comprehensive Assessment and Grading Decision: Based on the assessment results of Steps 5.1 - 5.3, take the worst function level as the final damage assessment level of the building.

7. A method for assessing functional damage to buildings based on lift-rail InSAR according to claim 6, characterized in that, The load-bearing function assessment criteria in Step 5.1 are as follows: Function intact: When |ΔH_avg| ≤ 0.1 m and |ΔH_max| ≤ 0.3 m, it is determined that the overall settlement and local deformation of the building structure are within the safety allowable range, the load-bearing function is not significantly affected, and the structure is stable; Function partially damaged: When 0.1 m < |ΔH_avg| ≤ 0.3 m or 0.3 m < |ΔH_max| ≤ 0.8 m, it is determined that visible damage has occurred to the main structure of the building, there may be potential safety hazards, and professional inspection and repair are required; Function severely damaged: When 0.3 m < |ΔH_avg| ≤ 0.5 m or 0.8 m < |ΔH_max| ≤ 1.5 m, it is determined that serious damage has occurred to the building's load-bearing structure, some components may have failed, and there are significant safety hazards; Function lost: When |ΔH_avg| > 0.5 m or |ΔH_max| > 1.5 m, it is determined that the building's load-bearing system has been destroyed, and the structure may collapse as a whole or locally at any time.

8. A method for assessing functional damage to buildings based on lift-orbit InSAR according to claim 6, characterized in that, The enclosure function assessment criteria in Step 5.2 are as follows: Function intact: When R_damage ≤ 5%, it is determined that the enclosure structure is basically intact, only slightly damaged, and does not affect normal use; Function partially damaged: When 5% < R_damage ≤ 20%, it is determined that local damage has occurred to the enclosure structure, which may cause rain leakage and a decline in insulation performance, and local repairs are required; Function severely damaged: When 20% < R_damage ≤ 50%, it is determined that the enclosure structure is severely damaged, and its shielding and insulation functions are basically lost, presenting serious safety hazards; Function lost: When R_damage > 50%, it is determined that the enclosure system has been completely destroyed and cannot provide any shielding function.

9. A method for assessing functional damage to buildings based on lift-rail InSAR according to claim 6, characterized in that, The vertical passage function assessment criteria in Step 5.3 are as follows: Function intact: In the vertical traffic core area, |ΔH_avg| ≤ 0.05 m and |ΔH_max| ≤ 0.15 m, and the passage is unobstructed; Function partially damaged: In the vertical traffic core area, 0.05 m < |ΔH_avg| ≤ 0.15 m or 0.15 m < |ΔH_max| ≤ 0.3 m, the passage is deformed and the passage is blocked, and it needs to be restricted for use after repair; Function severely damaged: In the vertical traffic core area, 0.15 m < |ΔH_avg| ≤ 0.25 m or 0.3 m < |ΔH_max| ≤ 0.6 m, the passage is severely damaged and passage is prohibited; Loss of function: When the vertical transportation core area |ΔH_avg|>0.25 meters or |ΔH_max|>0.6 meters, the passage is completely blocked or collapsed and cannot be repaired.

10. A method for assessing functional damage to buildings based on lift-orbit InSAR according to claim 6, characterized in that, Step 6 includes: Step 6.1, Generation of thematic map for building damage assessment: Spatially correlate the optimized change detection map obtained in Step 3 with the damage assessment level results obtained in Step 5, use a four-color rendering system to overlay and visualize it on the post-disaster high-resolution remote sensing base map to generate a thematic map for building damage assessment. Step 6.2, Generation of Building Damage Assessment Details: Using each building unit as a recording unit, the system integrates the quantitative feature parameters extracted in Step 4 with the damage assessment level results in Step 5 to generate a building damage assessment details table. Step 6.3, Statistical Analysis and Conclusion of Damage in Study Area: For all buildings in the area, the number, proportion, total damaged area and average damage rate of buildings at each damage assessment level are calculated; high-risk areas are identified through cross-analysis; the overall damage level, spatial distribution characteristics and main damage patterns are summarized, and based on the statistical results, priority treatment areas, resource allocation suggestions and long-term monitoring priorities are proposed, forming a statistical analysis chapter; Step 6.4: Generate an assessment report by integrating the thematic map of building damage assessment, detailed tables, statistical analysis of damage in the study area, and conclusions.

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