A method and system for detecting changes in the earth's surface

Abstract

This application relates to the field of land surface detection, and in particular to a method and system for detecting land surface changes. The method includes: acquiring remote sensing images from different periods via remote sensing satellites; preprocessing the remote sensing images; registering the processed remote sensing images based on operational data; comparing remote sensing images from different times and extracting target areas where changes have occurred; acquiring geographic base map vector data and change vector types, matching them with the target areas, and generating a first change result; comparing land surface construction conditions captured by cameras at different time periods to generate a second change result; and generating a land surface change result based on the first and second change results. This application uses land surface images captured by remote sensing satellites and cameras, comparing images from different times to detect whether land surface changes have occurred, reducing the burden of manual inspections and increasing detection efficiency.

Description

Technical Field

[0001] This application relates to the field of surface detection, and in particular to a method and system for detecting surface changes. Background Technology

[0002] As the world's most populous country, my country's large population dictates a long-term strategy of prioritizing public transportation development. To alleviate the pressure on my country's public transportation, the development of subways is imperative. However, since subways are built underground and the geological conditions are complex, unannounced overloading incidents have frequently occurred in suburban tunnels in recent years, which may cause cracks in the subway tunnels and pose significant safety hazards to their safe operation.

[0003] In related technologies, the inspection of surface changes along subway lines is currently mainly carried out by manual inspection. By manually inspecting the subway surface, changes that occur on the subway surface are reported and dealt with in a timely manner to ensure the safe operation of the subway.

[0004] Regarding the aforementioned technologies, the inventors believe that manually inspecting the ground along subway lines presents problems of high workload, large investment, and low efficiency. Summary of the Invention

[0005] To reduce the burden of manual inspections and improve monitoring efficiency, this application provides a method and system for monitoring the surface along subway lines.

[0006] The surface monitoring method and system provided in this application adopt the following technical solution:

[0007] A method for monitoring land surface changes includes acquiring remote sensing images from different periods using remote sensing satellites;

[0008] The remote sensing images are preprocessed;

[0009] The processed remote sensing images are registered based on business data;

[0010] Compare remote sensing images from different times and extract the target areas that have changed;

[0011] Obtain geographic base map vector data and change vector types, match them with the target area, and generate the first change result;

[0012] By comparing the surface construction conditions captured by cameras at different time periods, a second change result is generated.

[0013] Based on the first and second change results, the land surface change results are generated.

[0014] By adopting the above technical solution, after acquiring images of the subway line surface at different times through remote sensing satellites, the acquired images are preprocessed, and the processed images are registered with operational data to determine the monitoring range. Then, images from different time periods within the monitoring range are compared to extract areas that have changed. These areas are then matched with geographic base map vector data and change vector types to determine the specific location and type of change on the surface, generating a first change result. A second change result is then obtained by combining the engineering data captured by surface cameras. The first and second change results are combined to jointly determine the changes that have occurred on the surface. When changes occur along the subway line, images captured by satellites and some cameras installed along the surface are processed and compared to determine the changes and their locations. This eliminates the need for manual surface inspections and improves detection efficiency.

[0015] Optionally, preprocessing the remote sensing image includes:

[0016] Acquire raw images taken by remote sensing satellites;

[0017] The original images are then subjected to radiometric calibration, atmospheric correction, orthorectification, and image fusion.

[0018] By adopting the above technical solutions, the photos taken by remote sensing satellites are not very clear due to the influence of various factors. Radiometric positioning is performed on the original images, and the brightness gray values ​​in the image are converted into absolute radiometric values ​​so that the two images can be compared. Atmospheric correction is performed to accurately obtain the spectral properties of the object surface and eliminate atmospheric and solar information. Orthorectification is performed to eliminate the compression, distortion, stretching and offset of the image relative to the actual position of the ground target caused by the altitude of the remote sensing satellite and the Earth's rotation. Image fusion is performed to obtain more accurate image data. The original images are processed so that they can be compared and the errors introduced during the image taking process can be eliminated, making the results more accurate.

[0019] Optionally, the registration of the processed remote sensing image based on business data includes:

[0020] Based on business data, define the target detection range;

[0021] The remote sensing image is matched with the detection range to confirm the target area of ​​the remote sensing image.

[0022] By adopting the above technical solution, based on business data, the range of the images captured by remote sensing satellites is first determined, and then the monitoring range set by the captured remote sensing images is matched to determine the specific target area of ​​the captured remote sensing images.

[0023] Optionally, the step of comparing remote sensing images from different times and extracting the target area that has changed includes:

[0024] Vectorize the target region;

[0025] The vectorized data is then subjected to spatial overlay analysis to obtain the changing vectors;

[0026] By adopting the above technical solution, when the terminal compares the impacts, the image data must be digitized before comparison can be performed. The extracted target area is vectorized, and the vectorized impact data is spatially overlaid to form new features, resulting in the change vector. The change vector data is then matched with the geographic base map to obtain the surface change results.

[0027] Optionally, the step of acquiring geographic base map vector data and change vector types, matching them with the target area, and generating a first change result includes:

[0028] Preset the change vector types for different project types;

[0029] Match the target region change vector to the corresponding change vector type;

[0030] Match the change vector of the target area to the geographic base map;

[0031] The first change result is generated based on the matching project type and the matching geographic base map.

[0032] By adopting the above technical solution, the vector data of satellite imagery of different engineering types are preset in the terminal. The vector data and change vector types of the extracted target area are used to determine the type of change on the ground surface. The vector data of the target area are matched with the geographic base map to determine the specific location of the change on the ground surface. The change type of the engineering project and the specific location of the change on the ground surface are determined, and the change result on the ground surface is generated. The change result on the ground surface includes the type of change on the ground surface and the location of the change.

[0033] Optionally, the preset variation vectors for different engineering types include:

[0034] Obtain the project type and geographical coordinates;

[0035] The images of the project are captured by remote sensing satellites at the geographic coordinates of the project, and then processed and stored.

[0036] By adopting the above technical solution, the construction type and coordinates of the ongoing construction project on the ground are obtained. Remote sensing satellites take remote sensing images of the project's geographic coordinates, match these images with the corresponding project type, and store the corresponding project images. Later, when remote sensing satellites take photos, the stored photos can be compared to determine the project type corresponding to the images taken by the remote sensing satellites.

[0037] Optionally, the step of capturing images of surface construction work using a camera to generate a second change result includes:

[0038] Take initial photos of the project using a camera;

[0039] Process the initial photograph;

[0040] Compare the initial photos taken at different time periods to generate a second set of change results.

[0041] By adopting the above technical solution, since remote sensing satellites can only take pictures of a two-dimensional plane, and cannot take pictures of vertical construction, a camera is used to take three-dimensional pictures of the construction site. The physical photos taken by the camera are processed and compared with the initial photos at different time periods to generate a second comparison result.

[0042] A land surface change detection system includes: an acquisition module for acquiring remote sensing images of different periods via remote sensing satellites;

[0043] The processing module is used to preprocess the remote sensing image;

[0044] The matching module is used to register the processed remote sensing images based on business data;

[0045] The comparison module is used to compare remote sensing images from different times and extract target areas that have changed.

[0046] The first image module is used to acquire geographic base map vector data and change vector types, match them with the target area, and generate the first change result.

[0047] The second imaging module is used to capture images of the surface engineering construction using a camera and generate a second change result.

[0048] The results module is used to generate surface change results based on the first change result and the second change result.

[0049] By adopting the above technical solution, the acquisition module acquires remote sensing images from different periods, the processing module processes the acquired remote sensing images, the matching module registers the processed images with business data to determine the detection range, and the comparison module extracts the target areas that have changed in the remote sensing images from different periods. The first image module matches the target areas with the change vector types of the geographic base map to obtain the first change result detected by the satellite. Then, the second image module acquires the second change result captured by the camera, which captures the vertical engineering construction situation on the ground surface. The result module combines the first and second change results to jointly determine the changes on the ground surface. By comparing the ground surface photos taken by the satellite and the camera at different time periods, the results of the ground surface changes are obtained, which reduces the burden of manual inspection and speeds up the acquisition efficiency of ground surface change information.

[0050] Optional, a data reading unit for acquiring raw images captured by remote sensing satellites;

[0051] The data processing unit performs radiometric calibration, atmospheric correction, orthorectification, and image fusion on the original images.

[0052] By adopting the above technical solution, the data reading unit reads the original images captured by remote sensing satellites and processes the acquired original images through the data processing unit, enabling the terminal device to compare the images and improve the accuracy of the comparison.

[0053] In summary, this application includes at least one of the following beneficial technical effects:

[0054] After acquiring images of the subway line's surface at different times using remote sensing satellites, the images are preprocessed and registered with operational data to determine the monitoring range. Then, images from different time periods within the monitoring range are compared to extract areas of change. These changed areas are then matched with geographic base map vector data and change vector types to determine the specific location and type of change, generating a first change result. This is combined with engineering data captured by surface cameras to obtain a second change result. By combining the first and second change results, the changes occurring along the subway line can be determined. When changes occur along the subway line, images captured by satellites and some cameras installed along the line are processed and compared to determine the changes and their locations. This eliminates the need for manual surface inspections and improves detection efficiency. Attached Figure Description

[0055] Figure 1 This is a schematic flowchart of a method for detecting land surface changes according to an embodiment of this application;

[0056] Figure 2This application provides a schematic diagram of the method flow diagram for step S110 of a method for detecting surface changes;

[0057] Figure 3 This application provides a schematic diagram of the method flow diagram for step S120 of a method for detecting surface changes;

[0058] Figure 4 This application provides a schematic diagram of the method flow after step S130 in a method for detecting surface changes;

[0059] Figure 5 This application provides a schematic diagram of the method flow diagram for step S140 of a method for detecting surface changes;

[0060] Figure 6 This application provides a schematic diagram of the method flow before step S500 in a method for detecting surface changes;

[0061] Figure 7 This application provides a schematic diagram of the method flow diagram for step S150 of a method for detecting surface changes.

[0062] Explanation of reference numerals in the attached diagram: 1. Acquisition module; 2. Processing module; 3. Matching module; 4. Comparison module; 5. First image module; 6. Second image module; 7. Result module. Detailed Implementation

[0063] The present application will be further described in detail below with reference to all the accompanying drawings.

[0064] This application discloses a method for detecting land surface changes, referring to... Figure 1 ,include:

[0065] S100: Acquire remote sensing images from different periods using remote sensing satellites.

[0066] Among them, remote sensing images from different periods are images taken at different times by remote sensing satellites of the same geographical coordinates, such as images of the terminal station of Metro Line 7 taken in May and images taken in July.

[0067] S110. Preprocess the remote sensing images.

[0068] The purpose of preprocessing is to enable comparison of images captured by remote sensing satellites and to eliminate the influence of other factors during the shooting process, such as solar radiation and Earth's rotation, which can affect remote sensing images.

[0069] S120. Register the processed remote sensing images based on business data.

[0070] The business data is the geographical range to be detected. The captured images and the geographical range are registered to determine the geographical range of the captured images, reducing the data processing of the terminal.

[0071] S130. Compare remote sensing images from different times and extract the target areas that have changed.

[0072] Among them, remote sensing images taken by remote sensing satellites at different time periods are compared to extract target areas where the ground surface of the same project site has changed. For example, the target area is the area along Metro Line 7.

[0073] S140. Obtain geographic base map vector data and change vector type, match them with the target area, and generate the first change result.

[0074] The geographic base map contains data including latitude and longitude grids and basic geographic features, such as coastlines and transportation lines. The change vector type is vector imagery corresponding to different engineering types.

[0075] S150. The construction progress on the ground is captured by a camera, generating a second change result.

[0076] Since satellites can only capture planar images, they cannot detect other dimensions of construction that have a significant impact on surface construction. Therefore, cameras are used to capture images of surface construction. The second change is that surface construction occurs at the same location at different times.

[0077] S160. Based on the first and second change results, generate the surface change results.

[0078] Among them, the results of surface change obtained from images taken by remote sensing satellites and the results of surface change captured by cameras are combined to determine whether the surface has changed.

[0079] The implementation principle of the land surface change detection method in this application embodiment is as follows: After acquiring remote sensing images from different periods through remote sensing satellites, the remote sensing images are processed. The processed images are then matched with geographic locations to obtain the specific location of the captured images. The target areas that have changed are extracted from the remote sensing images from different times. The target areas are then matched with geographic base map vector data and change vector data to obtain the specific engineering type and specific location of the land surface changes. Finally, combined with images captured by cameras, the areas where the land surface has changed are determined. By combining the change areas extracted from the remote sensing satellite and camera images, it is jointly determined whether the land surface has changed.

[0080] Reference Figure 2 Preprocessing of remote sensing images includes:

[0081] S200: Acquire raw images taken by remote sensing satellites.

[0082] S210. Perform radiometric calibration, atmospheric correction, orthorectification, and image fusion on the original images.

[0083] In order to compare images from different remote sensing satellites at different times and extract change information, radiometric calibration of the original image requires converting the digitally quantized DN values ​​of the original image into absolute radiance values. DN values ​​are pixel values. The formula for converting digitally quantized DN values ​​into absolute radiance values ​​is as follows:

[0084] ,

[0085] In the formula, The original quantized DN value, for The radiance value when =0, for = The radiance value at time is used to perform atmospheric correction on the original image. Solar radiation is incident on the object surface through the atmosphere in some way and then reflected back to the sensor. Due to the influence of atmospheric aerosols, topography, and nearby ground objects, the original image contains a combination of information from the object surface, atmosphere, and solar information. To accurately obtain the spectrum of the object surface, its reflection information is separated from the atmospheric and solar information and atmospheric correction is performed. During satellite imaging, due to the influence of satellite flight speed, Earth's rotation, etc., geometric distortion occurs in the image relative to the ground target. This distortion manifests as compression, twisting, stretching, and offset of the image relative to the actual position of the ground target. To eliminate this distortion, orthorectification of the image is required. Influence fusion is to process multi-source data that is redundant in time or space to obtain more accurate and richer information and generate a synthetic image with new spatial and spectral characteristics. The HIS color space transformation fusion method is used. During HIS fusion processing, the multispectral RGB image with low spatial resolution is first transformed by HIS and mapped to HIS space. The high spatial resolution panchromatic image is histogram matched with the I-separated image and the I component is replaced, and then inversely transformed back to RGB color space.

[0086]

[0087] The resulting image is then cropped to remove areas outside the target region. Finally, the image is enhanced to improve its display quality, facilitating information extraction and recognition. This is achieved by highlighting important information and removing unimportant or unnecessary information. Image enhancement can be achieved by adjusting the histogram of the digital image and performing mathematical operations or transformations between pixel brightness values.

[0088] After image preprocessing, remote sensing indices are calculated to enhance the characteristic information of land cover. The spectral reflectance characteristics of land cover objects are intuitively expressed through reflectance spectrum curves, which vary with the reflected wavelength. Normalized Difference Vegetation Index (NDVI) and Normalized Difference Water Index (NDWI) are used to enhance the expression of land cover information by calculating spectral reflectance.

[0089] ,

[0090] ,

[0091] In the formula, and These represent the reflectivity of the infrared band and the red band, respectively. The reflectivity is for the green band.

[0092] The implementation principle of the preprocessing of remote sensing images in this application embodiment is as follows: After acquiring remote sensing images taken by remote sensing satellites, the original images are radiometrically located, and the brightness gray values ​​in the image are converted into absolute radiance so that the two images can be compared. Atmospheric correction is performed to accurately obtain the spectral properties of the object surface and eliminate atmospheric and solar information. Orthorectification is performed to eliminate the compression, distortion, stretching, and offset of the image relative to the actual position of the ground target caused by the altitude of the remote sensing satellite and the Earth's rotation. Image fusion is performed to obtain more accurate image data by processing the original images so that the original images can be compared and errors caused during image acquisition can be eliminated, making the results more accurate.

[0093] Reference Figure 3 Registration of processed remote sensing images based on operational data includes:

[0094] S300: Based on business data, set the target detection range.

[0095] The target detection range is the area of ​​the land surface that needs to be detected.

[0096] S310. Match the remote sensing image with the detection range to confirm the target area of ​​the remote sensing image.

[0097] In this process, the remote sensing image is matched with the detection range. For images taken by remote sensing satellites, the geographical location of the captured image is obtained by matching them with the detection range.

[0098] Extracting the target area requires setting change detection indicators. The extent of the change depends on the selection of these indicators and the setting of thresholds. Indicators such as a single distance index or similarity are used to compare feature differences between remote sensing images from different time periods. Then, based on the determined threshold, it is determined whether the land cover type of the corresponding pixel area has changed. The calculation formula is as follows:

[0099] ,

[0100] In the formula, This represents the change detection index value of the i-th pixel. and These represent the time phases of the i-th pixel and the p-th band, respectively. , The eigenvalues, where n represents the number of bands.

[0101] After calculating the change detection index, thresholds and judgment conditions need to be set to determine whether a pixel has changed, thereby detecting suspicious pixels that have changed. The threshold is defined using a weighted average and standard deviation by performing histogram statistics on the change detection index values. The calculation formula is as follows:

[0102] ,

[0103] In the formula, c represents the threshold. This represents the weighted average of the changing index values. Indicates standard deviation, This indicates the adjustment parameter, which ranges from [0, 1.5]. By adjusting the parameter, the determined threshold is made suitable for determining the change information of different land cover types in the target area. Pixels with change detection values ​​greater than or equal to the threshold are suspected pixels that have changed.

[0104] The implementation principle of this application embodiment for registering processed remote sensing images based on business data is as follows: the target range to be detected is preset in the terminal, and then the range to be detected is matched with the images captured by the remote sensing satellite to obtain the geographical location of the captured images.

[0105] Reference Figure 4 After comparing remote sensing images from different times and extracting the target areas that have changed, the process includes:

[0106] S400, Vectorize the target region.

[0107] When the terminal processes graphics, it cannot directly process the image; the image must be vectorized before processing. After vectorization, each target is composed of points, lines, and surfaces. By comparing images from different time periods, different regions can be extracted using the vectorized data.

[0108] S410. Perform spatial overlay analysis on the vectorized data to obtain the changing vector.

[0109] The process involves extracting vector data from the changed areas and then spatially overlaying it with preset geographic base map data and preset change vector types. Overlay analysis is an operation that overlays two or more layers of map elements to create a new element layer. The result is that the original elements are divided into new elements, and the new elements combine the attributes of the original two or more layers of elements.

[0110] The implementation principle of this application embodiment after comparing remote sensing images at different times and extracting the target area that has changed is as follows: In order to extract the vector of the changed area, the terminal vectorizes the image, then extracts the changed area through vector data, and then spatially overlays the extracted vector area to obtain a graphic and geographical location that can be recognized by humans.

[0111] Reference Figure 5 The process involves acquiring geographic base map vector data and change vector types, matching them with the target area, and generating the first change result, which includes:

[0112] S500, preset vector types for different engineering types.

[0113] The different types of projects refer to those that change the land surface, mainly including soil remediation, building demolition, road construction, new road construction, pedestrian walkway construction, surcharge, building construction, greening construction, and other factors. The different types of projects are preset in the terminal based on satellite-captured images. To facilitate later matching, the images captured by remote sensing satellites can be matched with the corresponding project types.

[0114] S510. Match the target area change vector with the corresponding change vector.

[0115] The extracted target area change vector is matched with a preset change vector to determine the type of change occurring on the land surface, such as soil remediation or building construction.

[0116] S520: Match the change vector of the target area to the geographic base map.

[0117] In this process, the target area is matched with the geographic base map to determine the specific geographical location of the images taken by the remote sensing satellite. The image raster is vectorized and paired with the vector of the geographic base map to obtain the specific geographical location of the changes on the land surface.

[0118] S530. Based on the matched project type and the matched geographic base map, generate the first change result.

[0119] The first change result is a graphic that includes the location and type of change on the ground surface, such as the location of the starting point of Metro Line 7 where road construction is underway.

[0120] The implementation principle of this application embodiment for obtaining geographic base map vector data and change vector types, matching them with target areas, and generating a first change result is as follows: extracting the changed areas from images taken by remote sensing satellites, matching the changed areas with preset change vector types to determine the type of change on the ground surface, matching the change vectors of the target area with the geographic base map to obtain the geographic location of the change on the ground surface, and then obtaining the first change result based on the obtained geographic location and the type of change on the ground surface.

[0121] Reference Figure 6 Before presetting the change vectors for different project types, the following are included:

[0122] S600: Obtain the project type and geographical coordinates.

[0123] Among them, the engineering geographic coordinates are the geographical locations of the engineering construction projects underway within the monitored area.

[0124] S610. Take images of the project type under the geographical coordinates of the project using remote sensing satellites, process the images and store them.

[0125] This involves storing different types of engineering construction images captured by satellite and mapping them one by one, such as satellite images corresponding to building construction and satellite images corresponding to soil remediation. When engineering construction is underway in the monitored area, the type and coordinates of the engineering construction are uploaded to the satellite, and the satellite captures an image of the engineering type at these geographic coordinates.

[0126] The implementation principle of this application embodiment before the preset change vectors of different engineering types is as follows: the engineering types carried out on the ground are corresponding to the satellite-captured images and stored. Later, the type of construction can be determined by directly comparing the satellite-captured images with the data in the terminal.

[0127] Reference Figure 7 By comparing the surface construction data captured by cameras at different time periods, the second set of change results includes:

[0128] S700: Takes initial photos of the project using a camera.

[0129] The cameras are typically installed along the target area to capture images of construction projects that provide a large view of the ground along the route, such as building construction or road construction.

[0130] S710, Processing initial photos.

[0131] The initial image processing involves taking several test image data, labeling the image data, marking buildings as 1 (displayed in white), and others as 0 (displayed in black), then dividing the image data and cropping it into pixel blocks of the required size, such as 160 pixel * 160 pixel image blocks, to increase the number of samples, improve the amount of sample information, and enhance accuracy.

[0132] S720: Compare the initial photos from different time periods to generate the second change result.

[0133] When comparing images from different time periods, the segmented image blocks are compared one by one, the changed graphic blocks are extracted, and the changes in buildings are determined based on the previous annotations.

[0134] This application embodiment uses a camera to capture images of surface engineering construction, generating a second change result: for buildings with significant surface changes, the captured images are marked, and buildings and other objects are marked differently, displaying different colors. Then, to improve detection accuracy, the image is segmented, and the segmented graphic blocks are compared to determine the changes that have occurred on the surface.

[0135] The above embodiments describe in detail a surface detection method. The following describes a surface detection system applied to a surface detection method.

[0136] Reference Figure 8 A land surface change detection system includes:

[0137] Module 1 is used to acquire remote sensing images from different periods via remote sensing satellites.

[0138] Processing module 2 is used to preprocess remote sensing images. Processing module 2 includes: a data reading unit, used to acquire the original images captured by remote sensing satellites.

[0139] The data processing unit performs radiometric calibration, atmospheric correction, orthorectification, and image fusion on the original images.

[0140] Matching module 3 is used to register the processed remote sensing images based on business data.

[0141] Comparison module 4 is used to compare remote sensing images from different times and extract target areas that have changed.

[0142] The first image module 5 is used to acquire geographic base map vector data and change vector types, match them with the target area, and generate the first change result.

[0143] The second image module 6 is used to capture images of the surface engineering construction using a camera and generate a second change result.

[0144] Results module 7 is used to generate surface change results based on the first change result and the second change result.

[0145] The implementation principle of a land surface change detection system according to an embodiment of this application is as follows: the acquisition module 1 acquires remote sensing images from different periods, and then the processing module 2 processes the acquired remote sensing images. The matching module 3 registers the processed images with business data to determine the detection range. Then, the comparison module 4 extracts the target areas that have changed in the remote sensing images from different periods. The first image module 5 matches the target areas with the change vector types of the geographic base map to obtain the first change result detected by the satellite. Then, the second image module 6 acquires the second change result captured by the camera, which captures the vertical engineering construction situation on the land surface. The result module 7 combines the first change result and the second change result to jointly determine the change situation of the land surface. The system compares the land surface photos taken by the satellite and the camera at different time periods to obtain the land surface change result.

[0146] The above are all preferred embodiments of this application, and are not intended to limit the scope of protection of this application. Therefore, all equivalent changes made in accordance with the structure, shape and principle of this application should be covered within the scope of protection of this application.

Claims

1. A method for detecting surface changes, characterized in that, include: Remote sensing images from different periods were acquired using remote sensing satellites; The remote sensing images are preprocessed; The processed remote sensing images are registered based on business data; Compare remote sensing images from different times and extract the target areas that have changed; Obtain geographic base map vector data and change vector types, match them with the target area, and generate the first change result; By comparing the surface construction conditions captured by cameras at different time periods, a second change result is generated. Based on the first and second change results, the land surface change results are generated; Among them, the business data is the geographical area to be detected, the geographical base map is data containing latitude and longitude grids and basic geographical features, and the change vector type is the vector image corresponding to different engineering types.

2. The method for detecting surface changes according to claim 1, characterized in that: Preprocessing the remote sensing image includes: Acquire raw images taken by remote sensing satellites; The original images are then subjected to radiometric calibration, atmospheric correction, orthorectification, and image fusion.

3. The method for detecting surface changes according to claim 1, characterized in that: The registration of the processed remote sensing image based on operational data includes: Define the target detection range based on business data; The remote sensing image is matched with the detection range to confirm the target area of ​​the remote sensing image.

4. The method for detecting surface changes according to claim 1, characterized in that: The process of comparing remote sensing images from different times and extracting the changed target areas includes: Vectorize the target region; The vectorized data is then subjected to spatial overlay analysis to obtain the changing vectors.

5. The method for detecting surface changes according to claim 1, characterized in that: The process of acquiring geographic base map vector data and change vector types, matching them with the target area, and generating the first change result includes: Preset the change vector types for different project types; Match the target region change vector with the corresponding change vector; Match the change vector of the target area to the geographic base map; The first change result is generated based on the matching project type and the matching geographic base map.

6. The method for detecting surface changes according to claim 5, characterized in that: The preset change vectors for different engineering types include: Obtain the project type and geographical coordinates; The images of the project are captured by remote sensing satellites at the geographic coordinates of the project, and then processed and stored.

7. The method for detecting surface changes according to claim 1, characterized in that: The process of capturing images of surface construction work using a camera to generate a second change result includes: Take initial photos of the project using a camera; Process the initial photograph.

8. A surface change detection system, characterized in that: include: The acquisition module (1) is used to acquire remote sensing images of different periods through remote sensing satellites; Processing module (2) is used to preprocess the remote sensing image; The matching module (3) is used to register the processed remote sensing image based on business data; The comparison module (4) is used to compare remote sensing images at different times and extract the target areas that have changed; The first image module (5) is used to acquire geographic base map vector data and change vector types, match them with the target area, and generate the first change result; The second image module (6) is used to capture the construction status of the ground engineering project through a camera and generate a second change result; The results module (7) is used to generate surface change results based on the first change results and the second change results; Among them, the business data is the geographical area to be detected, the geographical base map is data containing latitude and longitude grids and basic geographical features, and the change vector type is the vector image corresponding to different engineering types.

9. A land surface change detection system according to claim 8, characterized in that, The processing module (2) includes: The data reading unit is used to acquire raw images taken by remote sensing satellites; The data processing unit performs radiometric calibration, atmospheric correction, orthorectification, and image fusion on the original images.

Images