A data processing method, device and electronic equipment

Abstract

The application belongs to the technical field of time sequence subsidence data, and discloses a data processing method and device and electronic equipment. The application can realize spatial registration and reference unification of multi-source time sequence subsidence result images, that is, based on data standardization processing of a target time sequence subsidence result image, different sources, different resolutions, different ranges and point position differences of to-be-processed time sequence result subsidence images are unified to the same resolution, range and point position as the target time sequence subsidence result image, which provides a solid foundation for subsequent data fusion analysis and long time sequence subsidence monitoring, effectively solves the problem that multi-source data is difficult to directly match and connect in the prior art, and improves the availability, consistency and accuracy of data.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of time series subsidence data, and in particular to a data processing method and device and electronic equipment. BACKGROUND

[0002] SBAS-InSAR (Small Baseline Subset Interferometric Synthetic Aperture Radar) is a radar interferometric measurement technology that uses multi-period short baseline radar images to effectively monitor small ground deformation through differential interferometric measurement.

[0003] With the continuous development of radar technology, InSAR (Interferometric Synthetic Aperture Radar) technology has been widely used in the field of ground deformation monitoring. Among them, SBAS-InSAR technology as an effective radar interferometric measurement method can use multi-period short baseline radar images to monitor small ground deformation through differential interferometric measurement. However, in the actual application process, when using SBAS-InSAR time series subsidence data obtained by different software and different parameters, even if the storage format is TIF, there will be differences in data range, resolution and point position, which will make it difficult to directly connect in time to obtain longer cumulative subsidence data sequence, thereby bringing great difficulties and challenges to long time series, high precision ground subsidence analysis and modeling.

[0004] Traditional data processing methods often cannot effectively solve these problems of multi-source InSAR time series subsidence data in spatial registration and reference unification, or have the disadvantages of low efficiency, affected data accuracy or complex operation, etc. Therefore, there is an urgent need for a template TIF-based multi-source InSAR time series subsidence data spatial registration and reference unification method that can provide an efficient, accurate and practical solution to the above problems. SUMMARY

[0005] The present application provides a data processing method, device and electronic equipment to realize spatial registration and reference unification of multi-source time series subsidence result images, providing a solid foundation for subsequent data fusion analysis and long time series subsidence monitoring, effectively solving the problem of multi-source data difficult to directly match and connect in the prior art, and improving the usability, consistency and accuracy of the data.

[0006] In a first aspect, the present application provides a data processing method, which comprises:

[0007] obtaining a target time series subsidence result image; wherein the format of the target time series subsidence result image is a label image file format;

[0008] According to the target time sequence subsidence result image, a mask file corresponding to the target time sequence subsidence result image is generated;

[0009] According to the target time sequence subsidence result image, a to-be-processed time sequence subsidence image is processed to obtain a processed to-be-processed time sequence subsidence image; the resolution, size and shape of the processed to-be-processed time sequence subsidence image are the same as those of the target time sequence subsidence result image;

[0010] The pixel value of the processed to-be-processed time sequence subsidence image is extracted by using the mask file; the pixel value of a pixel point in the to-be-processed time sequence subsidence image is the subsidence amount of the position corresponding to the pixel point;

[0011] According to the time period corresponding to the processed to-be-processed time sequence subsidence image and the pixel value of the processed to-be-processed time sequence subsidence image, a reference change processing is performed on the processed to-be-processed time sequence subsidence image to obtain a time sequence subsidence image after uniform reference;

[0012] The format of the time sequence subsidence image after uniform reference is converted into an SHP file format.

[0013] In a second aspect, the present application provides a data processing device, which comprises:

[0014] A first unit is configured to obtain a target time sequence subsidence result image; the format of the target time sequence subsidence result image is a label image file format;

[0015] A second unit is configured to generate a mask file corresponding to the target time sequence subsidence result image according to the target time sequence subsidence result image;

[0016] A third unit is configured to process a to-be-processed time sequence subsidence image according to the target time sequence subsidence result image to obtain a processed to-be-processed time sequence subsidence image; the resolution, size and shape of the processed to-be-processed time sequence subsidence image are the same as those of the target time sequence subsidence result image;

[0017] A fourth unit is configured to extract the pixel value of the processed to-be-processed time sequence subsidence image by using the mask file; the pixel value of a pixel point in the to-be-processed time sequence subsidence image is the subsidence amount of the position corresponding to the pixel point;

[0018] The fifth unit is used to perform benchmark modification processing on the processed time series result settlement image based on the time period corresponding to the processed time series result settlement image and the pixel value of the processed time series result settlement image, so as to obtain a time series result settlement image with a unified benchmark.

[0019] The sixth unit is used to convert the time-series result settlement image after the unified benchmark into SHP file format.

[0020] Thirdly, this application provides a readable medium including executable instructions, which, when executed by a processor of an electronic device, cause the electronic device to perform any of the methods described in the first aspect.

[0021] Fourthly, this application provides an electronic device including a processor and a memory storing execution instructions, wherein when the processor executes the execution instructions stored in the memory, the processor performs the method as described in any of the first aspects.

[0022] As can be seen from the above technical solution, this application obtains a target time-series settlement result image; wherein the target time-series settlement result image is in the format of a tag image file; a mask file corresponding to the target time-series settlement result image is generated based on the target time-series settlement result image; and a time-series settlement result image to be processed is processed based on the target time-series settlement result image to obtain a processed time-series settlement result image; wherein the resolution, size, and shape of the processed time-series settlement result image to be processed are the same as those of the target time-series settlement result image. Using the mask file, the pixel values ​​of the processed time-series result settlement image are extracted; wherein, the pixel value of each pixel in the time-series result settlement image is the settlement amount at the corresponding position of the pixel; based on the time period corresponding to the processed time-series result settlement image and the pixel values ​​of the processed time-series result settlement image, the time-series result settlement image is modified according to a changed baseline to obtain a time-series result settlement image with a unified baseline; the format of the time-series result settlement image with the unified baseline is converted to SHP file format. As can be seen, this application can achieve spatial registration and benchmark unification of multi-source time-series settlement result images. That is, based on the data standardization processing of the target time-series settlement result image, the time-series result settlement images to be processed with different sources, different resolutions, different ranges, and different point locations are unified to the resolution, range, and point location that are completely consistent with the target time-series settlement result image. This provides a solid foundation for subsequent data fusion analysis and long-term series settlement monitoring, effectively solves the problem that multi-source data is difficult to directly match and connect in the prior art, and improves the availability, consistency, and accuracy of the data.

[0023] Further effects of the above-described preferred non-conventional modes will be explained in the following with respect to the specific embodiments. BRIEF DESCRIPTION OF DRAWINGS

[0024] In order to more clearly illustrate the embodiments of the present application or prior art, the following will briefly introduce the drawings needed to be used in the embodiments or prior art description. Obviously, the drawings described below are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative effort based on these drawings.

[0025] Figure 1 A flow diagram of a data processing method provided by the present application is shown in the figure.

[0026] Figure 2 An initial time sequence subsidence result image provided by the present application is shown in the figure.

[0027] Figure 3 A target time sequence subsidence result image provided by the present application is shown in the figure.

[0028] Figure 4 A structure diagram of a data processing device provided by the present application is shown in the figure.

[0029] Figure 5 A structure diagram of an electronic device provided by the present application is shown in the figure. DETAILED DESCRIPTION

[0030] In order to make the purpose, technical scheme and advantages of the present application more clear, the technical scheme of the present application will be described clearly and completely in the following by combining with specific embodiments and corresponding drawings. Obviously, the described embodiments are only some of the embodiments of the present application, but not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative effort belong to the scope of protection of the present application.

[0031] The various non-limiting embodiments of the present application will be described in detail below in combination with the drawings.

[0032] Referring to Figure 1 , a data processing method in an embodiment of the present application is shown. In the embodiment, the method may, for example, include the following steps:

[0033] S101: Obtain a target time sequence subsidence result image.

[0034] The target time sequence subsidence result image is in a tag image file format (TIF data format). The TIF data format is a storage format of raster data, which is similar to an image, each pixel point has latitude and longitude position information, and the pixel value is the subsidence amount at the position. It can be understood that each pixel point in the time sequence subsidence result image corresponds to a position (i.e., position information, coordinate information), and the pixel value corresponding to each pixel point is the subsidence amount (or subsidence value) of the position corresponding to the pixel point.

[0035] In this embodiment, the target time sequence subsidence result image can be obtained first. The target time sequence subsidence result image can be understood as an ideal standard reference template, that is, a template for data standardization processing of other time sequence subsidence result images.

[0036] As an example, an image region meeting a preset image parameter condition can be determined in the initial time sequence subsidence result image first, and then the image region can be taken as the target time sequence subsidence result image. The preset image parameter condition is that the image resolution of the image region meets a preset resolution threshold, and the size and shape of the image region meet preset size and shape conditions. That is, an image region meeting the resolution threshold, the size condition, and the shape condition is found in the initial time sequence subsidence result image as the target time sequence subsidence result image.

[0037] For example, due to the use of different software and different parameters, the time sequence subsidence amount (i.e., time sequence subsidence result image) obtained by using the SBAS-InSAR technology has different ranges and resolutions, and the positions of the points of each result are different. In order to connect in time and obtain longer cumulative subsidence amount data, a TIF file (i.e., target time sequence subsidence result image) with ideal resolution and range is selected first, and the TIF file is taken as a processing template for all other TIF files. For example, an ideal target time sequence subsidence result image can be extracted from the initial time sequence subsidence result image as shown in FIG. 6A (e.g., a target time sequence subsidence result image as shown in FIG. 6B). Figure 2 Figure 3

[0038] S102: generating a mask file corresponding to the target time sequence subsidence result image according to the target time sequence subsidence result image.

[0039] In this embodiment, after obtaining the target time sequence subsidence result image, a mask file mask corresponding to the target time sequence subsidence result image can be generated according to the target time sequence subsidence result image.

[0040] ​​In the embodiment, the pixel value of the first type of pixel point in the target time sequence subsidence result image can be set as 1, and the pixel value of the second type of pixel point in the target time sequence subsidence result image can be set as 0. The first type of pixel point is a pixel point whose subsidence amount at the corresponding position in the target time sequence subsidence result image is in a preset first interval, for example, the preset first interval can be (-1000, ) and (1000). The second type of pixel point is a pixel point whose subsidence amount at the corresponding position in the target time sequence subsidence result image is in a preset second interval, for example, the preset second interval can be an interval other than (-1000, ) and (1000).

[0041] That is, in the embodiment, a mask file mask is newly created, the mask file mask is completely consistent with the size and resolution of the ideal TIF (i.e., the target time sequence subsidence result image), the pixel value of the pixel point corresponding to the position of the value of the subsidence amount in the target time sequence subsidence result image in the range of (-1000, ) and (1000) is set as 1 in the mask file, and the pixel value of the pixel point corresponding to the other positions is set as 0. This way of making a mask file can more directly and conveniently remove the abnormal values (-999999 or 999999 or 0 or nan) in the target time sequence subsidence result image.

[0042] S103: processing the to-be-processed time sequence result subsidence image according to the target time sequence subsidence result image to obtain a processed to-be-processed time sequence result subsidence image.

[0043] In the embodiment, the to-be-processed time sequence result subsidence image can be processed according to the target time sequence subsidence result image to obtain a processed to-be-processed time sequence result subsidence image. In one implementation, the to-be-processed time sequence result subsidence image can be sampled according to the resolution of the target time sequence subsidence result image based on a resampling algorithm (for example, a nearest neighbor, a bilinear interpolation, a cubic convolution, or the like) to obtain a sampled time sequence result subsidence image. The resolution of the sampled time sequence result subsidence image is the same as the resolution of the target time sequence subsidence result image. Then, the sampled time sequence result subsidence image can be cropped according to the size, shape, and relative position information of the processed to-be-processed time sequence result subsidence image to obtain the processed to-be-processed time sequence result subsidence image. In this way, the resolution, size, and shape of the processed to-be-processed time sequence result subsidence image are the same as the resolution, size, and shape of the target time sequence subsidence result image.

[0044] ​​For example, the resolution and range size (i.e. size, shape) of the extraction target time series settlement result image can be extracted first. Then, all other TIFs (i.e. time series result settlement images to be processed) are resampled to the same resolution as the ideal TIF (i.e. target time series settlement result image) by using a resampling algorithm such as nearest neighbor, bilinear interpolation, cubic convolution, etc. Then, the resampled TIF (i.e. time series result settlement image to be processed) is cropped using the range size of the ideal TIF (i.e. target time series settlement result image). The processed time series result settlement image to be processed is obtained.

[0045] S104: Extract the pixel value of the processed time series result settlement image to be processed using the mask file.

[0046] In the processed time series result settlement image to be processed, the pixel value of a pixel point is the settlement amount at the position corresponding to the pixel point.

[0047] As an example, the pixel value of the pixel point corresponding to the position of the first type of pixel point with a pixel value of 1 in the target time series settlement result image can be extracted first.

[0048] If the pixel value of the pixel point corresponding to the position in the processed time series result settlement image to be processed is a preset abnormal value, the pixel value of the pixel point corresponding to the position is calculated based on the pixel values of the three nearest pixel points to the position in the processed time series result settlement image to be processed. The pixel values of the three nearest pixel points to the position are all normal values.

[0049] Specifically, the mask file mask can be used to extract the settlement value at the position of the first type of pixel point with a pixel value of 1 in the target time series settlement result image based on the position of the first type of pixel point with a pixel value of 1 in the target time series settlement result image. If the settlement value is an abnormal value (for example, -999999 or 999999 or 0 or nan), the pixel value of the correct pixel point corresponding to the position is calculated by inverse distance interpolation based on the three nearest pixel points with non-abnormal values (i.e. normal values) to the point (i.e. the position). At this time, a series of TIFs (i.e. processed time series result settlement images to be processed) that are completely consistent with the ideal TIF (i.e. target time series settlement result image) in resolution, range, and pixel point position have been obtained. The tif obtained by the mask file is completely consistent with the mask in terms of the position of the pixel point with a pixel value of 1.

[0050] It should be noted that each time sequence result deposition image tif is a deposition amount of a date, and each pixel point in each tif corresponds to a pixel value of a deposition amount at a position corresponding to the pixel point. The pixel values of all tifs extracted through the mask file are all deposition amounts of dates, which are to be stored as shp files. The number of rows in the shp file is the number of points (the number of 1s in the mask file), and the cumulative deposition amount in each row is the number of tifs.

[0051] S105: According to the time period corresponding to the processed time sequence result deposition image to be processed and the pixel value of the processed time sequence result deposition image to be processed, the processed time sequence result deposition image to be processed is processed to obtain a time sequence result deposition image after uniform reference.

[0052] In this embodiment, the processed time sequence result deposition image to be processed can be processed according to the time period corresponding to the processed time sequence result deposition image to be processed and the pixel value of the processed time sequence result deposition image to be processed to obtain a time sequence result deposition image after uniform reference.

[0053] As an example, the starting time of the time period corresponding to the processed time sequence result deposition image to be processed can be sorted from front to back to obtain a sorting result. Among them, the time periods corresponding to two adjacent processed time sequence result deposition images to be processed are partially overlapped, that is, the time periods corresponding to two adjacent processed time sequence result deposition images to be processed are partially overlapped, that is, a small part of the time periods are the same. The time periods corresponding to each two adjacent processed time sequence result deposition images to be processed are overlapped dates.

[0054] For the i-th processed to-be-processed time sequence result subsidence image in the sorting result, the termination time of the time period corresponding to the i-1-th processed to-be-processed time sequence result subsidence image is determined, the pixel value of the i-th processed to-be-processed time sequence result subsidence image after the termination time is subtracted by the pixel value corresponding to the i-th processed to-be-processed time sequence result subsidence image at the termination time, and then the pixel value is added by the pixel value corresponding to the i-1-th processed to-be-processed time sequence result subsidence image after the uniform reference of the time sequence result subsidence image at the termination time, to obtain the uniform reference time sequence result subsidence image corresponding to the i-th processed to-be-processed time sequence result subsidence image, wherein i is a positive integer greater than or equal to 2. It should be emphasized that if i-1 is 1, the uniform reference time sequence result subsidence image corresponding to the first processed to-be-processed time sequence result subsidence image is the first processed to-be-processed time sequence result subsidence image. It should be noted that the processing of the processed to-be-processed time sequence result subsidence image needs to be processed in order according to the sorting result, that is, the second processed to-be-processed time sequence result subsidence image is processed first, then the third processed to-be-processed time sequence result subsidence image is processed, and so on, until the uniform reference time sequence result subsidence image corresponding to the last processed to-be-processed time sequence result subsidence image in the sorting result is obtained. In this way, the continuity and consistency of the entire time sequence can be ensured.

[0055] For example, if there are now three time periods of multiple TIF files (i.e. processed time series result deposition images), the first time period from 20180101 to 20221230 of the cumulative deposition amount TIF file (i.e. the first processed time series result deposition image) is a_tif_1, a_tif_2,..., a_tif_n, the second time period from 20210101 to 20231230 of the cumulative deposition amount TIF (i.e. the second processed time series result deposition image) is b_tif_1, b_tif_2,..., b_tif_m, and the third time period from 20231201 to 20241230 of the cumulative deposition amount TIF (i.e. the third processed time series result deposition image) is c_tif_1, c_tif_2,..., c_tif_p, all of which are processed to be completely consistent in resolution, range size, and point position, and the starting reference of the time period of all TIF files (i.e. the three processed time series result deposition images) is changed to 20180101. The specific method is to first subtract the cumulative deposition amount of the second time period after 20221230 from all TIF files (i.e. the second processed time series result deposition image) in the second time period, and then add the deposition amount of 20221230 in the first time period (i.e. the deposition amount corresponding to this time in the first processed time series result deposition image), and then obtain the cumulative deposition amount of the TIF file in the second time period after the reference change. Then, subtract the deposition amount of 20231230 in the third time period from all TIF files (i.e. the third processed time series result deposition image) in the third time period after 20231230, and then add the deposition amount of 20231230 in the second time period after the reference change (i.e. the deposition amount of the second unified reference time series result deposition image), and finally obtain the fused 20180101 to 20241230 cumulative deposition amount TIF file (i.e. the unified reference time series result deposition image), and the resolution, range, and point position of the unified reference time series result deposition image are completely consistent.

[0056] S106: Convert the format of the unified reference time series result deposition image to SHP file format.

[0057] After the time series result subsidence image after the uniform reference is obtained, the format of the time series result subsidence image after the uniform reference can be converted into SHP file format. Specifically, the pixel value corresponding to each position in the time series result subsidence image after the uniform reference corresponding to all the processed time series result subsidence images can be extracted by using the mask file, and all the extracted pixel values corresponding to each position can be converted into SHP file format. For example, the TIF file of the cumulative subsidence amount from 20180101 to 20241230 after the uniform reference (i.e., the time series result subsidence image after the uniform reference) is extracted by the mask file to obtain the subsidence information of each point in the TIF, that is, the subsidence value at the same position on the TIF (i.e., the time series result subsidence image after the uniform reference) is extracted by the position with the pixel value of 1 in the mask file (i.e., the mask file), and the subsidence value is converted into SHP file, and all fields are lon, lat, 20180101xb, 20180113xb,... 20241230xb. Wherein xb is the abbreviation of deformation. The names of the attributes of the cumulative subsidence amount in the SHP are 20180101xb, 20180113xb,... 20241230xb, and xb is added for easy understanding.

[0058] In order to make the data trend clearer, it is easier to identify the real subsidence change and reduce the noise, the method can further include: smoothing the time series result subsidence image after the uniform reference in SHP file format to obtain a final time series result subsidence image. The smoothing can include at least one of the following: moving average, weighted moving average, wavelet transform, Gaussian smoothing, etc.; in an implementation, Gaussian smoothing filtering can be used as the smoothing method.

[0059] It can be seen from the above technical solution that the target time sequence subsidence result image is obtained; the format of the target time sequence subsidence result image is a label image file format; a mask file corresponding to the target time sequence subsidence result image is generated according to the target time sequence subsidence result image; a to-be-processed time sequence result subsidence image is processed according to the target time sequence subsidence result image to obtain a processed to-be-processed time sequence result subsidence image; the resolution, size and shape of the processed to-be-processed time sequence result subsidence image are the same as those of the target time sequence subsidence result image; pixel values of the processed to-be-processed time sequence result subsidence image are extracted by using the mask file; the pixel value of a pixel point in the to-be-processed time sequence result subsidence image is the subsidence amount of the position corresponding to the pixel point; a to-be-processed time sequence result subsidence image after reference change is obtained by performing reference change processing on the processed to-be-processed time sequence result subsidence image according to the time period corresponding to the processed to-be-processed time sequence result subsidence image and the pixel value of the processed to-be-processed time sequence result subsidence image; and the format of the to-be-processed time sequence result subsidence image after reference change is converted into an SHP file format. It can be seen that the application can realize spatial registration and reference unification of multi-source time sequence subsidence result images, that is, based on data standardization processing of the target time sequence subsidence result image, to-be-processed time sequence result subsidence images of different sources, different resolutions, different ranges and different point position differences are unified to the resolution, range and point position that are completely consistent with the target time sequence subsidence result image, which provides a solid foundation for subsequent data fusion analysis and long time sequence subsidence monitoring, effectively solves the problem that multi-source data is difficult to directly match and connect in the prior art, and improves the usability, consistency and accuracy of data.

[0060] It can be understood that the application has the following beneficial effects compared with the prior art:

[0061] 1. Data standardization based on template TIF: An ideal TIF file is selected as a template (i.e., a target time sequence subsidence result image), and other TIF files are standardized to the resolution, range and point position of the template, which is an effective spatial registration method.

[0062] 2. Mask file generation based on numerical range: By setting the subsidence amount range, abnormal values are automatically identified and removed, avoiding manual intervention and improving the efficiency and objectivity of data processing.

[0063] 3. Inverse distance weighted interpolation to fill abnormal values: The inverse distance weighted interpolation method is used to fill abnormal values, which can restore the authenticity of data to some extent and avoid the influence of NoData values on subsequent analysis.

[0064] 4. Multi-period reference unification strategy: For multiple time period TIF data (i.e. processed to-be-processed time sequence result subsidence image), a reference period-based reference unification method is proposed to ensure the continuity and consistency of the entire time sequence.

[0065] 5. Finally generate SHP file containing complete time sequence information: The subsidence information of all TIF files is summarized into an SHP file, which is convenient for subsequent time sequence analysis and visualization.

[0066] That is, the present application has good universality and adaptability, and can effectively process cumulative subsidence data of different sources, different resolutions and different ranges, providing a new technical approach for constructing long time sequence and high precision surface subsidence model.

[0067] As shown in Figure 4 , a specific embodiment of a data processing device provided by the present application. The device described in this embodiment, i.e. the entity device for executing the method described in the above embodiment. Its technical scheme is essentially consistent with the above embodiment, and the corresponding description in the above embodiment is also applicable to this embodiment. The device comprises:

[0068] The first unit 401 is configured to obtain a target time sequence subsidence result image; wherein the format of the target time sequence subsidence result image is Tagged Image File Format (TIFF);

[0069] The second unit 402 is configured to generate a mask file corresponding to the target time sequence subsidence result image according to the target time sequence subsidence result image;

[0070] The third unit 403 is configured to process a to-be-processed time sequence result subsidence image according to the target time sequence subsidence result image to obtain a processed to-be-processed time sequence result subsidence image; wherein the resolution, size and shape of the processed to-be-processed time sequence result subsidence image are the same as those of the target time sequence subsidence result image;

[0071] The fourth unit 404 is configured to extract pixel values of the processed to-be-processed time sequence result subsidence image by using the mask file; wherein the pixel value of a pixel point in the to-be-processed time sequence result subsidence image is the subsidence amount of the position corresponding to the pixel point;

[0072] The fifth unit 405 is configured to perform reference change processing on the processed to-be-processed time sequence result subsidence image according to the time period corresponding to the processed to-be-processed time sequence result subsidence image and the pixel values of the processed to-be-processed time sequence result subsidence image, to obtain a time sequence result subsidence image after unification of reference;

[0073] The sixth unit 406 is configured to convert the format of the time sequence result image after the uniform reference into an SHP file format.

[0074] Optionally, the first unit 401 is configured to:

[0075] determine an image region in the initial time sequence result image that satisfies a preset image parameter condition;

[0076] set the image region as a target time sequence result image;

[0077] The preset image parameter condition is that the image resolution of the image region satisfies a preset resolution threshold, and the size and shape of the image region satisfy preset size and shape conditions.

[0078] Optionally, the second unit 402 is configured to:

[0079] set the pixel value of a first type of pixel point in the target time sequence result image to 1;

[0080] set the pixel value of a second type of pixel point in the target time sequence result image to 0;

[0081] The first type of pixel point is a pixel point whose corresponding position in the target time sequence result image has a settlement amount in a preset first interval.

[0082] The second type of pixel point is a pixel point whose corresponding position in the target time sequence result image has a settlement amount in a preset second interval.

[0083] Optionally, the third unit 403 is configured to:

[0084] sample the time sequence result image to be processed according to the resolution of the target time sequence result image based on a resampling algorithm to obtain a sampled time sequence result image, wherein the resolution of the sampled time sequence result image is the same as the resolution of the target time sequence result image;

[0085] cut the sampled time sequence result image according to the size, shape and relative position information of the processed time sequence result image to be processed to obtain a processed time sequence result image to be processed.

[0086] Optionally, the fourth unit 404 is configured to:

[0087] extract the pixel value of a pixel point corresponding to a position in the processed time sequence result image to be processed according to the position of the first type of pixel point in the target time sequence result image whose pixel value is 1;

[0088] If the pixel value of the pixel point corresponding to the position in the processed to-be-processed time-series result subsidence image is a preset abnormal value, the pixel value of the pixel point corresponding to the position is calculated according to the pixel values of the three pixel points closest to the position in the processed to-be-processed time-series result subsidence image; wherein the pixel values of the three pixel points closest to the position are all normal values.

[0089] Optionally, the fifth unit 405 is configured to:

[0090] The starting times of the time periods corresponding to the processed to-be-processed time-series result subsidence images are sorted from front to back to obtain a sorting result; wherein the time periods corresponding to two adjacent processed to-be-processed time-series result subsidence images are partially overlapped.

[0091] For the i-th processed to-be-processed time-series result subsidence image in the sorting result, the ending time of the time period corresponding to the i-1-th processed to-be-processed time-series result subsidence image is determined, the pixel values of the i-th processed to-be-processed time-series result subsidence image after the ending time are all subtracted by the pixel value corresponding to the i-th processed to-be-processed time-series result subsidence image at the ending time, and then all added by the pixel value corresponding to the i-1-th processed to-be-processed time-series result subsidence image at the ending time, to obtain the uniform reference time-series result subsidence image corresponding to the i-th processed to-be-processed time-series result subsidence image.

[0092] wherein i is a positive integer greater than or equal to 2; if i-1 is 1, the uniform reference time-series result subsidence image corresponding to the first processed to-be-processed time-series result subsidence image is the first processed to-be-processed time-series result subsidence image.

[0093] Optionally, the sixth unit 406 is configured to:

[0094] Using the mask file, the pixel value corresponding to each position in the uniform reference time-series result subsidence image corresponding to all the processed to-be-processed time-series result subsidence images is extracted, and all the extracted pixel values corresponding to each position are converted into an SHP file format.

[0095] Optionally, the apparatus further comprises a seventh unit configured to:

[0096] The uniform reference time-series result subsidence image in the SHP file format is smoothed to obtain a final time-series result subsidence image.

[0097] In this way, the device can realize spatial registration and reference unification of multi-source time sequence subsidence result images, that is, based on data standardization processing of a target time sequence subsidence result image, different sources, different resolutions, different ranges, and point position differences of the to-be-processed time sequence subsidence images are unified to the same resolution, range, and point position as the target time sequence subsidence result image, thereby providing a solid foundation for subsequent data fusion analysis and long-time sequence subsidence monitoring, effectively solving the problem that multi-source data cannot be directly matched and connected in the prior art, and improving the availability, consistency, and accuracy of data.

[0098] Figure 5 is a structural schematic diagram of an electronic device provided by an embodiment of the present application. At the hardware level, the electronic device includes a processor and can optionally further include an internal bus, a network interface, and a memory. The memory can include a memory such as a random-access memory (RAM) and can also include a non-volatile memory such as at least one disk memory. Of course, the electronic device can also include other hardware required by a business.

[0099] The processor, the network interface, and the memory can be connected to each other through the internal bus, which can be an industry standard architecture (ISA) bus, a peripheral component interconnect (PCI) bus, or an extended industry standard architecture (EISA) bus. The bus can be divided into an address bus, a data bus, and a control bus. For ease of representation, Figure 5 Only one bidirectional arrow is used in the figure to represent the bus, but it does not mean that there is only one bus or only one type of bus.

[0100] The memory is used to store execution instructions. Specifically, the execution instructions are computer programs that can be executed. The memory can include a memory and a non-volatile memory and provide the processor with execution instructions and data.

[0101] In a possible implementation manner, the processor reads corresponding execution instructions from the non-volatile memory into the memory and then runs, and can also obtain corresponding execution instructions from other devices to form a data processing apparatus at a logical level. The processor executes the execution instructions stored in the memory to implement the data processing method provided in any embodiment of the present application through the executed execution instructions.

[0102] The above as described in the present application Figure 1The method executed by the data processing apparatus provided by the embodiment shown can be applied to a processor or implemented by the processor. The processor can be an integrated circuit chip with signal processing capability. In the implementation process, each step of the above method can be completed by integrated logic circuits in hardware or instructions in software form in the processor. The processor described above can be a general processor, including a central processing unit (CPU), a network processor (NP), etc.; or a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field-programmable gate array (FPGA) or other programmable logic device, a discrete gate or transistor logic device, a discrete hardware component. Each method, step and logic block diagram disclosed in the embodiments of the present application can be implemented or executed. The general processor can be a microprocessor or the processor can also be any conventional processor.

[0103] The steps of the method disclosed in the embodiments of the present application can be directly embodied as hardware code processing executed by a code processor, or executed by a combination of hardware and software modules in the code processor. The software module can be located in a random access memory, a flash memory, a read-only memory, a programmable read-only memory or an electrically erasable programmable memory, a register, or other mature storage medium in the art. The storage medium is located in the storage memory, and the processor reads information in the storage memory and combines hardware to complete the steps of the above method.

[0104] The embodiments of the present application further provide a readable storage medium storing execution instructions. When the execution instructions stored in the readable storage medium are executed by a processor of an electronic device, the electronic device can execute the data processing method provided in any of the embodiments of the present application, and is specifically used for executing the above evaluation method.

[0105] The electronic device described in each of the foregoing embodiments can be a computer.

[0106] Those skilled in the art shall understand that the embodiments of the present application can be provided as a method or a computer program product. Therefore, the present application can adopt a complete hardware embodiment, a complete software embodiment, or a combination of software and hardware.

[0107] Each of the embodiments in the present application is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other. Each of the embodiments focuses on the difference from other embodiments. In particular, for the device embodiments, since they are basically similar to the method embodiments, the description is relatively simple, and the relevant parts can be referred to the part of the method embodiments.

[0108] It should also be noted that the terms "comprising", "containing", or any other variant thereof are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements, but can also include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without more limitations, the element defined by the statement "comprising a" does not exclude the presence of additional identical elements in the process, method, article, or apparatus that includes the element.

[0109] The above only describes the embodiments of the present application and is not intended to limit the present application. The present application can have various modifications and changes for those skilled in the art. Any modification, equivalent replacement, improvement, etc. within the spirit and principle of the present application shall be included in the scope of the claims of the present application.

Claims

1. A data processing method, characterized in that, The method includes: Acquire the target time-series settlement result image; wherein the target time-series settlement result image is in the format of a tag image file; Based on the target time-series settlement result image, generate a mask file corresponding to the target time-series settlement result image; Based on the target time series settlement result image, the time series result settlement image to be processed is processed to obtain the processed time series result settlement image; wherein, the resolution, size, and shape of the processed time series result settlement image to be processed are the same as those of the target time series settlement result image. Using the mask file, the pixel values ​​of the processed time series result settlement image are extracted; wherein, the pixel value of each pixel in the time series result settlement image is the settlement amount at the position corresponding to that pixel. Based on the time period corresponding to the processed time series result settlement image and the pixel value of the processed time series result settlement image, the processed time series result settlement image is subjected to benchmark modification processing to obtain a time series result settlement image with unified benchmark. Convert the time-series sedimentation images after the unified benchmark to SHP file format; The step of performing baseline modification processing on the processed time-series result settlement image based on the time period corresponding to the processed time-series result settlement image and the pixel values ​​of the processed time-series result settlement image to obtain a time-series result settlement image with a unified baseline includes: The time periods corresponding to the processed time series results of the settlement images are sorted from front to back according to their start times to obtain the sorting results; wherein, the time periods corresponding to two adjacent processed time series results of the settlement images partially overlap. For the i-th processed time series result sinking image in the sorting result, determine the end time of the time period corresponding to the (i-1)-th processed time series result sinking image. Subtract the pixel value of the i-th processed time series result sinking image at the end time from the pixel value of the i-th processed time series result sinking image after the end time, and then add the pixel value of the time series result sinking image with unified benchmark corresponding to the (i-1)-th processed time series result sinking image at the end time to obtain the time series result sinking image with unified benchmark corresponding to the i-th processed time series result sinking image. Where i is a positive integer greater than or equal to 2; if i-1 is 1, the time series result settlement image after unified benchmark corresponding to the first processed time series result settlement image is the first processed time series result settlement image.

2. The method according to claim 1, characterized in that, The acquisition of the target time-series settlement result image includes: In the initial time-series settlement result image, identify the image region that meets the preset image parameter conditions; The image region is used as the target time-series settlement result image; The preset image parameter conditions are that the image resolution of the image region meets a preset resolution threshold, and the size and shape of the image region meet preset size and shape conditions.

3. The method according to claim 1, characterized in that, The step of generating a mask file corresponding to the target time-series settlement result image based on the target time-series settlement result image includes: Set the pixel value of the first type of pixel in the target time-series settlement result image to 1; Set the pixel value of the second type of pixel in the target time-series settlement result image to 0; Wherein, the first type of pixel is the pixel in the target time-series settlement result image whose settlement amount is in a preset first interval. The second type of pixel is the pixel in the target time-series settlement result image whose settlement amount is within a preset second interval.

4. The method according to claim 2, characterized in that, The step of processing the time-series settlement image to be processed based on the target time-series settlement image to obtain the processed time-series settlement image includes: Based on the resampling algorithm, the time-series settlement image to be processed is sampled according to the resolution of the target time-series settlement image to obtain a sampled time-series settlement image; wherein, the resolution of the sampled time-series settlement image is the same as the resolution of the target time-series settlement image. Based on the size, shape, and relative position information of the processed time series result settlement image, the sampled time series result settlement image is cropped to obtain the processed time series result settlement image.

5. The method according to claim 3, characterized in that, The step of extracting pixel values ​​from the processed time-series result sedimentation image using the mask file includes: Based on the position of the first type of pixel with a pixel value of 1 in the target time series settlement result image, extract the pixel value of the pixel corresponding to the position in the processed time series settlement result image to be processed. If the pixel value of the pixel corresponding to the location in the processed time series result settlement image is a preset abnormal value, then the pixel value of the pixel corresponding to the location is calculated based on the pixel values ​​of the three pixels closest to the location in the processed time series result settlement image; wherein, the pixel values ​​of the three pixels closest to the location are all normal values.

6. The method according to claim 1, characterized in that, The process of converting the time-series sedimentation image after the unified benchmark is in SHP file format includes: Using the mask file, the pixel values ​​corresponding to each position in the time series result settlement image after the unified benchmark corresponding to all the processed time series result settlement images are extracted, and all the extracted pixel values ​​corresponding to each position are converted into SHP file format.

7. The method according to claim 1, characterized in that, The method further includes: The time-series result settlement image after standardization in SHP file format is smoothed to obtain the final time-series result settlement image.

8. A data processing apparatus, characterized in that, The device includes: The first unit is used to acquire the target time-series settlement result image; wherein the target time-series settlement result image is in the format of a tag image file. The second unit is used to generate a mask file corresponding to the target time-series settlement result image based on the target time-series settlement result image; The third unit is used to process the time series result settlement image to be processed based on the target time series settlement result image to obtain the processed time series result settlement image; wherein the resolution, size, and shape of the processed time series result settlement image to be processed are the same as those of the target time series settlement result image. The fourth unit is used to extract the pixel values ​​of the processed time series result settlement image using the mask file; wherein, the pixel value of the pixel in the time series result settlement image is the settlement amount at the position corresponding to the pixel. The fifth unit is used to perform benchmark modification processing on the processed time series result settlement image based on the time period corresponding to the processed time series result settlement image and the pixel value of the processed time series result settlement image, so as to obtain a time series result settlement image with a unified benchmark. The sixth unit is used to convert the time-series result settlement image after the unified benchmark into SHP file format; The step of performing baseline modification processing on the processed time-series result settlement image based on the time period corresponding to the processed time-series result settlement image and the pixel values ​​of the processed time-series result settlement image to obtain a time-series result settlement image with a unified baseline includes: The time periods corresponding to the processed time series results of the settlement images are sorted from front to back according to their start times to obtain the sorting results; wherein, the time periods corresponding to two adjacent processed time series results of the settlement images partially overlap. For the i-th processed time series result sinking image in the sorting result, determine the end time of the time period corresponding to the (i-1)-th processed time series result sinking image. Subtract the pixel value of the i-th processed time series result sinking image at the end time from the pixel value of the i-th processed time series result sinking image after the end time, and then add the pixel value of the time series result sinking image with unified benchmark corresponding to the (i-1)-th processed time series result sinking image at the end time to obtain the time series result sinking image with unified benchmark corresponding to the i-th processed time series result sinking image. Where i is a positive integer greater than or equal to 2; if i-1 is 1, the time series result settlement image after unified benchmark corresponding to the first processed time series result settlement image is the first processed time series result settlement image.

9. An electronic device, characterized in that, The electronic device includes a processor and a memory storing execution instructions. When the processor executes the execution instructions stored in the memory, the processor performs the method as described in any one of claims 1-7.

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