A method and apparatus for visualizing long-term InSAR deformation monitoring data

Abstract

This invention relates to the field of data visualization technology, and provides a method and apparatus for visualizing long-term InSAR deformation monitoring data. The invention publishes a tile-free service based on the RGB data corresponding to a raster image file, uses this tile-free service to load and display real-time data on a map, creates a pre-tiled service based on the individual RGB data to generate pre-cut tile data for data display and arrangement, publishes a WCS service based on single-band data, and uses the WCS service to perform spatial queries to generate deformation monitoring data change curves. By displaying the pre-cut tile data or the real-time data, this invention solves the problem of balancing better display effects and faster display speeds that existing technologies cannot achieve.

Description

Technical Field

[0001] This invention relates to the field of data visualization technology, and in particular to a method and apparatus for visualizing long-term InSAR deformation monitoring data. Background Technology

[0002] Interferometric Synthetic Aperture Radar (InSAR) technology has been widely used in the field of geological disaster monitoring due to its advantages such as wide swath and area observation. In recent years, in particular, geological disaster prevention and control has received key attention from relevant departments, which has sparked a surge in the research and application of InSAR technology in the field of geological disaster monitoring.

[0003] InSAR deformation monitoring data is gridded data generated by vectorizing InSAR image data. Current technologies struggle to balance better display quality and faster display speed when visualizing InSAR deformation gridded data in a browser, limiting its use in practical applications, resulting in a poor user experience and limited usability. Therefore, overcoming the shortcomings of the existing technology is an urgent problem to be solved in this technical field. Summary of the Invention

[0004] The technical problem to be solved by the present invention is to provide a method and apparatus for visualizing long-term InSAR deformation monitoring data, with the aim of solving the problem of balancing better display effect and faster display speed that is difficult to achieve in the existing technology.

[0005] The present invention adopts the following technical solution: In a first aspect, the present invention provides a method for visualizing long-term InSAR deformation monitoring data, comprising: Publish slice-free service based on the RGB data corresponding to the raster image file; Use the tile-free service to load and display real-time data on the map; A pre-slicing service is created for each of the raster image files to generate pre-cut tile data; Display the pre-cut tile data or the real-time data.

[0006] Furthermore, the step of publishing the slice-free service based on the RGB data corresponding to the raster image file includes: Create the temporal and spatial indexes for the raster image file; Create a dynamic file dataset for the RGB data corresponding to each batch of raster image files; Based on the dynamic file dataset and the corresponding time and spatial indexes, a slice-free service is published.

[0007] Furthermore, the creation of the raster image file includes the following temporal and spatial indexes: The timestamp information of the raster image file entering the database is obtained as the value of the time field, and a time index is established based on the time field; The raster data of the raster image file is divided into sections to obtain data to be processed; the data to be processed is segmented to obtain grid data; the grid data is assigned a grid code according to the spatial grid it occupies, and the grid code is determined as a grid code field; a spatial index is established based on the grid code field.

[0008] Furthermore, the slice-free service consists of multiple RGB data services; The use of the tile-free service to load and display real-time data on a map also includes: Display all RGB data services to obtain the overlapping area processing scheme by selecting the overlapping area to process; The map loading and display of real-time data is achieved using the tile-free service based on the overlapping area processing scheme.

[0009] Furthermore, the display of all RGB data services, to obtain an overlap area processing scheme by selecting to process the overlap area, includes: Display the names of all RGB data services in the slice-free service; retrieve the RGB data service selected by the user according to the name; Display the RGB raster corresponding to the RGB data service selected by the user to obtain the RGB raster that the user wants to display; Determine the overlapping area processing scheme according to the RGB raster that the user needs to display.

[0010] Furthermore, the method also includes: Publish WCS service based on single-band data from the raster image file; A tree-structured index is constructed using the raster image file; Obtain the user drawing range on the interface displayed by the WCS service; The tree-structured index is used to perform a spatial query according to the user-drawn range to obtain grid data.

[0011] Furthermore, after performing a spatial query using the tree-structured index according to the user-drawn range to obtain grid data, the method further includes: The grid data is displayed in a list; The grid data is highlighted on the current display interface; Based on the location of the grid data, query the single-band data within a specified time period to generate a deformation monitoring data change curve.

[0012] Furthermore, the method also includes: Determine whether the pick point location belongs to a valid or invalid data area; If the pickup point location belongs to the valid data area, then query the single-band data according to the pickup point location to obtain the query result; according to the display order set by the RGB data service, remove the grid data in the overlapping area of ​​the query result to obtain the deformation time series value set; If the pick point location belongs to an invalid data area, then return "No data".

[0013] Secondly, the present invention also provides a long-time InSAR deformation monitoring data visualization device for implementing the long-time InSAR deformation monitoring data visualization method described in the first aspect, the device comprising: At least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor for performing the long-time-series InSAR deformation monitoring data visualization method described in the first aspect.

[0014] Thirdly, the present invention also provides a non-volatile computer storage medium storing computer-executable instructions, which are executed by one or more processors to perform the long-time-series InSAR deformation monitoring data visualization method described in the first aspect.

[0015] This invention publishes a tile-free service based on the RGB data corresponding to raster image files. The tile-free service is used to load and display real-time data on the map, showing the addition and update of RGB raster files within a batch. A pre-tile service is created based on the RGB data corresponding to a single RGB raster file to generate pre-tiled tile data, providing a smooth user experience for loading and arranging RGB raster files within a batch. Attached Figure Description

[0016] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the embodiments of the present invention will be briefly described below. Obviously, the drawings described below are merely some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without any creative effort.

[0017] Figure 1 This is a flowchart illustrating a method for visualizing long-term InSAR deformation monitoring data provided in an embodiment of the present invention. Figure 2 This is a flowchart illustrating step 10 provided in an embodiment of the present invention; Figure 3 This is a flowchart illustrating step 101 provided in an embodiment of the present invention; Figure 4 This is a schematic diagram illustrating a specific example of a segmentation range provided in an embodiment of the present invention; Figure 5 This is a flowchart illustrating step 20 provided in an embodiment of the present invention; Figure 6 This is a schematic diagram illustrating a specific example of a directory tree provided in an embodiment of the present invention; Figure 7 This is a schematic diagram illustrating a specific example of a service for displaying all RGB data provided in an embodiment of the present invention; Figure 8 This is a flowchart illustrating step 201 provided in an embodiment of the present invention; Figure 9 This is a flowchart illustrating step 50 provided in an embodiment of the present invention; Figure 10 This is a schematic diagram illustrating a specific example of a point buffer query provided in an embodiment of the present invention; Figure 11 This is a schematic diagram illustrating a specific example of a line-buffered query provided in an embodiment of the present invention; Figure 12 This is a schematic diagram illustrating a specific example of a face buffered query provided in an embodiment of the present invention; Figure 13 This is a flowchart illustrating step 60 provided in an embodiment of the present invention; Figure 14 This is a flowchart illustrating step 70 provided in an embodiment of the present invention; Figure 15 This is a schematic diagram of the architecture of a long-time InSAR deformation monitoring data visualization device provided in an embodiment of the present invention. Detailed Implementation

[0018] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0019] In the description of this invention, the terms "inner", "outer", "longitudinal", "lateral", "upper", "lower", "top", "bottom", etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing this invention and do not require that this invention must be constructed and operated in a specific orientation. Therefore, they should not be construed as limiting this invention.

[0020] In this invention, the terms "first," "second," etc., are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Therefore, a feature defined with "first," "second," etc., may explicitly or implicitly include one or more of that feature. In the description of this application, unless otherwise stated, "a plurality of" means two or more.

[0021] In this application, unless otherwise expressly specified and limited, the term "connection" should be interpreted broadly. For example, "connection" can be a fixed connection, a detachable connection, or an integral part; it can be a direct connection or an indirect connection through an intermediate medium. Furthermore, the term "coupled" can refer to an electrical connection that enables signal transmission.

[0022] Furthermore, the technical features involved in the various embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.

[0023] Example 1: Currently, the common methods for visualizing InSAR deformation grid data in a browser are as follows: (1) The server uses existing visualization methods to draw images from grid data. The browser obtains the images and performs cropping, scaling, and other transformation operations before setting them to " This method displays images within HTML elements such as "". However, it has drawbacks: achieving a balance between display quality and speed is difficult. When transmitting low-resolution images, distortion operations blur the image, resulting in poor display quality; while transmitting high-resolution images leads to high bandwidth consumption, long transmission times, and slow display speeds.

[0024] (2) Request grid data dynamically based on the map's visible range and then draw and display it on the map. The drawback of this approach is that when a large amount of grid data exists, the server response is too high, and the front-end interface loads too much grid data, resulting in poor visualization smoothness.

[0025] (3) Display grid data using static map services. The drawback of this approach is that the data changes cannot be displayed in real time after the grid data changes over time.

[0026] Currently, there is a lack of unified solutions to the above pain points. Application developers often need to develop their own solutions based on their specific needs, which is difficult and cannot guarantee the visualization effects and speed.

[0027] To solve the above problems, such as Figure 1 As shown, this embodiment of the invention provides a method for visualizing long-term InSAR deformation monitoring data, including: Step 10: Publish the slice-free service based on the RGB data corresponding to the raster image file.

[0028] The specific format of the raster image file is determined by those skilled in the art based on the specific application scenario. In one embodiment, the raster image file can be a Tag Image File Format (TIFF), that is, the raster image file is a TIFF file. The raster image file corresponds to Rhed Green Blue (RGB) data and single-band data; RGB data is stored through RGB files, and single-band data is stored through single-band files. A single-band file is a pure data file storing a single, quantitative physical quantity. An RGB file is an image file storing visual color information, typically synthesized from three single-band files (or data). Single-band files are used to record precise measurement values. RGB files are used for display to the user for visualization. A comparison table of the characteristics of single-band data and RGB data is provided in Table 1 below.

[0029] Table 1. Comparison of characteristics between single-band data and RGB data

[0030] This invention uses RGB files in raster image files to publish slice-free services.

[0031] It's important to note that raster image files store raster data, i.e., a numerical matrix, representing a regular grid composed of pixel rows, columns, and bands (channels). The value of each grid cell represents raw information such as reflectance, elevation, temperature, or color intensity. The RGB data corresponding to a raster image file (e.g., a TIFF file) refers to the RGB data that corresponds to a single raster image file and can be displayed or processed as a color image. This RGB data is the result of interpreting and applying the raster data in the raster image file according to the RGB color model.

[0032] Step 20: Use the tile-free service to load and display real-time data on the map.

[0033] In one embodiment, the tile-free service for the current batch of RGB files is displayed during map loading; the tile-free service renders data in real time and is immediately available after data updates. In one embodiment, the tile-free service can be the Open Geospatial Consortium Web Map Tile Service (OGC WMTS).

[0034] Step 30: Create a pre-slicing service for a single raster image file to generate pre-cut tile data.

[0035] In one embodiment, the pre-tiled data is an image returned after rendering by a WMTS service, consisting of multiple tile data. This is determined by those skilled in the art based on the specific use case. In one embodiment, a corresponding Web Map Tile Service (WMTS) is created for each RGB file. This process requires preprocessing time and is available after tiling is complete. In one embodiment, the pre-tiling service can be an OGC WMTS service.

[0036] Step 40: Display the pre-cut tile data or the real-time data.

[0037] It should be noted that the data flow relationship between the tile-free service and the pre-tile service in this embodiment of the invention is as follows: both the tile-free service and the pre-tile service are located at the upper layer, using internal analysis or preprocessing to visualize the raw data as images. The pre-tile service is a pre-cached version of the tile-free service. The tile-free service generates map tile data in real time based on the current map visibility range for rendering, while the pre-tile service pre-cuts this rendering result into tiles for quick access. When step 30 is completed, those skilled in the art determine under what circumstances the pre-cut tile data is displayed and under what circumstances the real-time data is displayed, and complete the display according to the corresponding visualization mechanism. In one embodiment, the pre-tile service displays individual RGB raster data from a batch of RGB raster files during data overlap area processing. The pre-tile service for displaying raster files in the overlap area is removed after arrangement. After the data overlap area processing is completed, the published tile-free service is used to present the data in real time to a batch of RGB raster files. The final presentation to the user is a tile-free service for a batch of RGB raster data, while the pre-tile service for individual RGB raster data is used for internal preprocessing.

[0038] This invention publishes a tile-free service based on the RGB data corresponding to raster image files. The tile-free service is used to load and display real-time data on the map, showing the addition and update of RGB raster files within a batch. A pre-tile service is created based on the RGB data corresponding to a single RGB raster file to generate pre-tiled tile data, providing a smooth user experience for loading and arranging RGB raster files within a batch.

[0039] In one embodiment, such as Figure 2 As shown, step 10 includes: Step 101: Create the time index and spatial index of the raster image file.

[0040] In one embodiment, an InSAR POI time-series raster data repository is constructed based on the DMEO2 database to store raster image files with dates as the time series. These raster image files include RGB band data and single-band data. The RGB band data is raster data rendered with color bands for visualization; the single-band data is historical deformation data corresponding to the RGB band data, containing average rate and temporal deformation values ​​for spatial querying. Both RGB and single-band files are raster files. The RGB raster files and their corresponding single-band files have the same range. When importing TIFF format raster image files into the repository using the DMEO2 raster data import tool (raster2dmsql), a time field and a BeiDou grid code field are created for the TIFF data. Based on the values ​​of the time field and the BeiDou grid code field, a time index and a spatial index are created for the TIFF data, respectively. A specific example will be given below, and will not be elaborated further.

[0041] Step 102: Create a dynamic file dataset for the RGB data corresponding to each batch of raster image files.

[0042] Create a dynamic file dataset for each batch of RGB raster files (updated every 12 days at the shortest interval).

[0043] Step 103: Based on the dynamic file dataset and the corresponding time index and spatial index, publish the slice-free service.

[0044] The service publishes a slice-free service based on the created dynamic file dataset; the slice-free service consists of multiple RGB raster data services. Simultaneously, a corresponding WMTS service is created for each RGB raster file.

[0045] In one embodiment, such as Figure 3 As shown, step 101 includes: Step 1011: Obtain the timestamp information of the raster image file as the value of the time field, and establish a time index based on the time field.

[0046] In one embodiment, time information is stored in the metadata TAG of the raster image file. The time-series TAG uses the TIFFTAG_DATETIME of the TIFF file (i.e., the raster image file). For example, it can be done using `gdal_translatein.tif out.tif -mo TIFFTAG_DATETIME="time"`, where `time` represents the added time, and the time must conform to the ISO standard. Specifically, the timestamp information is parsed from the TAG of the raster image file or from the filename of the raster image file using regular expressions as the time field value, and a time index is built based on the time field of the TIFF data.

[0047] Step 1012: Divide the raster data of the raster image file into sections to obtain data to be processed; divide the data to be processed into grid data; assign grid codes to the grid data according to the spatial grid they occupy; determine the grid codes as grid code fields; establish a spatial index based on the grid code fields.

[0048] The raster image file contains raster data, including RGB data and single-band data. InSAR Point of Interest (POI) time-series raster data is a specific implementation of raster data. POI raster data typically refers to geospatial data represented in pixel form, with each pixel containing specific attribute values ​​(such as elevation, temperature, etc.). An example of InSAR POI time-series raster data after being segmented according to a specified Keyhole Markup Language (KML) file is shown below. Figure 4 The diagram shows a specific example of a segmentation range.

[0049] When the data in the raster image file after framing is imported into the database using the DaMeng raster data import tool (raster2dmsql), the TIFF file (i.e., the raster image file) is divided into raster data according to the BeiDou grid code standard. The grid data is then assigned a grid code according to the spatial grid it occupies. This grid code is used as the BeiDou grid code field value of the TIFF data, and a spatial index of the TIFF data is established based on the BeiDou grid code field.

[0050] In one embodiment, the spatial grid can be implemented using the GeoSOT grid. The GeoSOT grid consists of 32 levels, ranging from global to centimeter-sized, uniformly dividing the Earth's surface into multi-level grids that form a global quadtree system. The area ratio between different levels of the GeoSOT grid is approximately 4:1 and varies uniformly. The number of GeoSOT grids at each level and their approximate spatial scale on the ground are shown in Table 2 below.

[0051] Table 2. Number and Spatial Scale of GeoSOT Grids at Each Level

[0052] In one embodiment, the slice-free service consists of multiple RGB data services; such as Figure 5 As shown, step 20 further includes: Step 201: Display all RGB data services to obtain an overlap processing scheme by selecting the overlap area to process.

[0053] In one embodiment, all RGB raster data services are displayed in a directory tree format. Service names are assigned based on the entry date. The border grid of each RGB raster is displayed, and annotations for the RGB raster names are supported. For overlapping areas, an overlapping area handling scheme is obtained by selecting the tiles to be displayed. A specific implementation of the directory tree is as follows: Figure 6 As shown; a kind Figure 7 Displays specific instances of all RGB data services.

[0054] Step 202: Use the tile-free service to load and display real-time data on the map based on the overlapping area processing scheme.

[0055] The tile-free service for the current batch of RGB raster files is displayed in the map loading based on the overlapping area processing scheme generated in step 4.

[0056] Point cloud data in point cloud files often contains overlapping areas, including average velocity, temporal deformation, RGB, and monochrome data. Taking a provincial unit on a map as an example, a provincial unit typically corresponds to dozens of raster image files. If these overlapping areas are not processed, RGB files will show obvious color differences when displayed, and single-band files will return two different deformation values ​​at the same point when obtaining deformation values ​​from grid information. Therefore, it is essential to process the overlapping areas.

[0057] In one embodiment, such as Figure 8 As shown, step 201 includes: Step 2011: Display the names of all RGB data services in the slice-free service; retrieve the RGB data service selected by the user according to the name.

[0058] Step 2012: Display the RGB raster corresponding to the RGB data service selected by the user to obtain the RGB raster that the user wants to display.

[0059] Step 2013: Determine the overlapping area processing scheme according to the RGB raster required by the user.

[0060] In one embodiment, when processing overlapping data areas, a batch of RGB files to be displayed is selected; for RGB raster files with overlapping areas in the services corresponding to the displayed RGB data, service orchestration is performed. The user selects the RGB raster to be displayed, and after enabling the I key operation, a list of all RGB data services within the range can be popped up by clicking the mouse to process the overlapping area (for example, selecting to move the raster file to the top, bottom, previous layer, or next layer), and the overlapping area processing scheme is saved.

[0061] This invention provides a slice-free service that ensures the latest batch of data is always visible without waiting for the lengthy preprocessing of the WMTS service. It also allows for dynamic adjustment of the rendering style to adapt to different visualization needs, such as handling overlapping areas.

[0062] Tiled-free service is a dynamic map service that does not pre-generate any cached images. When a user requests a map, the server queries the data source in real time based on the request parameters, renders, and generates a map tile, which is then returned. However, each request requires real-time calculation by the server.

[0063] WMTS is a cached map service that provides pre-generated and uniformly sized image tiles. It returns static image files, resulting in low server load, extremely fast client loading, and a smooth user experience. Its interface is strictly unified and compatible with all mainstream GIS software and map libraries. However, once a tile is generated, its content is fixed; data updates require re-preprocessing (i.e., re-tiling), which introduces latency.

[0064] In one embodiment, when a user needs in-depth analysis, this embodiment of the invention also provides a method for querying raw grid data; specifically, as shown in... Figure 9 As shown, the method further includes: Step 501: Publish WCS service based on the single-band data in the raster image file.

[0065] Web Coverage Service (WCS) is a raw data service that provides the raw pixel values ​​of the raster data itself, rather than a rendered image. In this embodiment of the invention, each batch of single-band files (i.e., historical deformation raster files) is published as a WCS service.

[0066] Step 502: Construct a tree-structured index using the raster image file.

[0067] In one embodiment, the coordinates of the four corners of each RGB file are obtained, and an RTree index is constructed based on the coordinates. The specific construction method is determined by those skilled in the art based on the specific use case and is not limited here.

[0068] Step 503: Obtain the user drawing range on the interface displayed by the WCS service.

[0069] When a user clicks on the drawing area, the system retrieves the user's drawn and confirmed drawing area and uses this user-drawn area as the query input.

[0070] Step 504: Use the tree structure index to perform a spatial query according to the user-drawn range to obtain grid data.

[0071] The time series curve is plotted by tracing back to the original values ​​in the single-band file. In one embodiment, the user queries the time series grid data by plotting a range (e.g., using a point-line-area buffer), retrieves the grid data within the range by querying the RTree index, displays the query results in a list, and highlights selected grid points.

[0072] In one embodiment, point, line, and surface objects are drawn, and a buffer surface is generated according to the set default radius. Spatial query is performed to obtain grid point data within the region. Specifically, for point selection, only one grid point is returned, and for lines and surfaces, the first 10 data points are returned. After obtaining the deformation rate data of the grid point data according to the set time range, a curve is generated, and there are two interaction modes: point selection and line / surface selection. Point selection is to accurately query a single representative monitoring point near a specific location, while line / surface selection is to query multiple monitoring points in a strip area (e.g., along a road) or area (e.g., the entire development zone) for comparative analysis.

[0073] A specific implementation of a user-drawn range point buffer query is as follows: Figure 10 As shown, a specific implementation of a user-drawn range for a line-buffered query is as follows: Figure 11 As shown, a specific implementation of a user-drawn area buffer query is as follows: Figure 12As shown in the figure, descriptions such as "2017-10-15" indicate the date "October 15, 2017", and so on. Each date corresponds to a batch of raster image files. The grid points in the figure refer to the pixels in the raster image files, and their size is the product of the width and height of the raster image file resolution. After obtaining the grid point data within the range based on spatial query, the following steps 601 to 603 are performed to query historical deformation rate single-band files within the set time range to obtain the deformation rate values ​​at the grid point locations, thereby generating a deformation monitoring data change rate curve. Specifically, the deformation rate value at a grid point location is obtained from a batch of deformation rate single-band files from a given date.

[0074] To demonstrate the characteristics of temporal variations in gridded data, in one embodiment, such as Figure 13 As shown, after step 504, the method further includes: Step 601: Display the grid data in a list.

[0075] Step 602: Highlight the grid data on the current display interface.

[0076] Step 603: Based on the location of the grid data, query the single-band data within the specified time period to generate a deformation monitoring data change curve.

[0077] By querying the single-band file within a specified time period based on the current page grid point data location, a deformation monitoring data change curve for the current page grid point data is generated.

[0078] In one embodiment, such as Figure 14 As shown, this embodiment of the invention also provides a visualization process for another user interaction method, the method further comprising: Step 701: Determine whether the pick point location belongs to a valid data area or an invalid data area.

[0079] The pickup point location is a specific location clicked by the user on a map image of RGB data. In one embodiment, the user clicks on the map interface to select a specific geographical location. First, the screen pixel coordinates of the clicked location are captured, and then converted into real-world geographic coordinates (e.g., latitude and longitude or projected coordinates) using a coordinate transformation algorithm. The acquired geographic coordinates are then checked for data validity. In one embodiment, this is done by querying the pixel values ​​of the coordinate point across all bands (red, green, and blue) of the RGB image: if the pixel value of the coordinate point in any RGB band is a predefined no-data value, this is considered an invalid data area, and a no-data response is returned directly; only when all RGB bands contain valid pixel values ​​at this coordinate point is it recognized as a valid data area, and subsequent processing continues.

[0080] Step 702: If the pickup point location belongs to the valid data area, then query the single-band data according to the pickup point location to obtain the query result; according to the display order set by the RGB data service, remove the grid data in the overlapping area of ​​the query result to obtain the deformation time series value set.

[0081] Considering that multiple RGB data services may be visually overlaid, the issue of data source conflicts needs to be resolved. The solution is to determine data priority according to the following logic: Read the display order list of pre-tiled RGB data services in the system configuration; where the display order list reflects the layer overlay order (later added layers cover earlier added layers). Check each service from top to bottom to see if it contains valid data at that coordinate point; select the top-level valid service as the data source to ensure that the user always interacts with the most visually prominent data. After determining the data source, begin extracting precise deformation history data: Based on the selected RGB data pre-tiled service, find the corresponding single-band file sequence; where multiple single-band files are organized chronologically, each file representing the deformation field at a specific time point. Traverse all available time points, read the pixel values ​​at that geographic coordinate from the single-band file corresponding to each time point, and pair these pixel values ​​(where represents the deformation) with the corresponding timestamp to form a complete "time-deformation value" sequence.

[0082] For valid data ranges, a data set containing the complete time series is returned, with each element containing a timestamp and the corresponding deformation measurement value.

[0083] Step 703: If the pickup point location belongs to an invalid data area, return "No data".

[0084] Return a "no data" status for invalid data areas to avoid ambiguity.

[0085] The pre-tiling service in this embodiment of the invention loads and arranges data from a single raster image file (e.g., an RGB raster file) to determine the display order of raster image files in overlapping areas within a single batch. Based on this display order, the raster data of the single batch is displayed using a non-tiling service. This display order is also applied to single-band raster files within the same overlapping area for spatial data querying and return. For duplicate grid data, only the topmost grid point is returned. This embodiment of the invention also addresses the limitation of the non-tiling service (lacking spatial query capabilities and only suitable for display) through the WCS service. The pre-tiling service compensates for the excessive server load and long request return times that can occur when using the non-tiling service (i.e., one spatial data service per raster image file, and each raster image file corresponding to one non-tiling service, all generating tiles in real time) during overlapping area processing. Non-tiling is used to meet the visualization needs of raster image files, while the WCS service is used to meet the need for generating historical trace rate curves (i.e., deformation monitoring data change curves) of grid data. The geospatial platform of this invention, through the combination of these three services, satisfies the need for high-performance visualization while ensuring the real-time nature and analyzability of the data.

[0086] Example 2: like Figure 15 The diagram shown is a schematic representation of the architecture of a long-time-series InSAR deformation monitoring data visualization device according to an embodiment of the present invention. The long-time-series InSAR deformation monitoring data visualization device of this embodiment includes one or more processors 21 and a memory 22. Figure 15 Take a processor 21 as an example.

[0087] Processor 21 and memory 22 can be connected via a bus or other means. Figure 15 Taking the example of a connection between China and Israel via a bus.

[0088] The memory 22, as a non-volatile computer-readable storage medium, can be used to store non-volatile software programs and non-volatile computer-executable programs, such as the long-term InSAR deformation monitoring data visualization method in Embodiment 1. The processor 21 executes the long-term InSAR deformation monitoring data visualization method by running the non-volatile software programs and instructions stored in the memory 22.

[0089] Memory 22 may include high-speed random access memory, and may also include non-volatile memory, such as at least one disk storage device, flash memory device, or other non-volatile solid-state storage device. In some embodiments, memory 22 may optionally include memory remotely located relative to processor 21, which can be connected to processor 21 via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

[0090] The program instructions / modules are stored in the memory 22. When executed by one or more processors 21, they perform the long-time InSAR deformation monitoring data visualization method in Embodiment 1 above, for example, performing each step of the long-time InSAR deformation monitoring data visualization method described above.

[0091] It is worth noting that the information interaction and execution process between the modules and units in the above-mentioned device and system are based on the same concept as the processing method embodiment of the present invention. For details, please refer to the description in the method embodiment of the present invention, and will not be repeated here.

[0092] Those skilled in the art will understand that all or part of the steps in the various methods of the embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium, which may include: read-only memory (ROM), random access memory (RAM), magnetic disk or optical disk, etc.

[0093] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for visualizing long-term InSAR deformation monitoring data, characterized in that, include: Publish slice-free service based on the RGB data corresponding to the raster image file; Use the tile-free service to load and display real-time data on the map; A pre-slicing service is created for each of the raster image files to generate pre-cut tile data; Display the pre-cut tile data or the real-time data.

2. The method for visualizing long-term InSAR deformation monitoring data according to claim 1, characterized in that, The method includes: Create the temporal and spatial indexes for the raster image file; Create a dynamic file dataset for the RGB data corresponding to each batch of raster image files; Based on the dynamic file dataset and the corresponding time and spatial indexes, a slice-free service is published.

3. The method for visualizing long-term InSAR deformation monitoring data according to claim 2, characterized in that, The method includes: The timestamp information of the raster image file entering the database is obtained as the value of the time field, and a time index is established based on the time field; The raster data of the raster image file is divided into sections to obtain data to be processed; the data to be processed is segmented to obtain grid data; the grid data is assigned a grid code according to the spatial grid it occupies, and the grid code is determined as a grid code field; a spatial index is established based on the grid code field.

4. The method for visualizing long-term InSAR deformation monitoring data according to claim 1, characterized in that, The slice-free service consists of multiple RGB data services; The method further includes: Display all RGB data services to obtain the overlapping area processing scheme by selecting the overlapping area to process; The map loading and display of real-time data is achieved using the tile-free service based on the overlapping area processing scheme.

5. The method for visualizing long-term InSAR deformation monitoring data according to claim 4, characterized in that, The method includes: Display the names of all RGB data services in the slice-free service; retrieve the RGB data service selected by the user according to the name; Display the RGB raster corresponding to the RGB data service selected by the user to obtain the RGB raster that the user wants to display; Determine the overlapping area processing scheme according to the RGB raster that the user needs to display.

6. The method for visualizing long-term InSAR deformation monitoring data according to claim 1, characterized in that, The method further includes: Publish WCS service based on single-band data from the raster image file; A tree-structured index is constructed using the raster image file; Obtain the user drawing range on the interface displayed by the WCS service; The tree-structured index is used to perform a spatial query according to the user-drawn range to obtain grid data.

7. The method for visualizing long-term InSAR deformation monitoring data according to claim 6, characterized in that, The method further includes: The grid data is displayed in a list; The grid data is highlighted on the current display interface; Based on the location of the grid data, query the single-band data within a specified time period to generate a deformation monitoring data change curve.

8. The method for visualizing long-term InSAR deformation monitoring data according to claim 6, characterized in that, The method further includes: Determine whether the pick point location belongs to a valid or invalid data area; If the pickup point location belongs to the valid data area, then query the single-band data according to the pickup point location to obtain the query result; according to the display order set by the RGB data service, remove the grid data in the overlapping area of ​​the query result to obtain the deformation time series value set; If the pick point location belongs to an invalid data area, then return "No data".

9. A non-volatile computer storage medium, characterized in that, The computer storage medium stores computer-executable instructions, which are executed by one or more processors to perform the long-time InSAR deformation monitoring data visualization method according to any one of claims 1-8.

10. A long-term InSAR deformation monitoring data visualization device, characterized in that, include: At least one processor; And a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, the instructions being executed by the processor for performing the long-time InSAR deformation monitoring data visualization method according to any one of claims 1-8.

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