A method, device, medium and product for detecting dynamic changes in a shoreline

Abstract

The application discloses a kind of shoreline dynamic change detection method, equipment, medium and product, the method comprises: obtaining the initial reference shoreline of target area in official ENC, and extracting each period remote sensing shoreline from multi-period time series remote sensing image;Select the rigid invariant feature inflection point on initial reference shoreline as alignment reference, rigid registration is carried out to each period remote sensing shoreline, and unified to same spatial coordinate system;For each period shoreline after registration, the band-shaped buffer zone of flat end point style is constructed;According to time sequence, the symmetric difference set between adjacent period buffer zones is calculated, to determine the time series shoreline change area;The spatial position of the change area is analyzed, and its type is automatically identified, and the area and type are combined, and the final shoreline dynamic change detection result is output;The technical scheme of the embodiment of the application can effectively improve the precision and reliability of shoreline change detection, and provide data support for related business applications.

Description

Technical Field

[0001] This invention relates to the field of remote sensing detection technology, and in particular to a method, equipment, medium, and product for detecting dynamic changes in shorelines. Background Technology

[0002] With the intensification of global climate change and the deepening impact of human activities, the dynamic changes of the coastline, as a key area of ​​land-sea interaction, are directly related to coastal disaster prevention and mitigation, resource management, national spatial planning, and the timeliness of ENC (Electronic Navigational Chart). The rapid development of multi-source remote sensing technology, especially the widespread availability of multi-period, multi-resolution time-series remote sensing imagery, has provided an unprecedented data foundation for macroscopic and continuous monitoring of coastline changes.

[0003] In existing technologies, shoreline dynamic change detection mainly relies on the following methods: First, direct registration and change detection based on multi-period remote sensing images, which is easily affected by image quality, illumination and tides, resulting in a high false detection rate; Second, overlay or buffer analysis based on single-period images and historical shorelines, where traditional circular buffers produce spatial expansion artifacts at the endpoints and rely on manual interpretation, resulting in low automation; Third, deep learning-based methods rely on a large number of labeled samples, have limited generalization ability, and their black-box nature leads to poor interpretability and traceability of results, making it difficult to meet the legal requirements of ENC and other services. Summary of the Invention

[0004] This invention provides a method, equipment, medium, and product for detecting dynamic changes in shorelines, in order to solve the problems of insufficient timeliness of official shoreline data and lack of legal benchmarks and large errors in remote sensing detection.

[0005] According to one aspect of the present invention, a method for detecting dynamic changes in shoreline is provided, the method comprising: In the official electronic nautical chart (ENC), the initial baseline shoreline of the target area and multiple time-series remote sensing images of the target area are obtained, and the remote sensing shoreline of the target area at each time period is extracted from the multiple time-series remote sensing images. The rigid, unchanging ground feature inflection points on the initial reference shoreline are selected as ENC reference alignment points. Using the coordinates of the ENC reference alignment points as a reference, the remote sensing shorelines of each period are rigidly registered, and all remote sensing shorelines are mapped to a unified spatial coordinate system. Based on the registered remote sensing shoreline of each period and the initial reference shoreline, a strip buffer zone with flat-headed endpoints for each period is constructed. Calculate the symmetrical difference set between the strip buffer zones of adjacent periods in chronological order, and determine the temporal shoreline change area based on the calculated symmetrical difference set. The time-series shoreline change area is analyzed to obtain the shoreline change type corresponding to the target area, and the time-series shoreline change area and the shoreline change type are combined into the detection result of shoreline dynamic change.

[0006] According to another aspect of the present invention, a shoreline dynamic change detection device is provided, the device comprising: The data acquisition module is used to acquire the initial baseline shoreline of the target area and multiple time-series remote sensing images of the target area in the official ENC, and extract the remote sensing shoreline of the target area in each period from the multiple time-series remote sensing images. The registration module is used to select the inflection point of the rigid and unchanging ground feature on the initial reference shoreline as the ENC reference alignment point, and to perform rigid registration of the remote sensing shoreline at each period based on the coordinates of the ENC reference alignment point, so as to map all remote sensing shorelines to a unified spatial coordinate system. The buffer generation module is used to construct strip-shaped buffers with flat-headed endpoints for each period based on the registered remote sensing shoreline for each period and the initial reference shoreline. The change area determination module is used to calculate the symmetric difference set between adjacent period band buffer zones in chronological order, and determine the time-series shoreline change area based on the calculated symmetric difference set. The detection result generation module is used to analyze the time-series shoreline change area, obtain the shoreline change type corresponding to the target area, and combine the time-series shoreline change area and the shoreline change type into a detection result of shoreline dynamic change.

[0007] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor, which is then executed by the at least one processor to enable the at least one processor to perform a shoreline dynamic change detection method according to any embodiment of the present invention.

[0008] According to another aspect of the present invention, a computer-readable storage medium is provided, the computer-readable storage medium storing computer instructions, the computer instructions being configured to cause a processor to execute and implement a shoreline dynamic change detection method according to any embodiment of the present invention.

[0009] According to another aspect of the present invention, a computer program product is also provided, including a computer program / instructions that, when executed by a processor, implement the steps of the method as described in any embodiment of the present invention.

[0010] The technical solution of this invention obtains the initial reference coastline of the target area from the official ENC and extracts the remote sensing coastline of each period from multiple time-series remote sensing images. Then, it selects the inflection points of rigid, unchanging features on the initial reference coastline as alignment references and performs rigid registration of the remote sensing coastlines of each period, unifying them to the same spatial coordinate system. Next, it constructs a strip-shaped buffer zone with flat-topped endpoints for each registered coastline. Subsequently, it calculates the symmetrical difference set between buffer zones of adjacent periods in chronological order to determine the time-series coastline change area. Finally, it analyzes the spatial location of the change area, automatically identifies its coastline change type, and combines the area and type into a detection result. This solves the problems of insufficient timeliness of official coastline data and the lack of legal benchmarks and large errors in remote sensing detection, achieving the beneficial effect of improving the accuracy and reliability of coastline change detection and providing authoritative and timely data support for related business applications.

[0011] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0012] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0013] Figure 1 This is a flowchart of a shoreline dynamic change detection method provided in Embodiment 1 of the present invention; Figure 2 This is a flowchart of another shoreline dynamic change detection method provided in Embodiment 2 of the present invention; Figure 3 This is a schematic diagram of the structure of a shoreline dynamic change detection device provided in Embodiment 3 of the present invention; Figure 4 This is a schematic diagram of the structure of an electronic device that implements a shoreline dynamic change detection method according to an embodiment of the present invention. Detailed Implementation

[0014] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0015] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0016] Example 1 Figure 1 This is a flowchart of a shoreline dynamic change detection method provided in Embodiment 1 of the present invention. This embodiment is applicable to situations where high-precision detection of shoreline dynamic changes is required. The method can be executed by a shoreline dynamic change detection device, which can be implemented in hardware and / or software and is generally configured in an electronic device.

[0017] Correspondingly, such as Figure 1 As shown, the method includes: S110. In the official ENC, obtain the initial baseline shoreline of the target area and multiple time-series remote sensing images of the target area, and extract the remote sensing shoreline of the target area in each period from the multiple time-series remote sensing images.

[0018] In this embodiment, shoreline data for the target area is first extracted from the officially released ENC (Engineering, Prospecting, and Certification) database, serving as the legally mandated initial reference shoreline for its location and coordinates. Simultaneously, multiple remote sensing images of the target area taken after the reference year are acquired and ordered chronologically. For each remote sensing image, data processing is performed to obtain the remote sensing shoreline corresponding to the period in which each image was captured.

[0019] Optionally, based on the above embodiments, extracting the remote sensing shoreline of the target area at each time period from the multi-period time-series remote sensing images may include: From the aforementioned multi-period time-series remote sensing images, obtain the target time-series remote sensing image for the target period; Calculate the water index of the target remote sensing image, and segment the water area and land area based on the threshold of the water index to obtain a water-land binary segmentation map; Edge detection is performed on the binary water-land segmentation map to obtain a preliminary water-land boundary, and morphological optimization processing is performed on the preliminary water-land boundary to obtain an optimized water-land boundary; Continuous land-water contour lines are extracted from the optimized land-water boundary, and the land-water contour lines are converted from raster format to vector format to generate remote sensing shorelines for the target period.

[0020] Generally, the processing begins by selecting an image from a collection of chronologically arranged remote sensing images from a specific period as input data. Next, a water index is calculated for this image. This index enhances the spectral differences between water and land; by setting an appropriate threshold, each pixel in the image can be clearly classified as either water or land, thus generating a black-and-white image containing only these two categories—a water-land binary segmentation map.

[0021] Generally, after obtaining a binary segmentation image, it is necessary to identify the boundary between water and land. This is achieved through edge detection algorithms, obtaining a preliminary water-land boundary that may contain jagged edges and discontinuities. Due to the influence of sensors, cloud shadows, or complex terrain, the preliminary boundary is often not smooth or continuous enough. Therefore, morphological processing methods are used to optimize it, such as connecting broken gaps through dilation operations and smoothing jagged edges through erosion or opening-closing operations, thereby obtaining a more complete and smooth optimized water-land boundary line.

[0022] Generally, from the optimized boundary, the land and water contour line, which is a continuous and closed outline, is extracted and converted from a pixel-based raster data format into a vector data format composed of a series of coordinate points. This vector line is the remote sensing shoreline finally extracted from the remote sensing imagery of that period and can be used for subsequent spatial analysis.

[0023] S120. Select the inflection point of the rigid, unchanging ground feature on the initial reference shoreline as the ENC reference alignment point, and use the coordinates of the ENC reference alignment point as the reference to perform rigid registration on the remote sensing shoreline of each period, mapping all remote sensing shorelines to a unified spatial coordinate system.

[0024] Among them, the object inflection point can be understood as a significant turning point formed by those man-made or natural features on the coastline that have long been stable in position and have a clear and identifiable shape (such as the end of the breakwater, the corner of the wharf, and the apex of the natural headland). These are selected as fixed reference points for spatial registration.

[0025] In this embodiment, to eliminate potential overall positional shifts between remote sensing images from different periods, it is necessary to select fixed-position inflection points of ground features on the initial baseline shoreline as reference points for spatial alignment. Using the legally accurate coordinates of these points in the official ENC as anchor points, the required translation amount for each period's remote sensing shoreline is calculated, and overall movement correction is performed. All remote sensing shorelines from all periods are accurately registered to a spatial coordinate system consistent with the initial baseline shoreline, thereby avoiding misjudgments caused by geometric errors in the images themselves.

[0026] Optionally, based on the above embodiments, a rigid, invariant feature inflection point on the initial reference shoreline is selected as the ENC reference alignment point, and the remote sensing shoreline at each period is rigidly registered using the coordinates of the ENC reference alignment point as a reference, mapping all remote sensing shorelines to a unified spatial coordinate system. This may include: On the initial reference shoreline, at least one rigid and invariant feature inflection point is identified and selected, and its legal coordinates in ENC are determined as the ENC reference alignment point coordinates. For each period of the remote sensing shoreline, the inflection point of the same ground feature corresponding to the ENC reference alignment point is located on the corresponding time-series remote sensing image and used as the inflection point of the same ground feature in the corresponding time-series remote sensing image. For each period of the remote sensing shoreline, based on the coordinates of the ENC reference alignment point and the coordinates of the corresponding land feature inflection point in the time-series remote sensing image, the translation parameters required to move the remote sensing shoreline of each period to be aligned with the initial reference shoreline are calculated. Based on the translation parameters, the remote sensing shoreline for each period is subjected to overall translation correction to complete rigid registration.

[0027] Generally, the first step is to locate and identify at least one well-defined, long-term stable feature on the legally mandated initial shoreline. These features are typically man-made structures such as breakwater endpoints or wharf corners, or the apex of a natural headland with a stable outline and minimal influence from natural forces. The precise coordinates of these points, recorded in authoritative electronic ENC data, are then formally established as the spatial reference coordinates for the entire registration process.

[0028] Generally, for each phase of remote sensing imagery to be processed and its extracted shoreline, the operator or algorithm will carefully identify the same actual feature represented by the reference point selected in the previous step. For example, if the reference point is the northeast corner of a specific pier, then the location of this northeast corner of the pier needs to be found in each phase of imagery and identified as the corresponding point on that image.

[0029] Generally, after obtaining the reference point with legal coordinates and the image coordinates of the corresponding points on each period of imagery, the overall offset of the remote sensing shoreline data in the plane position of each period can be calculated very directly by comparing these two sets of coordinate values. This offset is the translation parameter required to correct it to be aligned with the legal reference shoreline.

[0030] Generally, the calculated translation parameters are used to move the remotely sensed shoreline in vector format extracted in each period as a whole. This process does not change the shape of the shoreline itself, but simply translates it spatially as a whole, making it precisely aligned with the initial reference shoreline in spatial position, thus completing a simple and effective rigid registration, laying the foundation for subsequent accurate comparisons.

[0031] S130. Based on the registered remote sensing shoreline of each period and the initial reference shoreline, construct a strip buffer zone for the flat-head endpoint of each period.

[0032] The flat-end point can be understood as a method of vertically cutting off the two ends of the line segment instead of connecting them with an arc, so as to completely avoid the generation of a non-real semi-circular protrusion area at the end point.

[0033] In this embodiment, after completing the spatial coordinate system registration, it is necessary to construct buffer zones of a specific style for the initial reference coastline and the remotely sensed coastline after each registration period. The buffer zones are constructed using a flat-endpoint style, characterized by extending vertically only to both sides of the coastline (i.e., the land side and the sea side) with a specified width, and being vertically truncated at the start and end points of the line segment, thus avoiding the semi-circular protrusions seen in traditional circular-endpoint buffer zones. Each buffer zone generated in this way is a strip-shaped region with straight boundaries, parallel to the original coastline.

[0034] Optionally, based on the above embodiments, according to the registered remote sensing shoreline of each period and the initial reference shoreline, a strip-shaped buffer zone for the flat-headed endpoint of each period is constructed, including: The current processed shoreline is obtained from the registered remote sensing shorelines of various periods and the initial reference shoreline; The current shoreline is cut into a series of short, straight segments connected end to end; For each short straight line segment, the two endpoints are shifted by a preset buffer distance along a direction perpendicular to the short straight line segment towards both the land and ocean sides, resulting in four new endpoints corresponding to each straight line segment. Connect the four new endpoints corresponding to each line segment to form multiple rectangular regions, wherein the central axis of a rectangular region is a short line segment; The rectangular regions are merged to generate a strip buffer with flat-headed endpoints that match the current processing period of the shoreline.

[0035] Generally, the processing involves selecting the current coastline from all spatially registered coastline data for each period, in a batch manner. To accurately construct a buffer zone with a specific pattern, the coastline is first cut into numerous short, connected straight segments to approximate its tortuous shape and treat each segment as a straight line. Then, for each short straight segment, the two endpoints are simultaneously shifted a predetermined buffer distance along a direction perpendicular to the segment towards both land and sea, generating two new endpoints for each endpoint—one on the land side and one on the sea side—resulting in four new endpoints for each segment. Subsequently, the four new endpoints corresponding to the same short straight segment are connected sequentially: two points on the land side are connected, two points on the sea side are connected, and then the land and sea side points of the same endpoint are connected, constructing a rectangular region with the original short straight segment as its central axis and a width twice the buffer distance. Finally, all rectangular regions corresponding to the current coastline's short segments are spatially merged into a complete, continuous polygonal region, generating a flat-endpoint patterned buffer zone matching the coastline's period, used for subsequent precise change detection.

[0036] S140. Calculate the symmetrical difference set between the strip buffer zones of adjacent periods in chronological order, and determine the temporal shoreline change area based on the calculated symmetrical difference set.

[0037] Among them, the symmetric difference set can be understood as a way to accurately identify the non-overlapping parts between two adjacent shoreline buffer zones, which represent the specific areas of change in the shoreline where erosion or siltation has occurred.

[0038] In this embodiment, after obtaining the strip-shaped buffer zones of the coastline for each period, the buffer zones of adjacent periods are sequentially subjected to spatial symmetric difference operations according to chronological order. Symmetric difference can accurately calculate the unique portion of the buffer zone in the later period compared to the previous period. This spatial region represents the range of spatial displacement of the coastline between two adjacent periods. By compiling the difference regions calculated for all adjacent periods in chronological order, a complete set of temporally changing regions reflecting the annual spatial evolution of the coastline is formed.

[0039] S150. Analyze the time-series shoreline change area to obtain the shoreline change type corresponding to the target area, and combine the time-series shoreline change area and the shoreline change type into the detection result of shoreline dynamic change.

[0040] In this embodiment, spatial analysis and identification of the set of temporally changing regions are finally required. For each changing region, its change type is automatically determined based on its relative position to the shoreline: if the region is located on the landward side of the shoreline, it indicates that the original shoreline has retreated and is identified as an erosion area; if it is located on the oceanward side, it indicates that new land has formed and is identified as a siltation or artificial expansion area. Finally, the spatial extent of each changing region is combined with its corresponding change type information to output a structured shoreline dynamic change detection result.

[0041] The technical solution of this invention obtains the initial reference coastline of the target area from the official ENC and extracts the remote sensing coastline of each period from multiple time-series remote sensing images. Then, it selects the inflection points of rigid, unchanging features on the initial reference coastline as alignment references and performs rigid registration of the remote sensing coastlines of each period, unifying them to the same spatial coordinate system. Next, it constructs a strip-shaped buffer zone with flat-topped endpoints for each registered coastline. Subsequently, it calculates the symmetrical difference set between buffer zones of adjacent periods in chronological order to determine the time-series coastline change area. Finally, it analyzes the spatial location of the change area, automatically identifies its coastline change type, and combines the area and type into a detection result. This solves the problems of insufficient timeliness of official coastline data and the lack of legal benchmarks and large errors in remote sensing detection, achieving the beneficial effect of improving the accuracy and reliability of coastline change detection and providing authoritative and timely data support for related business applications.

[0042] Example 2 Figure 2 This is a flowchart of a shoreline dynamic change detection method provided in Embodiment 2 of the present invention. This embodiment is based on and optimized from the above embodiments. Specifically, the step of "constructing a strip buffer zone of the flat-headed endpoints for each period based on the registered remote sensing shoreline of each period and the initial reference shoreline" has been refined.

[0043] Correspondingly, such as Figure 2 As shown, the method includes: S210. In the official ENC, obtain the initial baseline shoreline of the target area and multiple time-series remote sensing images of the target area, and extract the remote sensing shoreline of the target area in each period from the multiple time-series remote sensing images.

[0044] S220. Select the inflection point of the rigid, unchanging ground feature on the initial reference shoreline as the ENC reference alignment point, and use the coordinates of the ENC reference alignment point as the reference to perform rigid registration on the remote sensing shoreline of each period, mapping all remote sensing shorelines to a unified spatial coordinate system.

[0045] S230. Add the registered remote sensing shorelines of each period together with the initial reference shoreline to the input shoreline set.

[0046] In this embodiment, after spatial registration of remote sensing shorelines for all periods is completed, the initial baseline shoreline, which serves as the legal authority, is collected along with the remote sensing shorelines from each period that have been corrected to a unified coordinate system, forming a complete set of shorelines to be processed. This set contains all shoreline data from the baseline time to the latest time, preparing the data for subsequent unified and batch spatial analysis.

[0047] S240. Configure the endpoint style of the preset spatial buffer analysis function as a flat endpoint mode, and use the preset buffer distance as the width parameter to configure the parameters of the spatial buffer analysis function.

[0048] In this embodiment, the buffer generation function in spatial analysis is invoked, and its endpoint style is explicitly specified as a flat-endpoint mode. A suitable buffer distance is also set as the buffer width. This buffer distance is a crucial parameter; it can be manually set to a fixed value based on actual needs, or an appropriate value can be automatically calculated based on the spatial resolution of the remote sensing image used. This ensures that the buffer width reasonably matches the data accuracy, avoiding excessive noise or omissions in the detection results due to improper parameters.

[0049] S250. Input each input item in the input shoreline set into the configured spatial buffer analysis function for processing to obtain multiple strip-shaped buffers that extend only to both sides of the shoreline and are vertically truncated at both ends, serving as strip-shaped buffers for the flat-headed endpoints of each period.

[0050] In this embodiment, the data for each shoreline in the prepared shoreline set is sequentially input into the buffer analysis function, which has been configured according to the above rules, for processing. For each input shoreline, the function extends a specified buffer distance vertically outward on both sides (i.e., towards the land and towards the sea), strictly ensuring vertical truncation at the start and end points of the line segment without generating any arcs. Through this processing, each shoreline generates a strip-shaped region with straight boundaries, completely parallel to the original shoreline, i.e., a flat-ended buffer zone. These buffer zones will be used for subsequent accurate calculation of the spatial changes of the shoreline.

[0051] S260. Calculate the symmetrical difference set between adjacent buffer zones in chronological order, and determine the temporal shoreline change area based on the calculated symmetrical difference set.

[0052] Optionally, based on the above embodiments, calculating the symmetrical difference sets between adjacent buffer zones in chronological order, and determining the temporal shoreline change region based on the calculated symmetrical difference sets, may include: The strip buffers at all the flat-headed ends of all periods are sorted according to their corresponding period order to form a time-series buffer sequence; Starting from the earliest period in the time-series buffer sequence, the current period's strip buffer and its immediately preceding period's strip buffer are sequentially subjected to a symmetric difference operation to obtain the change region characterizing the difference in the spatial position of the shoreline between these two adjacent periods. By compiling the change areas of all adjacent periods calculated in chronological order, a time-series shoreline change area reflecting the continuous evolution of the shoreline is generated.

[0053] Generally, the first step is to arrange all the generated strip-shaped buffers with flat-end points in strict chronological order according to the shooting or effective period they represent, from earliest to latest. This timeline-arranged list of buffers provides a clear and orderly foundation for subsequent step-by-step comparisons of shoreline changes.

[0054] Generally, processing begins at the start of this time series, sequentially performing a spatial operation called "symmetric difference" on the buffer strip of each period and its temporally adjacent buffer strip of the preceding period. The core purpose of this operation is to precisely identify the portions present in the latter buffer but not in the former, and the portions present in the former buffer but not in the latter. The sum of these two portions constitutes a region of change. This region accurately depicts the actual range of movement and change in the spatial location of the coastline within these two adjacent time periods.

[0055] Generally, the results of calculating all the changed areas for each pair of adjacent period buffers are integrated and aggregated according to their corresponding chronological order. This ultimately generates a complete spatial dataset of shoreline changes across multiple time periods. This dataset coherently demonstrates the complete spatial process of the gradual evolution of the coastline over time, providing direct evidence for analyzing trends.

[0056] S270. Analyze the time-series shoreline change area to obtain the shoreline change type corresponding to the target area, and combine the time-series shoreline change area and the shoreline change type into the detection result of shoreline dynamic change.

[0057] Optionally, based on the above embodiments, analyzing the time-series shoreline change region to obtain the shoreline change type corresponding to the target region may include: If the time-series shoreline change area is located on the landward side of the shoreline, then the shoreline change type corresponding to the target area is determined to be a shoreline erosion area. If the time-series shoreline change area is located on the seaward side of the shoreline, then the type of shoreline change corresponding to the target area is determined to be shoreline siltation or artificial expansion area.

[0058] Generally, after obtaining the temporal changes in the areas reflecting differences in shoreline location, it is necessary to automatically identify the geographical changes they represent. The core basis is the relative orientation between each changed area and the original shoreline used as a comparison benchmark: if the changed area is located on the landward side of the benchmark shoreline, it indicates that the original land has become water, that is, the coastline has retreated towards the land, and is therefore identified as a shoreline erosion area. Such changes are mostly caused by natural dynamic processes such as wave erosion and storm surges; conversely, if the changed area is located on the oceanward side of the benchmark shoreline, it indicates that new land has appeared in the original water area, that is, the coastline has advanced towards the sea, and is therefore identified as a shoreline siltation or artificial expansion area. Siltation mainly refers to the growth of tidal flats formed by natural sediment deposition, while artificial expansion specifically refers to new land formed by engineering activities such as land reclamation.

[0059] The technical solution of this invention involves obtaining the initial baseline shoreline of the target area from official electronic nautical charts and extracting the shorelines of each period from multi-period time-series remote sensing images. Rigid, unchanging feature inflection points on the initial baseline shoreline are selected as alignment references, and the shorelines of each period are rigidly registered to the same spatial coordinate system. All registered shorelines from each period are then aggregated and processed, and a spatial buffer analysis function with a flat-endpoint mode and appropriate buffer distance is configured to generate a strip-shaped buffer where the shoreline of each period extends vertically to both sides and is truncated at both ends. This method avoids the use of traditional circular buffers from the outset. The system identifies dilation artifacts generated at the endpoints; then, it calculates the symmetrical difference between adjacent buffer zones in chronological order to determine the temporal changes in the shoreline; finally, it analyzes the spatial position of the changed area relative to the baseline shoreline, automatically identifies whether it belongs to the erosion or siltation expansion type, and combines the area and type into the final detection result. This solves the problems of insufficient timeliness of official shoreline data and lack of legal benchmarks and large errors in remote sensing detection. It achieves the beneficial effect of improving the accuracy, automation and reliability of shoreline change detection, and providing direct and authoritative data support for electronic nautical chart updates and other operations.

[0060] Example 3 Figure 3 Embodiment 3 of the present invention provides a shoreline dynamic change detection device, such as Figure 3 As shown, the device includes: The data acquisition module 310 is used to acquire the initial baseline shoreline of the target area and multiple time-series remote sensing images of the target area in the official ENC, and extract the remote sensing shoreline of the target area in each period from the multiple time-series remote sensing images. The registration module 320 is used to select the rigid and unchanging ground feature inflection point on the initial reference shoreline as the ENC reference alignment point, and to perform rigid registration on the remote sensing shoreline of each period based on the coordinates of the ENC reference alignment point, so as to map all remote sensing shorelines to a unified spatial coordinate system. The buffer generation module 330 is used to construct strip-shaped buffers with flat-headed endpoints for each period based on the registered remote sensing shoreline for each period and the initial reference shoreline. The change area determination module 340 is used to calculate the symmetric difference set between the strip buffer zones of adjacent periods in chronological order, and determine the time-series shoreline change area based on the calculated symmetric difference set. The detection result generation module 350 is used to analyze the time-series shoreline change area, obtain the shoreline change type corresponding to the target area, and combine the time-series shoreline change area and the shoreline change type into a detection result of shoreline dynamic change.

[0061] The technical solution of this invention obtains the initial reference coastline of the target area from the official ENC and extracts the remote sensing coastline of each period from multiple time-series remote sensing images. Then, it selects the inflection points of rigid, unchanging features on the initial reference coastline as alignment references and performs rigid registration of the remote sensing coastlines of each period, unifying them to the same spatial coordinate system. Next, it constructs a strip-shaped buffer zone with flat-topped endpoints for each registered coastline. Subsequently, it calculates the symmetrical difference set between buffer zones of adjacent periods in chronological order to determine the time-series coastline change area. Finally, it analyzes the spatial location of the change area, automatically identifies its coastline change type, and combines the area and type into a detection result. This solves the problems of insufficient timeliness of official coastline data and the lack of legal benchmarks and large errors in remote sensing detection, achieving the beneficial effect of improving the accuracy and reliability of coastline change detection and providing authoritative and timely data support for related business applications.

[0062] Based on the above embodiments, the data acquisition module 310 is specifically used for: From the aforementioned multi-period time-series remote sensing images, obtain the target time-series remote sensing image for the target period; Calculate the water index of the target remote sensing image, and segment the water area and land area based on the threshold of the water index to obtain a water-land binary segmentation map; Edge detection is performed on the binary water-land segmentation map to obtain a preliminary water-land boundary, and morphological optimization processing is performed on the preliminary water-land boundary to obtain an optimized water-land boundary; Continuous land-water contour lines are extracted from the optimized land-water boundary, and the land-water contour lines are converted from raster format to vector format to generate remote sensing shorelines for the target period.

[0063] Based on the above embodiments, the registration module 320 is specifically used for, including: On the initial reference shoreline, at least one rigid and invariant feature inflection point is identified and selected, and its legal coordinates in ENC are determined as the ENC reference alignment point coordinates. For each period of the remote sensing shoreline, the inflection point of the same ground feature corresponding to the ENC reference alignment point is located on the corresponding time-series remote sensing image and used as the inflection point of the same ground feature in the corresponding time-series remote sensing image. For each period of the remote sensing shoreline, based on the coordinates of the ENC reference alignment point and the coordinates of the corresponding land feature inflection point in the time-series remote sensing image, the translation parameters required to move the remote sensing shoreline of each period to be aligned with the initial reference shoreline are calculated. Based on the translation parameters, the remote sensing shoreline for each period is subjected to overall translation correction to complete rigid registration.

[0064] Based on the above embodiments, the buffer generation module 330 is specifically used for: The registered remote sensing shorelines for each period are added together with the initial reference shoreline to the input shoreline set; Configure the endpoint style of the preset spatial buffer analysis function as a flat endpoint mode, and use the preset buffer distance as the width parameter to configure the parameters of the spatial buffer analysis function; Each input item in the input shoreline set is sequentially input into the configured spatial buffer analysis function for processing, resulting in multiple strip-shaped buffers that extend only to both sides of the shoreline and are vertically truncated at both ends, serving as strip-shaped buffers for the flat-headed endpoints of each period.

[0065] Based on the above embodiments, the buffer generation module 330 is specifically used for: The current processed shoreline is obtained from the registered remote sensing shorelines of various periods and the initial reference shoreline; The current shoreline is cut into a series of short, straight segments connected end to end; For each short straight line segment, the two endpoints are shifted by a preset buffer distance along a direction perpendicular to the short straight line segment towards both the land and ocean sides, resulting in four new endpoints corresponding to each straight line segment. Connect the four new endpoints corresponding to each line segment to form multiple rectangular regions, wherein the central axis of a rectangular region is a short line segment; The rectangular regions are merged to generate a strip buffer with flat-headed endpoints that match the current processing period of the shoreline.

[0066] Based on the above embodiments, the change region determination module 340 is specifically used for: The strip buffers at all the flat-headed ends of all periods are sorted according to their corresponding period order to form a time-series buffer sequence; Starting from the earliest period in the time-series buffer sequence, the current period's strip buffer and its immediately preceding period's strip buffer are sequentially subjected to a symmetric difference operation to obtain the change region characterizing the difference in the spatial position of the shoreline between these two adjacent periods. By compiling the change areas of all adjacent periods calculated in chronological order, a time-series shoreline change area reflecting the continuous evolution of the shoreline is generated.

[0067] Based on the above embodiments, the detection result generation module 350 is specifically used for: If the time-series shoreline change area is located on the landward side of the shoreline, then the shoreline change type corresponding to the target area is determined to be a shoreline erosion area. If the time-series shoreline change area is located on the seaward side of the shoreline, then the type of shoreline change corresponding to the target area is determined to be shoreline siltation or artificial expansion area.

[0068] The shoreline dynamic change detection device provided in this embodiment of the invention can execute the shoreline dynamic change detection method provided in any embodiment of the invention, and has the corresponding functional modules and beneficial effects of the method.

[0069] The collection, storage, use, processing, transmission, provision, and disclosure of user personal information involved in the technical solution disclosed herein comply with the provisions of relevant laws and regulations and do not violate public order and good morals.

[0070] Example 4 Figure 4 A schematic diagram of an electronic device 10 that can be used to implement embodiments of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices (such as helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0071] like Figure 4As shown, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12 or a random access memory (RAM) 13, communicatively connected to the at least one processor 11. The memory stores computer programs executable by the at least one processor. The processor 11 can perform various appropriate actions and processes based on the computer program stored in the ROM 12 or loaded from storage unit 18 into the RAM 13. The RAM 13 can also store various programs and data required for the operation of the electronic device 10. The processor 11, ROM 12, and RAM 13 are interconnected via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0072] Multiple components in electronic device 10 are connected to I / O interface 15, including: input unit 16, such as keyboard, mouse, etc.; output unit 17, such as various types of displays, speakers, etc.; storage unit 18, such as disk, optical disk, etc.; and communication unit 19, such as network card, modem, wireless transceiver, etc. Communication unit 19 allows electronic device 10 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0073] Processor 11 can be various general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 11 include, but are not limited to, central processing unit (CPU), graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, digital signal processors (DSPs), and any suitable processor, controller, microcontroller, etc. Processor 11 performs the various methods and processes described above, such as performing a shoreline dynamic change detection method as described in any embodiment of the present invention, i.e.: In the official electronic nautical chart (ENC), the initial baseline shoreline of the target area and multiple time-series remote sensing images of the target area are obtained, and the remote sensing shoreline of the target area at each time period is extracted from the multiple time-series remote sensing images. The rigid, unchanging ground feature inflection points on the initial reference shoreline are selected as ENC reference alignment points. Using the coordinates of the ENC reference alignment points as a reference, the remote sensing shorelines of each period are rigidly registered, and all remote sensing shorelines are mapped to a unified spatial coordinate system. Based on the registered remote sensing shoreline of each period and the initial reference shoreline, a strip buffer zone with flat-headed endpoints for each period is constructed. Calculate the symmetrical difference set between the strip buffer zones of adjacent periods in chronological order, and determine the temporal shoreline change area based on the calculated symmetrical difference set. The time-series shoreline change area is analyzed to obtain the shoreline change type corresponding to the target area, and the time-series shoreline change area and the shoreline change type are combined into the detection result of shoreline dynamic change.

[0074] In some embodiments, a shoreline dynamic change detection method as described in any one of the embodiments of the present invention can be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program can be loaded and / or installed on electronic device 10 via ROM 12 and / or communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the shoreline dynamic change detection method described above as described in any one of the embodiments of the present invention can be performed. Alternatively, in other embodiments, processor 11 can be configured by any other suitable means (e.g., by means of firmware) to perform the shoreline dynamic change detection method as described in any one of the embodiments of the present invention.

[0075] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0076] Computer programs used to implement the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be performed. The computer programs may be executed entirely on a machine, partially on a machine, or as a standalone software package, partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0077] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0078] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0079] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or middleware components (e.g., application servers), or frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0080] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system to address the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.

[0081] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0082] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A method for detecting dynamic changes in shoreline, characterized in that, The method includes: In the official electronic nautical chart (ENC), the initial baseline shoreline of the target area and multiple time-series remote sensing images of the target area are obtained, and the remote sensing shoreline of the target area at each time period is extracted from the multiple time-series remote sensing images. The rigid, unchanging ground feature inflection points on the initial reference shoreline are selected as ENC reference alignment points. Using the coordinates of the ENC reference alignment points as a reference, the remote sensing shorelines of each period are rigidly registered, and all remote sensing shorelines are mapped to a unified spatial coordinate system. Based on the registered remote sensing shoreline of each period and the initial reference shoreline, a strip buffer zone with flat-headed endpoints for each period is constructed. Calculate the symmetrical difference set between the strip buffer zones of adjacent periods in chronological order, and determine the temporal shoreline change area based on the calculated symmetrical difference set. The time-series shoreline change area is analyzed to obtain the shoreline change type corresponding to the target area, and the time-series shoreline change area and the shoreline change type are combined into the detection result of shoreline dynamic change. Specifically, based on the registered remote sensing shoreline for each period and the initial baseline shoreline, a strip-shaped buffer zone for the flat-headed endpoints of each period is constructed, including: The registered remote sensing shorelines for each period are added together with the initial reference shoreline to the input shoreline set; Configure the endpoint style of the preset spatial buffer analysis function as a flat endpoint mode, and use the preset buffer distance as the width parameter to configure the parameters of the spatial buffer analysis function; Each input item in the input shoreline set is sequentially input into the configured spatial buffer analysis function for processing, resulting in multiple strip-shaped buffers that extend only to both sides of the shoreline and are vertically truncated at both ends, serving as strip-shaped buffers with flat-headed endpoints for each period. The current processed shoreline is obtained from the registered remote sensing shorelines of various periods and the initial reference shoreline; The current shoreline is cut into a series of short, straight segments connected end to end; For each short straight line segment, the two endpoints are shifted by a preset buffer distance along a direction perpendicular to the short straight line segment towards both the land and ocean sides, resulting in four new endpoints corresponding to each straight line segment. Connect the four new endpoints corresponding to each line segment to form multiple rectangular regions, wherein the central axis of a rectangular region is a short line segment; The rectangular regions are merged to generate a strip buffer with flat-headed endpoints that match the current processing period of the shoreline.

2. The method according to claim 1, characterized in that, From the aforementioned multi-period time-series remote sensing images, the remote sensing shoreline of the target area at each period is extracted, including: From the aforementioned multi-period time-series remote sensing images, obtain the target time-series remote sensing image for the target period; Calculate the water index of the target remote sensing image, and segment the water area and land area based on the threshold of the water index to obtain a water-land binary segmentation map; Edge detection is performed on the binary water-land segmentation map to obtain a preliminary water-land boundary, and morphological optimization processing is performed on the preliminary water-land boundary to obtain an optimized water-land boundary; Continuous land-water contour lines are extracted from the optimized land-water boundary, and the land-water contour lines are converted from raster format to vector format to generate remote sensing shorelines for the target period.

3. The method according to claim 1, characterized in that, The rigid, invariant feature inflection points on the initial baseline shoreline are selected as ENC baseline alignment points. Using the coordinates of these ENC baseline alignment points as a reference, rigid registration is performed on the remote sensing shorelines at various periods, mapping all remote sensing shorelines to a unified spatial coordinate system, including: On the initial reference shoreline, at least one rigid and invariant feature inflection point is identified and selected, and its legal coordinates in ENC are determined as the ENC reference alignment point coordinates. For each period of the remote sensing shoreline, the inflection point of the same ground feature corresponding to the ENC reference alignment point is located on the corresponding time-series remote sensing image and used as the inflection point of the same ground feature in the corresponding time-series remote sensing image. For each period of the remote sensing shoreline, based on the coordinates of the ENC reference alignment point and the coordinates of the corresponding land feature inflection point in the time-series remote sensing image, the translation parameters required to move the remote sensing shoreline of each period to be aligned with the initial reference shoreline are calculated. Based on the translation parameters, the remote sensing shoreline for each period is subjected to overall translation correction to complete rigid registration.

4. The method according to claim 1, characterized in that, In chronological order, the symmetrical difference sets between adjacent buffer zones are calculated, and based on the calculated symmetrical difference sets, the temporal shoreline change areas are determined, including: The strip buffers at all the flat-headed ends of all periods are sorted according to their corresponding period order to form a time-series buffer sequence; Starting from the earliest period in the time-series buffer sequence, the current period's strip buffer and its immediately preceding period's strip buffer are sequentially subjected to a symmetric difference operation to obtain the change region characterizing the difference in the spatial position of the shoreline between these two adjacent periods. By compiling the change areas of all adjacent periods calculated in chronological order, a time-series shoreline change area reflecting the continuous evolution of the shoreline is generated.

5. The method according to any one of claims 1-4, characterized in that, The analysis of the time-series coastline change areas yields the coastline change types corresponding to the target area, including: If the time-series shoreline change area is located on the landward side of the shoreline, then the shoreline change type corresponding to the target area is determined to be a shoreline erosion area. If the time-series shoreline change area is located on the seaward side of the shoreline, then the type of shoreline change corresponding to the target area is determined to be shoreline siltation or artificial expansion area.

6. An electronic device, characterized in that, The electronic device includes: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform the shoreline dynamic change detection method according to any one of claims 1-5.

7. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that are used to cause a processor to execute the shoreline dynamic change detection method according to any one of claims 1-5.

8. A computer program product, characterized in that, The computer program product includes a computer program that, when executed by a processor, implements the shoreline dynamic change detection method according to any one of claims 1-5.

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