Land-sea integrated partition identification correction method

Abstract

The application discloses a land-sea integration partition identification correction method, and relates to the technical field of land-sea integration partition, and comprises the following steps: acquiring real-time contrast values of each pixel point in a real-time remote sensing image; acquiring a water body threshold value based on remote sensing images of a first number of seawater regions; acquiring an initial coast segmentation line in the real-time remote sensing image based on the water body threshold value and the real-time contrast values; acquiring first kind data, acquiring first function values and second function values based on real-time water depth values and the first kind data; acquiring an adjustment reference position and an adjustment distance value based on a water depth monitoring position, the initial coast segmentation line, the first function values and the second function values; adjusting the initial coast segmentation line based on the water depth monitoring position, the adjustment reference position and the adjustment distance value to acquire an adjusted coast segmentation line; and the application is used for solving the problem that, in the existing land-sea integration partition technology, the coast line partition deviates due to the diversity of coasts when the remote sensing image is divided.

Description

Technical Field

[0001] This invention relates to the field of integrated land-sea zoning technology, specifically to a method for identifying and correcting integrated land-sea zoning. Background Technology

[0002] Against the backdrop of global climate change, the importance of coastal areas is becoming increasingly prominent, and the demand for high-precision, seamlessly integrated geographic information data in land-sea interface areas has become more urgent than ever before.

[0003] Existing coastline delineation methods rely on remote sensing imagery and on-site surveys. However, coastlines vary in type, including bedrock, sandy, silty, and biogenic coasts. These differences make it difficult to distinguish between seawater and land areas when identifying coastlines from images, leading to errors in the delineation of land-sea boundaries. Furthermore, coastlines change over time, making on-site surveys time-consuming and labor-intensive. For example, patent application CN117392363A discloses a land-sea remote sensing image zoning correction method, system, equipment, and medium. This scheme corrects remote sensing images but fails to consider that even if the images are normal, the diversity of coastlines can still cause offsets in coastline delineation. In other words, existing integrated land-sea zoning technologies, which rely on remote sensing images for delineation, suffer from offsets due to the diversity of coastlines. Summary of the Invention

[0004] This invention aims to at least partially solve one of the technical problems in the prior art by acquiring multi-band remote sensing images of a target area and labeling them as real-time remote sensing images; acquiring real-time contrast values ​​for each pixel in the real-time remote sensing images; acquiring water body thresholds based on remote sensing images of a first number of seawater regions; acquiring initial coastline division lines in the real-time remote sensing images based on the water body thresholds and real-time contrast values; acquiring water depth monitoring locations and real-time water depth values ​​based on a water depth monitoring device; acquiring a first type of data; acquiring a first function value and a second function value based on the real-time water depth value and the first type of data; acquiring an adjustment reference location and an adjustment distance value based on the water depth monitoring location, the initial coastline division line, the first function value, and the second function value; and adjusting the initial coastline division line based on the water depth monitoring location, the adjustment reference location, and the adjustment distance value to obtain an adjusted coastline division line. This addresses the problem of coastline misalignment caused by the diversity of coastlines when dividing using remote sensing images in existing integrated land-sea zoning technologies.

[0005] To achieve the above objectives, this application provides a land-sea integrated zoning identification and correction method, comprising the following steps:

[0006] Acquire multi-band remote sensing images of the target area and label them as real-time remote sensing images;

[0007] Obtain the real-time comparison value of each pixel in a real-time remote sensing image;

[0008] Water thresholds are obtained based on remote sensing images of a first number of seawater regions;

[0009] Initial coastline segmentation lines in real-time remote sensing images are obtained based on water body thresholds and real-time comparison values.

[0010] The location and real-time water depth value are obtained based on the water depth monitoring device;

[0011] Obtain the first type of data, and based on the real-time water depth value and the first type of data, obtain the first function value and the second function value;

[0012] Based on the water depth monitoring location, the initial coastline division line, the first function value, and the second function value, the adjustment reference location and adjustment distance value are obtained;

[0013] The adjusted coastline is obtained by adjusting the initial coastline based on the water depth monitoring location, the adjusted reference location, and the adjusted distance value.

[0014] Furthermore, obtaining the real-time contrast value of each pixel in the real-time remote sensing image includes the following sub-steps:

[0015] Obtain the shortwave infrared band reflectance and green band reflectance of each pixel in the real-time remote sensing image, and label them as real-time infrared reflectance and real-time green reflectance, respectively.

[0016] The real-time contrast value is obtained as follows: Hs = (F1 - F2) / (F1 + F2); where Hs is the real-time contrast value, F1 is the real-time green reflectance, and F2 is the real-time infrared reflectance.

[0017] Furthermore, obtaining the water body threshold based on remote sensing images of a first number of seawater regions includes the following sub-steps:

[0018] The remote sensing images of the first number of seawater areas are marked as historical water images;

[0019] Historical water images are treated as real-time remote sensing images to obtain the real-time comparison value of each pixel, which is then marked as the historical comparison value.

[0020] A number line is created using historical comparison values ​​as the number line, and this line is labeled as the comparison value number line.

[0021] Plot the historical comparison values ​​on the comparison value axis to obtain coordinate points, and mark them as comparison value coordinate points;

[0022] Mark the line segment of length C1 on the comparison value axis as the search line segment.

[0023] Furthermore, obtaining the water body threshold based on remote sensing images of a first number of seawater regions also includes the following sub-steps:

[0024] Obtain the length from the smallest comparison value coordinate point to the largest comparison value coordinate point, and mark it as the data length;

[0025] Get the number of coordinate points of the comparison value and mark it as the total number of comparison values;

[0026] The coverage threshold is calculated as follows: A = b × [(C ÷ D) × E]; where A is the coverage threshold, b is the coverage ratio, D is the data length, and E is the total number of comparison values.

[0027] Furthermore, obtaining the water body threshold based on remote sensing images of a first number of seawater regions also includes the following sub-steps:

[0028] The number of times the search line segment passes through the coordinate points of the comparison value is marked as the number of times it is covered in real time;

[0029] Align the leftmost segment of the search line with the coordinate point of the smallest comparison value, and determine whether the real-time coverage number is less than the coverage number threshold. If so, delete the leftmost comparison value coordinate point, move the search line to the right so that the leftmost segment of the search line coincides with the next comparison value coordinate point, and continue to determine and delete until the real-time coverage number is greater than or the coverage number threshold is reached. Then, obtain the value of the leftmost end of the search line after stopping and mark it as the water body threshold.

[0030] Furthermore, obtaining the initial coastline segmentation line in the real-time remote sensing image based on water body thresholds and real-time contrast values ​​includes the following sub-steps:

[0031] Pixels with real-time comparison values ​​greater than or equal to the water body threshold are identified and marked as water body pixels; starting from any water body pixel, the region composed of water body pixels is obtained through an eight-neighbor search method and marked as seawater region; the region outside the seawater region is marked as non-seawater region.

[0032] Obtain the pixels in the seawater region that are adjacent to the non-seawater region and mark them as water boundary pixels;

[0033] A continuous line composed of water boundary pixels is marked as the initial coastline dividing line.

[0034] Further, obtaining the first type of data, and obtaining the first function value and the second function value based on the real-time water depth value and the first type of data, includes the following sub-steps:

[0035] The first type of data includes the distance of the water depth monitoring device to the closest point to the land and the water depth monitored by the water depth monitoring device, which are marked as historical distance and historical water depth, respectively.

[0036] Obtain a second number of different historical water depths and their corresponding historical distances;

[0037] A Cartesian coordinate system was established with historical water depth as the horizontal axis and historical distance as the vertical axis, and this system was marked as the water depth comparison coordinate system.

[0038] Further, obtaining the first type of data, and obtaining the first function value and the second function value based on the real-time water depth value and the first type of data, includes the following sub-steps:

[0039] Obtain the minimum and maximum historical distances at different historical water depths, and label them as the first distance and the second distance, respectively.

[0040] The coordinate point with historical water depth as the x-axis value and first distance as the y-axis value is marked as the first coordinate point;

[0041] The coordinate point with the historical water depth as the x-axis value and the second distance as the y-axis value is marked as the second coordinate point;

[0042] Plot the first and second coordinate points in the water depth reference coordinate system;

[0043] The function is obtained by fitting all the first coordinate points, and it is marked as the first threshold function.

[0044] The function is obtained by fitting all the second coordinate points to a function, and it is marked as the second threshold function.

[0045] The real-time water depth value is used as the horizontal axis value and substituted into the first threshold function and the second threshold function respectively to obtain the first function value and the second function value.

[0046] Furthermore, obtaining the adjustment reference position and adjustment distance value based on the water depth monitoring location, the initial coastline division line, the first function value, and the second function value includes the following sub-steps:

[0047] Obtain the position of the water depth monitoring location relative to the nearest initial coastline and mark it as the adjustment reference position;

[0048] The actual distance from the water depth monitoring location to the adjustment reference location is obtained based on real-time remote sensing images and marked as the real-time image distance.

[0049] If the distance to the real-time image is less than the first function value, the first function value is marked as the distance adjustment value;

[0050] If the real-time image distance is greater than or equal to the first function value and less than or equal to the second function value, the real-time image distance is marked as the adjustment distance value;

[0051] If the distance to the real-time image is greater than the second function value, the second function value is marked as the distance adjustment value.

[0052] Furthermore, the process of adjusting the initial coastline based on the water depth monitoring location, the adjusted reference location, and the adjusted distance value to obtain the adjusted coastline includes the following sub-steps:

[0053] The difference between the distance between the water depth monitoring location and the adjustment reference location and the adjustment distance value is marked as the adjustment difference;

[0054] Obtain the adjustment difference corresponding to all water depth monitoring devices;

[0055] Obtain a straight line from any adjustment reference position to the corresponding water depth monitoring position, and mark it as the path straight line;

[0056] Using the adjustment reference position as the moving reference point, move the initial coastline along the path in a straight line until the mean of all adjustment differences is minimized, then stop moving and mark the moved initial coastline as the adjustment coastline.

[0057] The beneficial effects of this invention are as follows: This invention acquires multi-band remote sensing images of a target area and marks them as real-time remote sensing images; acquires the real-time comparison value of each pixel in the real-time remote sensing image; acquires a water body threshold based on remote sensing images of a first number of seawater regions; acquires an initial coastline segmentation line in the real-time remote sensing image based on the water body threshold and the real-time comparison value; acquires the water depth monitoring location and real-time water depth value based on a water depth monitoring device; acquires a first type of data, and acquires a first function value and a second function value based on the real-time water depth value and the first type of data; acquires an adjustment reference position and an adjustment distance value based on the water depth monitoring location, the initial coastline segmentation line, the first function value, and the second function value; and adjusts the initial coastline segmentation line based on the water depth monitoring location, the adjustment reference position, and the adjustment distance value to obtain an adjusted coastline segmentation line. The advantage lies in the ability to adjust the initial coastline segmentation line acquired from the real-time remote sensing image using sensors, which improves the accuracy of obtaining the coastline compared to a single remote sensing image segmentation, and is more convenient than a single on-site survey segmentation. It also improves the accuracy of coastline segmentation for diverse coastlines.

[0058] This invention obtains an adjusted coastline by adjusting the initial coastline based on water depth monitoring location, adjusting reference location, and adjusting distance value. Its advantage lies in that it divides the coastline by combining sensors with images, which improves the accuracy of obtaining the coastline compared to dividing it by a single remote sensing image, and is more convenient than dividing it by a single on-site survey. It also improves the accuracy of coastline division when dealing with diverse coastlines. Attached Figure Description

[0059] Figure 1 This is a flowchart illustrating the steps of the method of the present invention;

[0060] Figure 2 This is a schematic diagram of the coordinate points of the comparison values ​​in this invention;

[0061] Figure 3 This is a schematic diagram of the first threshold function and the second threshold function of the present invention;

[0062] Figure 4 This is a schematic diagram of the adjustment of the coastline dividing line according to the present invention. Detailed Implementation

[0063] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. 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 are within the scope of protection of the present invention.

[0064] Example 1, please refer to Figure 1 As shown, this application provides a land-sea integrated zoning identification and correction method, including the following steps:

[0065] Step S1: Acquire multi-band remote sensing images of the target area and label them as real-time remote sensing images; multi-band images are used to better capture seawater areas, for example, including shortwave infrared bands.

[0066] Step S2: Obtain the real-time contrast value of each pixel in the real-time remote sensing image; Step S2 includes the following sub-steps:

[0067] Step S201: Obtain the shortwave infrared band reflectance and green band reflectance of each pixel in the real-time remote sensing image, and label them as real-time infrared reflectance and real-time green reflectance, respectively.

[0068] Step S202, obtain the real-time comparison value as: Hs = (F1 - F2) / (F1 + F2); where Hs is the real-time comparison value, F1 is the real-time green reflectance, and F2 is the real-time infrared reflectance. Because water has a high green band reflectance and an extremely low short-wave infrared band reflectance, while buildings, soil, and vegetation are the opposite, the real-time comparison value can be used to determine whether it is seawater or not.

[0069] Step S3: Obtain water body thresholds based on remote sensing images of a first number of seawater regions; Step S3 includes the following sub-steps:

[0070] Step S301: Mark the remote sensing images of a first number of seawater areas as historical water images; the first number of historical water images are used to obtain the distribution range of real-time comparison values ​​of water.

[0071] Step S302: Treat the historical water image as a real-time remote sensing image, obtain the real-time comparison value of each pixel, and mark it as the historical comparison value;

[0072] Step S303: Establish a data axis based on the historical comparison values, and label it as the comparison value axis; the comparison value axis is established to observe the distribution of historical comparison values ​​and to filter out historical comparison values ​​that are abnormally small.

[0073] Step S304: Plot the historical comparison values ​​on the comparison value axis to obtain coordinate points, and mark them as comparison value coordinate points;

[0074] For practical applications, please refer to Figure 2 As shown, the obtained comparison value axis and comparison value coordinate points are shown.

[0075] Step S305: Mark the line segment of length C1 as the search line segment on the comparison value axis; the setting of C1 is based on the data length setting, that is, C1 should be much smaller than the data length. For example, if the data length is 15cm, C1 is set to 1cm.

[0076] Step S306: Obtain the length from the smallest comparison value coordinate point to the largest comparison value coordinate point, and mark it as the data length;

[0077] Step S307: Obtain the number of coordinate points of the comparison values ​​and mark them as the total number of comparison values;

[0078] Step S308, calculate the coverage threshold as: A = b × [(C ÷ D) × E]; where A is the coverage threshold, b is the coverage ratio, D is the data length, and E is the total number of comparison values; where (C ÷ D) × E represents the average number of comparison value coordinate points on a search segment. The coverage threshold is set to less than 1 to obtain the number of fewer comparison value coordinate points on the search segment, for example, b = 0.1.

[0079] In practical applications, for example, if the total number of comparison values ​​is 200, the coverage threshold is calculated as: A = 0.1 × [(1 ÷ 15) × 200] = 1.3; the calculation result is rounded to the nearest integer.

[0080] Step S309: Mark the number of times the search line segment passes through the coordinate points of the comparison value as the number of times it is covered in real time;

[0081] Step S310: Align the leftmost segment of the search line with the coordinate point of the smallest comparison value, and determine whether the real-time coverage number is less than the coverage number threshold. If so, delete the leftmost comparison value coordinate point, move the search line to the right so that the leftmost segment of the search line coincides with the next comparison value coordinate point, and continue to determine and delete until the real-time coverage number is greater than or the coverage number threshold is reached. Obtain the value of the leftmost end of the search line after stopping and mark it as the water body threshold. The water body threshold is used to filter out historical comparison values ​​that are abnormally small.

[0082] For practical applications, please refer to Figure 2As shown, the leftmost segment of the search line is aligned with the coordinate point of the smallest comparison value. At this point, the real-time coverage count is 1, which is less than the coverage count threshold of 1.3. The leftmost comparison value coordinate point is deleted, and the search line is moved to the right until the leftmost segment of the search line is aligned with the next comparison value coordinate point. At this point, the real-time coverage count is 2, which is greater than the coverage count threshold of 1.3. The search line is then stopped, and the value of the leftmost end of the search line after stopping is obtained and marked as the water body threshold of 0.2. Therefore, the water body threshold is 0.2.

[0083] Step S4: Obtain the initial coastline segmentation line in the real-time remote sensing image based on the water body threshold and real-time comparison value; Step S4 includes the following sub-steps:

[0084] Step S401: Obtain pixels with real-time comparison values ​​greater than or equal to the water body threshold and mark them as water body pixels; Starting from any water body pixel, obtain the region composed of water body pixels using the eight-neighbor search method and mark it as seawater region; Mark the region outside the seawater region as non-seawater region; Because seawater has a higher real-time comparison value and non-seawater has a lower real-time comparison value, the water body threshold can be used to determine whether it is a seawater region.

[0085] Step S402: Obtain the pixels in the seawater region that are adjacent to the non-seawater region and mark them as water boundary pixels;

[0086] Step S403: The continuous line formed by the water boundary pixels is marked as the initial coastline segmentation line; the initial coastline segmentation line is the segmentation line between the seawater and the land obtained from the image.

[0087] Step S5: Obtain the water depth monitoring location and real-time water depth value based on the water depth monitoring device; in order to correct the initial coastline division line through the water depth monitoring device.

[0088] Step S6: Obtain the first type of data; based on the real-time water depth value and the first type of data, obtain the first function value and the second function value; Step S6 includes the following sub-steps:

[0089] Step S601, the first type of data includes the distance of the water depth monitoring device to the closest point to the land and the water depth monitored by the water depth monitoring device, which are marked as historical distance and historical water depth, respectively;

[0090] Step S602: Obtain a second number of different historical water depths and their corresponding historical distances; Obtain a second number of different historical water depths and their corresponding historical distances in order to obtain the relationship between historical water depths and historical distances;

[0091] Step S603: Establish a plane rectangular coordinate system with historical water depth as the horizontal axis value and historical distance as the vertical axis value, and mark it as the water depth comparison coordinate system;

[0092] Step S604: Obtain the minimum and maximum historical distances at different historical water depths, and label them as the first distance and the second distance, respectively;

[0093] Step S605: Mark the coordinate point with the historical water depth as the x-axis value and the first distance as the y-axis value as the first coordinate point;

[0094] Step S606: Mark the coordinate point with the historical water depth as the x-axis value and the second distance as the y-axis value as the second coordinate point;

[0095] Step S607: Plot the first coordinate point and the second coordinate point in the water depth comparison coordinate system;

[0096] Step S608: Perform function fitting on all first coordinate points to obtain a function, and mark it as the first threshold function;

[0097] Step S609: Perform function fitting on all second coordinate points to obtain a function, and mark it as the second threshold function;

[0098] Step S610: Substitute the real-time water depth value as the horizontal axis value into the first threshold function and the second threshold function respectively to obtain the first function value and the second function value;

[0099] For practical applications, please refer to Figure 3 As shown, the first threshold function and the second threshold function are plotted. For example, if the real-time water depth is 0.15m, and 0.15m is used as the horizontal axis value, the first function value is 1.38m and the second function value is 1.61m. The first function value represents the function formed by the minimum historical distance under the same historical water depth, and the second function value represents the function formed by the maximum historical distance under the same historical water depth. This facilitates the determination of whether the initial coastline is offset and the correction of the initial coastline.

[0100] Step S7: Based on the water depth monitoring location, the initial coastline division line, the first function value, and the second function value, obtain the adjustment reference location and adjustment distance value; Step S7 includes the following sub-steps:

[0101] Step S701: Obtain the position of the water depth monitoring location relative to the nearest initial coastline and mark it as the adjustment reference position;

[0102] Step S702: Obtain the actual distance from the water depth monitoring position to the adjustment reference position based on the real-time remote sensing image, and mark it as the real-time image distance; obtain the real-time image distance according to the scaling ratio between the real-time remote sensing image and the actual position;

[0103] Step S703: If the distance in the real-time image is less than the first function value, mark the first function value as the adjusted distance value; this indicates that the initial coastline is shifted towards the ocean.

[0104] Step S704: If the real-time image distance is greater than or equal to the first function value and less than or equal to the second function value, mark the real-time image distance as the adjustment distance value; that is, it means that the initial coastline division line has not shifted.

[0105] Step S705: If the distance in the real-time image is greater than the second function value, mark the second function value as the adjustment distance value; adjusting the distance value facilitates the adjustment of the initial coastline segmentation line; indicating that the initial coastline segmentation line is shifted towards the land.

[0106] In practical applications, for example, if the real-time image distance is 1.82m, and the real-time image distance of 1.82m is greater than the second function value of 1.61m, then 1.61m is marked as the adjustment distance value.

[0107] Step S8 involves adjusting the initial coastline based on the water depth monitoring location, the adjusted reference location, and the adjusted distance value to obtain the adjusted coastline. Step S8 includes the following sub-steps:

[0108] Step S801: Mark the difference between the distance between the water depth monitoring position and the adjustment reference position and the adjustment distance value as the adjustment difference;

[0109] Step S802: Obtain the adjustment difference corresponding to all water depth monitoring devices; generally, there are multiple water depth monitoring devices.

[0110] Step S803: Obtain a straight line from any adjustment reference position to the corresponding water depth monitoring position, and mark it as a path line; construct the path line to facilitate the correction of the initial coastline division line by movement.

[0111] Step S804: Using the adjustment reference position as the moving reference point, move the initial coastline along the path in a straight line until the mean of all adjustment differences is minimized, then stop moving and mark the moved initial coastline as the adjusted coastline. Since there are multiple water depth monitoring devices, it is not necessary to make all adjustment differences zero. The mean of the adjustment differences only needs to be minimized. That is, the adjusted coastline obtained by this method is the closest to the actual dividing line between the ocean and the land.

[0112] For practical applications, please refer to Figure 4 As shown, if there is only one water depth monitoring location, the real-time image distance is 1.82m, and the adjustment distance value is 1.61m, the initial coastline is moved along the path in a straight line with the adjustment reference position as the moving reference point until all adjustment differences are minimized to 0m, and then the movement is stopped to obtain the adjusted coastline. Then, the actual ocean and land dividing line can be obtained by adjusting the coastline to obtain the mean high tide level required for coastline division.

[0113] Example 2: This application also provides an electronic device, which may include: a processor, a communication interface, a memory, and a communication bus. The processor, communication interface, and memory communicate with each other via the communication bus. The memory stores computer-readable instructions, and the processor can call the instructions in the memory. When the computer-readable instructions are executed by the processor, steps such as those in a land-sea integrated zoning identification and correction method are performed, achieving the following functions: acquiring multi-band remote sensing images of the target area and labeling them as real-time remote sensing images; acquiring real-time comparison values ​​for each pixel in the real-time remote sensing images; acquiring water body thresholds based on remote sensing images of a first number of seawater regions; acquiring an initial coastline division line in the real-time remote sensing images based on the water body thresholds and real-time comparison values; acquiring water depth monitoring locations and real-time water depth values ​​based on a water depth monitoring device; acquiring a first type of data, and acquiring a first function value and a second function value based on the real-time water depth values ​​and the first type of data; acquiring an adjustment reference position and an adjustment distance value based on the water depth monitoring location, the initial coastline division line, the first function value, and the second function value; and adjusting the initial coastline division line based on the water depth monitoring location, the adjustment reference position, and the adjustment distance value to obtain an adjusted coastline division line.

[0114] Furthermore, when the logical instructions in the aforementioned memory can be implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0115] Example 3: This application also provides a computer program product, which includes a computer program stored on a computer-readable storage medium. The computer program includes program instructions. When the program instructions are executed by a computer, the computer can execute a land-sea integrated zoning identification and correction method provided by the above methods. The method includes: acquiring multi-band remote sensing images of a target area and marking them as real-time remote sensing images; acquiring real-time comparison values ​​of each pixel in the real-time remote sensing images; acquiring water body thresholds based on remote sensing images of a first number of seawater areas; acquiring an initial coastline division line in the real-time remote sensing images based on the water body thresholds and real-time comparison values; acquiring water depth monitoring locations and real-time water depth values ​​based on a water depth monitoring device; acquiring a first type of data; acquiring a first function value and a second function value based on the real-time water depth value and the first type of data; acquiring an adjustment reference location and an adjustment distance value based on the water depth monitoring location, the initial coastline division line, the first function value, and the second function value; and adjusting the initial coastline division line based on the water depth monitoring location, the adjustment reference location, and the adjustment distance value to obtain an adjusted coastline division line.

[0116] Example 4: This application also provides a computer-readable storage medium storing a computer program. When executed by a processor, the computer program performs the steps of the above-described integrated land-sea zoning identification and correction method to achieve the following functions: acquiring multi-band remote sensing images of the target area and labeling them as real-time remote sensing images; acquiring real-time comparison values ​​of each pixel in the real-time remote sensing images; acquiring water body thresholds based on remote sensing images of a first number of seawater regions; acquiring initial coastline division lines in the real-time remote sensing images based on the water body thresholds and real-time comparison values; acquiring water depth monitoring locations and real-time water depth values ​​based on a water depth monitoring device; acquiring a first type of data, and acquiring a first function value and a second function value based on the real-time water depth values ​​and the first type of data; acquiring an adjustment reference location and an adjustment distance value based on the water depth monitoring location, the initial coastline division line, the first function value, and the second function value; and adjusting the initial coastline division line based on the water depth monitoring location, the adjustment reference location, and the adjustment distance value to obtain an adjusted coastline division line.

[0117] Based on the above description of the embodiments, the embodiments of the present invention can be provided as methods, systems, or computer program products. Based on this understanding, the above technical solutions, in essence or in terms of their contribution to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or certain parts of the embodiments.

[0118] In the embodiments provided in this application, it should be understood that the disclosed system or method can be implemented in other ways. The embodiments described above are merely illustrative. For example, the division of modules or units is only a logical functional division, and there may be other division methods in actual implementation. Furthermore, multiple modules or units may be combined or integrated into another system, or some features may be ignored or not executed. Additionally, the coupling or direct coupling or communication connection shown or discussed may be through some communication interfaces. The indirect coupling or communication connection between systems, modules, and units may be electrical, mechanical, or other forms.

[0119] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

Claims

1. An integrated land-sea partition identification correction method, characterized in that, The method comprises the following steps: Obtain a multi-band remote sensing image of a target area, marked as a real-time remote sensing image; Obtain a real-time contrast value of each pixel point in the real-time remote sensing image; Obtain a water body threshold value based on the remote sensing images of the first number of seawater regions; Obtain an initial coast segmentation line in the real-time remote sensing image based on the water body threshold value and the real-time contrast value; Obtain a water depth monitoring position and a real-time water depth value based on a water depth monitoring device; Obtain a first kind of data, and obtain a first function value and a second function value based on the real-time water depth value and the first kind of data; Obtain an adjustment reference position and an adjustment distance value based on the water depth monitoring position, the initial coast segmentation line, the first function value, and the second function value; Adjust the initial coast segmentation line based on the water depth monitoring position, the adjustment reference position, and the adjustment distance value to obtain an adjusted coast segmentation line; The step of obtaining a first kind of data and obtaining a first function value and a second function value based on the real-time water depth value and the first kind of data comprises the following sub-steps: The first kind of data comprises a distance of the water depth monitoring device from the land closest to the water depth monitoring device and the water depth monitored by the water depth monitoring device, respectively marked as a historical distance and a historical water depth; Obtain a second number of different historical water depths and corresponding historical distances; Establish a plane rectangular coordinate system with the historical water depths as the horizontal axis values and the historical distances as the vertical axis values, marked as a water depth reference coordinate system; Obtain a minimum historical distance and a maximum historical distance under different historical water depths, respectively marked as a first distance and a second distance; Obtain a first coordinate point with the historical water depths as the horizontal coordinate values and the first distances as the vertical coordinate values; Obtain a second coordinate point with the historical water depths as the horizontal coordinate values and the second distances as the vertical coordinate values; Draw the first coordinate point and the second coordinate point in the water depth reference coordinate system; Obtain a function by function fitting of all the first coordinate points, marked as a first threshold function; Obtain a function by function fitting of all the second coordinate points, marked as a second threshold function; Obtain a first function value and a second function value by substituting the real-time water depth value as the horizontal axis value into the first threshold function and the second threshold function respectively.

2. The land-sea integrated partition identification correction method according to claim 1, characterized in that, The step of obtaining a real-time contrast value of each pixel point in the real-time remote sensing image comprises the following sub-steps: Obtain a short-wave infrared band reflectance and a green band reflectance in each pixel point in the real-time remote sensing image, respectively marked as a real-time infrared reflectance and a real-time green reflectance; Obtain a real-time contrast value as follows: Hs=(F1-F2) / (F1+F2); wherein Hs is the real-time contrast value, F1 is the real-time green reflectance, and F2 is the real-time infrared reflectance.

3. The land-sea integrated partition identification correction method according to claim 2, characterized in that, The step of obtaining a water body threshold value based on the remote sensing images of the first number of seawater regions comprises the following sub-steps: Mark the remote sensing images of the first number of seawater regions as historical water images; Obtain a real-time contrast value of each pixel point in the historical water images as if they were real-time remote sensing images, marked as a historical contrast value; Establish a number axis with the historical contrast value as the data value of the number axis, marked as a contrast value number axis; Draw the historical contrast value on the contrast value number axis to obtain a coordinate point, marked as a contrast value coordinate point; Mark a line segment with a length of C1 on the contrast value number axis as a search line segment.

4. The land-sea integrated partition identification correction method according to claim 3, characterized in that, The step of obtaining a water body threshold value based on the remote sensing images of the first number of seawater regions further comprises the following sub-steps: Obtaining the length from the coordinate point of the minimum contrast value to the coordinate point of the maximum contrast value, and marking the length as a data length; Obtaining the number of the coordinate points of the contrast values, and marking the number as a total number of the contrast values; Calculating the coverage number threshold value as A = b × [(C ÷ D) × E], wherein A is the coverage number threshold value, b is a coverage number ratio, D is the data length, and E is the total number of the contrast values.

5. The integrated land-sea partition identification correction method according to claim 4, characterized in that, The method for obtaining the water body threshold value based on the remote sensing images of the first number of sea areas further includes the following sub-steps: Obtaining the number of the coordinate points of the contrast values, and marking the number as a total number of the contrast values; Obtaining the number of the coordinate points of the contrast values, and marking the number as a total number of the contrast values; 6. The land-sea integrated partition identification correction method according to claim 5, characterized in that, Calculating the coverage number threshold value as A = b × [(C ÷ D) × E], wherein A is the coverage number threshold value, b is a coverage number ratio, D is the data length, and E is the total number of the contrast values. The method for obtaining the water body threshold value based on the remote sensing images of the first number of sea areas further includes the following sub-steps: Obtaining the number of the coordinate points of the contrast values, and marking the number as a total number of the contrast values; Obtaining the number of the coordinate points of the contrast values, and marking the number as a total number of the contrast values; 7. The integrated land-sea partition identification correction method according to claim 6, characterized in that, Calculating the coverage number threshold value as A = b × [(C ÷ D) × E], wherein A is the coverage number threshold value, b is a coverage number ratio, D is the data length, and E is the total number of the contrast values. The method for obtaining the water body threshold value based on the remote sensing images of the first number of sea areas further includes the following sub-steps: Obtaining the number of the coordinate points of the contrast values, and marking the number as a total number of the contrast values; Obtaining the number of the coordinate points of the contrast values, and marking the number as a total number of the contrast values; Calculating the coverage number threshold value as A = b × [(C ÷ D) × E], wherein A is the coverage number threshold value, b is a coverage number ratio, D is the data length, and E is the total number of the contrast values. The method for obtaining the water body threshold value based on the remote sensing images of the first number of sea areas further includes the following sub-steps:

8. The land-sea integrated partition identification correction method according to claim 7, characterized in that, Obtaining the number of the coordinate points of the contrast values, and marking the number as a total number of the contrast values; Obtaining the number of the coordinate points of the contrast values, and marking the number as a total number of the contrast values; Calculating the coverage number threshold value as A = b × [(C ÷ D) × E], wherein A is the coverage number threshold value, b is a coverage number ratio, D is the data length, and E is the total number of the contrast values. The method for obtaining the water body threshold value based on the remote sensing images of the first number of sea areas further includes the following sub-steps: Obtaining the number of the coordinate points of the contrast values, and marking the number as a total number of the contrast values; Obtaining the number of the coordinate points of the contrast values, and marking the number as a total number of the contrast values; Calculating the coverage number threshold value as A = b × [(C ÷ D) × E], wherein A is the coverage number threshold value, b is a coverage number ratio, D is the data length, and E is the total number of the contrast values. The method for obtaining the water body threshold value based on the remote sensing images of the first number of sea areas further includes the following sub-steps: Obtaining the number of the coordinate points of the contrast values, and marking the number as a total number of the contrast values; Obtaining the number of the coordinate points of the contrast values, and marking the number as a total number of the contrast values; Calculating the coverage number threshold value as A = b × [(C ÷ D) × E], wherein A is the coverage number threshold value, b is a coverage number ratio, D is the data length, and E is the total number of the contrast values. The method for obtaining the water body threshold value based on the remote sensing images of the first number of sea areas further includes the following sub-steps: Obtaining the number of the coordinate points of the contrast values, and marking the number as a total number of the contrast values; Obtaining the number of the coordinate points of the contrast values, and marking the number as a total number of the contrast values; Calculating the coverage number threshold value as A = b × [(C ÷ D) × E], wherein A is the coverage number threshold value, b is a coverage number ratio, D is the data length, and E is the total number of the contrast values. The method for obtaining the water body threshold value based on the remote sensing images of the first number of sea areas further includes the following sub-steps: Obtaining the number of the coordinate points of the contrast values, and marking the number as a total number of the contrast values; Obtaining the number of the coordinate points of the contrast values, and marking the number as a total number of the contrast values; Calculating the coverage number threshold value as A = b × [(C ÷ D) × E], wherein A is the coverage number threshold value, b is a coverage number ratio, D is the data length, and E is the total number of the contrast values. The method for obtaining the water body threshold value based on the remote sensing images of the first number of sea areas further includes the following sub-steps: Obtaining the number of the coordinate points of the contrast values, and marking the number as a total number of the contrast values; Obtaining the number of the coordinate points of the contrast values, and marking the number as a total number of the contrast values; Calculating the coverage number threshold value as A = b × [(C ÷ D) × E], wherein A is the coverage number threshold value, b is a coverage number ratio, D is the data length, and E is the total number of the contrast values. The method for obtaining the water body threshold value based on the remote sensing images of the first number of sea areas further includes the following sub-steps: Obtaining the number of the coordinate points of the contrast values, and marking the number as a total number of the contrast values; Obtaining the number of the coordinate points of the contrast values, and marking the number as a total number of the contrast values; Calculating the coverage number threshold value as A = b × [(C ÷ D) × E], wherein A is the coverage number threshold value, b is a coverage number ratio, D is the data length, and E is the total number of the contrast values. The method for obtaining the water body threshold value based on the remote sensing images of the first number of sea areas further includes the following sub-steps: Obtaining the number of the coordinate points of the contrast values, and marking the number as a total number of the contrast values; Obtaining the number of the coordinate points of the contrast values, and marking the number as a total number of the contrast values; Calculating the coverage number threshold value as A = b × [(C ÷ D) × E], wherein A is the coverage number threshold value, b is a coverage number ratio, D is the data length, and E is the total number of the contrast values. The method for obtaining the water body threshold value based on the remote sensing images of the first number of sea areas further includes the following sub-steps: Obtaining the number of the coordinate points of the contrast values, and marking the number as a total number of the contrast values; Obtaining the number of the coordinate points of the contrast values, and marking the number as a total number of the contrast values; Calculating the coverage number threshold value as A = b × [(C ÷ D) × E], wherein A is the coverage number threshold value, b is a coverage number ratio, D is the data length, and E is the total number of the contrast values. The method for obtaining the water body threshold value based on the remote sensing images of the first number of sea areas further includes the following sub-steps: Obtaining the number of the coordinate points of the contrast values, and marking the number as a total number of the contrast values; Obtaining the number of the coordinate points of the contrast values, and marking the number as a total number of the contrast values; Calculating the coverage number threshold value as A = b × [(C ÷ D) × E], wherein A is the coverage number threshold value, b is a coverage number ratio, D is the data length, and E is the total number of the contrast values. The method for obtaining the water body threshold value based on the remote sensing images of the first number of sea areas further includes the following sub-steps: Obtaining the number of the coordinate points of the contrast values, and marking the number as a total number of the contrast values; Obtaining the number of the coordinate points of the contrast values, and marking the number as a total number of the contrast values; Calculating the coverage number threshold value as A = b × [(C ÷ D) × E], wherein A is the coverage number threshold value, b is a coverage number ratio, D is the data length, and E is the total number of the contrast values. The method

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