Underwater terrain inversion method, device, equipment, medium and product

Abstract

The invention discloses an underwater terrain inversion method, device, equipment, medium and product, and relates to the field of remote sensing information processing and application, and the method comprises the steps: carrying out the spatial position registration of an obtained multi-temporal high-resolution remote sensing image and the real data of each hydrometric station, and obtaining a registered remote sensing image; based on a water body index and a floating algae index, setting a water area and land boundary threshold value, and carrying out land and water boundary delimitation on the registered remote sensing image; performing visual inspection on the delimited remote sensing image, and determining the water area change and the water level values of a plurality of hydrometric stations in the water area at the corresponding time; obtaining a water area image according to the water area change and the water level values of the plurality of hydrological stations in the water area at the corresponding time; according to the water area image, determining a correlation relationship between the water level value of the hydrometric station and the longitude and latitude data of the hydrometric station; and determining the water level value in the water area according to the correlation. According to the invention, the water area underwater terrain inversion can be realized, and the accuracy of the inversion result is improved.

Description

Technical Field

[0001] The present invention relates to the field of remote sensing information processing and application, and in particular to an underwater terrain inversion method, device, equipment, medium and product. Background Art

[0002] The study of underwater topography in water areas can provide important information about the hydrological process of water areas, help to understand and reveal the geomorphic features of oceans and lakes, and is of great significance to understanding the geological structure and geological processes of the earth. It plays a key role in the formation and maintenance of marine ecosystems and has guiding significance for the exploration and development and utilization of marine resources. Traditional underwater topography research is mostly limited to optical shallow water areas, that is, areas where the light penetration depth is greater than or equal to the water depth, and relies on spectral reflectance for calculation, but this process is limited by many factors such as image acquisition time (solar altitude angle), water quality, and underwater environment. Summary of the invention

[0003] The purpose of the present invention is to provide an underwater terrain inversion method, device, equipment, medium and product, which can realize underwater terrain inversion in any water area where measured hydrological and water level data exist, and increase the accuracy of the inversion result.

[0004] To achieve the above object, the present invention provides the following solutions:

[0005] In a first aspect, the present invention provides an underwater terrain inversion method, the underwater terrain inversion method comprising:

[0006] Acquire multi-temporal high-resolution remote sensing images of the water area and real data of multiple hydrological stations in the water area; the real data of the hydrological stations include latitude and longitude data of the hydrological stations and multi-temporal daily water level measured data.

[0007] The multi-temporal high-resolution remote sensing image is spatially aligned with the real data of each hydrological station to obtain an aligned remote sensing image.

[0008] Based on the water body index and the phytoplankton index, the water area and land boundary thresholds are set to delineate the water and land boundaries of the registered remote sensing image to obtain the delineated remote sensing image.

[0009] The demarcated remote sensing images are visually inspected to determine changes in the water area and water level values ​​of multiple hydrological stations in the water area at corresponding times; the changes in the water area are flooded areas of the water area at different periods.

[0010] A water area image is obtained according to the water area area change and the water level values ​​of multiple hydrological stations in the water area at the corresponding time; the water area image is a long-term time series water level change image of the water area and the hydrological stations.

[0011] Based on the water area image, the correlation relationship between the water level value of the hydrological station and the latitude and longitude data of the hydrological station is determined.

[0012] According to the correlation relationship, the water level value in the water area is determined.

[0013] Optionally, before the step of spatially registering the multi-temporal high-resolution remote sensing image with the real data of each hydrological station to obtain the registered remote sensing image, the underwater terrain inversion method further includes:

[0014] The multi-temporal high-resolution remote sensing images are preprocessed; the preprocessing includes: geometric correction, atmospheric correction and clipping.

[0015] Optionally, the water index is calculated as follows:

[0016]

[0017] Among them, RWI is the water body index, NIR is the remote sensing data of the near-infrared band, and Green is the remote sensing data of the green band.

[0018] Optionally, the phytoplankton index is calculated as follows:

[0019] FAI=ρ NIR -ρ′ NIR ;

[0020]

[0021] Among them, FAI is the phytoplankton index, ρ RED is the reflectivity of the red light band, ρ NIR is the reflectivity in the near-infrared band, ρ SWIR is the reflectivity in the short-wave infrared band, λ RED is the central wavelength of the red light band, λ NIR is the central wavelength of the near-infrared band, λ SWIR is the central wavelength of the short-wave infrared band, ρ' NIR is the interpolated reflectance of the near-infrared band.

[0022] Optionally, determining the water level value in the water area according to the correlation relationship specifically includes:

[0023] When the correlation relationship is greater than or equal to a preset threshold, the longitude and latitude interpolation method is used to obtain the water level value of each location in the water area.

[0024] When the correlation relationship is less than a preset threshold, the average water level value method is used to obtain the water level value of each location in the water area.

[0025] Optionally, the underwater terrain inversion method further includes:

[0026] An underwater topographic map of the water area is generated according to the water level value in the water area.

[0027] In a second aspect, the present invention provides an underwater terrain inversion device, the underwater terrain inversion device comprising:

[0028] The remote sensing image and real data acquisition module is used to obtain multi-temporal high-resolution remote sensing images in the water area and real data of multiple hydrological stations in the water area; the real data of the hydrological stations include the latitude and longitude data of the hydrological stations and multi-temporal daily water level measured data.

[0029] The spatial position registration module is used to perform spatial position registration on the multi-temporal high-resolution remote sensing image and the real data of each hydrological station to obtain the registered remote sensing image.

[0030] The water-land boundary delineation module is used to set the water area and land boundary threshold based on the water body index and the floating algae index to delineate the water-land boundary of the registered remote sensing image to obtain the delineated remote sensing image.

[0031] The visual inspection module is used to perform a visual inspection on the delineated remote sensing image to determine the change in water area and the water level values ​​of multiple hydrological stations in the water area at corresponding times; the change in water area is the flooded area of ​​the water area at different periods.

[0032] The water area image acquisition module is used to obtain a water area image according to the water area area change and the water level values ​​of multiple hydrological stations in the water area at the corresponding time; the water area image is a long-term time series water level change image of the water area and the hydrological stations.

[0033] The correlation relationship determination module is used to determine the correlation relationship between the water level value of the hydrological site and the longitude and latitude data of the hydrological site based on the water area image.

[0034] The water level value determination module in the water area is used to determine the water level value in the water area according to the correlation relationship.

[0035] In a third aspect, the present invention provides a computer device comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement any of the underwater terrain inversion methods described above.

[0036] In a fourth aspect, the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements any of the underwater terrain inversion methods described above.

[0037] In a fifth aspect, the present invention provides a computer program product, comprising a computer program, which, when executed by a processor, implements any of the underwater terrain inversion methods described above.

[0038] According to the specific embodiments provided by the present invention, the present invention discloses the following technical effects:

[0039] The present invention provides an underwater terrain inversion method, device, equipment, medium and product. First, a multi-phase high-resolution remote sensing image in a water area and real data of multiple hydrological stations in the water area are obtained; the multi-phase high-resolution remote sensing image is spatially aligned with the real data of each hydrological station to obtain an aligned remote sensing image; secondly, based on a water body index and a phytoplankton index, a water area and land boundary threshold is set to delineate the water-land boundary of the aligned remote sensing image to obtain a delineated remote sensing image; since the reflectivity difference between the water surface and the land in the near-infrared region is large, the FAI value of the water surface is much lower than the FAI value on the land, and a reasonable threshold for the water area and land boundary is set, the water area can be well distinguished from the land area and the boundary can be visually inspected, so as to determine the change in the water area and the water level values ​​of multiple hydrological stations in the water area at the corresponding time, and obtain a water area image; finally, according to the water area image, the correlation between the water level value of the hydrological station and the longitude and latitude data of the hydrological station is determined, and the water level value in the water area is obtained by decision. Compared with the traditional underwater topography calculation based on spectral reflectance, the present invention introduces multi-temporal, high-resolution remote sensing imaging technology into the underwater topography inversion process of water areas, relying on the actual changes in water area to increase the accuracy of the inversion results. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0041] Figure 1 A schematic flow chart of an underwater terrain inversion method provided by one embodiment of the present invention.

[0042] Figure 2 A flow chart of an underwater terrain inversion method based on multi-temporal high-resolution remote sensing images provided in one embodiment of the present invention.

[0043] Figure 3 A schematic diagram of long-term changes in water levels in a water area and a hydrological station provided in an embodiment of the present invention.

[0044] Figure 4 A schematic diagram of underwater topography inversion results of a test water area provided in one embodiment of the present invention.

[0045] Figure 5 This is a diagram of the verification accuracy of the inversion results provided by an embodiment of the present invention.

[0046] Figure 6 A schematic diagram of functional modules of an underwater terrain inversion device provided in one embodiment of the present invention.

[0047] Figure 7 A schematic diagram of the structure of a computer device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0048] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0049] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and understandable, the present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0050] In recent years, with the rapid development of aerospace and satellite remote sensing technology, long-term, high-resolution remote sensing images have been widely used in the research of natural resource surveys, land use changes, etc. Therefore, multi-temporal high-resolution satellite remote sensing images can be used to obtain water cover range information, thereby indirectly obtaining water underwater topography information.

[0051] In an exemplary embodiment, Figure 1 As shown, an underwater terrain inversion method is provided, which includes the following steps S1 to S7. Among them:

[0052] S1: Acquire multi-temporal high-resolution remote sensing images of the water area and real data of multiple hydrological stations in the water area; the real data of the hydrological stations include latitude and longitude data of the hydrological stations and multi-temporal daily water level measured data.

[0053] S2: spatially registering the multi-temporal high-resolution remote sensing image with the real data of each hydrological station to obtain a registered remote sensing image.

[0054] S3: Based on the water body index and the phytoplankton index, a water area and land boundary threshold is set to delineate the water and land boundary of the registered remote sensing image to obtain a delineated remote sensing image.

[0055] S4: Visually inspect the delineated remote sensing images to determine changes in the water area and water level values ​​of multiple hydrological stations in the water area at corresponding times; the changes in the water area are flooded areas of the water area at different periods.

[0056] S5: Obtain a water area image according to the water area area change and the water level values ​​of multiple hydrological stations in the water area at the corresponding time; the water area image is a long-term time series water level change image of the water area and the hydrological stations.

[0057] S6: Determine the correlation between the water level value of the hydrological station and the longitude and latitude data of the hydrological station based on the water area image.

[0058] S7: Determine the water level value in the water area according to the correlation relationship.

[0059] Implementing the above steps S1 to S7 is conducive to realizing the inversion of underwater topography in any water area where measured hydrological and water level data exist, and is not affected by factors such as water quality and water depth of the water area. It provides a novel and reliable method for identifying underwater topography in the water area and has high use value.

[0060] The advantages of the present invention are:

[0061] (1) Traditional underwater topography is calculated based on spectral reflectance, which is limited by many factors such as image acquisition time (sun altitude angle), water quality, underwater environment, etc. The present invention introduces multi-temporal, high-resolution remote sensing imaging technology into the process of underwater topography inversion in water areas, mainly relying on the actual water area changes, which increases the accuracy of the inversion results.

[0062] (2) Based on advantage (1), the traditional method mainly focuses on the study of optical shallow water areas (areas where the light penetration depth is greater than or equal to the water depth). The present invention achieves a range breakthrough from local special areas to overall general areas, that is, the present invention can be applied to underwater topography inversion in the entire water area and obtain good inversion results.

[0063] (3) The present invention analyzes the relationship between the water level and longitude and latitude of different hydrological stations, makes decisions on the water level of the water area under different circumstances, and can simply, intuitively and accurately display the underwater topography of the water area.

[0064] Before step S2, the underwater terrain inversion method further includes:

[0065] The multi-temporal high-resolution remote sensing images are preprocessed; the preprocessing includes: geometric correction, atmospheric correction and clipping. That is, after obtaining the multi-temporal high-resolution remote sensing images in the water area and the real data of multiple hydrological stations in the water area, the multi-temporal high-resolution remote sensing images in the water area are geometrically corrected and atmospherically corrected, and then the corresponding water area remote sensing images are clipped, and the spatial position is aligned according to the real geographic coordinates based on the spatial resolution of the remote sensing images and the locations of the hydrological stations.

[0066] In step S3, the water body index method is adopted, in which the water body index uses the difference in reflectance characteristics of water bodies in the visible light and near-infrared bands to eliminate the influence of mixed pixels and cloud shadows at the boundaries of water bodies to a certain extent, and incorporates the RWI index into the supervised classification process to extract water bodies from remote sensing images.

[0067] Based on the large differences in spectral reflectance between water and land in different bands, and taking into account the effects of water depth, image shooting conditions, aquatic plants, etc., the floating algae index (FAI) is used and combined with the water body index method to delineate the water-land interface.

[0068] Due to the large difference in reflectivity between water surface and land in the near-infrared region, the FAI value on the water surface is much lower than the FAI value on land. Setting a reasonable threshold for the boundary between water and land can well distinguish water from land and conduct visual inspection of the boundary.

[0069] The water index is calculated as follows:

[0070]

[0071] Among them, RWI is the water body index, NIR is the remote sensing data of the near-infrared band, and Green is the remote sensing data of the green band.

[0072] The calculation method of the phytoplankton index is:

[0073] FAI=ρ NIR -ρ′ NIR ;

[0074]

[0075] Among them, FAI is the phytoplankton index, ρ RED is the reflectivity of the red light band, ρ NIR is the reflectivity in the near-infrared band, ρ SWIR is the reflectivity in the short-wave infrared band, λ RED is the central wavelength of the red light band, λ NIR is the central wavelength of the near-infrared band, λ SWIR is the central wavelength of the short-wave infrared band, ρ' NIRis the interpolated reflectance of the near-infrared band. It is baseline subtraction, which is actually a kind of atmospheric correction, and it is expected to produce a relatively stable FAI value under various atmospheric and image shooting conditions.

[0076] In step S4, the process of gradually increasing from the minimum water area to the maximum water area is recorded.

[0077] In step S5, a water area image is obtained, and the water level values ​​of multiple hydrological stations in the water area corresponding to the time are obtained to form a long-term water level change image of the water area and the hydrological stations. According to the spatial gradient difference of the water level values ​​of different hydrological stations at the same time, the boundary between the water area and the land is corrected.

[0078] In step S6, it is determined whether the water level changes significantly with longitude or latitude, and the correlation R between the two is determined by linear regression. 2 .

[0079] In another exemplary embodiment of the present invention, in step S7, specifically including:

[0080] S71: When the correlation relationship is greater than or equal to a preset threshold, there is a strong spatial gradient between the water level of the entire water area and the longitude and latitude, and the longitude and latitude interpolation method is used to obtain the water level value of each location in the water area.

[0081] S72: When the correlation relationship is less than the preset threshold, the water levels of the various hydrological stations are similar, and there is almost no spatial gradient between the water level and longitude and latitude of the entire water area. At this time, the average water level method is used to obtain the water level value of each location in the water area, that is, the average water level value of all hydrological stations is used as the water level value in the water area.

[0082] In another exemplary embodiment of the present invention, the underwater terrain inversion method further includes:

[0083] An underwater topographic map of the water area is generated according to the water level value in the water area.

[0084] The present invention also provides an application scenario, and the application scenario applies the underwater terrain inversion method. Specifically: the underwater terrain inversion method provided in this embodiment can be applied in an underwater terrain inversion scenario. The underwater terrain inversion scene includes a remote sensing image acquisition link, a remote sensing image analysis and processing link, and a water area underwater terrain inversion link; after obtaining multi-phase high-resolution remote sensing images in the water area and real data of multiple hydrological stations in the water area, enter the remote sensing image analysis and processing link, spatially align the multi-phase high-resolution remote sensing images with the real data of each of the hydrological stations to obtain the aligned remote sensing images; based on the water body index and the phytoplankton index, set the water area and land boundary threshold to delineate the water and land boundaries of the aligned remote sensing images to obtain the delineated remote sensing images; then enter the water area underwater terrain inversion link, visually inspect the delineated remote sensing images, determine the water area change and the water level values ​​of multiple hydrological stations in the water area at the corresponding time, obtain the water area image according to the water area change and the water level values ​​of multiple hydrological stations in the water area at the corresponding time, determine the correlation relationship between the water level value of the hydrological station and the latitude and longitude data of the hydrological station according to the water area image; determine the water level value in the water area according to the correlation relationship.

[0085] like Figure 2 As shown, the underwater terrain inversion method based on multi-temporal high-resolution remote sensing images of the present invention comprises the following steps:

[0086] Step 1: Preprocess the multi-temporal high-resolution remote sensing images of the water area, including geometric correction and atmospheric correction.

[0087] In step 1, the multi-temporal high-resolution remote sensing images of Sentinel-2 in the Poyang Lake area from 2017 to 2023 were preprocessed, including geometric correction and atmospheric correction. The preprocessing was mainly carried out using Sentinel Application Platform, which is software provided by the European Space Agency (ESA) specifically for processing and analyzing Sentinel series satellite data, and performing atmospheric correction and geometric correction.

[0088] Step 2: Collect the latitude and longitude data of multiple hydrological stations in the water area and the multi-temporal daily water level measured data; crop the remote sensing image of the corresponding water area (not shown in the figure), and perform spatial position alignment according to the real geographic coordinates based on the spatial resolution of the remote sensing image and the location of the hydrological station.

[0089] In step 2, the latitude and longitude data of hydrological stations in the Poyang Lake area and the multi-temporal daily water level measured data are collected, and the Sentinel-2 10-meter spatial resolution satellite remote sensing image and the location of the hydrological station are spatially aligned according to the real geographic coordinates. Among them, the water level data of the hydrological station is calibrated according to the elevation reference of the Woosung horizontal zero point.

[0090] Step three: Use the water body index method, in which the RWI index uses the difference in reflectance characteristics of water bodies in the visible light and near-infrared bands, and can eliminate the influence of mixed pixels and cloud shadows at the boundaries of water bodies to a certain extent. The RWI index is incorporated into the supervised classification process to extract water bodies from remote sensing images.

[0091] Based on the large differences in spectral reflectance between water and land in different bands, and taking into account the effects of water depth, image shooting conditions, aquatic plants, etc., the floating algae index (FAI) is used and combined with the water body index method to delineate the water-land interface.

[0092] Due to the large difference in reflectivity between water surface and land in the near-infrared region, the FAI value on the water surface is much lower than the FAI value on land. Setting a reasonable threshold for the boundary between water and land can well distinguish water from land and conduct visual inspection of the boundary.

[0093] In step 3, the calculation method of the water index RWI of the Sentinel-2 satellite remote sensing image is as follows:

[0094]

[0095] Where R(560), R(705), R(842), R(865), and R(2190) are the remote sensing surface reflectances of the 3rd, 5th, 8th, 8A, and 12th bands of Sentinel-2, respectively.

[0096] In step 3, the calculation method of the floating algae index FAI of the Sentinel-2 satellite remote sensing image is as follows:

[0097] FAI=ρ 842.5 -ρ′ 842.5 ;

[0098]

[0099] Step 4: Record the process of the water area gradually increasing from the minimum to the maximum. The changing part of the water area is the flooded area of ​​the water area at different times, and obtain the water area image. Obtain the water level values ​​of multiple hydrological stations in the water area corresponding to the time, and together form an image of the gradual increase of the water area and the long-term water level of the hydrological stations. According to the spatial gradient difference of the water level values ​​of different hydrological stations at the same time, the boundary between the water area and the land is corrected.

[0100] Step 5: Determine the difference between the water level values ​​of each hydrological station, and calculate the correlation between the water level value and the longitude and latitude of the hydrological station, and make a decision to obtain the water level value of the water area. The output result is the underwater topography of the water area:

[0101] (1) When the water level value at the hydrological station has a high and significant correlation with longitude and latitude (R 2 ≥0.8), there is a strong spatial gradient between the water level of the whole water area and the longitude and latitude, that is, the water level at each location in the water area can be obtained by the longitude and latitude interpolation method;

[0102] (2) When the correlation between the water level value and longitude and latitude at the hydrological station is low (R 2 <0.8, the minimum is 0), the water levels of each hydrological station are similar, and there is almost no spatial gradient between the water level and longitude and latitude of the entire water area. At this time, the average water level of all hydrological stations is used to represent the water level value of the entire water area.

[0103] The input of the inversion process is multi-temporal high-resolution remote sensing images of the water area, and the output of the inversion process is the underwater topographic map of the water area.

[0104] In this implementation case, the test area is the Poyang Lake area of ​​Jiangxi Province. Figure 3 Schematic diagram of long-term changes in water levels in water areas and hydrological stations. Figure 4 This is a schematic diagram of the underwater topography inversion results in the Poyang Lake area. The results show that the elevation range of the water area in the Poyang Lake area is 0-20 meters, and the inversion process can realize the inversion of underwater topography in the entire water area. Figure 4 This is the accuracy map for verifying the underwater topography inversion results in the Poyang Lake area. Figure 5 It can be seen that there is a strong positive correlation between the underwater topography of the Poyang Lake area in the inversion results and the measured values ​​of some points, and the correlation coefficient R 2 That is, the goodness of fit reaches 0.935.

[0105] Based on the same inventive concept, an embodiment of the present invention further provides an underwater terrain inversion device for implementing the underwater terrain inversion method involved above. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the above method, so the specific limitations of one or more underwater terrain inversion device embodiments provided below can refer to the limitations of the underwater terrain inversion method above, and will not be repeated here.

[0106] In an exemplary embodiment, Figure 6 As shown, an underwater terrain inversion device is provided, comprising:

[0107] The remote sensing image and real data acquisition module M1 is used to obtain multi-temporal high-resolution remote sensing images in the water area and real data of multiple hydrological stations in the water area; the real data of the hydrological stations include the latitude and longitude data of the hydrological stations and multi-temporal daily water level measured data.

[0108] The spatial position registration module M2 is used to perform spatial position registration on the multi-temporal high-resolution remote sensing image and the real data of each hydrological station to obtain a registered remote sensing image.

[0109] The water-land boundary delineation module M3 is used to set the water area and land boundary threshold based on the water body index and the phytoplankton index to delineate the water-land boundary of the registered remote sensing image to obtain the delineated remote sensing image.

[0110] The visual inspection module M4 is used to visually inspect the delineated remote sensing images to determine the changes in the water area and the water level values ​​of multiple hydrological stations in the water area at corresponding times; the changes in the water area are the flooded areas of the water area at different periods.

[0111] The water area image acquisition module M5 is used to obtain a water area image according to the water area area change and the water level values ​​of multiple hydrological stations in the water area at the corresponding time; the water area image is a long-term time series water level change image of the water area and the hydrological stations.

[0112] The correlation relationship determination module M6 is used to determine the correlation relationship between the water level value of the hydrological site and the longitude and latitude data of the hydrological site based on the water area image.

[0113] The water level value determination module M7 in the water area is used to determine the water level value in the water area according to the correlation relationship.

[0114] In an exemplary embodiment, a computer device is provided. The computer device may be a server or a terminal. The internal structure diagram thereof may be as follows: Figure 7As shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, referred to as I / O) and a communication interface. The processor, the memory and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store multi-phase high-resolution remote sensing images in the water area and real data of multiple hydrological stations in the water area. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a method for underwater terrain inversion is implemented.

[0115] Those skilled in the art will understand that Figure 7 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present invention, and does not constitute a limitation on the computer device to which the solution of the present invention is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0116] In an exemplary embodiment, a computer device is further provided, including a memory and a processor, wherein a computer program is stored in the memory, and the above-mentioned method embodiments are implemented when the processor executes the computer program.

[0117] In an exemplary embodiment, a computer-readable storage medium is provided, storing a computer program, and when the computer program is executed by a processor, the above-mentioned method embodiments are implemented.

[0118] In an exemplary embodiment, a computer program product is provided, including a computer program, and when the computer program is executed by a processor, the above-mentioned method embodiments are implemented.

[0119] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in the present invention are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.

[0120] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiments can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided by the present invention can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM may be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM).

[0121] The database involved in each embodiment provided by the present invention may include at least one of a relational database and a non-relational database. The non-relational database may include a distributed database based on blockchain, etc., but is not limited thereto. The processor involved in each embodiment provided by the present invention may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but is not limited thereto.

[0122] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0123] The principles and implementation methods of the present invention are described in this article using specific examples. The description of the above embodiments is only used to help understand the method and core idea of ​​the present invention. At the same time, for those skilled in the art, according to the idea of ​​the present invention, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting the present invention.

Claims

1. A method for underwater terrain inversion, characterized in that: The underwater terrain inversion method comprises: Acquire multi-temporal high-resolution remote sensing images within the water area and real data of multiple hydrological stations within the water area; the real data of the hydrological stations include latitude and longitude data of the hydrological stations and multi-temporal daily water level measured data; Performing spatial registration of the multi-temporal high-resolution remote sensing image with the real data of each hydrological station to obtain a registered remote sensing image; Based on the water body index and the phytoplankton index, a water area and land boundary threshold is set to delineate the water and land boundary of the registered remote sensing image to obtain a delineated remote sensing image; Visually inspect the delineated remote sensing images to determine changes in the water area and water level values ​​of multiple hydrological stations in the water area at corresponding times; the changes in the water area are flooded areas of the water area at different periods; According to the water area change and the water level values ​​of multiple hydrological stations in the water area at the corresponding time, a water area image is obtained; the water area image is a long-term time series water level change image of the water area and the hydrological stations; Determine the correlation between the water level value of the hydrological station and the longitude and latitude data of the hydrological station according to the water area image; According to the correlation relationship, the water level value in the water area is determined.

2. The underwater terrain inversion method according to claim 1, characterized in that: Before the step of spatially registering the multi-temporal high-resolution remote sensing image with the real data of each hydrological station to obtain the registered remote sensing image, the underwater terrain inversion method further includes: The multi-temporal high-resolution remote sensing images are preprocessed; the preprocessing includes: geometric correction, atmospheric correction and clipping.

3. The underwater terrain inversion method according to claim 1, characterized in that: The water index is calculated as follows: Among them, RWI is the water body index, NIR is the remote sensing data of the near-infrared band, and Green is the remote sensing data of the green band.

4. The underwater terrain inversion method according to claim 1, characterized in that: The calculation method of the phytoplankton index is: FAI=ρ NIR -r' NIR ; Among them, FAI is the floating algae index, ρ RED is the reflectivity of the red light band, ρ NIR is the reflectivity in the near-infrared band, ρ SWIR is the reflectivity in the short-wave infrared band, λ RED is the central wavelength of the red light band, λ NIR is the central wavelength of the near-infrared band, λ SWIR is the central wavelength of the short-wave infrared band, ρ' NIR is the interpolated reflectance of the near-infrared band.

5. The underwater terrain inversion method according to claim 1, characterized in that: According to the correlation relationship, the water level value in the water area is determined, specifically including: When the correlation relationship is greater than or equal to a preset threshold, the water level value of each location in the water area is obtained by using the longitude and latitude interpolation method; When the correlation relationship is less than a preset threshold, the average water level value method is used to obtain the water level value of each location in the water area.

6. The underwater terrain inversion method according to claim 1, characterized in that: The underwater terrain inversion method also includes: An underwater topographic map of the water area is generated according to the water level value in the water area.

7. An underwater terrain inversion device, characterized in that: The underwater terrain inversion device comprises: A remote sensing image and real data acquisition module is used to acquire multi-temporal high-resolution remote sensing images in the water area and real data of multiple hydrological stations in the water area; the real data of the hydrological stations include latitude and longitude data of the hydrological stations and multi-temporal daily water level measured data; A spatial position registration module, used for performing spatial position registration of the multi-temporal high-resolution remote sensing image with the real data of each hydrological station to obtain a registered remote sensing image; A water-land boundary delineation module is used to set water-land boundary thresholds based on a water body index and a phytoplankton index to delineate the water-land boundary of the registered remote sensing image to obtain a delineated remote sensing image; A visual inspection module is used to visually inspect the demarcated remote sensing image to determine the change in water area and the water level values ​​of multiple hydrological stations in the water area at corresponding times; the change in water area is the flooded area of ​​the water area at different periods; A water area image acquisition module, used to obtain a water area image according to the water area change and the water level values ​​of multiple hydrological stations in the water area at the corresponding time; the water area image is a long-term time series water level change image of the water area and the hydrological stations; A correlation relationship determination module is used to determine the correlation relationship between the water level value of the hydrological station and the longitude and latitude data of the hydrological station according to the water area image; The water level value determination module in the water area is used to determine the water level value in the water area according to the correlation relationship.

8. A computer device comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the underwater terrain inversion method described in any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the underwater terrain inversion method described in any one of claims 1 to 6 is implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the underwater terrain inversion method described in any one of claims 1 to 6 is implemented.

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