River network reconstruction method and device

Abstract

The embodiment of the invention provides a river network reconstruction method and device, and the method comprises the steps: determining a segmentation point of a first river reach according to first information, the first information comprises the first river reach and first elevation information, the first elevation information comprises a plurality of pieces of height information in one-to-one correspondence with a plurality of pixels forming a first region, the first river reach is located in the first area; based on the segmentation point of the first river reach, the first river reach is segmented into a plurality of sub-river reaches, and the elevation change curvature corresponding to any one of the sub-river reaches is smaller than or equal to a first threshold value. By means of the method or device, the hydraulic property of the longitudinal section of the river can be considered in the river reach segmentation process, the elevation change curvature corresponding to the segmented river reach is smaller than or equal to the first threshold value, the consistency of the hydraulic property of the river reach can be better, and the display precision of a river network can also be improved.

Description

Technical Field

[0001] Embodiments of the present application relate to the field of hydrological applications, and more particularly, to a method and apparatus for river network reconstruction. Background Art

[0002] In existing vector river network reconstruction methods, river reaches in river network data are directly determined based on the flow relationship of water in space, and the basin density of machine learning is used as the basis for river network segmentation. Among them, the calculation of basin density depends on the training and learning of high-precision river network data, and the segmentation is difficult; moreover, in the segmented river reaches, there may be sub-river reaches with different gradients in the same river reach. Summary of the Invention

[0003] The present application provides a method, apparatus, and electronic device for river network reconstruction. Through this method, apparatus, and electronic device, the hydraulic properties of the river longitudinal profile can be considered during the process of segmenting river reaches, the consistency of the hydraulic properties of the river reaches can be better, and the display accuracy of the river network can also be improved.

[0004] In a first aspect, a method for river network reconstruction is provided. The method includes: determining a segmentation point of a first river reach according to first information, where the first information includes the first river reach and first elevation information, the first elevation information includes a plurality of height information corresponding one-to-one to a plurality of pixels constituting a first region, and the first river reach is located in the first region; based on the segmentation point of the first river reach, segmenting the first river reach into a plurality of sub-river reaches, and the elevation change curvature corresponding to any one of the plurality of sub-river reaches is less than or equal to a first threshold.

[0005] In some embodiments, the first elevation information may be a digital elevation model.

[0006] In some embodiments, the first elevation information is composed of one or more pixels, and the one or more pixels are presented as grids of the same size. The grid may be, for example, a square grid with a side length of d.

[0007] It can be understood that the width d of the pixels included in the first elevation information can also be understood as the resolution of the first elevation information. For the same first river reach, when segmenting the first river reach, if the resolutions of the input first elevation models are different, the number of pixels intersecting with the first river reach obtained may be different, which may lead to different elevation change curvatures corresponding to the calculated intersecting pixels, different first thresholds, and ultimately different determined segmentation points. Therefore, under the condition that the information of the input first river reach and the first elevation information are the same (the resolution is also the same), the determined segmentation points should be the same.

[0008] It should be understood that the first information may further include information on the second river section. According to the above method, the segmentation points of the second river section can be obtained, and then the second river section can be segmented. Similarly, the segmentation of multiple river sections in a certain basin can be achieved in sequence, and even the segmentation of all river sections in a certain river network can be achieved. This segmentation can be an automatic segmentation implemented according to the above method.

[0009] In the embodiments of the present application, during the process of segmenting the river section, the hydraulic properties of the river longitudinal profile can be considered, and the existing river section can be further segmented into multiple sub-river sections. After segmentation, the consistency of the hydraulic properties of the obtained river sections is better, and the display accuracy of the river network can also be improved.

[0010] Combined with the first aspect, in a possible implementation manner, determining the segmentation point of the first river section according to the first information includes: determining N intersecting pixels according to the first information, where the intersecting pixels are the pixels among the multiple pixels constituting the first region that intersect the first river section, and N is a positive integer greater than or equal to 1; determining the segmentation point of the first river section according to the N intersecting pixels.

[0011] Combined with the first aspect, in a possible implementation manner, determining the segmentation point of the first river section according to the N intersecting pixels includes: determining the elevation change curvature corresponding to the i-th intersecting pixel, where the i-th intersecting pixel belongs to the N intersecting pixels, and i = m + 1, m + 2, m + 3, …, N - m, and both i and m are positive integers greater than or equal to 1; when the elevation change curvature corresponding to the i-th intersecting pixel is greater than the first threshold, determining the position where the i-th intersecting pixel is located as the segmentation point of the first river section.

[0012] In some embodiments, the value range of m is any positive integer within the range of 1 to N / 2, for example, m = 1 or 2.

[0013] Among them, the process of determining the segmentation point of the first river section by the above method can be described as a sliding window calculation process. 2m + 1 intersecting pixels are the sliding window width, and the i-th intersecting pixel is the center of the sliding window of 2m + 1 intersecting pixels. This process can be understood as: using a sliding window to calculate the second-order differential of the elevation change at consecutive multiple intersecting pixel positions on the first river section from upstream to downstream, and further determining the segmentation point of the first river section according to the second-order differential value.

[0014] In still some other embodiments, the value range of the first threshold corresponding to the i-th intersecting pixel can be:

[0015] Among them, H max refers to the maximum value among the height corresponding to the (i - m)-th intersecting pixel, …, the height corresponding to the i-th intersecting pixel, …, the height corresponding to the (i + m)-th intersecting pixel; H minIt refers to the minimum value among the heights corresponding to the (i - m)-th intersecting pixel, …, the height corresponding to the i-th intersecting pixel, …, and the height corresponding to the (i + m)-th intersecting pixel.

[0016] It can also be described as: H max is the maximum value among the 2m + 1 heights corresponding one-to-one to the (i - m)-th intersecting pixel to the (i + m)-th intersecting pixel, and H min is the minimum value among the 2m + 1 heights corresponding one-to-one to the (i - m)-th intersecting pixel to the (i + m)-th intersecting pixel.

[0017] Among them, 2m + 1 can be understood as the width of the above-mentioned sliding window.

[0018] In the embodiments of the present application, a parameter (elevation change curvature) describing the hydraulic properties of the river longitudinal profile is introduced as the basis for river network segmentation, enabling the river network segmentation to have a physical mechanism basis, which can improve the consistency of the hydraulic properties of river reaches and also improve the display accuracy of the river network; moreover, the elevation change curvature is determined based on the superposition analysis of the digital elevation model and the current river reach. The digital elevation model is relatively easy to obtain, and the calculation method is simple and feasible, with low difficulty in river network reconstruction;

[0019] Moreover, by using a sliding window to calculate the second derivative of the elevation change at consecutive multiple intersecting pixel positions from upstream to downstream, the second differential (i.e., elevation change curvature) of each intersecting pixel position can be obtained, and further, based on the obtained second differential, it can be determined whether the intersecting pixel position is used as a river reach segmentation point. By sequentially performing numerical second differential calculations on the intersecting pixels, an objective basis for the automatic segmentation of river reaches is also provided, and the automatic reconstruction of large-scale river networks can be realized.

[0020] Combined with the first aspect, in a possible implementation manner, determining the elevation change curvature corresponding to the i-th intersecting pixel includes: determining the elevation change curvature corresponding to the i-th intersecting pixel according to the height corresponding to the (i - m)-th intersecting pixel, the height corresponding to the i-th intersecting pixel, and the height corresponding to the (i + m)-th intersecting pixel.

[0021] Combined with the first aspect, in a possible implementation manner, the method further includes: reconstructing the spatial attributes of the first river reach based on the one or more sub-river reaches.

[0022] In some embodiments, reconstructing the spatial attributes of the first river reach includes numbering the multiple sub-river reaches obtained by segmentation (for example: setting an id attribute for the sub-river reach), and establishing the upstream and downstream relationships between the multiple sub-river reaches (for example: setting a next attribute for the sub-river reach).

[0023] In the embodiments of the present application, after the river section is segmented, spatial attributes are set for the multiple sub-river sections obtained by the segmentation, so that there is a clear upstream and downstream relationship between all the segmented river sections.

[0024] Combined with the first aspect, in a possible implementation manner, before determining the N intersecting pixels according to the first information, the method further includes: obtaining the first information.

[0025] Combined with the first aspect, in a possible implementation manner, the method further includes: outputting a reconstructed river network diagram, and the multiple sub-river sections are marked on the reconstructed river network diagram.

[0026] In a second aspect, a device for river network reconstruction is provided. The device includes: a determination module, configured to determine a segmentation point of a first river section according to first information, where the first information includes the first river section and first elevation information, and the first elevation information includes multiple height information corresponding one by one to multiple pixels constituting a first area, and the first river section is located in the first area; a reconstruction module, configured to segment the first river section into multiple sub-river sections based on the segmentation point of the first river section, and the elevation change curvature corresponding to any one of the multiple sub-river sections is less than or equal to a first threshold.

[0027] In some embodiments, the first elevation information may be a digital elevation model.

[0028] In some embodiments, the first elevation information is composed of one or more pixels, and the one or more pixels are presented as grids with the same size. The grid may be, for example, a square grid with a side length of d.

[0029] It can be understood that the width d of the pixels included in the first elevation information can also be understood as the resolution of the first elevation information. For the same first river section, when the resolution of the first elevation model input during the segmentation of the first river section is different, the number of pixels intersecting with the first river section obtained may be different, which may lead to different elevation change curvatures corresponding to the calculated intersecting pixels, different corresponding first thresholds, and finally different determined segmentation points. Therefore, when the information of the input first river section and the first elevation information are the same (the resolution is also the same), the determined segmentation points should be the same.

[0030] It should be understood that the first information may further include information of a second river section. According to the above process, the device can also obtain the segmentation point of the second river section, and then segment the second river section. Similarly, it is possible to sequentially segment multiple river sections in a certain basin, and even segment all the river sections in a certain river network. The segmentation can be an automatic segmentation implemented based on the above device.

[0031] In the embodiments of the present application, during the process of segmenting river reaches, the hydraulic properties of the river longitudinal profile can be considered, and the existing river reaches can be further segmented into multiple sub-river reaches. After segmentation, the consistency of the hydraulic properties of the obtained river reaches is better, and the display accuracy of the river network can also be improved.

[0032] In combination with the second aspect, in a possible implementation manner, the determining module is specifically configured to: determine N intersecting pixels according to the first information, where the intersecting pixels are pixels among the multiple pixels forming the first area that intersect the first river reach, and N is a positive integer greater than or equal to 1; determine the segmentation point of the first river reach according to the N intersecting pixels.

[0033] In combination with the second aspect, in a possible implementation manner, the determining module is specifically configured to: determine the elevation change curvature corresponding to the i-th intersecting pixel, where the i-th intersecting pixel belongs to the N intersecting pixels, and i = m + 1, m + 2, m + 3, …, N - m, and both i and m are positive integers greater than or equal to 1; when the elevation change curvature corresponding to the i-th intersecting pixel is greater than the first threshold, determine the position where the i-th intersecting pixel is located as the segmentation point of the first river reach.

[0034] In some embodiments, the value range of m is any positive integer within the range of 1 to N / 2, for example, m = 1 or 2.

[0035] Among them, the process of the determining module determining the segmentation point of the first river reach can be described as the determining module determining the segmentation point of the first river reach through sliding window calculation. The 2m + 1 intersecting pixels are the sliding window width, and the i-th intersecting pixel is the center of the sliding window of the 2m + 1 intersecting pixels. This process can be understood as: the determining module uses sliding window calculation to calculate the second-order differential of the elevation change at the positions of multiple consecutive intersecting pixels from upstream to downstream on the first river reach, and further determines the segmentation point of the first river reach according to the second-order differential value.

[0036] In the embodiments of the present application, a parameter (elevation change curvature) describing the hydraulic properties of the river longitudinal profile is introduced as the basis for river network segmentation, so that the river network segmentation has a physical mechanism basis, can improve the consistency of the hydraulic properties of the river reaches, and can also improve the display accuracy of the river network; moreover, the elevation change curvature is determined based on the superposition analysis of the digital elevation model and the current river reach. The digital elevation model is relatively easy to obtain, the calculation method is simple and easy to implement, and the difficulty of river network reconstruction is low.

[0037] Moreover, by using a sliding window calculation to obtain the second derivative of the elevation change at a series of consecutive intersecting pixel positions from upstream to downstream, the second differential (i.e., the curvature of the elevation change) of each intersecting pixel position can be obtained, and further, based on the obtained second differential, it can be determined whether the intersecting pixel position is a river segment segmentation point. By sequentially performing numerical second differential calculations on the intersecting pixels, an objective basis for the automatic segmentation of river segments is also provided, enabling the automatic reconstruction of large-scale river networks.

[0038] In combination with the second aspect, in a possible implementation, the determination module is further specifically configured to: determine the elevation change curvature corresponding to the i-th intersecting pixel based on the height corresponding to the (i - m)-th intersecting pixel, the height corresponding to the i-th intersecting pixel, and the height corresponding to the (i + m)-th intersecting pixel.

[0039] In combination with the second aspect, in a possible implementation, the reconstruction module is further configured to: reconstruct the spatial attributes of the first river segment based on the one or more sub-river segments.

[0040] In some embodiments, reconstructing the spatial attributes of the first river segment includes numbering the multiple sub-river segments obtained by segmentation (e.g., setting an id attribute for the sub-river segments), and establishing the upstream and downstream relationships between the multiple sub-river segments (e.g., setting a next attribute for the sub-river segments).

[0041] In the embodiments of the present application, after the river segment segmentation is completed, spatial attributes are set for the multiple sub-river segments obtained by segmentation, so that there is a clear upstream and downstream relationship between all the segmented river segments.

[0042] In combination with the second aspect, in a possible implementation, the apparatus further includes: an acquisition module, configured to acquire the first information.

[0043] In combination with the second aspect, in a possible implementation, the apparatus further includes: an output module, configured to output a reconstructed river network map, on which the multiple sub-river segments are marked.

[0044] In a third aspect, an electronic device is provided, which includes a memory and a processor. The memory is used to store computer program code, and the processor is used to execute the computer program code stored in the memory to implement the method in the first aspect or any possible implementation manner of the first aspect.

[0045] In a fourth aspect, a computer-readable storage medium is provided, in which computer programs or instructions are stored. When the computer programs or instructions are executed, the method in the first aspect or any possible implementation manner of the first aspect is implemented.

[0046] In a fifth aspect, a chip is provided, which stores instructions that, when running on a device, cause the chip to execute the method in the above first aspect or any one of the possible implementation manners in the first aspect. Description of the Drawings

[0047] Figure 1 FIG. is a schematic flow chart of a method for generating a river channel map provided by an embodiment of the present application;

[0048] Figure 2 FIG. is a schematic flow chart of a method for river network reconstruction provided by an embodiment of the present application;

[0049] Figure 3 FIG. is a schematic flow chart of another method for river network reconstruction provided by an embodiment of the present application;

[0050] Figure 4 FIG. is a schematic diagram of the relationship among a first digital elevation model, a first river section, and an intersecting pixel provided by an embodiment of the present application;

[0051] Figure 5 FIG. is a schematic diagram of the effect of the river network reconstruction method provided by an embodiment of the present application;

[0052] Figure 6 FIG. is a schematic diagram of the functional modules of a device for river network reconstruction provided by an embodiment of the present application. Detailed Embodiments

[0053] Next, the technical solutions in the present application will be described with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all of the embodiments.

[0054] Next, the technical solutions in the embodiments of the present application will be described with reference to the accompanying drawings in the embodiments of the present application. Among them, in the description of the embodiments of the present application, unless otherwise specified, " / " means "or", for example, A / B may mean A or B; herein, "and / or" is only a description of the association relationship of associated objects, indicating that three relationships may exist, for example, A and / or B may mean: A exists alone, A and B exist simultaneously, and B exists alone. In addition, in the description of the embodiments of the present application, "a plurality of" or "multiple" means two or more than two.

[0055] Hereinafter, the terms "first" and "second" are only used for descriptive purposes and cannot be construed as indicating or implying relative importance or implicitly specifying the quantity of the indicated technical features. Thus, the features defined with "first" and "second" may explicitly or implicitly include one or more of such features. In the description of this embodiment, unless otherwise specified, the meaning of "a plurality of" is two or more than two.

[0056] The terms used in the following embodiments are only for the purpose of describing specific embodiments and are not intended to limit the present application. As used in the specification and appended claims of the present application, the singular forms "a", "an", "the", "above-mentioned", "this", and "such" are also intended to include expressions such as "one or more", unless the context clearly indicates otherwise. It should also be understood that in the following embodiments of the present application, "at least one" and "one or more" mean one, two, or more than two. The term "and / or" is used to describe the relationship between associated objects and indicates that three relationships can exist; for example, A and / or B can mean: A exists alone, A and B exist simultaneously, or B exists alone, where A and B can be singular or plural. The character " / " generally indicates that the associated objects before and after are in an "or" relationship.

[0057] Reference to "one embodiment" or "some embodiments" etc. described in this specification means that a specific feature, structure, or characteristic described in connection with that embodiment is included in one or more embodiments of the present application. Thus, statements such as "one embodiment", "some embodiments", "another embodiment", "some other embodiments", etc. that appear in different places in this specification do not necessarily all refer to the same embodiment, but mean "one or more but not all embodiments", unless otherwise specifically emphasized in other ways. The terms "comprising", "including", "having" and their variants all mean "including but not limited to", unless otherwise specifically emphasized in other ways.

[0058] The method provided by the embodiments of the present application can be applied to electronic devices with a time display function or a time recognition function, such as mobile phones, tablet computers, wearable devices, in-vehicle devices, augmented reality (AR) / virtual reality (VR) devices, laptop computers, ultra-mobile personal computers (UMPCs), netbooks, personal digital assistants (PDAs), smart home devices, etc. The embodiments of the present application do not impose any restrictions on the specific types of electronic devices.

[0059] It should be understood that the technical solutions in the embodiments of the present application can be used in systems such as Android, IOS, HarmonyOS, etc.

[0060] The technical solution of the embodiment of the present application can be applied to the river network reconstruction scenario. The reconstructed river network can be used to calculate and simulate the flow in the river course, and can play an important role in information services such as basin hydrological flood forecasting, water resource scheduling, and geographic information processing, as well as in software tools for geographic information systems.

[0061] The method provided by the embodiment of the present application can be applied to the platform as a service (PaaS) layer platform products in the water conservancy industry, such as the "whole river network water regime base" platform, etc.; the method provided by the embodiment of the present application can also be carried on public cloud services or integrated private deployment small data centers (all-in-one machines) including infrastructure as a service (IaaS) + PaaS + software as a service (SaaS), etc.

[0062] In the existing vector river network reconstruction methods, the river reaches in the river network data are directly determined according to the flow relationship of water in space. The basin density of machine learning is used as the basis for river network segmentation. The calculation of basin density depends on the training and learning of high-precision river network data, and the segmentation is difficult; moreover, the river network segmentation does not consider the hydraulic properties of the river longitudinal profiles with different slopes in the river reaches, resulting in sub-river reaches with different gradients in the same river reach.

[0063] In view of this, the embodiment of the present application provides a method and device for river network reconstruction. Through this method or device, each river reach in the river network can be further segmented into multiple different sub-river reaches according to the hydraulic properties of the longitudinal profile of each river reach in the river network, and the original river reaches are replaced by these segmented sub-river reaches, thereby reconstructing a new river network and improving the display fineness of the river network.

[0064] To more clearly understand the solution of the present application, first, some terms involved in the embodiment of the present application will be introduced below.

[0065] 1. Digital river network

[0066] A river network refers to a water system composed of densely distributed and crisscrossed river courses.

[0067] Digital river networks belong to a type of basic information in geographic information systems and water conservancy digital twin applications (such as digital twin basins, distributed hydrological model applications, etc.). Through digital river networks, the flow in the river can be calculated and simulated, playing an important role in information services such as basin hydrological flood forecasting, water resource scheduling, and geographic information processing, as well as in software tools for geographic information systems. Digital river networks can be divided into raster digital river networks and vector digital river networks. Among them, vector digital river networks can describe the river network of the basin with fewer linear elements by expressing rivers of different lengths through linear elements, thereby reducing the computational amount of simulating the water flow in the river.

[0068] 2. Basin density

[0069] The basin density can be characterized as the total length of all rivers in the basin divided by the basin area, that is, the river length per unit basin area.

[0070] 3. Digital elevation model (DEM)

[0071] The digital elevation model realizes the digital simulation of the ground terrain through limited terrain elevation data (that is, the digital expression of the terrain surface morphology). It is a solid ground model representing the ground elevation in the form of an ordered numerical array. The digital elevation model consists of multiple evenly distributed pixels. The width of these multiple pixels is d, and the width of the pixel can also be understood as the resolution of the digital elevation model. Each of these multiple pixels corresponds to a set of (longitude, latitude, altitude).

[0072] The solution of the embodiment of the present application can be applied to the process of generating a river map. Exemplarily, Figure 1 shows a schematic flowchart of a method 100 for generating a river map provided by an embodiment of the present application. As Figure 1 shown, the method 100 includes:

[0073] S101: Obtain the original river network data.

[0074] Among them, the original river network data may include one or more of the following data: river network data extracted based on elevation data, river network data extracted according to maps, remote sensing images, etc.

[0075] S102: Reconstruct the river network based on the original river network data.

[0076] Among them, river network reconstruction may include spatial statistical analysis along the river network and identification of river segment segmentation points.

[0077] S103: Water conservancy digital twin.

[0078] Among them, the digital twin of water conservancy after river network reconstruction can include the simulation and visualization of hydraulic spatial elements.

[0079] S104: Flow simulation calculation.

[0080] Among them, the flow simulation calculation can include the spatial discretization of the river channel and the simulation calculation of the flow evolution.

[0081] S105: Visualization of the river channel map.

[0082] Among them, the visualization of the river channel map can include the refined rendering display of the river.

[0083] The solution of the embodiment of the present application can be regarded as an improvement to the river network reconstruction process described in S102.

[0084] Exemplarily, Figure 2 shows a schematic flowchart of a river network reconstruction method 200 provided by an embodiment of the present application. As Figure 2 shown, the method 200 includes:

[0085] S201: Determine one or more intersecting pixels according to the first information.

[0086] Among them, the first information includes the information of the first river section and the first digital elevation model, the first digital elevation model covers the first river section, and the intersecting pixels are the pixels in the first digital elevation model that intersect the first river section.

[0087] Among them, the information of the first river section can be the position information of the first river section, for example, it can be the longitude information and latitude information of the first river section.

[0088] In some embodiments, the first information can be the input information of the user.

[0089] In one example, when the method 200 is applied to a cloud platform, the user can input the first information through the platform interface, and the output finally presented by the cloud platform can be a river network map, which includes multiple visible river sections and river section segmentation points.

[0090] In a specific example, the user inputs the first river section and the first digital elevation model through the platform interface, and the output finally presented by the cloud platform can be the segmentation form of the first river section, and the first river section is segmented into multiple sub-river sections.

[0091] In some embodiments, the first digital elevation model includes multiple pixels, and the multiple pixels correspond one-to-one to multiple sets of (longitude, latitude, height) information.

[0092] In some embodiments, the first river segment is associated with a first attribute and a second attribute. The first attribute is used to represent the number of the first river segment, and the second attribute is used to represent the number of the downstream river segment adjacent to the first river segment. In one example, the first attribute can be represented by an id string, and the second attribute can be represented by a next string.

[0093] Among them, the first river segment is presented as a broken line composed of one or more line segments connected end to end, and the first digital elevation model is presented as one or more pixels. The specific explanations of the first river segment and the first digital elevation model will be described in combination with the accompanying drawings in subsequent embodiments and will not be elaborated here for the time being.

[0094] This step can also be understood as establishing a mapping relationship between the first river segment and the first digital elevation model.

[0095] In some embodiments, the one or more determined intersecting pixels form a pixel sequence in the order from upstream to downstream. Since the first river segment is usually presented as a broken line composed of line segments connected end to end, determining the one or more pixels in the first digital elevation model that intersect the first river segment can be decomposed into: respectively determining the pixels in the first digital elevation model that intersect each line segment constituting the first river segment, and then forming a pixel sequence with the determined all pixels in the order from upstream to downstream.

[0096] In some embodiments, each of the one or more determined intersecting pixels is associated with its own row number and column number in the first digital elevation model. It can also be understood that the process of determining the one or more intersecting pixels is essentially a process of determining the row numbers and column numbers of the one or more intersecting pixels in the first digital elevation model. That is to say, the identification method of the intersecting pixels can be (row number, column number).

[0097] In one implementation manner, the pixel sequence composed of the one or more intersecting pixels in the order from upstream to downstream is essentially a sequence composed of multiple (row number, column number) identifiers, where each (row number, column number) identifier represents an intersecting pixel.

[0098] S202: Determine the segmentation points of the first river segment according to the one or more intersecting pixels.

[0099] In some embodiments, determine the elevation change curvature corresponding to the i-th intersecting pixel among the one or more intersecting pixels, where i = 1, 2, 3,..., and i is a positive integer greater than or equal to 1; when the elevation change curvature corresponding to the i-th intersecting pixel is greater than the first threshold, determine the position where the i-th intersecting pixel is located as the segmentation point of the first river segment. By analogy, all the segmentation points in the first river segment can be determined in turn.

[0100] In some embodiments, the value of the first threshold depends on the steepness of the terrain, and its value can be, for example, the standard deviation of the elevation of the basin where the first river segment is located multiplied by the first coefficient.

[0101] S203: Divide the first river segment into one or more sub - river segments according to the segmentation points of the first river segment.

[0102] Among them, the elevation change curvature corresponding to any one of the one or more sub - river segments obtained by segmentation is less than or equal to the first threshold, which can be specifically understood as: the elevation change curvature corresponding to each of the one or more intersecting pixels on the any one of the sub - river segments is less than or equal to the first threshold.

[0103] It should be understood that the elevation change curvature corresponding to any one of the one or more sub - river segments obtained by segmentation being less than or equal to the first threshold means that the hydraulic properties of the sub - river segments obtained after segmentation are more consistent in the longitudinal profile.

[0104] It should be understood that the river network can include multiple river basins, and a river basin can include multiple river segments. In the embodiments of the present application, a certain river segment (i.e., the first river segment) in a river basin is taken as an example to illustrate the river segment segmentation method, but this does not limit the applicable scenarios of the solution of the present application. Through the method provided by the embodiments of the present application, multiple river segments in the river basin can be segmented.

[0105] In the embodiments of the present application, a parameter (elevation change curvature) describing the hydraulic properties of the river longitudinal profile is introduced as the basis for river network segmentation, so that the river network segmentation has a physical mechanism basis, can improve the consistency of the hydraulic properties of the river segments, and can also improve the display accuracy of the river network; moreover, the elevation change curvature is determined based on the superposition analysis of the digital elevation model and the current river segment. The digital elevation model is relatively easy to obtain, the calculation method is simple and feasible, and the difficulty of river network reconstruction is low.

[0106] Exemplarily, Figure 3 shows a schematic flowchart of another river network reconstruction method 300 provided by the embodiments of the present application. As Figure 3 shown, the method 300 includes:

[0107] S301: Obtain first information, where the first information includes a first river segment and a first digital elevation model.

[0108] Among them, the explanations of the first river segment and the first digital elevation model have been described in detail in the Figure 2 shown embodiments. For the sake of brevity, they will not be elaborated here.

[0109] S302: Determine N intersecting pixels according to the first information, where N is a positive integer greater than or equal to 1.

[0110] Among them, the explanation of the N intersecting pixels is the same as the explanation of one or more intersecting pixels in the Figure 2 illustrated embodiment, that is to say, the N intersecting pixels are all the pixels in the first digital elevation model that intersect the first river section.

[0111] Among them, each of the N intersecting pixels is associated with its own row number and column number. It can also be understood that the row number and column number of the intersecting pixel are associated with the corresponding longitude and latitude.

[0112] S303: Determine the height corresponding to the i-th intersecting pixel among the N intersecting pixels according to the row number and column number of the i-th intersecting pixel in the first digital elevation model, where the initial value of i is m + 1, and both i and m are positive integers greater than or equal to 1.

[0113] In some embodiments, the value range of i can be m + 1 ≤ i ≤ N - m.

[0114] In some embodiments, the value of m is less than N / 2, (i - m) is greater than or equal to 1, and (i + m) is less than or equal to N. For example, m can be equal to 1 or 2.

[0115] Among them, the height corresponding to the i-th intersecting pixel refers to the elevation height corresponding to the i-th intersecting pixel.

[0116] In some embodiments, this step can be understood as: during the process of determining the river section segmentation point, the height of the intersecting pixel is retrieved based on the row number and column number of the intersecting pixel through an algorithm.

[0117] S304: Determine the elevation change curvature corresponding to the i-th intersecting pixel according to the height corresponding to the (i - m)-th intersecting pixel, the height corresponding to the i-th intersecting pixel, and the height corresponding to the (i + m)-th intersecting pixel.

[0118] In one example, the calculation formula for the elevation change curvature corresponding to the i-th intersecting pixel is:

[0119] Among them, H i is the height corresponding to the i-th intersecting pixel; H (i-m) is the height corresponding to the (i - m)-th intersecting pixel; H (i+m) is the height corresponding to the (i + m)-th intersecting pixel.

[0120] It can also be understood that: the (i - m)-th intersecting pixel, …, the i-th intersecting pixel, …, the (i + m)-th intersecting pixel form a sliding window with a width of 2m + 1. The (i - m)-th intersecting pixel is the leftmost pixel of the sliding window with a width of 2m + 1, the i-th intersecting pixel is the middle pixel of the sliding window with a width of 2m + 1, and the (i + m)-th intersecting pixel is the rightmost pixel of the sliding window with a width of 2m + 1. Among them, the i-th intersecting pixel can be used as the center of the sliding window. When the (m + 1)-th intersecting pixel to the (N - m)-th intersecting pixel are used as the center of the sliding window in sequence, the elevation change curvature corresponding to the (m + 1)-th intersecting pixel to the (N - m)-th intersecting pixel can be obtained in sequence.

[0121] S305: Determine whether the elevation change curvature corresponding to the i-th intersecting pixel is greater than the first threshold. If so, execute S306; if not, directly execute S307.

[0122] In some other embodiments, the value range of the first threshold corresponding to the i-th intersecting pixel can be:

[0123] Among them, H max refers to the maximum value among the heights corresponding to the (i - m)-th intersecting pixel, …, the height corresponding to the i-th intersecting pixel, …, the heights corresponding to the (i + m)-th intersecting pixel; H min refers to the minimum value among the heights corresponding to the (i - m)-th intersecting pixel, …, the height corresponding to the i-th intersecting pixel, …, the heights corresponding to the (i + m)-th intersecting pixel.

[0124] Among them, 2m + 1 can also be understood as the width of the above-mentioned sliding window.

[0125] In some embodiments, during the process of river network reconstruction, the algorithm running process will generate a corresponding log file, and relevant running information such as the elevation change curvature corresponding to the calculated pixel and the determination of the segmentation point based on the elevation change curvature corresponding to the pixel can be recorded in this log file.

[0126] S306: Determine the position where the i-th intersecting pixel is located as the segmentation point of the first river section, and further execute S307.

[0127] Among them, the method for determining the river section segmentation point described in S304 to S306 can be understood as: automatically extracting the segmentation point of the first river section through numerical second-order differentiation.

[0128] This process uses a sliding window calculation to obtain the second derivative of the elevation change at consecutive intersecting pixel positions from upstream to downstream. By calculating through the sliding window from upstream to downstream, the second differential of each intersecting pixel position can be obtained, and further, based on the obtained second differential, it can be determined whether the intersecting pixel position is a river segment segmentation point, which can make the granularity of the river segment segmentation point finer and the hydraulic properties of the segmented river segments more consistent. Moreover, by sequentially performing numerical second differential calculations on the intersecting pixels, an objective basis for the automatic segmentation of river segments is also provided, and the automatic reconstruction of large-scale river networks can be realized.

[0129] S307: Determine whether i + m is less than N. If so, assign i = i + 1 and return to step S303; if not, execute S308.

[0130] It can be understood that if i + m is less than N, it means that there are still intersecting pixels that can be used as the center of the sliding window downstream of the current intersecting pixel used as the center of the sliding window. Then, the curvature of the elevation change corresponding to the next intersecting pixel that can be used as the center of the sliding window will be determined, and based on this, it will be judged whether it can be used as a river segment segmentation point. If i + m is not less than N, it means that there are no intersecting pixels that can be used as the center of the sliding window downstream of the current intersecting pixel used as the center of the sliding window. At this time, all the segmentation points of the first river segment have been determined, and next, the spatial attribute reconstruction of the first river segment is carried out.

[0131] S308: Reconstruct the spatial attributes of the first river segment based on the segmentation points of the first river segment.

[0132] In some embodiments, reconstructing the spatial attributes of the first river segment is essentially numbering the multiple sub-river segments obtained after segmenting the first river segment. Each of the multiple sub-river segments that make up the first river segment is respectively associated with a first sub-attribute (for example: id attribute) and a second sub-attribute (for example: next attribute). Among them, the first sub-attribute is used to represent the number of the sub-river segment, and the second sub-attribute is used to represent the number of the downstream sub-river segment adjacent to the sub-river segment.

[0133] In one implementation, for the first sub-river segment segmented from the first river segment, the id attribute of the first sub-river segment is set to the number of the first river segment + the sequence number of the first sub-river segment among all the sub-river segments that make up the first river segment. Similarly, the next attribute of the first sub-river segment is set to the number of the downstream sub-river segment adjacent to the first sub-river segment. It can also be understood that the next attribute of the first sub-river segment is set to the id attribute of the downstream sub-river segment adjacent to the first sub-river segment. Among them, for the sub-river segment located at the most downstream among all the sub-river segments that make up the first river segment, its next attribute can not set the sequence number of the sub-river segment, and its next attribute directly continues to use the next attribute corresponding to the first river segment.

[0134] In one example, the serial number of the uppermost sub-river section separated from the first river section is set to 0, the serial number of the downstream sub-river section adjacent to the sub-river section with the serial number 0 is set to 1, and so on, and the serial numbers of all sub-river sections constituting the first river section are set in sequence.

[0135] For example:

[0136] If the id attribute of the first river section is "12301" and the next attribute of the first river section is "12456", it means that the number of the first river section is 12301 and the number of the downstream river section adjacent to the first river section is 12456; when the first river section is divided into 3 sub-river sections by the method provided in the embodiments of the present application, the id attributes (which are also the numbers of the 3 sub-river sections) of the 3 sub-river sections are respectively set to "12301-000", "12301-001", and "12301-002", where "12301-001" represents the sub-river section with the serial number 001 among the 3 sub-river sections constituting the river section with the number 12301 (i.e., the first river section), "12301-002" represents the sub-river section with the serial number 002 among the 3 sub-river sections constituting the river section with the number 12301, and "12301-003" represents the sub-river section with the serial number 003 among the 3 sub-river sections constituting the river section with the number 12301; among them, the next attribute of the sub-river section numbered "12301-000" is set to "12301-001", the next attribute of the sub-river section numbered "12301-001" is set to "12301-002", and the next attribute of the sub-river section numbered "12301-002" continues to use the next attribute of the first river section, that is, it is set to "12456"

[0137] It should be understood that: since when creating a new river section, the upstream new river section needs to be processed first and then the downstream new river section, when processing the upstream new river section (such as the sub-river section numbered 12301-000), its downstream new river section (such as the sub-river section numbered 12301-001) actually does not exist yet. Then, setting the next attribute of the upstream new river section to 12301-001 is a predictive setting.

[0138] In some embodiments, when searching for the downstream adjacent river section through a new river section, sometimes such special situations may be encountered. Some new river sections are the last sections split from the original river section. For example, when searching for the downstream adjacent river section through the next attribute of the sub-river section numbered 12301-002 above, the next attribute of the sub-river section numbered 12301-002 is 12456. However, the river section numbered 12456 has actually been split, and only new river sections numbered 12456-000, 12456-001, etc. exist in the river network. Then, the retrieval process for the downstream adjacent river channel can be specified as follows: First, search for the river section with the number (i.e., id attribute) of 12456. If the search is not successful, then search for the river section numbered 12456-000.

[0139] S309: Output the reconstructed river network of the first river section.

[0140] In some embodiments, the new river sections after splitting are stored in a river network file to achieve the reconstruction of the river network.

[0141] Among them, since the river sections after splitting are all set with id attributes and next attributes, when storing these river sections in the river network file, the storage order of the river sections does not need to be considered.

[0142] To more clearly understand the process of determining one or more intersecting pixels described in S201 and S302 above, hereinafter, by way of example, the method of determining one or more intersecting pixels by numerical differentiation is introduced in detail.

[0143] Assume that the first river section is presented as a broken line formed by connecting three line segments end to end. The process of determining one or more pixels in the first digital elevation model that intersect the first river section can be decomposed into sequentially determining: one or more pixels in the first digital elevation model that intersect the first line segment, one or more pixels in the first digital elevation model that intersect the second line segment, and one or more pixels in the first digital elevation model that intersect the third line segment; then arrange all the obtained intersecting pixels in the order from upstream to downstream to obtain one or more pixels in the first digital elevation model that intersect the first river section.

[0144] The following details the process of determining one or more pixels in the first digital elevation model that intersect the first line segment. Among them, this process is essentially the process of determining the row numbers and column numbers of one or more pixels in the first digital elevation model that intersect the first line segment:

[0145] (1) Assume that the starting point of the first line segment is P1(x1, y1) and the end point is P2(x2, y2), and calculate the slope k of the straight line where the first line segment is located. Among them, the calculation formula for the slope k is k = (y2 - y1) / (x2 - x1).

[0146] Among them, P1 and P2 can be longitude and latitude coordinates.

[0147] It should be noted that: when x2 = x1, if y2 > y1, then k is positive infinity; if y2 < y1, then k is negative infinity.

[0148] (2) Calculate the row number and column number of the starting point P1 and the ending point P2 of the first line segment in the first digital elevation model respectively.

[0149] Among them, the row number and column number of the starting point P1 in the first digital elevation model can be used to represent the pixel where the starting point P1 is located, and this pixel can be represented as (A1, B1), where A represents the row number and B represents the column number; the row number and column number of the ending point P2 in the first digital elevation model can be used to represent the pixel where the ending point P2 is located, and this pixel can be represented as (A2, B2). The width and length of each pixel (which is also a grid) are both d.

[0150] (3) Take the pixel where the starting point P1 is located as the first pixel in the intersecting pixel sequence, and let x = x1, y = y2. Then, starting from the starting point P1, determine the row number and column number of one or more pixels intersecting the first line segment in the first digital elevation model in sequence. Specifically, the determination method can be:

[0151] 1) When |k| < 1, let x = x + d, y = y + kd, and the row number and column number of the intersecting pixel after the pixel (A1, B1) are (A1 + k, B1 + 1); when |k| > 1 and |k| < MAX (MAX can be a relatively large number, such as 100), let x = x + d / k, y = y + d, and the row number and column number of the intersecting pixel after the pixel (A1, B1) are (A1 + 1, B1 + 1 / k); when |k| > 1, k > 0, and |k| > MAX, let x = x, y = y + d, and the row number and column number of the intersecting pixel after the pixel (A1, B1) are (A1 + 1, B1); when |k| > 1, k < 0, and |k| > MAX, let x = x, y = y - d, and the row number and column number of the intersecting pixel after the pixel (A1, B1) are (A1 - 1, B1).

[0152] 2) Output the row number and column number of the intersecting pixel after the pixel (A1, B1), and at the same time output the values of x and y.

[0153] 3) Judge whether the distance between the coordinate point (x, y) and P2(x2, y2) is less than d. If so, end the collection of intersecting pixels; if not, return to step 1) and continue to collect the intersecting pixels after the currently output pixel.

[0154] It should be understood that the embodiments of the present application are merely schematic illustrations of the method for determining intersecting pixels. In addition to using numerical differentiation to determine one or more intersecting pixels, other methods may also be used to determine the one or more intersecting pixels, and the present application does not limit this.

[0155] Below, exemplarily, in combination Figure 4 , the first digital elevation model, the first river section and the intersecting pixels described in the embodiment of the present application are introduced in detail.

[0156] like Figure 4 As shown in (a) in FIG. 1 , the first river section is a vector river section. For example, the first river section can be presented as a broken line composed of three line segments connected end to end (in Figure 4 In (a), it is represented by a black bold line), where Figure 4 The arrow in (a) indicates the flow direction of the first river section; the first digital elevation model covers the first river section, and the first digital elevation model is composed of a plurality of regularly arranged pixels, Figure 4 Each grid in (a) represents a pixel, where Figure 4 The pixels filled with shades in (a) are multiple intersecting pixels determined by the method of the embodiment of the present application.

[0157] Among them, each of the multiple pixels included in the first digital elevation model corresponds to a set of position information (longitude, latitude, altitude), for example, it can be represented by (x, y, z), wherein the first river section and the first digital elevation model can be accurately overlapped through the longitude and latitude information of the pixel and the position information (longitude and latitude information) of the first river section, so that the intersecting pixels can be determined, and then based on the altitude information of the intersecting pixels, the elevation change curvature of the location where the intersecting pixels are located can be calculated, thereby determining the segmentation of the river section.

[0158] On this basis, when the first river section is segmented by the method provided in the embodiment of the present application, Figure 4 The elevation change curvature corresponding to the intersecting pixel marked as 1 in (b) is greater than the first threshold value. Therefore, the position of the intersecting pixel marked as 1 is determined as the segmentation point of the first river section, and the first river section is divided into two sub-river sections, wherein the sub-river section is relative to the first river section, and the sub-river section is a plurality of river sections obtained by segmenting the first river section. It can also be understood that the plurality of sub-river sections are connected end to end according to the upstream and downstream order to form the first river section.

[0159] in, Figure 4 Marker 4 shown in (b) in the figure points to all unfilled pixels, which are used to represent pixels in the first digital elevation model that do not intersect the first river section; Marker 3 points to all pixels with shaded fills, which are used to represent pixels in the first digital elevation model that intersect the first river section.

[0160] Among them, the method of the embodiment of the present application can also filter out some pixels in the first digital elevation model that slightly intersect the first river section but do not play a substantial role in determining the segmentation point of the river section (for example Figure 4 The pixel pointed to by mark 2 in (b) in FIG. 1 ), that is, the intersecting pixels determined by the river section segmentation method provided in the embodiment of the present application are all valid intersecting pixels.

[0161] Below, illustratively, Figure 5 A schematic diagram showing the effect of the river network reconstruction method provided in an embodiment of the present application is shown.

[0162] like Figure 5 As shown in Figure 2, taking the vector river network of the upper Ganjiang River basin of about 40,000 square kilometers as an example, before the reconstruction of the vector river network, the vector river network consists of 2332 river sections (such as Figure 5 As shown in the left figure in FIG, the 2332 river sections can be further divided into 14796 river sections (as shown in FIG. Figure 5 As shown in the right figure in ), it can improve the spatial refinement of the vector river network and realize the refined display of the vector river network.

[0163] and, Figure 5 The first area ( Figure 5 The enlarged view of the river section corresponding to the area circled in the rectangle Figure 5 In the enlarged view of the first region corresponding to the left image in FIG. 1 , the broken lines represent multiple river sections in the first region, and the blank filled circles represent the segmentation points on the multiple river sections. Figure 5 In the enlarged view of the first area corresponding to the right figure in FIG. , the broken lines represent multiple river sections in the first area, and the black filled circles represent the segmentation points on the multiple river sections. Figure 5 It can be seen that through the river network map finally presented to the user, the segmentation points on the river section can be seen. By comparing the river network map before and after the river network reconstruction, the segmentation points newly added on the basis of the original river network map can be found, that is, the segmentation points determined by the river section segmentation method provided in the embodiment of the present application.

[0164] Optionally, the division point can also be expressed by using different colors to represent different river sections, and the connecting point of different river sections is the division point; the division point can also be represented by a number; or it can be other representation methods that can serve as an identification, which is not limited in this application.

[0165] For example, Figure 6 FIG. 6 is a schematic diagram showing the functional modules of a river network reconstruction device 600 provided in an embodiment of the present application. Figure 6 As shown, the device 600 includes:

[0166] A determination module 610 is configured to determine one or more intersecting pixels according to the first information.

[0167] Wherein, the first information includes information of a first river section and a first digital elevation model, the first digital elevation model covers the first river section, and the intersecting pixels are the pixels in the first digital elevation model that intersect the first river section.

[0168] Wherein, the information of the first river section may be the location information of the first river section, for example, it may be the longitude information and latitude information of the first river section.

[0169] In some embodiments, the first information may be the input information of the user.

[0170] In one example, when the method 200 is applied to a cloud platform, the user can input the first information through the platform interface, and the output finally presented by the cloud platform may be a river network map, which includes multiple visible river sections and river section segmentation points.

[0171] In a specific example, the user inputs a first river section and a first digital elevation model through the platform interface, and the output finally presented by the cloud platform may be the segmentation form of the first river section, and the first river section is segmented into multiple sub-river sections.

[0172] In some embodiments, the first digital elevation model includes multiple pixels, and the multiple pixels are in one-to-one correspondence with multiple sets of (longitude, latitude, altitude) information.

[0173] In some embodiments, the first river section is associated with a first attribute and a second attribute. Wherein, the first attribute is used to represent the number of the first river section, and the second attribute is used to represent the number of the downstream river section adjacent to the first river section. In one example, the first attribute may be represented by an id string, and the second attribute may be represented by a next string.

[0174] Wherein, the first river section is presented as a broken line composed of one or more line segments connected end to end, and the first digital elevation model is presented as one or more pixels. The specific explanations of the first river section and the first digital elevation model will be described in combination with the accompanying drawings in the subsequent embodiments, and will not be described in detail here.

[0175] This step can also be understood as the determination module 610 establishing a mapping relationship between the first river section and the first digital elevation model.

[0176] In some embodiments, the one or more intersecting pixels determined by the determination module 610 form a pixel sequence in the order from upstream to downstream. Since the first river section generally presents as a broken line composed of line segments connected end to end, the one or more pixels intersecting the first river section in the first digital elevation model determined by the determination module 610 can be decomposed as follows: determining the pixels intersecting each line segment constituting the first river section in the first digital elevation model respectively, and then forming a pixel sequence with the determined all pixels in the order from upstream to downstream.

[0177] In some embodiments, each of the one or more intersecting pixels determined by the determination module 610 is associated with its own row number and column number in the first digital elevation model. It can also be understood that: the process of the determination module 610 determining one or more intersecting pixels is essentially the process of determining the row numbers and column numbers of one or more intersecting pixels in the first digital elevation model. That is to say, the identification method of the intersecting pixels can be (row number, column number).

[0178] In one implementation manner, the pixel sequence formed by one or more intersecting pixels in the order from upstream to downstream is essentially a sequence composed of multiple (row number, column number) identifications, where each (row number, column number) identification represents an intersecting pixel.

[0179] The determination module 610 is further configured to determine the segmentation points of the first river section according to one or more intersecting pixels.

[0180] In some embodiments, the determination module 610 determines the elevation change curvature corresponding to the i-th intersecting pixel among one or more intersecting pixels, where i = 1, 2, 3,..., and i is a positive integer greater than or equal to 1; when the elevation change curvature corresponding to the i-th intersecting pixel is greater than the first threshold, the determination module 610 determines the position where the i-th intersecting pixel is located as the segmentation point of the first river section. And so on, the determination module 610 can sequentially determine all the segmentation points in the first river section.

[0181] In some embodiments, the value of the first threshold depends on the steepness of the terrain, and its value can be, for example, the standard deviation of the elevation of the basin where the first river section is located multiplied by the first coefficient.

[0182] The reconstruction module 620 is configured to segment the first river section into one or more sub-river sections according to the segmentation points of the first river section.

[0183] Wherein, the elevation change curvature corresponding to any one of the one or more sub-river sections obtained by segmentation is less than or equal to the first threshold, which can be specifically understood as: the elevation change curvature corresponding to each of the one or more intersecting pixels on the any one of the sub-river sections is less than or equal to the first threshold.

[0184] It should be understood that the elevation change curvature corresponding to any one of the one or more sub-river segments obtained by segmentation is less than or equal to the first threshold, which means that the hydraulic properties of the sub-river segments obtained after segmentation are more consistent in the longitudinal profile.

[0185] It should be understood that a river network may include multiple river basins, and a river basin may include multiple river segments. In the embodiments of the present application, a certain river segment (i.e., the first river segment) in a river basin is taken as an example to illustrate the river segment segmentation method, but this does not impose any limitation on the applicable scenarios of the solution of the present application. Through the method provided by the embodiments of the present application, multiple river segments in a river basin can be segmented.

[0186] In the embodiments of the present application, a parameter (elevation change curvature) describing the hydraulic properties of the river longitudinal profile is introduced as the basis for river network segmentation, so that the river network segmentation has a physical mechanism basis, can improve the consistency of the hydraulic properties of the river segments, and further improve the display accuracy of the river network; moreover, the elevation change curvature is determined by the way of superposition analysis of the digital elevation model and the current river segment, and the digital elevation model is relatively easy to obtain, and this calculation method is simple and feasible.

[0187] In some embodiments, the embodiments of the present application may further provide an application programming interface (API) that takes the information of the first river segment, the first digital elevation model, or the first threshold as input and outputs the reconstructed river network.

[0188] One or more of the modules or units described in this article can be implemented in software, hardware, or a combination of both. When any of the above modules or units is implemented in software, the software exists in the form of computer program instructions and is stored in the memory. The processor can be used to execute the program instructions and implement the above method flow. The processor can include, but is not limited to, at least one of the following: central processing unit (CPU), microprocessor, digital signal processor (DSP), microcontroller unit (MCU), or various computing devices that run software such as artificial intelligence processors. Each computing device can include one or more cores for executing software instructions to perform operations or processing. The processor can be built into a system-on-chip (SoC) or an application-specific integrated circuit (ASIC), or it can be an independent semiconductor chip. In addition to the cores in the processor for executing software instructions to perform operations or processing, it can further include necessary hardware accelerators, such as field programmable gate array (FPGA), programmable logic device (PLD), or logic circuits for implementing dedicated logical operations.

[0189] When the modules or units described in this article are implemented in hardware, the hardware can be any one or any combination of CPU, microprocessor, DSP, MCU, artificial intelligence processor, ASIC, SoC, FPGA, PLD, dedicated digital circuit, hardware accelerator, or non-integrated discrete devices, which can run the necessary software or execute the above method flow without relying on software.

[0190] When the modules or units described in this article are implemented using software, they can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the processes or functions described in the embodiments of this application are generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from a website, computer, server, or data center to another website, computer, server, or data center by wire (such as coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (such as infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that the computer can access or a data storage device such as a server or data center that includes one or more integrated available media. The available medium can be a magnetic medium (such as a floppy disk, hard disk, magnetic tape), an optical medium (such as a DVD), or a semiconductor medium (such as a solid state disk (SSD)), etc.

[0191] Those of ordinary skill in the art can realize that the units and algorithm steps of each example described in combination with the embodiments disclosed in this article can be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are executed in hardware or software depends on the specific application and design constraints of the technical solution. Professional technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of this application.

[0192] Those skilled in the art can clearly understand that for the convenience and conciseness of description, the specific working processes of the systems, devices, and units described above can refer to the corresponding processes in the foregoing method embodiments and will not be repeated here.

[0193] In several embodiments provided in this application, it should be understood that the disclosed systems, devices, and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of the units is only a logical function division, and there can be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed couplings or direct couplings or communication connections to each other can be through some interfaces. The indirect couplings or communication connections of devices or units can be in electrical, mechanical, or other forms.

[0194] The unit described as a separation component may or may not be physically separated. The component shown as a unit may or may not be a physical unit, that is, it may be located in one place or distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0195] In addition, each functional unit in various embodiments of the present application may be integrated in a processing unit, may exist physically alone for each unit, or two or more units may be integrated in one unit.

[0196] If the above function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of the present application, in essence, or the part that contributes to the prior art, or a part 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 enable a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of the present application. The aforementioned storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical discs that can store program codes.

[0197] As described above, the above are only the specific implementation manners of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art within the technical scope disclosed in the present application can easily think of changes or substitutions, which should all be covered by the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. A method for river network reconstruction, characterized in that, The method includes: Determining a segmentation point of a first river section according to first information, where the first information includes information of the first river section and first elevation information, the first elevation information includes a plurality of height information corresponding one by one to a plurality of pixels constituting a first area, and the first river section is located in the first area; Based on the segmentation point of the first river section, dividing the first river section into a plurality of sub-river sections, and the elevation change curvature corresponding to any one of the plurality of sub-river sections is less than or equal to a first threshold.

2. The method according to claim 1, characterized in that, The determining a segmentation point of a first river section according to first information includes: Determining N intersecting pixels according to the first information, where the intersecting pixels are the pixels among the plurality of pixels constituting the first area that intersect the first river section, and N is a positive integer greater than or equal to 1; Determining the segmentation point of the first river section according to the N intersecting pixels.

3. The method according to claim 2, characterized in that, The determining the segmentation point of the first river section according to the N intersecting pixels includes: Determining the elevation change curvature corresponding to the i-th intersecting pixel, where the i-th intersecting pixel belongs to the N intersecting pixels, and i = m + 1, m + 2, m + 3,..., N - m, and both i and m are positive integers greater than or equal to 1; When the elevation change curvature corresponding to the i-th intersecting pixel is greater than the first threshold, determining the position where the i-th intersecting pixel is located as the segmentation point of the first river section.

4. The method according to claim 3, characterized in that, The determining the elevation change curvature corresponding to the i-th intersecting pixel includes: Determining the elevation change curvature corresponding to the i-th intersecting pixel according to the height corresponding to the (i - m)-th intersecting pixel, the height corresponding to the i-th intersecting pixel, and the height corresponding to the (i + m)-th intersecting pixel.

5. The method according to claim 4, characterized in that, The first threshold is greater than or equal to 0 and less than or equal to where H max is the maximum value among 2m + 1 heights corresponding one-to-one to the (i - m)-th to (i + m)-th intersecting pixels, and H min is the minimum value among 2m + 1 heights corresponding one-to-one to the (i - m)-th to (i + m)-th intersecting pixels.

6. The method according to any one of claims 1 to 5, characterized in that, The method further includes: Reconstructing the spatial attribute of the first river section based on the one or more sub-river sections.

7. The method according to any one of claims 1 to 6, characterized in that, The method further includes: Outputting a reconstructed river network map, where the plurality of sub-river sections are marked on the reconstructed river network map.

8. An apparatus for river network reconstruction, characterized in that, The apparatus includes: A determining module, configured to determine a segmentation point of a first river section according to first information, where the first information includes information of the first river section and first elevation information, the first elevation information includes a plurality of height information corresponding one by one to a plurality of pixels constituting a first area, and the first river section is located in the first area; A reconstructing module, configured to divide the first river section into a plurality of sub-river sections based on the segmentation point of the first river section, and the elevation change curvature corresponding to any one of the plurality of sub-river sections is less than or equal to a first threshold.

9. The apparatus according to claim 8, characterized in that, The determining module is specifically configured to: Determine N intersecting pixels according to the first information, where the intersecting pixels are the pixels among the plurality of pixels constituting the first area that intersect the first river section, and N is a positive integer greater than or equal to 1; Determine the segmentation point of the first river section according to the N intersecting pixels.

10. The apparatus according to claim 9, characterized in that, The determining module is specifically configured to: Determine the elevation change curvature corresponding to the i-th intersecting pixel, where the i-th intersecting pixel belongs to the N intersecting pixels, and i = m + 1, m + 2, m + 3,..., N - m, and both i and m are positive integers greater than or equal to 1; When the elevation change curvature corresponding to the i-th intersecting pixel is greater than the first threshold, determine the position where the i-th intersecting pixel is located as the segmentation point of the first river section.

11. The apparatus according to claim 10, characterized in that, The determining module is further specifically configured to: Determine the elevation change curvature corresponding to the i-th intersecting pixel according to the height corresponding to the (i - m)-th intersecting pixel, the height corresponding to the i-th intersecting pixel, and the height corresponding to the (i + m)-th intersecting pixel.

12. The apparatus according to claim 11, characterized in that, The first threshold is greater than or equal to 0 and less than or equal to where H max is the maximum value among 2m + 1 heights corresponding one-to-one to the (i - m)-th to (i + m)-th intersecting pixels, and H min is the minimum value among 2m + 1 heights corresponding one-to-one to the (i - m)-th to (i + m)-th intersecting pixels.

13. The device according to any one of claims 8 to 12, characterized in that, The reconstructing module is further configured to: Reconstruct the spatial attributes of the first river section based on the one or more sub-river sections.

14. The device according to any one of claims 8 to 13, characterized in that, The device further includes: An output module, configured to output a reconstructed river network map, on which the multiple sub-river sections are marked.

15. An electronic device, characterized in that, Comprising: One or more processors; One or more memories; And one or more computer programs, wherein the one or more computer programs are stored in the one or more memories, and the one or more computer programs include instructions that, when executed by the one or more processors, cause the electronic device to execute the method according to any one of claims 1 to 7.

16. A computer-readable storage medium, characterized in that, A program or instruction is stored in the storage medium, and when the program or instruction is run, the method according to any one of claims 1 to 7 is implemented.

17. A chip, characterized in that, Instructions are stored in the chip, and when the instructions are run, the method according to any one of claims 1 to 7 is implemented.

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