Deep pool and shoal identification method based on slope ratio and curvature analysis

Abstract

The invention discloses a deep pool and shoal identification method based on slope ratio and curvature analysis. The method comprises the following steps: acquiring elevation data of equal division points on a riverbed thalweg line; calculating the slope ratio of each point on the riverbed thalweg by utilizing the elevation data of the equal division points on the riverbed thalweg; calculating the local curvature of each point on the riverbed thalweg by using the elevation data of the equal division points on the riverbed thalweg; and based on the slope ratio and the local curvature of each point on the riverbed thalweg line, deep pool and shoal identification is carried out. According to the method, the depth and the shoal can be objectively and efficiently identified by calculating the elevation change rate (landmark characteristics of the depth and the shoal) and the curvature (reflecting the concavity and convexity of the terrain) of the adjacent points, the concavity and convexity of the terrain are further distinguished, the defects that a traditional method depends on subjective judgment limit values and has high requirements on data quality are overcome, and the method is suitable for popularization and application. And the identification precision and the calculation efficiency are obviously improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of river geomorphology analysis, and particularly relates to a method for identifying deep pools and shoals based on slope ratio and curvature analysis. Background Art

[0002] Deep pools and shoals are important features in river geomorphology and have important impacts on river ecosystems, hydrological processes, and water conservancy projects. Among the existing methods for identifying deep pools and shoals, the local elevation difference method (O’Neil, 1984) is a classic discrimination method widely used in river geomorphology analysis. This method is based on the elevation data of the thalweg of the riverbed. By calculating the elevation differences and their standard deviations between adjacent points and combining the determination limit value (T), deep pools and shoals are identified. Although this method can provide relatively accurate results in most cases, there are still the following deficiencies: 1. Subjectivity of the determination limit value (T): The core of the local elevation difference method lies in the selection of the determination limit value (T), which is usually determined by a trial calculation method, that is, T = K * SD (SD is the standard deviation of the elevation differences between adjacent points, and K is an empirical coefficient, usually taking 0.5 - 2.2). However, the selection of the K value depends on artificial experience and lacks an objective mathematical basis, resulting in subjectivity and uncertainty in the identification results. The topographic features of different research areas vary greatly, and a fixed K value may not be applicable to all situations, leading to a decrease in identification accuracy; 2. Inability to reflect local features of the terrain: The local elevation difference method is mainly based on the elevation differences between adjacent points and lacks comprehensive consideration of terrain curvature and slope changes. This may lead to insufficient identification ability for complex terrains (such as areas with obvious convex and concave changes). This method cannot effectively distinguish the convexity and concavity (protrusion or depression) of the terrain, while convexity and concavity are important features of deep pools and shoals. Summary of the Invention

[0003] The purpose of the present invention is to provide a method for identifying deep pools and shoals based on slope ratio and curvature analysis, which is used to efficiently and accurately identify deep pools and shoals in river geomorphology, distinguish the convexity and concavity of the terrain, and overcome the deficiencies of relying on subjective determination limit values and low identification accuracy in traditional methods.

[0004] According to the first aspect of the embodiments of the present application, a method for identifying deep pools and shoals based on slope ratio and curvature analysis is provided, including:

[0005] Obtaining elevation data of equally spaced points on the thalweg of the riverbed;

[0006] Using the elevation data of the equally spaced points on the thalweg of the riverbed to calculate the slope ratio of each point on the thalweg of the riverbed;

[0007] Using the elevation data of the equally spaced points on the thalweg of the riverbed to calculate the local curvature of each point on the thalweg of the riverbed;

[0008] Identify deep pools and shoals based on the slope ratios and local curvatures of points on the thalweg of the riverbed.

[0009] Furthermore, obtain the elevation data of equally-spaced points on the thalweg of the riverbed, including:

[0010] Obtain the thalweg of the riverbed, equally divide the thalweg at a predetermined interval to obtain the number of equally-spaced points n on the thalweg;

[0011] Extract the elevation data of the thalweg at the positions of the equally-spaced points from upstream to downstream, denoted as h(i), where i represents the i-th point, i = 1, 2, ..., n, and n is the total number of points.

[0012] Furthermore, the calculation formula for the slope ratio of the i-th point is:

[0013]

[0014] In the formula: is the elevation of the (i + 1)-th point; is the elevation of the i-th point; is the elevation of the (i - 1)-th point.

[0015] Furthermore, the calculation formula for the curvature of the i-th point is:

[0016]

[0017] In the formula: is the elevation of the (i + 1)-th point; is the elevation of the i-th point; is the elevation of the (i - 1)-th point.

[0018] Furthermore, identify deep pools and shoals based on the slope ratios and local curvatures of points on the thalweg of the riverbed, specifically:

[0019] If the slope ratio of the i-th point and the curvature , then determine that the terrain of the i-th point is a deep pool;

[0020] If the slope ratio of the i-th point and the curvature , then determine that the terrain of the i-th point is a shoal;

[0021] If the slope ratio of the i-th point or the curvature , then determine that the terrain of the i-th point is neither a deep pool nor a shoal.

[0022] According to the second aspect of the embodiments of the present application, there is provided a deep pool and shoal identification device based on slope ratio and curvature analysis, including:

[0023] The elevation acquisition module is used to obtain the elevation data of the equally divided points on the riverbed deep line;

[0024] A slope ratio calculation module, used to calculate the slope ratio of each point on the riverbed deep channel line by using the elevation data of the equally divided points on the riverbed deep channel line;

[0025] A curvature calculation module, used to calculate the local curvature of each point on the riverbed deep channel line by using the elevation data of equally divided points on the riverbed deep channel line;

[0026] The terrain recognition module is used to identify deep pools and shallows based on the slope ratio and local curvature of each point on the riverbed deep channel line.

[0027] According to a third aspect of an embodiment of the present application, a computer program product is provided, comprising a computer program / instruction, which implements the method described in the first aspect when executed by a processor.

[0028] According to a fourth aspect of an embodiment of the present application, there is provided an electronic device, including:

[0029] one or more processors;

[0030] A memory for storing one or more programs;

[0031] When the one or more programs are executed by the one or more processors, the one or more processors implement the method as described in the first aspect.

[0032] According to a fifth aspect of an embodiment of the present application, a computer-readable storage medium is provided, on which computer instructions are stored, and when the instructions are executed by a processor, the steps of the method described in the first aspect are implemented.

[0033] The principle of the present invention is based on a comprehensive analysis of the slope ratio and curvature of the riverbed deep-water line elevation data, and automatically identifies deep pools and shallows by calculating the elevation change rate (the hallmark feature of deep pools and shallows) and curvature (reflecting the concavity and convexity of the terrain) of adjacent points. The slope ratio is used to capture the local change trend of the terrain. If the slope ratio is negative, it indicates that the local terrain has changed from rising to falling, or from falling to rising, while the curvature is used to judge the concavity and convexity of the terrain, and further determine whether it is a deep pool or a shallow. Through the calculation of the comprehensive index S(i), the present invention can objectively and efficiently identify deep pools and shallows, and further distinguish the concavity and convexity of the terrain, overcoming the shortcomings of traditional methods that rely on subjective judgment limits and have high requirements for data quality, and significantly improving recognition accuracy and calculation efficiency.

[0034] The technical solution provided by the embodiments of the present application may have the following beneficial effects:

[0035] As can be seen from the above embodiments, the present application introduces the slope ratio and curvature as comprehensive indicators: 1. Improve recognition accuracy: By calculating the slope ratio and curvature of adjacent points, the present invention comprehensively considers the local change characteristics of the terrain, avoiding the limitation of relying solely on elevation differences. The combination of the slope ratio and curvature can more accurately reflect the concavity and convexity of the terrain and the change trend, thereby improving the recognition accuracy; 2. Reduce subjectivity: There is no need to set slope ratio thresholds and curvature thresholds, avoiding the subjectivity of manually calculating and determining limit values. The calculation of the slope ratio and curvature is based on mathematical formulas, with objectivity and repeatability. Through the judgment of comprehensive indicators (combining the slope ratio and curvature), deep pools and shoals can be automatically recognized, reducing manual intervention; 3. Adapt to complex terrain: The present invention can not only recognize deep pools and shoals, but also further distinguish the concavity and convexity (protrusion or depression) of the terrain, thus more comprehensively describing the river geomorphic characteristics. Through the comprehensive analysis of the slope ratio and curvature, the present invention can adapt to complex terrain, especially in areas with obvious concave and convex changes, and the recognition effect is better than the local elevation difference method. The recognition results can be directly used for the planning and design of river ecological restoration projects, providing data support for the protection and restoration of deep pools and shoals, and having broad application prospects.

[0036] It should be understood that the above general description and the following detailed description are only exemplary and explanatory, and cannot limit the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] The accompanying drawings herein are incorporated into the specification and constitute a part of the specification, showing embodiments consistent with the present application, and are used together with the specification to explain the principles of the present application.

[0038] Figure 1 is a flowchart of a deep pool and shoal recognition method based on slope ratio and curvature analysis according to an exemplary embodiment.

[0039] Figure 2 is a result diagram of deep pool and shoal recognition in Embodiment 1.

[0040] Figure 3 is a result diagram of deep pool and shoal recognition in Embodiment 2.

[0041] Figure 4 is a block diagram of a deep pool and shoal recognition device based on slope ratio and curvature analysis according to an exemplary embodiment.

[0042] Figure 5 is a schematic diagram of an electronic device according to an exemplary embodiment. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0043] Exemplary embodiments will be described in detail herein, and examples thereof are shown in the accompanying drawings. When the following description refers to the accompanying drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present application.

[0044] The terms used in this application are for the purpose of describing specific embodiments only and are not intended to limit this application. The singular forms "a", "the", and "said" used in this application and the appended claims are also intended to include the plural forms unless the context clearly indicates otherwise. It should also be understood that the term "and / or" as used herein refers to and encompasses any and all possible combinations of one or more of the associated listed items.

[0045] It should be understood that although the terms first, second, third, etc. may be used in this application to describe various information, such information should not be limited to these terms. These terms are only used to distinguish the same type of information from each other. For example, without departing from the scope of this application, the first information may also be referred to as the second information, and similarly, the second information may also be referred to as the first information. Depending on the context, the word "if" as used herein may be interpreted as "when" or "while" or "in response to a determination".

[0046] As Figure 1 shown, this application provides a deep pool and shallow shoal identification method based on slope ratio and curvature analysis, including the following steps:

[0047] (1) Obtain the elevation data of equally divided points on the thalweg of the riverbed;

[0048] Specifically, through methods such as data collection and topographic survey, obtain the topography of the study reach, draw the thalweg of the river channel, equally divide the thalweg at a certain interval (such as 500 m) to obtain the number of equally divided points n of the thalweg, and extract the elevation data of the thalweg at the positions of the equally divided points from upstream to downstream, denoted as h(i), where i represents the i-th point, i = 1, 2,..., n, and n is the total number of points.

[0049] (2) Use the elevation data of the equally divided points on the thalweg of the riverbed to calculate the slope ratio of each point on the thalweg of the riverbed;

[0050] Specifically, in terrain analysis, slope generally represents the elevation change rate between two points, that is, the ratio of elevation to horizontal distance, and cannot reflect the local terrain changes. The slope ratio describes the measure of local terrain changes through the elevation changes of three adjacent points. The slope ratio is used to describe the elevation change trend between adjacent points and reflects the local change characteristics of the terrain. If the slope ratio is negative, it indicates that the local terrain changes from rising to falling or from falling to rising. By calculating the elevation change rate of adjacent points, the rising or falling trend of the terrain can be judged. For each point i (i ≠ 1 and i ≠ n), the calculation formula for the slope ratio is:

[0051] (1)

[0052] In the formula: is the elevation of the (i + 1)-th point; is the elevation of the i-th point; is the elevation of the (i - 1)-th point. If the denominator - has an absolute value less than 1e-6 (close to zero), the slope ratio is set to 0 to avoid division by zero error.

[0053] (3) Use the elevation data of the equally divided points on the thalweg of the riverbed to calculate the local curvature of each point on the thalweg of the riverbed;

[0054] The calculation of local terrain curvature based on the second derivative is used to describe the degree of terrain bending. By calculating the curvature change of adjacent points, it can be judged whether the terrain is convex or concave. For each equally spaced point i (i ≠ 1 and i ≠ n), the calculation formula for the curvature is:

[0055] (2)

[0056] In the formula: is the elevation of the (i + 1)-th point; is the elevation of the i-th point; is the elevation of the (i - 1)-th point.

[0057] (4) Based on the slope ratio and local curvature of each point on the thalweg of the riverbed, identify deep pools and shoals;

[0058] Combining the information of the slope ratio and curvature, deep pools and shoals can be automatically identified. For each point i (i ≠ 1 and i ≠ n):

[0059] If the slope ratio of the i-th point and the curvature , then it is determined that the terrain of the i-th point is a deep pool;

[0060] If the slope ratio of the i-th point and the curvature , then the terrain of the i-th point is judged to be a shoal;

[0061] If the slope of the i-th point is or curvature , then the terrain of the i-th point is judged to be neither a deep pool nor a shallow beach.

[0062] is the slope ratio. The condition of slope_ratio(i) < 0 is to capture the local change characteristics of the terrain, especially the turning point of the terrain (such as from rising to falling, or from falling to rising). If it is a deep pool or shallow beach, then the point must change from rising to falling or from falling to rising, so the slope ratio must be negative. This turning point is usually a signature feature of deep pools and shallow beaches. After determining whether it is a deep pool or shallow beach, further use the curvature To determine the concave and convexity of the point, and then judge whether it is a deep pool or a shallow beach, if the slope ratio is negative and the curvature is >0, the point is judged to be a deep pool; if the slope ratio is negative and the curvature is <0, the point is judged to be a shoal.

[0063] Embodiment 1:

[0064] Embodiment A sin curve is artificially constructed, as shown in Table 1 below, which contains a formula to generate 10 equally spaced x values ​​in the range of 0 to 2π, corresponding to The value is sin(x). Calculate its slope ratio slope_ratio(i) and curvature Kappa(i). When the slope ratio is negative, further judge the concavity of the river channel based on the curvature, and then judge the deep pool and shallow beach of the river channel.

[0065] Table 1

[0066]

[0067] The results after deep pool and shallow beach identification are as follows Figure 2 As shown, the locations of deep pools and shallows are fully identified.

[0068] Embodiment 2:

[0069] This embodiment selects a typical municipal river in the mountainous area of ​​southwestern Zhejiang, as shown in Table 2 below. The length of the river channel deep line is 2 km. Every 100 m, an elevation point h(i) is extracted to calculate its slope ratio slope_ratio(i) and curvature Kappa(i). Under the condition that the slope ratio is negative, the concavity of the river channel is further judged according to the curvature, and then the deep pool and shallow beach of the river channel are judged.

[0070] Table 2

[0071]

[0072] The identified deep pools and shallow shoals are as Figure 3 shown, and the positions of deep pools and shallow shoals can be fully identified.

[0073] Corresponding to the foregoing embodiments of the method for identifying deep pools and shallow shoals based on slope ratio and curvature analysis, the present application also provides embodiments of an apparatus for identifying deep pools and shallow shoals based on slope ratio and curvature analysis.

[0074] Figure 4 is a block diagram of an apparatus for identifying deep pools and shallow shoals based on slope ratio and curvature analysis shown according to an exemplary embodiment. Referring to Figure 4 , the apparatus may include:

[0075] An elevation acquisition module 21 for acquiring elevation data of equally divided points on the thalweg of the riverbed;

[0076] A slope ratio calculation module 22 for calculating the slope ratio of each point on the thalweg of the riverbed by using the elevation data of the equally divided points on the thalweg of the riverbed;

[0077] A curvature calculation module 23 for calculating the local curvature of each point on the thalweg of the riverbed by using the elevation data of the equally divided points on the thalweg of the riverbed;

[0078] A terrain identification module 24 for identifying deep pools and shallow shoals based on the slope ratio and local curvature of each point on the thalweg of the riverbed.

[0079] Regarding the apparatus in the above embodiments, the specific manners in which each module performs operations have been described in detail in the embodiments of the method, and will not be elaborated herein.

[0080] For the apparatus embodiments, since they basically correspond to the method embodiments, the relevant parts can refer to the partial descriptions of the method embodiments. The apparatus embodiments described above are only illustrative. The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place, or may be distributed to multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of the present application. Those of ordinary skill in the art can understand and implement it without creative efforts.

[0081] Correspondingly, the present application also provides a computer program product, including computer programs / instructions, which when executed by a processor implement the method for identifying deep pools and shallow shoals based on slope ratio and curvature analysis as described above.

[0082] Correspondingly, the present application further provides an electronic device, including: one or more processors; a memory for storing one or more programs; when the one or more programs are executed by the one or more processors, the one or more processors implement the deep pool and shallow shoal identification method based on slope ratio and curvature analysis as described above. As Figure 5 shown, it is a hardware structure diagram of a device with any data processing capability where the deep pool and shallow shoal identification device provided by an embodiment of the present invention is located. In addition to Figure 5 the processors, memory, and network interface shown, any device with data processing capability where the device in the embodiment is located usually further includes other hardware according to the actual functions of the device with any data processing capability, which will not be elaborated here.

[0083] Correspondingly, the present application further provides a computer-readable storage medium, on which computer instructions are stored, and when the instructions are executed by a processor, the deep pool and shallow shoal identification method based on slope ratio and curvature analysis as described above is implemented. The computer-readable storage medium may be an internal storage unit of any device with data processing capability described in any of the foregoing embodiments, such as a hard disk or a memory. The computer-readable storage medium may also be an external storage device, such as a plug-in hard disk, a smart media card (SMC), an SD card, a flash card, etc. equipped on the device. Further, the computer-readable storage medium may also include both an internal storage unit of any device with data processing capability and an external storage device. The computer-readable storage medium is used to store the computer program and other programs and data required by any device with data processing capability, and may also be used to temporarily store data that has been output or will be output.

[0084] Those skilled in the art will readily conceive of other embodiments of the present application after considering the specification and practicing the disclosure herein. The present application is intended to cover any variations, uses, or adaptations of the present application, which follow the general principles of the present application and include common general knowledge or conventional technical means in the technical field not disclosed in the present application.

Claims

1. A method for identifying deep pools and shallows based on slope ratio and curvature analysis, characterized in that: include: Obtain the elevation data of the equally divided points on the riverbed deep line; Calculate the slope ratio of each point on the riverbed deep channel line using the elevation data of equally divided points on the riverbed deep channel line; Calculate the local curvature of each point on the riverbed deep channel line using the elevation data of equally divided points on the riverbed deep channel line; Deep pools and shallows are identified based on the slope ratio and local curvature of each point on the riverbed deep channel line.

2. The method according to claim 1, characterized in that Obtain the elevation data of the equally divided points on the riverbed deep line, including: Obtain a riverbed deep-water line, divide the deep-water line equally at predetermined intervals, and obtain the number of equally divided points n of the deep-water line; The elevation data of the riverbed deep-water line at the equally divided points from upstream to downstream are extracted and recorded as h(i), where i represents the i-th point, i = 1, 2, ..., n, and n is the total number of points.

3. The method according to claim 1, characterized in that The calculation formula for the slope ratio of the i-th point is: Where: is the elevation of the i+1th point; is the elevation of the i-th point; is the elevation of the i-1th point.

4. The method according to claim 1, characterized in that The calculation formula for the curvature of the i-th point is: Where: is the elevation of the i+1th point; is the elevation of the i-th point; is the elevation of the i-1th point.

5. The method according to claim 1, characterized in that Based on the slope ratio and local curvature of each point on the riverbed deep channel line, deep pools and shallows are identified, specifically: If the slope of the i-th point is And the curvature , then the terrain of the i-th point is judged to be a deep pool; If the slope of the i-th point is And the curvature , then the terrain of the i-th point is judged to be a shoal; If the slope of the i-th point is or curvature , then the terrain of the i-th point is judged to be neither a deep pool nor a shallow beach.

6. A device for identifying deep pools and shallows based on slope ratio and curvature analysis, characterized in that: include: The elevation acquisition module is used to obtain the elevation data of the equally divided points on the riverbed deep line; A slope ratio calculation module, used to calculate the slope ratio of each point on the riverbed deep channel line by using the elevation data of the equally divided points on the riverbed deep channel line; A curvature calculation module, used to calculate the local curvature of each point on the riverbed deep channel line by using the elevation data of equally divided points on the riverbed deep channel line; The terrain recognition module is used to identify deep pools and shallows based on the slope ratio and local curvature of each point on the riverbed deep channel line.

7. A computer program product comprising a computer program / instructions, characterized in that When the computer program / instructions are executed by a processor, the method according to any one of claims 1 to 5 is implemented.

8. An electronic device, characterized in that: include: one or more processors; A memory for storing one or more programs; When the one or more programs are executed by the one or more processors, the one or more processors implement the method according to any one of claims 1 to 5.

9. A computer-readable storage medium having computer instructions stored thereon, characterized in that: When the instruction is executed by a processor, the steps of the method according to any one of claims 1 to 5 are implemented.

Images