Large-range loess tableland surface extraction method based on ridge points

Abstract

The invention discloses a ridge point-based large-range loess tableland surface extraction method, which comprises the following steps: S1, plane curvature calculation: calculating and obtaining an unbiased plane curvature of a research area based on the plane curvature of an original DEM (Digital Elevation Model) and the plane curvature of an inverted DEM of the research area; s2, ridge point extraction: threshold conditions are set for the unbiased plane curvature and local positive and negative terrains of the research area, and ridge points of the research area are screened out; s3, potential tableland surface extraction, wherein according to the local fluctuation degree of the research area, the potential tableland surface is screened out by setting a fluctuation degree threshold value; and S4, extraction of formal tableland: according to the number of ridge points in each potential tableland, screening out the potential tableland containing a preset number of ridge points, and taking the potential tableland as the formal tableland. The loess plateau surface extraction method has the advantages that the loess plateau surface can be accurately and efficiently extracted, the loess plateau surface extraction method is suitable for large-range loess plateau surface extraction, and powerful support is provided for landform analysis, land utilization planning and ecological environment protection of loess plateau regions.

Description

Technical Field

[0001] The invention relates to the technical field of loess plateau surface extraction, and in particular to a large-scale loess plateau surface extraction method based on ridge points. Background Art

[0002] The loess plateau is a gully area composed of plateau surfaces, plateau slopes and gullies formed under the influence of tectonic movement, erosion, accumulation and human activities. The loess plateau surface is the most valuable land resource suitable for cultivation, farming and living in the Loess Plateau. Gully erosion leads to the fragmentation of the plateau surface, which seriously affects land use. Accurately extracting the plateau surface is crucial for scientific research and protection of the Loess Plateau.

[0003] At present, the main methods for extracting the plateau surface are field measurement, remote sensing image extraction, and DEM extraction. Although field measurement can obtain relatively accurate plateau surface edges, its accuracy is subject to the subjective judgment of the operator and its efficiency is relatively low. The remote sensing image method can accurately identify the edge of the plateau surface through image segmentation and feature recognition, but it is not suitable for large-scale feature extraction. The DEM method first determines the ditch line based on the slope change point, and then identifies the plateau surface. However, in practical applications, there are certain challenges in ensuring the effectiveness and consistency of the feature points along the ditch line. At the same time, most of the existing studies are based on the extraction of the ditch line of a local small watershed, and the geomorphic units need to be redefined for different landform types. To solve this problem, researchers urgently need to develop a technical means to quickly, simply, and effectively extract large-scale loess plateau surfaces and is suitable for different regions. Summary of the invention

[0004] The purpose of the present invention is to provide a large-scale loess plateau surface extraction method based on ridge points, so as to solve the above-mentioned problems existing in the prior art.

[0005] In order to achieve the above object, the technical solution adopted by the present invention is as follows:

[0006] A large-scale loess plateau surface extraction method based on ridge points includes the following steps:

[0007] S1. Plane curvature calculation: Based on the plane curvature of the original DEM and the plane curvature of the inverted DEM of the study area, the unbiased plane curvature of the study area is calculated;

[0008] S2, ridge point extraction: according to the local average elevation of the study area, the local positive and negative terrain of the study area is calculated, and the ridge points of the study area are screened out by setting threshold conditions for the unbiased plane curvature and local positive and negative terrain of the study area;

[0009] S3, potential plateau surface extraction: according to the local relief of the study area, potential plateau surfaces are screened out by setting relief threshold;

[0010] S4. Formal plateau surface extraction: According to the number of ridge points inside each potential plateau surface, the potential plateau surfaces containing a preset number of ridge points are screened out and used as formal plateau surfaces.

[0011] Preferably, step S1 is specifically as follows: based on the original DEM of the study area, the plane curvature of the original DEM of the study area and the plane curvature of the inverted DEM are calculated respectively; the plane curvature of the original DEM of the study area is added to the plane curvature of the inverted DEM and the absolute value of the difference between the two is subtracted, and then the average value is calculated to obtain the unbiased plane curvature of the study area.

[0012] Preferably, the planar curvature of the original DEM is calculated as follows:

[0013] Based on the original DEM of the study area, the downslope direction with the largest rate of change in value from each pixel to other adjacent pixels, i.e., the slope aspect, is calculated; based on the slope aspect, the maximum rate of change in the slope aspect of each pixel from the pixel to its adjacent pixels, i.e., the plane curvature of the original DEM of the study area, is calculated.

[0014] Preferably, the slope aspect is represented by positive degrees between 0 and 359.9 degrees, measured clockwise with north as the reference direction.

[0015] Preferably, the planar curvature of the inverted DEM is calculated as follows:

[0016] Based on the original DEM of the study area, the maximum elevation of the study area is extracted, and the difference between the maximum elevation of the study area and the original DEM of the study area is calculated to obtain the inverted terrain. Referring to the calculation method of the plane curvature of the original DEM, the plane curvature of the inverted DEM of the study area is calculated.

[0017] Preferably, step S2 is specifically as follows: based on the original DEM of the study area, the local average elevation of each pixel is calculated using a moving window method; the local average elevation value of each pixel is subtracted from the original DEM of the study area, and the local positive and negative terrain of each pixel is obtained according to the positive or negative value of the calculation result; threshold conditions are set for the unbiased plane curvature of the study area and the local positive and negative terrain of each pixel, and pixels with positive terrain and plane curvature greater than a preset threshold are screened out, that is, the ridge points of the study area are obtained.

[0018] Preferably, the local plane elevation is calculated as follows:

[0019] The moving window method is used to calculate the average value of all pixels in the specified neighborhood for each pixel of the original DEM of the study area to obtain the local average elevation of each pixel.

[0020] Preferably, step S3 specifically includes calculating the elevation difference between the highest point and the lowest point in the local area where each pixel is located as the local relief of the pixel; setting a relief threshold to screen out flat areas with small relief as potential plateau surfaces.

[0021] Preferably, step S4 specifically includes using a spatial statistical tool to count the number of ridge points in the potential plateau surface, setting a ridge point number threshold, screening out potential plateau surfaces containing a preset number of ridge points, and taking them as formal plateau surfaces.

[0022] Preferably, a raster-to-vector tool is used to convert the screened formal plateau surface in raster format into a formal plateau surface in vector format to facilitate subsequent spatial analysis and processing.

[0023] The beneficial effects of the present invention are as follows: 1. The present invention calculates the plane curvature according to the original terrain and inverted terrain of the study area, which can reduce the deviation of terrain features and obtain a more comprehensive and unbiased description of terrain features; 2. The present invention obtains the local positive terrain according to the original terrain and the local average elevation, and the ridge points of the study area can be obtained in combination with the plane curvature, ensuring that it is located at the high point of the terrain and has obvious convex features, thereby improving the accuracy of ridge point identification. 3. The present invention identifies the flat area as a potential plateau surface according to the local terrain undulation, which conforms to the terrain characteristics of the loess plateau surface. 4. The present invention selects the potential plateau surface containing a certain number of ridge points as the formal plateau surface by counting the number of ridge points in each potential plateau surface. These areas are not only flat, but also contain a certain number of ridge points, ensuring their reliability and scientificity as loess plateau surfaces. 5. The present invention can realize the accurate and efficient extraction of loess plateau surfaces, is suitable for the extraction of loess plateau surfaces in a large range, and provides strong support for geomorphic analysis, land use planning and ecological environmental protection in the Loess Plateau region. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 It is a technical roadmap of the extraction method in the embodiment of the present invention;

[0025] Figure 2 is the extraction result of the loess plateau surface in Qingyang City in the embodiment of the present invention (the whole city);

[0026] Figure 3 It is the extraction result (partial) of the potential plateau surface of the loess plateau surface in Qingyang City in the embodiment of the present invention;

[0027] Figure 4 This is the official extraction result (partial) of the loess plateau in Qingyang City in the embodiment of the present invention. DETAILED DESCRIPTION

[0028] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings. It should be understood that the specific implementation methods described herein are only used to explain the present invention and are not used to limit the present invention.

[0029] Embodiment 1

[0030] like Figure 1 As shown, in this embodiment, a large-scale loess plateau surface extraction method based on ridge points is provided, which specifically includes the following four parts:

[0031] 1. Plane curvature calculation

[0032] Based on the plane curvature of the original DEM and the plane curvature of the inverted DEM of the study area, the unbiased plane curvature of the study area is calculated. Specifically, it includes the following contents:

[0033] 1.1. Calculate the plane curvature of the original terrain

[0034] First, the downslope direction with the largest rate of change in the value from each pixel to its adjacent pixel is calculated, i.e., the aspect. The aspect is represented by a positive degree between 0 and 359.9 degrees, measured clockwise from north. Based on the aspect, the maximum rate of change in the aspect of each pixel's calculated value from the pixel to its adjacent pixel is calculated to identify the maximum change in the aspect within a small local range on the surface.

[0035] 1.2. Calculate the plane curvature of the inverted terrain

[0036] The maximum elevation of the study area is extracted, and the difference between it and the original DEM is calculated to obtain the inverted terrain. The slope aspect variability of the inverted terrain is calculated by referring to the slope aspect variability calculation method of the original terrain.

[0037] 1.3 Unbiased DEM Slope Variability

[0038] In order to correct the aspect variability deviation in the north slope area, the sum of the aspect variability of the original terrain and the inverted terrain minus the absolute value of the difference between the two is calculated, and then the average is calculated to obtain the unbiased plane curvature of the study area. The area with a large plane curvature value is the ridge or valley.

[0039] 2. Ridge Point Extraction

[0040] The local positive and negative terrain of the study area is obtained by calculating the local average elevation of the study area, and the ridge points of the study area are screened out by setting threshold conditions for the unbiased plane curvature and local positive and negative terrain of the study area. The specific contents include the following:

[0041] 2.1. Calculate local average elevation

[0042] Using the moving window method, the average value of all pixels in the specified neighborhood is calculated for each pixel to obtain the local average elevation of each grid. This process is equivalent to local averaging. For example, the elevations of 4 pixels are 10, 8, 6, and 4, where 10 is a peak and 4 is a valley. After averaging, the average of the 4 pixels is 7.

[0043] 2.2. Positive and negative terrain calculation

[0044] Subtract the local mean elevation from the original DEM to get the local positive and negative terrain (ZFDX), which reflects the elevation change of each grid relative to its neighboring area. Among them, a positive value indicates that the elevation of the pixel is higher than the local mean, and a negative value indicates that the elevation of the pixel is lower than the local mean. For example, after subtracting the local mean 7 from the original DEM, the results are 3, 1, -1, and -3. Values ​​greater than 0 are positive terrain, and values ​​less than 0 are negative terrain.

[0045] 2.3 Ridge point identification

[0046] Threshold conditions are set for plane curvature and positive and negative terrain, and pixels with positive terrain and large plane curvature (plane curvature greater than the preset threshold) are screened out to obtain the ridge points of the study area. The threshold conditions can be selected according to actual conditions to better meet actual needs. For example, the threshold conditions can be set to plane curvature greater than 80 and local terrain is positive.

[0047] 3. Potential plateau extraction

[0048] According to the local undulation of the study area, potential plateau surfaces are screened out by setting the undulation threshold. The specific contents include the following:

[0049] 1. Fluctuation calculation

[0050] The elevation difference between the highest point and the lowest point in the local area of ​​each pixel is calculated to obtain the relief.

[0051] 2. Potential plateau identification

[0052] Set the undulation threshold to filter out flat areas with small undulation as potential plateaus. This step is based on the assumption that loess plateaus usually appear as relatively flat terrain. The undulation threshold can be set according to actual conditions to better meet actual needs. For example, the undulation threshold can be set to 20.

[0053] 4. Formal plateau extraction

[0054] According to the number of ridge points inside each potential plateau surface, potential plateau surfaces containing a certain number of ridge points are screened out and used as formal plateau surfaces. The specific contents include the following:

[0055] 4.1. Counting the number of potential ridge points in the plateau

[0056] Using spatial analysis tools, count the number of ridge points within each potential plateau.

[0057] 4.2. Formal plateau surface extraction

[0058] Potential plateau surfaces containing a preset number of ridge points are screened out and used as formal plateau surfaces. The preset number can be set according to actual conditions to better meet actual needs. For example, the preset number can be set to 10.

[0059] 4.3 Vector Conversion

[0060] Use the raster-to-vector tool to convert the filtered formal plateau surface in raster format into a formal plateau surface in vector format to facilitate subsequent spatial analysis and processing.

[0061] Embodiment 2

[0062] like Figure 2 and Figure 3 As shown, taking Qingyang City in Gansu Province as an example, the method of the present invention is used to extract the loess plateau surface of Qingyang City, including the following contents:

[0063] 1. Plane curvature calculation

[0064] 1.1. Calculate the curvature of the original terrain: This study takes Qingyang City, Gansu Province as the research area. The terrain data comes from the DEM data with a spatial resolution of 12.5m×12.5m and a vertical accuracy of 6m released by USGS. The Aspect tool of ArcGIS is used to calculate the slope of the original DEM. On this basis, the slope of the slope tool is used to obtain the plane curvature of the original DEM.

[0065] 1.2. Extract the curvature of the inverted terrain: Extract the maximum value of the study area, calculate the difference with the original DEM, obtain the inverted terrain, and refer to the previous step to calculate the slope aspect and plane curvature of the inverted terrain.

[0066] 1.3. Calculation of unbiased plane curvature: Sum the plane curvatures of the original terrain and the inverted terrain, then subtract the absolute value of the difference between the two to obtain the unbiased plane curvature.

[0067] 2. Ridge Point Extraction

[0068] 2.1. Calculate the local mean elevation: Use the Focal Statistics tool of ArcGIS to calculate the local mean of each grid with a 12×12 moving window.

[0069] 2.2. Calculation of positive and negative terrain: Use the Raster Calculator tool of ArcGIS to calculate the difference between the original terrain and the local average elevation to obtain the positive and negative terrain.

[0070] 2.3. Ridge point identification: Using the Raster Calculator tool of ArcGIS, 1,997,732 ridge points in the study area were obtained with positive terrain and plane curvature greater than 80 as conditions.

[0071] 3. Potential plateau extraction

[0072] 3.1. Calculation of relief: Use the Focal Statistics tool of ArcGIS to calculate the relief of the local area where each pixel is located with a 12×12 window.

[0073] 3.2. Identification of potential plateaus: Using the Raster Calculator tool of ArcGIS, we screened out areas with a relief less than 20 meters based on the relief results, and obtained 57,461 potential plateaus.

[0074] 4. Formal plateau extraction

[0075] 4.1. Statistics of the number of ridge points in potential plateaus: Use the Zonal Statistics tool of ArcGIS to conduct regional statistical analysis on the ridge points in the identified potential plateau areas and calculate the number of ridge points in each potential plateau.

[0076] 4.2. Screening out formal plateau surfaces: Using the Extract by Attributes tool in ArcGIS, potential plateau surfaces with more than 10 ridge points were screened out, and a final total of 2,709 formal plateau surfaces were obtained.

[0077] 4.3. Conversion of the formal plateau surface into vector format: Use the Raster To Polygon tool of ArcGIS to convert the formal plateau surface in raster format obtained in the previous step into vector format to facilitate subsequent spatial analysis and processing.

[0078] By adopting the above technical solution disclosed in the present invention, the following beneficial effects are obtained:

[0079] The invention discloses a large-scale extraction method of loess plateau surface based on ridge points. The invention calculates the plane curvature according to the original terrain and inverted terrain of the study area, which can reduce the deviation of terrain features and obtain a more comprehensive and unbiased description of terrain features; the invention obtains the local positive terrain according to the original terrain and the local average elevation, and the ridge points of the study area can be obtained in combination with the plane curvature, which ensures that it is located at the high point of the terrain and has obvious convex features, thereby improving the accuracy of ridge point identification. The invention identifies the flat area as a potential plateau surface according to the local terrain undulation, which conforms to the terrain characteristics of the loess plateau surface. The invention selects the potential plateau surface containing a certain number of ridge points as the formal plateau surface by counting the number of ridge points in each potential plateau surface. These areas are not only flat, but also contain a certain number of ridge points, ensuring their reliability and scientificity as loess plateau surfaces. The invention can realize accurate and efficient extraction of loess plateau surfaces, is suitable for large-scale loess plateau surface extraction, and provides strong support for geomorphic analysis, land use planning and ecological environmental protection in the Loess Plateau region.

[0080] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principle of the present invention. These improvements and modifications should also be considered as the scope of protection of the present invention.

Claims

1. A large-scale loess plateau surface extraction method based on ridge points, characterized in that: The following steps are included: S1. Plane curvature calculation: Based on the plane curvature of the original DEM and the plane curvature of the inverted DEM of the study area, the unbiased plane curvature of the study area is calculated; S2, ridge point extraction: according to the local average elevation of the study area, the local positive and negative terrain of the study area is calculated, and the ridge points of the study area are screened out by setting threshold conditions for the unbiased plane curvature and local positive and negative terrain of the study area; S3, potential plateau surface extraction: according to the local relief of the study area, potential plateau surfaces are screened out by setting relief threshold; S4. Formal plateau surface extraction: According to the number of ridge points inside each potential plateau surface, the potential plateau surfaces containing a preset number of ridge points are screened out and used as formal plateau surfaces.

2. The large-scale loess plateau surface extraction method based on ridge points according to claim 1 is characterized in that: Step S1 specifically comprises: based on the original DEM of the study area, respectively calculating the plane curvature of the original DEM of the study area and the plane curvature of the inverted DEM; adding the plane curvature of the original DEM of the study area to the plane curvature of the inverted DEM and subtracting the absolute value of the difference between the two, and then calculating the average value to obtain the unbiased plane curvature of the study area.

3. The large-scale loess plateau extraction method based on ridge points according to claim 2 is characterized in that: The planar curvature of the original DEM is calculated as follows: Based on the original DEM of the study area, the downslope direction with the largest rate of change in value from each pixel to other adjacent pixels, i.e., the slope aspect, is calculated; based on the slope aspect, the maximum rate of change in the slope aspect of each pixel from the pixel to its adjacent pixels, i.e., the plane curvature of the original DEM of the study area, is calculated.

4. The large-scale loess plateau surface extraction method based on ridge points according to claim 3 is characterized in that: The aspect is expressed in positive degrees between 0 and 359.9 degrees, measured clockwise from north.

5. The large-scale loess plateau surface extraction method based on ridge points according to claim 3 is characterized in that: The plan curvature of the inverted DEM is calculated as follows: Based on the original DEM of the study area, the maximum elevation of the study area is extracted, and the difference between the maximum elevation of the study area and the original DEM of the study area is calculated to obtain the inverted terrain. Referring to the calculation method of the plane curvature of the original DEM, the plane curvature of the inverted DEM of the study area is calculated.

6. The large-scale loess plateau surface extraction method based on ridge points according to claim 1 is characterized in that: Step S2 specifically includes: calculating the local average elevation of each pixel using the moving window method based on the original DEM of the study area; subtracting the local average elevation value of each pixel from the original DEM of the study area, and obtaining the local positive and negative terrain of each pixel according to the positive or negative value of the calculation result; setting threshold conditions for the unbiased plane curvature of the study area and the local positive and negative terrain of each pixel, screening out pixels with positive terrain and plane curvature greater than the preset threshold, that is, obtaining the ridge points of the study area.

7. The method for extracting large-scale loess plateau surface based on ridge points according to claim 6 is characterized in that: The local plane elevation is calculated as follows: The moving window method is used to calculate the average value of all pixels in the specified neighborhood for each pixel of the original DEM of the study area to obtain the local average elevation of each pixel.

8. The method for extracting large-scale loess plateau surface based on ridge points according to claim 1 is characterized in that: Step S3 specifically includes calculating the elevation difference between the highest point and the lowest point in the local area where each pixel is located as the local relief of the pixel; setting a relief threshold to screen out flat areas with small relief as potential plateau surfaces.

9. The method for extracting large-scale loess plateau surface based on ridge points according to claim 1, characterized in that: Step S4 specifically includes using a spatial statistics tool to count the number of ridge points in the potential plateau surface, setting a ridge point number threshold, and screening out potential plateau surfaces containing a preset number of ridge points as formal plateau surfaces.

10. The method for extracting large-scale loess plateau surface based on ridge points according to claim 9, characterized in that: Use the raster-to-vector tool to convert the filtered formal plateau surface in raster format into a formal plateau surface in vector format to facilitate subsequent spatial analysis and processing.

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