Land investigation slope grading map smoothing method

Abstract

The invention provides a land investigation gradient grading map smoothing method. The method comprises the following steps: S1, obtaining a land investigation gradient grading map; s2, after the land investigation gradient grading map is obtained, smoothness processing is carried out on the obtained land investigation gradient grading map; and S3, displaying the processed land investigation slope grading map. According to the method, the slope grading graph can be smoothed, so that the slope grading graph is more regular and continuous.

Description

Technical Field

[0001] The present invention relates to the technical field of land slope treatment, and particularly to a method for smoothing a slope classification map in national land surveys. Background Art

[0002] Slope represents the degree of steepness of the surface unit. Generally, the ratio of the vertical height to the horizontal distance of the slope surface is called the slope (or slope ratio). The terrain shows topographic features such as plains, hills, and mountains in the form of slopes. Patent Application No. 2023113322252, titled "Land Use Evaluation Method and Device", discloses the following steps: obtaining a map base map; obtaining the terrain slope information of the land corresponding to the map base map, and generating a slope classification map based on the map base map and the terrain slope information; obtaining the elevation information of the land corresponding to the map base map, and generating a first urban land resource grade map based on the map base map, the slope classification map, and the elevation information; obtaining the terrain undulation information of the land corresponding to the map base map, and correcting the first urban land resource grade map to a second urban land resource grade map based on the terrain undulation information; showing the second urban land resource grade map, which is helpful for land use evaluation of urban expansion. The slope classification map generated in this patent application may be irregular, resulting in inaccurate data. Summary of the Invention

[0003] The present invention aims to at least solve the technical problems existing in the prior art, and particularly innovatively proposes a method for smoothing a slope classification map in national land surveys.

[0004] To achieve the above object of the present invention, the present invention provides a method for smoothing a slope classification map in national land surveys, including the following steps:

[0005] S1, obtaining a slope classification map in national land surveys;

[0006] S2, after obtaining the slope classification map in national land surveys, performing a smoothness treatment on the obtained slope classification map in national land surveys;

[0007] S3, displaying the processed slope classification map in national land surveys.

[0008] In a preferred embodiment of the present invention, the method for performing a smoothness treatment on the obtained slope classification map in national land surveys in step S2 includes the following steps:

[0009] S21, setting the size of the pixel search box to P×P;

[0010] S22, determining the position of the current pixel search box in the slope classification map in national land surveys; recording the central pixel point coordinates of the determined position of the current pixel search box in the slope classification map in national land surveys as (i, j), then the pixel point coordinates of the determined position of the current pixel search box in the slope classification map in national land surveys are:

[0011]

[0012] It can also be recorded as:

[0013]

[0014] The pixel point coordinates of the left position of the current pixel search box on the land survey slope classification map are:

[0015]

[0016] It can also be recorded as:

[0017]

[0018] The pixel point coordinates of the upper position of the current pixel search box on the land survey slope classification map are:

[0019] It can also be recorded as:

[0020]

[0021] The pixel point coordinates of the right position of the current pixel search box on the land survey slope classification map are:

[0022] It can also be recorded as:

[0023]

[0024] The pixel point coordinates of the lower position of the current pixel search box on the land survey slope classification map are:

[0025] It can also be recorded as:

[0026]

[0027] S23. Obtain the slope classification value of each pixel point coordinate under the current pixel search box; according to all the obtained slope classification values, count the number of numerical values of the slope classification value at the left position, and record the maximum number as A Left , A Left represents the numerical value with the largest number after counting the number of numerical values of the slope classification value at the left position;

[0028] Count the number of numerical values of the slope classification value at the upper position, and record the maximum number as A Up , A Up represents the numerical value with the largest number after counting the number of numerical values of the slope classification value at the upper position;

[0029] Count the number of values of the slope classification value at the right position, and record the maximum number as A Right , A Right represents the value with the largest number after counting the number of values of the slope classification value at the right position;

[0030] Count the number of values of the slope classification value at the left position, and record the maximum number as A Down , A Down represents the value with the largest number after counting the number of values of the slope classification value at the lower position;

[0031] S24, let A Left , A Up , A Right , A Down After arranging these four values in descending order, they are respectively: A max , A max-1 , A max-2 , A max-3 ;

[0032] Among them, A max represents the value that ranks first after arranging A Left , A Up , A Right , A Down these four values in descending order;

[0033] A max-1 represents the value that ranks second after arranging A Left , A Up , A Right , A Down these four values in descending order;

[0034] A max-2 represents the value that ranks third after arranging A Left , A Up , A Right , A Down these four values in descending order;

[0035] A max-3 represents the value that ranks fourth after arranging A Left , A Up , A Right , A Down these four values in descending order;

[0036] If A max > A max-1, then replace the slope classification value of the central pixel point coordinate at the position of the current pixel search box on the national land survey slope classification map with the slope classification value corresponding to the numerically first-ranked value;

[0037] If A max = A max-1 , then execute the next step;

[0038] S25. Obtain the positions corresponding to the slope classification values of A max and the positions corresponding to the slope classification values of A max-1 . Form a position set with the positions corresponding to the slope classification values of A max and the positions corresponding to the slope classification values of A max-1 ;

[0039] If there is a left position in the position set, then replace the slope classification value of the central pixel point coordinate at the position of the current pixel search box on the national land survey slope classification map with the slope classification value having the largest number of numerical values among the slope classification values of the left positions;

[0040] If there is no left position in the position set but there is an upper position, then replace the slope classification value of the central pixel point coordinate at the position of the current pixel search box on the national land survey slope classification map with the slope classification value having the largest number of numerical values among the slope classification values of the upper positions;

[0041] If there are right and lower positions in the position set, then replace the slope classification value of the central pixel point coordinate at the position of the current pixel search box on the national land survey slope classification map with the slope classification value having the largest number of numerical values among the slope classification values of the right positions;

[0042] S26. The pixel search box moves to the next position until the entire national land survey slope classification map is traversed.

[0043] In a preferred embodiment of the present invention, in step S21, P is an odd number greater than or equal to 3.

[0044] In a preferred embodiment of the present invention, in step S21, the size of the pixel search box is 5×5.

[0045] In a preferred embodiment of the present invention, in step S22, the relationship between P and p is expressed as:

[0046]

[0047] where P represents the number of horizontal / vertical pixel points of the pixel search box;

[0048] represents the floor function symbol;

[0049] p represents the number of pixel points between the center position of the pixel search box and the left bounding box / upper bounding box / right bounding box / lower bounding box.

[0050] In a preferred embodiment of the present invention, before step S1, there is also step S0, using an aerial drone to take a vertical aerial view of land resources by land type, and converting the vertical aerial view of land resources by land type into a slope grading map for land survey and generating a sampling inspection map.

[0051] In a preferred embodiment of the present invention, the method for generating a sampling inspection map according to the vertical aerial view of land resources by land type in step S0 includes the following steps:

[0052] S11, dividing the land type contours of the vertical aerial view of land resources by land type;

[0053] S12, performing land resource land type annotation on the vertical aerial view of land resources by land type after the land type contour division in step S11;

[0054] S13, classifying the vertical aerial view of land resources by land type after annotation in step S12 to generate a sampling inspection map for rapid sampling inspection and verification. The present invention can quickly verify and identify according to the sampling inspection map, improving efficiency and accuracy.

[0055] In a preferred embodiment of the present invention, the land type contour division in step S11 is the land type contour division of the vertical aerial view of land resources by land type using the brush tool in Photoshop drawing software.

[0056] The present invention also discloses a computer system, including:

[0057] A processor;

[0058] A memory for storing processor-executable instructions;

[0059] Wherein, the processor is configured to implement the land survey slope grading map smoothing method when executing the executable instructions.

[0060] The present invention also discloses a computer-readable storage medium, including:

[0061] A memory, on which a computer program is stored;

[0062] A processor, for executing the program in the memory to implement the land survey slope grading map smoothing method.

[0063] In summary, due to the adoption of the above technical solutions, the present invention can smooth the slope grading map, making the slope grading map more regular and continuous.

[0064] Additional aspects and advantages of the present invention will be given in part in the following description, become apparent in part from the following description, or be learned by practice of the present invention. Brief Description of the Drawings

[0065] The above and / or additional aspects and advantages of the present invention will become apparent and be readily understood from the description of the embodiments in conjunction with the following drawings, in which:

[0066] Figure 1 is a schematic flow diagram of the present invention.

[0067] Figure 2 are schematic diagrams before and after the smoothness processing of the slope classification map of the national land survey of the present invention.

[0068] Figure 3 are schematic diagrams before and after the smoothness processing of the slope classification map of the national land survey of the present invention.

[0069] Figure 4 are schematic diagrams before and after the smoothness processing of the slope classification map of the national land survey of the present invention.

[0070] Figure 5 are schematic diagrams before and after the smoothness processing of the slope classification map of the national land survey of the present invention. Detailed Description of the Embodiments

[0071] Embodiments of the present invention will be described in detail below. Examples of the embodiments are shown in the drawings, where the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the drawings are exemplary only for explaining the present invention and should not be construed as limiting the present invention.

[0072] The present invention provides a method for smoothing the slope classification map of the national land survey, as Figure 1 shown, including the following steps:

[0073] S1, obtaining the slope classification map of the national land survey; as Figures 2 to 5 shown in (a) of

[0074] S2, after obtaining the slope classification map of the national land survey, performing smoothness processing on the obtained slope classification map of the national land survey;

[0075] S3, displaying the processed slope classification map of the national land survey as Figures 2 to 5 shown in (b) of

[0076] In a preferred embodiment of the present invention, the method for performing smoothness processing on the obtained slope classification map of the national land survey in step S2 includes the following steps:

[0077] S21, setting the pixel search box size to P×P;

[0078] S22. Determine the position of the current pixel search box on the national land survey slope classification map; Denote the center pixel coordinates of the determined position of the current pixel search box on the national land survey slope classification map as (i, j), then the pixel coordinates of the determined position of the current pixel search box on the national land survey slope classification map are:

[0079]

[0080] It can also be denoted as:

[0081]

[0082] The pixel coordinates of the left position of the determined position of the current pixel search box on the national land survey slope classification map are:

[0083] It can also be denoted as:

[0084]

[0085] The pixel coordinates of the upper position of the determined position of the current pixel search box on the national land survey slope classification map are:

[0086] It can also be denoted as:

[0087]

[0088] The pixel coordinates of the right position of the determined position of the current pixel search box on the national land survey slope classification map are:

[0089]

[0090] It can also be denoted as:

[0091]

[0092] The pixel coordinates of the lower position of the determined position of the current pixel search box on the national land survey slope classification map are:

[0093]

[0094] It can also be denoted as:

[0095]

[0096] S23. Obtain the slope classification value of each pixel coordinate under the current pixel search box; According to all the obtained slope classification values, count the number of numerical values of the slope classification value at the left position, and denote the maximum number as A Left , A LeftRepresents the value with the largest number after counting the number of numerical values of the slope classification value at the left position;

[0097] Count the number of numerical values of the slope classification value at the upper position, and record the largest number as A Up , A Up Represents the value with the largest number after counting the number of numerical values of the slope classification value at the upper position;

[0098] Count the number of numerical values of the slope classification value at the right position, and record the largest number as A Right , A Right Represents the value with the largest number after counting the number of numerical values of the slope classification value at the right position;

[0099] Count the number of numerical values of the slope classification value at the left position, and record the largest number as A Down , A Down Represents the value with the largest number after counting the number of numerical values of the slope classification value at the lower position;

[0100] S24, take A Left , A Up , A Right , A Down After arranging these four values of A max , A max-1 , A max-2 , A max-3 ;

[0101] Among them, A max Represents the value that ranks first after arranging these four values of A Left , A Up , A Right , A Down in descending order;

[0102] A max-1 Represents the value that ranks second after arranging these four values of A Left , A Up , A Right , A Down in descending order;

[0103] A max-2 Represents the value that ranks third after arranging these four values of A Left , A Up , A Right , A Down in descending order;

[0104] A max-3 Represents the value that ranks fourth after arranging these four values of A Left , AUp , A Right , A Down The value that ranks fourth after arranging these four values in descending order;

[0105] If A max > A max-1 , then replace the slope classification value of the center pixel point coordinate at the position of the current pixel search box in the national land survey slope classification map with the slope classification value corresponding to the value that ranks first in the statistics;

[0106] If A max = A max-1 , then perform the next step;

[0107] S25. Obtain the positions corresponding to the slope classification values of A max and the positions corresponding to the slope classification values of A max-1 . Form a position set with the positions corresponding to the slope classification values of A max and the positions corresponding to the slope classification values of A max-1 ;

[0108] If there is a left position in the position set, then replace the slope classification value of the center pixel point coordinate at the position of the current pixel search box in the national land survey slope classification map with the slope classification value that has the largest number of numerical values among the slope classification values of the left position;

[0109] If there is no left position in the position set but there is an upper position, then replace the slope classification value of the center pixel point coordinate at the position of the current pixel search box in the national land survey slope classification map with the slope classification value that has the largest number of numerical values among the slope classification values of the upper position;

[0110] If there are a right position and a lower position in the position set, then replace the slope classification value of the center pixel point coordinate at the position of the current pixel search box in the national land survey slope classification map with the slope classification value that has the largest number of numerical values among the slope classification values of the right position;

[0111] S26. The pixel search box moves to the next position until the entire national land survey slope classification map is traversed.

[0112] In a preferred embodiment of the present invention, in step S21, P is an odd number greater than or equal to 3.

[0113] In a preferred embodiment of the present invention, in step S21, the size of the pixel search box is 5×5.

[0114] In a preferred embodiment of the present invention, the relationship between P and p in step S22 is expressed as:

[0115]

[0116] Among them, P represents the number of horizontal / vertical pixel points of the pixel search box;

[0117] represents the floor function symbol;

[0118] p represents the number of pixel points between the center position of the pixel search box and the left / upper / right / lower boundary box.

[0119] The present invention also discloses a computer system, including:

[0120] a processor;

[0121] a memory for storing processor-executable instructions;

[0122] wherein, when the processor is configured to execute the executable instructions, the smooth method of the land survey slope grading map is implemented.

[0123] The present invention also discloses a computer-readable storage medium, including:

[0124] a memory having a computer program stored thereon;

[0125] a processor for executing the program in the memory to implement the smooth method of the land survey slope grading map.

[0126] In a preferred embodiment of the present invention, before step S1, there is also step S0, using an aerial camera to take a vertical aerial view of land resources land types, and converting the vertical aerial view of land resources land types into a land survey slope grading map and generating a sampling inspection map.

[0127] In a preferred embodiment of the present invention, the method for generating a sampling inspection map according to the vertical aerial view of land resources land types in step S0 includes the following steps:

[0128] S11, dividing the land type outlines of the vertical aerial view of land resources land types;

[0129] S12, performing land resources land type annotation on the vertical aerial view of land resources land types after the land type outline division in step S11;

[0130] S13, classifying the vertical aerial view of land resources land types after annotation in step S12 to generate a sampling inspection map for rapid sampling inspection and verification.

[0131] In a preferred embodiment of the present invention, step S0 is

[0132] using M vertical aerial views of land resources land types taken by an aerial camera, where M is a positive integer greater than or equal to 2;

[0133] Stitch M vertical aerial views of land types of land and resources into one vertical aerial view of land types of land and resources.

[0134] In a preferred embodiment of the present invention, in step S12, the land types of land and resources include one or any combination of reservoir water surface land type, dry land land type, paddy field land type, arbor forest land type, shrub forest land type, water conservancy and hydropower construction land type, rural homestead land type, pond water surface land type, bamboo forest land type, and rural road land type.

[0135] In a preferred embodiment of the present invention, in step S0, the area photographed by the aerial camera is an area unitized by group / village, village / community, town / township / sub-district, and district / county.

[0136] In a preferred embodiment of the present invention, in step S11, the land type contour division is performed on the vertical aerial view of land types of land and resources through a drawing software (such as the brush tool in Photoshop, Adobe Illustrator, CorelDRAW, etc.) to outline the land type contour of the land type.

[0137] In a preferred embodiment of the present invention, in step S13, the method for classifying the marked vertical aerial view of land types of land and resources includes the following steps:

[0138] S131, count the number of land type categories of land and resources, denoted as N, which are the 1st land type of land and resources, the 2nd land type of land and resources, the 3rd land type of land and resources,..., the Nth land type of land and resources; in this embodiment, N = 10, and correspondingly, the 1st land type of land and resources is the dry land land type, the 2nd land type of land and resources is the rural homestead land type, the 3rd land type of land and resources is the paddy field land type, the 4th land type of land and resources is the reservoir water surface land type, the 5th land type of land and resources is the arbor forest land type, the 6th land type of land and resources is the shrub forest land type, the 7th land type of land and resources is the water conservancy and hydropower construction land type, the 8th land type of land and resources is the pond water surface land type, the 9th land type of land and resources is the bamboo forest land type, and the 10th land type of land and resources is the rural road land type.

[0139] Count the number of contour areas after the land type contour division of the vertical aerial view of land types of land and resources, denoted as K, which are the 1st contour land type area, the 2nd contour land type area, the 3rd contour land type area,..., the Kth contour land type area, and the area of each contour land type area is S 1 、S 2 、S 3 、……、S K ;S 1 is the area of the 1st contour land type area, S 2 is the area of the 2nd contour land type area, S 3is the area of the 3rd contour land use type area, S K is the area of the Kth contour land use type area;

[0140] Arrange the areas of each contour land use type area in ascending order as follows:

[0141] S′ min , S′ min-1 , S′ min-2 , S′ min-K+1 ,

[0142] wherein, S′ min represents the area ranked 1st after arranging the areas of each contour land use type area in ascending order;

[0143] S′ min-1 represents the area ranked 2nd after arranging the areas of each contour land use type area in ascending order;

[0144] S′ min-2 represents the area ranked 3rd after arranging the areas of each contour land use type area in ascending order;

[0145] S′ min-K+1 represents the area ranked Kth after arranging the areas of each contour land use type area in ascending order;

[0146] S132, set the size of the sampling frame (φ×φ, preferably 31×31, that is, 31 pixel points horizontally and 31 pixel points vertically, a square sampling frame of 31 pixel points), the number of samples for each land use type contour division area, and N sampling maps; N is the number of land use type categories of land and resources; the calculation method of the number of samples is:

[0147]

[0148] wherein, O k represents the number of samples for the kth contour land use type area;

[0149] S k is the area of the kth contour land use type area;

[0150] S′ min represents the area ranked 1st after arranging the areas of each contour land use type area in ascending order;

[0151] represents the ceiling function;

[0152] <> represents taking the fractional part;

[0153] Z represents an integer;

[0154] The size of each sampled inspection image is preferably 310×310. At this time respectively represent the number of sizes of the sampled inspection frames that can be placed horizontally and vertically in the sampled inspection image; the sampled inspection image is composed of 10×10 pure white images with the size of the sampled inspection frame. The size of each pure white image is the same as the size of the sampled inspection frame. From left to right and from top to bottom (the setting order, this setting order can also be from top to bottom and from left to right, and can be other orders), they are the 11th pure white image, the 12th pure white image, the 13th pure white image, ……, the 1φth pure white image in sequence, and this is the first row of pure white images;

[0155] the 21st pure white image, the 22nd pure white image, the 23rd pure white image, ……, the 2φth pure white image, and this is the second row of pure white images;

[0156] the 31st pure white image, the 32nd pure white image, the 33rd pure white image, ……, the 3φth pure white image, and this is the third row of pure white images;

[0157] ……;

[0158] the φ1st pure white image, the φ2nd pure white image, the φ3rd pure white image, ……, the φφth pure white image, and this is the φth row of pure white images;

[0159] When φ takes 10, from left to right and from top to bottom, they are the 11th pure white image, the 12th pure white image, the 13th pure white image, ……, the 110th pure white image in sequence, and this is the first row of pure white images;

[0160] the 21st pure white image, the 22nd pure white image, the 23rd pure white image, ……, the 210th pure white image, and this is the second row of pure white images;

[0161] the 31st pure white image, the 32nd pure white image, the 33rd pure white image, ……, the 310th pure white image, and this is the third row of pure white images;

[0162] ……;

[0163] the 101st pure white image, the 102nd pure white image, the 103rd pure white image, ……, the 1010th pure white image, and this is the tenth row of pure white images;

[0164] S133. Perform row and column division on the vertical aerial view of land resources land types after the land type contour division in step S12. Among them, the number of pixel points between row lines is equal to the number of vertical pixel points of the sampling frame, and the number of pixel points between column lines is equal to the number of horizontal pixel points of the sampling frame. If the number of row pixel points or column pixel points in the last row or the last column (the first row or the first column) is less than the number of horizontal pixel points or the number of vertical pixel points of the sampling frame, then this row or this column can be retained or discarded.

[0165] When retaining, corresponding row pixel points or column pixel points can be added before the corresponding first row or first column or after the last row or last column, so that the number of row pixel points or column pixel points in the last row or the last column (the first row or the first column) is equal to the number of horizontal pixel points or the number of vertical pixel points of the sampling frame; the pixel values of the added row pixel points or column pixel points are pure white.

[0166] S134. Select contour regions from the vertical aerial view of land resources land types after the land type contour division in step S12 in the set order (the set order can be from left to right, from top to bottom, or from top to bottom, from left to right, or randomly). Randomly select one or more sampling frames within the selected contour regions (the number of sampling frames here is determined by the number of samplings in each land type contour division region). If the sampling frames do not all completely belong to the selected contour regions, then translate the selected sampling frames up, down, left, or right (each time moving a distance of one pixel point) or, with the center of the selected sampling frame as the center, reduce the size of the sampling frame by the number of pixel points reduced, which is an even number greater than 1; so that the selected sampling frames are completely within the selected contour regions;

[0167] S135. Copy (overlay) the image in the selected sampling frame to the sampling map corresponding to the land type category, and make the center of the image in the selected sampling frame coincide with the center of the overlaid sampling frame, so that the image in the selected sampling frame is completely within the sampling frame in the sampling map; this step also includes obtaining the link pixel point coordinates of the image in the selected sampling frame and storing the obtained link pixel point coordinates in the image in the selected sampling frame, which is convenient for subsequent querying the position of the image in the vertical aerial view of land resources land types according to the pixel point coordinates to view the annotation of the land type category.

[0168] S136. Execute steps S134 - S135 until all contour regions in the vertical aerial view of land resources land types after the land type contour division in step S12 are selected.

[0169] In a preferred embodiment of the present invention, after step S13, there is further a step S14. When viewing the sampling inspection map, if a certain sampling inspection box in the sampling inspection map is selected and viewed, then it jumps to the position of the vertical aerial view of the land resource land type corresponding to the image in the sampling inspection box after the annotation in step S12, and determines whether the classification is correct.

[0170] In a preferred embodiment of the present invention, step S14 includes the following steps:

[0171] S141, determine whether a trigger signal for selecting a certain sampling inspection box in the sampling inspection map is received:

[0172] If a trigger signal for selecting a certain sampling inspection box in the sampling inspection map is received, then execute the next step;

[0173] If a trigger signal for selecting a certain sampling inspection box in the sampling inspection map is not received, then execute step S141;

[0174] S142, determine whether a trigger signal for viewing a certain sampling inspection box in the selected sampling inspection map is received:

[0175] If a trigger signal for viewing a certain sampling inspection box in the selected sampling inspection map is received, then execute the next step;

[0176] If a trigger signal for viewing a certain sampling inspection box in the selected sampling inspection map is not received, then execute step S142;

[0177] S143, obtain the link pixel point coordinates of the image in a certain sampling inspection box in the selected sampling inspection map, and determine whether the link pixel point coordinates of the image in a certain sampling inspection box in the selected sampling inspection map are obtained:

[0178] If the link pixel point coordinates of the image in a certain sampling inspection box in the selected sampling inspection map are obtained, then execute step S144;

[0179] If the link pixel point coordinates of the image in a certain sampling inspection box in the selected sampling inspection map are not obtained, then execute step S143;

[0180] S144, search for the image position corresponding to the vertical aerial view of the land resource land type where the link pixel point coordinates are located according to the link pixel point coordinates;

[0181] There is also a step S145. After searching for the image position corresponding to the vertical aerial view of the land resource land type where the link pixel point coordinates are located according to the link pixel point coordinates, the (sampling inspector) can then determine whether the land type category corresponding to the image contained in the contour area where the image position is located is the land type category marked for the contour area according to the image contained in the contour area where the image position is located;

[0182] If the sampling inspector determines that the land use category corresponding to the image contained in the contour area is not the land use category marked for the contour area, then mark the contour area (this mark can be to mark the text "to be confirmed" within the contour area), or mark the image in a certain sampling box in the sampled inspection map selected for viewing (this mark can be to mark the text "to be confirmed" within the contour area), which is convenient for subsequent search.

[0183] Although the embodiments of the present invention have been shown and described, those of ordinary skill in the art can understand that various changes, modifications, substitutions, and variations can be made to these embodiments without departing from the principles and spirit of the present invention. The scope of the present invention is defined by the claims and their equivalents.

Claims

1. A method for smoothing a slope classification map of land survey, characterized in that: The following steps are involved: S1, obtain the slope classification map of land survey; S2, after obtaining the land survey slope classification map, performing smoothing processing on the obtained land survey slope classification map; S3, displays the processed land survey slope classification map.

2. The method for smoothing the slope classification map of land survey according to claim 1 is characterized in that: The method for performing smoothness processing on the acquired land survey slope classification map in step S2 comprises the following steps: S21, setting the pixel search box size to P×P; S22, determining the position of the land survey slope classification map where the current pixel search frame is located; the pixel coordinates of the center point of the land survey slope classification map where the current pixel search frame is located are recorded as (i, j), and the pixel coordinates of the land survey slope classification map where the current pixel search frame is located are determined as: It can also be written as: The pixel coordinates of the left side of the land survey slope classification map where the current pixel search box is located are determined as follows: It can also be written as: The pixel coordinates of the upper side of the land survey slope classification map where the current pixel search box is located are determined as follows: It can also be written as: The pixel coordinates of the right side of the land survey slope classification map where the current pixel search box is located are determined as follows: It can also be written as: The pixel coordinates of the lower side of the land survey slope classification map where the current pixel search box is located are determined as follows: It can also be written as: S23, obtaining the slope classification value of each pixel coordinate under the current pixel search box; according to all the obtained slope classification values, the number of values ​​of the slope classification values ​​at the left position is counted, and the maximum number is recorded as A Left , A Left It indicates the maximum value after counting the number of values ​​of the slope classification values ​​at the left position; The number of values ​​of the upper slope classification value is counted, and the maximum number is recorded as A Up , A Up It indicates the maximum value after counting the number of values ​​of the slope classification values ​​at the upper side; Count the number of slope classification values ​​at the right position, and record the maximum number as A Right , A Right It indicates the maximum value after counting the number of values ​​of the slope classification values ​​at the right position; Count the number of slope classification values ​​at the left position, and record the maximum number as A. Down , A Down It indicates the maximum value after counting the number of values ​​of the slope classification value at the lower side; S24, A Left , A Up , A Right , A Down The four values ​​are arranged in order from largest to smallest: A max , A max-1 , A max-2 , A max-3 ; Among them, A max Indicates that A Left , A Up , A Right , A Down The first value after these four values ​​are arranged in order from largest to smallest; A max-1 Indicates that A Left , A Up , A Right , A Down The second value after these four values ​​are arranged in order from largest to smallest; A max-2 Indicates that A Left , A Up , A Right , A Down The third value after these four values ​​are arranged in order from largest to smallest; A max-3 Indicates that A Left , A Up , A Right , A Down The fourth value after these four values ​​are arranged in order from largest to smallest; If A max >A max-1 , then the slope classification value of the pixel coordinates of the center point of the location of the land survey slope classification map where the current pixel search box is located is replaced with the slope classification value corresponding to the value in the first place in the statistics; If A max =A max-1 , then proceed to the next step; S25, get A max The corresponding position of the slope classification value and A max-1 The position corresponding to the slope classification value is A max The corresponding position of the slope classification value and A max-1 The positions corresponding to the corresponding slope classification values ​​constitute a position set; If there is a left position in the position set, the slope classification value of the center pixel coordinates of the position of the land survey slope classification map where the current pixel search box is located is replaced with the slope classification value with the largest number of values ​​of the slope classification values ​​of the left position; If there is no left position in the position set, but there is an upper position, then the slope classification value of the pixel point coordinates of the center point of the position of the land survey slope classification map where the current pixel search box is located is replaced with the slope classification value with the largest number of values ​​of the slope classification value of the upper position; If there are right and lower positions in the position set, the slope classification value of the pixel point coordinates of the center point of the position of the land survey slope classification map where the current pixel search box is located is replaced with the slope classification value with the largest number of slope classification values ​​of the right position; S26, the pixel search box executes the next position until the entire land survey slope classification map is traversed.

3. The method for smoothing the slope classification map of land survey according to claim 1, characterized in that: In step S21 , P is an odd number greater than or equal to 3.

4. The method for smoothing the slope classification map of land survey according to claim 1, characterized in that: In step S21, the pixel search box size is 5×5.

5. The method for smoothing the slope classification map of land survey according to claim 1, characterized in that: In step S22, the relationship between P and p is expressed as: Wherein, P represents the number of horizontal / vertical pixels in the pixel search box; Indicates the floor symbol; p represents the number of pixels from the center of the pixel search box to the left bounding box / upper bounding box / right bounding box / lower bounding box.

6. The method for smoothing the slope classification map of land survey according to claim 1, characterized in that: Before step S1, step S0 is also included, using an aerial camera to take a vertical bird's-eye view of the land resources classification, converting the vertical bird's-eye view of the land resources classification into a land survey slope classification map and generating a sampling map.

7. The method for smoothing the slope classification map of land survey according to claim 1, characterized in that: In step S0, the method for generating a sampling map based on a vertical bird's-eye view of land and resources classification includes the following steps: S11, divide the land type contours of the vertical bird's-eye view of the land resources; S12, marking the land and resources categories on the vertical bird's-eye view of the land and resources categories after the land category outlines are divided in step S11; S13, classifying the vertical bird's-eye view of the land resources classification marked in step S12 to generate a sampling map for rapid sampling and verification.

8. The method for smoothing the slope classification map of land survey according to claim 1, characterized in that: In step S11, the land type contour division is performed on the vertical bird's-eye view of the land resources land type by using the brush tool in the Photoshop drawing software.

9. A computer system, characterized in that: include: processor; a memory for storing processor-executable instructions; Wherein, the processor is configured to implement the land survey slope classification map smoothing method as described in one of claims 1 to 8 when executing the executable instructions.

10. A computer-readable storage medium, characterized in that: include: a memory having a computer program stored thereon; A processor is used to execute the program in the memory to implement the land survey slope classification map smoothing method as described in any one of claims 1 to 8.

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