Vegetation coverage instrument calibration method and device

Abstract

The invention relates to the technical field of botanical and ecological measurement, and discloses a vegetation coverage instrument calibration method and device, and the method comprises the steps: determining the position and area of a sample plot which actually needs to be shot, carrying out the photographing of the sample plot, obtaining a sample plot picture, carrying out the preprocessing of the sample plot picture, obtaining a processed picture, and carrying out the calibration of a vegetation coverage instrument. Selecting several main vegetation colors in the processed photo as vegetation pixel colors and several main soil colors as soil pixel colors, setting a display screen, and filling the display screen based on the selected vegetation pixel colors and soil pixel colors to form a training combination of the vegetation area proportion of the current color; and obtaining a standardized vegetation map of the current color vegetation area proportion, carrying out similarity comparison on the standardized vegetation map and the training combination to obtain a comparison difference value, and calibrating the vegetation coverage instrument based on the difference value. According to the invention, the problems of lack of measurement standards, large data deviation, strong subjectivity of measurement results and the like of an existing vegetation coverage instrument can be solved.

Description

Technical Field

[0001] The present invention relates to the field of botanical and ecological measurement technology, and in particular to a vegetation cover meter calibration method and device. Background Art

[0002] Vegetation cover is an important indicator for measuring the health of ecosystems and the extent of soil erosion. Its changes are of great significance to ecological protection, rational resource development, land pattern optimization, and sustainable development. Traditional methods for measuring vegetation cover are relatively extensive, usually relying on visual estimation or simple image segmentation techniques, which are subject to considerable subjectivity and uncertainty. With advances in measurement technology, various types of vegetation cover meters have emerged on the market, mainly using image analysis algorithms to quantitatively assess vegetation. However, the lack of unified production standards and calibration methods for existing vegetation cover instruments leads to large differences in measurement results between brands and models. Especially in the field of soil and water conservation, the consistency and accuracy of vegetation cover monitoring data are difficult to effectively control, which has an adverse impact on ecological research and governance decision-making.

[0003] Therefore, developing a standardized calibration method for different vegetation cover meters can not only eliminate data deviations between different instruments, but also provide a scientific measurement basis for the industry and promote the standardization and refinement of vegetation cover measurement work. Summary of the Invention

[0004] The object of the present invention is to overcome one or more of the above-mentioned existing technical problems and provide a vegetation cover meter calibration method.

[0005] To achieve the above object, the present invention provides a vegetation cover meter calibration method, comprising: Determine the location and area of ​​the sample plots that need to be photographed, and take photos of the sample plots; Preprocessing the sample plot photos to obtain processed photos; Select the main vegetation colors in the processed photo as vegetation pixel colors, and the main soil colors as soil pixel colors; Setting a display screen, filling the display screen based on the selected vegetation pixel color and soil pixel color, to form a training combination of the current color vegetation area ratio, wherein the coverage of the foreground color to the background color in the display screen in the training combination is different; Obtain the standardized vegetation map of the current color vegetation area ratio and compare it with the training combination for similarity, obtain the difference between the comparisons, and calibrate the vegetation cover meter based on the difference.

[0006] According to one aspect of the present invention, the method for obtaining the processed photo is: Normalize the sample site photos to obtain image data based on RGB space; Filter the characteristic pixel rows of the image data, grayscale the image data, binarize the grayscale image data, and initially segment the pixels into vegetation and soil; Count the number of green plant pixels in each row of the grayscale image data, select a suitable pixel row with the largest percentage of green plant pixels but less than 100%, find the first pixel point from left to right in this pixel row, and use the R channel data, G channel data, or B channel data from the first pixel point to the right edge of the green leaf in this row; Starting from the starting point of the intercepted channel data, the data is divided into two groups as the dividing point. If the values ​​at the dividing point are all greater than the first group and smaller than the second group, this point is selected as the threshold; The determined threshold value is used to form a mask map for the image data, and the mask map and the sample site photo are converted into RGB format to complete the segmentation of vegetation and soil.

[0007] According to one aspect of the present invention, the method for forming a training combination of the current color vegetation area ratio is: Set up a display screen, divide the display screen into two or more even-numbered areas of the same shape and area, and divide the areas into two groups of equal number; randomly distributing the selected vegetation pixel colors to the various regions of the first group, and randomly distributing the selected soil pixel colors to the various regions of the second group; An area of ​​the first group is randomly selected as the foreground color of the display screen, and an area of ​​the second group is randomly selected as the background color of the display screen to form a training combination of the current color vegetation area ratio.

[0008] According to one aspect of the present invention, a method for obtaining a standardized vegetation map of the current color vegetation area ratio is as follows: Generate a×a resolution height map, and take the middle height h0 in the height map according to the vegetation area ratio n input by the user; Determine the number of pixels greater than the middle height k0 / (a×a) and compare it with n. If it is greater than n, take h0 to h max The middle height h1 in the image is used to determine the number of pixels k1 / (a×a) greater than h1 and compare it with n. Otherwise, take h min Compare the number of pixels k2 / (a×a) greater than the middle height h2 in h0 with n; Repeat the above process to calculate the positions of pixels that meet the vegetation area ratio, add vegetation area colors to these positions, and add non-vegetation area colors to other positions to obtain a standardized vegetation map with the current color vegetation area ratio.

[0009] According to one aspect of the present invention, a cluster analysis method is used to screen vegetation color and soil color.

[0010] According to one aspect of the present invention, at least two main vegetation colors and at least two main soil colors are selected.

[0011] To achieve the above object, the present invention provides a vegetation cover meter calibration device, comprising: Display screen; A slide rail perpendicular to the direction of the display screen is provided below the display screen and opposite to the display screen; A slide seat is provided on the slide rail, and the slide seat can slide back and forth along the slide rail; A fixed bracket is provided above the slide, and a vegetation coverage meter to be calibrated is set on the fixed bracket, with the center of the lens of the vegetation coverage meter facing the center of the display screen; Calibrate the parameters of the vegetation coverage meter and adjust the position of the slide on the slide rail according to the focal length of the vegetation coverage meter.

[0012] According to one aspect of the present invention, a horizontally rotating lead screw is provided on the slide rail; Install a handwheel at the end of the screw; The lead screw is connected to the slide seat by threads. When the hand wheel is rotated to drive the lead screw to rotate, the slide seat is controlled to adjust the distance between the vegetation cover meter and the display screen.

[0013] According to one aspect of the present invention, the fixed bracket includes a bottom frame and a top frame; The bottom frame is fixed on the slide, and the top frame is set on the vegetation cover meter; The bottom frame and the top frame are rotatably connected, and a bolt is provided at the bottom end of the top frame, and the bolt is located below the rotation position of the two; The bottom frame is provided with arc-shaped strip holes for the bolts to slide through, and when the bolts are tightened, the bottom frame 31 and the top frame are fixed, thereby achieving the adjustment of the inclination angle of the vegetation coverage meter.

[0014] According to one aspect of the present invention, a level is further included, and the level is respectively arranged on the slide seat, the slide rail and the display screen.

[0015] Based on this, the present invention has the beneficial effect of simulating different vegetation cover conditions, achieving precise calibration of various vegetation coverage meters, and eliminating measurement discrepancies between instruments of different brands and models. This method not only improves the accuracy and consistency of vegetation coverage meter measurement results, but also provides reliable data for vegetation coverage monitoring in soil and water conservation, ecological protection, and resource development, helping to promote the standardization, scientificization, and refinement of measurement work in this field. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 is a flow chart of a vegetation cover meter calibration method according to an exemplary embodiment; Figure 2 is a schematic diagram of a vegetation cover meter calibration device according to an exemplary embodiment; Figure 3 The figure is a schematic diagram of a fixing bracket of a vegetation cover meter calibration device according to an exemplary embodiment.

[0017] Figure numerals: 1, slide rail; 2, slide seat; 3, fixed bracket; 31, base frame; 32, top frame; 33, bolt; 34, strip hole; 4, screw; 5, handwheel; 6, level. DETAILED DESCRIPTION

[0018] The present invention will now be discussed with reference to exemplary embodiments. It should be understood that the embodiments discussed are only for enabling those skilled in the art to better understand and thereby implement the present invention, rather than implying any limitation on the scope of the present invention.

[0019] As used herein, the term “including” and variations thereof are to be interpreted as open-ended terms meaning “including, but not limited to.” The term “based on” is to be interpreted as “based, at least in part, on,” and the terms “one embodiment” and “an embodiment” are to be interpreted as “at least one embodiment.”

[0020] According to one embodiment of the present invention, Figure 1 FIG. 1 is a flow chart of a vegetation coverage meter calibration method according to an exemplary embodiment. Figure 1 To achieve the above-mentioned purpose, the present invention provides a vegetation cover meter calibration method, comprising: Determine the location and area of ​​the sample plots that need to be photographed, and take photos of the sample plots; Preprocessing the sample plot photos to obtain processed photos; Select the main vegetation colors in the processed photo as vegetation pixel colors, and the main soil colors as soil pixel colors; Setting a display screen, filling the display screen based on the selected vegetation pixel color and soil pixel color, to form a training combination of the current color vegetation area ratio, wherein the coverage of the foreground color to the background color in the display screen in the training combination is different; Obtain the standardized vegetation map of the current color vegetation area ratio and compare it with the training combination for similarity, obtain the difference between the comparisons, and calibrate the vegetation cover meter based on the difference.

[0021] According to one embodiment of the present invention, the method for obtaining the processed photo is: Normalize the sample site photos to obtain image data based on RGB space; Filter the characteristic pixel rows of the image data, grayscale the image data, binarize the grayscale image data, and initially segment the pixels into vegetation and soil; Count the number of green plant pixels in each row of the grayscale image data, select a suitable pixel row with the largest percentage of green plant pixels but less than 100%, find the first pixel point from left to right in this pixel row, and use the R channel data, G channel data, or B channel data from the first pixel point to the right edge of the green leaf in this row; Starting from the starting point of the intercepted channel data, the data is divided into two groups as the dividing point. If the values ​​at the dividing point are all greater than the first group and smaller than the second group, this point is selected as the threshold; The determined threshold value is used to form a mask map for the image data, and the mask map and the sample site photo are converted into RGB format to complete the segmentation of vegetation and soil.

[0022] According to one embodiment of the present invention, the method for forming a training combination of the current color vegetation area ratio is: Set up a display screen, divide the display screen into two or more even-numbered areas of the same shape and area, and divide the areas into two groups of equal number; randomly distributing the selected vegetation pixel colors to the various regions of the first group, and randomly distributing the selected soil pixel colors to the various regions of the second group; An area of ​​the first group is randomly selected as the foreground color of the display screen, and an area of ​​the second group is randomly selected as the background color of the display screen to form a training combination of the current color vegetation area ratio.

[0023] According to one embodiment of the present invention, a method for obtaining a standardized vegetation map of the current color vegetation area ratio is as follows: Generate a×a resolution height map, and take the middle height h0 in the height map according to the vegetation area ratio n input by the user; Determine the number of pixels greater than the middle height k0 / (a×a) and compare it with n. If it is greater than n, take h0 to h max The middle height h1 in the image is used to determine the number of pixels k1 / (a×a) greater than h1 and compare it with n. Otherwise, take h min Compare the number of pixels k2 / (a×a) greater than the middle height h2 in h0 with n; Repeat the above process to calculate the positions of pixels that meet the vegetation area ratio, add vegetation area colors to these positions, and add non-vegetation area colors to other positions to obtain a standardized vegetation map with the current color vegetation area ratio.

[0024] According to one embodiment of the present invention, a cluster analysis method is used to screen vegetation color and soil color.

[0025] According to one embodiment of the present invention, at least two main vegetation colors and at least two main soil colors are selected.

[0026] According to one embodiment of the present invention, the sample plot photos are manually taken, photos taken by drones, or satellite aerial photos.

[0027] According to one embodiment of the present invention, a dataset of images of different vegetation and soil types is established, and cluster centers and boundaries of the dataset are determined. The RGB color values ​​in the dataset are averaged to obtain the cluster centers. The RGB color values ​​in the dataset are subtracted from the cluster centers to obtain a difference matrix. Cluster boundaries are then determined based on the cluster centers using a preset threshold factor, where the threshold factor ranges from 0.9 to 1.1. Perform RGB color clustering analysis on the segmented RGB images of vegetation and soil according to the cluster centers and boundaries of different vegetation and soil image datasets, calculate the minimum distance between the RGB color value of each pixel in the RGB image of vegetation and soil and the elements in the boundaries of different vegetation and soil image datasets, and obtain the minimum distance set; Determine the pixel point of the segmented vegetation and soil RGB image that is closest to the element in the cluster boundary and corresponds to the minimum value in the minimum distance set, and determine whether its modulus is less than the threshold. If it is less than the threshold, the type of vegetation and soil can be determined; Pixel points are calculated based on the known vegetation and soil types. The color of the vegetation type with an area greater than the preset threshold is selected as the vegetation pixel color, and the color of the soil type with an area greater than the preset threshold is selected as the soil pixel color. If the area is not greater than the preset threshold, this color is discarded.

[0028] According to one embodiment of the present invention, in this embodiment, the display screen is divided into four identical rectangular areas to obtain a first area, a second area, a third area and a fourth area. The display screen is divided into four identical areas, and vegetation pixel colors or soil pixel colors with an area greater than a preset threshold are randomly selected in equal amounts. The ideal state is that there are two vegetation pixel colors or two soil pixel colors. The selected content is the pixel color ranked at the top in terms of area. The selected vegetation pixel colors are randomly distributed in the first area or the second area, and the selected soil pixel colors are randomly distributed in the third area or the fourth area. One of the areas, namely the first area or the second area, is selected as the foreground color of the display screen, and one of the areas, namely the third area or the fourth area, is selected as the background color of the display screen. When the pixel color is determined, there are four randomly selected training sets. If there are three selectable vegetation pixel colors and two selectable soil pixel colors, there are 6 randomly selected training sets.

[0029] According to one embodiment of the present invention, the coverage of the foreground color of the display screen to the background color is adjusted to one of the values ​​between 0-100%, and this value is not limited to an integer. The resolution of the display screen can be adjusted, and during calibration, the resolution of the display screen is consistent with the resolution of the vegetation coverage meter. Therefore, the present application may not be limited to a single type of vegetation coverage meter.

[0030] Furthermore, in order to achieve the above-mentioned purpose, the present invention also provides a vegetation coverage meter calibration device. Figure 2 is a schematic diagram of a vegetation coverage meter calibration device according to an exemplary embodiment. Figure 3 FIG. 1 is a schematic diagram of a fixing bracket of a vegetation cover meter calibration device according to an exemplary embodiment. Figure 2 and Figure 3 As shown, a vegetation cover meter calibration device in the present invention includes: A slide rail 1 perpendicular to the display screen is provided below and opposite the display screen. A slide seat 2 is provided on the slide rail 1. The slide seat 2 can slide back and forth along the slide rail 1. A fixed bracket 3 is provided above the slide seat 2. A vegetation coverage meter to be calibrated is provided on the fixed bracket 3, with the lens center of the vegetation coverage meter facing the center of the display screen. A horizontally rotating screw 4 is provided on the slide rail 1, and a hand wheel 5 is installed at the tail end of the screw 4. The screw 4 is threadedly connected to the slide 2. When the hand wheel 5 is rotated to drive the screw 4 to rotate, the sliding control of the slide 2 is realized, and the distance between the vegetation cover meter and the display screen is adjusted; The fixing bracket 3 includes a bottom frame 31 and a top frame 32. The bottom frame 31 is fixed to the slide 2, and the top frame 32 is arranged on the vegetation cover meter. The bottom frame 31 and the top frame 32 are rotatably connected. A bolt 33 is provided at the bottom end of the top frame 32. The bolt 33 is located below the rotation position of the two. The bottom frame 31 is provided with an arc-shaped strip hole 34 for the bolt 33 to slide. When the bolt 33 is tightened, the bottom frame 31 and the top frame 32 are fixed, thereby realizing the adjustment of the inclination angle of the vegetation cover meter to meet different usage requirements. Calibrate the parameters of the vegetation coverage meter and adjust the position of the slide 2 on the slide rail 1 according to the focal length of the vegetation coverage meter.

[0031] The level 6 is respectively arranged on the slide 2, the slide rail 1 and the display screen, so that the entire device is at the same level.

[0032] Those skilled in the art will appreciate that the modules and algorithm steps described in conjunction with the embodiments disclosed herein can be implemented using electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professionals and technicians may use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the present invention.

[0033] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the above-described devices and equipment can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0034] In the embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are merely schematic. For example, the division of the modules is merely a logical function division. In actual implementation, there may be other division methods, such as multiple modules or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or modules, which can be electrical, mechanical or other forms.

[0035] The modules described as separate components may or may not be physically separate, and the components shown as modules may or may not be physical modules, that is, they may be located in one place or distributed across multiple network modules. Some or all of these modules may be selected according to actual needs to achieve the objectives of the embodiments of the present invention.

[0036] In addition, each functional module in the embodiment of the present invention may be integrated into one processing module, or each module may exist physically separately, or two or more modules may be integrated into one module.

[0037] If the functions are implemented as software modules and sold or used as standalone products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the portion that contributes to the prior art, or the portion of the technical solution itself, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the energy-saving signal transmission / reception method according to various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as a USB flash drive, a mobile hard drive, ROM, RAM, a magnetic disk, or an optical disk.

[0038] The above description is merely a preferred embodiment of the present application and an illustration of the technical principles employed. Those skilled in the art should understand that the scope of the invention herein is not limited to the technical solutions formed by the specific combination of the above-mentioned technical features, but also encompasses other technical solutions formed by any combination of the above-mentioned technical features or their equivalents without departing from the inventive concept. For example, a technical solution formed by replacing the above-mentioned features with (but not limited to) technical features having similar functions disclosed in this application.

[0039] It should be understood that the size of the serial numbers of each step in the content of the invention and the embodiments of the present invention does not absolutely mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

Claims

1. A vegetation cover meter calibration method, characterized in that: include: Determine the location and area of ​​the sample plots that need to be photographed, and take photos of the sample plots; Preprocessing the sample plot photos to obtain processed photos; Select the main vegetation colors in the processed photo as vegetation pixel colors, and the main soil colors as soil pixel colors; Setting a display screen, filling the display screen based on the selected vegetation pixel color and soil pixel color, to form a training combination of the current color vegetation area ratio, wherein the coverage of the foreground color to the background color in the display screen in the training combination is different; Obtain the standardized vegetation map of the current color vegetation area ratio and compare it with the training combination for similarity, obtain the difference between the comparisons, and calibrate the vegetation cover meter based on the difference.

2. A vegetation coverage meter calibration method according to claim 1, characterized in that: The method for obtaining the processed photo is: Normalize the sample site photos to obtain image data based on RGB space; Filter the characteristic pixel rows of the image data, grayscale the image data, binarize the grayscale image data, and initially segment the pixels into vegetation and soil; Count the number of green plant pixels in each row of the grayscale image data, select a suitable pixel row with the largest percentage of green plant pixels but less than 100%, find the first pixel point from left to right in this pixel row, and use the R channel data, G channel data, or B channel data from the first pixel point to the right edge of the green leaf in this row; Starting from the starting point of the intercepted channel data, the data is divided into two groups as the dividing point. If the values ​​at the dividing point are all greater than the first group and smaller than the second group, this point is selected as the threshold; The determined threshold value is used to form a mask map for the image data, and the mask map and the sample site photo are converted into RGB format to complete the segmentation of vegetation and soil.

3. A vegetation coverage meter calibration method according to claim 2, characterized in that: The method for forming the training combination of the current color vegetation area ratio is: Set up a display screen, divide the display screen into two or more even-numbered areas of the same shape and area, and divide the areas into two groups of equal number; randomly distributing the selected vegetation pixel colors to the various regions of the first group, and randomly distributing the selected soil pixel colors to the various regions of the second group; An area of ​​the first group is randomly selected as the foreground color of the display screen, and an area of ​​the second group is randomly selected as the background color of the display screen to form a training combination of the current color vegetation area ratio.

4. A vegetation coverage meter calibration method according to claim 3, characterized in that: The method to obtain the standardized vegetation map of the current color vegetation area ratio is: Generate a×a resolution height map, and take the middle height h0 in the height map according to the vegetation area ratio n input by the user; Determine the number of pixels greater than the middle height k0 / (a×a) and compare it with n. If it is greater than n, take h0 to h max The middle height h1 in the image is used to determine the number of pixels k1 / (a×a) greater than h1 and compare it with n. Otherwise, take h min Compare the number of pixels k2 / (a×a) greater than the middle height h2 in h0 with n; Repeat the above process to calculate the positions of pixels that meet the vegetation area ratio, add vegetation area colors to these positions, and add non-vegetation area colors to other positions to obtain a standardized vegetation map with the current color vegetation area ratio.

5. A vegetation coverage meter calibration method according to claim 4, characterized in that: Cluster analysis method was used to screen vegetation color and soil color.

6. A vegetation coverage meter calibration method according to claim 5, characterized in that: Select at least 2 main vegetation colors and at least 2 main soil colors.

7. A vegetation cover meter calibration device applied to a vegetation cover meter calibration method according to claims 1-6, characterized in that: Display screen; A slide rail perpendicular to the direction of the display screen is provided below the display screen and opposite to the display screen; A slide seat is provided on the slide rail, and the slide seat can slide back and forth along the slide rail; A fixed bracket is provided above the slide, and a vegetation coverage meter to be calibrated is set on the fixed bracket, with the center of the lens of the vegetation coverage meter facing the center of the display screen; Calibrate the parameters of the vegetation coverage meter and adjust the position of the slide on the slide rail according to the focal length of the vegetation coverage meter.

8. A vegetation coverage meter calibration device according to claim 7, characterized in that: A horizontally rotating lead screw is arranged on the slide rail; Install a handwheel at the end of the screw; The lead screw is connected to the slide seat by threads. When the hand wheel is rotated to drive the lead screw to rotate, the slide seat is controlled to adjust the distance between the vegetation cover meter and the display screen.

9. A vegetation coverage meter calibration device according to claim 8, characterized in that: The fixed bracket includes a bottom frame and a top frame; The bottom frame is fixed on the slide, and the top frame is set on the vegetation cover meter; The bottom frame and the top frame are rotatably connected, and a bolt is provided at the bottom end of the top frame, and the bolt is located below the rotation position of the two; The bottom frame is provided with arc-shaped strip holes for the bolts to slide through, and when the bolts are tightened, the bottom frame 31 and the top frame are fixed, thereby achieving the adjustment of the inclination angle of the vegetation coverage meter.

10. A vegetation coverage meter calibration device according to claim 7, characterized in that: The utility model also comprises a level meter, which is respectively arranged on the slide seat, the slide rail and the display screen.

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