Method and system for calculating number of yaks in alpine meadow based on unmanned aerial vehicle images

Abstract

The invention belongs to but not limited to the technical field of animal husbandry statistics, and particularly relates to an alpine meadow yak number calculation method and system based on an unmanned aerial vehicle image, and the method comprises the steps: S1, employing an unmanned aerial vehicle to shoot an orthoimage of a sample plot, and carrying out the statistics of the yak number; s2, splicing the shot images by using Pix4D software, screening a proper sample plot, and respectively counting the quantity of wet cow dung and the quantity of dry cow dung in a visual interpretation mode; and S3, carrying out linear fitting on the obtained data by using Origin 2024b, so as to obtain three relation curves. According to the method for estimating the number of the yaks through statistics of the number of the cow dung in the unmanned aerial vehicle image, the workload of data collection is greatly reduced, and the limitation that the number of the yaks cannot be obtained when the yaks are not grazed in the grassland is avoided. According to the invention, the data acquisition frequency of experimenters is effectively reduced, and the research cost is reduced.

Description

Technical Field

[0001] The present invention belongs to but is not limited to the field of animal husbandry statistics technology, and in particular relates to a method and system for calculating the number of yaks in an alpine meadow based on drone images. Background Art

[0002] The alpine meadow is one of the main animal husbandry bases in my country, with an area of ​​5.82×10 5 km 2 Therefore, the degradation of alpine meadows will not only affect the output and quality of local animal husbandry, but also affect the ecological security of my country and even Asia. Relevant studies have shown that overgrazing is one of the main factors of grassland degradation. The monitoring and control of grazing intensity can provide basic guarantees for the scientific and rational use of grasslands and the promotion of grassland recovery. The basis for judging grazing intensity is mainly the number of livestock grazing on a unit area of ​​grassland within a certain period of time. At present, the statistics of the number of livestock are mainly through field surveys, so there are many inconveniences. First, due to the grazing system, herders usually graze in several pastures in turn. The number of livestock in winter pastures cannot be collected in summer, and the number of livestock in winter pastures cannot be collected in summer. Second, even on the same type of pasture, it is difficult to accurately count the number of livestock due to the flow of livestock. For example, in the same summer pasture, livestock are also transferred in different grazing units (communities), and the number of livestock without grazing communities is difficult to count. Third, due to the cold climate in pastoral areas, there is more rain and snow in winter and spring, and the roads are difficult to walk, which often affects researchers or managers from going to the field to count the number of livestock. Fourth, even in good weather, cattle and sheep have relatively fixed times to go out of the pen to feed. If the statisticians do not conduct surveys during the feeding period, they cannot obtain the number of livestock. However, scientific research or management personnel are usually busy and cannot stay for a long time, which seriously limits their work progress. Fifth, the terrain of the alpine meadow distribution area is complex, and transportation can only reach a limited range. For example, it is difficult to count the number of livestock behind the mountains that cannot be seen by the naked eye.

[0003] In view of the above analysis, the technical problems that urgently need to be solved in the existing technology are: in scientific research and management work, due to the influence of factors such as grazing system, climatic conditions, grazing time, complex terrain, etc., it is impossible to quickly and accurately obtain information on the number of livestock when counting grassland grazing intensity. Summary of the invention

[0004] In view of the problems existing in the prior art, the present invention provides a method and system for calculating the number of yaks in alpine meadows based on UAV images, which provides new ideas and approaches for dealing with the problem of counting the number of grazing livestock in alpine meadows.

[0005] The present invention is implemented as follows: a method for calculating the number of yaks in alpine meadows based on drone images, comprising:

[0006] S1: Use drones to take orthophotos of the sample plots and count the number of yaks;

[0007] S2: Pix4D software was used to stitch the captured images, select suitable sample plots, and count the number of wet cow dung and dry cow dung by visual interpretation;

[0008] S3: Use Origin2024b to perform linear fitting on the obtained data and obtain three relationship curves.

[0009] Furthermore, the three relationship curves include:

[0010] (1) Relationship between the amount of dry cow dung and the number of yaks:

[0011] y=18.44+1.32*x

[0012] Among them, y is the number of yaks (heads), and x is the number of dry cow dung (piles);

[0013] (2) Relationship between the amount of wet cow dung and the number of yaks:

[0014] y=-18.53+0.85*x

[0015] Among them, y is the number of yaks (heads), and x is the number of wet cow dung (piles);

[0016] (3) Relationship between the total amount of cow dung (wet cow dung + dry cow dung) and the number of yaks:

[0017] y=-4.97+0.53*x

[0018] Among them, y is the number of yaks (heads), and x is the total amount of cow dung (piles).

[0019] Furthermore, in the step S1, the height of the orthophoto image of the sample plot taken by the drone is set between 30 and 50 m to ensure that the resolution of the image is clear enough to be suitable for counting the number of yaks and cow dung.

[0020] Furthermore, when the Pix4D software is used to stitch the images in step S2, a denoising process is further performed on the image data to eliminate interference from other factors.

[0021] Furthermore, the visual interpretation method includes feature extraction and marking of the morphology, color and distribution area of ​​wet cow dung and dry cow dung.

[0022] Furthermore, in step S3, data fitting is performed through Origin2024b, which further includes superimposing the three relationship curves on the sample plot distribution map of the drone image data to intuitively display the distribution of yak numbers.

[0023] Another object of the present invention is to provide a system for calculating the number of yaks in an alpine meadow based on drone images, which implements the method for calculating the number of yaks in an alpine meadow based on drone images, comprising:

[0024] Drone photography module: Use drones to take orthophotos of the sample plots and count the number of yaks;

[0025] Sample site screening module: Pix4D software is used to stitch the captured images, select suitable sample sites, and count the number of wet cow dung and dry cow dung respectively through visual interpretation;

[0026] Relationship curve acquisition module: Use Origin2024b to perform linear fitting on the acquired data to obtain three relationship curves.

[0027] Another object of the present invention is to provide a computer device, which includes a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the processor executes the steps of the method for calculating the number of yaks in the alpine meadow based on drone images.

[0028] Another object of the present invention is to provide a computer-readable storage medium storing a computer program. When the computer program is executed by a processor, the processor executes the steps of the method for calculating the number of yaks in alpine meadows based on drone images.

[0029] Another object of the present invention is to provide an information data processing terminal, which includes the alpine meadow yak number calculation system based on drone images.

[0030] In combination with the above technical solutions and the technical problems solved, the advantages and positive effects of the technical solutions to be protected by the present invention are as follows:

[0031] First, the present invention can obtain the approximate information of the number of yaks grazing in the sample plot, which is of great significance to the livestock statistics problem in the gentle slope (0°~25°) pastures in the alpine pastoral areas.

[0032] (1) Simplify data collection

[0033] Traditional methods mainly involve visiting herders or counting the number of yaks one by one on the spot. However, in actual surveys, researchers often face language barriers with herders, emotional resistance from herders, inability to obtain data when yaks are grazing on the grassland or herders are not there during field surveys, and difficulty in fully counting the number of yaks due to the complex terrain of the alpine pastoral areas. Compared with traditional methods, the method of estimating the number of yaks by counting the number of cow dung in drone images greatly reduces the workload of data collection, avoids many inconveniences in communicating with herders, and the limitation of being unable to obtain the number of yaks when yaks are not grazing on the grassland.

[0034] (2) Provide new ideas for dynamic monitoring

[0035] The traditional method of dynamic monitoring of the number of yaks in pastoral areas requires researchers to collect data regularly, which is time-consuming and laborious. The present invention finds that there is a color difference between wet cow dung and dry cow dung when extracting cow dung information. By counting the number of wet cow dung and dry cow dung respectively, the dynamic change of the number of yaks grazing can be inferred. This method effectively reduces the number of times scientific researchers and managers collect data and reduces costs.

[0036] Second, the technical solution of the present invention fills the technical gap in the industry at home and abroad:

[0037] The present invention aims to infer the number of yaks by the number of cow dung. This method has rarely been reported in literature at home and abroad. It provides a solution when there is a lack of conditions for directly counting the number of yaks in research, and provides new ideas for the innovation and development of similar technologies at home and abroad.

[0038] The technical solution of the present invention solves the technical problem that people have been eager to solve but have never been successful: there are currently two main ways to count the number of yak grazing, one is direct statistics on the spot, and the other is to query relevant data from the local management department. However, in actual research, field statistics are often difficult to achieve due to factors such as weather, topography, grazing system, grazing time, language barriers, etc. The data of the local management department usually comes from the household survey of village-level epidemic prevention personnel and reports step by step, but this process has long been constrained by factors such as institutional reform, personnel changes, and production transformation, and there are problems such as large data uncertainty and lack of effectiveness, which cannot meet the actual needs of scientific researchers and managers, especially scientific research requires the number of livestock in a specific sample plot, and the data of the management department is for the entire herder or a region, which cannot meet the research needs. The proposal of the present invention realizes indirect statistics away from yaks, effectively solves the problem of difficult yak statistics, significantly improves work efficiency, and reduces costs.

[0039] Third, the technical solution of the present invention solves many problems in the prior art regarding the number of yaks in alpine meadows by using drone images and multiple data fusion analysis, which is specifically reflected in the following aspects and achieves significant technical progress:

[0040] 1. Solved the problem of large errors and low efficiency of traditional manual counting: In the alpine meadow area, the traditional method of manually counting the number of yaks is limited by human resources and environmental conditions, with low efficiency and large errors. The present invention greatly improves the accuracy and efficiency of yak counting through drone image acquisition and automated data processing procedures.

[0041] 2. Realized efficient fusion and utilization of different data sources: The present invention adopts UAV images combined with Pix4D stitching technology, Origin2024b data fitting and other data fusion processing technologies to achieve accurate measurement of the number and distribution of yaks under the influence of climate change or vegetation coverage, effectively eliminating the interference factors caused by differences in observation environment in traditional methods.

[0042] 3. Provides accurate quantity statistics and distribution information: Through the identification and visual interpretation of wet and dry cow dung based on drone images, a relationship model with the number of yaks was established in combination with the linear fitting method, which can intuitively display the density information of the yak population distribution. This achievement can not only improve statistical accuracy, but also be applied to the ecological balance analysis and grassland management of alpine meadows.

[0043] 4. Greatly reduced the labor and time costs of data collection: The automation, accuracy and high-resolution images taken by drones reduce the workload of manual interpretation, and the stitching and data processing processes are more efficient, thereby significantly reducing human resource costs and data collection time.

[0044] 5. Strong adaptability and can be applied to gentle slopes under different climates: The method of the present invention can use multi-source data fusion and denoising processing under various climatic conditions, which effectively improves the adaptability and accuracy of the system in complex natural environments. Compared with traditional technical solutions, the present invention has a wider applicability and meets more complex pasture management needs.

[0045] 6. Real-time and visualization of monitoring data is achieved: Through the data fitting and mapping functions of Origin2024b, the distribution of yaks is intuitively presented on the sample distribution map, providing managers with immediately available monitoring data, improving the scientificity and accuracy of management decisions, and providing data support with reference value for industrialization.

[0046] In summary, the present invention has achieved remarkable technical progress in terms of statistical accuracy, time efficiency, applicability and resource conservation, and provides a modern solution for yak population management and ecological protection in alpine meadows. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 is a flow chart of a method for calculating the number of yaks in an alpine meadow based on drone images provided by an embodiment of the present invention;

[0048] Figure 2 is an example diagram of a sample plot provided by an embodiment of the present invention;

[0049] Figure 3 is a curve diagram showing the relationship between the amount of dry cow dung and the number of yaks provided by an embodiment of the present invention;

[0050] Figure 4is a curve diagram showing the relationship between the amount of wet cow dung and the number of yaks provided by an embodiment of the present invention;

[0051] Figure 5 is a curve diagram showing the relationship between the amount of cow dung and the number of yaks provided by an embodiment of the present invention;

[0052] Figure 6 This is a structural diagram of a system for calculating the number of yaks in an alpine meadow based on drone images provided by an embodiment of the present invention;

[0053] Figure 7 Schematic diagram of wet cow dung and dry cow dung provided by an embodiment of the present invention, wherein (a) is wet cow dung, and (b) is dry cow dung. DETAILED DESCRIPTION

[0054] 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 embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0055] like Figure 1 As shown, the method for calculating the number of yaks in the alpine meadow based on drone images provided by the embodiment of the present invention includes:

[0056] S1: Use DJI Mavic 3M drone to take orthophotos of sample plots and count the number of yaks in the upper, middle and lower reaches of the Hargai River Basin in Gangcha County, Haibei Tibetan Autonomous Prefecture, Qinghai Province, and Henan County, Huangnan Tibetan Autonomous Prefecture. Figure 2 As shown, the sample plots are all 50m×50m in area and have a gentle slope with a slope of 0° to 25°. The specific shooting parameters are: height 30m, route speed 2.36m / s, lateral overlap rate 70%, and heading overlap rate 80%.

[0057] S2: Pix4D software was used to stitch the captured images, select suitable sample plots, and count the number of wet cow dung and dry cow dung respectively through visual interpretation.

[0058] Table 1 Number of cow dung and yaks in the sample plot

[0059]

[0060]

[0061] S3: Use Origin2024b to perform linear fitting on the obtained data and obtain three relationship curves:

[0062] (1) Figure 3 As shown in Figure 2, the relationship between the amount of dry cow dung and the number of yaks

[0063] y=18.44+1.32*x

[0064] Among them, y is the number of yaks (heads), and x is the number of dry cow dung (piles).

[0065] (2) Figure 4 As shown in Figure 2, the relationship between the amount of wet cow dung and the number of yaks

[0066] y=-18.53+0.85*x

[0067] Among them, y is the number of yaks (heads), and x is the number of wet cow dung (piles).

[0068] (3) Figure 5 As shown in the figure, the relationship between the total amount of cow dung (dry cow dung + wet cow dung) and the number of yaks

[0069] y=-4.97+0.53*x

[0070] Among them, y is the number of yaks (heads), and x is the total amount of cow dung (piles).

[0071] The embodiment of the present invention provides a method for calculating the number of yaks in an alpine meadow based on drone images. By collecting drone images and processing data, an accurate estimation of the number of yaks is achieved. The method is divided into the following steps:

[0072] 1. Sample plot image acquisition (step S1): Use a drone to collect sample plot images in the alpine meadow area. The flight altitude of the drone is set between 30 and 50 meters to ensure that the image resolution is clear enough to accurately identify the amount of cow dung in the sample plot. This height setting not only avoids the limitation of the shooting area due to the low altitude, but also ensures that the image resolution can meet the subsequent image processing requirements.

[0073] 2. Image stitching and processing (step S2): After shooting, the image data is imported into Pix4D software for stitching to form a complete orthophoto of the sample site. During the stitching process, the image is denoised to eliminate interference from other factors (such as other animals, vegetation, etc.). The application of denoising improves the accuracy of cow dung quantity identification, ensuring that only cow dung targets can be accurately marked and counted.

[0074] 3. Visual interpretation and marking: In the spliced ​​orthophotos, cow dung and related traces are analyzed in combination with the interpretation standards. Visual interpretation refers to the manual identification of cow dung traces in the image, including the statistics of wet and dry cow dung. Wet cow dung and dry cow dung have significant differences in morphology, color and distribution area. With these differential features, operators can extract and mark the distribution location and quantity of wet cow dung and dry cow dung in the image.

[0075] 4. Data analysis and fitting (step S3): All collected data, including the number of yaks, wet cow dung, and dry cow dung, will be imported into the data analysis software Origin2024b, and the relationship curve between the number of yaks and the number of traces will be established through the linear fitting analysis method. Specifically, three relationship curves are fitted through the corresponding relationship between the number of wet cow dung, the number of dry cow dung, and the number of yaks. These relationship curves can predict and estimate the actual number of yaks to a certain extent.

[0076] 5. Multi-curve overlay analysis: The three fitted relationship curves were overlaid on the plot distribution map of the drone image data through Origin2024b software to form an intuitive cow dung quantity distribution map. This distribution map can intuitively show the distribution density of cow dung quantity at different locations in the plot. After processing the cow dung data, detailed distribution information is provided for the grazing management of yaks in alpine meadows.

[0077] 6. Application and analysis of results: Through the collaborative analysis method of image processing and data fitting, the method of the present invention can significantly improve the calculation accuracy of the number of yaks and overcome the shortcomings of inaccurate traditional manual estimation. In addition, through the combination of multi-source data, this method provides scientific yak population estimation data for subsequent grazing management, meadow environmental protection and other applications.

[0078] like Figure 6 As shown, the alpine meadow yak number calculation system based on drone images provided by the embodiment of the present invention includes:

[0079] Drone photography module: Use drones to take orthophotos of the sample plots and count the number of yaks;

[0080] Sample site screening module: Pix4D software is used to stitch the captured images, select suitable sample sites, and count the number of wet cow dung and dry cow dung respectively through visual interpretation;

[0081] Relationship curve acquisition module: Use Origin2024b to perform linear fitting on the acquired data to obtain three relationship curves.

[0082] The present invention can obtain the approximate information of the number of yaks grazing in the sample plot, which is of great significance to the livestock statistics problem in the gentle slope (0°-25°) pastures in the alpine pastoral areas.

[0083] (1) Simplify data collection

[0084] Traditional methods mainly rely on visiting herders or counting the number of yaks one by one on the spot. However, in actual surveys, researchers often face language barriers with herders, emotional resistance from herders, and the inability to obtain data due to the yaks not grazing on the grassland or the herders not being there during field surveys. In addition, the complex terrain of the alpine pastoral area makes it difficult to fully count the number of yaks. Compared with traditional methods, the method of estimating the number of yaks by counting the number of cow dung in drone images greatly reduces the workload of data collection, avoids many inconveniences in communicating with herders, and the limitation of not being able to obtain the number of yaks when the yaks are not grazing on the grassland.

[0085] (2) Provide new ideas for dynamic monitoring

[0086] Traditional methods of monitoring the dynamics of yak population in pastoral areas require experimenters to collect data regularly, which is time-consuming and laborious. Figure 7 As shown, the present invention finds that there is a color difference between wet cow dung and dry cow dung when extracting cow dung information. By counting the number of wet cow dung and dry cow dung respectively, the dynamic changes in the number of yak grazing can be inferred. This method effectively reduces the number of times experimenters collect data and reduces research costs.

[0087] An application embodiment of the present invention provides a computer device, which includes a memory and a processor. The memory stores a computer program. When the computer program is executed by the processor, the processor executes the steps of a method for calculating the number of yaks in an alpine meadow based on drone images.

[0088] An application embodiment of the present invention provides a computer-readable storage medium storing a computer program. When the computer program is executed by a processor, the processor executes the steps of a method for calculating the number of yaks in an alpine meadow based on drone images.

[0089] An application embodiment of the present invention provides an information data processing terminal, which includes a system for calculating the number of yaks in an alpine meadow based on drone images.

[0090] The invention is mainly used in the fields of alpine meadow investigation, grassland management, ecological restoration, grazing intensity research, etc.

[0091] Table 2 Relationship curve fitting analysis

[0092]

[0093] It can be seen from Table 2 that the three fitting curves are highly correlated with the data, among which dry cow dung can explain more than 95% of the data variation.

[0094] It should be noted that the embodiments of the present invention can be implemented by hardware, software, or a combination of software and hardware. The hardware part can be implemented using dedicated logic; the software part can be stored in a memory and executed by an appropriate instruction execution system, such as a microprocessor or dedicated design hardware. It can be understood by a person of ordinary skill in the art that the above-mentioned devices and methods can be implemented using computer executable instructions and / or contained in a processor control code, such as a carrier medium such as a disk, CD or DVD-ROM, a programmable memory such as a read-only memory (firmware), or a data carrier such as an optical or electronic signal carrier. Such code is provided on the carrier medium. The device and its modules of the present invention can be implemented by hardware circuits such as very large-scale integrated circuits or gate arrays, semiconductors such as logic chips, transistors, etc., or programmable hardware devices such as field programmable gate arrays, programmable logic devices, etc., can also be implemented by software executed by various types of processors, and can also be implemented by a combination of the above-mentioned hardware circuits and software, such as firmware.

[0095] The above description is only a specific implementation mode of the present invention, but the protection scope of the present invention is not limited thereto. Any modifications, equivalent substitutions and improvements made by any technician familiar with the technical field within the technical scope disclosed by the present invention and within the spirit and principle of the present invention should be covered by the protection scope of the present invention.

Claims

1. A method for calculating the number of yaks in alpine meadows based on drone images, characterized in that: include: S1: Use drones to take orthophotos of the sample plots and count the number of yaks; S2: Pix4D software was used to stitch the captured images, select suitable sample plots, and count the number of wet cow dung and dry cow dung by visual interpretation; S3: Use Origin2024b to perform linear fitting on the obtained data and obtain three relationship curves.

2. The method for calculating the number of yaks in alpine meadows based on drone images according to claim 1, characterized in that: In the step S1, the height of the orthophoto image of the sample plot taken by the drone is set between 30 and 50 meters to ensure that the resolution of the image is clear enough to be suitable for counting the number of yaks and cow dung.

3. The method for calculating the number of yaks in alpine meadows based on drone images according to claim 1, characterized in that: When stitching images using Pix4D software in step S2, denoising of the image data is performed to eliminate interference from non-yak targets.

4. The method for calculating the number of yaks in alpine meadows based on drone images as claimed in claim 2, characterized in that: The visual interpretation method includes feature extraction and marking of the shape, color and distribution area of ​​wet cow dung and dry cow dung.

5. The method for calculating the number of yaks in alpine meadows based on drone images according to any one of claims 1 to 3, characterized in that: In step S3, data fitting is performed using Origin2024b, including superimposing the three relationship curves on the sample plot distribution map of the drone image data to intuitively display the distribution of yaks.

6. The method for calculating the number of yaks in alpine meadows based on drone images according to claim 1, characterized in that: The three relationship curves include: (1) Relationship between the amount of dry cow dung and the number of yaks: y=18.44+1.32*x Among them, y is the number of yaks (heads), and x is the number of dry cow dung (piles); (2) Relationship between the amount of wet cow dung and the number of yaks: y=-18.53+0.85*x Among them, y is the number of yaks (heads), and x is the number of wet cow dung (piles); (3) Relationship between the total amount of cow dung (dry cow dung + wet cow dung) and the number of yaks: y=-4.97+0.53*x Among them, y is the number of yaks (heads), and x is the total amount of cow dung (piles).

7. A system for calculating the number of yaks in alpine meadows based on drone images, which implements the method for calculating the number of yaks in alpine meadows based on drone images as claimed in any one of claims 1 to 2, characterized in that: include: Drone photography module: Use drones to take orthophotos of the sample plots and count the number of yaks; Sample site screening module: Pix4D software is used to stitch the captured images, select suitable sample sites, and count the number of wet cow dung and dry cow dung respectively through visual interpretation; Relationship curve acquisition module: Use Origin2024b to perform linear fitting on the acquired data to obtain three relationship curves.

8. A computer device, comprising a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the processor executes the steps of the method for calculating the number of yaks in the alpine meadow based on drone images as described in any one of claims 1 to 2.

9. A computer-readable storage medium storing a computer program. When the computer program is executed by a processor, the processor executes the steps of the method for calculating the number of yaks in an alpine meadow based on drone images as described in any one of claims 1 to 2.

10. An information data processing terminal, comprising the alpine meadow yak number calculation system based on drone images as claimed in claim 3.

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