Grassland multi-region rotation grazing management optimization method and system based on GIS

Abstract

The invention relates to the technical field of path optimization, in particular to a grassland multi-region rotation grazing management optimization method and system based on a GIS (Geographic Information System). According to the method, firstly, the position relation between an unpainted grassland area and an obstacle area is considered, and a minimum obstacle encirclement circle of the unpainted grassland area is made; and the initial grazing optimization degree of each non-grazing grassland area is quantified, and the grazing optimization degree can be obtained by further combining the grazing amount so as to be used for path planning of a single sheep flock. The grazing road strength of different sheep flocks is combined, and the optimal path combination mode can be screened out by analyzing the coincidence degree in each path combination mode and the appropriate grazing degree of the end point non-grazing grassland area. According to the method, the optimal path combination mode is determined through position analysis, path planning and path combination analysis, it can be guaranteed that the coincidence degree of the grazing paths of multiple sheep flocks is small, normal grazing of the sheep flocks can be guaranteed in the non-grazing grassland area of the path end point, and the grazing efficiency is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of path optimization, and in particular to a GIS-based grassland multi-region rotational grazing management optimization method and system. Background Art

[0002] To scientifically manage sheep, there are currently clear regulations and systems for grazing pastures, such as rest periods, to ensure the ecological recovery of pastures. This rest period allows sheep to rotate grazing across different pastures, improving the ecological potential of the pastures while ensuring high-quality forage intake.

[0003] To ensure grazing efficiency, existing technologies utilize path optimization algorithms to plan a route based on the flock's initial distance and pasture location. This ensures that the planned route can quickly reach the destination pasture while avoiding obstacles. However, path planning also requires consideration of the distribution of adjacent areas to the target pasture. If adjacent areas form a significant barrier around the target pasture, sheep may be unable to access optimal pastures in a timely manner, impacting grazing efficiency. Furthermore, for multiple flocks, continuous trampling of the same area by other flocks is not considered, which can affect pasture ecological recovery and further impact grazing efficiency. Summary of the Invention

[0004] In order to solve the technical problem that the existing technology does not consider the path planning of non-grazing grassland areas sufficiently, which affects grazing efficiency, the purpose of the present invention is to provide a GIS-based grassland multi-region rotational grazing management optimization method and system. The technical solutions adopted are as follows: The present invention proposes a GIS-based grassland multi-region rotational grazing management optimization method, which includes: Obtaining a grassland information map based on a GIS system, wherein the grassland information map includes obstacle areas and grassland areas; the grassland areas include non-grazing grassland areas and grazing grassland areas; Based on the positional relationship between the locations of the ungrazed grassland areas and the obstacle areas, a minimum obstacle encirclement formed by each ungrazed grassland area is constructed on the grassland information map; based on the size of the minimum obstacle encirclement and the grazing time of the grazing grassland areas on the minimum obstacle encirclement, the initial grazing preference of each ungrazed grassland area is obtained, and combined with the amount of grass in each ungrazed grassland area, the grazing preference of each ungrazed grassland area is obtained; Determining multiple grazing paths for a single flock of sheep based on the grazing preference; obtaining a grazing suitability for each grazing path based on the path length between an initial area and an ungrazed grassland area at the end of the grazing path, and the grazing preference of the grassland area at the end; The grazing paths of different sheep flocks are combined to obtain a variety of path combinations. The optimal path combination is screened out based on the degree of path overlap in each path combination and the grazing suitability of the grazing paths.

[0005] Furthermore, the method for obtaining the minimum obstacle encirclement includes: Take the ungrazed grassland area as the regional node, the nearest obstacle area in each direction as the new regional node, and continue to use the regional node to search for the nearest obstacle area in different directions as the new regional node, until the area formed by the connection line between the regional nodes is the minimum enclosing area of the ungrazed grassland area, and the area passed by the connection line corresponding to the minimum enclosing area constitutes the minimum obstacle encirclement.

[0006] Furthermore, the method for obtaining the initial grazing preference includes: The rest time of all rest grassland areas in the minimum obstacle enclosure is averaged and normalized to obtain the degree of restorable grazing in the minimum obstacle enclosure; the degree of restorable grazing is multiplied by the size of the minimum obstacle enclosure to obtain the initial grazing preference.

[0007] Furthermore, the method for obtaining the grazing preference degree includes: The grass amount in each non-grazing grassland area is normalized, and the product of the normalized grass amount and the initial grazing preference is used as the grazing preference of each non-grazing grassland area.

[0008] Furthermore, the method for obtaining the grazing suitability includes: The product of the reciprocal of the path length and the grazing preference is taken as the grazing suitability of the grazing path.

[0009] Furthermore, the grazing path is obtained based on an A* algorithm.

[0010] Furthermore, the screening method of the optimal path combination mode includes: For each path combination, the total overlapping length between the paths is used as the overlap degree; the overlap degree is negatively correlated and normalized to obtain a confidence weight; the grazing suitability of all grazing paths is accumulated and multiplied by the confidence weight to obtain the path combination optimization degree; The path combination method corresponding to the largest path combination preference is taken as the optimal path combination method.

[0011] Furthermore, the grassland information map is a rasterized map that is rasterized based on a GIS system.

[0012] Furthermore, the amount of grass in the non-fallow grassland area is obtained based on the GIS system using a standard vegetation coverage formula.

[0013] The present invention also proposes a GIS-based grassland multi-region rotational grazing management optimization system, including a memory, a processor, and a computer program stored in the memory and runnable on the processor. When the processor executes the computer program, it implements any step of the GIS-based grassland multi-region rotational grazing management optimization method.

[0014] The present invention has the following beneficial effects: The present invention first takes into account the positional relationship between the ungrazed grassland area and the obstacle area, and makes a minimum obstacle encirclement for the ungrazed grassland area. On the minimum obstacle encirclement, the larger the encirclement, the less likely the ungrazed grassland area is to be surrounded in actual circumstances; and the longer the grazing time of the grazing grassland area on the encirclement has been resting, it means that the grazing grassland area has undergone a long period of grass recovery and can be entered or passed normally. Based on this, the initial grazing preference of each ungrazed grassland area can be quantified, and the grazing preference can be further obtained by combining the grass amount for the path planning of a single flock of sheep. After the multiple path planning of each single flock of sheep is completed, the grazing paths of different flocks of sheep are combined. By analyzing the degree of overlap in each path combination method and the grazing suitability of the ungrazed grassland area at the end point, the optimal path combination method can be screened. The present invention determines the optimal path combination method through position analysis, path planning, and path combination analysis, which can ensure that the grazing paths of multiple flocks have a small degree of overlap, and the ungrazed grassland area at the end of the path can ensure normal grazing of the sheep flock, thereby improving grazing efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the technical solutions and advantages of the embodiments of the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the prior art descriptions. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0016] Figure 1 A flowchart of a GIS-based multi-region rotational grazing management optimization method for grasslands according to one embodiment of the present invention is provided; Figure 2 A schematic diagram of a rasterized map provided in accordance with an embodiment of the present invention; Figure 3 A schematic diagram of an analysis process of a path combination method provided by an embodiment of the present invention; Figure 4 A schematic diagram of the analysis process of another path combination method provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0017] To further illustrate the technical means and effectiveness of the present invention to achieve its intended purpose, the following, in conjunction with the accompanying drawings and preferred embodiments, describes in detail the specific implementation, structure, features, and effectiveness of a GIS-based multi-regional rotational grazing management optimization method and system for grasslands proposed in accordance with the present invention. In the following description, different references to "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics of one or more embodiments may be combined in any suitable manner.

[0018] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

[0019] The following describes in detail a specific scheme of a GIS-based grassland multi-region rotational grazing management optimization method and system provided by the present invention in conjunction with the accompanying drawings.

[0020] See also Figure 1 , which shows a flow chart of a multi-region rotational grazing management optimization method for grassland based on GIS according to one embodiment of the present invention, the method comprising: Step S1: obtaining a grassland information map based on a GIS system, wherein the grassland information map includes obstacle areas and grassland areas; the grassland areas include non-rested grassland areas and rested grassland areas.

[0021] For grassland areas, the GIS system can effectively detect and quantify information such as the size, vegetation coverage, and location of an area. Therefore, a grassland information map can be obtained based on the GIS system. The grassland information map includes obstacle areas and various grassland areas. Among them, obstacle areas are areas where grazing is not allowed, such as houses and villages, power equipment, and areas that require a long time to recover from overgrazing. The grassland area GIS system pre-divides various grassland areas, among which grassland areas include ungrazed grassland areas and resting grassland areas. Among them, ungrazed grassland areas are grassland areas where sheep can be arranged to graze, while resting grassland areas are grassland areas that are in the resting stage. Resting grassland areas cannot be grazed and the effective recovery of the ecological environment should be ensured.

[0022] Preferably, in the embodiment of the present invention, the grassland information map is a rasterized map after being rasterized based on the GIS system. Map rasterization refers to the use of various color grids on the map to mark obstacles and feasible spaces in the real environment, which can directly reflect whether the area in the real environment is an obstacle area. Each grid is equal in size and has binary information. Figure 2 , which shows a schematic diagram of a rasterized map provided by an embodiment of the present invention, Figure 2In the figure, dark areas represent obstacles, and the rest are grasslands. During the rasterization process, if the divided area does not fill a grid, expansion processing is used. If the area exceeds one-third of the grid, it is treated as a full grid, and if it does not exceed one-third, it is not filled. The specific rasterization process is a technical means well known to those skilled in the art and will not be detailed here.

[0023] It should be noted that the GIS system can directly evaluate the amount of grass in each grassland area based on existing technical means, which can be obtained through the standard vegetation cover formula, including: in, represents the amount of grass in the jth grassland area, is the normalized difference vegetation index, is the average normalized difference vegetation index of the bare soil area, is the average normalized index of dense grassland areas. The standard vegetation coverage formula is well known to those skilled in the art and will not be described in detail here. In the prior art, grass quantity can be used to determine whether a grassland area should be rested, and the details will not be described in detail here.

[0024] Step S2: Based on the position of the non-grazing grassland area and the positional relationship of the obstacle area, a minimum obstacle encirclement formed by each non-grazing grassland area is constructed on the grassland information map; based on the size of the minimum obstacle encirclement and the grazing time of the grazing grassland area on the minimum obstacle encirclement, the initial grazing preference of each non-grazing grassland area is obtained, and combined with the amount of grass in each non-grazing grassland area, the grazing preference of each non-grazing grassland area is obtained.

[0025] When grazing, in order to ensure that the selected grazing area can meet the feeding requirements of the flock as much as possible, areas with large grass volume should be selected for grazing. At the same time, considering the existence of rest grassland areas, in order to ensure the recovery of rest grassland areas, rest grassland areas should be avoided as much as possible when planning grazing routes. And for the target grassland area selected for grazing, once the grazing area is selected, it will be identified as an area that needs to be rested after grazing. The grazing area and other obstacle areas and other rest grazing areas will block and surround the non-rest areas. The greater the degree of encirclement and blocking, the more it means that the grazing area should not be used as a grazing area at this time. It should wait until the rest grazing areas around it are finished before grazing, so as to ensure the scientific grazing of the entire grassland area as much as possible. Therefore, the embodiment of the present invention constructs a minimum obstacle encirclement for each ungrazed grassland area on the grassland information map based on the position relationship between the initial area position and the obstacle area. The larger the minimum obstacle encirclement, the more uncertainty there is in the construction process, and the more other areas it will pass through, and the smaller the probability of complete occlusion. Conversely, the smaller the encirclement, the more obvious occlusion the current ungrazed grassland area will cause to other grassland areas after grazing. Further considering the grazing time of the grazing grassland area on the minimum obstacle encirclement, the longer the grazing time, the longer the ecological recovery time of the grazing grassland area, and the faster it can be re-grazed. At this time, the ungrazed grassland area is less likely to cause occlusion to other grassland areas. Based on this, the initial grazing preference of each ungrazed grassland area can be quantified, and the grazing preference of each ungrazed grassland area can be obtained by further combining the grass amount of each ungrazed grassland area.

[0026] Preferably, in an embodiment of the present invention, a depth-first search method is used to traverse a certain ungrazed grassland area as the starting position, thereby obtaining the minimum obstacle encirclement of the ungrazed grassland area. Specifically, the method includes: using the ungrazed grassland area as a regional node, using the nearest obstacle area in each direction as a new regional node, and continuing to search for the nearest obstacle area in different directions using the regional node as a new regional node. The depth-first search can obtain an encircled area formed by multiple regional nodes until the area formed by the lines between the regional nodes is the minimum encircled area of the ungrazed grassland area, and the traversal stops. The area on the line corresponding to the minimum encircled area constitutes the minimum obstacle encirclement.

[0027] Preferably, in an embodiment of the present invention, the method for obtaining the initial grazing preference includes: The rest time of all rested grassland areas on the minimum obstacle encirclement is averaged and normalized to obtain the degree of restorable grazing in the minimum obstacle encirclement; the degree of restorable grazing is multiplied by the size of the minimum obstacle encirclement to obtain the initial grazing preference. In the embodiment of the present invention, the normalization method adopts range normalization, that is, normalization is performed by counting the maximum and minimum values in the corresponding dimension. The greater the degree of restorable grazing and the larger the minimum obstacle encirclement, the less likely the non-rested grassland area is to block other grassland areas, and the more suitable it is for grazing, and the greater the initial grazing preference.

[0028] The grass amount in each ungrazed grassland area is further normalized, and the product of the grass amount and the initial grazing preference is used as the grazing preference of each ungrazed grassland area. The grass amount normalization method can be a maximum normalization method, that is, the maximum grass amount is used as the denominator and the grass amount of the ungrazed grassland area is used as the numerator to achieve the normalization purpose.

[0029] Step S3: Determine multiple grazing paths for a single flock of sheep based on the grazing preference; under each grazing path, obtain the grazing suitability of the non-grazing grassland area at the end point based on the path length between the initial area and the non-grazing grassland area at the end point of the grazing path, and the grazing preference of the grassland area at the end point.

[0030] After analyzing the location and grass abundance of ungrazed pastures in the above steps, the resulting grazing preference can be used as a factor in path planning. Combined with the existing distance factor, multiple grazing routes can be generated through path planning. For each grazing route, the grazing suitability of the route can be determined based on the path length between the starting area and the ungrazed pasture area at the end of the grazing route, as well as the grazing preference of the endpoint pasture area. Specifically, for a route, the shorter the path length between the starting and end points, and the greater the grazing preference of the endpoint pasture area, the better the route.

[0031] It should be noted that, because the subsequent steps in the embodiment of the present invention need to combine the grazing paths of different flocks, multiple grazing paths for a single flock need to be obtained in step S3. For each flock, the embodiment of the present invention selects the top three paths with the highest grazing suitability as the obtained grazing paths.

[0032] Preferably, in an embodiment of the present invention, path planning is performed based on the A* algorithm to obtain multiple grazing paths for a single flock of sheep. The A* search algorithm is commonly known as the A-star algorithm. The A* algorithm is one of the more popular heuristic search algorithms and is widely used in the field of path optimization. Its uniqueness lies in the introduction of global information when checking each possible node in the shortest path, estimating the distance of the current node from the end point, and using this as a measure to evaluate the possibility of the node being on the shortest route. The embodiment of the present invention further introduces the grazing preference of the end point into the algorithm, which can screen out multiple grazing paths that meet expectations.

[0033] Preferably, in an embodiment of the present invention, the method for obtaining the grazing suitability includes: The product of the reciprocal of the path length and the grazing preference is used as the grazing suitability of the grazing path. In the embodiment of the present invention, the path length is the number of grids that the path passes through in the grid map.

[0034] Step S4: combining the grazing paths of different flocks to obtain a variety of path combinations, and selecting the optimal path combination based on the degree of path overlap in each path combination and the grazing suitability of the grazing paths.

[0035] After the above steps, each flock of sheep corresponds to multiple grazing paths. Each flock selects a path for combination, resulting in multiple path combinations for different flocks of sheep. For a path combination, the smaller the degree of overlap, the less impact the sheep will have on a certain pasture area when they pass through it. At the same time, the greater the grazing suitability of the path, the more scientific and reasonable the current path combination is. Therefore, the optimal path combination can be screened out by the degree of path overlap in each path combination and the grazing suitability of the grazing path. Preferably, please refer to Figure 3 and Figure 4 , Figure 3 FIG. 1 is a schematic diagram showing an analysis process of a path combination method provided by an embodiment of the present invention. Figure 4 A schematic diagram of an analysis process of another path combination method provided by an embodiment of the present invention is shown. Figure 3 The middle area A is the initial area where flock A is located, and area B is the initial area where flock B is located. The path corresponding to the arrow is the combined grazing path, and the area pointed by the arrow is the end area of the path. It should be noted that because Figure 3 and Figure 4 The different path combinations belong to the same processing object, so the marks in the two figures are the same. Figure 3 and Figure 4 In contrast, the starting and ending points of the paths are the same, but the grazing paths are different. In a path combination, there is an overlapping area between the two paths, where Figure 3 There are three overlapping regions. Figure 4 There is an overlapping area, that is, the overlap degree of the sub-graph on the right is low. We can further analyze the grazing suitability of the grazing paths and select which of the two path combinations is more suitable for grazing.

[0036] Preferably, in an embodiment of the present invention, the method for screening the optimal path combination includes: For each path combination, the total overlap length between the paths is taken as the overlap degree, such as Figure 3 As shown, the overlap degree of the left subgraph is 3, and the overlap degree of the right subgraph is 1. After negative correlation mapping of the overlap degrees, a confidence weight is obtained. The grazing suitability of all grazing paths is accumulated and multiplied by the confidence weight to obtain the path combination preference. The path combination with the highest path combination preference is selected as the optimal path combination.

[0037] It should be noted that the negative correlation mapping method in the embodiment of the present invention adopts an inverse form, and the details are not repeated or limited thereto.

[0038] In summary, the present invention first takes into account the positional relationship between the ungrazed grassland area and the obstacle area, and makes a minimum obstacle encirclement for the ungrazed grassland area. The initial grazing preference of each ungrazed grassland area is quantified, and the grazing preference can be further obtained in combination with the grass amount for path planning of a single flock of sheep. After the multiple path planning of each single flock is completed, the grazing paths of different flocks of sheep are combined, and the optimal path combination can be screened by analyzing the degree of overlap in each path combination and the grazing suitability of the ungrazed grassland area at the end point. The present invention determines the optimal path combination through position analysis, path planning, and path combination analysis, which can ensure that the grazing paths of multiple flocks of sheep have a small degree of overlap, and the ungrazed grassland area at the end of the path can ensure normal grazing of the sheep flock, thereby improving grazing efficiency.

[0039] Based on the same inventive concept, the present invention also proposes a GIS-based grassland multi-region rotational grazing management optimization system, including a memory, a processor, and a computer program stored in the memory and runnable on the processor. When the processor executes the computer program, it implements any step of the GIS-based grassland multi-region rotational grazing management optimization method.

[0040] It should be noted that the order in which the embodiments of the present invention are described above is for illustrative purposes only and does not necessarily represent the superiority or inferiority of the embodiments. The processes depicted in the accompanying drawings do not necessarily require the specific order or sequential order shown to achieve the desired results. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0041] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on the differences from other embodiments.

Claims

1. A GIS-based grassland multi-region rotational grazing management optimization method, characterized in that: The method comprises: Obtaining a grassland information map based on a GIS system, wherein the grassland information map includes obstacle areas and grassland areas; the grassland areas include non-grazing grassland areas and grazing grassland areas; Based on the positional relationship between the locations of the ungrazed grassland areas and the obstacle areas, a minimum obstacle encirclement formed by each ungrazed grassland area is constructed on the grassland information map; based on the size of the minimum obstacle encirclement and the grazing time of the grazing grassland areas on the minimum obstacle encirclement, the initial grazing preference of each ungrazed grassland area is obtained, and combined with the amount of grass in each ungrazed grassland area, the grazing preference of each ungrazed grassland area is obtained; Determining multiple grazing paths for a single flock of sheep based on the grazing preference; obtaining a grazing suitability for each grazing path based on the path length between an initial area and an ungrazed grassland area at the end of the grazing path, and the grazing preference of the grassland area at the end; Combine the grazing paths of different flocks to obtain multiple path combinations, and select the optimal path combination based on the degree of path overlap in each path combination and the grazing suitability of the grazing paths; The method for obtaining the initial grazing preference degree includes: The rest time of all rest grassland areas in the minimum barrier encirclement is averaged and normalized to obtain the degree of restorable grazing in the minimum barrier encirclement; the degree of restorable grazing is multiplied by the size of the minimum barrier encirclement to obtain the initial grazing preference; The method for obtaining the grazing preference degree includes: The grass amount in each non-grazing grassland area is normalized, and the product of the normalized grass amount and the initial grazing preference is used as the grazing preference of each non-grazing grassland area.

2. A GIS-based grassland multi-region rotational grazing management optimization method according to claim 1, characterized in that: The method for obtaining the minimum obstacle encirclement includes: Take the ungrazed grassland area as the regional node, the nearest obstacle area in each direction as the new regional node, and continue to use the regional node to search for the nearest obstacle area in different directions as the new regional node, until the area formed by the connection line between the regional nodes is the minimum enclosing area of the ungrazed grassland area, and the area passed by the connection line corresponding to the minimum enclosing area constitutes the minimum obstacle encirclement.

3. The GIS-based multi-regional rotational grazing management optimization method for grassland according to claim 1, characterized in that: The method for obtaining the grazing suitability includes: The product of the reciprocal of the path length and the grazing preference is taken as the grazing suitability of the grazing path.

4. The GIS-based multi-regional rotational grazing management optimization method for grassland according to claim 1, characterized in that: The grazing path is obtained based on the A* algorithm.

5. The GIS-based multi-regional rotational grazing management optimization method for grassland according to claim 1, characterized in that: The screening method of the optimal path combination mode includes: For each path combination, the total overlapping length between the paths is used as the overlap degree; the overlap degree is negatively correlated and normalized to obtain a confidence weight; the grazing suitability of all grazing paths is accumulated and multiplied by the confidence weight to obtain the path combination optimization degree; The path combination method corresponding to the largest path combination preference is taken as the optimal path combination method.

6. The GIS-based multi-regional rotational grazing management optimization method for grassland according to claim 1, characterized in that: The grassland information map is a rasterized map that is rasterized based on the GIS system.

7. The GIS-based multi-regional rotational grazing management optimization method for grassland according to claim 1, characterized in that: The amount of grass in the non-fallow grassland area is obtained based on the GIS system using the standard vegetation coverage formula.

8. A GIS-based grassland multi-region rotational grazing management optimization system, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the steps of the GIS-based grassland multi-region rotational grazing management optimization method as described in any one of claims 1 to 7 are implemented.

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