Method and device for safe early warning of grazing intensity in pastoral areas based on beidou and remote sensing cooperation

Abstract

The application provides a grazing intensity safety early warning method and device based on Beidou and remote sensing cooperation, and the index standardization values corresponding to each preset environment evaluation index of a target pasture are obtained through a Beidou system and a remote sensing device; all the index standardization values are input into a fuzzy analytic hierarchy process model to obtain the index weight of each preset environment evaluation index; the weighted sum of all the index standardization values and the index weight of the corresponding preset environment evaluation index is obtained to obtain the grazing intensity value of the target pasture, and the ecological safety level of the target pasture is determined according to the preset interval range to which the change amount of the grazing intensity value in the adjacent time interval belongs. Compared with the current generally used method of determining the comprehensive evaluation index of the current environment based on the historical information of the pasture, the grazing level can be dynamically determined according to the real-time state of the current pasture, the accuracy and real-time performance of the ecological management system are improved, and thus the intelligent level of the grassland ecological management system is improved.

Description

Technical Field

[0001] This invention relates to the field of intelligent ecological management technology, and in particular to a method and device for safety early warning of grazing intensity in pastoral areas based on the synergy of Beidou and remote sensing. Background Technology

[0002] Grassland pastoral ecosystems are a crucial area in ecological development, requiring both economic benefits and ecological balance. To prevent damage to grassland ecosystems due to overgrazing, it is necessary to monitor and assess them, determine the ecological safety level of grassland pastoral areas, and thus clarify the scale and timing of grazing.

[0003] Currently, the method of using remote sensing technology to process grassland underlying surface information from different historical periods and applying it to guide current grassland pastoral management has been widely applied. However, because this method relies heavily on historical information, it lags behind in determining the current grazing safety level of grasslands. Due to the uncertainty of current environmental changes, this method is difficult to provide real-time dynamic guidance for grazing management in pastoral areas and is still not intelligent enough. Summary of the Invention

[0004] To address the problems existing in the prior art, this invention provides a method and device for safety early warning of grazing intensity in pastoral areas based on the synergy of BeiDou and remote sensing.

[0005] This invention provides a method for safety early warning of grazing intensity in pastoral areas based on the synergy of BeiDou and remote sensing, comprising:

[0006] Obtain standardized values ​​of the indicators corresponding to each preset environmental assessment indicator for the target pastoral area;

[0007] All standardized values ​​of the indicators are input into the fuzzy hierarchical analysis model to obtain the indicator weight of each preset environmental evaluation indicator output by the fuzzy hierarchical analysis model; wherein, the fuzzy hierarchical analysis model is used to compare each preset environmental evaluation indicator belonging to multiple preset levels pairwise to determine the indicator weight of each preset environmental evaluation indicator.

[0008] The grazing intensity value of the target pastoral area is obtained by weighting and summing the standardized values ​​of all indicators and the corresponding preset environmental assessment indicators.

[0009] The ecological security level of the target pastoral area is determined based on the preset range of the change in grazing intensity value within adjacent time intervals.

[0010] In one embodiment, the preset environmental assessment indicators include aboveground biomass per unit area; before obtaining the standardized values ​​of the indicators corresponding to each preset environmental assessment indicator for the target pastoral area, the method further includes:

[0011] The system receives vegetation indices collected by remote sensing devices in the target pastoral area, inputs the real-time remote sensing data into a biomass remote sensing estimation model, and obtains the surface biomass (PFB) output by the biomass remote sensing estimation model. p for:

[0012]

[0013] Among them, PFB p B(VI) represents the aboveground fresh biomass per unit area in the target pastoral area; B(VI) represents the biomass remote sensing estimation model; VI represents the vegetation index collected by the remote sensing equipment; PS p The total area of ​​the target pastoral area.

[0014] In one embodiment, the preset environmental assessment indicators further include precipitation coefficient, slope difference index, and human disturbance intensity index; before obtaining the standardized values ​​of the indicators corresponding to each preset environmental assessment indicator for the target pastoral area, the method further includes:

[0015] The precipitation coefficient PRI of the target pastoral area was calculated using real-time environmental parameters collected by remote sensing equipment in the target pastoral area. i for:

[0016]

[0017] In the formula, PRI i PR represents the precipitation coefficient of target pastoral area i. j Let be the average annual precipitation of grid j in target pastoral area i; n be the number of grids contained in target pastoral area i; s0 be the area of ​​each grid; PR be the average annual precipitation of each grid. max S represents the average annual maximum precipitation in target pastoral area i; i The area of ​​the foraging area of ​​the target pastoral region;

[0018] as well as,

[0019] The slope difference index LS of the target pastoral area was calculated using real-time environmental parameters collected by remote sensing equipment in the target pastoral area. i for:

[0020]

[0021]

[0022] Among them, LS i LS represents the slope difference index of target pastoral area i; j S is the average elevation of grid j in target pastoral area i; s0 is the area of ​​each grid cell; S i f is the area of ​​the foraging area of ​​the target pastoral area. lsiσ is the grid slope difference coefficient for target pastoral area i; lsi Let μ be the variance of the grid in the target pastoral area i; lsi Let be the mean of the grid cells in the target pastoral area i;

[0023] as well as,

[0024] The Human Interference Intensity Index (PII) is calculated using real-time environmental parameters collected by remote sensing equipment in the target pastoral area. i for:

[0025]

[0026] Among them, PII i Land use intensity of target pastoral area i; SPI j Let w represent the area of ​​land use type j with human disturbance in grid j within target pastoral area i. k S represents the weight of human interference type k; i The area of ​​the foraging area of ​​the target pastoral area.

[0027] In one embodiment, the preset environmental assessment indicators further include livestock herd feed intake, the area of ​​the feeding area, and livestock feeding intensity; before obtaining the standardized values ​​of the indicators corresponding to each preset environmental assessment indicator for the target pastoral area, the method further includes:

[0028] The location information of each animal is obtained by using a Beidou positioning device carried on each animal in the target pastoral area;

[0029] The livestock feed intake (FTV) is calculated based on the location information and the preset livestock type information. ijk for:

[0030]

[0031] Among them, FTV ijk n represents the feed intake of livestock in the target pastoral area. i Let B represent the number of livestock of different types and at different growth stages, where i represents the number of individuals of different types and at different growth stages. j t represents the feed intake of individual livestock of different types and growth stages, where j is the ranking number of individual feed intake of different types and growth stages; k The number of fixed time intervals Δt for livestock to feed, where Δt is the time interval for acquiring BeiDou signals; k is the order number of feeding at a certain time interval, i.e., the kth time interval; n1, B1, and t1 are the maximum (or upper limit) numbers of i, j, and k, respectively.

[0032] as well as,

[0033] Based on the location information and the preset livestock type information, the spatial range FS involved in livestock grazing within the specified time period is calculated. p for:

[0034]

[0035] Among them, FS p For t k Area of ​​livestock grazing during the time period; r p The radius of the livestock herd's influence area is mainly determined by the time point, location, livestock herd type, growth stage, and number obtained by the BeiDou positioning system; p is the ranking number of the foraging radius for a certain livestock herd size; p1 is the maximum ranking number of the foraging radius for a certain livestock herd size.

[0036] as well as,

[0037] The livestock herd grazing intensity (FUI) within a certain time period is calculated based on the location information and the preset livestock type information. k Estimate

[0038]

[0039] Among them, FUI k For a certain time t k The feeding intensity of livestock herds within a given area refers to the amount of fresh biomass available for feeding per unit area within a certain time frame.

[0040] In one embodiment, the preset environmental evaluation index includes a grazing index; before obtaining the standardized value of the index corresponding to each preset environmental evaluation index for the target grazing area, the method further includes:

[0041] Based on the surface biomass PFB p The grazing index FUII is determined based on the amount of feed consumed by the livestock herd:

[0042]

[0043] In one embodiment, the preset environmental assessment indicators also include one or more of the following: landscape fragmentation index, soil moisture, ecosystem resilience, ecosystem vitality index, and protected area coefficient.

[0044] This invention also provides a safety early warning device for grazing intensity in pastoral areas based on the synergy of BeiDou and remote sensing, comprising:

[0045] The data acquisition module is used to standardize the values ​​of the indicators corresponding to each preset environmental evaluation indicator for the target pastoral area;

[0046] The weight calculation module is used to input the standardized values ​​of all indicators into the fuzzy hierarchical analysis model to obtain the indicator weight of each preset environmental indicator output by the fuzzy hierarchical analysis model; wherein, the fuzzy hierarchical analysis model is used to compare each preset environmental evaluation indicator belonging to multiple preset levels pairwise to determine the indicator weight of each preset environmental evaluation indicator.

[0047] The grazing intensity value calculation module is used to perform a weighted summation of the standardized values ​​of all indicators and the corresponding preset environmental assessment indicators to obtain the grazing intensity value of the target grazing area.

[0048] The ecological security level determination module is used to determine the ecological security level of the target pastoral area based on the preset range of the change in the grazing intensity value within adjacent time intervals.

[0049] The present invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, it implements the above-described method for safety early warning of grazing intensity in pastoral areas based on the coordination of BeiDou and remote sensing.

[0050] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the above-described method for safety early warning of grazing intensity in pastoral areas based on the coordination of BeiDou and remote sensing.

[0051] The present invention also provides a computer program product, including a computer program that, when executed by a processor, implements the above-described method for safety early warning of grazing intensity in pastoral areas based on the coordination of BeiDou and remote sensing.

[0052] This invention provides a method and device for early warning of grazing intensity safety in pastoral areas based on the synergy of BeiDou and remote sensing. It acquires real-time environmental assessment index values ​​of the target pastoral area, processes these values ​​using a fuzzy hierarchical analysis model to determine the relative importance of each index, and then weights and sums the standardized values ​​of the indicators with their importance to obtain a comprehensive environmental assessment index for the pastoral area. This index guides the grazing suitability of the pastoral area. Furthermore, it determines the ecological safety level of the target pastoral area based on a preset range of changes in grazing intensity values ​​within adjacent time intervals. Compared to the currently widely used method of determining the comprehensive environmental assessment index based on historical information of the pastoral area, this method dynamically determines the ecological safety level based on the real-time status of the pastoral area, improving the accuracy and real-time performance of the ecological management system and thus enhancing the intelligence level of the grassland ecological management system. Attached Figure Description

[0053] To more clearly illustrate the technical solutions in this invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0054] Figure 1 This is a schematic diagram of the application environment of the safety early warning method for grazing intensity in pastoral areas based on the synergy of Beidou and remote sensing provided by the present invention;

[0055] Figure 2 This is a flowchart illustrating the safety early warning method for grazing intensity in pastoral areas based on the synergy of BeiDou and remote sensing provided by the present invention.

[0056] Figure 3 This is a schematic diagram of the structure of the safety early warning device for grazing intensity in pastoral areas based on the synergy of Beidou and remote sensing provided by the present invention;

[0057] Figure 4 This is a schematic diagram of the structure of the electronic device provided by the present invention. Detailed Implementation

[0058] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0059] It should be noted that in the description of the embodiments of the present invention, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element. The terms "upper," "lower," etc., indicating orientation or positional relationships based on the orientation or positional relationships shown in the accompanying drawings, are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of the present invention. Unless otherwise expressly specified and limited, the terms "installed," "connected," and "linked" should be interpreted broadly, for example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; they can refer to the internal communication of two elements. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0060] The terms "first," "second," etc., used in this application are used to distinguish similar objects and not to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that embodiments of this application can be implemented in orders other than those illustrated or described herein, and the objects distinguished by "first," "second," etc., are generally of the same class, without limiting the number of objects; for example, a first object can be one or more. Furthermore, "and / or" indicates at least one of the connected objects, and the character " / " generally indicates that the preceding and following objects have an "or" relationship.

[0061] The following is combined with Figures 1-4 The specific implementation process of the present invention is described.

[0062] The safety early warning method for grazing intensity in pastoral areas based on the synergy of BeiDou and remote sensing provided in this application embodiment can be applied to, for example... Figure 1In the application environment shown, remote sensing device 101 communicates with server 102 via a network. A data storage system can store the data that server 102 needs to process. The data storage system can be integrated onto server 102 or placed on a cloud or other network server. Server 102 also transmits information with BeiDou positioning system 103 via a network. Remote sensing device 101 can be, but is not limited to, various UAV-borne measurement devices, such as lidar, digital cameras, spectrometers, scanners, etc. BeiDou positioning system 103 includes a positioning system composed of various positioning devices and BeiDou satellites. Server 102 can be implemented using a standalone server or a server cluster composed of multiple servers.

[0063] In one embodiment, such as Figure 2 As shown, a method for safety early warning of grazing intensity in pastoral areas based on the synergy of BeiDou and remote sensing is provided, and this method is applied to... Figure 1 Taking server 102 as an example, the explanation includes the following steps:

[0064] Step 201: Obtain the standardized values ​​of the target pastoral areas for each preset environmental assessment indicator;

[0065] The target pastoral area refers to the grazing area where the grazing intensity is to be assessed, such as grassland, and also includes arid and semi-arid pastoral areas. Preset environmental assessment indicators refer to the measurement standards pre-established for environmental elements to evaluate the environmental quality of pastoral areas. In this invention, there are multiple preset environmental assessment indicators, including estimated grassland aboveground biomass, estimated livestock grazing intensity over a certain period, precipitation coefficient, slope difference index, land use intensity, soil moisture, ecosystem resilience, and protection area coefficient. It is worth noting that the indicators listed above do not represent all environmental assessment indicators; other indicators related to the pastoral environment are also within the scope of this invention, and will not be elaborated upon here.

[0066] Specifically, server 102 receives raw values ​​corresponding to preset environmental evaluation indicators sent from remote sensing device 101 and BeiDou system 103. Since different environmental evaluation indicators have different units, they cannot be directly compared. Therefore, it is necessary to standardize these preset environmental evaluation indicators first. In this embodiment, linear interpolation is used for standardization. The processing formula is as follows:

[0067]

[0068]

[0069] In formula (1), X′ +The standardized value of the positive indicator among the aforementioned preset environmental assessment indicators is the result of standardization. A positive indicator represents an indicator whose higher value indicates greater safety; where X... + This represents the original value of the positive indicator. The minimum value of the time series of positive indicators; The maximum value of the time series of positive indicators;

[0070] In formula (2), X′ - The standardized value of the negative indicators in the aforementioned preset environmental assessment indicators is the result of standardization. A negative indicator indicates that the smaller the value, the safer the indicator. Where X... - This represents the original value of the negative indicator. The minimum value of the time series of a negative indicator; The maximum value of the time series for a negative indicator.

[0071] Step 202: Input all the standardized values ​​of the indicators into the fuzzy hierarchical analysis model to obtain the indicator weight of each preset environmental evaluation indicator output by the fuzzy hierarchical analysis model.

[0072] The fuzzy hierarchical analysis model is constructed based on AHP (the Analytic Hierarchy Process) and FAHP (Fuzzy Analytic Hierarchy Process). It is used to compare each preset environmental evaluation index belonging to multiple preset levels pairwise to determine the relative importance of each preset environmental evaluation index, i.e., the index weight.

[0073] Specifically, determining the weights of the indicators is a crucial step in the evaluation. AHP decomposes the objective into multiple standards and indicators with hierarchical relationships, and obtains decision results through qualitative and quantitative analysis. By introducing fuzzy numbers to measure the relationships between elements in the PSR (Pressure-State-Response) indicator system, and by constructing a fuzzy consistent judgment matrix to calculate the weights, the inaccuracy or fuzziness in the standard judgment can be effectively resolved.

[0074] Step 203: Weighted summation of the standardized values ​​of all indicators and the corresponding preset environmental assessment indicators to obtain the grazing intensity value of the target pastoral area.

[0075] Among them, the grazing intensity value is a comprehensive environmental evaluation index for the target grazing area, which is used to characterize whether the ecosystem of the target grazing area is safe.

[0076] Specifically, the standardized values ​​and corresponding weights of each of the aforementioned preset environmental assessment indicators are weighted and summed to obtain a comprehensive evaluation indicator, namely the grazing intensity value of the target pastoral area. The calculation formula is as follows:

[0077]

[0078] Where LES is the grazing intensity value, n is the number of preset environmental assessment indicators, and W j X represents the weight of the j-th preset environmental assessment indicator; j Let be the standardized value of the j-th preset environmental assessment indicator.

[0079] Step 204: Determine the grazing warning level of the target grazing area based on the preset range of the grazing intensity.

[0080] Specifically, the safety diagnosis and early warning system for target pastoral areas refers to analyzing and predicting the impact of natural and human activities on the environment within a certain period, thereby determining the trend and speed of ecological environment changes. The grassland safety diagnosis and early warning method adopted in this invention establishes different preset interval ranges by setting different critical values ​​in the early warning system, calculates the change value (ΔEV) of the above-mentioned grazing intensity value in adjacent time intervals, and determines the preset interval range to which the change value (ΔEV) of the target pastoral area belongs, thereby determining the safety level of the target pastoral area. The determination method is shown in Table 1.

[0081] Table 1. Classification Methods for Ecological Security Diagnosis and Early Warning Status

[0082]

[0083]

[0084] Where a and b are the preset safety level range endpoints, and a1 to a7 are different critical values ​​for grazing intensity changes that are predetermined based on expert experience.

[0085] The above embodiments obtain standardized values ​​of indicators corresponding to each preset environmental assessment indicator for the target pastoral area; input all standardized indicator values ​​into a fuzzy hierarchical analysis model to obtain the indicator weights of each preset environmental assessment indicator output by the fuzzy hierarchical analysis model; perform a weighted summation of all standardized indicator values ​​and the corresponding preset environmental assessment indicator weights to obtain the grazing intensity value of the target pastoral area; and determine the safety level of the target pastoral area by the range of variation of the grazing intensity value within adjacent time intervals, thereby improving the intelligent level of pastoral ecological management. This invention obtains real-time environmental assessment indicator values ​​of the target pastoral area, processes these real-time environmental assessment indicator values ​​using a fuzzy hierarchical analysis model to determine the relative importance of each indicator, and then performs a weighted summation of the standardized indicator values ​​and indicator importance to obtain the comprehensive environmental assessment index of the pastoral area, thereby guiding the current grazing suitability of the pastoral area. Compared with the currently commonly used method of determining the comprehensive environmental assessment index based on historical information of the pastoral area, this method can dynamically determine the grazing suitability level according to the real-time status of the pastoral area, improving the accuracy and real-time performance of the ecological management system.

[0086] In one embodiment, the above-mentioned indicator weights are specifically calculated using the following steps: obtaining a hierarchical weight vector for the preset levels to which the plurality of preset environmental evaluation indicators belong; wherein each element in the hierarchical weight vector is determined using the analytic hierarchy process (AHP); obtaining the membership degree of each preset environmental evaluation indicator to which a preset level belongs, and constructing a weight judgment matrix based on the membership degree; obtaining a fuzzy consistency judgment matrix based on the product of the weight vector of the preset level and the weight judgment matrix; and processing each element in the fuzzy consistency judgment matrix to obtain the indicator weights for each preset environmental evaluation indicator.

[0087] The above embodiments determine the relative importance of each preset environmental assessment indicator through the AHP method, thereby providing a scientific decision-making basis for the subsequent calculation of the comprehensive environmental assessment index, reducing the influence of subjective human evaluation, and making the calculation results more objective and accurate.

[0088] In one embodiment, step 201 includes: obtaining the original index values ​​of each of the preset environmental assessment indicators collected for the target pastoral area; obtaining the maximum and minimum values ​​of the time series of each of the preset environmental assessment indicators within a preset time period; performing linear interpolation calculations on the original index values, the maximum and minimum values ​​of the time series of the indicators within the preset time period for each of the preset environmental assessment indicators to obtain the standardized values ​​of each of the preset environmental assessment indicators; and the set of standardized values ​​of all the preset environmental assessment indicators is the set of standardized values.

[0089] Specifically, since different preset environmental assessment indicators have different units, they cannot be directly compared. Therefore, it is necessary to process these indicators uniformly first. Thus, the standardization of indicator data is carried out by linear interpolation. The specific calculation formulas are as described in formulas (1)-(2) above, and will not be repeated here.

[0090] The above embodiments standardize the original indicators of different units using linear interpolation, providing effective data for subsequent calculation of comprehensive evaluation indicators.

[0091] In one embodiment, the aforementioned preset environmental assessment index includes aboveground biomass per unit area, and the process before step 201 further includes:

[0092] The system receives vegetation indices collected by remote sensing devices in the target pastoral area, inputs the real-time remote sensing data into a biomass remote sensing estimation model, and obtains the surface biomass (PFB) output by the biomass remote sensing estimation model. p for:

[0093]

[0094] Among them, PFB p B(VI) represents the aboveground fresh biomass per unit area in the target pastoral area; B(VI) represents the biomass remote sensing estimation model; VI represents the vegetation index collected by the remote sensing equipment; PS p The total area of ​​the target pastoral area.

[0095] Specifically, aboveground fresh biomass per unit area (PFB) p PFB represents the aboveground fresh biomass per unit area at a given point in time. p The calculation formula is as follows:

[0096]

[0097] Among them, PFB p FB represents the aboveground biomass per unit area, indicating the grassland aboveground biomass of the target pastoral area; PS p This represents the total area of ​​the target pastoral area;

[0098] Furthermore, the above-mentioned grassland aboveground fresh biomass FB was calculated using remote sensing estimation model B(VI). The formula for calculating grassland aboveground fresh biomass FB is as follows:

[0099] FB=B(VI) (6)

[0100] Wherein, FB is the grassland aboveground biomass of the target pastoral area; B(VI) is the remote sensing estimation model of grassland aboveground biomass, and the estimation of grassland aboveground biomass is affected by the current grassland type and other natural and human factors; VI is the vegetation index collected by the remote sensing equipment for the target pastoral area.

[0101] The above embodiments acquire biomass through remote sensing equipment, providing a data source for subsequent evaluation of the ecological security level of pastoral areas.

[0102] In one embodiment, the aforementioned preset environmental evaluation indicators include livestock herd feed intake, the area of ​​the feeding area, and livestock feeding intensity; prior to step 201, the method further includes: acquiring the location information of each livestock using a Beidou positioning device carried on each livestock in the target pasture; and calculating the livestock feed intake (FTV) based on the location information and preset livestock type information. ijk .

[0103] Specifically, each animal in the grazing herd in the pastoral area is equipped with a Beidou positioning device (such as a collar with a Beidou locator), and information such as the number of animals in the herd and their growth period is known.

[0104] (1) Feed intake of livestock herds (FTV) ijk Estimate

[0105]

[0106] In the formula, FTV ijk n represents the feed intake of livestock in the target pastoral area. i Let B represent the number of livestock of different types and at different growth stages, where i represents the number of individuals of different types and at different growth stages. j t represents the feed intake of individual livestock of different types and growth stages, where j is the ranking number of individual feed intake of different types and growth stages; k The number of fixed time intervals Δt for livestock to feed, where Δt is the time interval for acquiring BeiDou signals; k is the order number of feeding at a certain time interval, i.e., the kth time interval; n1, B1, and t1 are the maximum (or upper limit) numbers of i, j, and k, respectively.

[0107] Based on the location information and the preset livestock type information, the spatial range FS involved in livestock grazing within the specified time period is calculated. p ;

[0108] (2) The spatial range FS of livestock grazing within a certain period of time p Estimate

[0109]

[0110] In the formula, FSp For t k Area of ​​livestock grazing during the time period; r p The radius of the livestock herd's influence area is mainly determined by the time point, location, livestock herd type, growth stage, and number obtained by the BeiDou positioning system; p is the ranking number of the foraging radius for a certain livestock herd size; p1 is the maximum number (or upper limit) of the ranking number of the foraging radius for a certain livestock herd size.

[0111] The livestock herd grazing intensity (FUI) within a certain time period is calculated based on the location information and the preset livestock type information. k The details are as follows:

[0112] (3) Livestock herd feed intensity FUI within a certain time period k Estimate

[0113]

[0114] In the formula, FUI k For a certain time t k FTV (Farming Intensity) refers to the amount of fresh biomass available for grazing per unit area within a given timeframe. ijk The feed intake of livestock in the target pastoral area is calculated using the formula above (6); FS p The area covered by livestock grazing is calculated using the formula above (7).

[0115] Based on the above livestock feed intake FTV ijk FS area of ​​livestock grazing p Livestock herd feed intensity (FUI) k and aboveground fresh biomass per unit area FEB p The original index values ​​of each preset environmental assessment index are calculated according to the calculation method of the preset environmental assessment index.

[0116] The pre-set environmental assessment indicators in this invention are constructed according to the internationally accepted PSR method, that is, environmental indicators are established at multiple levels. The first-level indicators are comprehensive environmental assessment indicators, namely the grazing intensity value in this invention; the second-level indicators include three parts: a set of stress indicators, a set of state indicators, and a set of response indicators; the third-level indicators cover multiple aspects and belong to the different sets of the above-mentioned second-level indicators. The specific indicators are established as follows:

[0117] (I) Set of Pressure Indicators

[0118] The set of stress indicators includes at least one of the following: precipitation coefficient, slope difference index, land use intensity, elevation indicators (including but not limited to elevation, slope, and aspect), and human disturbance intensity (including but not limited to grazing intensity and the proportion of artificial underlying surface). Specifically, it includes:

[0119] 1. Precipitation coefficient

[0120]

[0121] In the formula, PRI i PR represents the precipitation coefficient of target pastoral area i. j Let be the average annual precipitation of grid j in target pastoral area i; n be the number of grids contained in target pastoral area i; s0 be the area of ​​each grid; PR be the average annual precipitation of each grid. max S represents the average annual maximum precipitation in target pastoral area i; i The area of ​​the foraging area in the target pastoral area.

[0122] Slope difference index

[0123]

[0124]

[0125] In the formula, LS i LS represents the slope difference index of target pastoral area i; j S is the average elevation of grid j in target pastoral area i; s0 is the area of ​​each grid cell; S i f is the area of ​​the foraging area of ​​the target pastoral area. lsi σ is the grid slope difference coefficient for target pastoral area i; lsi Let μ be the variance of the grid in the target pastoral area i; lsi Let be the mean of the grid cells in the target pastoral area i.

[0126] 2. Human Interference Intensity Index

[0127]

[0128] In the formula, PII i Human disturbance intensity index for target pastoral area i; SPI j Let w represent the area of ​​land use type j with human disturbance in grid j within target pastoral area i. k S represents the weight of human interference type k; i The area of ​​the foraging area of ​​the target pastoral area.

[0129] 1. Grazing Index

[0130] Based on surface biomass PFB p The grazing index FUII is determined based on the amount of feed consumed by the livestock herd:

[0131]

[0132] In the formula, FUII is the grazing index obtained by collaborative calculation of the BeiDou positioning system and remote sensing imagery; FTVijk The feed intake of livestock in the target pastoral area is calculated using the formula above (6); FEB p The above-ground biomass per unit area is calculated using the formula (4) above.

[0133] (II) Set of Status Indicators

[0134] The set of state indicators includes at least one of the following: landscape fragmentation index, soil moisture, ecosystem resilience, and ecosystem vitality index. The specific calculation method is as follows:

[0135] 1. Landscape fragmentation index

[0136] Remote sensing devices distributed throughout the target pastoral areas collect data on various land use types within the mountainous red line areas, including natural forests, water bodies, planted forests, grasslands, transportation land, settlements, farmland, and beaches, as data sources to calculate the landscape fragmentation index. The formula for calculating the landscape fragmentation index is as follows:

[0137]

[0138] In the formula, FI i TA represents the landscape fragmentation index of target pastoral area i. i N represents the total area of ​​monitoring unit i. i This represents the total number of all land use type patches within a given monitoring unit i.

[0139] 2. Soil moisture

[0140]

[0141] In the formula, SWI i SW represents the soil moisture index of target pastoral area i. j Sij represents the average soil moisture in the j-th grid of the target pastoral area i; s0 represents the grid area of ​​each grid; Sij represents the average soil moisture in the j-th grid of the target pastoral area i. i This refers to the area of ​​the foraging area.

[0142] 2. Ecosystem resilience

[0143]

[0144] In the formula, ESI i For ecosystem resilience index; w kj TD is the elasticity coefficient of land type k for grid j; kj S represents the proportion of land type k in grid j; s0 represents the grid area of ​​each grid; S i The area of ​​the foraging area of ​​the target pastoral area.

[0145] 4. Ecosystem vitality index

[0146]

[0147] In the formula, EI i For the ecosystem vitality index in target pastoral area i, NPP j S represents the average net primary productivity (NPP0) of grid j in target pastoral area i, where NPP0 is a preset value; i The area of ​​the foraging area of ​​the target pastoral area.

[0148] (III) Set of Response Indicators

[0149] The set of response indicators includes, but is not limited to, the protected area index, and the specific calculation method is as follows:

[0150] 1. Protection Area Index

[0151]

[0152] In the formula, PTI i SP is the protected area index of target pastoral area i; ij S represents the area of ​​grid j in target pastoral area i where protective measures have been implemented; i The area of ​​the foraging area of ​​the target pastoral area.

[0153] The original index values ​​of each of the above-mentioned preset environmental assessment indicators are calculated using the formulas described above.

[0154] The above embodiments, through the internationally accepted PSR method, which establishes environmental indicators at multiple levels, provide a scientific basis for subsequent decision-making in obtaining a comprehensive environmental assessment index.

[0155] In one embodiment, after determining the safety level, the method further includes: receiving the grazing intensity of the livestock herd in the target pasture area collected by the Beidou positioning device worn by each livestock in the target pasture area; receiving the aboveground biomass per unit area collected by remote sensing equipment in the target pasture area; and adjusting the safety level based on the safety adjustment coefficient f. q The biomass of available food in the target pastoral area is calculated based on the grazing intensity of livestock herds and the aboveground biomass per unit area.

[0156] Specifically, it receives the feed intake intensity (FUI) of the livestock herd in the target pasture area from the Beidou positioning devices worn by each livestock in the target pasture area. k The calculation formula is as described in formula (8) above; the aboveground biomass per unit area PFB collected by remote sensing equipment in the target pastoral area is received. p The calculation formula is as shown in formula (4) above; based on the level adjustment coefficient f corresponding to the above ecological security level. q Based on the feed intake intensity of livestock herds (FUI) k and aboveground fresh biomass per unit area PFB pThe biomass of currently available food in the target pasture area (AFB) was calculated. q The calculation formula is as follows:

[0157] AFB q =f q (PFB p -FUI k (19)

[0158] In the formula, AFB q f is the current biomass of edible food in the target pasture area. q PFB is the level adjustment coefficient corresponding to ecological security level q; q represents different ecological security levels; p FUI is the aboveground biomass per unit area. k The intensity of feed intake by livestock herds.

[0159] Furthermore, this invention, based on information on grassland surface changes caused by grazing obtained from BeiDou and remote sensing, and combined with ecological security assessment results, determines early warning levels according to different grazing intensities and corresponding ecological security levels in grassland pastoral areas. These levels are divided into five categories: degradation - early warning, slow degradation - early warning, rapid degradation - early warning, safety diagnosis - early warning, and early warning with improvement. The correspondence between these ecological security levels and the corresponding livestock herd grazing intensities is shown in Table 2 below.

[0160] Table 2 Classification of Ecological Security Diagnosis and Early Warning Status

[0161]

[0162]

[0163] The above embodiments determine the biomass (AFB) of currently available edible food in a target pastoral area based on its ecological security level. q It can provide timely early warning information for grassland ecological management, which is conducive to improving the ecological level of grassland.

[0164] The following describes the safety early warning device 300 for grazing intensity in pastoral areas based on the synergy of BeiDou and remote sensing provided by the present invention. The safety early warning device 300 for grazing intensity in pastoral areas based on the synergy of BeiDou and remote sensing described below can be referred to in correspondence with the safety early warning method for grazing intensity in pastoral areas based on the synergy of BeiDou and remote sensing described above.

[0165] In one embodiment, such as Figure 3 As shown, a grazing intensity assessment device 300 is provided, including: a data acquisition module 301, a weight calculation module 302, and a grazing intensity value calculation module 303, wherein:

[0166] Data acquisition module 301 is used to standardize the values ​​of indicators corresponding to each preset environmental evaluation indicator for the target pastoral area;

[0167] The weight calculation module 302 is used to input all standardized values ​​of indicators into the fuzzy hierarchical analysis model to obtain the indicator weight of each preset environmental indicator output by the fuzzy hierarchical analysis model; wherein, the fuzzy hierarchical analysis model is used to compare each preset environmental evaluation indicator belonging to multiple preset levels pairwise to determine the indicator weight of each preset environmental evaluation indicator.

[0168] The grazing intensity value calculation module 303 is used to perform a weighted summation of the standardized values ​​of all indicators and the corresponding preset environmental assessment indicators to obtain the grazing intensity value of the target grazing area.

[0169] The ecological security level determination module 304 is used to determine the ecological security level of the target pastoral area based on the preset range of the change in the grazing intensity value within adjacent time intervals.

[0170] In one embodiment, the above-mentioned preset environmental assessment indicators include one or more of the following: aboveground biomass per unit area, precipitation coefficient, slope difference index, human disturbance intensity index, livestock feed intake, area of ​​the feeding area, livestock feed intensity, grazing index, landscape fragmentation index, soil moisture, ecosystem resilience, ecosystem vitality index, and protection area coefficient; the calculation formulas for each indicator are shown in the above formulas (4)-(19); they will not be repeated here.

[0171] In one embodiment, the index weight is specifically calculated using the following steps, and the weight calculation module 302 is further used for:

[0172] Obtain the hierarchical weight vector of the preset levels to which the plurality of preset environmental evaluation indicators belong; wherein each element in the hierarchical weight vector is determined using the analytic hierarchy process (AHP); obtain the membership degree of each preset level to which the preset environmental evaluation indicators belong, and construct a weight judgment matrix based on the membership degree; obtain a fuzzy consistency judgment matrix based on the product of the weight vector of the preset level and the weight judgment matrix; process each element in the fuzzy consistency judgment matrix to obtain the indicator weights of each preset environmental evaluation indicator.

[0173] In one embodiment, the data acquisition module 301 described above is further configured to:

[0174] Obtain the original index values ​​of each of the preset environmental assessment indicators collected for the target pastoral area; obtain the maximum and minimum values ​​of each preset environmental assessment indicator within a preset time period; for each preset environmental assessment indicator, use linear interpolation to interpolate the original index values, the maximum and minimum values ​​of the time series within the preset time period to obtain the standardized values ​​of each preset environmental indicator; the set of standardized values ​​of all preset environmental indicators is the standardized value set.

[0175] In one embodiment, the data acquisition module 301 described above is further used for:

[0176] Obtain the aboveground biomass per unit area of ​​the target pasture; receive the feed intake, feed area, and feed intensity of the livestock herd collected by the Beidou positioning device worn by each livestock in the target pasture; and calculate the original index values ​​of each of the preset environmental assessment indicators according to the calculation method of the preset environmental assessment indicators.

[0177] In one embodiment, the data acquisition module 301 described above is further used for:

[0178] Receive vegetation index collected by remote sensing equipment in the target pastoral area; input the vegetation index into the biomass remote sensing estimation model to obtain the aboveground fresh biomass per unit area output by the biomass remote sensing estimation model.

[0179] In one embodiment, the above-mentioned pastoral grazing intensity safety early warning device 300 based on Beidou and remote sensing collaboration further includes an ecological safety level determination unit, used to: determine the ecological safety level of the target pastoral area according to the preset range of the change in the grazing intensity value in adjacent time intervals.

[0180] In one embodiment, the data acquisition module 301 is further configured to: receive the feeding intensity of the livestock herd in the target pasture area collected by the Beidou positioning device worn by each livestock in the target pasture area; and receive the aboveground biomass per unit area collected by the remote sensing equipment in the target pasture area.

[0181] The aforementioned ecological security level determination unit is also used for:

[0182] Based on the safety adjustment coefficient corresponding to the ecological safety level, the current available food biomass of the target pastoral area is calculated according to the livestock herd grazing intensity and the aboveground fresh biomass per unit area.

[0183] Figure 4An example is a schematic diagram of the physical structure of an electronic device, such as... Figure 4 As shown, the electronic device may include a processor 410, a communication interface 420, a memory 430, and a communication bus 440, wherein the processor 410, the communication interface 420, and the memory 430 communicate with each other through the communication bus 440. The processor 410 can call logical instructions in the memory 430 to execute a grazing intensity safety early warning method for pastoral areas based on BeiDou and remote sensing collaboration. This method includes: obtaining standardized values ​​of indicators corresponding to each preset environmental assessment indicator for the target pastoral area; inputting all standardized indicator values ​​into a fuzzy hierarchical analysis model to obtain the indicator weights of each preset environmental assessment indicator output by the fuzzy hierarchical analysis model; performing a weighted summation of all standardized indicator values ​​and the corresponding indicator weights of the preset environmental assessment indicators to obtain the grazing intensity value of the target pastoral area; and determining the ecological security level of the target pastoral area according to the preset interval range to which the change in the grazing intensity value belongs in adjacent time intervals.

[0184] Furthermore, the logical instructions in the aforementioned memory 430 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, essentially, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0185] On the other hand, the present invention also provides a computer program product, which includes a computer program that can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the grazing intensity assessment method provided by the above methods. The method includes: obtaining standardized values ​​of indicators corresponding to each preset environmental evaluation indicator for a target grazing area; inputting all standardized values ​​of indicators into a fuzzy hierarchical analysis model to obtain the indicator weights of each preset environmental evaluation indicator output by the fuzzy hierarchical analysis model; performing a weighted summation of all standardized values ​​of indicators and the corresponding indicator weights of preset environmental evaluation indicators to obtain the grazing intensity value of the target grazing area; and determining the ecological security level of the target grazing area according to the preset interval range to which the change in the grazing intensity value belongs in adjacent time intervals.

[0186] In another aspect, the present invention also provides a non-transitory computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the grazing intensity assessment method provided by the above methods. This method includes: obtaining standardized values ​​of indicators corresponding to each preset environmental assessment indicator for a target grazing area; inputting all standardized indicator values ​​into a fuzzy hierarchical analysis model to obtain the indicator weights of each preset environmental assessment indicator output by the fuzzy hierarchical analysis model; performing a weighted summation of all standardized indicator values ​​and the corresponding indicator weights of the preset environmental assessment indicators to obtain the grazing intensity value of the target grazing area; and determining the ecological security level of the target grazing area based on the preset interval range to which the change in the grazing intensity value belongs within adjacent time intervals.

[0187] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0188] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0189] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for safety early warning of grazing intensity in pastoral areas based on the synergy of BeiDou and remote sensing, characterized in that, include: Obtain standardized values ​​of the indicators corresponding to each preset environmental assessment indicator for the target pastoral area; All standardized values ​​of the indicators are input into the fuzzy hierarchical analysis model to obtain the indicator weight of each preset environmental evaluation indicator output by the fuzzy hierarchical analysis model; wherein, the fuzzy hierarchical analysis model is used to compare each preset environmental evaluation indicator belonging to multiple preset levels pairwise to determine the indicator weight of each preset environmental evaluation indicator. The grazing intensity value of the target pastoral area is obtained by weighting and summing the standardized values ​​of all indicators and the corresponding preset environmental assessment indicators. The ecological security level of the target grazing area is determined based on the preset range of the change in the grazing intensity value within adjacent time intervals. The preset environmental assessment indicators also include livestock herd feed intake, the area of ​​the feeding area, and livestock feeding intensity; before obtaining the standardized values ​​of the indicators corresponding to each preset environmental assessment indicator for the target pastoral area, the process also includes: The location information of each animal is obtained by using a Beidou positioning device carried on each animal in the target pastoral area; The feed intake of the livestock herd is calculated based on the location information and the preset livestock type information. for: （6） in, The feed intake of livestock in the target pastoral area Let i represent the number of livestock of different types and different growth stages, and let i represent the number of individual livestock of different types and different growth stages. denoted as feed intake of individual livestock of different types and growth stages, and j is the sorting number of feed intake of individual livestock of different types and growth stages; Fixed time intervals for feeding livestock Quantity, The time interval for acquiring BeiDou signals; k is the sorting number of the food collection within a certain time interval, i.e., the kth time interval; n1, j1, and k1 are the maximum or upper limit of i, j, and k, respectively; as well as, Based on the location information and the preset livestock type information, the spatial area covered by livestock grazing within the specified time period is calculated. for: （7） in, for Area grazing by livestock during the time period; The radius of the livestock herd's influence area is mainly determined by the time point, location, livestock herd type, growth stage, and number obtained by the BeiDou positioning system; p is the ranking number of the foraging radius for a certain livestock herd size; p1 is the maximum ranking number of the foraging radius for a certain livestock herd size. as well as, The livestock herd grazing intensity over a certain period of time is calculated based on the location information and the preset livestock type information. for: （8） in, For a certain period of time The feeding intensity of livestock herds within a given area refers to the amount of fresh biomass available for feeding per unit area within a certain time frame.

2. The method for safety early warning of grazing intensity in pastoral areas based on the synergy of BeiDou and remote sensing as described in claim 1, characterized in that, The preset environmental evaluation indicators include aboveground biomass per unit area. Before obtaining the standardized values ​​of the indicators corresponding to each preset environmental assessment indicator for the target pastoral area, the process also includes: The system receives vegetation indices collected by remote sensing devices in the target pastoral area, inputs real-time remote sensing data into a biomass remote sensing estimation model, and obtains the surface biomass output by the biomass remote sensing estimation model. for: （4） in, The aboveground biomass per unit area in the target pastoral area; For biomass remote sensing estimation models; The vegetation index is collected by remote sensing equipment; The total area of ​​the target pastoral area.

3. The method for safety early warning of grazing intensity in pastoral areas based on the synergy of BeiDou and remote sensing as described in claim 1, characterized in that, The preset environmental assessment indicators also include precipitation coefficient, slope difference index, and human disturbance intensity index; before obtaining the standardized values ​​of the indicators corresponding to each preset environmental assessment indicator for the target pastoral area, the process also includes: The precipitation coefficient of the target pastoral area was calculated using real-time environmental parameters collected by remote sensing equipment in the target pastoral area. for: （9） In the formula, Let be the precipitation coefficient of target pastoral area i; Let n be the average annual precipitation of grid j in target pastoral area i; n is the number of grids contained in target pastoral area i. The area of ​​each grid cell; The average annual maximum precipitation for target pastoral area i; The area of ​​the foraging area of ​​the target pastoral region; as well as, The slope difference index of the target pastoral area is calculated using real-time environmental parameters collected by remote sensing equipment in the target pastoral area. for: （10） （11） in, The slope difference index for target pastoral area i; Let the average elevation of grid j in target pastoral area i be denoted as ; The area of ​​each grid cell; The area of ​​the foraging area of ​​the target pastoral region; denoted as the grid slope difference coefficient for target pastoral area i; Let Variance be the variance of the grid in the target pastoral area i; Let be the mean of the grid cells in the target pastoral area i; as well as, The human interference intensity index was calculated using real-time environmental parameters collected by remote sensing equipment in the target pastoral area. for: （12） in, Human disturbance intensity index for target pastoral area i; Let the area of ​​land use type j with human disturbance be the area of ​​grid j in target pastoral area i. The weight of human interference type k; The area of ​​the foraging area of ​​the target pastoral area.

4. The method for safety early warning of grazing intensity in pastoral areas based on the synergy of BeiDou and remote sensing as described in claim 1, characterized in that, The preset environmental evaluation indicators include the grazing index; Before obtaining the standardized values ​​of the indicators corresponding to each preset environmental assessment indicator for the target pastoral area, the process also includes: Based on surface biomass Grazing index determined by livestock feed intake for: （13） in, The feed intake of livestock in the target pastoral area The aboveground biomass per unit area in the target pastoral area is denoted as .

5. The method for safety early warning of grazing intensity in pastoral areas based on the synergy of BeiDou and remote sensing as described in claim 1, characterized in that, The preset environmental assessment indicators also include one or more of the following: landscape fragmentation index, soil moisture, ecosystem resilience, ecosystem vitality index, and protected area coefficient.

6. A safety early warning device for grazing intensity in pastoral areas based on the synergy of BeiDou and remote sensing, characterized in that, The apparatus for executing the method for early warning of grazing intensity in pastoral areas based on the synergy of BeiDou and remote sensing as described in claim 1, comprises: The data acquisition module is used to standardize the values ​​of the indicators corresponding to each preset environmental evaluation indicator for the target pastoral area; The weight calculation module is used to input the standardized values ​​of all indicators into the fuzzy hierarchical analysis model to obtain the indicator weight of each preset environmental evaluation indicator output by the fuzzy hierarchical analysis model; wherein, the fuzzy hierarchical analysis model is used to compare each preset environmental evaluation indicator belonging to multiple preset levels pairwise to determine the indicator weight of each preset environmental evaluation indicator. The grazing intensity value calculation module is used to perform a weighted summation of the standardized values ​​of all indicators and the corresponding preset environmental assessment indicators to obtain the grazing intensity value of the target grazing area. The ecological security level determination module is used to determine the ecological security level of the target pastoral area based on the preset range of the change in the grazing intensity value within adjacent time intervals.

7. An electronic device 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 program, it implements the method for safety early warning of grazing intensity in pastoral areas based on the synergy of Beidou and remote sensing as described in any one of claims 1 to 5.

8. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the method for safety early warning of grazing intensity in pastoral areas based on the synergy of Beidou and remote sensing as described in any one of claims 1 to 5.

9. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, it implements the method for safety early warning of grazing intensity in pastoral areas based on the synergy of Beidou and remote sensing as described in any one of claims 1 to 5.

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