A forestry environment monitoring method and system

Abstract

The present application provides a forestry environment monitoring method and system, which starts fire alarm monitoring of the forestry environment, obtains vegetation layer moisture storage flow data of the forestry environment, determines non-redundant moisture storage flow data of the vegetation layer moisture storage flow data, and then determines the nuisance moisture storage normal sequence and nuisance moisture storage excess of the vegetation layer nuisance moisture storage micro-cluster, determines the vegetation layer circulation heat carrying capacity according to the nuisance moisture storage normal sequence, determines the vegetation layer fire empowerment factor by the nuisance moisture storage excess and the vegetation layer circulation heat carrying capacity, determines the disaster bearing shrinkage false alarm rate by the vegetation layer neighboring disaster bearing data, performs positive concentration on the vegetation layer fire empowerment factor and the disaster bearing shrinkage false alarm rate, and obtains the fire alarm concentration value of the vegetation layer. When the fire alarm concentration value of the vegetation layer is higher than the preset forestry environment fire alarm weight threshold, it is determined that there is a fire risk in the forestry environment, and sends an alarm message to the forestry environment monitoring and control center, which can improve the sensitivity of fire monitoring alarm in the forestry environment.

Description

Technical Field

[0001] The present application relates to the technical field of forestry fire alarm technology, and more specifically, to a forestry environment monitoring method and system. Background Art

[0002] Forestry fire alarm technology refers to the technology used to detect specific events, conditions or situations in the forestry environment and to issue an alarm when a fire anomaly or danger is found. The implementation of forestry fire alarm technology is usually completed by the coordinated cooperation of sensors or detection equipment, data acquisition and processing links to be tested, and alarm generation and transmission mechanisms. Forestry fire monitoring and alarm technology covers multiple fields, including forestry environment monitoring, fire safety monitoring, fire sensor equipment monitoring, forestry ecological health monitoring, etc. The main function of forestry fire monitoring and alarm technology is to promptly discover, identify and respond to specific events, conditions or situations in the forestry environment to ensure that necessary measures are taken to deal with potential dangers, risks or anomalies.

[0003] Forestry environment monitoring refers to the process of systematic, real-time or regular monitoring, observation and data collection of trees, soil, water sources, air and other natural elements related to forest and woodland ecosystems. Its purpose is to understand and evaluate the status of the forest environment in order to support sustainable forestry management, ecological protection, rational use of resources and environmental supervision. In forestry environment monitoring, fire monitoring and alarm refers to the system using different technical means to monitor and identify potential forest fires and issue an alarm when a fire is found. This helps to detect fires early so that emergency measures can be taken to control and extinguish the fire and minimize the damage caused by the fire. However, in the existing fire monitoring and alarm in the forestry environment, the inducing factors of potential fire points in large areas of forestry environment are inconsistent, which interferes with the judgment ability of the fire alarm mechanism, resulting in the low sensitivity of fire monitoring and alarm in the forestry environment. Summary of the invention

[0004] The present application provides a forestry environment monitoring method and system to solve the technical problem of low sensitivity of fire monitoring alarm in a forestry environment.

[0005] In order to solve the above technical problems, this application adopts the following technical solutions:

[0006] In a first aspect, the present application provides a forestry environment monitoring method, comprising the following steps:

[0007] Start fire alarm monitoring in forestry environment and obtain moisture storage flow data of vegetation layer in forestry environment;

[0008] Determine non-redundant moisture storage flow data of the vegetation layer moisture storage flow data, and convert the non-redundant moisture storage flow data into corresponding vegetation layer nuisance moisture storage micro-clusters;

[0009] Determine the nuisance moisture storage normal sequence and the nuisance moisture storage dissipation of the nuisance moisture storage micro-clusters of the vegetation layer, determine the vegetation layer circulation heat carrying capacity through the nuisance moisture storage normal sequence, and determine the vegetation layer fire empowerment factor according to the nuisance moisture storage dissipation and the vegetation layer circulation heat carrying capacity;

[0010] Obtaining vegetation layer neighboring disaster bearing data of a forestry environment, determining a disaster bearing shrinkage false alarm rate based on the vegetation layer neighboring disaster bearing data, performing positive clustering on the vegetation layer fire empowerment factor and the disaster bearing shrinkage false alarm rate, and obtaining a vegetation layer fire alarm clustering value;

[0011] When the vegetation layer fire alarm concentration value is higher than the preset forestry environment fire alarm right threshold, it is determined that there is a fire risk in the forestry environment, and an alarm message is sent to the forestry environment monitoring and control center.

[0012] In some embodiments, determining the non-redundant moisture storage flow data of the vegetation layer moisture storage flow data specifically includes:

[0013] Determine the vegetation layer normalized moisture storage flow data of the vegetation layer moisture storage flow data;

[0014] Determine the redundant threshold value of the vegetation layer moisture storage flow data;

[0015] The non-redundant moisture storage flow data is determined by the normalized moisture storage flow data of the vegetation layer and the redundant boundary value.

[0016] In some embodiments, converting the non-redundant moisture storage flow data into corresponding vegetation layer nuisance moisture storage micro-clusters specifically includes:

[0017] Determine the vegetation layer moisture storage nuisance amount according to the non-redundant moisture storage flow data;

[0018] determining a nuisance factor of the non-redundant humidity storage data;

[0019] Get the cluster offset center of the vegetation layer moisture storage nuisance;

[0020] The vegetation layer nuisance moisture storage micro-cluster is determined according to the vegetation layer moisture storage nuisance amount, the nuisance factor of the non-redundant moisture storage data and the cluster offset center of the vegetation layer moisture storage nuisance amount.

[0021] In some embodiments, determining the nuisance moisture storage normal sequence and the nuisance moisture storage dissipation of the nuisance moisture storage microclusters of the vegetation layer specifically comprises:

[0022] Obtaining the maximum value of the vegetation layer nuisance moisture storage micro-cluster;

[0023] Obtaining the minimum value of the vegetation layer nuisance moisture storage micro-cluster;

[0024] The normal state of the nuisance moisture storage microclusters of the vegetation layer is serialized according to the maximum value of the nuisance moisture storage microcluster of the vegetation layer and the minimum value of the nuisance moisture storage microcluster of the vegetation layer to obtain the nuisance moisture storage normal state sequence, and then the nuisance moisture storage dissipation amount is determined.

[0025] In some embodiments, determining the nuisance storage moisture dissipation specifically includes:

[0026] Determine the nuisance cross-over window width ;

[0027] Determine the diffusion nucleation factor of the vegetation layer nuisance moisture storage microclusters ;

[0028] Obtain the spatial data dimension of the vegetation layer nuisance moisture storage micro-cluster ;

[0029] According to the nuisance dispersion window width , the vegetation layer disturbs the diffusion nucleation factor of the moisture storage microclusters and the spatial data dimension of the vegetation layer nuisance moisture storage micro-clusters Determine the nuisance moisture storage dissipation, wherein the nuisance moisture storage dissipation is determined by the following formula:

[0030]

[0031] in, Indicates that the amount of moisture storage and dissipation is excessive. represents the sample parameter of the data in the nuisance storage humidity normal sequence, represents the discreteness of the nuisance humidity storage normal sequence, Indicates the nuisance storage humidity normal sequence A nuisance humidity storage normal value, .

[0032] In some embodiments, the nuisance moisture storage normal sequence includes a vegetation layer moisture change threshold and a vegetation layer temperature change threshold.

[0033] In some embodiments, it also includes: when the fire alarm concentration value is lower than or equal to a preset forestry environment fire alarm authority threshold, it is determined that there is no fire risk in the forestry environment and the fire alarm monitoring status is maintained.

[0034] In a second aspect, the present application provides a forestry environment monitoring system, which includes a fire alarm control unit, and the fire alarm control unit includes:

[0035] The vegetation layer moisture storage flow data determination module is used to start the fire alarm monitoring of the forestry environment and obtain the vegetation layer moisture storage flow data of the forestry environment;

[0036] A vegetation layer nuisance moisture storage micro-cluster determination module is used to determine the non-redundant moisture storage flow data of the vegetation layer moisture storage flow data, and convert the non-redundant moisture storage flow data into corresponding vegetation layer nuisance moisture storage micro-clusters;

[0037] a fire empowerment factor determination module, used to determine the nuisance moisture storage normal sequence and the nuisance moisture storage dissipation of the nuisance moisture storage micro-clusters of the vegetation layer, determine the vegetation layer circulation heat carrying capacity through the nuisance moisture storage normal sequence, and determine the vegetation layer fire empowerment factor according to the nuisance moisture storage dissipation and the vegetation layer circulation heat carrying capacity;

[0038] A fire alarm concentration potential value determination module is used to obtain vegetation layer neighboring disaster bearing data of a forestry environment, determine the disaster bearing shrinkage false alarm rate based on the vegetation layer neighboring disaster bearing data, and perform positive concentration on the vegetation layer fire empowerment factor and the disaster bearing shrinkage false alarm rate to obtain a fire alarm concentration potential value;

[0039] The fire alarm determination module is used to determine that there is a fire risk in the forestry environment when the fire alarm concentration value is higher than the preset forestry environment fire alarm authority threshold, and send an alarm message to the forestry environment monitoring and control center.

[0040] In a third aspect, the present application provides a computer device, comprising a memory and a processor, wherein the memory stores codes, and the processor is configured to obtain the codes and execute the above-mentioned forestry environment monitoring method.

[0041] In a fourth aspect, the present application provides a computer-readable storage medium, the computer forestry environment monitoring method.

[0042] The technical solution provided by the embodiments disclosed in this application has the following beneficial effects:

[0043] In the forestry environment monitoring method and system provided by the present application, fire alarm monitoring of the forestry environment is first started, vegetation layer moisture storage flow data of the forestry environment is obtained, non-redundant moisture storage flow data of the vegetation layer moisture storage flow data is determined, the non-redundant moisture storage flow data is converted into corresponding vegetation layer nuisance moisture storage micro-clusters, the nuisance moisture storage normal sequence and the nuisance moisture storage excess of the vegetation layer nuisance moisture storage micro-clusters are determined, the vegetation layer circulation heat carrying capacity is determined by the nuisance moisture storage normal sequence, and the nuisance moisture storage excess and The vegetation layer circulating heat carrier determines the vegetation layer fire empowerment factor, the vegetation layer neighboring disaster bearing data of the forestry environment, and the disaster bearing shrinkage false alarm rate is determined by the vegetation layer neighboring disaster bearing data. The vegetation layer fire empowerment factor and the disaster bearing shrinkage false alarm rate are positively concentrated to obtain the fire alarm concentration value of the vegetation layer. When the fire alarm concentration value of the vegetation layer is higher than the preset forestry environment fire alarm authority threshold, it is determined that there is a fire risk in the forestry environment, and an alarm message is sent to the forestry environment monitoring and control center.

[0044] The scheme determines the nuisance amount of moisture storage in the vegetation layer, which can accurately measure the humidity, temperature and other conditions of the vegetation layer, improve the sensitivity of fire alarms between vegetation layers in the forestry environment, and achieves a detailed analysis of the fire hidden in the vegetation layer by analyzing the normal sequence of nuisance moisture storage and the amount of nuisance moisture storage dissipation, which helps to fully understand the factors that trigger fire alarms in the vegetation layer. Determining the circulation heat load of the vegetation layer can dynamically reflect the changes in the heat state between the vegetation layers, and more accurately identify the heat transfer between the vegetation layers. Determining the fire enabling factor of the vegetation layer can better measure the adjustment amount that triggers the fire alarm between the vegetation layers in the forestry environment, improve the accuracy of fire alarm management in the forestry environment, determine the false alarm rate of disaster-bearing shrinkage, which can improve the accuracy of fire warnings, improve the ability to correctly alarm when an actual fire occurs, and improve the credibility of fire alarms in the forestry environment. Determining the fire alarm concentration value of the vegetation layer can improve the overall performance of fire alarms in the forestry environment, and more comprehensively evaluate the potential risks of vegetation layer fires, thereby improving the sensitivity of fire monitoring alarms in the forestry environment. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] Figure 1 is an exemplary flow chart of a forestry environment monitoring method according to some embodiments of the present application;

[0046] Figure 2 It is a schematic diagram of a process for determining the heat carrying capacity of the vegetation layer circulation according to some embodiments of the present application;

[0047] Figure 3 is a schematic diagram of exemplary hardware and / or software of a fire alarm control unit according to some embodiments of the present application;

[0048] Figure 4 It is a structural schematic diagram of a computer device for implementing a forestry environment monitoring method according to some embodiments of the present application. DETAILED DESCRIPTION

[0049] The core of the present application is to start fire alarm monitoring of the forestry environment, obtain the vegetation layer moisture storage flow data of the forestry environment, determine the non-redundant moisture storage flow data of the vegetation layer moisture storage flow data, determine the nuisance moisture storage normal sequence and the nuisance moisture storage excess of the vegetation layer nuisance moisture storage micro-cluster, determine the vegetation layer circulation heat carrier according to the nuisance moisture storage normal sequence, determine the vegetation layer fire empowerment factor according to the nuisance moisture storage excess and the vegetation layer circulation heat carrier, determine the disaster bearing shrinkage false alarm rate according to the vegetation layer neighboring disaster bearing data, positively concentrate the vegetation layer fire empowerment factor and the disaster bearing shrinkage false alarm rate to obtain the vegetation layer fire alarm concentration value, when the vegetation layer fire alarm concentration value is higher than the preset forestry environment fire alarm weight threshold, it is determined that there is a fire risk in the forestry environment, and an alarm message is sent to the forestry environment monitoring and control center, which can improve the sensitivity of fire monitoring alarm in the forestry environment.

[0050] In order to better understand the above technical solution, the above technical solution will be described in detail below in conjunction with the accompanying drawings and specific implementation methods. Figure 1 , which is an exemplary flow chart of a forestry environment monitoring method according to some embodiments of the present application. The forestry environment monitoring method 100 mainly includes the following steps:

[0051] In step 101, fire alarm monitoring of the forestry environment is started, and moisture storage flow data of the vegetation layer of the forestry environment is obtained.

[0052] In specific implementation, the fire alarm monitoring of the forestry environment in this application can adopt a fire warning device with a temperature and humidity sensor, which is not limited here. In this step, after the forestry environment fire point monitoring alarm device is activated, the fire warning device will record the historical monitoring data of the forestry environment in the historical time in the sampling area, and the historical monitoring data of the forestry environment includes vegetation transpiration humidity data, vegetation layer moisture storage data, ambient temperature, ambient humidity and vegetation layer moisture spontaneous evaporation data, etc. The sampling area refers to the forestry area where fire alarm monitoring is carried out. The historical time can be set to the past month. The vegetation layer moisture storage flow data is determined by the humidity generated by vegetation transpiration and the surface moisture evaporation humidity of the vegetation layer in the past month. It is a set of ordered data carrying time series, which will be continuously updated according to the time progression, change with time, and have fluidity, indicating the storage amount of humidity between vegetation layers.

[0053] In step 102, non-redundant moisture storage flow data of the vegetation layer moisture storage flow data is determined, and the non-redundant moisture storage flow data is converted into corresponding vegetation layer nuisance moisture storage micro-clusters.

[0054] In some embodiments, determining the non-redundant moisture storage flow data of the vegetation layer moisture storage flow data may be achieved by the following steps:

[0055] Determine the vegetation layer normalized moisture storage flow data of the vegetation layer moisture storage flow data;

[0056] Determine the redundant threshold value of the vegetation layer moisture storage flow data;

[0057] The non-redundant moisture storage flow data is determined by the normalized moisture storage flow data of the vegetation layer and the redundant boundary value.

[0058] In specific implementation, the normalized moisture storage flow data of the vegetation layer moisture storage flow data is determined. In some embodiments, the normalization technology in the prior art, such as the Z-Score normalization technology, can be used to normalize the vegetation moisture storage flow data to obtain the normalized moisture storage flow data of the vegetation layer. In other embodiments, other methods can also be used for implementation, which are not limited here; the redundant boundary value of the vegetation layer moisture storage flow data is determined, and a sliding window is set to divide the vegetation layer moisture storage flow data into vegetation layer moisture storage flow data of multiple windows, and the average value of the vegetation layer moisture storage flow data in a time window is calculated, and the average value is used as the redundant boundary value in the window. The above steps are repeated to obtain the redundant boundary values ​​in all windows. For example, the length of the sliding window is set to 10 minutes, and the counting start time of the vegetation layer moisture storage flow data corresponds to the starting time of the sliding window, and the starting point of the sliding window division is determined. 10 minutes is used as a boundary to divide the vegetation layer moisture storage flow data into data corresponding to multiple time windows, and the vegetation within every 10 minutes is calculated. The average value of the vegetation layer moisture storage flow data is obtained, and then the redundant boundary value of the vegetation layer moisture storage flow data in each sliding window is obtained; the non-redundant moisture storage flow data is determined by the vegetation layer normalized moisture storage flow data and the redundant boundary value, the vegetation layer normalized moisture storage flow data is divided into multiple intervals, the number of intervals is equal to the number of sliding windows of the vegetation layer moisture storage flow data, the sliding window of the first vegetation layer moisture storage flow data is aligned with the first vegetation layer normalized moisture storage flow data interval, the data in the first vegetation layer normalized moisture storage flow data interval that is smaller than the redundant boundary value of the vegetation layer moisture storage flow data in the first sliding window is removed, and the non-redundant moisture storage flow data in the first interval is obtained, and the above steps are repeated to obtain the non-redundant moisture storage flow data in all intervals, the redundant boundary value refers to the boundary value that defines data redundancy and non-redundancy in each vegetation layer normalized moisture storage flow data interval, the non-redundant moisture storage flow data refers to the moisture storage flow data after the redundant data in the moisture storage flow data is removed according to the boundary value, and the moisture storage flow data smaller than the redundant boundary value is set as redundant data, and the redundant data interferes with the accuracy of the moisture storage flow data.

[0059] It should be noted that the normalized moisture storage flow data of the vegetation layer determined in this step can be improved by normalizing the moisture storage flow data of the vegetation layer and eliminating abnormal moisture storage flow data values. The non-redundant moisture storage flow data is determined in this step to reduce the amount of data and ensure the compactness and effectiveness of the data.

[0060] In some embodiments, converting the non-redundant moisture storage flow data into corresponding vegetation layer nuisance moisture storage micro-clusters can be achieved by using the following steps:

[0061] Determine the vegetation layer moisture storage nuisance amount according to the non-redundant moisture storage flow data;

[0062] determining a nuisance factor of the non-redundant humidity storage data;

[0063] Get the cluster offset center of the vegetation layer moisture storage nuisance;

[0064] The vegetation layer nuisance moisture storage micro-cluster is determined according to the vegetation layer moisture storage nuisance amount, the nuisance factor of the non-redundant moisture storage data and the cluster offset center of the vegetation layer moisture storage nuisance amount.

[0065] In specific implementation, the vegetation layer moisture nuisance is determined according to the non-redundant moisture storage flow data, and a set of time scales is set. ,exist Non-redundant moisture storage data points adjacent to each other at a certain time ,in Indicates the nuisance frequency of the data. The nuisance frequency of the data refers to the degree of influence of the vegetation layer moisture storage data on interference. The larger the nuisance frequency value, the lower the validity of the data. It is usually set between 0.25 and 0.75. Indicates the current data. It represents the number of data contained in the non-redundant vegetation layer moisture storage flow data, takes the average value of every 5 non-redundant moisture storage data points as the data center, obtains multiple data centers, takes every 5 moments as a time scale, obtains multiple time scales, each time scale corresponds to a data center, calculates the distance from each non-redundant moisture storage data to the data center within a time scale, and then determines the discreteness of the distance, removes the data whose distance from the non-redundant moisture storage data to the data center is greater than the discreteness of the distance, and takes the other data as the vegetation layer moisture storage nuisance within a time scale, repeats the above steps, and obtains the vegetation layer moisture storage nuisance of all non-redundant moisture storage flow data within all time scales, wherein the discreteness of the distance can be determined by using the data distance formula in the prior art, such as the Euclidean distance, and the discreteness of the distance can be obtained by calculating the average value of the distance from all non-redundant moisture storage data to the data center within a time scale, and taking the average value as the discreteness of the distance, and the vegetation layer moisture storage nuisance indicates that the humidity, temperature, etc. of the vegetation layer can be accurately measured in the non-redundant vegetation layer moisture storage flow data, and is used to control the fire alarm sensitivity between vegetation layers in the forestry environment.

[0066] In some embodiments, the nuisance factor of the non-redundant humidity storage data may be determined using the following formula:

[0067]

[0068] in, represents the nuisance factor of non-redundant humidity storage data, represents the steady-state threshold of non-redundant storage flow data, represents the nuisance distribution entropy of non-redundant storage flow data, Indicates the abnormal amount of nuisance. Represents the logarithm with the natural number e as base.

[0069] It should be noted that the steady-state threshold of the non-redundant moisture storage flow data in this step is It measures the compactness of non-redundant moisture storage flow data and can be set to 0.65. The nuisance steady-state entropy of non-redundant moisture storage flow data The parameter that indicates the data stability of the non-redundant moisture storage flow data is set between 0.25 and 0.75, and the nuisance anomaly deviation The parameter indicating the influence of the non-redundant moisture storage flow data on the accuracy of the non-redundant moisture storage flow data in the time progression may be set to 1.2. In other embodiments, it may be set according to actual conditions and is not limited here.

[0070] In a specific implementation, the cluster offset center of the vegetation layer moisture storage nuisance quantity is obtained, and the average of the non-redundant vegetation layer moisture storage flow data is calculated, and the average is added to the data center of each time long scale and then the median is taken to obtain a plurality of cluster offset centers of the vegetation layer moisture storage nuisance quantity. The cluster offset center of the vegetation layer moisture storage nuisance quantity is used to classify the vegetation layer moisture storage nuisance quantity. Each type of vegetation layer moisture storage nuisance quantity forms a data cluster, i.e., a vegetation layer nuisance moisture storage micro-cluster. The vegetation layer nuisance moisture storage micro-cluster is determined according to the vegetation layer moisture storage nuisance quantity, the nuisance factor of the non-redundant moisture storage data and the cluster offset center of the vegetation layer moisture storage nuisance quantity. In some embodiments, the micro-cluster boundary is determined according to the cluster offset center of the vegetation layer moisture storage nuisance quantity. For example, the vegetation layer moisture storage nuisance quantity is divided into a plurality of clusters. The value of the cluster offset center of the quantity minus 1 is used as the lower boundary of the vegetation layer nuisance moisture storage micro-cluster, and the value of the cluster offset center of the vegetation layer moisture storage nuisance quantity plus 1 is used as the upper boundary of the vegetation layer nuisance moisture storage micro-cluster. The above steps are repeated to obtain all micro-cluster boundaries. According to each micro-cluster boundary, the result obtained by multiplying the number of vegetation layer moisture storage nuisance disturbance quantities by the nuisance factor of non-redundant moisture storage data is screened, that is, it is determined whether the result belongs to the micro-cluster boundary. If it is within the micro-cluster boundary, the data is retained. If it is not within the micro-cluster boundary, the next micro-cluster boundary is entered for determination. The above steps are repeated to obtain vegetation layer nuisance moisture storage micro-clusters. The vegetation layer nuisance moisture storage micro-clusters represent different categories of vegetation layer nuisance moisture storage data, and each vegetation layer nuisance moisture storage micro-cluster represents the same nature of vegetation layer temperature and humidity.

[0071] In step 103, the nuisance moisture storage normal sequence and the nuisance moisture storage dissipation of the vegetation layer nuisance moisture storage microclusters are determined, the vegetation layer circulating heat carrying capacity is determined through the nuisance moisture storage normal sequence, and the vegetation layer fire enabling factor is determined according to the nuisance moisture storage dissipation and the vegetation layer circulating heat carrying capacity.

[0072] In some embodiments, determining the nuisance moisture storage normal sequence and the nuisance moisture storage dissipation of the nuisance moisture storage micro-clusters of the vegetation layer can be achieved by using the following steps:

[0073] Obtaining the maximum value of the vegetation layer nuisance moisture storage micro-cluster;

[0074] Obtaining the minimum value of the vegetation layer nuisance moisture storage micro-cluster;

[0075] The normal state of the nuisance moisture storage microclusters of the vegetation layer is serialized according to the maximum value of the nuisance moisture storage microcluster of the vegetation layer and the minimum value of the nuisance moisture storage microcluster of the vegetation layer to obtain the nuisance moisture storage normal state sequence, and then the nuisance moisture storage dissipation amount is determined.

[0076] In specific implementation, the maximum value of the vegetation layer nuisance moisture storage microcluster is obtained. In some embodiments, the maximum value of the vegetation layer nuisance moisture storage microcluster is obtained by traversing the data in all vegetation layer nuisance moisture storage microclusters. Similarly, the minimum value of the vegetation layer nuisance moisture storage microcluster is obtained, and then the maximum value and minimum value of each vegetation layer nuisance moisture storage microcluster are obtained. According to the maximum value of the vegetation layer nuisance moisture storage microcluster and the minimum value of the vegetation layer nuisance moisture storage microcluster, the vegetation layer nuisance moisture storage microcluster is normalized to obtain the nuisance moisture storage normal sequence, and the maximum value of the vegetation layer nuisance moisture storage microcluster and the minimum value of the vegetation layer nuisance moisture storage microcluster are determined. The median of the values ​​is obtained to obtain the median of all vegetation layer nuisance moisture storage microclusters, that is, the normal value. The data with values ​​greater than the normal value in each vegetation layer nuisance moisture storage microcluster are retained, that is, the normal value of the vegetation layer nuisance moisture storage microcluster is obtained. The normal values ​​of the normal values ​​of all vegetation layer nuisance moisture storage microclusters are arranged in order from small to large to obtain the nuisance moisture storage normal sequence. The nuisance moisture storage normal sequence represents the growth progression of the normal values ​​of the vegetation layer nuisance moisture storage microclusters, reflecting the changing trend of temperature and humidity between vegetation layers under the influence of the external environment. The accuracy of the fire alarm can be adjusted by studying the changes in the normal values ​​of the vegetation layer nuisance moisture storage microclusters.

[0077] In some embodiments, determining the nuisance moisture dissipation amount may be achieved by the following steps:

[0078] Determine the nuisance cross-over window width ;

[0079] Determine the diffusion nucleation factor of the vegetation layer nuisance moisture storage microclusters ;

[0080] Obtain the spatial data dimension of the vegetation layer nuisance moisture storage micro-cluster ;

[0081] According to the nuisance dispersion window width , the vegetation layer disturbs the diffusion nucleation factor of the moisture storage microclusters and the spatial data dimension of the vegetation layer nuisance moisture storage micro-clusters Determine the nuisance moisture storage dissipation, wherein the nuisance moisture storage dissipation can be determined using the following formula:

[0082]

[0083] in, Indicates that the amount of moisture storage and dissipation is excessive. represents the sample parameter of the data in the nuisance storage humidity normal sequence, represents the discreteness of the nuisance humidity storage normal sequence, Indicates the nuisance storage humidity normal sequence A nuisance humidity storage normal value, .

[0084] In specific implementation, determine the interference dispersion window width In some embodiments, 5 can be set as the nuisance diffusion window width, that is, 5 nuisance moisture storage normal values ​​are used as a nuisance diffusion window width, and the diffusion nucleation factor of the vegetation layer nuisance moisture storage microcluster is , usually set to 0.5, the vegetation layer disturbs the spatial data dimension of the moisture storage micro-cluster , the nuisance storage humidity normal sequence contains temperature and humidity, that is, the dimension is 2, the sample parameters of the data in the nuisance storage humidity normal sequence , is determined according to the number of nuisance humidity storage normal values ​​in the nuisance humidity storage normal sequence, and the variance of the nuisance humidity storage normal values ​​in the nuisance humidity storage normal sequence is used as the dispersion of the nuisance humidity storage normal sequence. , represents the discreteness of the nuisance storage humidity normal sequence and the The absolute value of the difference between the normal value of the nuisance storage humidity,

[0085] It should be noted that the nuisance moisture storage dispersion in this step refers to the measure of the sensitivity of the vegetation layer fire alarm in the vegetation layer nuisance moisture storage micro-cluster, which represents the span distance of the dispersion degree between two adjacent nuisance moisture storage data, that is, the square of the difference in the variance between two adjacent nuisance moisture storage data. The larger the nuisance moisture storage dispersion, the more sensitive the vegetation layer fire alarm is, and the dispersion nucleation factor of the vegetation layer nuisance moisture storage micro-cluster is The adjustment value that represents the correlation between the vegetation layer nuisance moisture storage micro-cluster and the cluster core of the nuisance moisture storage micro-cluster.

[0086] In some embodiments, reference Figure 2 As shown, this figure is a schematic diagram of the process of determining the heat carrying capacity of the vegetation layer circulation in some embodiments of the present application. In this embodiment, the heat carrying capacity of the vegetation layer circulation can be determined by the following steps:

[0087] In step 1031, the vegetation layer moisture change threshold is determined through the nuisance moisture storage normal sequence;

[0088] In step 1032, the vegetation layer temperature change flow threshold is determined through the nuisance moisture storage normal sequence;

[0089] In step 1033, the vegetation layer circulation heat carrying factor is obtained;

[0090] In step 1034, the vegetation layer circulation heat carrying capacity is determined according to the vegetation layer temperature change threshold, the vegetation layer moisture change threshold and the vegetation layer circulation heat carrying factor.

[0091] In specific implementation, the vegetation layer moisture change threshold is determined by the nuisance moisture storage normal sequence. In some embodiments, the nuisance moisture storage normal data median in each nuisance diffusion window width in the nuisance moisture storage normal sequence is selected as the vegetation layer moisture change threshold, and the selection of the nuisance moisture storage normal data in all the nuisance diffusion window widths is completed to obtain multiple vegetation layer moisture change thresholds. The vegetation layer moisture change threshold is a parameter that can determine the fire alarm sensitivity after the vegetation cover layer in the forestry environment removes the interference fire alarm factors, and the parameter is variable.

[0092] In some embodiments, the vegetation layer wet flow threshold can be determined using the following formula:

[0093]

[0094] in, Indicates the vegetation layer moisture change threshold The vegetation layer moisture change threshold value, Indicates the actual water vapor content in the vegetation layer moisture threshold, It indicates the saturated water vapor content in the wet flow threshold of the vegetation layer.

[0095] In specific implementation, the vegetation layer temperature change flow threshold is determined by the nuisance moisture storage normal sequence. In some embodiments, the percentage of the ratio of the actual water vapor content in the vegetation layer moisture change flow threshold to the saturated water vapor content in the vegetation layer moisture change flow threshold is determined. A vegetation layer moisture change threshold value is obtained, and then a vegetation layer temperature change threshold is obtained. The vegetation layer temperature change threshold represents the degree of humidity transition over time in the nuisance moisture storage normal sequence of the vegetation layer in the forestry environment. The faster the transition over time, the easier it is to trigger a forestry environment fire alarm. In other embodiments, other methods can also be used to achieve this, which is not limited here.

[0096] It should be noted that the actual water vapor content in the wet flow threshold of the vegetation layer indicates the actual water vapor content in the wet flow threshold of the vegetation layer. The higher the actual water vapor content in the wet flow threshold of the vegetation layer, the higher the actual water vapor content in the wet flow threshold of the vegetation layer. The saturated water vapor content in the wet flow threshold of the vegetation layer indicates the saturated water vapor content in the wet flow threshold of the vegetation layer. The higher the saturated water vapor content in the wet flow threshold of the vegetation layer, the higher the saturated water vapor content in the wet flow threshold of the vegetation layer.

[0097] In specific implementation, the vegetation layer circulation heat carrying factor is obtained. In some embodiments, the vegetation layer circulation heat carrying factor can be set to a number between 0.25 and 0.75. In other embodiments, other methods can be used to determine the vegetation layer circulation heat carrying factor, which is not limited here. In some embodiments, the vegetation layer circulation heat carrying factor is determined according to the vegetation layer temperature change threshold, the vegetation layer moisture change threshold and the vegetation layer circulation heat carrying factor. The result obtained by multiplying the ratio of the vegetation layer moisture change threshold to the vegetation layer temperature change threshold by the vegetation layer circulation heat carrying factor is used as the vegetation layer circulation heat carrying factor. The vegetation layer circulation heat carrying factor refers to a parameter that affects the surrounding heat carrying capacity between adjacent plants in the vegetation layer. The smaller the vegetation layer circulation heat carrying factor is, the smaller the influence of temperature and humidity on the adjacent plants in the vegetation layer is, and the larger the surrounding heat carrying capacity is. The surrounding heat carrying capacity is the heat contained in the surrounding vegetation, which changes with the changes in temperature and humidity.

[0098] In some embodiments, determining the vegetation layer fire enabling factor according to the nuisance moisture storage dissipation and the vegetation layer circulation heat load can be achieved by using the following steps:

[0099] Get the nuisance moisture dissipation ;

[0100] Obtain the vegetation layer circulation heat capacity ;

[0101] Get the first The threshold value of vegetation layer moisture change ;

[0102] Get the first The vegetation layer temperature change threshold value ;

[0103] Get the first Nuisance moisture storage micro-cluster data of vegetation layer ;

[0104] According to the nuisance moisture dissipation , the vegetation layer circulation heat carrying capacity , the nuisance moisture storage normal sequence The threshold value of vegetation layer moisture change , the nuisance moisture storage normal sequence The vegetation layer temperature change threshold value and the vegetation layer disturbs the moisture storage micro-cluster Nuisance moisture storage micro-cluster data of vegetation layer Determine the fire empowerment factor of the vegetation layer, where the fire empowerment factor of the vegetation layer can be determined using the following formula:

[0105]

[0106] in, represents the fire enabling factor of the vegetation layer, It represents the total number of vegetation layer temperature change threshold values ​​in the nuisance moisture storage normal sequence. , It represents the total number of vegetation layer moisture change threshold values ​​in the nuisance moisture storage normal sequence. , It represents the total number of vegetation layer nuisance moisture storage micro-cluster data in the vegetation layer nuisance moisture storage micro-cluster. , Indicates that the result is rounded to 3 significant digits.

[0107] It should be noted that the vegetation layer fire enabling factor in the present application refers to the regulating amount in the vegetation layer that induces fire and triggers fire alarms; by analyzing the normal sequence of nuisance moisture storage and the amount of nuisance moisture storage dissipation, a detailed analysis of the fire hidden in the vegetation layer can be achieved, which helps to fully understand the factors that trigger fire alarms in the vegetation layer and determine the circulating heat carrier of the vegetation layer. It can dynamically reflect the changes in the thermal state between vegetation layers, and at the same time more accurately identify the heat transfer between vegetation layers. Determining the vegetation layer fire enabling factor can better measure the regulating amount that triggers fire alarms between vegetation layers in forestry environments, thereby improving the accuracy of fire alarm management in forestry environments.

[0108] In step 104, the vegetation layer neighboring disaster bearing data of the forestry environment is obtained, the disaster bearing shrinkage false alarm rate is determined based on the vegetation layer neighboring disaster bearing data, the vegetation layer fire empowerment factor and the disaster bearing shrinkage false alarm rate are positively concentrated to obtain a fire alarm concentration value.

[0109] In specific implementation, the vegetation layer neighboring disaster susceptibility data of the forestry environment is obtained. In some embodiments, the vegetation layer neighboring disaster susceptibility data is determined based on the heat storage and temperature and humidity transfer rate in adjacent plants between vegetation layers in the forestry environment. The vegetation layer neighboring disaster susceptibility data is used to represent indicator data of the fire resistance of adjacent plants between vegetation layers in the forestry environment, that is, the key measurement scale for triggering fire alarms in vegetation layers in the forestry environment. The smaller the vegetation layer neighboring disaster susceptibility data, the more likely the vegetation layer is to have a fire, that is, the easier it is to trigger a fire alarm in the vegetation layer.

[0110] In some embodiments, determining the disaster bearing shrinkage false alarm rate based on the vegetation layer adjacent disaster bearing data can be achieved by using the following steps:

[0111] Determine the vegetation layer disaster bearing warning sequence of the vegetation layer neighboring disaster bearing data;

[0112] Determine a plurality of vegetation layer field alarm strips according to the vegetation layer disaster warning sequence;

[0113] Determine the vegetation layer shrinkage false alarm coefficient according to the vegetation layer field alarm strip;

[0114] The disaster-bearing shrinkage false alarm rate is determined according to the vegetation layer shrinkage false alarm coefficient.

[0115] In a specific implementation, a vegetation layer disaster warning sequence of the vegetation layer neighbor disaster data is determined. In some embodiments, the vegetation layer disaster warning sequence is obtained by sorting the vegetation layer neighbor disaster data in time progression. The vegetation layer disaster warning sequence represents the amount of change of the vegetation layer disaster warning in time progression. A plurality of vegetation layer field alarm bars are determined according to the vegetation layer disaster warning sequence. In some embodiments, the discreteness of the vegetation layer neighbor disaster data can be used as a field threshold to equally divide the vegetation layer disaster warning sequence into a plurality of vegetation layer field alarm bars, for example, 20 bars. , the data in each vegetation layer field alarm strip that is greater than the field threshold is used as the field alarm data, and the data in each vegetation layer field alarm strip that is less than or equal to the field threshold is used as the field non-alarm data; the disaster-bearing shrinkage false alarm rate is determined according to the vegetation layer shrinkage false alarm coefficient. In some embodiments, the disaster-bearing shrinkage false alarm rate can be obtained by multiplying the difference between the field alarm data and the field non-alarm data by the vegetation layer shrinkage false alarm coefficient. The disaster-bearing shrinkage false alarm rate represents the probability of a fire alarm being falsely triggered due to environmental factors between vegetation layers in a forestry environment.

[0116] It should be noted that in this step, the discreteness of the vegetation layer neighboring disaster-bearing data can be determined by the average value of the vegetation layer neighboring disaster-bearing data, and the field-based threshold refers to the measurement of the proportion of scenarios with fire alarms and without fire alarms, and is determined by calculating the ratio of field-based non-alarm data to field-based alarm data. The field-based alarm data is the number of occurrences of data that can trigger a fire alarm in the vegetation layer neighboring disaster-bearing data in a forestry environment, and the field-based non-alarm data is the number of occurrences of data that does not trigger a fire alarm in the vegetation layer neighboring disaster-bearing data in a forestry environment.

[0117] In some embodiments, the vegetation layer fire empowerment factor and the disaster bearing shrinkage false alarm rate are positively concentrated to obtain a fire alarm concentration value, which can be achieved by the following steps:

[0118] Get the vegetation layer fire energy factor ;

[0119] Get the first Nuisance moisture storage micro-cluster data of vegetation layer ;

[0120] Get the first The vegetation layer temperature change threshold value ;

[0121] Get the first The threshold value of vegetation layer moisture change ;

[0122] Obtain the vegetation layer adjacent disaster bearing data Localized alarm data ;

[0123] Obtain the vegetation layer adjacent disaster bearing data Field-based non-alarm data ;

[0124] According to the fire enabling factor of vegetation layer , the vegetation layer disturbs the moisture storage micro-cluster Nuisance moisture storage micro-cluster data of vegetation layer , the nuisance moisture storage normal sequence The vegetation layer temperature change threshold value , the nuisance moisture storage normal sequence The threshold value of vegetation layer moisture change , the vegetation layer adjacent disaster bearing data Localized alarm data The vegetation layer adjacent to the disaster-bearing data Field-based non-alarm data Determine the fire alarm concentration value, wherein the fire alarm concentration value can be determined using the following formula:

[0125]

[0126] in, Indicates the fire alarm concentration value. represents the fire enabling factor of the vegetation layer, represents an exponential function with the natural number e as base, It indicates the total number of non-alarm data in the vegetation layer neighboring disaster-bearing data. , It indicates the total number of midfield alarm data in the vegetation layer neighboring disaster-bearing data. , It represents the total number of vegetation layer temperature change threshold values ​​in the nuisance moisture storage normal sequence. , It represents the total number of vegetation layer moisture change threshold values ​​in the nuisance moisture storage normal sequence. , It represents the total number of vegetation layer nuisance moisture storage micro-cluster data in the vegetation layer nuisance moisture storage micro-cluster. .

[0127] It should be noted that in this step, the fire alarm concentration value refers to the data in which multiple fire-inducing factors in the vegetation layer in the forestry environment gather together, which can accurately analyze the trend of fire occurrence and trigger fire alarms. In this application, obtaining the adjacent disaster-bearing data of the vegetation layer helps to comprehensively analyze the state of adjacent vegetation between vegetation layers in the forestry environment and its ability to withstand fire. Determining the false alarm rate of disaster-bearing shrinkage can improve the accuracy of fire warnings, improve the ability to correctly alarm when an actual fire occurs, and thus improve the credibility of fire alarms in the forestry environment. Determining the fire alarm concentration value of the vegetation layer can improve the overall performance of fire alarms in the forestry environment, and more comprehensively evaluate the potential risks of vegetation layer fires, thereby improving the sensitivity of fire monitoring alarms in the forestry environment.

[0128] In step 105, when the fire alarm potential value is higher than the preset forestry environment fire alarm right threshold, it is determined that there is a fire risk in the forestry environment, and an alarm message is sent to the forestry environment monitoring and control center.

[0129] In specific implementation, when the fire alarm concentration value of the vegetation layer is higher than the preset forestry environment fire alarm authority threshold, it is determined that there is a fire risk in the forestry environment, the current monitored forestry area is marked as a fire-prone area, and the geographical location coordinates of the area are sent to the forestry environment monitoring and control center, and the fire alarm response is triggered at the same time. When the fire alarm concentration value of the vegetation layer is lower than or equal to the preset forestry environment fire alarm authority threshold, it is determined that there is no fire risk in the forestry environment, and the current monitored forestry area is marked as not prone to fire or not having a fire risk. At this time, the forestry environment monitoring and control center maintains the monitoring status of the fire alarm in the area, that is, the forestry environment fire alarm response is in a silent state and continues to monitor.

[0130] It should be noted that the forestry environment fire alarm authority threshold in this step is determined based on the critical value of comprehensive induced fire in the forestry environment of the monitored area. The critical value of comprehensive induced fire in the forestry environment refers to the minimum value of the dryness of the surface of the vegetation cover layer in the forestry environment without the risk of fire.

[0131] In addition, in another aspect of the present application, in some embodiments, the present application provides a forestry environment monitoring system, the system includes a fire alarm control unit, reference Figure 3 , which is a schematic diagram of exemplary hardware and / or software of a fire alarm control unit according to some embodiments of the present application, the fire alarm control unit 300 includes: a vegetation layer moisture storage flow data determination module 301, a vegetation layer nuisance moisture storage micro-cluster determination module 302, a fire enabling factor determination module 303, a fire alarm concentration potential value determination module 304 and a fire alarm determination module 305, which are respectively described as follows:

[0132] The vegetation layer moisture storage flow data determination module 301, in the present application, the vegetation layer moisture storage flow data determination module 301 is mainly used to start the fire alarm monitoring of the forestry environment and obtain the vegetation layer moisture storage flow data of the forestry environment;

[0133] The vegetation layer nuisance moisture storage micro-cluster determination module 302 in the present application is mainly used to determine the non-redundant moisture storage flow data of the vegetation layer moisture storage flow data, and convert the non-redundant moisture storage flow data into the corresponding vegetation layer nuisance moisture storage micro-cluster;

[0134] The fire empowerment factor determination module 303 in the present application is mainly used to determine the nuisance moisture storage normal sequence and the nuisance moisture storage dissipation of the nuisance moisture storage micro-clusters of the vegetation layer, determine the vegetation layer circulation heat carrying capacity through the nuisance moisture storage normal sequence, and determine the vegetation layer fire empowerment factor according to the nuisance moisture storage dissipation and the vegetation layer circulation heat carrying capacity;

[0135] The fire alarm concentration potential value determination module 304 in the present application is mainly used to obtain the vegetation layer adjacent disaster bearing data of the forestry environment, determine the disaster bearing shrinkage false alarm rate from the vegetation layer adjacent disaster bearing data, and perform positive concentration on the vegetation layer fire empowerment factor and the disaster bearing shrinkage false alarm rate to obtain the vegetation layer fire alarm concentration potential value;

[0136] The fire alarm determination module 305 in the present application is mainly used to determine that there is a fire risk in the forestry environment when the fire alarm potential value of the vegetation layer is higher than the preset forestry environment fire alarm authority threshold, and send an alarm message to the forestry environment monitoring and control center.

[0137] In addition, the present application also provides a computer device, which includes a memory and a processor, the memory stores codes, and the processor is configured to obtain the codes and execute the above-mentioned forestry environment monitoring method.

[0138] In some embodiments, reference Figure 4 , which is a schematic diagram of the structure of a computer device for implementing a forestry environment monitoring method according to some embodiments of the present application. The forestry environment monitoring method in the above embodiment can be Figure 4 The computer device shown in the figure is implemented, and the computer device includes at least one processor 401, a communication bus 402, a memory 403 and at least one communication interface 404.

[0139] The processor 401 may be a general-purpose central processing unit (CPU), an application-specific integrated circuit (ASIC), or one or more processors for controlling the execution of the forestry environment monitoring method in the present application.

[0140] Communication bus 402 may include a pathway for transmitting information between the above-mentioned components.

[0141] The memory 403 may be a read-only memory (ROM) or other types of static storage devices that can store static information and instructions, a random access memory (RAM) or other types of dynamic storage devices that can store information and instructions, or an electrically erasable programmable read-only memory (EEPROM), a compact disc read-only memory (CD-ROM) or other optical disc storage, an optical disc storage (including a compressed optical disc, a laser disc, an optical disc, a digital versatile disc, a Blu-ray disc, etc.), a magnetic disk or other magnetic storage device, or any other medium that can be used to carry or store the desired program code in the form of an instruction or data structure and can be accessed by a computer, but is not limited thereto. The memory 403 may exist independently and be connected to the processor 401 via the communication bus 402. The memory 403 may also be integrated with the processor 401.

[0142] The memory 403 is used to store the program code for executing the solution of the present application, and the execution is controlled by the processor 401. The processor 401 is used to execute the program code stored in the memory 403. The program code may include one or more software modules. The forestry environment monitoring method in the above embodiment can be implemented by the processor 401 and one or more software modules in the program code in the memory 403.

[0143] The communication interface 404 uses any transceiver or other device for communicating with other devices or communication networks, such as Ethernet, radio access network (RAN), wireless local area networks (WLAN), etc.

[0144] In a specific implementation, as an embodiment, a computer device may include multiple processors, each of which may be a single-CPU processor or a multi-CPU processor. The processor here may refer to one or more devices, circuits, and / or processing cores for processing data (e.g., computer program instructions).

[0145] The above-mentioned computer device may be a general-purpose computer device or a special-purpose computer device. In a specific implementation, the computer device may be a desktop computer, a portable computer, a network server, a personal digital assistant (PDA), a mobile phone, a tablet computer, a wireless terminal device, a communication device or an embedded device. The embodiment of the present application does not limit the type of computer device.

[0146] In addition, the present application also provides a computer-readable storage medium, which stores a computer program, and when the computer program is executed by a processor, the above-mentioned forestry environment monitoring method is implemented.

[0147] In summary, in the forestry environment monitoring method and system disclosed in the embodiment of the present application, firstly, determining the nuisance amount of moisture storage in the vegetation layer can accurately measure the humidity, temperature and other conditions of the vegetation layer, improve the sensitivity of fire alarm in controlling the vegetation layers in the forestry environment, and realize detailed analysis of the fire hidden in the vegetation layer by analyzing the normal sequence of nuisance moisture storage and the amount of nuisance moisture storage dissipation, which is helpful to fully understand the factors that trigger the fire alarm in the vegetation layer, and determine the circulation heat carrying capacity of the vegetation layer, which can dynamically reflect the changes in the heat state between the vegetation layers, and more accurately identify the heat transfer between the vegetation layers, and determine the vegetation layer fire enabling factor, which can better measure the adjustment amount that triggers the fire alarm between the vegetation layers in the forestry environment, improve the accuracy of fire alarm management in the forestry environment, determine the false alarm rate of disaster-bearing shrinkage, which can improve the accuracy of fire warning, improve the ability of correct alarm when an actual fire occurs, and improve the credibility of fire alarm in the forestry environment, determine the vegetation layer fire alarm concentration value, which can improve the overall performance of fire alarm in the forestry environment, and more comprehensively evaluate the potential risk of vegetation layer fire, thereby improving the sensitivity of fire monitoring alarm in the forestry environment.

[0148] Although the preferred embodiments of the present application have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications falling within the scope of the present application.

[0149] Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present application fall within the scope of the claims of the present application and their equivalents, the present application is also intended to include these modifications and variations.

Claims

1. A forestry environment monitoring method, characterized in that: The steps include: Start fire alarm monitoring of forestry environment and obtain vegetation layer moisture storage flow data of forestry environment, wherein the vegetation layer moisture storage flow data is determined by the humidity generated by vegetation transpiration and the surface moisture evaporation humidity of the vegetation layer in the past month; Determine non-redundant moisture storage flow data of the vegetation layer moisture storage flow data, and convert the non-redundant moisture storage flow data into corresponding vegetation layer nuisance moisture storage micro-clusters, wherein the non-redundant moisture storage flow data refers to the moisture storage flow data after redundant data in the moisture storage flow data is removed according to a boundary value, and the vegetation layer nuisance moisture storage micro-clusters represent different categories of vegetation layer nuisance moisture storage data; Determine the nuisance moisture storage normal sequence and the nuisance moisture storage dissipation of the vegetation layer nuisance moisture storage micro-cluster, determine the vegetation layer circulation heat carrying capacity through the nuisance moisture storage normal sequence, and determine the vegetation layer fire empowerment factor according to the nuisance moisture storage dissipation capacity and the vegetation layer circulation heat carrying capacity, wherein the nuisance moisture storage normal sequence represents the growth and progression of the normal value of the vegetation layer nuisance moisture storage micro-cluster, the nuisance moisture storage normal sequence includes the vegetation layer moisture change threshold and the vegetation layer temperature change threshold, the nuisance moisture storage dissipation capacity refers to the measure that affects the sensitivity of the vegetation layer fire alarm in the vegetation layer nuisance moisture storage micro-cluster, and the vegetation layer fire empowerment factor refers to the adjustment amount that induces fire and triggers the fire alarm in the vegetation layer; Obtain the vegetation layer neighboring disaster bearing data of the forestry environment, determine the disaster bearing shrinkage false alarm rate based on the vegetation layer neighboring disaster bearing data, perform positive aggregation on the vegetation layer fire empowerment factor and the disaster bearing shrinkage false alarm rate, and obtain the fire alarm aggregation value, wherein the vegetation layer neighboring disaster bearing data represents the index data of the fire bearing capacity of the adjacent plants between the vegetation layers in the forestry environment, and the vegetation layer neighboring disaster bearing data is determined according to the heat storage and temperature and humidity transfer rate in the adjacent plants between the vegetation layers in the forestry environment, and the fire alarm aggregation value refers to the data that a variety of fire-inducing factors are condensed in the vegetation layer in the forestry environment, and can accurately analyze the fire occurrence trend and trigger the fire alarm; When the fire alarm concentration value is higher than the preset forestry environment fire alarm right threshold, it is determined that there is a fire risk in the forestry environment, and an alarm message is sent to the forestry environment monitoring and control center; Wherein, determining the non-redundant moisture storage flow data of the vegetation layer moisture storage flow data specifically includes: Determine the vegetation layer normalized moisture storage flow data of the vegetation layer moisture storage flow data; Determine the redundant threshold value of the vegetation layer moisture storage flow data; Determine non-redundant moisture storage flow data through the vegetation layer normalized moisture storage flow data and the redundant threshold value; The conversion of the non-redundant moisture storage flow data into corresponding vegetation layer nuisance moisture storage micro-clusters specifically includes: Determine the vegetation layer moisture storage nuisance amount according to the non-redundant moisture storage flow data; determining a nuisance factor of the non-redundant humidity storage data; Get the cluster offset center of the vegetation layer moisture storage nuisance; Determine the vegetation layer nuisance moisture storage micro-cluster according to the vegetation layer moisture storage nuisance amount, the nuisance factor of the non-redundant moisture storage data and the cluster offset center of the vegetation layer moisture storage nuisance amount; Wherein, determining the nuisance moisture storage normal sequence and the nuisance moisture storage dissipation of the nuisance moisture storage micro-clusters of the vegetation layer specifically includes: Obtaining the maximum value of the vegetation layer nuisance moisture storage micro-cluster; Obtaining the minimum value of the vegetation layer nuisance moisture storage micro-cluster; According to the maximum value of the vegetation layer nuisance moisture storage micro-cluster and the minimum value of the vegetation layer nuisance moisture storage micro-cluster, the normal sequence of the vegetation layer nuisance moisture storage micro-cluster is sequenced to obtain the nuisance moisture storage normal sequence, and then the nuisance moisture storage dissipation amount is determined; Among them, determining the heat carrying capacity of the vegetation layer circulation specifically includes: Determine the vegetation layer moisture change threshold through the nuisance moisture storage normal sequence, wherein the vegetation layer moisture change threshold is a parameter that can determine the fire alarm sensitivity after removing the interference fire alarm factors of the vegetation cover layer in the forestry environment; Determine the vegetation layer temperature change threshold through the nuisance moisture storage normal sequence, wherein the vegetation layer temperature change threshold represents the degree of humidity transition over time in the nuisance moisture storage normal sequence of the vegetation layer in the forestry environment; Obtain the heat carrying factor of vegetation layer circulation; Determine the vegetation layer circulation heat carrying capacity according to the vegetation layer temperature change threshold, the vegetation layer moisture change threshold and the vegetation layer circulation heat carrying factor; The method of determining the vegetation layer fire enabling factor according to the nuisance moisture storage dissipation and the vegetation layer circulation heat load specifically includes: Get the amount of moisture dissipation ; Obtain the vegetation layer circulation heat capacity ; Get the first The vegetation layer moisture change threshold value ; Get the first The vegetation layer temperature change threshold value ; Get the first Nuisance moisture storage micro-cluster data of vegetation layer ; According to the nuisance moisture dissipation , the vegetation layer circulation heat carrying capacity , the nuisance moisture storage normal sequence The vegetation layer moisture change threshold value , the nuisance moisture storage normal sequence The vegetation layer temperature change threshold value and the vegetation layer disturbs the moisture storage micro-cluster Nuisance moisture storage micro-cluster data of vegetation layer Determine the fire empowerment factor of the vegetation layer, where the fire empowerment factor of the vegetation layer is determined using the following formula: in, represents the fire enabling factor of the vegetation layer, It represents the total number of vegetation layer temperature change threshold values ​​in the nuisance moisture storage normal sequence. , It represents the total number of vegetation layer moisture change threshold values ​​in the nuisance moisture storage normal sequence. , It represents the total number of vegetation layer nuisance moisture storage micro-cluster data in the vegetation layer nuisance moisture storage micro-cluster. , Indicates that the result retains 3 significant figures; The method of determining the disaster bearing shrinkage false alarm rate based on the vegetation layer adjacent disaster bearing data specifically includes: The vegetation layer neighboring disaster bearing data are sorted in time progression to obtain a vegetation layer disaster bearing warning sequence, the vegetation layer disaster bearing warning sequence represents the change amount of the vegetation layer disaster bearing warning in time progression, the discreteness of the vegetation layer neighboring disaster bearing data is used as the field threshold, the vegetation layer disaster bearing warning sequence is equally divided into a plurality of vegetation layer field alarm strips, the data in each vegetation layer field alarm strip greater than the field threshold is used as the field alarm data, and the data in each vegetation layer field alarm strip less than or equal to the field threshold is used as the field non-alarm data; the disaster bearing shrinkage false alarm rate is obtained by multiplying the difference between the field alarm data and the field non-alarm data by the vegetation layer shrinkage false alarm coefficient, and the disaster bearing shrinkage false alarm rate represents the probability of the fire alarm being falsely triggered due to environmental factors between vegetation layers in a forestry environment; Among them, determining the nuisance moisture storage and dissipation specifically includes: Determine the nuisance cross-over window width ; Determine the diffusion nucleation factor of the vegetation layer nuisance moisture storage microclusters The vegetation layer disturbs the diffusion nucleation factor of the moisture storage microclusters The adjustment amount representing the correlation between the vegetation layer nuisance moisture storage micro-cluster and the cluster core of the nuisance moisture storage micro-cluster; Obtain the spatial data dimension of the vegetation layer nuisance moisture storage micro-cluster ; According to the nuisance dispersion window width , the vegetation layer disturbs the diffusion nucleation factor of the moisture storage microclusters and the spatial data dimension of the vegetation layer nuisance moisture storage micro-clusters Determine the nuisance moisture storage dissipation, wherein the nuisance moisture storage dissipation is determined by the following formula: in, Indicates that the amount of moisture storage and dissipation is excessive. represents the sample parameter of the data in the nuisance humidity storage normal sequence, represents the discreteness of the nuisance storage moisture normal sequence, Indicates the nuisance storage humidity normal sequence A nuisance humidity storage normal value, .

2. The method according to claim 1, characterized in that Also includes: When the fire alarm potential value is lower than or equal to the preset forestry environment fire alarm authority threshold, it is determined that there is no fire risk in the forestry environment and the fire alarm monitoring status is maintained.

3. A forestry environment monitoring system, which adopts the method of any one of claims 1 to 2 for monitoring, characterized in that: The forestry environment monitoring system includes a fire alarm control unit, which includes: The vegetation layer moisture storage flow data determination module is used to start the fire alarm monitoring of the forestry environment and obtain the vegetation layer moisture storage flow data of the forestry environment; A vegetation layer nuisance moisture storage micro-cluster determination module is used to determine the non-redundant moisture storage flow data of the vegetation layer moisture storage flow data, and convert the non-redundant moisture storage flow data into corresponding vegetation layer nuisance moisture storage micro-clusters; a fire empowerment factor determination module, used to determine the nuisance moisture storage normal sequence and the nuisance moisture storage dissipation of the nuisance moisture storage micro-clusters of the vegetation layer, determine the vegetation layer circulation heat carrying capacity through the nuisance moisture storage normal sequence, and determine the vegetation layer fire empowerment factor according to the nuisance moisture storage dissipation and the vegetation layer circulation heat carrying capacity; A fire alarm concentration potential value determination module is used to obtain vegetation layer neighboring disaster bearing data of a forestry environment, determine the disaster bearing shrinkage false alarm rate based on the vegetation layer neighboring disaster bearing data, and perform positive concentration on the vegetation layer fire empowerment factor and the disaster bearing shrinkage false alarm rate to obtain a fire alarm concentration potential value; The fire alarm determination module is used to determine that there is a fire risk in the forestry environment when the fire alarm concentration value is higher than the preset forestry environment fire alarm authority threshold, and send an alarm message to the forestry environment monitoring and control center.

4. A computer device, characterized in that: The computer device includes a memory and a processor, the memory stores codes, and the processor is configured to obtain the codes and execute the forestry environment monitoring method as described in any one of claims 1 to 2.

5. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the forestry environment monitoring method as described in any one of claims 1 to 2 is implemented.

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