Mountain forest fire prevention early warning method and system

Abstract

The invention discloses a mountain forest fire prevention early warning method and system, and belongs to the technical field of forest fire prevention. The method comprises the following steps: acquiring patrol data; early warning of high-temperature fire is carried out; early warning of foggy fire is realized; and fire in sunny days can be warned. The method comprises the following steps: determining an area of which the temperature is not higher than a set temperature threshold value, obtaining current meteorological monitoring information, judging whether fog exists or not, if so, monitoring a forest in real time by using high-definition fog-penetrating imaging equipment, obtaining a monitoring image, analyzing a foggy fire index, and if the foggy fire index exceeds the set threshold value, determining whether the foggy fire index exceeds the set threshold value. And if yes, triggering foggy fire early warning, and if not, not carrying out early warning, so that the probability of fire existence under the foggy condition is judged, the probability of analyzing the foggy fire in combination with the manual patrol result and the forest monitoring image acquired by the high-definition fog-penetrating imaging equipment in the foggy condition is achieved, and the problem that in the prior art, under the dense fog weather condition, the foggy fire early warning cannot be carried out in the foggy condition is solved. And the fire risk cannot be effectively identified.

Description

Technical Field

[0001] The present invention relates to the technical field of forest fire prevention, and in particular to a forest fire prevention early warning method and system in mountainous areas. Background Art

[0002] With the intensification of climate change, the increase of forest resources and the frequent human activities, the probability and severity of fires are also increasing. At present, forest fire early warning technology is developing rapidly, mainly relying on advanced technologies such as remote sensing, Internet of Things, big data and artificial intelligence. Through satellite remote sensing and drone monitoring, forest fire risk index, meteorological data and precursor information of fire can be obtained in real time. At the same time, Internet of Things devices, such as temperature and humidity sensors and smoke detectors, can achieve accurate monitoring in the forest.

[0003] Most of the existing forest fire early warning methods use drone patrols, which collect information and environmental data of forest areas in real time and use these data to plan the patrol routes of drones. Drones patrol forest areas according to predetermined routes to ensure frequent monitoring of fire-prone areas. During the patrol process, drones collect environmental data such as temperature and humidity, smoke, and gas composition through various sensors, and then transmit these data to the information processing platform in real time. The platform analyzes and processes the data, identifies fire risks, and issues early warning information based on the processing results. In addition, the system will dynamically adjust the patrol frequency and route of drones according to the degree of fire susceptibility and patrol needs.

[0004] For example, the invention patent with publication number: CN104217526A discloses a fire warning method and fire isolation method, including: using a flame detection unit to detect the pulse amount and continuous occurrence time of ultraviolet rays in a specific band in the flame; when the pulse amount and continuous occurrence time of ultraviolet rays in a specific band in the flame detected by the flame detection unit reach a predetermined value, the system is awakened to enter a working state and an early warning signal is output. The fire isolation method includes: when the pulse amount and continuous occurrence time of ultraviolet rays in a specific band in the flame detected by the flame detection unit reach a predetermined value and the system is awakened to enter a working state, the automatic directional control nozzle of the spray unit is used to spray a water-based fire extinguishing agent to the fire position to form a fire isolation zone to prevent the spread of the fire.

[0005] For example, the invention patent with publication number: CN118522109A discloses a forest fire warning method and device, including: using the information of the forest area and the environmental information collection unit of the temporary parking platform in each area to plan the patrol route of the drone in real time with the collected information; the drone flies and patrols according to the planned patrol route, obtains patrol information and transmits it to the information processing platform. The processed information is transmitted to the background processor; the background information processor issues warning information based on the received information. The forest is divided into multiple fire-prone areas of different levels, and the patrol routes are planned according to the level of susceptibility. The higher the fire level in the patrol route, the more frequent the patrol, so as to achieve targeted patrols and improve the efficiency of fire warning patrols. The parking platform can better provide parking places for patrolling drones, and temporarily provide parking places during the patrol path, replenish power for drones in time, and extend the length of the drone patrol route.

[0006] However, in the process of implementing the technical solution of the invention in the embodiments of the present application, the present application found that the above technology has at least the following technical problems:

[0007] In the existing technology, dense fog will attenuate optical signals and ultraviolet radiation, resulting in a decrease in the detection capabilities of optical sensors and ultraviolet detectors, thereby limiting the visual range of drone vision and infrared sensors, affecting data collection and fire source identification during inspections. In summary, there is a problem that fire risks cannot be effectively identified under dense fog conditions. Summary of the invention

[0008] In view of the above-mentioned problems, the present invention is proposed.

[0009] Therefore, the problem to be solved by the present invention is that in the prior art, dense fog weather will attenuate optical signals and ultraviolet radiation, resulting in a decrease in the detection capabilities of optical sensors and ultraviolet detectors, and there is a problem that fire risks cannot be effectively identified under dense fog weather conditions.

[0010] To solve the above technical problems, the present invention provides the following technical solutions: a forest fire warning method in mountainous areas, which comprises the following steps: obtaining manual patrol trajectory data and manual patrol monitoring data; real-time monitoring of the forest by high-temperature identification equipment to obtain a forest temperature distribution map, and analyzing a high-temperature fire index according to the forest temperature distribution map, wherein the high-temperature fire index is used to reflect the probability of fire in the forest area under high temperature conditions. If the high-temperature fire index is higher than the high-temperature fire threshold, a high-temperature fire warning is issued; if the high-temperature fire index is not higher than the high-temperature fire threshold, no high-temperature fire warning is issued; for areas in the forest temperature distribution map where the temperature is not higher than the set temperature threshold, current meteorological monitoring information is obtained, and it is determined whether there is fog in the current forest area. If there is fog in the current forest area, a high-definition fog-penetrating imaging device is used to monitor the forest in real time to obtain a forest monitoring image; based on the forest temperature The foggy day fire index is analyzed based on the forest temperature distribution map, forest monitoring images, manual patrol trajectory data and manual patrol monitoring data. The foggy day fire index is used to reflect the probability of fire in the forest area under foggy conditions. If the foggy day fire index is higher than the foggy day fire threshold, a foggy day fire warning is issued. If the foggy day fire index is not higher than the foggy day fire threshold, no foggy day fire warning is issued. If there is no fog in the current forest area, the forest is monitored in real time through video surveillance equipment to obtain forest monitoring videos. Based on the forest temperature distribution map, forest monitoring videos, manual patrol trajectory data and manual patrol monitoring data, the sunny day fire index is analyzed. The sunny day fire index is used to reflect the probability of fire in the forest area under sunny conditions. If the sunny day fire index is higher than the sunny day fire threshold, a sunny day fire warning is issued. If the sunny day fire index is not higher than the sunny day fire threshold, no sunny day fire warning is issued.

[0011] As an optimal solution of the forest fire prevention and early warning method in mountainous areas described in the present invention, the specific method of obtaining the high temperature fire index is: extracting high temperature fire threat data from the forest temperature distribution map, and the high temperature fire threat data includes: temperature peak, maximum temperature gradient in the area where the temperature peak is located, duration of the temperature peak, and contour density of the area where the temperature peak is located; preprocessing the high temperature fire threat data; obtaining the threat factor of the high temperature fire threat data for the high temperature fire index through an objective weighting method; and deriving the high temperature fire index through the high temperature fire index formula based on the high temperature fire threat data and the threat factor.

[0012] As a preferred solution of the forest fire early warning method for mountainous areas described in the present invention, the high temperature fire index formula is:

[0013]

[0014] In the formula, HI i is the high temperature fire index corresponding to the i-th temperature peak, is the i-th temperature peak, is the maximum allowable peak temperature, is the maximum temperature gradient in the area where the i-th temperature peak is located, To allow for temperature gradients, is the duration of the i-th temperature peak, is the duration of the temperature peak, μ i is the contour density of the area where the ith temperature peak is located, μ avg is the average density of the contour lines in the forest area, ε 1 is the peak temperature ratio for HI i The threat factor, ε 2 is the temperature gradient ratio for HI i The threat factor, ε 3 is the contour density ratio for HI i threat factors.

[0015] As a preferred solution of the forest fire prevention and early warning method in mountainous areas described in the present invention, the specific method for obtaining the foggy day fire index is as follows: extracting the first position label and the temperature peak value corresponding to the temperature peak value from the forest temperature distribution map; extracting the image acquisition second position label, the fire source probability judgment result, and the minimum visibility in foggy days from the forest monitoring image; matching the first position label with the second position label to obtain the fire source position label; extracting the third position label from the manual patrol trajectory data; extracting the fourth position label and the flammability level of the tree species from the manual patrol monitoring data; and matching the third position label with the second position label to obtain the fire source position label. The position tag is matched with the fourth position tag to obtain the patrol position tag; the patrol position tag closest to the fire source position tag is counted and recorded as the reference position tag; the temperature peak value corresponding to the fire source position tag, the fire source probability judgment result, the minimum visibility in foggy weather and the flammability level of the tree species corresponding to the reference position tag are recorded as the foggy weather fire threat data; the foggy weather fire threat data is preprocessed; the threat factor of the foggy weather fire threat data for the foggy weather fire index is obtained through the objective weighting method; based on the foggy weather fire threat data and its threat factor, the foggy weather fire index is obtained through the foggy weather fire index formula.

[0016] As a preferred solution of the forest fire early warning method for mountainous areas described in the present invention, the foggy day fire index formula is:

[0017]

[0018] Where FI k is the foggy fire index corresponding to the k-th fire source location label, is the peak temperature corresponding to the kth fire source location label, FP k is the fire source probability discrimination result of the kth fire source location label, FC kis the minimum visibility in foggy weather of the kth fire source location label, FR k is the flammability level of the tree species corresponding to the reference location label of the kth fire source location label, δ 1 for For FI k Threat factor, δ 2 FP k For FI k Threat factor, δ 3 For FR k For FI k Threat factor, δ 4 For FC k For FI k threat factors.

[0019] As a preferred embodiment of the forest fire prevention and early warning method in mountainous areas described in the present invention, the foggy day fire warning specifically refers to: when the foggy day fire index of a certain fire source location tag is higher than the foggy day fire threshold, the foggy day fire index of the fire source location tag continues to be tracked; if the foggy day fire index no longer increases, the patrol personnel closest to the fire source location tag is immediately notified to check the fire source; if the patrol personnel confirms the fire, an alarm is immediately sounded; if the foggy day fire index continues to increase, an alarm is directly sounded.

[0020] As a preferred solution of the forest fire prevention and early warning method in mountainous areas described in the present invention, the specific method for obtaining the sunny day fire index is as follows: extracting the first positioning tag and the temperature peak value corresponding to the temperature peak value from the forest temperature distribution map; extracting the second positioning tag of video acquisition, the fire source identification result, and the accumulation area of ​​flammable vegetation from the forest monitoring video; matching the first positioning tag with the second positioning tag to obtain the fire source positioning tag; extracting the third positioning tag from the manual patrol trajectory data; extracting the fourth positioning tag, the flammability level of the tree species, and the air humidity in the forest from the manual patrol monitoring data; and matching the third positioning tag with the second positioning tag to obtain the fire source positioning tag. The positioning tag is matched with the fourth positioning tag to obtain the patrol positioning tag; the patrol positioning tag closest to the fire source positioning tag is counted and recorded as the reference positioning tag; the temperature peak value, fire source identification result, flammable vegetation accumulation area corresponding to the fire source positioning tag, and the flammability level of the tree species and forest air humidity corresponding to the reference positioning tag are recorded as sunny day fire threat data; the sunny day fire threat data is preprocessed; the threat factor of the sunny day fire threat data for the sunny day fire index is obtained through the objective weighting method; based on the sunny day fire threat data and its threat factor, the sunny day fire index is obtained through the sunny day fire index formula.

[0021] As a preferred solution of the forest fire early warning method for mountainous areas described in the present invention, the sunny day fire index formula is:

[0022]

[0023] Where, SI g is the sunny day fire index corresponding to the g-th fire source location label, is the temperature peak value corresponding to the g-th fire source location tag, SP g is the fire source identification result of the g-th fire source location tag, SD g The flammable vegetation accumulation area of ​​the g-th fire source location tag, FR g is the flammability level of the tree species corresponding to the reference location label of the g-th fire source location label, HW g is the forest air humidity corresponding to the reference positioning label of the g-th fire source positioning label, ω 1 for For SI g Threat factor, ω 2 For SP g For SI g Threat factor, ω 3 For SD g *FR g For SI g Threat factor, ω 4 For HW g For SI g threat factors.

[0024] As a preferred embodiment of the forest fire prevention and early warning method in mountainous area described in the present invention, the sunny day fire warning specifically refers to: when the sunny day fire index of a certain fire source location tag is higher than the sunny day fire threshold, the sunny day fire index of the fire source location tag continues to be tracked; if the sunny day fire index no longer increases, the patrol personnel closest to the fire source location tag is immediately notified to check the fire source; if the patrol personnel confirms the fire, an alarm is immediately sounded; if the sunny day fire index continues to increase, an alarm is directly sounded.

[0025] Another object of the present invention is to provide a mountain forest fire warning system, which can be used to analyze the probability of fire in foggy days by combining manual patrol results and forest monitoring images collected by high-definition fog-penetrating imaging equipment.

[0026] To solve the above technical problems, the present invention provides the following technical solutions: a system for implementing a forest fire prevention and early warning method in mountainous areas, comprising: a patrol data acquisition module, a high temperature fire warning module, a foggy day fire warning module, and a sunny day fire warning module; wherein the patrol data acquisition module is used to obtain manual patrol trajectory data and manual patrol monitoring data; the high temperature fire warning module is used to monitor the forest in real time through a high temperature identification device to obtain a forest temperature distribution map, and analyze a high temperature fire index according to the forest temperature distribution map. The high temperature fire index is used to reflect the probability of the existence of a fire in the forest area under high temperature conditions. If the high temperature fire index is higher than the high temperature fire threshold, a high temperature fire warning is issued. If the high temperature fire index is not higher than the high temperature fire threshold, no high temperature fire warning is issued. The foggy day fire warning module is used to obtain current meteorological monitoring information for areas in the forest temperature distribution map where the temperature is not higher than the set temperature threshold, and to determine whether there is fog in the current forest area. If there is fog in the current forest area, Use high-definition fog-penetrating imaging equipment to monitor the forest in real time and obtain forest monitoring images; analyze the foggy day fire index based on the forest temperature distribution map, forest monitoring images, manual patrol trajectory data and manual patrol monitoring data, the foggy day fire index is used to reflect the probability of fire in the forest area under foggy conditions. If the foggy day fire index is higher than the foggy day fire threshold, a foggy day fire warning is issued; if the foggy day fire index is not higher than the foggy day fire threshold, no foggy day fire warning is issued. The sunny day fire warning module is used to monitor the forest in real time through video surveillance equipment to obtain forest monitoring videos if there is no fog in the current forest area; analyze the sunny day fire index based on the forest temperature distribution map, forest monitoring videos, manual patrol trajectory data and manual patrol monitoring data, the sunny day fire index is used to reflect the probability of fire in the forest area under sunny conditions. If the sunny day fire index is higher than the sunny day fire threshold, a sunny day fire warning is issued; if the sunny day fire index is not higher than the sunny day fire threshold, no sunny day fire warning is issued.

[0027] The beneficial effects of the present invention are as follows: the present invention analyzes the probability of fire in foggy days by combining the results of manual patrols with forest monitoring images collected by high-definition fog-penetrating imaging equipment on foggy days, thereby realizing the probability of judging the existence of fire in foggy days, and effectively solving the problem in the prior art that fire risks cannot be effectively identified under dense fog weather conditions.

[0028] The present invention combines the fire source location tag with the patrol location tag to quickly identify patrol personnel near the fire source, so that when a fire occurs, the nearest patrol force can be quickly deployed to the scene for inspection, greatly shortening the time from fire discovery to response, thereby improving the efficiency and accuracy of fire emergency response.

[0029] The present invention can promptly capture any abnormal fluctuations in the foggy fire index by accurately tracking the fire source and real-time monitoring of fire changes. When it is monitored that the foggy fire index exceeds the preset foggy fire threshold, an early warning is quickly initiated, thereby greatly improving the efficiency of fire detection and handling and effectively preventing the spread of fire. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0031] Figure 1 This is a flow chart of a forest fire early warning method in a mountain area in Example 1;

[0032] Figure 2 This is a structural diagram of a mountain forest fire warning system in Example 2. DETAILED DESCRIPTION

[0033] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the accompanying drawings.

[0034] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0035] Example 1

[0036] This embodiment 1 provides a forest fire warning method in mountainous areas, which solves the problem in the prior art that fire risks cannot be effectively identified under dense fog weather conditions. By combining manual patrol results and forest monitoring images collected by high-definition fog-penetrating imaging equipment on foggy days, the probability of fire on foggy days is analyzed, thereby realizing the probability of judging the existence of fire on foggy days.

[0037] 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.

[0038] Figure 1 A flow chart of a mountain forest fire warning method provided in Example 1 of the present application is applied to a mountain forest fire warning system. The method includes the following steps: obtaining patrol data: obtaining manual patrol trajectory data and manual patrol monitoring data.

[0039] Early warning of high temperature fire: Real-time monitoring of the forest is carried out through high temperature identification equipment to obtain the forest temperature distribution map. The high temperature fire index is analyzed based on the forest temperature distribution map. The high temperature fire index is used to reflect the probability of fire in the forest area under high temperature conditions. If the high temperature fire index is higher than the high temperature fire threshold, a high temperature fire early warning will be issued. If the high temperature fire index is not higher than the high temperature fire threshold, no high temperature fire early warning will be issued.

[0040] Early warning of fire in foggy weather: For areas in the forest temperature distribution map where the temperature is not higher than the set temperature threshold, obtain the current meteorological monitoring information and determine whether there is fog in the current forest area. If there is fog in the current forest area, use high-definition fog-penetrating imaging equipment to monitor the forest in real time and obtain forest monitoring images.

[0041] Based on the forest temperature distribution map, forest monitoring images, manual patrol trajectory data and manual patrol monitoring data, the foggy day fire index is analyzed. The foggy day fire index is used to reflect the probability of the existence of a fire in the forest area in foggy days. If the foggy day fire index is higher than the foggy day fire threshold, a foggy day fire warning will be issued. If the foggy day fire index is not higher than the foggy day fire threshold, no foggy day fire warning will be issued.

[0042] Early warning of fire on sunny days: If there is no fog in the current forest area, the forest will be monitored in real time through video surveillance equipment to obtain forest monitoring video.

[0043] Based on the forest temperature distribution map, forest monitoring video, manual patrol trajectory data and manual patrol monitoring data, the sunny day fire index is analyzed. The sunny day fire index is used to reflect the probability of the existence of a fire in the forest area on a sunny day. If the sunny day fire index is higher than the sunny day fire threshold, a sunny day fire warning will be issued. If the sunny day fire index is not higher than the sunny day fire threshold, no sunny day fire warning will be issued.

[0044] Furthermore, the specific method of obtaining the high temperature fire index is: extracting high temperature fire threat data from the forest temperature distribution map, the high temperature fire threat data including: temperature peak, maximum temperature gradient in the area where the temperature peak is located, duration of the temperature peak, and contour density in the area where the temperature peak is located; preprocessing the high temperature fire threat data; obtaining the threat factor of the high temperature fire threat data for the high temperature fire index through an objective weighting method; and deriving the high temperature fire index through the high temperature fire index formula based on the high temperature fire threat data and threat factors.

[0045] Among them, preprocessing at least includes standardization processing to unify and eliminate units.

[0046] Furthermore, the high temperature fire index formula is:

[0047]

[0048] In the formula, HI i is the high temperature fire index corresponding to the i-th temperature peak, is the i-th temperature peak, is the maximum allowable peak temperature, is the maximum temperature gradient in the area where the i-th temperature peak is located, To allow for temperature gradients, is the duration of the i-th temperature peak, is the duration of the temperature peak, μ i is the contour density of the area where the ith temperature peak is located, μ avg is the average density of the contour lines in the forest area, ε 1 is the peak temperature ratio for HI i The threat factor, ε 2 is the temperature gradient ratio for HI i The threat factor, ε 3 is the contour density ratio for HI i threat factors.

[0049] Among them, when is 36 degrees Celsius, is 34 degrees Celsius, is 10 degrees Celsius, is 2 degrees Celsius, is 0.028 days, is 0.040 days, μ i 2 lines / hectare (where the contour interval unit is 1*10 2 m), μ avg 1.2 per hectare, ε 1 is 0.2, ε 2 is 0.5, ε 3 0.3, HI i The higher the high temperature fire index is, the higher the probability of fire due to high temperature is.

[0050] when is 26 degrees Celsius, is 34 degrees Celsius, is 3 degrees Celsius, is 2 degrees Celsius, is 0.013 days, is 0.040 days, μ i 1 line / hectare (where the contour interval unit is 1*10 2 m), μ avg 1.2 per hectare, ε 1 is 0.2, ε 2 is 0.5, ε3 0.3, HI i The lower the high temperature fire index is, the lower the probability of fire due to high temperature is.

[0051] Furthermore, the specific method for obtaining the foggy day fire index is as follows: extract the first position label and the temperature peak value corresponding to the temperature peak value from the forest temperature distribution map; extract the second position label of image acquisition, the fire source probability judgment result, and the minimum visibility in foggy day from the forest monitoring image; match the first position label with the second position label to obtain the fire source position label; extract the third position label from the manual patrol trajectory data; extract the fourth position label and the flammability level of the tree species from the manual patrol monitoring data; match the third position label with the fourth position label to obtain the patrol position label; count the patrol position labels closest to the fire source position label and record them as reference position labels; record the temperature peak value corresponding to the fire source position label, the fire source probability judgment result, the minimum visibility in foggy day, and the flammability level of the tree species corresponding to the reference position label as foggy day fire threat data; preprocess the foggy day fire threat data; obtain the threat factor of the foggy day fire threat data to the foggy day fire index through the objective weighting method; based on the foggy day fire threat data and its threat factor, the foggy day fire index is obtained through the foggy day fire index formula.

[0052] In this embodiment, under foggy conditions, traditional monitoring methods (such as infrared monitoring, visual monitoring, etc.) are easily affected, making it difficult to identify the fire source. The high-definition fog-penetrating imaging equipment can penetrate the thick fog, obtain clearer forest monitoring images and conduct real-time monitoring. Although the forest monitoring images obtained are clearer, due to the interference of tall trees in the forest, there are many visual blind spots that make it difficult to directly identify whether there is a fire at the location where the current high-definition fog-penetrating imaging equipment is located in foggy conditions. In addition, in foggy conditions, there are situations where flames and lights are difficult to distinguish. Therefore, this embodiment uses the fire source probability judgment results and corresponding positions identified by the high-definition fog-penetrating imaging equipment, combined with manual patrol monitoring data to analyze the probability of fire occurring in the vicinity of the location, which can solve the problem of limited visibility of traditional monitoring equipment in foggy days, and facilitate accurate judgment of the location of the fire source.

[0053] Furthermore, the formula for the foggy fire index is:

[0054]

[0055] Where FI k is the foggy fire index corresponding to the k-th fire source location label, is the peak temperature corresponding to the kth fire source location label, FP k is the fire source probability discrimination result of the kth fire source location label, FC kis the minimum visibility in foggy weather of the kth fire source location label, FR k is the flammability level of the tree species corresponding to the reference location label of the kth fire source location label, δ 1 for For FI k Threat factor, δ 2 FP k For FI k Threat factor, δ 3 For FR k For FI k Threat factor, δ 4 For FC k For FI k threat factors.

[0056] in, 28 degrees Celsius, FP k 0.78, FC k 0.56km, FR k is 3,δ 1 is 0.2, δ 2 is 0.4, δ 3 is 0.2, δ 4 is 0.2, and FI is obtained k The larger the foggy fire index is, the greater the probability that there is a fire at the kth fire source location label in foggy weather.

[0057] It should be explained that the temperature peak is obtained by high temperature recognition equipment, such as a thermal imaging camera. The fire source probability discrimination result is obtained by analyzing the forest monitoring image through image processing or machine learning algorithms. For example, the probability of the existence of the fire source is determined by identifying features such as hot spots, smoke, and spectral changes in the image. The minimum visibility on foggy days is obtained by a visibility sensor or an atmospheric transmission meter.

[0058] The flammability level of tree species can be obtained through a machine learning model, for example: by obtaining historical meteorological data (such as humidity, wind speed, temperature, etc.), historical fire data and tree species attributes (such as oil content, leaf moisture content, growth cycle, etc.), preprocessing the above-obtained data, and extracting features from the preprocessed data, dividing the extracted features into a training set and a test set, using the training set data to train the machine learning model, using the test set to evaluate the trained machine learning model, and generating a final model for analyzing the flammability of tree species under different climatic conditions. Set multiple thresholds to determine the flammability level of tree species based on the position of the predicted probability of the flammability of the tree species obtained by the final model between the set thresholds. In this embodiment, the more flammable the tree species, the higher the corresponding tree species flammability level.

[0059] Furthermore, the foggy day fire warning specifically means: when the foggy day fire index of a certain fire source location tag is higher than the foggy day fire threshold, the foggy day fire index of the fire source location tag will continue to be tracked. If the foggy day fire index no longer increases, the patrol personnel closest to the fire source location tag will be immediately notified to check the fire source. If the patrol personnel confirms the fire, the police will be immediately called; if the foggy day fire index continues to increase, the police will be called directly.

[0060] Furthermore, the specific method for obtaining the sunny day fire index is as follows: extract the first positioning tag and the temperature peak value corresponding to the temperature peak value from the forest temperature distribution map; extract the second positioning tag of video acquisition, the fire source identification result, and the accumulation area of ​​flammable vegetation from the forest monitoring video; locate and match the first positioning tag with the second positioning tag to obtain the fire source positioning tag; extract the third positioning tag from the manual patrol trajectory data; extract the fourth positioning tag, the flammability level of the tree species, and the air humidity in the forest from the manual patrol monitoring data; locate and match the third positioning tag with the fourth positioning tag to obtain the patrol positioning tag; count the patrol positioning tags closest to the fire source positioning tag and record them as reference positioning tags; record the temperature peak value, fire source identification result, and accumulation area of ​​flammable vegetation corresponding to the fire source positioning tag, and the flammability level of the tree species and the air humidity in the forest corresponding to the reference positioning tag as sunny day fire threat data; pre-process the sunny day fire threat data; obtain the threat factor of the sunny day fire threat data for the sunny day fire index through the objective weighting method; based on the sunny day fire threat data and its threat factor, the sunny day fire index is obtained through the sunny day fire index formula.

[0061] Furthermore, the sunny day fire index formula is:

[0062]

[0063] Where, SI g is the sunny day fire index corresponding to the g-th fire source location label, is the temperature peak value corresponding to the g-th fire source location tag, SP g is the fire source identification result of the g-th fire source location tag, SD g The flammable vegetation accumulation area of ​​the g-th fire source location tag, FR g is the flammability level of the tree species corresponding to the reference location label of the g-th fire source location label, HW g is the forest air humidity corresponding to the reference positioning label of the g-th fire source positioning label, ω 1 for For SI g Threat factor, ω 2 For SP g For SI g Threat factor, ω 3 For SD g *FRg For SI g Threat factor, ω 4 For HW g For SI g threat factors.

[0064] in, 32 degrees Celsius, SP g 0.68, SD g 0.08 hectares, FR g 3, HW g 0.74rh,ω 1 is 0.35, δ 2 is 0.35, δ 3 is 0.2, δ 4 0.2, SI g The higher the sunny day fire index is, the greater the probability of fire on sunny days.

[0065] Furthermore, the sunny day fire warning specifically means: when the sunny day fire index of a certain fire source location tag is higher than the sunny day fire threshold, the sunny day fire index of the fire source location tag will continue to be tracked. If the sunny day fire index no longer increases, the patrol personnel closest to the fire source location tag will be immediately notified to check the fire source. If the patrol personnel confirms the fire, the police will be immediately called; if the sunny day fire index continues to increase, the police will be called directly.

[0066] Example 2

[0067] Different from the first embodiment, this embodiment 2 provides a system for implementing a forest fire early warning method in mountainous areas. Figure 2 The shown modules include: patrol data acquisition module, high temperature fire warning module, foggy day fire warning module, and sunny day fire warning module.

[0068] Among them, the patrol data acquisition module is used to obtain manual patrol trajectory data and manual patrol monitoring data.

[0069] The high temperature fire warning module is used to monitor the forest in real time through high temperature identification equipment, obtain the forest temperature distribution map, and analyze the high temperature fire index based on the forest temperature distribution map. The high temperature fire index is used to reflect the probability of fire in the forest area under high temperature conditions. If the high temperature fire index is higher than the high temperature fire threshold, a high temperature fire warning will be issued. If the high temperature fire index is not higher than the high temperature fire threshold, no high temperature fire warning will be issued.

[0070] The foggy fire warning module is used to obtain current meteorological monitoring information for areas in the forest temperature distribution map where the temperature is not higher than the set temperature threshold, and to determine whether there is fog in the current forest area. If there is fog in the current forest area, high-definition fog-penetrating imaging equipment is used to monitor the forest in real time and obtain forest monitoring images.

[0071] The foggy day fire index is analyzed based on the forest temperature distribution map, forest monitoring images, manual patrol trajectory data and manual patrol monitoring data. The foggy day fire index is used to reflect the probability of fire in the forest area under foggy conditions. If the foggy day fire index is higher than the foggy day fire threshold, a foggy day fire warning will be issued. If the foggy day fire index is not higher than the foggy day fire threshold, no foggy day fire warning will be issued.

[0072] The sunny day fire warning module is used to monitor the forest in real time through video surveillance equipment and obtain forest monitoring videos if there is no fog in the current forest area.

[0073] Based on the forest temperature distribution map, forest monitoring video, manual patrol trajectory data and manual patrol monitoring data, the sunny day fire index is analyzed. The sunny day fire index is used to reflect the probability of the existence of a fire in the forest area on a sunny day. If the sunny day fire index is higher than the sunny day fire threshold, a sunny day fire warning will be issued. If the sunny day fire index is not higher than the sunny day fire threshold, no sunny day fire warning will be issued.

[0074] In summary, the embodiments of the present application analyze the probability of fire in foggy days by combining the results of manual patrols and forest monitoring images collected by high-definition fog-penetrating imaging equipment, thereby realizing the probability of judging the existence of fire in foggy days.

[0075] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0076] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0077] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0078] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process in the computer or other programmable device. Figure 1 A process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0079] Although the preferred embodiments of the present invention 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 that fall within the scope of the present invention.

[0080] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A forest fire early warning method in mountainous areas, characterized in that: The following steps are involved: Obtain manual patrol trajectory data and manual patrol monitoring data; Real-time monitoring of the forest is performed through high-temperature identification equipment to obtain a forest temperature distribution map, and a high-temperature fire index is analyzed based on the forest temperature distribution map. The high-temperature fire index is used to reflect the probability of fire in the forest area under high temperature conditions. If the high-temperature fire index is higher than the high-temperature fire threshold, a high-temperature fire warning is issued. If the high-temperature fire index is not higher than the high-temperature fire threshold, no high-temperature fire warning is issued; For areas in the forest temperature distribution map where the temperature is not higher than the set temperature threshold, obtain the current meteorological monitoring information and determine whether there is fog in the current forest area. If there is fog in the current forest area, use high-definition fog-penetrating imaging equipment to monitor the forest in real time and obtain forest monitoring images; Based on the forest temperature distribution map, forest monitoring images, manual patrol trajectory data and manual patrol monitoring data, the foggy day fire index is analyzed. The foggy day fire index is used to reflect the probability of fire in the forest area under foggy conditions. If the foggy day fire index is higher than the foggy day fire threshold, a foggy day fire warning is issued. If the foggy day fire index is not higher than the foggy day fire threshold, no foggy day fire warning is issued. If there is no fog in the current forest area, the forest is monitored in real time through video surveillance equipment to obtain forest surveillance video; Based on the forest temperature distribution map, forest monitoring video, manual patrol trajectory data and manual patrol monitoring data, the sunny day fire index is analyzed. The sunny day fire index is used to reflect the probability of the existence of a fire in the forest area on a sunny day. If the sunny day fire index is higher than the sunny day fire threshold, a sunny day fire warning is issued. If the sunny day fire index is not higher than the sunny day fire threshold, no sunny day fire warning is issued.

2. A mountain forest fire early warning method as claimed in claim 1, characterized in that: The specific method of obtaining the high temperature fire index is as follows: Extract high temperature fire threat data from the forest temperature distribution map, wherein the high temperature fire threat data includes: temperature peak, maximum temperature gradient in the area where the temperature peak is located, duration of the temperature peak, and contour line density in the area where the temperature peak is located; Preprocessing of high temperature fire threat data; The threat factor of high temperature fire threat data to high temperature fire index is obtained through objective weighting method; Based on the high temperature fire threat data and threat factors, the high temperature fire index is obtained through the high temperature fire index formula.

3. A mountain forest fire early warning method as claimed in claim 2, characterized in that: The high temperature fire index formula is: In the formula, HI i is the high temperature fire index corresponding to the i-th temperature peak, is the i-th temperature peak, is the maximum allowable peak temperature, is the maximum temperature gradient in the area where the i-th temperature peak is located, To allow for temperature gradients, is the duration of the i-th temperature peak, is the duration of the temperature peak, μ i is the contour density of the area where the ith temperature peak is located, μ avg is the average density of contour lines in the forest area, ε1 is the peak temperature ratio to HI i The threat factor, ε2 is the temperature gradient ratio for HI i Threat factor, ε3 is the contour density ratio for HI i threat factors.

4. A mountain forest fire early warning method as claimed in claim 1, characterized in that: The specific method of obtaining the foggy fire index is as follows: Extract the first position label and the temperature peak value corresponding to the temperature peak value from the forest temperature distribution map; Extract the image acquisition second position label, fire source probability discrimination result, and foggy minimum visibility from the forest monitoring image; Positionally matching the first position tag with the second position tag to obtain a fire source position tag; Extracting a third location tag from manual patrol trajectory data; Extract the fourth location tag and tree species flammability level from the manual patrol monitoring data; Performing position matching on the third position tag and the fourth position tag to obtain a patrol position tag; Count the patrol location tags closest to the fire source location tags and record them as reference location tags; The temperature peak value corresponding to the fire source location label, the fire source probability judgment result, the minimum visibility in foggy weather, and the flammability level of the tree species corresponding to the reference location label are recorded as the foggy weather fire threat data; Preprocess the fire threat data in foggy weather; The threat factor of foggy day fire threat data to foggy day fire index is obtained through objective weighting method; Based on the foggy day fire threat data and its threat factors, the foggy day fire index is derived using the foggy day fire index formula.

5. A mountain forest fire early warning method as claimed in claim 4, characterized in that: The foggy day fire index formula is: In the formula, FI k is the foggy fire index corresponding to the k-th fire source location label, is the peak temperature corresponding to the kth fire source location label, FP k is the fire source probability discrimination result of the kth fire source location label, FC k is the minimum visibility in foggy weather of the kth fire source location label, FR k is the flammability level of the tree species corresponding to the reference location label of the kth fire source location label, δ1 is For FI k Threat factor, δ2 is FP k For FI k Threat factor, δ3 is FR k For FI k Threat factor, δ4 is FC k For FI k threat factors.

6. A mountain forest fire early warning method as claimed in claim 4, characterized in that: The foggy day fire warning specifically refers to: When the foggy day fire index of a fire source location tag is higher than the foggy day fire threshold, the foggy day fire index of the fire source location tag will continue to be tracked. If the foggy day fire index does not increase any more, the patrol personnel closest to the fire source location tag will be notified immediately to check the fire source. If the patrol personnel confirm the fire, the police will be called immediately. If the fire index continues to rise in foggy weather, call the police directly.

7. A mountain forest fire early warning method as claimed in claim 1, characterized in that: The specific method for obtaining the sunny day fire index is as follows: Extracting a first positioning label and a temperature peak value corresponding to a temperature peak value from a forest temperature distribution map; Extract the second positioning tag of video acquisition, fire source identification result, and flammable vegetation accumulation area from the forest monitoring video; Positioning and matching the first positioning tag with the second positioning tag to obtain a fire source positioning tag; Extracting the third positioning tag from the manual patrol trajectory data; Extract the fourth location tag, tree species flammability level, and forest air humidity from the manual patrol monitoring data; Performing positioning matching on the third positioning tag and the fourth positioning tag to obtain a patrol positioning tag; Count the patrol location tags closest to the fire source location tags and record them as reference location tags; The temperature peak value, fire source identification result, flammable vegetation accumulation area corresponding to the fire source location tag, and the flammability level of the tree species and forest air humidity corresponding to the reference location tag are recorded as the sunny day fire threat data; Preprocess the sunny day fire threat data; The threat factor of sunny day fire threat data to sunny day fire index is obtained through objective weighting method; Based on the sunny day fire threat data and its threat factors, the sunny day fire index is obtained using the sunny day fire index formula.

8. A mountain forest fire early warning method as claimed in claim 7, characterized in that: The sunny day fire index formula is: Where, SI g is the sunny day fire index corresponding to the g-th fire source location label, is the temperature peak value corresponding to the g-th fire source location tag, SP g is the fire source identification result of the g-th fire source location tag, SD g The flammable vegetation accumulation area of ​​the g-th fire source location tag, FR g is the flammability level of the tree species corresponding to the reference location label of the g-th fire source location label, HW g is the forest air humidity corresponding to the reference positioning label of the g-th fire source positioning label, ω1 is For SI g Threat factor, ω2 is SP g For SI g Threat factor, ω3 is SD g *FR g For SI g Threat factor, ω4 is HW g For SI g threat factors.

9. A mountain forest fire early warning method as claimed in claim 1, characterized in that: The sunny day fire warning specifically refers to: When the sunny day fire index of a fire source location tag is higher than the sunny day fire threshold, the sunny day fire index of the fire source location tag will continue to be tracked. If the sunny day fire index does not increase any more, the patrol personnel closest to the fire source location tag will be notified immediately to check the fire source. If the patrol personnel confirm the fire, the police will be called immediately. If the fire index continues to rise on a sunny day, call the police directly.

10. A mountain forest fire early warning system, applied to a mountain forest fire early warning method according to any one of claims 1 to 9, characterized in that: include: Patrol data acquisition module, high temperature fire warning module, foggy day fire warning module, sunny day fire warning module; Wherein, the patrol data acquisition module is used to obtain manual patrol trajectory data and manual patrol monitoring data; The high temperature fire warning module is used to monitor the forest in real time through the high temperature identification equipment, obtain the forest temperature distribution map, and analyze the high temperature fire index according to the forest temperature distribution map. The high temperature fire index is used to reflect the probability of fire in the forest area under high temperature conditions. If the high temperature fire index is higher than the high temperature fire threshold, a high temperature fire warning is issued. If the high temperature fire index is not higher than the high temperature fire threshold, no high temperature fire warning is issued. The foggy fire warning module is used to obtain current meteorological monitoring information for areas in the forest temperature distribution map where the temperature is not higher than the set temperature threshold, and to determine whether there is fog in the current forest area. If there is fog in the current forest area, a high-definition fog-penetrating imaging device is used to monitor the forest in real time to obtain forest monitoring images; Based on the forest temperature distribution map, forest monitoring images, manual patrol trajectory data and manual patrol monitoring data, the foggy day fire index is analyzed. The foggy day fire index is used to reflect the probability of fire in the forest area under foggy conditions. If the foggy day fire index is higher than the foggy day fire threshold, a foggy day fire warning is issued. If the foggy day fire index is not higher than the foggy day fire threshold, no foggy day fire warning is issued. The sunny day fire warning module is used to monitor the forest in real time through video monitoring equipment to obtain forest monitoring video if there is no fog in the current forest area; Based on the forest temperature distribution map, forest monitoring video, manual patrol trajectory data and manual patrol monitoring data, the sunny day fire index is analyzed. The sunny day fire index is used to reflect the probability of the existence of a fire in the forest area on a sunny day. If the sunny day fire index is higher than the sunny day fire threshold, a sunny day fire warning is issued. If the sunny day fire index is not higher than the sunny day fire threshold, no sunny day fire warning is issued.

Images