CN112216052A - Forest fire prevention monitoring and early warning method, device and equipment and storage medium - Google Patents
Forest fire prevention monitoring and early warning method, device and equipment and storage medium Download PDFInfo
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Abstract
The application relates to a forest fire prevention monitoring and early warning method, which comprises the following steps: acquiring image data of a monitored area; the image data is acquired in real time by image acquisition equipment arranged at a monitoring point; analyzing the image data, identifying a firework area from the image data and determining the geographic position of the firework area; acquiring a current remote sensing image at a geographic position, and carrying out forest fire dynamic simulation on an electronic map by taking a fire point of a firework area as a center according to the current remote sensing image to obtain a fire development prediction result; the current remote sensing image is obtained by calling a remote sensing satellite and collecting the area at the geographic position by the remote sensing satellite. The method and the device realize the prediction of the fire development trend of the current fire area in the forest area, so that fire rescue workers can rapidly appoint corresponding rescue measures according to the fire prediction result, the fire rescue efficiency is effectively improved, and the fire loss is reduced.
Description
Technical Field
The application relates to the technical field of forest fire prevention monitoring, in particular to a forest fire prevention monitoring and early warning method, a forest fire prevention monitoring and early warning device, forest fire prevention monitoring and early warning equipment and a storage medium.
Background
At present, forest fire prevention monitoring means include various means, such as: ground manual patrol, watchtower monitoring, infrared video monitoring, satellite remote sensing monitoring and the like. The fire condition is judged on site by decision-making personnel by adopting the mode of monitoring the ground manual patrol and the observation tower, so that the fire early warning mode of monitoring the ground manual patrol and the observation tower is greatly influenced by the observation factor, the efficiency is lower, and great personnel potential safety hazards exist. And an infrared video monitoring mode and a satellite remote sensing monitoring mode are adopted, so that although the situation of on-site judgment of personnel is avoided, effective reference data cannot be provided when a forest fire disaster occurs, and the fire disaster suppression is assisted.
Disclosure of Invention
In view of this, the application provides a forest fire prevention monitoring and early warning method, which can predict the development trend of a fire, thereby providing a reference basis for fire rescue.
According to one aspect of the application, a forest fire prevention monitoring and early warning method is provided, which comprises the following steps:
acquiring image data of a monitored area; the image data is acquired in real time by image acquisition equipment arranged at a monitoring point;
analyzing the image data, identifying a firework area from the image data and determining the geographic position of the firework area;
acquiring a current remote sensing image at the geographic position, and carrying out forest fire dynamic simulation on an electronic map by taking the fire point of the firework area as a center according to the current remote sensing image to obtain a fire development prediction result;
and acquiring the region of the geographic position by the remote sensing satellite by calling the remote sensing satellite from the current remote sensing image.
In one possible implementation, the image capturing device is disposed at a base station at the monitored area or at the top of a building in a forest;
the image acquisition equipment comprises a camera, a telephoto lens and a thermal imaging lens, wherein the telephoto lens is configured on the camera and used for acquiring images of the monitored area, and the thermal imaging lens is used for acquiring a thermal imaging graph of the monitored area.
In one possible implementation, analyzing the image data, and identifying a smoke region from the image data includes:
after preprocessing the image data, analyzing the image data by adopting a forest fire smoke detection algorithm, and identifying smoke and fire candidate areas from the image data;
inputting the firework candidate area into a two-dimensional convolutional neural network, performing feature extraction and identification on the firework candidate area by the two-dimensional convolutional neural network according to the difference between fireworks and interference factors, and determining a firework area from the firework candidate area;
wherein the disturbance factor comprises at least one of fog, cloud, and surface reflection.
In one possible implementation, the determining the geographic location of the pyrotechnic region includes:
acquiring acquisition parameters of the image data; wherein the acquisition parameter comprises at least one of an installation height of the image acquisition device, an acquisition orientation of the image acquisition device, and a focal length of the image acquisition device;
and determining the geographic position of the firework area by combining the GIS and the GPS according to the acquisition parameters.
In one possible implementation manner, the method further includes:
acquiring a satellite image acquired by the remote sensing satellite, and preprocessing the satellite image to obtain a corresponding digital elevation model;
acquiring a prediction parameter related to fire danger from the satellite image; wherein the prediction parameters include at least one of normalized vegetation number, normalized multiband drought index, relative humidity, precipitation, and surface temperature;
calculating to obtain a fire risk potential index by combining the prediction parameters;
and determining the risk level of fire danger in the geographic range corresponding to the acquired satellite image according to the fire danger potential index.
In a possible implementation manner, the calculating, in combination with the prediction parameter, a fire risk potential index includes:
calculating to obtain the water content of the vegetation combustible according to the prediction parameters;
analyzing the dryness of the humus layer, the peat layer, the ground and the overground fuel based on the water content of the vegetation combustible;
calculating vegetation coverage according to a satellite picture, and calculating to obtain the fire hazard potential index by combining with the water content of the vegetation combustible;
wherein, the calculation formula of the fire risk potential index is as follows:
FPI＝100*(1-FMC10hr)*(1-VC)；
wherein FPI is the fire hazard potential index, FMC10hrThe water content of the vegetation combustibles after correction is 10 hours, and VC is the vegetation coverage.
In one possible implementation manner, the method further includes:
acquiring a remote sensing image before disaster and a remote sensing image after disaster by the remote sensing satellite;
comparing the remote sensing image before the disaster with the remote sensing image after the disaster, identifying a fire passing area and calculating to obtain the area of the fire passing area;
and calculating a combustion area index based on the area of the fire passing area, and evaluating the combustion damage degree of the fire passing area according to the combustion area index.
According to an aspect of this application, still provide a forest fire prevention monitoring and early warning device, include: the device comprises a data acquisition module, a data analysis module and a fire prediction module;
the data acquisition module is configured to acquire image data at a monitored area; the image data is acquired in real time by image acquisition equipment arranged at a monitoring point;
the data analysis module is configured to analyze the image data, identify a firework area from the image data and determine a geographic position of the firework area;
the fire prediction module is configured to acquire a current remote sensing image at the geographic position, and dynamically simulate forest fire on an electronic map by taking a fire point of the firework area as a center according to the current remote sensing image to obtain a fire development prediction result;
and acquiring the region of the geographic position by the remote sensing satellite by calling the remote sensing satellite from the current remote sensing image.
According to another aspect of this application, still provide a forest fire prevention monitoring and early warning equipment, include:
a processor;
a memory for storing processor-executable instructions;
wherein the processor is configured to execute the executable instructions to implement any of the methods described above.
According to an aspect of the application, there is also provided a non-transitory computer readable storage medium having stored thereon computer program instructions which, when executed by a processor, implement the method of any of the preceding.
The image data of the monitored area is collected by the image collecting device arranged at the monitoring point, and then the image data is analyzed according to the collected image data, so that the firework area is identified from the image data. As will be understood by those skilled in the art, the smoke and fire area refers to an area in the image data where a fire occurs. When the firework area is identified from the image data, the remote sensing satellite is called again, the remote sensing satellite acquires the current remote sensing image of the geographic position of the firework area, forest fire dynamic simulation is carried out on the electronic map by taking the firework area as the center according to the acquired current remote sensing image, so that a corresponding fire development prediction result is obtained, the prediction of the fire development trend of the area where the fire happens currently in the forest area is finally realized, and therefore fire rescue personnel can rapidly designate corresponding rescue measures according to the fire prediction result, the fire rescue efficiency is effectively improved, and the fire loss is reduced.
Other features and aspects of the present application will become apparent from the following detailed description of exemplary embodiments, which proceeds with reference to the accompanying drawings.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate exemplary embodiments, features, and aspects of the application and, together with the description, serve to explain the principles of the application.
Fig. 1 shows a flowchart of a forest fire monitoring and early warning method according to an embodiment of the present application;
FIG. 2 shows a schematic structural diagram of a system for implementing the forest fire monitoring and early warning method in the embodiment of the present application;
fig. 3a shows image data of a certain area in a daytime when an application scene is acquired in the forest fire monitoring and early warning method according to the embodiment of the present application;
FIG. 3b shows a graph of the effect of the pyrotechnic region identified from the image data shown in FIG. 3 a;
fig. 4a shows image data of a certain area when an application scene is at night in the forest fire monitoring and early warning method according to the embodiment of the present application;
FIG. 4b shows a graph of the effect of the pyrotechnic region identified from the image data shown in FIG. 4 a;
fig. 5a shows image data of another area when the application scene is daytime, which is acquired in the forest fire monitoring and early warning method according to the embodiment of the present application;
FIG. 5b shows a graph of the effect of the pyrotechnic region identified from the image data shown in FIG. 5 a;
fig. 6a shows image data of another area when an application scene acquired in the forest fire monitoring and early warning method according to the embodiment of the present application is at night;
FIG. 6b shows a graph of the effect of the pyrotechnic region identified from the image data shown in FIG. 6 a;
fig. 7 shows a block diagram of a forest fire monitoring and early warning device according to an embodiment of the present application;
fig. 8 shows a block diagram of a forest fire monitoring and early warning device according to an embodiment of the present application.
Detailed Description
Various exemplary embodiments, features and aspects of the present application will be described in detail below with reference to the accompanying drawings. In the drawings, like reference numbers can indicate functionally identical or similar elements. While the various aspects of the embodiments are presented in drawings, the drawings are not necessarily drawn to scale unless specifically indicated.
The word "exemplary" is used exclusively herein to mean "serving as an example, embodiment, or illustration. Any embodiment described herein as "exemplary" is not necessarily to be construed as preferred or advantageous over other embodiments.
Furthermore, in the following detailed description, numerous specific details are set forth in order to provide a better understanding of the present application. It will be understood by those skilled in the art that the present application may be practiced without some of these specific details. In some instances, methods, means, elements and circuits that are well known to those skilled in the art have not been described in detail so as not to obscure the present application.
Fig. 1 shows a flowchart of a forest fire monitoring and early warning method according to an embodiment of the present application. Fig. 2 shows a schematic structural diagram of a forest fire monitoring and early warning system constructed by implementing the method of the embodiment of the present application. As shown in fig. 1 and 2, the method includes: in step S100, image data of the monitored area is acquired. Here, it should be noted that the monitored area refers to a certain area in a forest area. The size of the area is determined by the shooting parameters of the image acquisition equipment acquiring the image data. Wherein, the image acquisition is installed at corresponding monitoring point. And S200, analyzing the image data, identifying a firework area from the image data and determining the geographic position of the firework area. Then, in step S300, a current remote sensing image at the geographic location is obtained, and forest fire dynamic simulation is performed on the electronic map with the fire point of the smoke and fire area as the center according to the current remote sensing image, so as to obtain a fire development prediction result. Here, it should be noted that the current remote sensing image is obtained by acquiring an area at a geographic position by a remote sensing satellite by calling the remote sensing satellite.
Therefore, the forest fire prevention monitoring and early warning method provided by the embodiment of the application acquires the image data of the monitored area through the image acquisition equipment installed at the monitoring point, analyzes the acquired image data and identifies the smoke and fire area from the image data. As will be understood by those skilled in the art, the smoke and fire area refers to an area in the image data where a fire occurs. When the firework area is identified from the image data, the remote sensing satellite is called again, the remote sensing satellite acquires the current remote sensing image of the geographic position of the firework area, forest fire dynamic simulation is carried out on the electronic map by taking the firework area as the center according to the acquired current remote sensing image, so that a corresponding fire development prediction result is obtained, the prediction of the fire development trend of the area where the fire happens currently in the forest area is finally realized, and therefore fire rescue personnel can rapidly designate corresponding rescue measures according to the fire prediction result, the fire rescue efficiency is effectively improved, and the fire loss is reduced.
It should be noted that, in the forest fire monitoring and early warning method in the embodiment of the present application, the acquisition of the image data at the monitored area is implemented by the image acquisition device arranged at the monitoring point. Therefore, the selection of the position of the monitoring point and the configuration of the image acquisition equipment directly affect the acquisition quality of the image data at the monitored area.
In one possible implementation, the monitoring points may be located on a base station near the monitored area or at the top of a building near the monitored area. Correspondingly, the image acquisition equipment comprises a camera, a telephoto lens for acquiring images of the monitored area and a thermal imaging lens for acquiring thermal radiation images of the monitored area.
The high-definition camera, the telephoto lens and the thermal imaging lens are configured to respectively perform visible light monitoring, remote video monitoring and thermal infrared fire source monitoring on the monitored area, so that the method of the embodiment of the application can meet the requirements of visible light monitoring, remote monitoring and thermal infrared fire source monitoring, and covers forest fire prevention mountaineering bayonets and mountain remote vision field monitoring.
Specifically, firstly, a thermal imaging lens collects a thermal radiation image of a monitored area in real time to show the surface temperature distribution of the area, and simultaneously, a thermal infrared temperature alarm threshold is set. The temperature of the area where smoke and fire occur rises, so that the thermal infrared band changes, and the collected thermal imaging image is different from the image when smoke and fire do not occur. And after the set alarm threshold value is exceeded, giving an alarm, and acquiring the firework occurrence area and position. Meanwhile, images collected by the high-definition camera and the telephoto lens are collected, and the firework area is further identified, so that the purpose of further checking the fire condition is achieved.
The image acquisition equipment is arranged on a base station near a forest area or the top end of a building near the forest area, so that when video monitoring is carried out on a monitored area, the image acquisition equipment can be installed by adopting a digital holder, and the image acquisition equipment can carry out omni-directional scanning monitoring on an azimuth angle of 360 degrees and a pitch angle of-45 degrees to +45 degrees. Referring to fig. 3a to 6b, forest region image data collected under four application scenes and smoke and fire regions identified from the image data are respectively shown.
Meanwhile, the image data collected by the image collecting device is transmitted to the monitoring center through the transmission device, the transmission device can be installed in the mobile base station and is connected with the monitoring center network point to point through a transmission network of a communication operator, and therefore the monitoring video image and various control signals of the base station can be rapidly transmitted back to the monitoring center. It should be noted that in the forest fire monitoring and early warning method in the embodiment of the present application, the front end base station may further be correspondingly provided with a power supply system, an anti-theft system, a lightning protection grounding system and an iron tower infrastructure system, so as to ensure that the image acquisition device can normally perform image acquisition of the monitored area for a long time.
After the image data of the monitored area is acquired by the image acquisition equipment, the image data can be analyzed, and the smoke and fire area is identified from the image data. Here, it is understood by those skilled in the art that the firework area refers to an area in the image data showing a fire occurrence.
Wherein, it should be pointed out that to image data analysis, discerned the fireworks region by in the image data and both can set up in forest fire front end intelligent monitoring system, also can set up at rear end surveillance center (promptly, fire prevention command center). In one possible implementation, referring to fig. 2, the analysis of the image data and the identification of the smoke and fire area are set at the front end (i.e., in the forest fire front end intelligent monitoring system), so that only the identified smoke and fire area needs to be transmitted to the monitoring center when data transmission is performed. Compared with the mode of arranging the analysis and the identification of the image data at the back end, the method effectively reduces the data transmission quantity, thereby accelerating the data transmission rate.
Specifically, in analyzing the image data, the identification of the smoke and fire area from the image data can be achieved in the following manner.
Firstly, preprocessing image data, analyzing the image data by adopting a forest fire smoke detection algorithm, and identifying smoke and fire candidate areas from the image data. Then, the identified smoke and fire candidate regions are input into a two-dimensional convolutional neural network, the two-dimensional convolutional neural network carries out deeper feature extraction and identification on the smoke and fire candidate regions according to the difference between smoke and fire and interference factors, and final smoke and fire regions are extracted from the smoke and fire candidate regions.
Here, it should be noted that the disturbance factor refers to an image that disturbs the recognition of smoke and fire, such as: at least one of fog, cloud, and surface reflection. The difference between smoke and interference factors mainly refers to the difference between smoke and fog, cloud, water surface reflection and the like in spectral characteristics and space geometric characteristics.
That is to say, in the forest fire monitoring and early warning method according to the embodiment of the application, in the process of identifying the smoke and fire area, the current situation of the monitored area is mainly identified by using a forest fire smoke detection algorithm in the smoke and fire identification algorithm.
Meanwhile, it is also noted that when a forest fire smoke detection algorithm is adopted to identify a smoke and fire candidate area from image data, the image data needs to be preprocessed so as to improve the accuracy of an identification result. In one possible implementation, the pre-processing of the image data includes de-noising. Specifically, the video quality interference such as salt and pepper noise and gaussian noise in the image data can be removed by a mean filtering method. And then, a motion area is extracted by adopting dynamic monitoring, and a suspected smoke and fire area (namely a smoke and fire candidate area) is obtained from the image data by comprehensively analyzing the color and shape of smoke, the color and shape of fire, the color distribution, the outline, the texture, the motion characteristics and other factors.
Note that, when the firework candidate region is identified, the processing target video data is image data of a plurality of consecutive frames. By identifying the image data of continuous multiple frames, the accuracy of the identification result of the firework candidate area is improved.
In addition, the color feature and the motion feature are used independently, and the interference of elements with colors similar to smoke and fire or similar to motion features cannot be eliminated, so in order to further improve the accuracy of the smoke and fire area identification result, in the method of the embodiment of the application, after the smoke and fire candidate area is identified from the image data in the above manner, the extracted smoke and fire candidate area is input into the two-dimensional convolutional neural network, and the two-dimensional convolutional neural network performs deeper feature extraction and identification according to the difference between smoke and fire and interference factors such as fog, cloud, water surface reflection and the like on the spectral feature and the spatial geometric feature, so as to finally determine the smoke and fire area in the image data.
After the corresponding fire and smoke area is finally determined, the fact that the fire occurs in the monitored area is shown, and therefore the specific geographic position where the fire occurs needs to be determined, and fire rescue is facilitated. Wherein in determining the geographic location of the pyrotechnic region, this may be accomplished in the following manner.
That is, first, acquisition parameters of image data are acquired. Here, it should be noted that the acquisition parameter includes at least one of an installation height of the image acquisition device (e.g., a height of the base), an acquisition orientation of the image acquisition device (e.g., an orientation of the pan/tilt head), and a focal length of the image acquisition device. And then, according to the acquisition parameters, combining a GIS (geographic information system) and a GPS (Beidou navigation and positioning system), determining the geographic position of the firework area, and determining the occurrence position of the fire.
After the geographical position of the firework area is determined, the remote sensing satellite with high resolution can be called to shoot the firework area in real time, and the current remote sensing image of the firework area is obtained. And then based on the obtained current remote sensing image of the firework area, taking the fire point of the firework area as the center, and performing forest fire dynamic simulation on the electronic map to obtain a fire development prediction result.
Specifically, the high-resolution remote sensing satellite is called to shoot the fire scene area in real time, and the fire scene area is processed to generate a high-resolution fire situation analysis product. By taking a fire point as a center, combining meteorological factors such as wind direction, vegetation and combustible substances, landforms, barriers and other factors, directly carrying out forest fire dynamic simulation on an electronic map, automatically generating a prediction effect of fire development and spread through model dynamic calculation, and providing a reference basis for making a fire extinguishing decision. The scene of a fire suppression site is simulated on the map, and information such as a fire fighter, an isolation zone, a suppression route and the like can be marked. The shortest path between any two points on the map can be analyzed, and reference basis is provided for the fire fighter to rapidly arrive at the fire fighting site.
Further, in the above embodiment, by analyzing the image data, when no firework area is identified in the image data, it is indicated that no fire occurs in the monitored area, and therefore, the remote sensing satellite may not be called, and the real-time monitoring of the area may be directly continued.
In addition, in the method of the embodiment of the present application, referring to fig. 2, the data source of the satellite remote sensing monitoring system mainly includes large-scale meteorological satellite data and high-resolution remote sensing satellite data. By accumulating historical data, a mathematical model is established, and an artificial intelligence technology is utilized to realize pre-disaster fire hazard index prediction, in-disaster fire spread prediction and post-disaster damage condition evaluation.
Namely, a corresponding digital elevation model is obtained by acquiring a satellite image acquired by a remote sensing satellite and preprocessing the satellite image (such as geometric correction, radiation correction and the like). And acquiring data such as terrain, gradient, slope direction, altitude and the like from the digital elevation model. Then, combined with ground meteorological station data (including relative humidity, precipitation, wind speed and the like), prediction parameters related to fire risks are obtained from the satellite images. Here, it should be noted that the prediction parameters include at least one of a normalized vegetation number, a normalized multiband drought index, relative humidity, precipitation, and surface temperature. And further, calculating to obtain a fire risk potential index by combining the prediction parameters. And finally, determining the risk level of fire danger in the geographic range corresponding to the acquired satellite image according to the fire danger potential index.
More specifically, after geometric and radiometric correction, the satellite images may be further processed to obtain a Digital Elevation Model (DEM) so as to obtain data of terrain, gradient, slope, Elevation, and the like. By using supervision and classification, the earth surface coverage condition can be known, and the satellite remote sensing data after normalization processing can automatically generate a quantitative inversion product related to fire danger by combining auxiliary information such as historical fire records, ground vegetation surveys, weather station data (including relative humidity, precipitation, wind speed and the like), and the method comprises the following steps: normalized Difference Vegetation Index (NDVI), Normalized Multiband Drought Index (NMDI), relative humidity, precipitation, surface temperature, etc. Based on the information, vegetation combustible Content (FMC (mf-md)/md (md) is sample wet weight, and mf is sample dry weight) is calculated, and further based on the vegetation combustible Moisture Content, the drying degree of humus layers, peat layers, ground and ground fuels is analyzed, a mathematical model is established, Fire risk Potential Index (Fire Potential Index, FPI (FPI) 100 (1-FMC10hr) × (1-VC) is calculated, FMC10hr is corrected 10-hour stagnant combustible Moisture Content, and VC is vegetation coverage, and forest Fire occurrence risk prediction is carried out. The FPI gradually increases before the occurrence of a forest fire and peaks on the day of the fire.
By the embodiment, the forest fire prevention monitoring and early warning method effectively realizes prediction of the pre-disaster fire risk index, so that corresponding remedial measures can be carried out before the fire occurs, the probability of the fire occurrence is effectively reduced, and the purpose of fire prevention early warning is really realized.
Furthermore, the forest fire prevention monitoring and early warning method in the embodiment of the application further comprises the step of evaluating damage after disaster. Namely, a remote sensing satellite is used for obtaining a pre-disaster remote sensing image and a post-disaster remote sensing image, the pre-disaster remote sensing image and the post-disaster remote sensing image are compared, a fire passing area is identified, and the area of the fire passing area is calculated. And then, calculating a combustion area index based on the area of the fire passing area, and evaluating the combustion damage degree of the fire passing area according to the combustion area index to generate a corresponding fire scene evaluation report and provide a corresponding reference basis for the formulation of a subsequent repair plan.
The method comprises the steps of obtaining a pre-disaster remote sensing image, obtaining a post-disaster remote sensing image, obtaining a fire passing area, and identifying the fire passing area. Meanwhile, the calculation of the area of the fire passing region and the calculation of the combustion area index based on the area of the fire passing region can be realized by adopting a conventional mode in the field, and therefore, the detailed description is omitted.
In addition, it should be noted that, in the mode of the embodiment of the present application, no matter the image acquisition device is arranged in the forest fire front-end intelligent monitoring system, or the meteorological satellite and the remote sensing satellite are arranged in the satellite remote sensing monitoring system, the acquired data (or the result of processing and analyzing the acquired data) need to be transmitted to the monitoring center through the transmission network system.
Namely, the transmission network system is a necessary channel for realizing the transmission of the front-end video image and the satellite remote sensing information to the back-end monitoring center. Therefore, the configuration of the transmission network system may be implemented directly by using the operator optical fiber, or may be transmitted by using the microwave method, which is not specifically limited herein. It should be noted that the signals collected by the front end are collected to the mobile machine room through the operator optical fiber, and then sent to the fire prevention command center (i.e., the monitoring center) through the operator machine room gateway, so as to achieve the purpose of rapidly acquiring and transmitting data in real time.
Correspondingly, based on any one of the forest fire prevention monitoring and early warning methods, the application also provides a forest fire prevention monitoring and early warning device. Because the working principle of the forest fire prevention monitoring and early warning device that this application provided is the same as or similar to the principle of the forest fire prevention monitoring and early warning method that this application provided, therefore the repetition point no longer redundantly describes.
Referring to fig. 7, the forest fire monitoring and early warning apparatus 100 according to the embodiment of the present application includes a data acquisition module 110, a data analysis module 120, and a fire prediction module 130. The data acquisition module 110 is configured to acquire image data at the monitored area; the image data is acquired in real time by image acquisition equipment arranged at a monitoring point. A data analysis module 120 configured to analyze the image data, identify a pyrotechnic region from the image data, and determine a geographic location of the pyrotechnic region. The fire prediction module 130 is configured to obtain a current remote sensing image at a geographic location, and perform dynamic forest fire simulation on an electronic map by taking a fire point of a smoke and fire area as a center according to the current remote sensing image to obtain a fire development prediction result. The current remote sensing image is obtained by calling a remote sensing satellite and collecting the area at the geographic position by the remote sensing satellite.
Still further, according to another aspect of the present application, a forest fire monitoring and early warning apparatus 200 is also provided. Referring to fig. 8, the forest fire monitoring and early warning apparatus 200 according to the embodiment of the present application includes a processor 210 and a memory 220 for storing instructions executable by the processor 210. Wherein the processor 210 is configured to execute the executable instructions to implement any of the forest fire monitoring and warning methods described above.
Here, it should be noted that the number of the processors 210 may be one or more. Meanwhile, the forest fire monitoring and early warning apparatus 200 according to the embodiment of the present application may further include an input device 230 and an output device 240. The processor 210, the memory 220, the input device 230, and the output device 240 may be connected via a bus, or may be connected via other methods, which is not limited in detail herein.
The memory 220, which is a computer-readable storage medium, may be used to store software programs, computer-executable programs, and various modules, such as: the program or the module corresponding to the forest fire prevention monitoring and early warning method in the embodiment of the application. The processor 210 executes various functional applications and data processing of the forest fire monitoring and warning apparatus 200 by running software programs or modules stored in the memory 220.
The input device 230 may be used to receive an input number or signal. Wherein the signal may be a key signal generated in connection with user settings and function control of the device/terminal/server. The output device 240 may include a display device such as a display screen.
According to another aspect of the present application, there is also provided a non-transitory computer readable storage medium having stored thereon computer program instructions, which when executed by the processor 210, implement any of the forest fire monitoring and warning methods described above.
Having described embodiments of the present application, the foregoing description is intended to be exemplary, not exhaustive, and not limited to the disclosed embodiments. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments. The terms used herein were chosen in order to best explain the principles of the embodiments, the practical application, or technical improvements to the techniques in the marketplace, or to enable others of ordinary skill in the art to understand the embodiments disclosed herein.
Claims (10)
1. A forest fire prevention monitoring and early warning method is characterized by comprising the following steps:
acquiring image data of a monitored area; the image data is acquired in real time by image acquisition equipment arranged at a monitoring point;
analyzing the image data, identifying a firework area from the image data and determining the geographic position of the firework area;
acquiring a current remote sensing image at the geographic position, and carrying out forest fire dynamic simulation on an electronic map by taking the fire point of the firework area as a center according to the current remote sensing image to obtain a fire development prediction result;
and acquiring the region of the geographic position by the remote sensing satellite by calling the remote sensing satellite from the current remote sensing image.
2. The method of claim 1, wherein the image capture device is located at a base station at the monitored area or at the top of a building in a forest;
the image acquisition equipment comprises a camera, a telephoto lens and a thermal imaging lens, wherein the telephoto lens is configured on the camera and used for acquiring images of the monitored area, and the thermal imaging lens is used for acquiring a thermal imaging graph of the monitored area.
3. The method of claim 1, wherein analyzing the image data to identify pyrotechnic regions from the image data comprises:
after preprocessing the image data, analyzing the image data by adopting a forest fire smoke detection algorithm, and identifying smoke and fire candidate areas from the image data;
inputting the firework candidate area into a two-dimensional convolutional neural network, performing feature extraction and identification on the firework candidate area by the two-dimensional convolutional neural network according to the difference between fireworks and interference factors, and determining a firework area from the firework candidate area;
wherein the disturbance factor comprises at least one of fog, cloud, and surface reflection.
4. The method of claim 1, wherein determining the geographic location of the pyrotechnic region comprises:
acquiring acquisition parameters of the image data; wherein the acquisition parameter comprises at least one of an installation height of the image acquisition device, an acquisition orientation of the image acquisition device, and a focal length of the image acquisition device;
and determining the geographic position of the firework area by combining the GIS and the GPS according to the acquisition parameters.
5. The method of any of claims 1 to 4, further comprising:
acquiring a satellite image acquired by the remote sensing satellite, and preprocessing the satellite image to obtain a corresponding digital elevation model; acquiring a prediction parameter related to fire danger from the satellite image; wherein the prediction parameters include at least one of normalized vegetation number, normalized multiband drought index, relative humidity, precipitation, and surface temperature;
calculating to obtain a fire risk potential index by combining the prediction parameters;
and determining the risk level of fire danger in the geographic range corresponding to the acquired satellite image according to the fire danger potential index.
6. The method of claim 5, wherein calculating a fire risk potential index in conjunction with the predicted parameters comprises:
calculating to obtain the water content of the vegetation combustible according to the prediction parameters;
analyzing the dryness of the humus layer, the peat layer, the ground and the overground fuel based on the water content of the vegetation combustible;
calculating vegetation coverage according to the satellite picture, and calculating to obtain the fire hazard potential index by combining the water content of the combustible vegetation;
wherein, the calculation formula of the fire risk potential index is as follows:
FPI＝100*(1-FMC10hr)*(1-VC)；
wherein FPI is the fire hazard potential index, FMC10hrThe water content of the vegetation combustibles after correction is 10 hours, and VC is the vegetation coverage.
7. The method of any of claims 1 to 4, further comprising:
acquiring a remote sensing image before disaster and a remote sensing image after disaster by the remote sensing satellite;
comparing the remote sensing image before the disaster with the remote sensing image after the disaster, identifying a fire passing area and calculating to obtain the area of the fire passing area;
and calculating a combustion area index based on the area of the fire passing area, and evaluating the combustion damage degree of the fire passing area according to the combustion area index.
8. The utility model provides a forest fire prevention monitoring and early warning device which characterized in that includes: the device comprises a data acquisition module, a data analysis module and a fire prediction module;
the data acquisition module is configured to acquire image data at a monitored area; the image data is acquired in real time by image acquisition equipment arranged at a monitoring point;
the data analysis module is configured to analyze the image data, identify a firework area from the image data and determine a geographic position of the firework area;
the fire prediction module is configured to acquire a current remote sensing image at the geographic position, and dynamically simulate forest fire on an electronic map by taking a fire point of the firework area as a center according to the current remote sensing image to obtain a fire development prediction result;
and acquiring the region of the geographic position by the remote sensing satellite by calling the remote sensing satellite from the current remote sensing image.
9. The utility model provides a forest fire prevention monitoring and forewarning equipment which characterized in that includes:
a processor;
a memory for storing processor-executable instructions;
wherein the processor is configured to carry out the executable instructions when implementing the method of any one of claims 1 to 7.
10. A non-transitory computer readable storage medium having computer program instructions stored thereon, wherein the computer program instructions, when executed by a processor, implement the method of any of claims 1 to 7.
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