CN116437226A - Method and system for selecting distribution point positions of visual device for monitoring mountain fire - Google Patents
Method and system for selecting distribution point positions of visual device for monitoring mountain fire Download PDFInfo
- Publication number
- CN116437226A CN116437226A CN202211489246.0A CN202211489246A CN116437226A CN 116437226 A CN116437226 A CN 116437226A CN 202211489246 A CN202211489246 A CN 202211489246A CN 116437226 A CN116437226 A CN 116437226A
- Authority
- CN
- China
- Prior art keywords
- fire
- monitoring
- satellite
- region
- mountain
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000012544 monitoring process Methods 0.000 title claims abstract description 78
- 238000000034 method Methods 0.000 title claims abstract description 30
- 230000000007 visual effect Effects 0.000 title claims abstract description 28
- 238000009826 distribution Methods 0.000 title claims abstract description 26
- 238000012876 topography Methods 0.000 claims abstract description 21
- 239000000463 material Substances 0.000 claims description 16
- 238000012800 visualization Methods 0.000 claims description 13
- 230000002159 abnormal effect Effects 0.000 claims description 9
- 238000003032 molecular docking Methods 0.000 claims description 9
- 230000008569 process Effects 0.000 claims description 6
- 238000004458 analytical method Methods 0.000 claims description 4
- 238000001514 detection method Methods 0.000 claims description 4
- 238000009434 installation Methods 0.000 claims description 4
- 238000004364 calculation method Methods 0.000 claims description 3
- 238000004891 communication Methods 0.000 claims description 3
- 230000003993 interaction Effects 0.000 claims description 3
- 238000001556 precipitation Methods 0.000 claims description 3
- 238000001931 thermography Methods 0.000 claims description 3
- 230000005540 biological transmission Effects 0.000 claims 1
- 238000011179 visual inspection Methods 0.000 claims 1
- 238000012806 monitoring device Methods 0.000 abstract description 6
- 238000007689 inspection Methods 0.000 abstract description 3
- 230000007547 defect Effects 0.000 abstract description 2
- 238000002360 preparation method Methods 0.000 abstract description 2
- 230000002265 prevention Effects 0.000 abstract description 2
- 238000010586 diagram Methods 0.000 description 6
- 238000004590 computer program Methods 0.000 description 5
- 230000006870 function Effects 0.000 description 5
- 238000012545 processing Methods 0.000 description 5
- 238000002485 combustion reaction Methods 0.000 description 4
- 239000000126 substance Substances 0.000 description 3
- 238000004422 calculation algorithm Methods 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 230000003287 optical effect Effects 0.000 description 2
- 230000005855 radiation Effects 0.000 description 2
- 239000000779 smoke Substances 0.000 description 2
- 238000003860 storage Methods 0.000 description 2
- 239000002028 Biomass Substances 0.000 description 1
- 241000218652 Larix Species 0.000 description 1
- 235000005590 Larix decidua Nutrition 0.000 description 1
- 235000011615 Pinus koraiensis Nutrition 0.000 description 1
- 240000007263 Pinus koraiensis Species 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000009792 diffusion process Methods 0.000 description 1
- 238000011835 investigation Methods 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000012216 screening Methods 0.000 description 1
- 241000894007 species Species 0.000 description 1
- 238000001228 spectrum Methods 0.000 description 1
- 230000003068 static effect Effects 0.000 description 1
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B17/00—Fire alarms; Alarms responsive to explosion
- G08B17/005—Fire alarms; Alarms responsive to explosion for forest fires, e.g. detecting fires spread over a large or outdoors area
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01W—METEOROLOGY
- G01W1/00—Meteorology
- G01W1/10—Devices for predicting weather conditions
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
- H04N23/10—Cameras or camera modules comprising electronic image sensors; Control thereof for generating image signals from different wavelengths
- H04N23/11—Cameras or camera modules comprising electronic image sensors; Control thereof for generating image signals from different wavelengths for generating image signals from visible and infrared light wavelengths
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
- H04N23/90—Arrangement of cameras or camera modules, e.g. multiple cameras in TV studios or sports stadiums
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N7/00—Television systems
- H04N7/18—Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast
- H04N7/181—Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast for receiving images from a plurality of remote sources
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
- Y02A90/00—Technologies having an indirect contribution to adaptation to climate change
- Y02A90/10—Information and communication technologies [ICT] supporting adaptation to climate change, e.g. for weather forecasting or climate simulation
Landscapes
- Engineering & Computer Science (AREA)
- Signal Processing (AREA)
- Multimedia (AREA)
- Environmental & Geological Engineering (AREA)
- Biodiversity & Conservation Biology (AREA)
- Life Sciences & Earth Sciences (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Emergency Management (AREA)
- Business, Economics & Management (AREA)
- Atmospheric Sciences (AREA)
- Ecology (AREA)
- Environmental Sciences (AREA)
- Alarm Systems (AREA)
Abstract
The invention discloses a method and a system for selecting a distribution position of a visualized device for monitoring mountain fires, and a star field integrated omnibearing mountain fire monitoring system is constructed. The system overcomes the defect of monitoring mountain fire by satellite remote sensing, breaks through the limit of man-machine inspection in time, weather, topography and the like, realizes an omnibearing and dead-angle-free mountain fire monitoring system, and improves the timeliness and accuracy of mountain fire monitoring. The limitation of satellite missing report caused by cloud cover is broken through, the monitoring accuracy is improved, cloud fire points which cannot be monitored by the satellite are found in time, and satellite misjudgment caused by cloud edge reflection can be reduced by combining visual monitoring data. Satellite monitoring data and comprehensive fire risk index are used as the basis for the distribution of the mountain fire visual monitoring device. The data are used as support, the data such as mountain fire risk level, cloud cover rate, satellite remote sensing and the like are comprehensively considered, the visual device is distributed, full preparation of early prevention, early discovery and early solution is made, and full coverage of power grid mountain fire monitoring is achieved.
Description
Technical Field
The invention relates to the field of mountain fire disaster monitoring in an electric power corridor, in particular to a method and a system for selecting a distribution position of a visual device for monitoring mountain fire.
Background
Currently, mountain fire monitoring has formed a mountain fire monitoring system combining satellite remote sensing monitoring, line visualization device monitoring and mobile operation inspection. The mountain fire has the characteristics of time randomness and space dispersibility, the manual and machine patrol difficulty coefficient is high, the difficulty is high, the satellite remote sensing mountain fire monitoring has the characteristics of high timeliness, wide coverage area and the like, and the satellite remote sensing provides the most feasible and economical means for the mountain fire wide-area monitoring. The basic principle of satellite remote sensing hotspot identification is two standards that the temperature rise leads to the enhancement of heat radiation and the difference of the increase amplitude of different heat infrared channels. When different substances on the land surface burn, the different substances present different spectrum characteristics due to different temperatures and physical and chemical properties, and are further remotely monitored by different thermal infrared channels of the satellite. However, if obstructions occur in the satellite signal reception optical path, or the combustion temperature of individual organisms (such as grasslands and shrubs) is insufficient to affect significant changes in the radiation wavelength, early small fires near the line path can affect the timeliness and accuracy of satellite monitoring fires.
Disclosure of Invention
The invention aims to provide a method and a system for selecting the distribution point position of a visual device for monitoring mountain fires, and a star field integrated omnibearing mountain fire monitoring system is constructed. The system overcomes the defect of monitoring mountain fire by satellite remote sensing, breaks through the limit of man-machine inspection in time, weather, topography and the like, realizes an omnibearing and dead-angle-free mountain fire monitoring system, and improves the timeliness and accuracy of mountain fire monitoring.
The invention is realized by the following technical scheme:
a method for selecting a distribution point position of a visual device for monitoring mountain fire comprises the following steps:
s1: collecting historical space-time data of the current region, extracting a fire factor, and calculating a comprehensive fire risk index of the current region; the fire factor comprises meteorological factors, vegetation factors, topography factors and accidental factors;
s2: judging the mountain fire risk level of the current region according to the calculation result in the step S1, if the mountain fire risk level is greater than the preset risk level of the current region, listing the region as a region to be installed and distributing points, and extracting the influence factors of the region; the influence factors comprise cloud cover thickness, combustible material load and topography;
s3: calculating cloud cover coverage rate of a region to be installed and distributing points, directly performing point installation in a region where thick cloud cover is accumulated for a long time, and if the cloud cover coverage rate is smaller than a preset value, judging whether the combustible material capacity of the cloud cover can trigger a remote sensing satellite or not;
s4: and (3) analyzing the terrain and the gradient of the region to be installed and the distribution point according to the judgment result of the step (S3), judging whether the region is positioned in a monitoring blind area of the remote sensing satellite, and if so, arranging a visualization device in the region.
As an alternative, in the step S1, the comprehensive fire risk index is a risk prediction result according to weather, geographical environment and historical fire elements of the current region, and the fire factor is obtained by statistics of interactions between weather, forest features, topography and topography, social factors and fire sources.
As an alternative, the comprehensive fire index is used for arranging the preconditions of the visualization device, and the determination process comprises the following steps:
the precipitation, the air temperature, the relative humidity and the wind speed meteorological data provided by the numerical forecast data are counted, and a fire hazard meteorological index is output;
obtaining subsurface information such as surface temperature, solar irradiance and the like through satellite inversion;
and calculating the occurrence frequency of the fire in the current area according to the historical fire data, respectively calculating the weight of the fire through a analytic hierarchy process, and outputting a comprehensive fire risk index.
As an alternative, in the above step S3, the cloud coverage is obtained by the following method:
comprehensively judging the cloud information of the satellites and the remote sensing fire point detection data of the satellites for many years, and calculating the cloud coverage time ratio of the current region;
and grading the cloud cover coverage according to a preset value, wherein the visual device arrangement is not carried out in the areas to be installed and distributed with the grading level smaller than the preset value, and the combustible material amount judgment is carried out in the areas to be installed and distributed with the grading level larger than the preset value.
As an alternative way, the combustible material amount is used for judging the fire point diffusion degree when the fire condition occurs in the area, and the method comprises the step of carrying out statistics on the underlying surface information and the ground object environment information of the vegetation index in the area to judge whether the combustible material amount belongs to the observable fire point in one pixel unit or not.
Alternatively, in the step S4, the terrain and gradient analysis includes analyzing the terrain and land feature of the region and the satellite detection angle in combination according to the comprehensive fire risk index in time and space according to the difference between the stationary satellite and the polar orbit satellite for monitoring the mountain fire condition of the region, and determining the satellite monitoring terrain blind area.
On the other hand, the invention also provides a system for selecting the distribution position of the visual device for monitoring the mountain fire, which is used for executing the method for selecting the distribution position of the visual device for monitoring the mountain fire, and comprises the following steps:
the computer terminal is used for collecting historical space-time data of the current region, extracting fire factors and then outputting comprehensive fire risk indexes and combustible material load of the current region;
the satellite signal docking device is used for being in communication connection with remote sensing satellites in a monitoring current area to acquire monitoring signals of the satellites in real time; calculating cloud coverage rate by matching with a computer terminal;
the visualizer is used for being arranged in mountain forest areas to detect fire situations in the current areas.
As an optional way, the computer terminal further comprises an identification module, an acquisition module and a sending module;
the identification module is used for identifying the comprehensive fire risk index grade of the current region, and distinguishing the current region, the region to be installed and the closed region of the region to be installed from each other on the map by adopting a color identification mode through different color identifications;
the acquisition module is used for connecting with the satellite signal docking device and collecting and counting satellite monitoring data with abnormal satellite monitoring results;
the sending module is used for sending the abnormal satellite monitoring data to the processing center for early warning prompt.
As an alternative, the satellite signal docking apparatus employs a mountain satellite ground receiving station.
As an alternative, the visualization device employs an infrared thermal imaging visible camera.
Compared with the prior art, the invention has the following advantages and beneficial effects:
the method breaks through the limitation of satellite reporting omission caused by cloud cover, improves monitoring accuracy, timely discovers cloud fire points which cannot be monitored by the satellite, and can reduce satellite misjudgment caused by cloud edge reflection by combining with visual monitoring data. Satellite monitoring data and comprehensive fire risk index are used as the basis for the distribution of the mountain fire visual monitoring device. The data are used as support, the data such as mountain fire risk level, cloud cover rate, satellite remote sensing and the like are comprehensively considered, the visual device is distributed, full preparation of early prevention, early discovery and early solution is made, and full coverage of power grid mountain fire monitoring is achieved.
Drawings
The accompanying drawings, which are included to provide a further understanding of embodiments of the invention and are incorporated in and constitute a part of this application, illustrate embodiments of the invention. In the drawings:
fig. 1 is a schematic flow chart of a method for selecting a distribution point position of a visual device for monitoring mountain fire according to an embodiment of the present invention.
Detailed Description
For the purpose of making apparent the objects, technical solutions and advantages of the present invention, the present invention will be further described in detail with reference to the following examples and the accompanying drawings, wherein the exemplary embodiments of the present invention and the descriptions thereof are for illustrating the present invention only and are not to be construed as limiting the present invention.
Thus, the following detailed description of the embodiments of the invention, as presented in the figures, is not intended to limit the scope of the invention, as claimed, but is merely representative of selected embodiments of the invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
Those of ordinary skill in the art will appreciate that implementing all or part of the above facts and methods may be accomplished by a program to instruct related hardware, the program involved or the program may be stored in a computer readable storage medium, the program when executed comprising the steps of: the corresponding method steps are introduced at this time, and the storage medium may be a ROM/RAM, a magnetic disk, an optical disk, or the like.
Examples
Referring to fig. 1, the embodiment provides a method for selecting a distribution point position of a visual device for monitoring mountain fire, which includes the steps of:
s1: collecting historical space-time data of the current region, extracting a fire factor, and calculating a comprehensive fire risk index of the current region; the fire factor comprises meteorological factors, vegetation factors, topography factors and accidental factors;
s2: judging the mountain fire risk level of the current region according to the calculation result in the step S1, if the mountain fire risk level is greater than the preset risk level of the current region, listing the region as a region to be installed and distributing points, and extracting the influence factors of the region; the influence factors comprise cloud cover thickness, combustible material load and topography;
s3: calculating cloud cover coverage rate of a region to be installed and distributing points, directly performing point installation in a region where thick cloud cover is accumulated for a long time, and if the cloud cover coverage rate is smaller than a preset value, judging whether the combustible material capacity of the cloud cover can trigger a remote sensing satellite or not;
s4: and (3) analyzing the terrain and the gradient of the region to be installed and the distribution point according to the judgment result of the step (S3), judging whether the region is positioned in a monitoring blind area of the remote sensing satellite, and if so, arranging a visualization device in the region.
In the step S1, the comprehensive fire risk index refers to a fire risk index that comprehensively considers elements such as weather, geographical environment, and historical fire points, and predicts fire risk. Forest fires have 5 constraints of climate, forest features, topography, social factors and fire sources, wherein the social factors and the fire sources do not have mature quantitative models and can only be characterized according to the space-time distribution data of historical fire points. Forest fires occur as a result of interactions of factors, the primary conditions being necessarily weather, then vegetation, and finally fire. And (3) extracting meteorological factors, vegetation factors, topography factors and accidental factors according to the conditions, and analyzing and obtaining index values by referring to a comprehensive fire risk index algorithm.
The comprehensive fire risk index algorithm utilizes the precipitation, air temperature, relative humidity, wind speed and other meteorological factors provided by the numerical forecast data to calculate the fire risk meteorological index; surface temperature, solar irradiance and other subsurface pad information obtained by satellite inversion; calculating the occurrence frequency of fire according to the historical fire data, and reflecting the influence of artificial factors in different areas and different time periods to a certain extent; and calculating the weight of each element by using an analytic hierarchy process to obtain the comprehensive fire risk index. To more intuitively reveal the index, the forest fire risk class is classified into 5 classes, the classification criteria are as follows:
for the grade 1 mountain fire risk area, the possibility of mountain fire is almost avoided, the combustion does not spread in a large area, and a visual monitoring device is not required to be installed; and for the 2-5-level mountain fire risk area, reasonably distributing the coverage degree of the device in the area according to different fire risk grades when the visual device is spotted. The comprehensive fire risk index is used as a prerequisite for the point distribution of the visual device, so that the efficiency of the installation and point distribution of the forest fire visual monitoring device is greatly improved.
Investigation and collection are carried out on mountain regions which are easy to generate mountain fire, and the accuracy and timeliness of satellite monitoring fire in mountain forest regions can be affected by four factors from the viewpoints of comprehensive historical satellite fire monitoring data missing report and misjudgment conditions: cloud cover thickness, combustible material loading, topography and abnormal heat source, wherein the abnormal heat source can be solved by adopting an abnormal interference source screening technology. Therefore, the embodiment takes the comprehensive fire risk index as the basis, and develops the visual device distribution point according to the cloud cover, the combustible material condition and the mountain land topography.
The climate areas in the mountain forest areas in China have obvious performance differences, the eastern basin is rich in cloud and fog and little in sunlight, and the western basin is rich in sunlight and concentrated in rainfall. According to the basic principle of remote sensing fire judgment, when a satellite remotely senses and monitors a fire, the existence of a thick cloud layer often causes that ground fire energy cannot penetrate through the cloud layer to cause the fire to be missed, cloud pixels at the cloud edge and the satellite form mirror reflection, so that satellite misjudgment can be caused, and cloud coverage becomes a great difficulty of satellite remote sensing technology. In order to solve the monitoring blind area, the cloud coverage time ratio is calculated by comprehensively judging satellite cloud information and satellite remote sensing fire point monitoring data for many years, and the real situation is combined, the visualized device is distributed in the area where the thick cloud layer is accumulated for a long time, so that mountain fire is timely and accurately found, and damage caused by the mountain fire is remarkably reduced. The cloud cover can be classified into the following grades according to the judgment of the thick cloud layer: full cloud coverage, multi-cloud coverage, mid-cloud coverage, few-cloud coverage and no-cloud coverage, the grading criteria are as follows:
under the condition of no cloud or little cloud, the monitoring result is more accurate; when the medium clouds or the clouds are covered, the monitoring result can only be used as a reference, and whether the forest fire occurs is comprehensively judged according to the data of the visualization device; monitoring results cannot be used in full cloud coverage, and distribution points of the forest fire visualization device are required to be reasonably planned. Therefore, in order to find the fire point timely and accurately, the medium cloud coverage is required to be used as a reference point, and the visualized mountain fire monitoring device is required to be distributed in an area with the cloud coverage rate of more than 35%.
The analysis for combustible charge is based on the following: most areas in mountain forest areas are grasslands, arbor forests and shrubs, and the combustible load is relatively low. Starting from the technical principle, the satellite fire point monitoring is the fire point intensity in one pixel, and the satellite can not find the fire point in time under the following three conditions: the energy released after the burning of herbaceous organisms may not be enough to trigger the satellite to monitor the fire point, causing the missed report of the mountain fire; in arbor forests, the water content in vegetation bodies such as larch, korean pine and the like is high, the vegetation bodies belong to nonflammable species, a large amount of smoke can be released when the vegetation bodies are burnt, the fire intensity is low, and the crown is shielded to cause that mountain fire cannot be transmitted to the outside of the crown, so that the combustion cannot be monitored by satellites; the underlying biomass of the shrubs catches fire, and the dense shrubs and the large amount of smoke can block the energy released by the combustion, and is insufficient to trigger the satellite to monitor the fire. The ground object environment information such as the underlying surface information, the vegetation index, the combustible object capacity and the like is also a factor to be considered in the mountain fire visualization device distribution, and the device is arranged in the monitoring blind area according to the comprehensive fire risk index and combining satellite remote sensing data and vegetation distribution statistical data.
Meanwhile, the influence of topography is considered. In existing remote sensing satellite mountain forest monitoring, satellites are classified into two types, stationary satellites and polar satellites. The static satellite can observe once every 10 minutes, but because the satellite observation angle has a certain blind area under the shielding of mountain terrain, the timeliness of fire monitoring can be influenced. Considering the rotation of the earth and the running orbit of the polar orbit satellite, the average day only passes through the same region for 2 times, the transit time interval is longer, and a monitoring blind area exists in time. According to the comprehensive fire risk index, the visual monitoring device is arranged in a relief blind area by combining regional topography and relief and satellite monitoring angle analysis, so that the mountain fire monitoring range can be further enlarged.
On the other hand, the embodiment also provides a system for selecting the distribution position of the visualizer for monitoring mountain fire, which is used for executing the method for selecting the distribution position of the visualizer for monitoring mountain fire, and comprises the following steps: the computer terminal is used for collecting historical space-time data of the current region, extracting fire factors and then outputting comprehensive fire risk indexes and combustible material load of the current region; the satellite signal docking device is used for being in communication connection with remote sensing satellites in a monitoring current area to acquire monitoring signals of the satellites in real time; calculating cloud coverage rate by matching with a computer terminal; the visualizer is used for being arranged in mountain forest areas to detect fire situations in the current areas.
The computer terminal may be any device having a processing function, and the embodiment is not limited. The system comprises an identification module, an acquisition module and a sending module; the identification module is used for identifying the comprehensive fire risk index grade of the current region, and distinguishing the current region, the region to be installed and the closed region of the region to be installed from each other on the map by adopting a color identification mode through different color identifications; the acquisition module is used for connecting with the satellite signal docking device and collecting and counting satellite monitoring data with abnormal satellite monitoring results; the sending module is used for sending the abnormal satellite monitoring data to the processing center for early warning prompt. The satellite signal docking device can adopt a satellite ground receiving station suitable for mountain area setting. The visualization device adopts an infrared thermal imaging visible light camera.
The foregoing description of the embodiments has been provided for the purpose of illustrating the general principles of the invention, and is not meant to limit the scope of the invention, but to limit the invention to the particular embodiments, and any modifications, equivalents, improvements, etc. that fall within the spirit and principles of the invention are intended to be included within the scope of the invention.
Claims (10)
1. A method for selecting a distribution point position of a visual device for monitoring mountain fires is characterized by comprising the following steps:
s1: collecting historical space-time data of the current region, extracting a fire factor, and calculating a comprehensive fire risk index of the current region; the ignition factors comprise meteorological factors, vegetation factors, topography factors and accidental factors;
s2: judging the mountain fire risk level of the current region according to the calculation result in the step S1, if the mountain fire risk level is greater than the preset risk level of the current region, listing the region as a region to be installed and distributing points, and extracting the influence factors of the region; the influence factors comprise cloud cover thickness, combustible material capacity and topography;
s3: calculating cloud cover coverage rate of the region to be installed with the points, directly carrying out point installation in a region where thick cloud cover is accumulated for a long time, and if the cloud cover coverage rate is smaller than a preset value, judging whether the combustible material capacity of the cloud cover can trigger a remote sensing satellite or not;
s4: and (3) analyzing the terrain and the gradient of the region to be installed according to the judgment result of the step (S3), judging whether the region to be installed is positioned in a monitoring blind area of the remote sensing satellite, and if so, arranging a visualization device in the region.
2. The method according to claim 1, wherein in the step S1, the comprehensive fire risk index is a risk prediction result according to weather, geographical environment and historical fire elements of the current region, and the fire factor is obtained by statistics of interactions between weather, forest features, topography and topography, social factors and fire sources.
3. A method for selecting a placement position of a visualizer for mountain fires according to claim 2, characterized in that the comprehensive fire index is used for arranging preconditions of the visualizer, and the determination process comprises the steps of:
the precipitation, the air temperature, the relative humidity and the wind speed meteorological data provided by the numerical forecast data are counted, and a fire hazard meteorological index is output;
obtaining subsurface information such as surface temperature, solar irradiance and the like through satellite inversion;
and calculating the occurrence frequency of the fire in the current area according to the historical fire data, respectively calculating the weight of the fire through a analytic hierarchy process, and outputting a comprehensive fire risk index.
4. The method for selecting a distribution point of a visual device for monitoring mountain fires according to claim 1, wherein in the step S3, the cloud coverage is obtained by:
comprehensively judging the cloud information of the satellites and the remote sensing fire point detection data of the satellites for many years, and calculating the cloud coverage time ratio of the current region;
and grading the cloud cover coverage according to a preset value, wherein the visual device arrangement is not carried out in the areas to be installed and distributed with the grading level smaller than the preset value, and the combustible material amount judgment is carried out in the areas to be installed and distributed with the grading level larger than the preset value.
5. The method according to claim 4, wherein the combustible material amount is used for judging the fire spreading degree when the fire occurs in the area, and the method comprises the step of counting the underlying surface information and the ground object environment information of the vegetation index in the area to judge whether the fire belongs to the observable fire in one pixel unit.
6. The method according to claim 1, wherein in the step S4, the analysis of the topography and gradient includes analyzing the topography and the satellite detection angle of the region according to the comprehensive fire index in time and space according to the difference between the stationary satellite and the polar orbit satellite for monitoring the condition of the mountain fire in the region, and determining the satellite monitoring topography blind area.
7. A system for selecting a placement position of a mountain fire monitoring visual device, characterized by being configured to perform the mountain fire monitoring visual device placement position selecting method according to any one of claims 1 to 6, comprising:
the computer terminal is used for collecting historical space-time data of the current region, extracting ignition factors and outputting comprehensive fire risk indexes and combustible material load of the current region;
the satellite signal docking device is used for being in communication connection with remote sensing satellites in a monitoring current area to acquire monitoring signals of the satellites in real time; and calculate cloud coverage rate in cooperation with the computer terminal;
and the visualization device is used for being arranged in mountain forest areas to detect fire situations in the current areas.
8. The system for selecting a distribution position of a visual device for monitoring mountain fires according to claim 7, wherein the computer terminal further comprises an identification module, an acquisition module and a transmission module;
the identification module is used for identifying the comprehensive fire risk index grade of the current region, and distinguishing the current region, the region to be installed and the closed region of the region to be installed from each other on the map by adopting a color identification mode through different color identifications;
the acquisition module is used for connecting the satellite signal docking device and collecting and counting satellite monitoring data with abnormal satellite monitoring results;
the sending module is used for sending the abnormal satellite monitoring data to the processing center for early warning prompt.
9. The system for selecting a deployment site of a visual inspection apparatus for a mountain fire as recited in claim 7, wherein said satellite signal docking means is a mountain satellite ground receiving station.
10. The system for selecting a placement position of a mountain fire monitoring visualization device as recited in claim 7, wherein the visualization device employs an infrared thermal imaging visible camera.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211489246.0A CN116437226A (en) | 2022-11-25 | 2022-11-25 | Method and system for selecting distribution point positions of visual device for monitoring mountain fire |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211489246.0A CN116437226A (en) | 2022-11-25 | 2022-11-25 | Method and system for selecting distribution point positions of visual device for monitoring mountain fire |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN116437226A true CN116437226A (en) | 2023-07-14 |
Family
ID=87078435
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202211489246.0A Pending CN116437226A (en) | 2022-11-25 | 2022-11-25 | Method and system for selecting distribution point positions of visual device for monitoring mountain fire |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN116437226A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117854213A (en) * | 2024-01-10 | 2024-04-09 | 吉林省林业科学研究院(吉林省林业生物防治中心站) | Forest fire prevention monitoring and early warning system and method based on meteorological data |
-
2022
- 2022-11-25 CN CN202211489246.0A patent/CN116437226A/en active Pending
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117854213A (en) * | 2024-01-10 | 2024-04-09 | 吉林省林业科学研究院(吉林省林业生物防治中心站) | Forest fire prevention monitoring and early warning system and method based on meteorological data |
| CN117854213B (en) * | 2024-01-10 | 2024-06-04 | 吉林省林业科学研究院(吉林省林业生物防治中心站) | Forest fire prevention monitoring and early warning system and method based on meteorological data |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN202434011U (en) | Automatic monitoring and alarming system for forest fire | |
| CN103455708A (en) | Power transmission line disaster monitoring and risk assessment platform based on satellite and weather information | |
| CN111783634A (en) | Fire point detection method based on satellite remote sensing data | |
| Owayjan et al. | Firoxio: Forest fire detection and alerting system | |
| CN102176073A (en) | Ambient air quality comprehensive monitoring method based on first ambient satellite | |
| Jones et al. | Satellite and radar remote sensing of southern plains grass fires: A case study | |
| CN114724337A (en) | Remote intelligent monitoring and early warning system and method based on photovoltaic cell power supply | |
| CN111311866A (en) | Satellite data fusion mountain fire monitoring and fire deduction-based early warning method and system | |
| Ommi et al. | Trajectory-based models and remote sensing for biomass burning assessment in Bangladesh | |
| CN116437226A (en) | Method and system for selecting distribution point positions of visual device for monitoring mountain fire | |
| Tilloy et al. | A methodology for the spatiotemporal identification of compound hazards: wind and precipitation extremes in Great Britain (1979–2019) | |
| CN116307739A (en) | Forest fire prevention intelligent monitoring early warning system | |
| KR102034193B1 (en) | Automatic Information System for hazard map of facilities collapse using Modis satellite image and AWS materials | |
| Vara-Vela et al. | A new predictive framework for Amazon forest fire smoke dispersion over South America | |
| Ren et al. | Monitoring potential spontaneous combustion in a coal waste dump after reclamation through unmanned aerial vehicle RGB imagery based on alfalfa aboveground biomass | |
| Humstad et al. | Infrasound detection of avalanches in Grasdalen and Indreeidsdalen, Norway | |
| Pizzuti et al. | On the relationship between lightning superbolts and TLEs in Northern Europe | |
| CN107704713B (en) | Power transmission line forest fire distribution evaluation method | |
| Chen et al. | Wildfire monitoring technology of transmission lines based on Himawari-8 geostationary meteorological satellite | |
| Di et al. | Research on secondary analysis method of synchronous satellite monitoring data of power grid wildfire | |
| Ruminski et al. | Use of multiple satellite sensors in NOAA's operational near real-time fire and smoke detection and characterization program | |
| Giordani et al. | Characterizing hail-prone environments using convection-permitting reanalysis and overshooting top detections over south-central Europe | |
| Laneve et al. | SIGRI project: Products validation results | |
| CN117197680B (en) | Power transmission and distribution forest fire monitoring method and monitoring device based on multi-source satellite data | |
| Chew et al. | Data Acquisition Guide for Forest Fire Risk Modelling in Malaysia |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |