CN113506431B - Multi-platform-based forest and grassland fire danger monitoring and early warning method and device - Google Patents
Multi-platform-based forest and grassland fire danger monitoring and early warning method and device Download PDFInfo
- Publication number
- CN113506431B CN113506431B CN202110742675.3A CN202110742675A CN113506431B CN 113506431 B CN113506431 B CN 113506431B CN 202110742675 A CN202110742675 A CN 202110742675A CN 113506431 B CN113506431 B CN 113506431B
- Authority
- CN
- China
- Prior art keywords
- forest
- early warning
- grassland
- platform
- monitoring sub
- 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.)
- Active
Links
Images
Classifications
-
- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B21/00—Alarms responsive to a single specified undesired or abnormal condition and not otherwise provided for
- G08B21/18—Status alarms
- G08B21/182—Level alarms, e.g. alarms responsive to variables exceeding a threshold
-
- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B21/00—Alarms responsive to a single specified undesired or abnormal condition and not otherwise provided for
- G08B21/18—Status alarms
- G08B21/20—Status alarms responsive to moisture
-
- 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
- Business, Economics & Management (AREA)
- Emergency Management (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Image Processing (AREA)
- Alarm Systems (AREA)
Abstract
The invention discloses a multi-platform-based forest and grassland fire danger monitoring and early warning method and a multi-platform-based forest and grassland fire danger monitoring and early warning device, which comprise the following steps: aiming at a target forest grassland, a plurality of monitoring sub-platforms are respectively adopted for monitoring; according to the correlation characteristics between the soil and the combustible of the target forest grassland, uniformly processing the surface soil moisture measured by the forest grassland fire hazard weather factor monitoring sub-platform, the surface combustible moisture content measured by the forest grassland combustible combustibility monitoring sub-platform and the surface combustible average moisture content measured by the handheld hyperspectral forest grassland fire hazard monitoring sub-platform and the small unmanned aerial vehicle-mounted hyperspectral forest grassland fire hazard monitoring sub-platform into quantitative indexes: calculating the surface water content of the target forest grassland; and carrying out early warning grade evaluation on the target forest grassland. The invention completes the fusion of multiple platforms and simultaneously realizes a monitoring and early warning method with better effect on the basis of the fused multiple platforms.
Description
Technical Field
The invention relates to the technical field of forest and grassland resources and environmental protection, in particular to a multi-platform-based forest and grassland fire danger monitoring and early warning method and device.
Background
The method is characterized in that the forest and grassland fire caused by global climate change is increasingly serious, the control of the major forest and grassland fire is a worldwide problem, and the most important problem is that people lack effective monitoring and early warning on the risk of the forest and grassland fire, so that small fire cannot be found early, and the small fire is spread into uncontrollable large fire due to the fact that the small fire is found late, and even becomes a disaster.
The monitoring and early warning of forest and grassland fires are one of important tasks for preventing the occurrence of the forest fires, and the monitoring and early warning of the forest and grassland fires are generally combined into one and are regarded as an important link of prevention work. According to the indexes of the forest grassland fire hazards, the fire behavior characteristics and the possible harm degree, the early warning level of the forest grassland fire hazards is divided into four levels, the four levels are sequentially represented by red, orange, yellow and blue from high to low, and the specific grading standard is executed according to relevant regulations. Obviously, the monitoring of forest and grassland fires is the basis of early warning, and the early warning is the centralized embodiment of monitoring results. The essence of the method for monitoring and early warning the fire in the forest and grassland is to research the method for monitoring the fire in the forest and grassland and give early warning on the basis of monitoring.
The existing forest and grassland fire monitoring and early warning method can be generally divided into 4 spatial levels: (1) ground patrol (human or by vehicle); (2) lookout and video (remote) monitoring; (3) aeronautical grommets (manned aircraft, unmanned aerial vehicles, or other aircraft, etc.); (4) and (5) satellite monitoring. The used monitoring and early warning methods are basically 'self-administration', the supporting technology and means are generally single, and no forest and grassland fire monitoring and early warning method supported by multiple platforms is available. In addition, the 4 spatial levels of forest and grassland fire monitoring and early warning methods can only solve the problem in one aspect required by forest and grassland fire monitoring and early warning, and have advantages and defects. Therefore, a forest and grassland fire monitoring and early warning method based on multiple platforms is in urgent need in practice.
Disclosure of Invention
Aiming at the defects in the prior art, the invention provides a multi-platform-based forest and grassland fire risk monitoring and early warning method and device, which completes the fusion of multiple platforms and realizes a better-effect monitoring and early warning method on the basis of the fused multiple platforms.
In order to realize the purpose, the invention adopts the following technical scheme:
in a first aspect, the embodiment of the invention provides a multi-platform-based forest and grassland fire danger monitoring and early warning method, which comprises the following steps:
aiming at a target forest grassland, monitoring by adopting a plurality of or all of a forest grassland fire hazard weather factor monitoring sub-platform, a forest grassland combustible substance combustibility monitoring sub-platform, a handheld hyperspectral forest grassland fire hazard monitoring sub-platform and a small unmanned aerial vehicle-mounted hyperspectral forest grassland fire hazard monitoring sub-platform; the early warning indexes of the forest and grassland fire hazard weather factor monitoring sub-platform at least comprise surface soil moisture, and the early warning indexes of the forest and grassland combustible monitoring sub-platform, the handheld hyperspectral forest and grassland fire hazard monitoring sub-platform and the small unmanned aerial vehicle-mounted hyperspectral forest and grassland fire hazard monitoring sub-platform at least comprise surface combustible moisture content;
calculating to obtain the average moisture content of the surface combustible of the target forest grassland according to the moisture content of the surface combustible monitored by the handheld hyperspectral forest grassland fire danger monitoring sub-platform and the small unmanned aerial vehicle-mounted hyperspectral forest grassland fire danger monitoring sub-platform;
according to the correlation characteristics between the soil and the combustible of the target forest grassland, uniformly processing the surface soil moisture measured by the forest grassland fire hazard weather factor monitoring sub-platform, the surface combustible moisture content measured by the forest grassland combustible combustibility monitoring sub-platform and the surface combustible average moisture content measured by the handheld hyperspectral forest grassland fire hazard monitoring sub-platform and the small unmanned aerial vehicle-mounted hyperspectral forest grassland fire hazard monitoring sub-platform into quantitative indexes: calculating the surface water content of the target forest grassland;
and performing early warning grade evaluation on the target forest grassland by combining the water content of the earth surface and other early warning indexes measured by the forest grassland fire danger weather factor monitoring sub-platform, the forest grassland combustible substance combustibility monitoring sub-platform, the handheld hyperspectral forest grassland fire danger monitoring sub-platform and the small unmanned aerial vehicle-mounted hyperspectral forest grassland fire danger monitoring sub-platform.
Optionally, the early warning indexes measured by the forest grassland fire hazard weather factor monitoring sub-platform at least comprise an environmental temperature, an estimated atmospheric humidity, surface soil moisture and an estimated wind power level;
the early warning indexes measured by the forest grassland combustible monitoring sub-platform at least comprise the water content of surface combustible and the burning point of the surface combustible;
the early warning indexes measured by the handheld hyperspectral forest and grassland fire danger monitoring sub-platform and the small unmanned aerial vehicle airborne hyperspectral forest and grassland fire danger monitoring sub-platform at least comprise the moisture content of surface combustibles and the temperature state index.
Optionally, the monitoring and early warning method further includes:
and weighting and calculating the average value of the early warning indexes with the same properties measured by the handheld hyperspectral forest and grassland fire danger monitoring sub-platform and the small unmanned aerial vehicle airborne hyperspectral forest and grassland fire danger monitoring sub-platform according to the monitoring precision of the handheld hyperspectral forest and grassland fire danger monitoring sub-platform and the small unmanned aerial vehicle airborne hyperspectral forest and grassland fire danger monitoring sub-platform.
Optionally, the monitoring and early warning method further includes:
combining all early warning indexes according to regional characteristics of a target forest grassland, and performing regional early warning on the target forest from four directions of an environment angle, a combustible angle, an environment and combustible comprehensive angle and a temperature state index angle respectively to obtain four preliminary early warning results of each region;
and calculating to obtain the total early warning grade of the target forest grassland by combining the obtained preliminary early warning result of each area.
Optionally, the process of obtaining four kinds of preliminary warning results for each region includes the following steps:
setting a plurality of preliminary early warning levels;
and carrying out regional early warning on the target forest steppe from four early warning directions:
(1) performing regional early warning on the target forest grassland by combining seasons, environmental temperature and estimated atmospheric humidity to obtain a preliminary early warning level of each region;
(2) performing regional early warning on a target forest steppe by combining seasons, surface dead combustible water content, estimated wind power level and estimated atmospheric humidity to obtain a preliminary early warning level of each region;
(3) according to the burning point of the surface combustible matter, carrying out regional early warning on the target forest steppe to obtain the preliminary early warning grade of each region;
(4) and carrying out regional early warning on the target forest grassland according to the temperature state index to obtain the preliminary early warning grade of each region.
Optionally, the step of calculating the total early warning level of the target forest grassland by combining the obtained preliminary early warning result of each area includes the following steps:
assigning a value to each preliminary early warning level, wherein the higher the preliminary early warning level is, the larger the value is;
respectively counting the number A of the regions corresponding to each primary early warning level aiming at four early warning directions ij J is an early warning direction type, j is 1,2,3,4, i is a preliminary early warning level, and i is 1, 2. n is the total number of preliminary early warning levels;
calculating the total number A of the regions corresponding to each preliminary early warning level i ，
Combining the regional characteristics of the target forest grassland and the total area A corresponding to each preliminary early warning level i And obtaining the final early warning grade YJ of the target forest grassland:
in the formula, F i The score corresponding to the i-th level preliminary early warning level is obtained, and the value is determined by the regional characteristics of the target forest grassland.
In a second aspect, an embodiment of the present invention provides a multi-platform-based forest and grassland fire risk monitoring and early warning apparatus, where the monitoring and early warning apparatus includes:
a forest and grassland fire weather factor monitoring sub-platform;
a forest and grassland combustible substance combustibility monitoring sub-platform;
a handheld hyperspectral forest and grassland fire danger monitoring sub-platform;
the small unmanned aerial vehicle carries a hyperspectral forest and grassland fire danger monitoring sub-platform;
the average water content calculation module is used for calculating the average water content of the surface combustible of the target forest grassland according to the surface combustible water content monitored by the handheld hyperspectral forest grassland fire danger monitoring sub-platform and the small unmanned aerial vehicle-mounted hyperspectral forest grassland fire danger monitoring sub-platform;
the surface moisture content calculation module is used for uniformly processing the surface soil moisture of the forest grassland fire hazard weather factor monitoring sub-platform determination, the surface combustible moisture content of the forest grassland combustible combustibility monitoring sub-platform determination and the surface combustible average moisture content of the handheld hyperspectral forest grassland fire hazard monitoring sub-platform and the small unmanned aerial vehicle airborne hyperspectral forest grassland fire hazard monitoring sub-platform determination into quantitative indexes according to the correlation characteristics between the soil of the target forest grassland and the combustible: calculating the surface water content of the target forest grassland;
and the early warning module is used for carrying out early warning grade evaluation on the target forest grassland by combining the water content of the earth surface and other early warning indexes measured by the forest grassland fire danger weather factor monitoring sub-platform, the forest grassland combustible substance combustibility monitoring sub-platform, the handheld hyperspectral forest grassland fire danger monitoring sub-platform and the small unmanned aerial vehicle-mounted hyperspectral forest grassland fire danger monitoring sub-platform.
The invention has the beneficial effects that:
(1) the invention quantificationally uses the preliminary early warning grade of the forest grassland fire danger preliminarily determined by a single index, and finally calculates an early warning grade, namely the early warning grade of the forest grassland fire danger released to the society. The invention solves the difference of different indexes in preliminary determination of the early warning level, increases the contribution of high level in determining the final early warning level score, and ensures that the 'forecasting of high fire risk into low fire risk' is avoided in practice.
(2) The invention completes the fusion of multiple platforms and realizes a better monitoring and early warning method on the basis of the fused multiple platforms.
Drawings
FIG. 1 is a flow chart of a forest and grassland fire monitoring and early warning method based on multiple platforms in an embodiment of the invention.
Fig. 2 is a schematic structural diagram of a forest and grassland fire monitoring and early warning device based on multiple platforms in an embodiment of the invention.
FIG. 3 is a schematic structural diagram of a forest and grassland fire weather factor monitoring sub-platform according to an embodiment of the present invention.
Fig. 4 is a schematic monitoring principle diagram of a forest and grassland combustible monitoring sub-platform according to an embodiment of the invention.
Detailed Description
The present invention will now be described in further detail with reference to the accompanying drawings.
It should be noted that the terms "upper", "lower", "left", "right", "front", "back", etc. used in the present invention are for clarity of description only, and are not intended to limit the scope of the present invention, and the relative relationship between the terms and the terms may be changed or adjusted without substantial technical change.
Example one
FIG. 1 is a flow chart of a forest and grassland fire monitoring and early warning method based on multiple platforms in an embodiment of the invention. Referring to fig. 1, the monitoring and early warning method includes the following steps:
in a first aspect, an embodiment of the invention provides a multi-platform-based forest and grassland fire risk monitoring and early warning method, which comprises the following steps:
aiming at a target forest grassland, respectively adopting a plurality of or all of a forest grassland fire hazard weather factor monitoring sub-platform, a forest grassland combustible substance combustibility monitoring sub-platform, a handheld hyperspectral forest grassland fire hazard monitoring sub-platform and a small unmanned aerial vehicle-mounted hyperspectral forest grassland fire hazard monitoring sub-platform for monitoring; the early warning index of the forest grassland fire disaster weather factor monitoring sub-platform at least comprises surface soil moisture, and the early warning index of the forest grassland combustible substance combustibility monitoring sub-platform, the handheld hyperspectral forest grassland fire disaster monitoring sub-platform and the small unmanned aerial vehicle onboard hyperspectral forest grassland fire disaster monitoring sub-platform at least comprises surface combustible substance water content.
As shown in fig. 3, the forest grassland fire weather factor monitoring sub-platform: the method is constructed based on the wireless transmission Internet of things technology. In fig. 3, various PLC (programmable logic controller), RTU (remote control unit), sensors, etc. may be selected and matched according to actual needs. However, temperature and humidity sensors (temperature sensors and humidity sensors), surface soil (within 0-5 cm) moisture sensors and wind speed sensors are the most basic configurations. Therefore, the early warning indexes measured by the forest grassland fire hazard weather factor monitoring sub-platform at least comprise the environmental temperature, the estimated atmospheric humidity, the surface soil moisture and the estimated wind power level.
As shown in fig. 4, the early warning indexes measured by the forest and grassland combustible monitoring sub-platform at least include the moisture content of the surface combustible and the ignition point of the surface combustible.
The early warning indexes measured by the handheld hyperspectral forest and grassland fire danger monitoring sub-platform and the small unmanned aerial vehicle-mounted hyperspectral forest and grassland fire danger monitoring sub-platform at least comprise the moisture content of surface combustibles and the temperature state index (TCI). Because the measurement principle of the handheld hyperspectral forest and grassland fire danger monitoring sub-platform is similar to that of the small unmanned aerial vehicle-mounted hyperspectral forest and grassland fire danger monitoring sub-platform, the early warning indexes with the same properties measured by the handheld hyperspectral forest and grassland fire danger monitoring sub-platform and the small unmanned aerial vehicle-mounted hyperspectral forest and grassland fire danger monitoring sub-platform are combined with the monitoring precision of the handheld hyperspectral forest and grassland fire danger monitoring sub-platform and the small unmanned aerial vehicle-mounted hyperspectral forest and grassland fire danger monitoring sub-platform to weight and calculate the average value. For example, the average moisture content of the surface combustible of the target forest grassland is calculated according to the moisture content of the surface combustible monitored by the handheld hyperspectral forest grassland fire danger monitoring sub-platform and the small unmanned aerial vehicle-mounted hyperspectral forest grassland fire danger monitoring sub-platform.
Step two, according to the correlation characteristic between the soil and the combustible of the target forest grassland, uniformly processing the surface soil moisture measured by the forest grassland fire hazard weather factor monitoring sub-platform, the surface combustible water content measured by the forest grassland combustible combustibility monitoring sub-platform and the surface combustible average water content measured by the handheld hyperspectral forest grassland fire hazard monitoring sub-platform and the small unmanned aerial vehicle airborne hyperspectral forest grassland fire hazard monitoring sub-platform into quantitative indexes: and calculating the water content of the ground surface to obtain the water content of the ground surface of the target forest grassland.
For multiple platforms with different early warning indexes, due to the different early warning indexes, the early warning mechanisms are also different, which is a fundamental reason that the four platforms cannot be fused in the traditional technical scheme. Therefore, in order to ensure the fusion effect, the moisture content (water) is selected from the early warning indexes of the four platforms as a connection index in the embodiment, the moisture content of the surface combustible measured by the forest grassland combustible monitoring sub-platform and the average moisture content of the surface combustible measured by the handheld hyperspectral forest grassland fire monitoring sub-platform and the small unmanned aerial vehicle airborne hyperspectral forest grassland fire monitoring sub-platform can be regarded as the same early warning index, and the surface soil moisture (0-5 cm) measured by the forest grassland fire weather factor monitoring sub-platform needs to be converted by combining the correlation characteristics between the soil and the combustible of the target forest grassland. Fig. 4 is a schematic diagram of the monitoring principle of the combustible monitoring sub-platform for forest and grassland of the embodiment of the present invention, and the types of surface combustibles are divided into three types, namely shrubs, herbaceous plants and dead groundcover, it should be understood that the surface combustibles include but are not limited to the three types, and the surface combustibles of different forest grasslands are different, for example, in the case of the Changbai mountain forest area, the most dominant surface combustibles are larch forest and the like, but in other forest areas, the same is not necessarily true.
In this embodiment, the basis of the ground surface moisture content is still the combustible moisture content that directly arouses the fire, only need combine the forest zone characteristic, unify the measured value of ground surface soil moisture and combustible moisture content and convert another kind of ground surface moisture content that is used for expressing combustible moisture content into to accomplish the fusion of many platforms. The relationship between the water content of combustible materials on different ground surfaces and the soil moisture depends on the water absorption characteristics of the combustible materials. Assuming that the combustible materials of the forest grassland comprise dead ground objects and moss, for the dead ground objects, soil moisture can provide sufficient moisture for the understructure in a decomposition or semi-decomposition state, so as to improve the water content of the dead ground objects, similarly, surface soil moisture can provide sufficient moisture for the forest moss, so as to ensure the water content of the forest moss, and the measured surface soil moisture, the combustible material moisture content of the dead ground objects and the forest moss can be uniformly converted into the surface moisture content according to the water absorption characteristics of the dead ground objects and the forest moss at the moment. However, moss growing on bark and branches is a dangerous combustible substance causing fire of crowns of evergreen trees due to the characteristic of easy drying, but the moss has little relation with soil moisture on the ground surface, and the moss should be treated separately when the moisture content of the combustible substance is converted. In places with a lot of mud moss, there is also a possibility of underground fire occurring when the soil on the surface has low moisture. That is, when the combustible material on the surface contains mud moss, the relationship between the moisture content of the soil on the surface and the moisture content of the combustible material on the surface is more compact, and the influence of the moisture content of the soil on the surface should be considered more in the conversion.
And thirdly, performing early warning grade evaluation on the target forest grassland by combining the water content of the earth surface and other early warning indexes measured by the forest grassland fire danger weather factor monitoring sub-platform, the forest grassland combustible substance combustibility monitoring sub-platform, the handheld hyperspectral forest grassland fire danger monitoring sub-platform and the small unmanned aerial vehicle-mounted hyperspectral forest grassland fire danger monitoring sub-platform.
Specifically, all early warning indexes are combined according to regional characteristics of a target forest grassland, and the target forest is subjected to regional early warning in four directions of an environment angle, a combustible angle, an environment and combustible comprehensive angle and a temperature state index angle respectively to obtain four primary early warning results of each region;
and calculating to obtain the total early warning grade of the target forest grassland by combining the obtained preliminary early warning result of each area.
Illustratively, the process of obtaining four preliminary warning results for each area includes the following steps:
setting a plurality of preliminary early warning levels;
carrying out regional early warning on the target forest grassland from the following early warning directions:
(1) and carrying out regional early warning on the target forest grassland by combining seasons, environmental temperature and estimated atmospheric humidity to obtain the preliminary early warning level of each region. Table 1 is a classification table of forest and grassland fire warning levels corresponding to the temperature and humidity in this embodiment.
TABLE 1 forest and grassland fire early warning grade corresponding to temperature and humidity
(2) And performing regional early warning on the target forest grassland by combining seasons, surface dead combustible water content, estimated wind power level and estimated atmospheric humidity to obtain a preliminary early warning level of each region. Table 2 is a classification table of the forest and grassland fire hazard early warning levels corresponding to the surface moisture content in this embodiment.
TABLE 2 forest and grassland fire hazard early warning grade corresponding to surface moisture content
In some examples, the target forest grassland can be subjected to subarea early warning according to the wind speed or the wind power level. And the table 3 is a classification table of the forest and grassland fire hazard early warning grade corresponding to the wind speed (wind grade).
Table 3 is a classification table of the forest and grassland fire warning levels corresponding to the wind speed (wind power level) in this embodiment.
TABLE 3 forest and grassland fire danger early warning grade corresponding to wind speed (wind power grade)
(3) And carrying out regional early warning on the target forest and grassland according to the ignition point of the surface combustible to obtain the preliminary early warning grade of each region. Table 4 is a classification table of forest and grassland fire warning levels corresponding to the ignition points of the surface combustibles in this embodiment.
TABLE 4 forest and grassland fire hazard early warning grade corresponding to ignition point of surface combustible substance
(4) And carrying out regional early warning on the target forest grassland according to the temperature state index to obtain the preliminary early warning grade of each region. Table 5 is a warning level classification table corresponding to the TCI of this embodiment.
TABLE 5 early warning levels corresponding to TCI
| TCI index | Early warning level |
| ≤30 | Red (A) |
| 31～45 | Orange (B) |
| 46～55 | Yellow (C) |
| ≥56 | Blue (D) |
As can be seen from the foregoing example, the present embodiment divides the preliminary warning level into four levels: red, orange, yellow and blue. It should be understood that in practical applications, other numbers of early warning grades may be set according to specific requirements.
On the basis, the process of calculating the total early warning grade of the target forest grassland by combining the acquired preliminary early warning result of each area comprises the following steps:
and assigning a value to each preliminary early warning level, wherein the higher the preliminary early warning level is, the larger the value is.
Respectively counting the number A of the regions corresponding to each primary early warning level aiming at four early warning directions ij J is the type of the warning direction, j is 1,2,3,4, i is the preliminary warning level, i is 1,2, …, n; n is the preliminary warning level total.
Calculating the total number A of the regions corresponding to each preliminary early warning level i ，
Combining the regional characteristics of the target forest steppe and the total area A corresponding to each preliminary early warning level i And obtaining the final early warning level YJ of the target forest grassland:
in the formula, F i The score corresponding to the i-th level preliminary early warning level is obtained, and the value is determined by the regional characteristics of the target forest grassland.
Assume that four preliminary warning levels "red (a), orange (B), yellow (C) and blue (D)" are assigned with values of 20, 15, 10 and 5, respectively, as detailed in table 6.
TABLE 6 valuation of the preliminary early warning levels of the four forest grassland fire hazards
It should be understood that this is just a simple example for the convenience of explaining the technical solution of the embodiment, and in practical application, the score corresponding to the preliminary warning level depends on the regional characteristics of the target forest grassland, such as the spreading speed and spreading depth of the fire. If a certain forest is in fire once, the coverage is wide, the extinguishing difficulty is high, the damage is serious, and the corresponding score value is correspondingly higher.
Calculating a final early warning grade score (YJ) by adopting the following formula:
in the formula: YJ is the final early warning grade score value of the forest grassland fire danger; a. the 1 The number of red (A) for the preliminary early warning level; a. the 2 The number of orange (B) for the preliminary early warning level; a. the 3 The number of yellow (C) is the primary early warning level; a. the 4 The number of blue (D) for the preliminary warning level.
The final warning level, i.e. the warning level issued to the society, is looked up from table 7.
TABLE 7 Final early warning level determination of four forest grassland fire risks
| Final early warning level | Representing symbol | YJ (fen) |
| Red colour | A | 1.2～2.0 |
| Orange colour | B | 0.9～1.1 |
| Yellow colour | C | 0.7～0.8 |
| Blue colour | D | 0.5～0.6 |
Therefore, the method and the device can be used for carrying out the forest grassland fire danger monitoring and early warning on a single platform by a single index, and can also be used for carrying out the forest grassland fire danger monitoring and early warning on a single platform by multiple indexes. The invention can ensure that the high fire risk is prevented from being forecasted to be low fire risk in practice, and when 5 primary early warning levels have higher levels, the final early warning level can float upwards in proportion: for example, when 4 yellow colors and 1 red color appear in the preliminary warning level, the color of the red bar is generally used as an abnormal value in practice, and the yellow color is predicted, but the YJ of the invention is 1.6, and the red color is mentioned in a grade-exceeding way, so that related departments are reminded to prevent forest fires according to the highest grade. The following steps are repeated: when the primary early warning level has 2 colors of blue, 1 color of yellow, 1 color of orange and 1 color of red, the forest and grassland fire prevention practice is the most difficult to decide, but the YJ of the invention is 1.1, the orange early warning level is determined, and a basis is provided for the forest and grassland fire prevention practice decision. The method can accurately and early provide the early warning of the fire danger of the forest and grassland, can prevent the fire danger as early as possible, can ensure that no serious forest fire occurs locally, can prevent the fire from forming the disaster, is favorable for protecting the safety of the ecological environment, and prevents the forest and grassland resources and the lives and properties of people from being damaged and lost.
Example two
Fig. 2 is a schematic structural diagram of a forest and grassland fire monitoring and early warning device based on multiple platforms in an embodiment of the invention. Referring to fig. 3, the monitoring and early warning device comprises a forest grassland fire disaster weather factor monitoring sub-platform, a forest grassland combustible substance combustibility monitoring sub-platform, a handheld hyperspectral forest grassland fire disaster monitoring sub-platform, a small unmanned aerial vehicle airborne hyperspectral forest grassland fire disaster monitoring sub-platform, an average moisture content calculation module, a ground surface moisture content calculation module and an early warning module.
And the average water content calculation module is used for calculating the average water content of the surface combustible of the target forest grassland according to the surface combustible water content monitored by the handheld hyperspectral forest grassland fire danger monitoring sub-platform and the small unmanned aerial vehicle airborne hyperspectral forest grassland fire danger monitoring sub-platform.
The surface moisture content calculation module is used for uniformly processing the surface soil moisture of the forest grassland fire hazard weather factor monitoring sub-platform determination, the surface combustible moisture content of the forest grassland combustible combustibility monitoring sub-platform determination and the surface combustible average moisture content of the handheld hyperspectral forest grassland fire hazard monitoring sub-platform and the small unmanned aerial vehicle airborne hyperspectral forest grassland fire hazard monitoring sub-platform determination into quantitative indexes according to the correlation characteristics between the soil of the target forest grassland and the combustible: and calculating the surface water content of the target forest grassland.
And the early warning module is used for carrying out early warning grade evaluation on the target forest grassland by combining the water content of the earth surface and other early warning indexes measured by the forest grassland fire danger weather factor monitoring sub-platform, the forest grassland combustible substance combustibility monitoring sub-platform, the handheld hyperspectral forest grassland fire danger monitoring sub-platform and the small unmanned aerial vehicle-mounted hyperspectral forest grassland fire danger monitoring sub-platform.
The above are only preferred embodiments of the present invention, and the scope of the present invention is not limited to the above examples, and all technical solutions that fall under the spirit of the present invention belong to the scope of the present invention. It should be noted that modifications and embellishments within the scope of the invention may be made by those skilled in the art without departing from the principle of the invention.
Claims (5)
1. A forest and grassland fire danger monitoring and early warning method based on multiple platforms is characterized by comprising the following steps:
aiming at a target forest and grassland, monitoring by adopting a plurality of or all of a forest and grassland fire hazard weather factor monitoring sub-platform, a forest and grassland combustible substance combustibility monitoring sub-platform, a handheld hyperspectral forest and grassland fire hazard monitoring sub-platform and a small unmanned aerial vehicle-mounted hyperspectral forest and grassland fire hazard monitoring sub-platform; the early warning indexes of the forest and grassland fire hazard weather factor monitoring sub-platform at least comprise surface soil moisture, and the early warning indexes of the forest and grassland combustible monitoring sub-platform, the handheld hyperspectral forest and grassland fire hazard monitoring sub-platform and the small unmanned aerial vehicle-mounted hyperspectral forest and grassland fire hazard monitoring sub-platform at least comprise surface combustible moisture content;
calculating to obtain the average moisture content of the surface combustible of the target forest grassland according to the moisture content of the surface combustible monitored by the handheld hyperspectral forest grassland fire danger monitoring sub-platform and the small unmanned aerial vehicle-mounted hyperspectral forest grassland fire danger monitoring sub-platform;
according to the correlation characteristics between the soil and the combustible of the target forest grassland, uniformly processing the surface soil moisture measured by the forest grassland fire hazard weather factor monitoring sub-platform, the surface combustible moisture content measured by the forest grassland combustible combustibility monitoring sub-platform and the surface combustible average moisture content measured by the handheld hyperspectral forest grassland fire hazard monitoring sub-platform and the small unmanned aerial vehicle-mounted hyperspectral forest grassland fire hazard monitoring sub-platform into quantitative indexes: calculating the surface water content of the target forest grassland;
performing early warning grade evaluation on the target forest grassland by combining the water content of the earth surface and other early warning indexes measured by a forest grassland fire danger weather factor monitoring sub-platform, a forest grassland combustible substance combustibility monitoring sub-platform, a handheld hyperspectral forest grassland fire danger monitoring sub-platform and a small unmanned aerial vehicle-mounted hyperspectral forest grassland fire danger monitoring sub-platform;
the early warning indexes measured by the forest grassland fire weather factor monitoring sub-platform at least comprise environmental temperature, estimated atmospheric humidity, surface soil moisture and estimated wind power level;
the early warning indexes measured by the forest grassland combustible monitoring sub-platform at least comprise the water content of surface combustible and the burning point of the surface combustible;
early warning indexes measured by the handheld hyperspectral forest and grassland fire danger monitoring sub-platform and the small unmanned aerial vehicle-mounted hyperspectral forest and grassland fire danger monitoring sub-platform at least comprise the moisture content of surface combustibles and temperature state indexes;
the monitoring and early warning method further comprises the following steps:
combining all early warning indexes according to regional characteristics of a target forest grassland, and performing regional early warning on the target forest from four directions of an environment angle, a combustible angle, an environment and combustible comprehensive angle and a temperature state index angle respectively to obtain four preliminary early warning results of each region;
and calculating to obtain the total early warning grade of the target forest grassland by combining the obtained preliminary early warning result of each area.
2. The multi-platform based forest and grassland fire monitoring and early warning method as claimed in claim 1, wherein the monitoring and early warning method further comprises:
and weighting and calculating the average value of the early warning indexes with the same properties measured by the handheld hyperspectral forest and grassland fire danger monitoring sub-platform and the small unmanned aerial vehicle airborne hyperspectral forest and grassland fire danger monitoring sub-platform according to the monitoring precision of the handheld hyperspectral forest and grassland fire danger monitoring sub-platform and the small unmanned aerial vehicle airborne hyperspectral forest and grassland fire danger monitoring sub-platform.
3. The multi-platform based forest and grassland fire danger monitoring and early warning method as claimed in claim 1, wherein the process of obtaining four kinds of preliminary early warning results for each area comprises the following steps:
setting a plurality of preliminary early warning levels;
and carrying out regional early warning on the target forest grassland from four early warning directions:
(1) performing regional early warning on the target forest grassland by combining seasons, environmental temperature and estimated atmospheric humidity to obtain a preliminary early warning level of each region;
(2) performing regional early warning on the target forest grassland by combining seasons, surface dead combustible water content, estimated wind power level and estimated atmospheric humidity to obtain a preliminary early warning level of each region;
(3) according to the burning point of the surface combustible, performing regional early warning on the target forest grassland to obtain a preliminary early warning grade of each region;
(4) and carrying out regional early warning on the target forest grassland according to the temperature state index to obtain the preliminary early warning grade of each region.
4. The multi-platform-based forest grassland fire danger monitoring and early warning method as claimed in claim 3, wherein the step of calculating the total early warning level of the target forest grassland by combining the obtained preliminary early warning result of each area comprises the following steps:
assigning a value to each preliminary early warning level, wherein the higher the preliminary early warning level is, the larger the value is;
respectively counting the number A of the areas corresponding to each primary early warning level according to four early warning directions ij J is the type of the warning direction, j is 1,2,3,4, i is the preliminary warning level, i is 1,2, …, n; n is the total number of preliminary early warning levels;
calculating the total number A of the regions corresponding to each preliminary early warning level i ，
Combining the regional characteristics of the target forest steppe and the total area A corresponding to each preliminary early warning level i And obtaining the final early warning level YJ of the target forest grassland:
in the formula, F i The score corresponding to the i-th level preliminary early warning level is obtained, and the value is determined by the regional characteristics of the target forest grassland.
5. A forest and grassland fire danger monitoring and early warning device based on multiple platforms is characterized in that the monitoring and early warning device adopts the monitoring and early warning method as claimed in claim 1 to carry out early warning grade evaluation on a target forest and grassland;
the monitoring and early warning device comprises:
a forest and grassland fire weather factor monitoring sub-platform;
a forest and grassland combustible substance combustibility monitoring sub-platform;
a handheld hyperspectral forest and grassland fire danger monitoring sub-platform;
the small unmanned aerial vehicle carries a hyperspectral forest and grassland fire danger monitoring sub-platform;
the average water content calculation module is used for calculating the average water content of surface combustible materials of the target forest grassland according to the surface combustible material water content monitored by the handheld hyperspectral forest grassland fire danger monitoring sub-platform and the small unmanned aerial vehicle-mounted hyperspectral forest grassland fire danger monitoring sub-platform;
the surface moisture content calculation module is used for uniformly processing the surface soil moisture of the forest grassland fire hazard weather factor monitoring sub-platform determination, the surface combustible moisture content of the forest grassland combustible combustibility monitoring sub-platform determination and the surface combustible average moisture content of the handheld hyperspectral forest grassland fire hazard monitoring sub-platform and the small unmanned aerial vehicle airborne hyperspectral forest grassland fire hazard monitoring sub-platform determination into quantitative indexes according to the correlation characteristics between the soil of the target forest grassland and the combustible: calculating the surface water content of the target forest grassland;
and the early warning module is used for carrying out early warning grade evaluation on the target forest grassland by combining the water content of the earth surface and other early warning indexes measured by the forest grassland fire hazard weather factor monitoring sub-platform, the forest grassland combustible substance combustibility monitoring sub-platform, the handheld hyperspectral forest grassland fire hazard monitoring sub-platform and the small unmanned aerial vehicle-mounted hyperspectral forest grassland fire hazard monitoring sub-platform.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110742675.3A CN113506431B (en) | 2021-06-30 | 2021-06-30 | Multi-platform-based forest and grassland fire danger monitoring and early warning method and device |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110742675.3A CN113506431B (en) | 2021-06-30 | 2021-06-30 | Multi-platform-based forest and grassland fire danger monitoring and early warning method and device |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN113506431A CN113506431A (en) | 2021-10-15 |
| CN113506431B true CN113506431B (en) | 2022-09-23 |
Family
ID=78010084
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110742675.3A Active CN113506431B (en) | 2021-06-30 | 2021-06-30 | Multi-platform-based forest and grassland fire danger monitoring and early warning method and device |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113506431B (en) |
Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN202523166U (en) * | 2012-04-24 | 2012-11-07 | 鲍鹏飞 | Device for acquiring specific site or region real-time forest fire danger grade |
| CN103065045A (en) * | 2012-12-21 | 2013-04-24 | 浙江农林大学 | Forecast method of forest fire danger of coupling climate and vegetation |
| CN103377535A (en) * | 2012-04-24 | 2013-10-30 | 鲍鹏飞 | Method for obtaining real-time forest fire grades in specific place or area |
| CN205722350U (en) * | 2016-04-27 | 2016-11-23 | 南京森林警察学院 | Integrated risk of forest fire key element acquisition system based on Beidou communication |
| CN106951992A (en) * | 2017-03-20 | 2017-07-14 | 上海事凡物联网科技有限公司 | The Forecasting Methodology and system, server of a kind of surface fuel moisture content |
| CN110379113A (en) * | 2019-06-28 | 2019-10-25 | 北京中科锐景科技有限公司 | A method of based on satellite remote sensing date Forest Fire Alarm |
| CN111970384A (en) * | 2020-10-20 | 2020-11-20 | 四川极云智飞科技有限公司 | Forest fire danger level real-time dynamic monitoring system and method |
| CN112633588A (en) * | 2020-12-30 | 2021-04-09 | 中国林业科学研究院资源信息研究所 | Forest fire behavior potential prediction method based on multi-source data fusion |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US8776906B2 (en) * | 2008-04-23 | 2014-07-15 | Srirangapatnam A. Char | System and method for preventing the incidence of forest fires over large areas |
-
2021
- 2021-06-30 CN CN202110742675.3A patent/CN113506431B/en active Active
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN202523166U (en) * | 2012-04-24 | 2012-11-07 | 鲍鹏飞 | Device for acquiring specific site or region real-time forest fire danger grade |
| CN103377535A (en) * | 2012-04-24 | 2013-10-30 | 鲍鹏飞 | Method for obtaining real-time forest fire grades in specific place or area |
| CN103065045A (en) * | 2012-12-21 | 2013-04-24 | 浙江农林大学 | Forecast method of forest fire danger of coupling climate and vegetation |
| CN205722350U (en) * | 2016-04-27 | 2016-11-23 | 南京森林警察学院 | Integrated risk of forest fire key element acquisition system based on Beidou communication |
| CN106951992A (en) * | 2017-03-20 | 2017-07-14 | 上海事凡物联网科技有限公司 | The Forecasting Methodology and system, server of a kind of surface fuel moisture content |
| CN110379113A (en) * | 2019-06-28 | 2019-10-25 | 北京中科锐景科技有限公司 | A method of based on satellite remote sensing date Forest Fire Alarm |
| CN111970384A (en) * | 2020-10-20 | 2020-11-20 | 四川极云智飞科技有限公司 | Forest fire danger level real-time dynamic monitoring system and method |
| CN112633588A (en) * | 2020-12-30 | 2021-04-09 | 中国林业科学研究院资源信息研究所 | Forest fire behavior potential prediction method based on multi-source data fusion |
Also Published As
| Publication number | Publication date |
|---|---|
| CN113506431A (en) | 2021-10-15 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Ghobadi et al. | Forest fire risk zone mapping from geographic information system in Northern Forests of Iran (Case study, Golestan province) | |
| US9833647B2 (en) | Wildfire arrest and prevention system | |
| Attri et al. | A review on status, implications and recent trends of forest fire management | |
| Akay et al. | Forest fire risk mapping by using GIS techniques and AHP method: A case study in Bodrum (Turkey) | |
| Tian et al. | Changes in forest fire danger for south-western China in the 21st century | |
| CN112102578B (en) | Forest fire monitoring and early warning system, method, storage medium and computer equipment | |
| Shvidenko et al. | Fire and the carbon budget of Russian forests | |
| Stefanović et al. | Multi-criteria forest road network planning in fire-prone environment: a case study in Serbia | |
| CN113506431B (en) | Multi-platform-based forest and grassland fire danger monitoring and early warning method and device | |
| CN105096511B (en) | A kind of method for automatically generating cigarette district testing result | |
| Ganteaume et al. | CFD modelling of WUI fire behaviour in historical fire cases according to different fuel management scenarios | |
| CN106909918B (en) | Mountain fire danger identification method based on satellite images along power transmission line | |
| Chrysoulakis et al. | A new algorithm for the detection of plumes caused by industrial accidents, based on NOAA/AVHRR imagery | |
| Duff et al. | Quantifying wildfire growth rates using smoke plume observations derived from weather radar | |
| CN116386252A (en) | Combustible monitoring method based on forest area division | |
| Heilman et al. | Atmospheric turbulence | |
| Noble | Prescribed Fire in Mallee Rangelands and the Potential Role of Aerial Ignition. | |
| Alkhatib et al. | Forest fire monitoring | |
| Potter | Landscape patterns of burn severity in the Soberanes Fire of 2016 | |
| Stipaničev | Automatic Surveillance Methods | |
| Ottmar | Activity fuels | |
| Won et al. | Estimation of non-CO 2 GHGs emissions by analyzing burn severity in the Samcheok fire, South Korea | |
| Nowzad | Airborne-based fire detection | |
| Wanthongchai et al. | Integrated highland wildfire, smoke, and haze management in the Upper Indochina region | |
| Suter | Airtankers |
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 | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |