Screening method of sensitive disaster-inducing factors influencing forest fire

Abstract

The invention discloses a method for screening sensitive disaster-inducing factors influencing forest fire, which comprises the following steps of: 1, carrying out terrain acquisition on a forest to obtain terrain influence factors; 2, analyzing terrain influence factors of the forest to obtain terrain evaluation information; 3, collecting map information of the forest, and obtaining other influence factors; 4, analyzing other influence factors to obtain evaluation information of other influence factors; 5, forest image information is collected through unmanned equipment, the forest image information is processed, and image analysis factors are obtained; step 6, analyzing the image analysis factors to obtain image analysis evaluation information; and step 7, collecting the meteorological environment of the position where the forest is located, and obtaining meteorological influence factors. According to the invention, more comprehensive screening of sensitive disaster-inducing factors influencing forest fire can be carried out.

Description

Technical Field

[0001] The invention relates to the field of forest protection, and in particular to a method for screening sensitive disaster-causing factors affecting forest fires. Background Art

[0002] Forest fire refers to a forest fire that loses human control, spreads and expands freely in the forest, and causes certain harm and losses to the forest, forest ecosystem and humans;

[0003] Forest fire is a serious natural disaster that requires the joint efforts of the whole society to prevent and respond to. By strengthening publicity and education, strictly managing fire sources, establishing fire prevention facilities, and strengthening monitoring and early warning, the incidence and degree of harm of forest fires can be effectively reduced;

[0004] Therefore, it is necessary to conduct screening and analysis of sensitive disaster factors of forest fires, and the screening method of sensitive disaster factors will be used during the analysis process.

[0005] Existing screening methods mostly only monitor, analyze and screen relevant information existing in the forest itself, resulting in low reliability of the final screening results, which has a certain impact on the use of the screening method. Therefore, a screening method for sensitive disaster factors affecting forest fires is proposed. Summary of the invention

[0006] The technical problem to be solved by the present invention is: how to solve the problem that the existing screening methods mostly only monitor, analyze and screen the relevant information existing in the forest itself, resulting in low reliability of the screening results finally obtained, which has a certain impact on the use of the screening method. A screening method for sensitive disaster factors that affect forest fires is provided.

[0007] The present invention solves the above technical problems through the following technical solutions, and the present invention comprises the following steps:

[0008] Step 1: Collect forest terrain and obtain terrain influencing factors;

[0009] Step 2: Analyze the terrain influencing factors of the forest itself and obtain terrain assessment information;

[0010] Step 3: Collect forest map information and obtain other influencing factors;

[0011] Step 4: Analyze other influencing factors and obtain evaluation information of other influencing factors;

[0012] Step 5: Collect forest image information through unmanned equipment, process the forest image information, and obtain image analysis factors;

[0013] Step 6: Analyze the image analysis factors and obtain image analysis evaluation information;

[0014] Step 7: Collect the meteorological environment of the forest location and obtain meteorological influencing factors;

[0015] Step 8: Analyze meteorological influencing factors and obtain meteorological impact assessment information;

[0016] Step 9: Analyze and rate all the evaluation information obtained.

[0017] Furthermore, the terrain influencing factors include abnormal slope information and altitude information;

[0018] Terrain assessment information includes primary terrain assessment, secondary terrain assessment and tertiary terrain assessment. The specific process of analyzing terrain influencing factors and obtaining terrain assessment information is as follows:

[0019] Extract the acquired terrain influencing factors, and extract abnormal slope information from the terrain influencing factors, the abnormal slope information including the total number of slopes with a slope greater than a preset value, the number of sunny slopes with a slope greater than a preset value, and the number of shady slopes with a slope greater than a preset value;

[0020] Calculate the ratio of the number of sunny slopes with a slope greater than a preset value to the total number of slopes with a slope greater than the preset value to obtain a first parameter;

[0021] Calculate the ratio of the number of shady slopes with a slope greater than a preset value to the total number of slopes with a slope greater than the preset value to obtain a second parameter;

[0022] Then extract the altitude information, score the altitude information, and obtain the third parameter. When the altitude information is greater than the preset value a1, the third parameter is the preset value m1;

[0023] When the altitude information is between the preset value a1 and a2, the third parameter is the preset value m2;

[0024] When the altitude information is less than the preset value a2, the third parameter is the preset value m3;

[0025] a1>a2,m1>m2>m3;

[0026] The first parameter is labeled as Z1, the second parameter is labeled as Z2, and the third parameter is labeled as Z3;

[0027] When Z1 is less than the preset value, and Z2 and Z3 are both greater than the preset values, a first-level terrain assessment is generated;

[0028] When Z1 is greater than the preset value, Z2 is less than the preset value, and Z3 is greater than the preset value, a secondary terrain assessment is generated;

[0029] When Z1 is greater than a preset value, Z2 is less than a preset value, and Z3 is less than a preset value, a third-level terrain assessment is generated.

[0030] Furthermore, the specific process of collecting forest map information and obtaining other influencing factors is as follows:

[0031] Collect forest map information from the Internet and mark the forest contour on the forest map;

[0032] Then, the number of residential areas outside the contour line whose distance to the contour line is less than the preset value is collected, and the forest map information is analyzed to obtain the forest area information. The number of residential areas and the forest area information constitute other influencing factors.

[0033] Furthermore, other impact factor assessment information includes primary impact assessment, secondary impact assessment and tertiary impact assessment;

[0034] Analyze other influencing factors and obtain evaluation information of other influencing factors;

[0035] Extract other influencing factors, extract the number of residential clusters and forest area information from other influencing factors, calculate the ratio of forest area information to the number of residential clusters, and obtain impact assessment parameters;

[0036] When the impact assessment parameter is greater than the preset value f1, a first-level impact assessment is generated; when the impact assessment parameter is between the preset values ​​f1 and f2, a second-level impact assessment is generated; when the impact assessment parameter is less than the preset value f2, a third-level impact assessment is generated.

[0037] Furthermore, the process of obtaining the image analysis factors is as follows:

[0038] Selecting a corresponding number of unmanned devices according to a preset selection rule, and using the unmanned devices to collect forest image information according to the preset collection rules;

[0039] The forest image information includes first image information and second image information;

[0040] Processing the first image information to obtain the number of reflective objects, the number of people, and the number of preset markers;

[0041] The second image information is processed to obtain the number of luminous objects and the number of abnormal infrared areas.

[0042] The specific process of selecting a corresponding number of unmanned devices according to the preset selection rules is as follows:

[0043] Collect forest information and unmanned equipment information. The forest information refers to forest area information, and the unmanned equipment information refers to the maximum patrol area information of a single unmanned equipment.

[0044] The forest area information is marked as G1, and the maximum patrol area information of a single unmanned device is marked as G2;

[0045] The selected corresponding quantity Gg is obtained by the formula G1 / G2*α=Gg. When Gg is a non-integer, it is rounded up. α is the correction value. 1.5≥α≥1.3. α is proportional to G1.

[0046] The specific process of collecting forest image information according to the preset collection rules is as follows: when it is currently in the daytime state, a corresponding number of drones are selected to collect real-time images of the forest to obtain first image information;

[0047] When it is currently in night state, a corresponding number of drones are selected to collect real-time images and real-time infrared images of the forest to obtain the second image information.

[0048] Furthermore, the specific process of processing the first image information to obtain the number of reflective objects, the number of people, and the number of preset markers is as follows:

[0049] Extracting first image information collected by a single unmanned device, and detecting the number of objects with brightness greater than a preset value from the first image information;

[0050] Then, a human body recognition model is introduced into the first image information, and the number of human body models recognized is detected from the first image information;

[0051] Then, a preset marker model is imported into the first image information, and the number of the preset marker models is detected from the first image information;

[0052] Then, the sum of the number of objects whose brightness is greater than the preset value, the sum of the number of human models and the sum of the number of preset marker models obtained by all unmanned equipment is calculated, and the number of reflective objects, the number of people and the number of preset markers are obtained;

[0053] The specific process of processing the second image information to obtain the number of luminous objects and the number of infrared abnormal areas is as follows:

[0054] Extracting the second image information collected by a single unmanned device, and collecting the number of luminous places whose brightness is greater than a preset value from the real-time image of the second image information;

[0055] Extracting the number of regions with a color depth greater than a preset value from the real-time infrared image of the second image information;

[0056] Then, the sum of the number of luminous points with brightness greater than the preset value and the sum of the number of areas with color depth greater than the preset value collected by all unmanned equipment are calculated, that is, the number of luminous objects and the number of infrared abnormal areas are obtained.

[0057] Further, the image analysis evaluation information includes a first image analysis evaluation, a second image analysis evaluation, and a third image analysis evaluation;

[0058] The specific process of analyzing image analysis factors and obtaining image analysis evaluation information is as follows:

[0059] When the image to be analyzed is the first image information, the number of reflective objects, the number of people, and the number of preset markers are extracted;

[0060] When the number of reflective objects is less than a preset value, the number of people is less than a preset value, and the number of preset markers is less than a preset value, a first image analysis evaluation is generated;

[0061] When any one of the number of reflective objects, the number of people and the number of preset markers is greater than a preset value, a second image analysis and evaluation is generated;

[0062] When any two or more of the number of reflective objects, the number of people, and the number of preset markers are greater than the preset values, a third image analysis and evaluation is generated.

[0063] Furthermore, the meteorological impact assessment information includes primary meteorological assessment, secondary meteorological assessment and tertiary meteorological assessment;

[0064] The specific process of analyzing meteorological influencing factors and obtaining meteorological impact assessment information is as follows:

[0065] Extracting the collected meteorological influencing factors, the meteorological influencing factors include precipitation information within a preset time period and temperature information within a preset time period;

[0066] When the precipitation within the preset time is greater than the preset value, and the temperature information within the preset time is less than the preset value, a first-level meteorological assessment is generated;

[0067] When the precipitation within the preset time is less than the preset value, and the temperature information within the preset time is less than the preset value, a secondary meteorological assessment is generated;

[0068] Except for the above conditions, a level 3 meteorological assessment is generated.

[0069] Furthermore, the obtained evaluation information is analyzed and rated, and the obtained rating content includes first-level forest rating, second-level forest rating and third-level forest rating;

[0070] The acquisition process of the first-level forest rating, the second-level forest rating and the third-level forest rating is as follows: extracting the acquired terrain assessment information, other influencing factor assessment information, image analysis assessment information, and meteorological impact assessment information;

[0071] When the assessment levels of terrain assessment information, other influencing factors assessment information, image analysis assessment information, and meteorological impact assessment information are all level one, a level one forest rating is generated;

[0072] When there is a second level in the assessment levels of terrain assessment information, other influencing factor assessment information, image analysis assessment information, and meteorological impact assessment information, a second-level forest rating is generated;

[0073] When there are two or more second-level assessment levels or one third-level assessment level in the terrain assessment information, other influencing factor assessment information, image analysis assessment information, and meteorological impact assessment information, a third-level forest rating is generated.

[0074] Compared with the prior art, the present invention has the following advantages: the screening method of sensitive disaster factors affecting forest fires can intuitively understand whether the terrain where the forest is located is a terrain state prone to fire through the generated terrain assessment information, and then can focus on screening key locations prone to fire based on the terrain assessment information; through the generated other influencing factor assessment information, the collection and analysis of residential areas around the forest is realized; more residential areas around the forest means that the probability of residents entering the forest is greater, which in turn leads to a greater possibility of forest fires; therefore, through the generated other influencing factor assessment information, supervisors can focus on screening human-induced fire factors; through the generated image analysis assessment information, unmanned equipment is set to collect forest image information to achieve diversified and comprehensive screening of factors that may cause fire in the forest; through the generated meteorological impact assessment information, supervisors can understand the fire factors that may be caused by meteorological reasons, and a more comprehensive screening of sensitive disaster factors affecting forest fires is achieved; the obtained screening and analysis results are more reliable, making the method more worthy of popularization and use. BRIEF DESCRIPTION OF THE DRAWINGS

[0075] Figure 1 It is the overall flow chart of the present invention. DETAILED DESCRIPTION

[0076] The following is a detailed description of an embodiment of the present invention. This embodiment is implemented on the premise of the technical solution of the present invention, and a detailed implementation method and a specific operation process are given, but the protection scope of the present invention is not limited to the following embodiment.

[0077] like Figure 1 As shown, this embodiment provides a technical solution: a method for screening sensitive disaster factors affecting forest fires, comprising the following steps:

[0078] Step 1: Collect forest terrain and obtain terrain influencing factors;

[0079] Step 2: Analyze the terrain influencing factors of the forest itself and obtain terrain assessment information;

[0080] Step 3: Collect forest map information and obtain other influencing factors;

[0081] Step 4: Analyze other influencing factors and obtain evaluation information of other influencing factors;

[0082] Step 5: Collect forest image information through unmanned equipment, process the forest image information, and obtain image analysis factors;

[0083] Step 6: Analyze the image analysis factors and obtain image analysis evaluation information;

[0084] Step 7: Collect the meteorological environment of the forest location and obtain meteorological influencing factors;

[0085] Step 8: Analyze meteorological influencing factors and obtain meteorological impact assessment information;

[0086] Step 9: Analyze and rate all the evaluation information obtained.

[0087] Topographic factors include abnormal slope information and altitude information;

[0088] Terrain assessment information includes primary terrain assessment, secondary terrain assessment and tertiary terrain assessment. The specific process of analyzing terrain influencing factors and obtaining terrain assessment information is as follows:

[0089] Extract the acquired terrain influencing factors, and extract abnormal slope information from the terrain influencing factors, the abnormal slope information including the total number of slopes with a slope greater than a preset value, the number of sunny slopes with a slope greater than a preset value, and the number of shady slopes with a slope greater than a preset value;

[0090] Calculate the ratio of the number of sunny slopes with a slope greater than a preset value to the total number of slopes with a slope greater than the preset value to obtain a first parameter;

[0091] Calculate the ratio of the number of shady slopes with a slope greater than a preset value to the total number of slopes with a slope greater than the preset value to obtain a second parameter;

[0092] Then extract the altitude information, score the altitude information, and obtain the third parameter. When the altitude information is greater than the preset value a1, the third parameter is the preset value m1;

[0093] When the altitude information is between the preset value a1 and a2, the third parameter is the preset value m2;

[0094] When the altitude information is less than the preset value a2, the third parameter is the preset value m3;

[0095] a1>a2,m1>m2>m3;

[0096] The first parameter is labeled as Z1, the second parameter is labeled as Z2, and the third parameter is labeled as Z3;

[0097] When Z1 is less than the preset value, and Z2 and Z3 are both greater than the preset values, a first-level terrain assessment is generated, which means that the possibility of fire in the terrain is low and normal inspection is sufficient;

[0098] When Z1 is greater than the preset value, Z2 is less than the preset value, and Z3 is greater than the preset value, a secondary terrain assessment is generated. The secondary terrain assessment indicates that there is a certain possibility of fire in the terrain, and inspections need to be strengthened;

[0099] When Z1 is greater than the preset value, Z2 is less than the preset value, and Z3 is less than the preset value, a level 3 terrain assessment is generated. Level 3 terrain assessment means that the terrain has a greater possibility of fire and needs to be inspected closely;

[0100] Sunny slope: Long-term exposure to direct sunlight makes the temperature of the sunny slope higher and the humidity relatively low. The water in the soil and vegetation evaporates faster and becomes drier. This dry environment provides favorable conditions for the occurrence of fire. Once a fire source appears, the fire will expand rapidly and spread rapidly upward along the slope.

[0101] Shaded slope: Due to less sunlight exposure, the temperature on the shady slope is lower, the humidity is higher, and the vegetation grows lushly and contains a lot of water. Such an environment is not conducive to the occurrence and spread of fires. Even if a fire occurs, it is easy to control;

[0102] As the altitude increases, the climate conditions and vegetation types will change. High altitude areas usually have lower temperatures, more precipitation, dense vegetation and high water content, so the probability of forest fires is relatively low. However, in specific areas at high altitudes (such as dry valleys, meadows, etc.), if the climate conditions are suitable (such as drought, high temperature, strong winds, etc.), serious forest fires may still occur.

[0103] The specific process of collecting forest map information and obtaining other influencing factors is as follows:

[0104] Collect forest map information from the Internet and mark the forest contour on the forest map;

[0105] Then, the number of residential areas outside the contour line whose distance to the contour line is less than the preset value is collected, and the forest map information is analyzed to obtain the forest area information. The number of residential areas and the forest area information constitute other influencing factors.

[0106] Other impact factor assessment information includes primary impact assessment, secondary impact assessment and tertiary impact assessment;

[0107] Analyze other influencing factors and obtain evaluation information of other influencing factors;

[0108] Extract other influencing factors, extract the number of residential clusters and forest area information from other influencing factors, calculate the ratio of forest area information to the number of residential clusters, and obtain impact assessment parameters;

[0109] When the impact assessment parameter is greater than the preset value f1, a first-level impact assessment is generated, which means that there are fewer residents around the forest, and the fire factor caused by human factors is relatively small;

[0110] When the impact assessment parameter is between the preset values ​​f1 and f2, a secondary impact assessment is generated, which means that there are a certain number of residential areas around the forest, and there is a possibility of people entering, so regular inspections are required;

[0111] When the impact assessment parameter is less than the preset value f2, a third-level impact assessment is generated. The third-level impact assessment means that there are many residential areas around the forest, and the possibility of human-caused fires is high, which requires key supervision, f1>f2.

[0112] The process of obtaining the image analysis factors is as follows:

[0113] Selecting a corresponding number of unmanned devices according to a preset selection rule, and using the unmanned devices to collect forest image information according to the preset collection rules;

[0114] The forest image information includes first image information and second image information;

[0115] Processing the first image information to obtain the number of reflective objects, the number of people, and the number of preset markers;

[0116] There may be many abnormal reflective objects in the forest, which are very dangerous. For example, plastic bottles and glass bottles left behind by people entering the forest. If there is water left in the plastic bottles and glass bottles, the light shining on the plastic bottles and glass bottles will produce a focusing effect, focusing the sunlight directly on one point, causing the local temperature to be too high and ignite flammable materials to cause a fire;

[0117] Too many people enter the forest, because they may light fires in the forest to cook or smoke, which is likely to cause fires;

[0118] The preset markers are tombstones or graves. If there are a large number of graves in the forest, the decomposition of the bodies buried in the graves will release phosphine, which may spontaneously ignite related combustibles and cause fires.

[0119] Processing the second image information to obtain the number of luminous objects and the number of infrared abnormal areas;

[0120] The number of luminous objects in the second image information may be emitted by the spontaneous combustion of phosphine released by animal carcasses in the forest, and the infrared abnormal area is the area with abnormal temperature in the forest;

[0121] By monitoring the number of luminous objects and the number of abnormal infrared areas, it is possible to detect factors that may cause fires in the forest at night, and then set up timely protective measures.

[0122] The specific process of selecting a corresponding number of unmanned devices according to the preset selection rules is as follows:

[0123] Collect forest information and unmanned equipment information. The forest information refers to forest area information, and the unmanned equipment information refers to the maximum patrol area information of a single unmanned equipment.

[0124] The forest area information is marked as G1, and the maximum patrol area information of a single unmanned device is marked as G2;

[0125] The selected corresponding quantity Gg is obtained by the formula G1 / G2*α=Gg. When Gg is a non-integer, it is rounded up. α is the correction value. 1.5≥α≥1.3. α is proportional to G1.

[0126] The specific process of collecting forest image information according to the preset collection rules is as follows: when it is currently in the daytime state, a corresponding number of drones are selected to collect real-time images of the forest to obtain first image information;

[0127] When it is currently in the night state, a corresponding number of drones are selected to collect real-time images and real-time infrared images of the forest to obtain the second image information;

[0128] Through the above process, the setting of the specific relevant information collection process is realized, ensuring that the collected relevant information is reliable and stable.

[0129] The specific process of processing the first image information to obtain the number of reflective objects, the number of people, and the number of preset markers is as follows:

[0130] Extracting first image information collected by a single unmanned device, and detecting the number of objects with brightness greater than a preset value from the first image information;

[0131] Then, a human body recognition model is introduced into the first image information, and the number of human body models recognized is detected from the first image information;

[0132] Then, a preset marker model is imported into the first image information, and the number of the preset marker models is detected from the first image information;

[0133] Then, the sum of the number of objects whose brightness is greater than the preset value, the sum of the number of human models and the sum of the number of preset marker models obtained by all unmanned equipment is calculated, and the number of reflective objects, the number of people and the number of preset markers are obtained;

[0134] The specific process of processing the second image information to obtain the number of luminous objects and the number of infrared abnormal areas is as follows:

[0135] Extracting the second image information collected by a single unmanned device, and collecting the number of luminous places whose brightness is greater than a preset value from the real-time image of the second image information;

[0136] Extracting the number of regions with a color depth greater than a preset value from the real-time infrared image of the second image information;

[0137] Then, the sum of the number of luminous points with brightness greater than the preset value and the sum of the number of areas with color depth greater than the preset value collected by all unmanned equipment is calculated, that is, the number of luminous objects and the number of infrared abnormal areas are obtained;

[0138] Through the above process, more accurate relevant parameters can be obtained, thereby ensuring the accuracy of the final evaluation results.

[0139] The image analysis and evaluation information includes a first image analysis and evaluation, a second image analysis and evaluation, and a third image analysis and evaluation;

[0140] The specific process of analyzing image analysis factors and obtaining image analysis evaluation information is as follows:

[0141] When the image to be analyzed is the first image information, the number of reflective objects, the number of people, and the number of preset markers are extracted;

[0142] When the number of reflective objects is less than a preset value, the number of people is less than a preset value, and the number of preset markers is less than a preset value, a first image analysis evaluation is generated;

[0143] The first image analysis assessment indicates that there are few abnormal factors in the forest and normal monitoring is sufficient;

[0144] When any one of the number of reflective objects, the number of people and the number of preset markers is greater than a preset value, a second image analysis and evaluation is generated;

[0145] The second image analysis assessment indicates that there are certain influencing factors within the forest that require monitoring;

[0146] When any two or more of the number of reflective objects, the number of people and the number of preset markers are greater than the preset value, a third image analysis and evaluation is generated;

[0147] The third image analysis and assessment indicates that there are many influencing factors in the forest, and it is necessary to focus on monitoring abnormal factors.

[0148] Furthermore, the meteorological impact assessment information includes primary meteorological assessment, secondary meteorological assessment and tertiary meteorological assessment;

[0149] The specific process of analyzing meteorological influencing factors and obtaining meteorological impact assessment information is as follows:

[0150] Extracting the collected meteorological influencing factors, the meteorological influencing factors include precipitation information within a preset time period and temperature information within a preset time period;

[0151] When the precipitation within the preset time period is greater than the preset value, and the temperature information within the preset time period is less than the preset value, a first-level meteorological assessment is generated.

[0152] Level 1 meteorological assessment means that the weather is normal, level 2 meteorological assessment means that there are certain abnormalities in the weather, which may cause fires, and level 3 meteorological assessment means that there are major abnormalities in the weather, which have a high probability of causing fires.

[0153] When the precipitation within the preset time is less than the preset value, and the temperature information within the preset time is less than the preset value, a secondary meteorological assessment is generated;

[0154] Except for the above conditions, a level 3 meteorological assessment is generated.

[0155] The above mentioned analysis and rating of all the acquired assessment information includes the first-level forest rating, the second-level forest rating and the third-level forest rating;

[0156] A first-level forest rating means that there are fewer factors that cause forest fires, and the possibility of fire is low;

[0157] A secondary forest rating means that there are certain factors for forest fires;

[0158] The second-level forest rating means that there are more fire factors and more protection monitoring is needed;

[0159] The acquisition process of the first-level forest rating, the second-level forest rating and the third-level forest rating is as follows: extracting the acquired terrain assessment information, other influencing factor assessment information, image analysis assessment information, and meteorological impact assessment information;

[0160] When the assessment levels of terrain assessment information, other influencing factors assessment information, image analysis assessment information, and meteorological impact assessment information are all level one, a level one forest rating is generated;

[0161] When there is a second level in the assessment levels of terrain assessment information, other influencing factor assessment information, image analysis assessment information, and meteorological impact assessment information, a second-level forest rating is generated;

[0162] When there are two or more second-level assessment levels or one third-level assessment level in the terrain assessment information, other influencing factor assessment information, image analysis assessment information, and meteorological impact assessment information, a third-level forest rating is generated.

[0163] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of the features. In the description of the present invention, the meaning of "plurality" is at least two, such as two, three, etc., unless otherwise clearly and specifically defined.

[0164] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, without contradiction.

[0165] Although the embodiments of the present invention have been shown and described above, it is to be understood that the above embodiments are exemplary and are not to be construed as limitations of the present invention. A person skilled in the art may change, modify, replace and vary the above embodiments within the scope of the present invention.

Claims

1. A method for screening sensitive disaster factors affecting forest fires, characterized in that: The following steps are involved: Step 1: Collect forest terrain and obtain terrain influencing factors; Step 2: Analyze the terrain influencing factors of the forest itself and obtain terrain assessment information; Step 3: Collect forest map information and obtain other influencing factors; Step 4: Analyze other influencing factors and obtain evaluation information of other influencing factors; Step 5: Collect forest image information through unmanned equipment, process the forest image information, and obtain image analysis factors; Step 6: Analyze the image analysis factors and obtain image analysis evaluation information; Step 7: Collect the meteorological environment of the forest location and obtain meteorological influencing factors; Step 8: Analyze meteorological influencing factors and obtain meteorological impact assessment information; Step 9: Analyze and rate all the evaluation information obtained.

2. The method for screening sensitive disaster factors affecting forest fires according to claim 1, characterized in that: Topographic factors include abnormal slope information and altitude information; Terrain assessment information includes primary terrain assessment, secondary terrain assessment and tertiary terrain assessment. The specific process of analyzing terrain influencing factors and obtaining terrain assessment information is as follows: Extract the acquired terrain influencing factors, and extract abnormal slope information from the terrain influencing factors, the abnormal slope information including the total number of slopes with a slope greater than a preset value, the number of sunny slopes with a slope greater than a preset value, and the number of shady slopes with a slope greater than a preset value; Calculate the ratio of the number of sunny slopes with a slope greater than a preset value to the total number of slopes with a slope greater than the preset value to obtain a first parameter; Calculate the ratio of the number of shady slopes with a slope greater than a preset value to the total number of slopes with a slope greater than the preset value to obtain a second parameter; Then extract the altitude information, score the altitude information, and obtain the third parameter. When the altitude information is greater than the preset value a1, the third parameter is the preset value m1; When the altitude information is between the preset value a1 and a2, the third parameter is the preset value m2; When the altitude information is less than the preset value a2, the third parameter is the preset value m3; a1>a2,m1>m2>m3; The first parameter is labeled as Z1, the second parameter is labeled as Z2, and the third parameter is labeled as Z3; When Z1 is less than the preset value, and Z2 and Z3 are both greater than the preset values, a first-level terrain assessment is generated; When Z1 is greater than the preset value, Z2 is less than the preset value, and Z3 is greater than the preset value, a secondary terrain assessment is generated; When Z1 is greater than a preset value, Z2 is less than a preset value, and Z3 is less than a preset value, a third-level terrain assessment is generated.

3. The method for screening sensitive disaster factors affecting forest fires according to claim 1, characterized in that: The specific process of collecting forest map information and obtaining other influencing factors is as follows: Collect forest map information from the Internet and mark the forest contour on the forest map; Then, the number of residential areas outside the contour line whose distance to the contour line is less than the preset value is collected, and the forest map information is analyzed to obtain the forest area information. The number of residential areas and the forest area information constitute other influencing factors.

4. The method for screening sensitive disaster factors affecting forest fires according to claim 3, characterized in that: Other impact factor assessment information includes primary impact assessment, secondary impact assessment and tertiary impact assessment; Analyze other influencing factors and obtain evaluation information of other influencing factors; Extract other influencing factors, extract the number of residential clusters and forest area information from other influencing factors, calculate the ratio of forest area information to the number of residential clusters, and obtain impact assessment parameters; When the impact assessment parameter is greater than the preset value f1, a first-level impact assessment is generated; when the impact assessment parameter is between the preset values ​​f1 and f2, a second-level impact assessment is generated; when the impact assessment parameter is less than the preset value f2, a third-level impact assessment is generated.

5. The method for screening sensitive disaster factors affecting forest fires according to claim 1, characterized in that: The process of obtaining the image analysis factors is as follows: Selecting a corresponding number of unmanned devices according to a preset selection rule, and using the unmanned devices to collect forest image information according to the preset collection rules; The forest image information includes first image information and second image information; Processing the first image information to obtain the number of reflective objects, the number of people, and the number of preset markers; The second image information is processed to obtain the number of luminous objects and the number of abnormal infrared areas.

6. A method for screening sensitive disaster factors affecting forest fires according to claim 5, characterized in that: The specific process of processing the first image information to obtain the number of reflective objects, the number of people, and the number of preset markers is as follows: Extracting first image information collected by a single unmanned device, and detecting the number of objects with brightness greater than a preset value from the first image information; Then, a human body recognition model is introduced into the first image information, and the number of human body models recognized is detected from the first image information; Then, a preset marker model is imported into the first image information, and the number of the preset marker models is detected from the first image information; Then, the sum of the number of objects whose brightness is greater than the preset value, the sum of the number of human models and the sum of the number of preset marker models obtained by all unmanned equipment is calculated, and the number of reflective objects, the number of people and the number of preset markers are obtained; The specific process of processing the second image information to obtain the number of luminous objects and the number of infrared abnormal areas is as follows: Extracting the second image information collected by a single unmanned device, and collecting the number of luminous places whose brightness is greater than a preset value from the real-time image of the second image information; Extracting the number of regions with a color depth greater than a preset value from the real-time infrared image of the second image information; Then, the sum of the number of luminous points with brightness greater than the preset value and the sum of the number of areas with color depth greater than the preset value collected by all unmanned equipment are calculated, that is, the number of luminous objects and the number of infrared abnormal areas are obtained.

7. The method for screening sensitive disaster factors affecting forest fires according to claim 5, characterized in that: The image analysis and evaluation information includes a first image analysis and evaluation, a second image analysis and evaluation, and a third image analysis and evaluation; The specific process of analyzing image analysis factors and obtaining image analysis evaluation information is as follows: When the image to be analyzed is the first image information, the number of reflective objects, the number of people, and the number of preset markers are extracted; When the number of reflective objects is less than a preset value, the number of people is less than a preset value, and the number of preset markers is less than a preset value, a first image analysis evaluation is generated; When any one of the number of reflective objects, the number of people and the number of preset markers is greater than a preset value, a second image analysis and evaluation is generated; When any two or more of the number of reflective objects, the number of people, and the number of preset markers are greater than the preset values, a third image analysis and evaluation is generated.

8. The method for screening sensitive disaster factors affecting forest fires according to claim 1, characterized in that: Meteorological impact assessment information includes primary meteorological assessment, secondary meteorological assessment and tertiary meteorological assessment; The specific process of analyzing meteorological influencing factors and obtaining meteorological impact assessment information is as follows: Extracting the collected meteorological influencing factors, the meteorological influencing factors include precipitation information within a preset time period and temperature information within a preset time period; When the precipitation within the preset time is greater than the preset value, and the temperature information within the preset time is less than the preset value, a first-level meteorological assessment is generated; When the precipitation within the preset time is less than the preset value, and the temperature information within the preset time is less than the preset value, a secondary meteorological assessment is generated; Except for the above conditions, a level 3 meteorological assessment is generated.

9. A method for screening sensitive disaster factors affecting forest fires according to any one of claims 1 to 8, characterized in that: The above mentioned analysis and rating of all the acquired assessment information includes the first-level forest rating, the second-level forest rating and the third-level forest rating; The acquisition process of the first-level forest rating, the second-level forest rating and the third-level forest rating is as follows: extracting the acquired terrain assessment information, other influencing factor assessment information, image analysis assessment information, and meteorological impact assessment information; When the assessment levels of terrain assessment information, other influencing factors assessment information, image analysis assessment information, and meteorological impact assessment information are all level one, a level one forest rating is generated; When there is a second level in the assessment levels of terrain assessment information, other influencing factor assessment information, image analysis assessment information, and meteorological impact assessment information, a second-level forest rating is generated; When there are two or more second-level assessment levels or one third-level assessment level in the terrain assessment information, other influencing factor assessment information, image analysis assessment information, and meteorological impact assessment information, a third-level forest rating is generated.

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