A method and system for analyzing forest fire spread

Abstract

This invention discloses a method and system for analyzing forest fire spread. By establishing a polar coordinate system and introducing the angle β between the spread direction and the reference direction and the angle θ between the prevailing wind direction and the reference direction, the method uses a directional projection method to project wind speed and slope effects onto any fire spread direction, achieving a breakthrough from discrete five directions to continuous calculation in all directions. While maintaining the physical mechanism of the original model, this method calculates the fire spread rate through wind speed correction factor V cos(β-θ) and slope correction factor (e.g., φcosβ for uphill direction and φcos(180°-β) for downhill direction), significantly improving the accuracy of fire shape simulation and dynamic visualization capabilities. It is easy to integrate with GIS or CAD software, providing an efficient technical means for accurate forest fire prediction, emergency decision-making, and smart forestry development.

Description

Technical Field

[0001] This invention relates to the field of forest fire prevention and control, and in particular to a method and system for analyzing forest fire spread based on a variation correction model of the Wang Zhengfei-Mao Xianmin forest fire spread model. Background Technology

[0002] Forest fires, as a highly destructive natural disaster, have long posed a serious threat to global ecosystems, socio-economic development, and human safety. Accurately predicting forest fire spread behavior is a core challenge in fire prevention and control, and mathematical models play a crucial role in this process. In my country, the Wang Zhengfei forest fire spread model is a typical example of a semi-empirical model. Developed by Professor Wang Zhengfei in the 1980s based on hundreds of fire experiments in the Greater Khingan Mountains and Sichuan Province, and combined with physical theory analysis, it became the first fire prediction tool specifically designed for the characteristics of local forests. Subsequently, Mao Xianmin further introduced the dynamic coupling relationship between wind speed and topography, forming the Wang Zhengfei-Mao Xianmin combined model. This model calculates the spread speed of the fire in five fixed directions (uphill, downhill, and lateral) and uses the elliptic approximation method to estimate the fire area, and has been widely used in forest fire management practices in my country.

[0003] However, despite the excellent performance of the Wang Zhengfei-Mao Xianmin model in basic predictions, it reveals significant limitations in practical applications. First, the model suffers from directional errors: in complex terrain conditions with high wind speeds or steep slopes, using only uphill and downhill directions as the major axis of the ellipse for fire boundary prediction often leads to bias and fails to accurately reflect the true shape of the fire. Second, its operability is insufficient: the determination of the minor axis relies on empirical wind correction coefficients, lacking universal rules, making standardized operation difficult and limiting its practicality in emergency response. Finally, computational efficiency is a prominent issue: the manual input of the five-directional velocity factors hinders the integration of the model with modern digital tools (such as GIS or CAD software), affecting the real-time performance and dynamic visualization capabilities of fire simulation, and failing to meet the development needs of smart forestry. Summary of the Invention

[0004] This invention addresses the shortcomings of existing technologies by providing a method and system for analyzing forest fire spread.

[0005] To achieve the above-mentioned objectives, the technical solution adopted by the present invention is as follows:

[0006] A method for analyzing forest fire spread, based on a modified version of the original Wang Zhengfei-Mao Xianmin forest fire spread model, includes the following steps:

[0007] S1. By establishing a polar coordinate system, the fire spread rate in any direction can be calculated. A two-dimensional Cartesian coordinate system is constructed with the ignition point O as the origin. The positive Y-axis is defined as the uphill direction, the negative Y-axis is defined as the downhill direction, the positive X-axis is defined as the right-side flat slope direction, and the negative X-axis is defined as the left-side flat slope direction. The angle β between the spread direction and the reference direction is introduced, 0°≤β<360°, and the clockwise angle θ between the prevailing wind direction and the positive Y-axis is introduced, 0°≤θ<360°. The slope effect and wind field effect are projected onto β through directional projection transformation, realizing the transition from discrete direction calculation to continuous direction calculation.

[0008] S2, considering the directional characteristics of the wind field, for β, calculate the projection component of the wind vector in this direction, set a wind speed correction factor, and express the effective wind speed as Vcos(β-θ), where V is the measured wind speed and θ is the angle between the main wind direction and the reference direction.

[0009] S3. In the modified model, for uphill directions 0°≤β<90° or 270°<β≤360°, φcosβ is used as the effective slope angle, and for downhill directions 90°≤β≤270°, φcos(180°-β) is used as the effective slope angle, where φ is the original slope angle, ensuring the model's compatibility in any direction and adherence to physical laws.

[0010] S4. Based on wind speed and slope projection corrections, an all-directional fire spread rate calculation model is established. For the uphill direction, the spread rate calculation formula is:

[0011] R = R o ·K s ·EXP[3.533(tan(φcosβ))¹·²]·EXP[0.1783Vcos(β-θ)];

[0012] For the downhill direction, the calculation formula is:

[0013] R = R o ·K s ·EXP[-3.533(tan(φcos(180°-β)))¹·²]·EXP[0.1783Vcos(β-θ)];

[0014] Where R o K represents the initial velocity of forest fire spread. s The configuration correction factor for combustible materials is given, where V is the wind speed;

[0015] S5 utilizes the fire spread rate results calculated in S4 to generate a dynamic fire map and perform risk analysis. Specifically, this includes: simulating the dynamic expansion of the fire boundary through software integration; calculating the fire area and outline based on the time parameter Δt; generating a visualized dynamic fire map and identifying high-risk areas.

[0016] Furthermore, the establishment of the polar coordinate system described in S1 retains the calculation benchmarks of the five characteristic directions in the original model, including uphill, downhill, left flat slope, right flat slope and prevailing wind direction, and realizes the calculation of fire spread speed in any direction through the continuity of β, which is convenient for integration with GIS system or CAD software for dynamic visualization simulation.

[0017] Furthermore, the introduction of β and θ in S1 enables the accurate expression of the spatial relationship between the wind field and the fire spread direction during the calculation process. The projection of the original slope angle φ reflects the influence component of topographic factors on β, and the projection of θ characterizes the intensity of the wind field's effect on β.

[0018] Furthermore, the wind speed correction factor described in S2 is based on the wind speed correction relationship of the original model. It reflects the spatial relationship between the wind field and the fire spread direction through the projection term cos(β-θ). The correction factor reaches its maximum value when β=θ, and the wind field has no direct effect on the spread speed when β is perpendicular to θ.

[0019] Furthermore, the modified model described in S3 automatically degenerates to the original model calculation results when the spread direction is consistent with the reference direction, i.e., β=0° or β=180°, ensuring the compatibility of the improved scheme with the original model. At the same time, positive values ​​are taken in the uphill direction to enhance spread and negative values ​​are taken in the downhill direction to suppress spread, which is in line with the physical laws of fire spread.

[0020] Furthermore, the omnidirectional fire spread rate calculation model described in S4 achieves accurate determination of the fire field boundary through continuous adjustment of β. It is suitable for fire field simulation with approximately elliptical or complex irregular shapes, and the model parameter system is consistent with the original model, ensuring the continuity and comparability of the prediction results.

[0021] Furthermore, the dynamic fire map generation described in S5 is based on the calculation speed of S4, simulates the fire spread process through numerical integration, and outputs visual graphics using software tools. The fire area calculation adopts the polygon integration method, and the risk analysis includes identifying high spread probability areas and assessing the distance to sensitive targets.

[0022] This invention also discloses a forest fire spread analysis system, which is based on the above-mentioned forest fire spread analysis method and includes:

[0023] The data input module is configured to receive input parameters, including measured wind speed V, the angle θ between the prevailing wind direction and the reference direction, the angle β between the spread direction and the reference direction, the original slope angle φ, and the initial velocity R of the forest fire spread. o and the correction coefficient K for the configuration of combustible materials sThe reference direction is defined as the positive Y-axis direction of a two-dimensional Cartesian coordinate system. This two-dimensional Cartesian coordinate system takes the ignition point O as the origin, the positive Y-axis direction as the uphill direction, the negative Y-axis direction as the downhill direction, the positive X-axis direction as the right-side flat slope direction, and the negative X-axis direction as the left-side flat slope direction. The coordinate system uses a polar coordinate system to calculate the fire spread rate in any direction.

[0024] The processing module, connected to the data input module, is configured to perform fire spread rate calculation based on the input parameters, including:

[0025] By transforming the direction projection, the slope effect and wind field effect are projected onto the target direction β. The wind field effect projection uses the wind speed correction factor V cos(β-θ), and the slope effect projection uses φ cosβ as the effective slope angle for the uphill direction and φ cos(180°-β) as the effective slope angle for the downhill direction.

[0026] Applying the formula for calculating the omnidirectional fire spread rate, for the uphill direction, calculate R = R o ·K s ·EXP[3.533(tan(φ cosβ))¹·²]·EXP[0.1783V cos(β-θ)], for the downhill direction, calculate R = R o ·K s ·EXP[-3.533(tan(φ cos(180°-β)))¹·²]·EXP[0.1783V cos(β-θ)];

[0027] The output module, connected to the processing module, is configured to generate a dynamic fire map and perform risk analysis, including simulating the dynamic expansion of the fire boundary, calculating the fire area, identifying high-risk areas, and outputting visualization results.

[0028] The storage module is configured to store the input parameters, intermediate calculation results, and historical data to support model validation and real-time updates.

[0029] Compared with the prior art, the advantages of the present invention are as follows:

[0030] 1. This invention introduces continuous direction angle β and prevailing wind angle θ, combined with directional projection transformation, to accurately project slope and wind field effects onto any fire spread direction, thus solving the prediction bias caused by the original model relying only on five fixed directions. For example, in steep slopes or variable wind field environments, the model can automatically calculate the spread velocities uphill, downhill, and lateral, avoiding the directional errors of the traditional elliptic approximation method. This improvement ensures that the fire boundary simulation is closer to reality, especially suitable for mountainous or hilly areas, significantly improving prediction accuracy and reliability.

[0031] 2. The parametric representation method of this invention (such as continuous calculation by adjusting the direction angle β) greatly enhances the compatibility of the model with digital tools, enabling seamless integration with Geographic Information System (GIS) or Computer-Aided Design (CAD) software. This integration supports real-time data input, dynamic fire simulation, and visualization output, such as automatically generating fire boundary maps or animation sequences, improving the efficiency and operability of emergency response. In practical applications, users only need to input basic parameters (such as wind speed and slope), and the software can automatically process projection calculations, reducing manual intervention, meeting the development needs of smart forestry, and reducing reliance on experience.

[0032] 3. Based on the omnidirectional spread rate calculation formula, this invention can more accurately determine fire boundaries, applicable to fires of both approximately elliptical and complex irregular shapes. By introducing a time parameter, the model supports dynamic simulation of fire development, thereby updating area estimates and risk maps in real time. This not only helps predict fire spread trends but also provides reliable data support for evacuation decisions and resource allocation, enhancing the model's practicality and emergency response value.

[0033] 4. In the improvement process, this invention retains the physical meaning of all parameters of the Wang Zhengfei-Mao Xianmin model. When the direction angle β takes a specific value (such as 0° or 180°), the model automatically degenerates into the original calculation result, ensuring the continuity and backward compatibility of the prediction results. This design allows those skilled in the art to smoothly transition to the new model, while facilitating historical data comparison and model verification, thus maintaining the continuity of technological accumulation.

[0034] 5. By simplifying the calculation process through mathematical projection, this invention eliminates the limitation of relying on empirical coefficients to determine the minor axis in the original model, provides universal rules, and makes fire spread analysis easier to standardize and promote. Attached Figure Description

[0035] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments of the present invention will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0036] Figure 1 This is a flowchart of the forest fire spread analysis method according to an embodiment of the present invention;

[0037] Figure 2 This is a polar coordinate system diagram in an embodiment of the present invention. Detailed Implementation

[0038] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0039] like Figure 1 As shown in the figure, an embodiment of the present invention provides a method for analyzing the spread of forest fires, comprising:

[0040] When implementing this, common tools such as CAD or GIS software should be used, and on-site data (such as wind speed, slope, and combustible parameters) should be entered.

[0041] Step 1: Establish a polar coordinate system to calculate the fire spread rate in any direction.

[0042] In step 1, refer to Figure 2 The process of establishing a polar coordinate system is as follows:

[0043] First, a two-dimensional Cartesian coordinate system is constructed with the ignition point O as the origin. In this coordinate system, the positive Y-axis direction OU is defined as the uphill direction, corresponding to the terrain slope angle φ; the negative Y-axis direction OD represents the downhill direction; the positive X-axis direction OR represents the right-hand level slope direction; and the negative X-axis direction OL corresponds to the left-hand level slope direction. This coordinate system preserves the calculation basis for the five characteristic directions (uphill, downhill, left-hand level slope, right-hand level slope, and prevailing wind direction) in the original model, while providing a mathematical foundation for directional expansion.

[0044] Secondly, two key angular parameters are introduced: the clockwise angle θ between the prevailing wind direction and the positive Y-axis (0°≤θ<360°), and the clockwise angle β between the direction of fire spread to be calculated and the positive Y-axis (0°≤β<360°). These two parameters accurately represent the spatial relationship between the wind field and the fire spread direction. During the calculation, the slope effect and wind field effect need to be projected onto the target direction β—the projection of the slope angle φ reflects the influence component of topographic factors in that direction, and the projection of the wind direction θ characterizes the intensity of the wind field's effect in that direction. During implementation, technicians can use programming languages ​​(such as Python) or GIS tools to define the coordinate system and angular parameters, ensuring consistent data input formats.

[0045] Step 2: Consider the directional characteristics of the wind field and establish a wind speed correction factor.

[0046] In step (2), for any given fire spread direction β, the actual effective wind speed needs to be calculated as the projection component of the wind vector in that direction. Let the angle between the prevailing wind direction and the reference direction (positive Y-axis direction) be θ, then the effective wind speed is Vcos(β-θ), where V is the measured wind speed (unit: m / s).

[0047] Based on the wind speed correction relationship of the Wang Zhengfei-Mao Xianmin model, the correction factor considering the directional projection effect is:

[0048] Kw=e 0.1783Vcos（β-θ）

[0049] In the formula: V is the measured wind speed (m / s), θ is the angle between the prevailing wind direction and the reference direction (°), and β is the angle between the spread direction and the reference direction (°).

[0050] In this formula, the projection term cos(β-θ) reflects the spatial relationship between the wind field and the fire spread direction—the correction factor is largest when β=θ; when the two are perpendicular, the wind field has no direct impact on the spread rate. During implementation, technicians need to collect real-time wind speed data V and wind direction θ, and then calculate the effective wind speed β in each direction using the above formula, which serves as input for subsequent fire spread rate calculations.

[0051] Step 3: Build a slope correction model and ensure directional compatibility.

[0052] The slope correction model considers the compatibility of directional effects with the original model. Specifically:

[0053] For uphill directions (0°≤β<90° or 270°<β≤360°), φcosβ is used as the effective slope angle, see the formula: .

[0054] For downhill directions (90°≤β≤270°), φcos(180°-β) is used to characterize the actual effective slope, as shown in the formula: .

[0055] In the formula: φ is the original slope angle (°), and β is the angle between the spread direction and the reference direction (°).

[0056] Specifically, when the direction of spread coincides with the reference direction (β=0° or 180°), the model automatically degenerates into the original calculation result, demonstrating the compatibility of the improved scheme. During implementation, technicians need to measure the terrain slope φ and select the corresponding formula to calculate the effective slope based on the direction β. For example, in GIS software, digital elevation model (DEM) data can be imported to automatically extract the φ value, and then the slope projection calculation can be performed through a script.

[0057] Step 4: Calculate the omnidirectional fire spread rate based on wind speed and slope projection correction.

[0058] Based on the aforementioned corrections, a calculation model for omnidirectional fire spread velocity is established. The specific calculation formula is as follows:

[0059] For the uphill direction (0°≤β<90° or 270°<β≤360°), the formula for calculating the spread rate R is:

[0060] R = R o ·K s ·EXP[3.533(tan(φcosβ))¹·²]·EXP[0.1783Vcos(β-θ)].

[0061] For downhill directions (90°≤β≤270°), the calculation formula is adjusted as follows:

[0062] R = R o ·K s ·EXP[-3.533(tan(φcos(180°-β)))¹·²]·EXP[0.1783Vcos(β-θ)].

[0063] In the formula: R o It is the initial velocity of forest fire spread (which can be obtained through laboratory measurements or fitting meteorological factors), K s The configuration correction factor is set for combustible materials, where V is the wind speed (unit: m / min), φ is the slope, and θ is the angle between the prevailing wind direction and the reference direction.

[0064] During implementation, technicians need to determine R in advance. o and K s (For example, based on historical fire data), then substitute the values ​​of V, φ, θ, and β to calculate the spread velocity in each direction. This step can be performed in batches via programming, such as using MATLAB or Python scripts, and the output velocity matrix can be used for subsequent simulations.

[0065] Step 5: Generate a dynamic fire scene map and perform risk analysis.

[0066] Using the fire spread rate calculated in step 4, the dynamic expansion of the fire boundary is simulated through software integration (such as a GIS or CAD system). For example, the fire location is updated at time intervals Δt (e.g., every minute), and the fire outline is generated based on a numerical integration method.

[0067] Generate dynamic fire scene maps, such as heat maps or animation sequences, and identify high-risk areas (e.g., areas where the spread rate exceeds a threshold). During implementation, perform area comparison verification—evaluate the accuracy of the improved model by comparing the calculation results of the original model and the extended model.

[0068] Risk analysis includes calculating the fire area (using polygon integration), identifying distances to sensitive targets (such as residential areas), and generating a risk assessment report. Technical personnel can use tools such as ArcGIS or custom scripts to visualize the data, improving the efficiency of emergency decision-making.

[0069] The implementation details and precautions are as follows:

[0070] Parameter settings: All parameters (such as β, θ, φ) must be based on actual measurements or reliable data sources, and the units must be consistent (e.g., angles in degrees, wind speed in m / min).

[0071] Software integration: This method is easy to interface with GIS or CAD software, for example, by automatically importing data through API interfaces to achieve real-time simulation.

[0072] Verification and Adjustment: After implementation, it is recommended to verify the model by comparing it with historical fire data, and adjust the parameters if necessary.

[0073] Beneficial effects: This implementation method significantly improves the accuracy of fire prediction, is particularly suitable for complex terrain, and provides technical support for smart forestry.

[0074] In another embodiment, a forest fire spread analysis system is provided, which corresponds one-to-one with the forest fire spread analysis methods described in the above embodiments. The forest fire spread analysis system includes:

[0075] The data input module is configured to receive input parameters, including measured wind speed V, the angle θ between the prevailing wind direction and the reference direction, the angle β between the spread direction and the reference direction, the original slope angle φ, and the initial velocity R of the forest fire spread. o and the correction coefficient K for the configuration of combustible materials s The reference direction is defined as the positive Y-axis direction of a two-dimensional Cartesian coordinate system. This coordinate system takes the ignition point O as the origin, the positive Y-axis direction as the uphill direction, the negative Y-axis direction as the downhill direction, the positive X-axis direction as the right-side flat slope direction, and the negative X-axis direction as the left-side flat slope direction. The coordinate system uses a polar coordinate system to calculate the fire spread rate in any direction.

[0076] The processing module, connected to the data input module, is configured to perform fire spread rate calculation based on the input parameters, including:

[0077] By transforming the direction projection, the slope effect and wind field effect are projected onto the target direction β. The wind field effect projection uses the wind speed correction factor V cos(β-θ), and the slope effect projection uses φ cosβ as the effective slope angle for the uphill direction and φ cos(180°-β) as the effective slope angle for the downhill direction.

[0078] Applying the formula for calculating the omnidirectional fire spread rate, for the uphill direction, calculate R = R o ·K s ·EXP[3.533(tan(φ cosβ))¹·²]·EXP[0.1783V cos(β-θ)], for the downhill direction, calculate R = R o·K s ·EXP[-3.533(tan(φ cos(180°-β)))¹·²]·EXP[0.1783V cos(β-θ)];

[0079] The output module, connected to the processing module, is configured to generate a dynamic fire map and perform risk analysis, including simulating the dynamic expansion of the fire boundary, calculating the fire area, identifying high-risk areas, and outputting visualization results.

[0080] The storage module is configured to store the input parameters, intermediate calculation results, and historical data to support model validation and real-time updates.

[0081] Specific limitations regarding the forest fire spread analysis system can be found in the above description of the limitations of a forest fire spread analysis method, and will not be repeated here. Each module in the aforementioned forest fire spread analysis system can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device, or stored in the memory of a computer device as software, so that the processor can call and execute the corresponding operations of each module.

[0082] In another embodiment of the present invention, a terminal device is provided, comprising a processor and a memory. The memory stores a computer program, which includes program instructions. The processor executes the program instructions stored in the computer storage medium. The processor may be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. It is the computing and control core of the terminal, suitable for implementing one or more instructions, specifically suitable for loading and executing one or more instructions to achieve a corresponding method flow or corresponding function. The processor described in this embodiment of the present invention can be used for the operation of the aforementioned forest fire spread analysis method.

[0083] In another embodiment of the present invention, a storage medium is provided, specifically a computer-readable storage medium (Memory). This computer-readable storage medium is a memory device in a terminal device used to store programs and data. It is understood that the computer-readable storage medium here can include both the built-in storage medium in the terminal device and extended storage media supported by the terminal device. The computer-readable storage medium provides storage space that stores the terminal's operating system. Furthermore, this storage space also stores one or more instructions suitable for loading and execution by a processor. These instructions can be one or more computer programs (including program code). It should be noted that the computer-readable storage medium here can be high-speed RAM or non-volatile memory, such as at least one disk storage device.

[0084] One or more instructions stored in a computer-readable storage medium can be loaded and executed by a processor to implement the corresponding steps of the forest fire spread analysis method in the above embodiments; one or more instructions in the computer-readable storage medium are loaded and executed by a processor.

[0085] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. This computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0086] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is used as an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above.

[0087] The above-described embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included within the protection scope of the present invention.

Claims

1. A method for analyzing forest fire spread, based on a modified model of the original Wang Zhengfei-Mao Xianmin forest fire spread model, characterized in that... Includes the following steps: S1. By establishing a polar coordinate system, the fire spread rate in any direction can be calculated. A two-dimensional Cartesian coordinate system is constructed with the ignition point O as the origin. The positive Y-axis is defined as the uphill direction, the negative Y-axis is defined as the downhill direction, the positive X-axis is defined as the right-side flat slope direction, and the negative X-axis is defined as the left-side flat slope direction. The angle β between the spread direction and the reference direction is introduced, 0°≤β<360°, and the clockwise angle θ between the prevailing wind direction and the positive Y-axis is introduced, 0°≤θ<360°. The slope effect and wind field effect are projected onto β through directional projection transformation, realizing the transition from discrete direction calculation to continuous direction calculation. S2, considering the directional characteristics of the wind field, for β, calculate the projection component of the wind vector in any direction, set a wind speed correction factor, and express the effective wind speed as Vcos(β-θ), where V is the measured wind speed and θ is the angle between the main wind direction and the reference direction. S3. In the modified model, for uphill directions 0°≤β<90° or 270°<β≤360°, φcosβ is used as the effective slope angle, and for downhill directions 90°≤β≤270°, φcos(180°-β) is used as the effective slope angle, where φ is the original slope angle, ensuring the model's compatibility in any direction and adherence to physical laws. S4. Based on wind speed and slope projection corrections, an all-directional fire spread rate calculation model is established. For the uphill direction, the spread rate calculation formula is: R= R o ·K s ·EXP[3.533(tan(φcosβ))¹·²]·EXP[0.1783Vcos(β-θ)] For the downhill direction, the calculation formula is: R= R o ·K s ·EXP[-3.533(tan(φcos(180°-β)))¹·²]·EXP[0.1783Vcos(β-θ)] Where R o K represents the initial velocity of forest fire spread. s The configuration correction factor for combustible materials is given, where V is the wind speed; S5 uses the fire spread rate results calculated in S4 to generate a dynamic fire map and perform risk analysis, specifically including: simulating the dynamic expansion of the fire boundary through software integration, and calculating the fire area and outline based on the time parameter Δt; Generate a visual, dynamic fire scene map and identify high-risk areas.

2. The forest fire spread analysis method according to claim 1, characterized in that, The establishment of the polar coordinate system described in S1 retains the calculation reference of the five characteristic directions in the original model, including uphill, downhill, left flat slope, right flat slope and prevailing wind direction, and realizes the calculation of fire spread speed in any direction through the continuity of β, which is convenient for integration with GIS system or CAD software for dynamic visualization simulation.

3. The forest fire spread analysis method according to claim 2, characterized in that, The introduction of β and θ in S1 enables the accurate expression of the spatial relationship between the wind field and the fire spread direction during the calculation process. The projection of the original slope angle φ reflects the influence component of topographic factors on β, and the projection of θ characterizes the intensity of the wind field's effect on β.

4. The forest fire spread analysis method according to claim 1, characterized in that, The wind speed correction factor described in S2 is based on the wind speed correction relationship of the original model. It reflects the spatial relationship between the wind field and the fire spread direction through the projection term cos(β-θ). The correction factor reaches its maximum value when β=θ. When β is perpendicular to θ, the wind field has no direct effect on the spread speed.

5. The forest fire spread analysis method according to claim 1, characterized in that, The modified model described in S3 automatically degenerates to the original model calculation results when the spread direction is consistent with the reference direction, i.e., β=0° or β=180°, ensuring the compatibility of the improved scheme with the original model. At the same time, positive values ​​are taken in the uphill direction to enhance spread and negative values ​​are taken in the downhill direction to suppress spread, which is in line with the physical laws of fire spread.

6. The forest fire spread analysis method according to claim 1, characterized in that, The omnidirectional fire spread rate calculation model described in S4 achieves accurate determination of the fire field boundary through continuous adjustment of β. It is suitable for simulating fire fields with approximately elliptical or complex irregular shapes, and the model parameter system is consistent with the original model, ensuring the continuity and comparability of the prediction results.

7. The forest fire spread analysis method according to claim 1, characterized in that, The dynamic fire map generation described in S5 is based on the calculation speed of S4. It simulates the fire spread process through numerical integration and outputs visual graphics using software tools. The fire area is calculated using polygon integration, and the risk analysis includes identifying high-probability spread areas and assessing the distance to sensitive targets.

8. A forest fire spread analysis system, wherein the forest fire spread analysis system is based on the forest fire spread analysis method according to any one of claims 1 to 7, characterized in that, include: The data input module is configured to receive input parameters, including measured wind speed V, the angle θ between the prevailing wind direction and the reference direction, the angle β between the spread direction and the reference direction, the original slope angle φ, and the initial velocity R of the forest fire spread. o and the correction coefficient K for the configuration of combustible materials s The reference direction is defined as the positive Y-axis direction of a two-dimensional Cartesian coordinate system. This two-dimensional Cartesian coordinate system takes the ignition point O as the origin, the positive Y-axis direction as the uphill direction, the negative Y-axis direction as the downhill direction, the positive X-axis direction as the right-side flat slope direction, and the negative X-axis direction as the left-side flat slope direction. The coordinate system uses a polar coordinate system to calculate the fire spread rate in any direction. The processing module, connected to the data input module, is configured to perform fire spread rate calculation based on the input parameters, including: By transforming the direction projection, the slope effect and wind field effect are projected onto the target direction β. The wind field effect projection uses the wind speed correction factor V cos(β-θ), and the slope effect projection uses φ cosβ as the effective slope angle for the uphill direction and φ cos(180°-β) as the effective slope angle for the downhill direction. Applying the formula for calculating the omnidirectional fire spread rate, for the uphill direction, calculate R = R o ·K s ·EXP[3.533(tan(φcosβ))¹·²]·EXP[0.1783V cos(β-θ)], for the downhill direction, calculate R = R o ·K s ·EXP[-3.533(tan(φ cos(180°-β)))¹·²]·EXP[0.1783V cos(β-θ)]; The output module, connected to the processing module, is configured to generate a dynamic fire map and perform risk analysis, including simulating the dynamic expansion of the fire boundary, calculating the fire area, identifying high-risk areas, and outputting visualization results. The storage module is configured to store the input parameters, intermediate calculation results, and historical data to support model validation and real-time updates.

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