A method and system for analyzing wildfire spread trend in combination with real-time environmental information

Abstract

The application discloses a mountain fire spreading trend analysis method and system combined with real-time environment information, relates to the technical field of power transmission line mountain fire early warning, and comprises the following steps: constructing an initial observation area by taking the core of a fire site area and associated meteorological stations, gridizing the initial observation area to obtain a plurality of fire observation grids; updating real-time environment data for each fire observation grid to obtain fire change trend data of each fire observation grid, identifying fire head information of the fire site area based on the fire change trend data of all fire observation grids, and calculating a fire spreading adjustment coefficient; and taking the fire spreading adjustment coefficient as the calculation basis of a mountain fire alarm threshold. The method and system gridize the fire site area, determine the development of the fire head by using the real-time environment data change of each fire observation grid, further determine the fire spreading parameters, calculate the adjustment threshold, and are more suitable for the current fire development situation, so that the threshold parameter early warning effect is improved.

Description

Technical Field

[0001] This invention relates to the field of power transmission line wildfire early warning technology, and more specifically, to a method and system for analyzing wildfire spread trends by combining real-time environmental information. Background Technology

[0002] Wildfires affecting power transmission lines are characterized by their suddenness, rapid spread, and significant damage. Accurate early identification and warning are crucial for ensuring the safe operation of the power grid. Currently, most mainstream wildfire identification and warning methods employ fixed threshold mechanisms. This involves setting fixed values ​​for one or more monitoring indicators (such as temperature, smoke concentration, and infrared radiation intensity) as the threshold for wildfire occurrence. When real-time monitoring data exceeds this threshold, an warning is triggered. While this fixed threshold method can provide some early warning and prediction, it only allows for judgment at a single stage and lacks comprehensive tracking and analysis of the wildfire's development. The development of a wildfire from a small initial spark to a large-scale blaze is a dynamic process, with varying degrees of threat to power transmission lines at different stages. To address these limitations, existing technologies are exploring more flexible warning strategies, such as multi-stage dynamic threshold adjustment methods based on wildfire development. By dividing the wildfire into different stages from its initial ignition to its spread and dynamically adjusting the warning threshold according to the threat level to power transmission lines at each stage, this method achieves "stage-specific" tracking throughout the entire process, representing a significant improvement over traditional fixed threshold methods.

[0003] While the multi-stage dynamic threshold method improves adaptability in principle, its early warning accuracy still heavily relies on the calculation method for threshold adjustment. Current technologies typically base threshold adjustment on relatively single indicators, lacking a comprehensive consideration of the dynamics of the fire situation in the fire area. This results in insufficient characterization of fire development, and the adjusted threshold becomes distorted to some extent, limiting further improvements in early warning effectiveness.

[0004] In view of the above, this application is hereby submitted. Summary of the Invention

[0005] The purpose of this invention is to provide a method and system for analyzing the spread trend of wildfires by combining real-time environmental information. This method and system performs grid processing on the fire area and selectively constructs different fire observation grids. It uses the real-time environmental data changes of each fire observation grid to determine the development of the fire front, and then determines the fire spread parameters of the entire fire area. Based on this, it calculates the dynamic adjustment threshold of the fire situation, which is more in line with the current fire development situation in the fire area and improves the early warning effect of the threshold parameters.

[0006] The embodiments of the present invention are implemented as follows:

[0007] Firstly, a method for analyzing the spread trend of wildfires by combining real-time environmental information includes the following steps: determining the core of the fire area and the associated meteorological station group of the fire area, wherein the associated meteorological station group refers to a group of at least one meteorological station capable of directly observing real-time environmental data of the fire area; constructing an initial observation area based on the core of the fire area and each meteorological station, and gridding the initial observation area to obtain multiple fire observation grids; wherein the initial observation area is constructed by constructing multiple observation areas at different distances from the meteorological stations to the core of the fire area, and the initial observation area is formed by superimposing multiple observation areas. The system performs real-time environmental data updates for each fire observation grid to obtain fire change parameters for a single fire observation grid in each update cycle. These fire change parameters are calculated based on the degree of change in real-time environmental data observed in adjacent update cycles. Fire change trend data is determined based on all fire change parameters corresponding to each fire observation grid. Fire head information for the fire area is identified based on the fire change trend data of all fire observation grids. The fire spread adjustment coefficient for the fire area is calculated based on the obtained fire head information, and this fire spread adjustment coefficient is used as the basis for calculating the wildfire alarm threshold for the fire area.

[0008] In some optional implementations, the step of constructing an initial observation area based on the core of the fire area and each meteorological station, and then gridding the initial observation area to obtain multiple fire observation grids, includes the following steps: determining the line distance between each meteorological station and the core of the fire area; constructing a first observation area around the core of the fire area using the shortest line distance as the radius, and constructing a second observation area around the core of the fire area using the longest line distance as the radius; superimposing the first observation area and the second observation area to form the initial observation area; performing a first gridding on the first observation area to obtain a fire observation grid, and performing a second gridding on the second observation area outside the first observation area to obtain a fire observation grid, wherein the size of the first gridding is smaller than the size of the second gridding.

[0009] In some optional implementations, the method further includes optimizing the initial observation area: determining whether a meteorological station is located outside the fire area, and constructing the first observation area based on the shortest line distance between a meteorological station located outside the fire area and the core of the fire area; determining whether a meteorological station is located within the observation area, and constructing the second observation area based on the longest line distance between a meteorological station located within the observation area and the core of the fire area; wherein, whether a meteorological station is located outside the fire area means that the meteorological station is located outside the coverage area of ​​the fire area determined in the previous update cycle; whether a meteorological station is located within the observation area means that the line distance between the meteorological station and the core of the fire area does not exceed a first preset distance and is located within the observation area.

[0010] In some optional implementations, after determining whether a meteorological station is located outside the fire area and constructing the first observation area based on the shortest line distance between a meteorological station located outside the fire area and the core of the fire area, the method further includes the following steps: marking the shortest line between a meteorological station located outside the fire area and the core of the fire area as a first marked line, and marking the longest line between a meteorological station located within the fire area and the core of the fire area as a second marked line; determining whether the distance difference between the first marked line and the second marked line is greater than a second preset distance; if the distance difference is greater than the second preset distance, constructing the first observation area based on the sum of the distance of the second marked line and the second preset distance; if the distance difference is not greater than the second preset distance, constructing the first observation area based on the distance of the first marked line.

[0011] In some optional implementations, the step of updating the real-time environmental data of each fire observation grid to obtain the fire change parameters of a single fire observation grid in each update cycle includes the following steps: taking the real-time environmental data of a single fire observation grid in each update cycle, which is obtained by comprehensively calculating the real-time data observed by all meteorological stations in the associated meteorological station group, including the following steps: determining the single environmental data of the corresponding fire observation grid observed by each meteorological station; determining the calculation weight of each meteorological station; comprehensively calculating the real-time environmental data by combining the single environmental data observed by all meteorological stations with their respective calculation weights; wherein, the calculation weight of the meteorological station is comprehensively determined by the distance between the meteorological station and the core of the fire area and the distance between the meteorological station and the fire observation grid; comparing the two real-time environmental data corresponding to a single fire observation grid in adjacent update cycles to determine the fire change parameters.

[0012] In some optional implementations, the method further includes a step of correcting the real-time environmental data of a single fire observation grid: identifying fire observation grids with abnormal real-time environmental data in the same update cycle, and recording them as abnormal observation grids; acquiring remote sensing environmental data of the abnormal observation grids in the same update cycle; merging the remote sensing environmental data with the real-time environmental data to obtain corrected real-time environmental data, and using the corrected real-time environmental data as the basis for calculating the fire change parameters; wherein, the higher the abnormal value of the abnormal observation grid, the smaller the merging weight of its real-time environmental data, and the larger the merging weight of its remote sensing environmental data.

[0013] In some optional implementations, acquiring remote sensing environmental data for the same update cycle of the anomaly observation grid includes the following steps: determining the anomaly result type of the anomaly observation grid in the update cycle, wherein the anomaly result type includes mild anomaly, severe anomaly, and no displayed anomaly; matching the source type of the remote sensing environmental data according to the anomaly result type, including the following scenarios: if it is a mild anomaly, then select the remote sensing environmental data source closest to the current update cycle time; if it is a severe anomaly, then select the predicted value source of the remote sensing data in the current update cycle; if it is no displayed anomaly, then select the remote sensing environmental data source according to the degree of anomaly of the remote sensing environmental data between adjacent update cycles.

[0014] In some optional implementations, determining the fire change trend data based on all fire change parameters corresponding to each fire observation grid, and identifying the fire head information of the fire area based on the fire change trend data of all fire observation grids, includes the following steps: obtaining all fire change parameters corresponding to each fire observation grid, arranging all fire change parameters in chronological order to construct a fire change trend line; determining whether the fire observation grid is a fire head grid based on the graph of the fire change trend line; performing positional analysis on all determined fire head grids to obtain fire head grid distribution data; and determining the fire head information based on the fire head grid distribution data, wherein the fire head information includes the size, number, distribution direction, and spread rate of the fire head area.

[0015] In some optional implementations, calculating the fire spread adjustment coefficient for the fire area based on the obtained firehead information includes the following steps: constructing a firehead threat model based on the size, number, distribution direction, and spread rate of the firehead areas; determining the time barrier window parameters for the firehead areas based on the firehead threat model; and comparing the selection range of the fire spread adjustment coefficient with the time barrier window parameters. Specifically, determining the time barrier window parameters for the firehead areas based on the firehead threat model includes: outputting the firehead threat level by inputting parameters of the size, number, and spread rate of the firehead areas in the current update cycle; determining the basic barrier window parameters based on the firehead threat level; determining the modified barrier window parameters based on the distribution direction of the firehead areas; and merging the basic barrier window parameters and the modified barrier window parameters into the time barrier window parameters.

[0016] Secondly, a wildfire spread trend analysis system that combines real-time environmental information includes:

[0017] The first acquisition unit is used to determine the core of the fire area and the associated meteorological station group of the fire area. The associated meteorological station group refers to a group of at least one meteorological station that can directly observe the real-time environmental data of the fire area.

[0018] The first processing unit is used to construct an initial observation area based on the core of the fire area and each meteorological station, and to grid the initial observation area to obtain multiple fire observation grids; wherein, the initial observation area is constructed by constructing multiple observation areas from different distances from the meteorological stations to the core of the fire area, and the initial observation area is formed by superimposing multiple observation areas.

[0019] The first calculation unit is used to update the environmental data of each fire observation grid in real time and obtain the fire change parameters of a single fire observation grid in each update cycle. The fire change parameters are calculated by the degree of change of the real-time environmental data observed in the corresponding adjacent update cycles.

[0020] The second calculation unit is used to determine the fire change trend data based on all fire change parameters corresponding to each fire observation grid, identify the fire head information of the fire area based on the fire change trend data of all fire observation grids, calculate the fire spread adjustment coefficient of the fire area based on the obtained fire head information, and use the fire spread adjustment coefficient as the basis for calculating the wildfire alarm threshold of the fire area.

[0021] The beneficial effects of the embodiments of the present invention are:

[0022] The wildfire spread trend analysis method and system provided in this invention, which combines real-time environmental information, constructs a dynamic initial observation area by integrating the fire area (initial stage) of a wildfire with associated meteorological stations. This initial observation area can more purposefully select observation data from different meteorological stations to construct a more hierarchical initial observation area. By gridding this initial observation area, the changes in each fire observation grid are analyzed to determine the wildfire spread in the entire fire area. In particular, by analyzing the fire change parameters of a single fire observation grid, the fire head information of the fire area is determined. Based on the fire head information, the spread of the fire is accurately analyzed, thereby fully grasping the development trend and threat level of the fire. Finally, the wildfire alarm threshold of the fire area is calculated as the basis for adjusting the wildfire alarm threshold values ​​at different stages, improving the accuracy of multi-stage early warning of wildfire disasters in power transmission projects. Attached Figure Description

[0023] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as a limitation on the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0024] Figure 1A flowchart of the main steps of the analysis method is provided for embodiments of the present invention;

[0025] Figure 2 for Figure 1 A flowchart of one of the main steps, S200, is shown below;

[0026] Figure 3 for Figure 1 A flowchart of one of the main steps, S300, is shown.

[0027] Figure 4 for Figure 1 A flowchart of one of the main steps, S400, is shown.

[0028] Figure 5 A modular schematic diagram of the analysis system is provided for embodiments of the present invention.

[0029] Icons: 500 - Analysis System; 510 - First Acquisition Unit; 520 - First Processing Unit; 530 - First Calculation Unit; 540 - Second Calculation Unit. Detailed Implementation

[0030] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, 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 embodiments of the present invention, and not all embodiments. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations.

[0031] Therefore, the following detailed description of the embodiments of the invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the invention without inventive effort are within the scope of protection of the invention.

[0032] It should be understood that the terms "system," "device," and / or "module" used in this invention are methods for distinguishing different components, elements, parts, sections, or assemblies at different levels. However, if other terms can achieve the same purpose, they may be replaced by other expressions.

[0033] As indicated in this invention and the claims, unless the context clearly indicates otherwise, the words "a," "an," "an," and / or "the" do not specifically refer to the singular and may also include the plural. Generally, the terms "comprising" and "including" only indicate the inclusion of explicitly identified steps and elements, which do not constitute an exclusive list, and the method or apparatus may also include other steps or elements.

[0034] Flowcharts are used in this invention to illustrate the operations performed by the system according to embodiments of this application. It should be understood that the preceding or following operations are not necessarily performed precisely in sequence. Instead, the steps can be processed in reverse order or simultaneously. Furthermore, other operations can be added to these processes, or one or more steps can be removed from them.

[0035] Example: Previously, the fixed threshold identification method used in the field of power transmission line wildfire identification and early warning had significant limitations. Fixed thresholds could not reflect the dynamic changes in environmental observation parameters during fire development, and could not provide accurate and detailed early warning signals tailored to different stages of wildfire development. This made it impossible to formulate effective response strategies in advance during actual protection work, failing to meet the actual protection needs of power transmission lines. Based on this, we propose a power transmission line wildfire early warning scheme based on dynamic thresholds. By adopting a dynamic threshold approach, multi-stage identification and early warning are achieved. The alarm thresholds are adjusted in real time according to the wildfire risk level and environmental changes, significantly reducing false alarms and missed alarms, and improving early warning accuracy. Furthermore, by tracking the wildfire development trend throughout the multi-stage identification process and using different thresholds for precise early warning at different stages, the accuracy of wildfire identification and early warning is greatly improved. Under this technical solution, it is necessary to consider how to determine and adjust the alarm thresholds based on real-time data on wildfire risk levels and environmental changes. Existing technologies use a single method to calculate the adjustment of alarm thresholds. For example, they directly collect and calculate real-time data on wildfire risk levels and environmental changes based on periodic observations of temperature, infrared radiation, and smoke concentration in the fire area. This method can only determine the current fire extent and intensity, but it ignores the dynamic changes in the fire, especially the direction of fire development. As a result, the final adjustment of alarm thresholds cannot accurately reflect the fire threat and spread, leading to distorted representation results.

[0036] To address the aforementioned issues, this embodiment proposes a method for analyzing wildfire spread trends by incorporating real-time environmental information. This method enables a more detailed analysis of the fire situation, dynamic development, and spread threat within the fire zone, thereby ensuring that the wildfire alarm threshold calculated using the final determined fire spread adjustment coefficient more accurately reflects the urgency of the wildfire's dynamic development. Please refer to the following for details. Figure 1 This embodiment provides a method for analyzing the spread trend of wildfires by combining real-time environmental information, which includes the following steps:

[0037] S100: Determine the core of the fire area and the associated meteorological station group for that fire area. The associated meteorological station group refers to a group of at least one meteorological station capable of directly observing real-time environmental data of the fire area. This step means that after determining that the initial power transmission line caused the wildfire, the location of the wildfire is identified as the initial core of the fire area. Then, automatic meteorological data collection points are determined around the fire area, that is, meteorological stations capable of directly observing the real-time environment (temperature field, humidity field, wind field, infrared radiation field, etc.) of the fire area. The distribution of these meteorological stations is spread around the core of the fire area, and only one meteorological station needs to be determined in the same direction (positive and negative deflection angles less than 10° are tentatively defined as the same direction), thus forming a ring of associated meteorological stations around the core of the fire area.

[0038] S200: Based on the core of the fire area and each meteorological station, an initial observation area is constructed. This initial observation area is then gridded to obtain multiple fire observation grids. This step means that all the previously determined meteorological stations serve as the basis for constructing all or part of the outer contour, and the region is constructed around the core of the fire area. For example, the initial observation area is constructed by drawing circles with the core of the fire area as the center. The obtained initial observation area is then fragmented into grids, and the multiple fire observation grids are used as the basis for subsequent fire development calculations, making the calculations more refined and closer to the actual fire development results.

[0039] The initial observation area is constructed by dividing the meteorological stations into multiple observation areas at different distances from the core of the fire area. These multiple observation areas are then superimposed to form the initial observation area. This means that the construction of the initial observation area is crucial. On the one hand, the participation of all meteorological stations in the construction is to ensure the comprehensiveness of the data. On the other hand, by constructing different observation areas and superimposing them in a certain way, the inconsistent gridding ratios of different observation areas are taken into account. This allows the data computing power to be more concentrated on all grids in a certain area, thereby balancing the comprehensiveness of data collection and the concentration of computing power.

[0040] S300: Real-time environmental data is updated for each fire observation grid to obtain the fire change parameters of a single fire observation grid in each update cycle. The fire change parameters are calculated based on the degree of change of the real-time environmental data observed in the corresponding adjacent update cycles. This step means that the real-time environmental data of each fire observation grid is updated at a preset cycle interval from the initial stage of fire development to the subsequent period, thereby determining the real-time environmental data of a single fire observation grid after each update. This data is used as the fire change parameters in the subsequent calculation of the entire fire area. In other words, the fire change parameters are calculated based on the difference between the update value of the previous cycle and the update value of the current cycle, thus reflecting the real-time environmental data changes of a single fire observation grid.

[0041] S400: Determine the fire change trend data based on all fire change parameters corresponding to each fire observation grid. Identify the fire head information of the fire area based on the fire change trend data of all fire observation grids. Calculate the fire spread adjustment coefficient of the fire area based on the obtained fire head information. Use this fire spread adjustment coefficient as the basis for calculating the wildfire alarm threshold of the fire area. This step means that fire change trend data is uniformly generated by determining the fire change parameters calculated for each fire observation grid in all update cycles. This fire change trend data characterizes the real-time environmental parameter changes (including but not limited to temperature field, humidity field, wind field, infrared radiation field, etc.) of the fire observation grid throughout the entire continuous process from the initial stage of the fire to the extinguishing stage.

[0042] Then, by uniformly analyzing the fire change trend data corresponding to each of the fire observation grids, such as analyzing the steepness of the change trend and the rate of change, it is possible to determine which area of ​​the fire observation grid is in a rapid development and outward expansion trend. This is used to determine the fire head information of the entire fire area during its development process. Based on the situation of at least one fire head, the fire spread situation of the entire fire area is calculated, i.e., the fire spread adjustment coefficient. This fire spread adjustment coefficient is used as the basis for calculating the (to be adjusted) wildfire alarm threshold of the fire area during its dynamic development process.

[0043] The above technical solution identifies the core fire area and related meteorological stations to construct an initial observation area and grid it. Then, it periodically updates environmental data for each fire observation grid to obtain fire change parameters. Based on the parameters of all grids, it integrates and analyzes the fire head information and calculates the spread adjustment coefficient, thus providing a dynamic calculation basis for the wildfire alarm threshold. The entire implementation scheme uses grid subdivision and periodic data updates to achieve refined monitoring of the fire environment. By identifying the fire head, it accurately captures the direction of fire spread and dynamic development trend, so that the final generated fire spread adjustment coefficient can more realistically reflect the actual urgency of the fire, thereby improving the accuracy and timeliness of the wildfire warning threshold dynamically adjusted according to the fire stage and environmental changes.

[0044] Based on the above technical solutions, in order to ensure that the initial observation area can comprehensively and effectively reflect the changes in the fire situation in the fire area—that is, not only to observe the spread of the fire after multiple update cycles, but also to focus more on the core situation of the fire area while conducting comprehensive observation—please refer to [the relevant documentation / reference]. Figure 2 The step of constructing an initial observation area based on the core of the fire area and each meteorological station, and then gridding the initial observation area to obtain multiple fire observation grids, includes the following steps:

[0045] S210: Determine the linear distance between each meteorological station and the core of the fire area; this step means pre-determining the linear distance between each meteorological station and the core of the fire area (the initial location where the fire is identified is used as the coordinates of the core area). Then proceed to step S220: Construct a first observation area around the core of the fire area using the shortest linear distance as the radius, and construct a second observation area around the core of the fire area using the longest linear distance as the radius; that is, the first and second observation areas are obtained by drawing circles, the first observation area is a focused observation area, and the second observation area is a comprehensive observation area.

[0046] S230: The first observation area and the second observation area are superimposed to form the initial observation area; this step means that the obtained circular or near-circular first observation area and the second observation area are superimposed with the core of the fire area as the center to form the initial observation area. The initial observation area has both the first observation area located near the center for focused observation and the remaining circular part of the second observation area outside the first observation area (the part located near the outer edge) for supplementary observation, so as to achieve the purpose of comprehensive observation.

[0047] S240: The first observation area is first gridded to obtain a fire observation grid, and the second observation area outside the first observation area is second gridded to obtain a fire observation grid, wherein the size of the first grid is smaller than the size of the second grid. This step means that by first gridding the first observation area located near the center, and second gridding the remaining annular portion of the second observation area located near the outer edge, and with the size of the first grid being smaller than the size of the second grid, fire observation grids of different sizes are obtained for the two observation areas. The grid of the first observation area is smaller (e.g., at the ten-meter level), which allows for higher accuracy of the observation data, while the grid of the second observation area is relatively larger (e.g., at the hundred-meter level), which reduces the pressure on data resource acquisition when observations are carried out simultaneously.

[0048] By employing the aforementioned technical solution, the shortest and longest linear distances between meteorological stations and the fire's core are determined. Concentric and superimposed first and second observation areas are then constructed, spatially forming an initial observation area that focuses on the fire's core while covering its peripheral spread. Based on this, smaller grid sizes are used in areas closer to the core to achieve high-precision data acquisition, while larger grid sizes are used in areas closer to the periphery to ensure comprehensive observation while reducing data acquisition complexity. This dual-layer area overlay and differentiated grid division enhances the ability to capture detailed changes in the fire's center while also effectively monitoring the overall spread, thereby improving the accuracy of fire-related parameters in the core area and optimizing the efficiency of data resource utilization.

[0049] Considering the dynamic development of the fire in the fire area, with the fire spreading outwards at different data update cycles, the first observation area needs dynamic optimization to consistently monitor the area with the largest fire intensity. Furthermore, the second observation area should not be too large, as this would result in lower data value. Therefore, further dynamic optimization of the initial observation area is required. Please refer to [link / reference needed]. Figure 2 It also includes the step of optimizing the initial observation area:

[0050] S221: Determine whether the meteorological station is located outside the fire zone. Construct the first observation area using the shortest line distance between the meteorological station located outside the fire zone and the core of the fire zone. This means first determining whether the meteorological station's coordinates are outside the fire zone (areas unaffected by the fire). Whether the meteorological station is located outside the fire zone means that the meteorological station is outside the coverage area of ​​the fire zone determined in the previous update cycle. If the meteorological station is located within the fire zone, on the one hand, the observation data may be affected by the fire, leading to increased errors; on the other hand, the first observation area constructed in this way cannot focus on all areas affected by the fire, causing subsequent calculations of fire change parameters to be distorted. Therefore, the first observation area needs to always cover areas affected by the fire to ensure data focus and accuracy.

[0051] Similarly, to determine whether a meteorological station is located within the observation area, the second observation area is constructed using the longest line distance between a meteorological station within the observation area and the core of the fire area. A meteorological station being located within the observation area means that the line distance between the meteorological station and the core of the fire area does not exceed a first preset distance and is within the observation area. This means that if a meteorological station is located outside the observation area (too far away), on the one hand, the constructed second observation area will be too large, resulting in the collection of too much low-value data; on the other hand, the data collection error will be greater for meteorological stations that are too far away, which is not conducive to improving the accuracy of subsequent fire situation change parameters. Therefore, the second observation area needs to be controlled within a certain range, covering the maximum affected area of ​​the wildfire from its initial stage to the end of the rescue and firefighting process, but not exceeding this range too much, which would result in low data calculation value and accuracy.

[0052] The above technical solution dynamically assesses the spatial relationship between meteorological stations and the fire area. A first observation area is constructed using the shortest line distance between a meteorological station outside the fire area and the core of the fire area. This ensures the focused area can track the fire's spread in real time, preventing data distortion due to interference from meteorological stations within the fire area. Simultaneously, a second observation area is constructed using the longest line distance between a meteorological station within the observation area and the core of the fire area. This reasonably controls the outer monitoring range within the effective boundary that the wildfire might affect, avoiding the collection of large amounts of low-value data due to excessive expansion. By dynamically selecting meteorological stations participating in the construction of the areas, the first observation area closely follows the actual fire development area to ensure data focusing accuracy, while the second observation area maintains an appropriate coverage range to balance observational comprehensiveness and data validity. This continuously optimizes the boundaries of the initial observation area during the dynamic evolution of the fire, providing a more reliable data foundation for the accurate calculation of subsequent fire change parameters.

[0053] Based on the above technical solution, considering the possibility that the first observation area may not be sufficiently focused after construction, for example, after the fire has just spread to the meteorological station that participated in constructing the first observation area, the next meteorological station participating in constructing the first observation area along the outer edge is far away, resulting in the constructed first observation area being larger than the fire-affected area. In this case, it is necessary to make the first observation area more closely aligned with the fire-affected area within a certain period of time, that is, the construction of the first observation area still needs to be optimized. Specifically, after determining whether the meteorological station is located outside the fire area and constructing the first observation area based on the shortest line distance between the meteorological station located outside the fire area and the core of the fire area, the following steps are also included:

[0054] The shortest line connecting the meteorological station outside the fire zone to the core of the fire zone is designated as the first marked line, and the longest line connecting the meteorological station within the fire zone to the core of the fire zone is designated as the second marked line. This means constructing a line that just crosses the previous meteorological station participating in the construction of the first observation area and connects it to the core of the fire zone, designated as the second marked line. Then, constructing a line connecting the meteorological station closest to the current fire zone's periphery (the first observation area constructed by this meteorological station can cover the entire fire's spread range) and the core of the fire zone is designated as the first marked line.

[0055] Then, it is determined whether the distance difference between the first marker line and the second marker line is greater than a second preset distance. This second preset distance is a pre-set distance value (which can be an empirical value or a data learning prediction value) used to control the maximum circular range of the first observation area. If the distance difference is greater than the second preset distance, the first observation area is constructed based on the sum of the distance of the second marker line and the second preset distance, indicating that the first marker line is too long and the sum of the distance of the second marker line and the second preset distance is needed as the basis for constructing the first observation area. If the distance difference is not greater than the second preset distance, the first observation area is constructed based on the distance of the first marker line, indicating that the length of the first marker line is within an acceptable range and can be used as the basis for constructing the first observation area.

[0056] According to the above technical solution, by introducing a first marker line connecting meteorological stations located outside the fire area and a second marker line connecting meteorological stations located within the fire area, and by comparing the distance difference between the two with a second preset distance, the construction radius of the first observation area is dynamically adjusted. That is, when the first marker line is too long and causes the area to expand excessively, the sum of the distance of the second marker line and the second preset distance is used as the construction basis. Thus, even when the next available meteorological station is far away, the first observation area can still closely fit the actual range of the fire. This can, to a certain extent, avoid the problem of excessive expansion of the first observation area that may be caused by the sparse distribution of meteorological stations, and ensure that the focused area always maintains accurate coverage of the fire front during the dynamic spread of the fire.

[0057] In some implementations, to improve the accuracy of real-time environmental data calculations for the fire observation grid, a weighted comprehensive calculation method based on data from multiple observations can be used. Please refer to [link / reference] for details. Figure 3 The step of updating the environmental data in real time for each fire observation grid to obtain the fire change parameters of a single fire observation grid in each update cycle includes the following steps:

[0058] First, real-time environmental data is updated for each fire observation grid. This means obtaining the real-time environmental data of a single fire observation grid in each update cycle. This real-time environmental data is obtained by comprehensively calculating the real-time data observed by all meteorological stations in the associated meteorological station group, and includes the following steps:

[0059] S310: Determine the single environmental data of the corresponding fire observation grid observed by each meteorological station; this step means first obtaining the data observed by each meteorological station for the same fire observation grid in this update cycle, and recording it as single environmental data. Then proceed to step S320: Determine the calculation weight of each meteorological station; this step means pre-configuring a weighted calculation weight for each meteorological station. In some implementations, the calculation weight of a meteorological station is determined by a combination of the distance between the meteorological station and the core of the fire area and the distance between the meteorological station and the fire observation grid. For example, the farther the distance from the core of the fire area, the lower the calculation weight; the closer the distance from the fire observation grid, the higher the calculation weight, so as to balance the value and accuracy of the observation data. Then perform weighted calculation, i.e., step S330: Combine the single environmental data observed by all meteorological stations with their respective calculation weights to calculate the real-time environmental data; this step means that the observation data of each meteorological station for the fire observation grid, combined with its own calculation weight, participates in the entire weighting, so that all meteorological stations are finally weighted and combined to obtain the real-time environmental data of the fire observation grid.

[0060] Next, the degree of change is calculated based on the real-time environmental data of the fire observation grid in two update cycles. That is, step S340 is performed: comparing the two real-time environmental data corresponding to a single fire observation grid in adjacent update cycles to determine the fire change parameter. This step means that the change ratio of the real-time environmental data obtained in the previous update cycle of the fire observation grid and the real-time environmental data obtained in the current update cycle is calculated, and the fire change parameter is determined by this change ratio.

[0061] Through the above technical solution, multi-source data fusion processing is performed on each fire observation grid. By using multi-site weighted calculation, the random errors that may be introduced by a single observation source can be effectively avoided. At the same time, the design of the correlation between weight and spatial distance takes into account the representativeness and accuracy of the data sources, so that the real-time environmental data of each fire observation grid can more comprehensively and evenly reflect the actual fire status. The fire change obtained by dynamic comparison can provide a more accurate and time-comparable data foundation for subsequent fire development trend analysis.

[0062] Based on the above technical solutions, to further ensure the reliability of real-time environmental data calculations, especially when meteorological stations are affected by fires leading to increased data observation errors or when abnormal terrain in the data collection grid causes data anomalies, remote sensing data can be used to supplement the data and fill these gaps. Specifically, after acquiring the real-time environmental data of a single fire observation grid in each update cycle, the process also includes a step of correcting the real-time environmental data of that single fire observation grid.

[0063] The process involves identifying fire observation grids with abnormal real-time environmental data within the same update cycle, and denoting them as abnormal observation grids. This step involves identifying abnormal fire observation grids during the calculation of real-time environmental data for all fire observation grids within the same update cycle. These abnormal grids are those whose real-time environmental data significantly differs from that of their neighboring grids. For example, if the surrounding area is within the fire's reach, the actual temperature or radiation data may be normal. Conversely, if the surrounding area is at the edge of the fire's reach, where temperatures are low or normal, the actual temperature or radiation data may be higher. These fire observation grids with clearly abnormal real-time environmental data under horizontal comparison are denoted as abnormal observation grids. Then, remote sensing environmental data for the abnormal observation grid within the same update cycle is acquired. This step involves supplementing or compensating for the abnormal observation grid by acquiring remote sensing environmental data from the same update cycle when its real-time environmental data is abnormal.

[0064] The remote sensing environmental data and real-time environmental data are merged to obtain corrected real-time environmental data. This means that the remote sensing environmental data and real-time environmental data are weighted using a weighted calculation method to obtain corrected real-time environmental data, which is used as the basis for calculating the fire change parameters. Specifically, the higher the outlier value of the anomaly observation grid, the smaller the merging weight in the real-time environmental data weighting, and the larger the merging weight in the remote sensing environmental data weighting.

[0065] Using the above technical solution, real-time environmental data of each fire observation grid are compared horizontally within the same update cycle to identify abnormal observation grids with obvious data anomalies. For these grids, remote sensing environmental data from the same period is introduced for weighted fusion. The higher the degree of anomaly, the lower the weight of real-time data in the fusion and the higher the weight of remote sensing data. This generates corrected real-time environmental data as the basis for subsequent calculations. By using remote sensing data to dynamically compensate for ground observation data that is distorted by fire interference or terrain, the error risk of observations from a single meteorological station due to environmental factors can be effectively reduced. (It should be noted that remote sensing data has a greater lag than ground station observation data, and normal ground station observation data is given priority in the calculation.)

[0066] Since the correction of real-time environmental data is calculated by weighting remote sensing data with real-time environmental data, and considering that remote sensing data has a greater lag than meteorological station observation data, it is necessary to classify the sources of remote sensing data according to the degree of anomalies. Specifically, the acquisition of remote sensing environmental data in the same update cycle of the anomaly observation grid includes the following steps:

[0067] The outlier result type of the abnormal observation grid in the current update cycle is determined. The outlier result type includes mild anomaly, severe anomaly, and no displayed anomaly. The source type of the remote sensing environmental data is matched according to the outlier result type, including the following situations:

[0068] If the anomaly is minor, select the remote sensing environmental data source that is closest to the current update cycle time. This situation indicates that the real-time environmental data is slightly distorted, so select remote sensing environmental data from the same period. If there is a difference between the update time of the remote sensing data and the update time of the real-time environmental data, select the remote sensing environmental data as the source based on the principle of closest time.

[0069] If there is a severe anomaly, the predicted value of the remote sensing data in the current update cycle is selected as the source. This situation indicates that the real-time environmental data is severely distorted. If the remote sensing environmental data with the closest time is selected as the source, errors will inevitably occur due to the difference between the update time of the remote sensing data and the update time of the real-time environmental data. Therefore, the update time of the real-time environmental data can be used as the standard to determine the predicted value of the remote sensing data at that update time. For example, the value at that update time can be determined by fitting multi-period data (in other implementations, machine learning can also be used to obtain the value).

[0070] If no anomalies are displayed, the source of remote sensing environmental data is selected based on the degree of anomaly in the remote sensing environmental data between adjacent update cycles. This situation indicates that real-time environmental data cannot be measured by ground stations. To rule out whether the cause is the station or the anomaly in the observation grid itself, it is necessary to further judge based on whether historical remote sensing environmental data is abnormal. If historical remote sensing environmental data does not show regular changes such as increasingly higher or lower temperatures, then the cause is the station. In this case, the predicted value under the current update cycle is selected as the source of remote sensing environmental data. If the change pattern of historical remote sensing environmental data is consistent with the change pattern of real-time environmental data observed by the station, and is close to or the same as no data is displayed, then it is speculated that the cause is the anomaly in the observation grid itself. In this case, the remote sensing environmental data with the closest time is selected as the source.

[0071] By identifying anomalous observation grids and introducing weighted corrections based on remote sensing data, this method further differentiates the source types of remote sensing data according to the severity of the anomalies. Specifically, for minor anomalies, the most recent remote sensing data is selected to balance timeliness and a smooth transition; for severe anomalies, predicted values ​​based on multi-period fitting or learning are used as the source to avoid biases potentially introduced by data lag; and for anomalies without visible data, the variation patterns of historical remote sensing data are analyzed to distinguish between station malfunctions and grid anomalies, thus selecting predicted values ​​or contemporaneous data as the source. This dynamic matching of anomaly severity and source type fully leverages the real-time advantage of ground station observations while effectively avoiding the interference of remote sensing data lag on correction results in severe anomaly scenarios. Furthermore, the source tracing for anomalies without visible data further enhances the logical rigor of the data correction.

[0072] The solutions described in the above embodiments further ensure the reliability and accuracy of real-time environmental data, resulting in more accurate and reliable fire change parameters, thus providing data support for subsequent calculations of fire head information. Please refer to... Figure 4 In some implementations, determining the fire change trend data based on all fire change parameters corresponding to each fire observation grid, and identifying the fire head information of the fire area based on the fire change trend data of all fire observation grids, includes the following steps:

[0073] S410: Obtain all fire change parameters corresponding to each fire observation grid, arrange all fire change parameters in time sequence, and construct a fire change trend line; This step means that for each fire observation grid, the fire change trend line of the fire observation grid is constructed by the fire change parameters obtained in each update cycle. That is, by arranging the fire change parameters in time sequence, the fire change trend line is obtained, which reflects the development trend of the fire change parameters of the fire observation grid from the initial stage of the wildfire to the current cycle (the last period is the extinguishing period).

[0074] S420: Determine whether a fire observation grid is a firehead grid based on the graph of the fire situation trend line. This means determining whether a grid is a firehead grid based on whether the graph of the fire situation trend line meets the criteria for firehead identification (e.g., similarity to historical firehead development trends such as temperature and radiation). The status of firehead grids changes dynamically with the development of the fire, and information is updated through different update cycles. Then, perform location analysis on all identified firehead grids to obtain firehead grid distribution data. This means calculating the distribution of all firehead grid locations (calculating coordinates, area, formation time difference, and contour bias, etc.) to obtain firehead grid distribution data.

[0075] S430: Determine the firehead information based on the firehead grid distribution data, wherein the firehead information includes the size, number, distribution direction, and spread rate of the firehead area. This step means that the firehead grid distribution data obtained from the above calculation is integrated into a firehead information (set), which includes the size of the firehead area (e.g., determined by the coordinates and area of ​​each firehead grid), the number (e.g., determined by the number of independently distributed firehead grids), the distribution direction (e.g., determined by the coordinates and contour bias of a single firehead grid), and the spread rate (e.g., determined by the time difference of formation of all firehead grids and the contour bias), thereby obtaining a dataset that can characterize the firehead situation in the fire area.

[0076] By constructing a fire change trend line based on time-series fire change parameters for each fire observation grid, and determining whether a grid is a fire front based on the graphical characteristics of this trend line, spatial distribution analysis is performed on all fire front grids to extract multi-dimensional fire front information such as the size, number, distribution direction, and spread rate of the fire front area. By combining the temporal dimension of fire development with the spatial dimension of distribution, dynamic positioning of the active fire front is achieved through trend line graphical recognition. Furthermore, the distribution analysis of the fire front grids integrates discrete fire front locations into a fire front information set with spatial attributes, thus providing a comprehensive data foundation for subsequent calculation of the fire spread coefficient, encompassing both the evolution of fire intensity and the spatial expansion trend.

[0077] By obtaining a comprehensive dataset of fire information, the fire spread adjustment coefficient can be calculated. Please refer to [link / reference needed]. Figure 4 The calculation of the fire spread adjustment coefficient for the fire area based on the obtained fire head information includes the following steps:

[0078] S440: Constructing a fire threat model based on the size, number, distribution direction, and spread rate of fire-prone areas. This step indicates that the fire threat model uses the size, number, distribution direction, and spread rate of fire-prone areas as core input parameters, and outputs a quantitative index characterizing the degree of fire threat through a comprehensive constraint mechanism. Specifically, firstly, the size of the fire-prone areas is normalized and converted into an area weight coefficient to reflect the burning intensity of the fire. Simultaneously, a risk superposition factor is set based on the number of fire-prone areas to reflect the cumulative threat to transmission lines when multiple fires start. In the directional dimension, the model introduces the angle between the transmission line orientation and the main fire spread direction as a spatial constraint; the smaller the angle, the higher the threat weight. Regarding the spread rate, a rate grading function is constructed to convert the instantaneous spread speed into a time urgency coefficient. Furthermore, the model employs a weighted fusion algorithm to nonlinearly couple the parameters of the above four dimensions and adaptively adjusts the weights using geographical environmental data, ultimately outputting a dynamically updated fire threat index, which serves as the basis for determining the subsequent processing time window parameters.

[0079] S450: Determine the time barrier window parameters for the fire front area based on the fire front threat model. This step involves inputting parameters such as the size, number, distribution direction, and spread rate of different fire front areas, and then outputting a fire front threat index. The corresponding time barrier window parameters can be determined according to a preset lookup table. However, during the determination of these time barrier window parameters, further adjustments are made based on the distribution direction of the fire front areas to address situations where the distribution direction threatens important areas or critical power facilities in reality.

[0080] Specifically, the time barrier window parameters for determining the fire front area based on the fire front threat model include: outputting the fire front threat level by inputting parameters such as the size, number, and spread rate of the fire front area in the current update cycle; that is, within the current update cycle, the size, number, and spread rate of the fire front area determined in real time are used as input, and the current fire front threat level is output after comprehensive calculation. This level quantifies the immediate degree of harm of the fire to the transmission line.

[0081] Then, the basic barrier window parameters are determined based on the fire threat level; that is, the basic barrier window parameters are mapped according to the fire threat level. These parameters represent the basic time or space range required to suppress the spread of fire without considering the direction of the fire.

[0082] Next, the modified barrier window parameters are determined based on the distribution direction of the fire front area. This means that, based on the basic barrier window parameters, the distribution direction of the fire front area is introduced as a correction factor. By analyzing the spatial relationship between the main fire spread direction and the location of important areas or important power facilities, the amplification or attenuation effect of the directional angle on the threat is calculated, thereby generating the modified barrier window parameters to adjust the priority or range of the basic window in different directions.

[0083] Finally, the basic barrier window parameters and the modified barrier window parameters are combined into the aforementioned time barrier window parameters. This means that the basic window and the modified window are combined through weighted or superimposed methods to obtain a comprehensive time barrier window parameter. This time barrier window parameter can dynamically reflect the real-time changes and spatial directionality of the fire threat, providing accurate time-based decision-making for power transmission line wildfire early warning and emergency response, ensuring that effective barrier measures are taken before the fire approaches critical facilities.

[0084] S460: Based on the time barrier window parameter, refer to the selection range of the fire spread adjustment coefficient; this step means that by mapping the calculated time barrier window parameter size to the value range of the fire spread adjustment coefficient, the larger the time barrier window parameter, the smaller the value range of the fire spread adjustment coefficient.

[0085] By constructing a fire threat model, the parameters of four dimensions—size, number, distribution direction, and spread rate of fire front areas—are nonlinearly coupled and weighted to output a dynamically updated fire threat index. Based on this index, basic barrier window parameters are determined, and modified barrier window parameters are generated based on the spatial relationship between the main fire spread direction and critical facilities. These two are combined into a comprehensive time barrier window parameter. Finally, the magnitude of this parameter maps the selection range of the fire spread adjustment coefficient. This entire implementation scheme integrates multiple factors such as fire intensity, multi-point cumulative effect, spatial directionality, and spread rate into a unified threat quantification index. Through direction correction, the time barrier window dynamically reflects the actual approach of the fire front to critical facilities, thus creating a negative correlation between the value of the fire spread adjustment coefficient and the real-time changes and spatial directionality of the fire threat. This provides a quantitative basis for the dynamic adjustment of wildfire alarm thresholds that is both timely and spatially targeted.

[0086] This embodiment also provides a wildfire spread trend analysis system 500 that combines real-time environmental information. Please refer to [link / reference]. Figure 5 This is a modular schematic diagram of the wildfire spread trend analysis system 500 that combines real-time environmental information. It is mainly used to divide the wildfire spread trend analysis system 500 into functional modules according to the embodiments of the above method. For example, it can be divided into individual functional modules, or two or more functions can be integrated into one processing module. The integrated modules can be implemented in hardware or as software functional modules. It should be noted that the module division in this invention is illustrative and only represents one logical functional division; other division methods may be used in actual implementation. For example, in the case of dividing each functional module according to its corresponding function, Figure 5 The diagram shown is only a schematic of a system / device. The wildfire spread trend analysis system 500, which combines real-time environmental information, may include a first acquisition unit 510, a first processing unit 520, a first calculation unit 530, and a second calculation unit 540. The functions of each unit module are described below.

[0087] The first acquisition unit 510 is used to determine the core of the fire area and the associated meteorological station group of the fire area. The associated meteorological station group refers to a group of at least one meteorological station that can directly observe the real-time environmental data of the fire area.

[0088] The first processing unit 520 is used to construct an initial observation area based on the core of the fire area and each meteorological station, and to grid the initial observation area to obtain multiple fire observation grids. The initial observation area is constructed from multiple observation areas at different distances from the meteorological stations to the core of the fire area, and these multiple observation areas are superimposed to form the initial observation area. In some embodiments, the first processing unit 520 is further used to determine the line distance between each meteorological station and the core of the fire area; to construct a first observation area around the core of the fire area using the shortest line distance as the radius, and to construct a second observation area around the core of the fire area using the longest line distance as the radius; to superimpose the first observation area and the second observation area to form the initial observation area; to perform a first gridding on the first observation area to obtain the fire observation grid, and to perform a second gridding on the second observation area outside the first observation area to obtain the fire observation grid. The system is also used to determine whether a meteorological station is located outside the fire zone, and to construct a first observation area based on the shortest line distance between a meteorological station outside the fire zone and the core of the fire zone; and to determine whether a meteorological station is located within the observation area, and to construct a second observation area based on the longest line distance between a meteorological station within the observation area and the core of the fire zone. It is further used to mark the shortest line connecting a meteorological station outside the fire zone to the core of the fire zone as a first marked line, and the longest line connecting a meteorological station within the fire zone to the core of the fire zone as a second marked line; to determine whether the distance difference between the first marked line and the second marked line is greater than a second preset distance; if the distance difference is greater than the second preset distance, the first observation area is constructed based on the sum of the distance of the second marked line and the second preset distance; if the distance difference is not greater than the second preset distance, the first observation area is constructed based on the distance of the first marked line.

[0089] The first calculation unit 530 is used to update the real-time environmental data of each fire observation grid to obtain the fire change parameters of a single fire observation grid in each update cycle. The fire change parameters are calculated based on the degree of change in the real-time environmental data observed in corresponding adjacent update cycles. In some embodiments, the first calculation unit 530 is also used to acquire the real-time environmental data of a single fire observation grid in each update cycle. This real-time environmental data is obtained by comprehensively calculating the real-time data observed by all meteorological stations in the associated meteorological station group. This includes the following steps: determining the single environmental data of the corresponding fire observation grid observed by each meteorological station; determining the calculation weight of each meteorological station; comprehensively calculating the real-time environmental data by combining the single environmental data observed by all meteorological stations with their respective calculation weights; wherein the calculation weight of a meteorological station is comprehensively determined by the distance between the meteorological station and the core of the fire area and its distance from the fire observation grid; and comparing the two real-time environmental data corresponding to a single fire observation grid in adjacent update cycles to determine the fire change parameters. And a fire observation grid used to identify anomalies in real-time environmental data under the same update cycle, denoted as an anomaly observation grid; obtain remote sensing environmental data of the anomaly observation grid under the same update cycle; merge the remote sensing environmental data with the real-time environmental data to obtain corrected real-time environmental data, and use the corrected real-time environmental data as the basis for calculating the fire change parameters;

[0090] The second calculation unit 540 is used to determine fire change trend data based on all fire change parameters corresponding to each fire observation grid, identify the fire head information of the fire area based on the fire change trend data of all fire observation grids, calculate the fire spread adjustment coefficient of the fire area based on the obtained fire head information, and use the fire spread adjustment coefficient as the basis for calculating the wildfire alarm threshold of the fire area. In some embodiments, the second calculation unit 540 is also used to obtain all fire change parameters corresponding to each fire observation grid, arrange all fire change parameters in time sequence to construct a fire change trend line; determine whether the fire observation grid is a fire head grid based on the graph of the fire change trend line; perform position analysis on all determined fire head grids to obtain fire head grid distribution data; and determine the fire head information based on the fire head grid distribution data, wherein the fire head information includes the size, number, distribution direction, and spread rate of the fire head area. The system includes a method for constructing a fire threat model based on the size, number, distribution direction, and spread rate of fire front areas; determining time barrier window parameters for fire front areas based on the fire threat model; and adjusting the selection range of fire spread adjustment coefficients according to the time barrier window parameters. The determination of the time barrier window parameters based on the fire threat model includes: outputting the fire threat level by inputting parameters of the size, number, and spread rate of fire front areas in the current update cycle; determining the basic barrier window parameters based on the fire threat level; determining the modified barrier window parameters based on the distribution direction of the fire front areas; and merging the basic barrier window parameters and the modified barrier window parameters into the time barrier window parameters.

[0091] In the above embodiments, the more specific working processes of each functional unit can be referred to the corresponding content disclosed in the foregoing method embodiments. Furthermore, each functional unit can be implemented entirely or partially through software, hardware, firmware, or any combination thereof. When implemented using software, it can be implemented entirely or partially in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired or wireless means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that integrates one or more available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., a solid-state drive (SSD)).

[0092] This application describes embodiments of methods, apparatus (systems), and computer program products according to embodiments of this application with reference to flowchart illustrations and / or block diagrams. It should be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0093] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0094] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0095] Obviously, those skilled in the art can make various modifications and variations to the embodiments of this application without departing from the spirit and scope of this application. Therefore, if these modifications and variations to the embodiments of this application fall within the scope of the claims of this application and their equivalents, this application also intends to include these modifications and variations.

Claims

1. A method for analyzing the spread trend of wildfires by combining real-time environmental information, characterized in that, Includes the following steps: The core of the fire area and the associated meteorological station group of the fire area are identified. The associated meteorological station group refers to a group of at least one meteorological station that can directly observe the real-time environmental data of the fire area. An initial observation area is constructed based on the core of the fire area and each meteorological station. The initial observation area is then gridded to obtain multiple fire observation grids. The initial observation area is constructed by constructing multiple observation areas at different distances from the meteorological stations to the core of the fire area. The initial observation area is formed by superimposing multiple observation areas. Real-time environmental data is updated for each fire observation grid to obtain the fire change parameters of a single fire observation grid in each update cycle. The fire change parameters are calculated by the degree of change of the real-time environmental data observed in the corresponding adjacent update cycles. Fire change trend data is determined based on all fire change parameters corresponding to each fire observation grid. Fire head information of the fire area is identified based on the fire change trend data of all fire observation grids. Fire spread adjustment coefficient of the fire area is calculated based on the obtained fire head information. Fire spread adjustment coefficient is used as the basis for calculating the wildfire alarm threshold of the fire area.

2. The method for analyzing the spread of wildfires by combining real-time environmental information according to claim 1, characterized in that, The process of constructing an initial observation area based on the core of the fire area and each meteorological station, and then gridding the initial observation area to obtain multiple fire observation grids, includes the following steps: Determine the linear distance between each meteorological station and the core of the fire area; construct a first observation area around the core of the fire area using the shortest linear distance as the radius, and construct a second observation area around the core of the fire area using the longest linear distance as the radius; The first observation area and the second observation area are superimposed to form the initial observation area; the first observation area is gridded in the first way to obtain a fire observation grid, and the second observation area outside the first observation area is gridded in the second way to obtain a fire observation grid, wherein the size of the first grid is smaller than the size of the second grid.

3. The method for analyzing the spread trend of wildfires by combining real-time environmental information according to claim 2, characterized in that, It also includes the step of optimizing the initial observation area: Determine whether a meteorological station is located outside the fire area, and construct the first observation area based on the shortest line distance between the meteorological station located outside the fire area and the core of the fire area; determine whether a meteorological station is located within the observation area, and construct the second observation area based on the longest line distance between the meteorological station located within the observation area and the core of the fire area. Among them, whether the meteorological station is located outside the fire area means that the meteorological station is outside the coverage area of ​​the fire area determined in the previous update cycle; the meteorological station is located within the observation area means that the distance between the meteorological station and the core of the fire area does not exceed the first preset distance and is located within the observation area.

4. The method for analyzing the spread trend of wildfires by combining real-time environmental information according to claim 3, characterized in that, After determining whether a meteorological station is located outside the fire area, and constructing the first observation area based on the shortest line distance between the meteorological station located outside the fire area and the core of the fire area, the following steps are also included: The shortest line connecting the meteorological station located outside the fire area to the core of the fire area is designated as the first marked line, and the longest line connecting the meteorological station located within the fire area to the core of the fire area is designated as the second marked line. It is determined whether the distance difference between the first marked line and the second marked line is greater than a second preset distance. If the distance difference is greater than the second preset distance, the first observation area is constructed by the sum of the distance of the second marked line and the second preset distance. If the distance difference is not greater than the second preset distance, then the first observation area is constructed based on the distance of the line connecting the first markers.

5. The method for analyzing the spread trend of wildfires by combining real-time environmental information according to claim 4, characterized in that, The step of updating the environmental data in real time for each fire observation grid to obtain the fire change parameters of a single fire observation grid in each update cycle includes the following steps: The real-time environmental data of a single fire observation grid in each update cycle is obtained. This real-time environmental data is obtained by comprehensive calculation of the real-time data observed by all meteorological stations in the associated meteorological station group. The process includes the following steps: determining the single environmental data of the corresponding fire observation grid observed by each meteorological station. Determine the calculation weight of each meteorological station; combine the single environmental data observed by all meteorological stations with their respective calculation weights to calculate the real-time environmental data; wherein, the calculation weight of a meteorological station is determined by the combined distance between the meteorological station and the core of the fire area and the distance between the meteorological station and the fire observation grid. The fire change parameters are determined by comparing two real-time environmental data corresponding to a single fire observation grid in adjacent update cycles.

6. The method for analyzing the spread trend of wildfires by combining real-time environmental information according to claim 5, characterized in that, It also includes steps for correcting the real-time environmental data of individual fire observation grids: Fire observation grids that exhibit abnormal real-time environmental data within the same update cycle are designated as abnormal observation grids. Obtain remote sensing environmental data for the same update cycle of the abnormal observation grid; merge the remote sensing environmental data with the real-time environmental data to obtain corrected real-time environmental data, and use the corrected real-time environmental data as the basis for calculating the fire change parameters; wherein, the higher the abnormal value of the abnormal observation grid, the smaller the merging weight of its real-time environmental data, and the larger the merging weight of its remote sensing environmental data.

7. The method for analyzing the spread trend of wildfires by combining real-time environmental information according to claim 6, characterized in that, The process of acquiring remote sensing environmental data for the same update cycle of the abnormal observation grid includes the following steps: The outlier result type of the abnormal observation grid in the current update cycle is determined. The outlier result type includes mild anomaly, severe anomaly, and no displayed anomaly. The source type of the remote sensing environmental data is matched according to the outlier result type, including the following situations: If the anomaly is minor, the remote sensing environmental data source closest to the current update cycle time is selected; if the anomaly is severe, the predicted value of the remote sensing data in the current update cycle is selected; if there is no displayed anomaly, the remote sensing environmental data source is selected based on the degree of anomaly between adjacent update cycles.

8. The method for analyzing the spread trend of wildfires by combining real-time environmental information according to claim 1, characterized in that, The process of determining fire change trend data based on all fire change parameters corresponding to each fire observation grid, and identifying the fire front information of the fire area based on the fire change trend data of all fire observation grids, includes the following steps: Obtain all fire change parameters corresponding to each fire observation grid, arrange all fire change parameters in time sequence, and construct a fire change trend line; determine whether the fire observation grid is a fire head grid based on the graph of the fire change trend line; perform position analysis on all determined fire head grids to obtain fire head grid distribution data; determine the fire head information based on the fire head grid distribution data, wherein the fire head information includes the size, number, distribution direction, and spread rate of the fire head area.

9. The method for analyzing the spread trend of wildfires by combining real-time environmental information according to claim 8, characterized in that, The calculation of the fire spread adjustment coefficient for the fire area based on the obtained fire head information includes the following steps: A fire threat model is constructed based on the size, number, distribution direction, and spread rate of the fire front areas; the time barrier window parameters of the fire front areas are determined based on this fire threat model; and the selection range of the fire spread adjustment coefficient is determined according to the time barrier window parameters. The determination of the time barrier window parameters for the firehead area based on the firehead threat model includes: outputting the firehead threat level by inputting parameters such as the size, number, and spread rate of the firehead area in the current update cycle; determining the basic barrier window parameters based on the firehead threat level; determining the modified barrier window parameters based on the distribution direction of the firehead area; and merging the basic barrier window parameters and the modified barrier window parameters into the time barrier window parameters.

10. A wildfire spread trend analysis system that combines real-time environmental information, characterized in that, include: The first acquisition unit is used to determine the core of the fire area and the associated meteorological station group of the fire area. The associated meteorological station group refers to a group of at least one meteorological station that can directly observe the real-time environmental data of the fire area. The first processing unit is used to construct an initial observation area based on the core of the fire area and each meteorological station, and to grid the initial observation area to obtain multiple fire observation grids; wherein, the initial observation area is constructed by constructing multiple observation areas from different distances from the meteorological stations to the core of the fire area, and the initial observation area is formed by superimposing multiple observation areas. The first calculation unit is used to update the environmental data of each fire observation grid in real time and obtain the fire change parameters of a single fire observation grid in each update cycle. The fire change parameters are calculated by the degree of change of the real-time environmental data observed in the corresponding adjacent update cycles. The second calculation unit is used to determine the fire change trend data based on all fire change parameters corresponding to each fire observation grid, identify the fire head information of the fire area based on the fire change trend data of all fire observation grids, calculate the fire spread adjustment coefficient of the fire area based on the obtained fire head information, and use the fire spread adjustment coefficient as the basis for calculating the wildfire alarm threshold of the fire area.

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