Method for evaluating fire resistance of urban green zone plant community based on space structure

Abstract

The invention discloses a method for evaluating fire resistance of a green-zone plant community based on a space structure, and belongs to the technical field of garden fire prevention, and the method comprises the steps: employing a sample method to investigate the space structure characteristics of the green-zone plant community, and extracting principal component factors based on the space structure characteristics; on the basis of the fire spread characteristics of the plant community in the urban green zone, determining the key index of the fire resistance of the plant community represented by the surface litters, and obtaining the fire resistance score of the community according to the key index; constructing a community fire resistance evaluation model based on the space structure according to the influence of the principal component factor of the community space structure on the community fire resistance score; and evaluating the fire resistance of the plant community around the city according to the model. According to the method, the fire resistance of the community can be rapidly judged through the plant community space structure indexes easy to measure, tedious measurement and combustion tests on plants are not needed, the fire risk of the community can be regularly evaluated, and then fire prevention measures are taken, so that the fire occurrence rate is reduced.

Description

Technical Field

[0001] This application relates to the technical field of garden fire prevention, and particularly to a method for evaluating the fire resistance of a plant community in an urban green belt based on spatial structure. Background Art

[0002] As an urban ecological barrier and recreational space, the urban green belt around the city undertakes multiple functions such as regulating climate, purifying air, and protecting biodiversity. However, its fragmented distribution, high-intensity human activity interference, and single vegetation type characteristics significantly increase the fire risk. In recent years, extreme drought events caused by global climate change have occurred frequently, further exacerbating the fire risk level of the urban green belt.

[0003] The fire resistance of the plant community in the urban green belt is directly related to the stability of the green belt ecosystem and the urban fire risk prevention and control ability. On the one hand, traditional evaluations of plant community fire resistance focus on using statistical analysis methods based on measured data to study plant fire resistance, classifying the fire resistance of garden tree species according to the fire resistance of tree species, and then configuring tree species according to the fire resistance level to improve the fire resistance ability of the plant community. On the other hand, many scholars focus on exploring important factors affecting plant fire resistance. Among them, traditional research usually attributes the fire resistance of plant communities to the fire-resistant properties of tree species, while ignoring the systematic influence of community spatial structure on fire behavior. Moreover, existing research has not been able to effectively screen the main component factors of spatial structure that are strongly related to fire behavior, making it difficult to conduct a comprehensive evaluation by combining community spatial structure and plant fire resistance. In addition, the commonly used methods for evaluating plant fire resistance are cumbersome to operate, requiring a combination of field research and indoor combustion tests, with a large workload and complex analysis. Summary of the Invention

[0004] In view of the above deficiencies in the prior art, the present application provides a method for evaluating the fire resistance of a plant community in an urban green belt based on spatial structure, which solves the shortage of the influence of plant combinations and their spatial structure on fire spread at the community level.

[0005] To achieve the above invention objective, the technical solution adopted in the present application is as follows: The present application provides a method for evaluating the fire resistance of a plant community in an urban green belt based on spatial structure, including: S1: Using the quadrat method to conduct field investigations on the spatial structure characteristics of the plant community in the urban green belt, and determining the main component factors representing the spatial structure of the plant community; S2: Based on the fire spread characteristics of the plant community in the urban green belt, determining the key indicators of the plant community's fire resistance represented by surface litter, and obtaining the community fire resistance score according to the key indicators; S3: Constructing a community fire resistance evaluation model based on spatial structure according to the influence of the main component factors of the community spatial structure on the community fire resistance score; S4: Evaluate the fire resistance of the urban green belt plant community according to the fire resistance evaluation model of the community based on the spatial structure.

[0006] Further, the specific steps of S1 include: S101: Select representative areas in the urban green belt for plot planning, investigate the indicators representing the spatial structure characteristics of the plant community in the plots, and calculate the correlation between the indicators using the Pearson correlation coefficient model; S102: Based on the correlation between the indicators, perform dimensionality reduction on the indicators of the community spatial structure characteristics, extract the principal component factors representing the spatial structure of the plant community, and obtain the stem form factor, crown cover factor, and density factor of the urban green belt plant community; S103: Calculate according to the weights of the principal component factors, and use the cluster analysis method to cluster the stem form factor, crown cover factor, and density factor of the common plant communities in the urban green belt.

[0007] Further, the principal component factors in S102 specifically include:

[0008]

[0009]

[0010] Among them, , , represent the stem form factor, crown cover factor, and density factor respectively; ~ represent the breast diameter, ground diameter, basal cover, tree height, crown width, height under branches, canopy density, and arbor density respectively.

[0011] The specific steps of S2 include: S201: Based on the fire spread characteristics of the urban green belt plant community, use the quadrat method and laboratory combustion method to determine the key indicators representing the fire resistance of the plant community, and obtain the mass characteristics, spatial distribution characteristics, and combustion characteristics of the surface litter; S202: Based on the mass characteristics, spatial distribution characteristics, and combustion characteristics, select multiple plant community fire resistance evaluation indicators, and use the CRITIC weight method to construct a comprehensive evaluation system for the fire resistance of the community based on the surface litter; S203: Based on the comprehensive evaluation system for the fire resistance of the community, conduct a fire resistance score for the community, and obtain the mass fire resistance score, spatial distribution fire resistance score, and combustion fire resistance score.

[0012] Further, the mass characteristics, spatial distribution characteristics, and combustion characteristics of the surface litter specifically include: The quality characteristics include the average mass per unit area, the coefficient of variation of mass, the skewness of mass, and the kurtosis of mass; The spatial distribution characteristics include the spatial structure range and fractal dimension of the surface litter; The combustion characteristics include the calorific value of the surface litter, the combustion time, the temperature change, and the incomplete combustion index.

[0013] Furthermore, the comprehensive evaluation system for the fire resistance of the community based on the surface litter is as follows:

[0014] Among them, ~ represent the average mass per unit area, the coefficient of variation of mass, the skewness of mass, the kurtosis of mass, the spatial structure range, the fractal dimension, the calorific value, the combustion time, the temperature change, and the incomplete combustion index of the surface litter.

[0015] Furthermore, the specific steps of S3 are as follows: S301: Establish a linear mathematical model between the fire resistance score of mass and the community spatial structure:

[0016] Among them, is the fire resistance score of mass, is the stem form factor of the community spatial structure; S302: Establish a linear mathematical model between the fire resistance score of spatial distribution and the community spatial structure:

[0017] Among them, is the fire resistance score of spatial distribution, is the crown cover factor of the community spatial structure, is the density factor of the community spatial structure; S303: Establish a linear mathematical model between the fire resistance score of combustion and the community spatial structure:

[0018] Among them, is the fire resistance score of combustion; S304: Based on the linear mathematical models of S301, S302, and S303, construct an evaluation model for the fire resistance of the community based on the spatial structure:

[0019] Among them, is the comprehensive fire resistance score.

[0020] The beneficial effects of this application are: A method for evaluating the fire resistance of a plant community in the green belt around a city based on spatial structure provided by this application reveals the influence mechanism of the community's spatial structure on its fire resistance performance through the measured spatial structure characteristics of the plant community and the comprehensive evaluation of fire resistance. A fire resistance evaluation model of the plant community is constructed with the spatial structure as the independent variable. This model can quickly judge the fire resistance performance of the community through easily measurable spatial structure indicators of the plant community, without the need for cumbersome determination and combustion tests on plants. It can regularly evaluate the fire risk of the plant community in the green belt around the city, and then take fire prevention measures to reduce the fire incidence rate. In addition, starting from the green belt around the city and focusing on the research of fire-resistant plant communities, this application can provide ideas for the configuration of resistant plant communities in other types of urban green spaces, thereby enhancing the resilience of the urban ecological network to climate change and promoting urban safety. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] In order to more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments of this application, and those of ordinary skill in the art can also obtain other embodiments based on these drawings.

[0022] Figure 1 It is a schematic diagram of a method for evaluating the fire resistance of a plant community in the green belt around a city based on spatial structure provided by an embodiment of this application.

[0023] Figure 2 It is a schematic diagram of a quadrat design provided by an embodiment of this application.

[0024] Figure 3 It is a schematic diagram of the weighing points of surface litter provided by an embodiment of this application.

[0025] Figure 4 It is a dendrogram of the clustering of spatial structure factors of the plant community in the green belt around a city provided by an embodiment of this application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0026] The following will clearly and completely describe the technical solutions in the embodiments of this application with reference to the drawings in the embodiments of this application. Obviously, the described embodiments are only some embodiments of this application, rather than all embodiments. Based on the embodiments in this application, all other embodiments obtained by those of ordinary skill in the art based on this application belong to the scope of protection of this application.

[0027] At present, the research on the fire resistance of plant communities mainly focuses on the following two methods: The post-fire site investigation method is limited by the occasional occurrence of fires, resulting in fewer investigation opportunities; the laboratory combustion method has cumbersome index determination and complex analysis processes. There is relatively little research on the evaluation of the fire resistance of plant communities; the lack of evaluation will put the fire prevention of urban green spaces in a passive state, easily leading to the spread of fires and unnecessary hazards. Currently, most research focuses on the screening of fire-resistant plants, with less research on the impact of plant combinations and their spatial structures on fire spread at the community level, and limited practical application significance.

[0028] Based on this, the embodiments of this application provide a method for evaluating the fire resistance of the plant community in the green belt around the city based on the spatial structure. This method can be seen in Figure 1 , Figure 1 FIG. shows a schematic diagram of a method for evaluating the fire resistance of the plant community in the green belt around the city based on the spatial structure provided by the embodiments of this application, including: S1: Adopt the quadrat method to conduct field investigations on the spatial structure characteristics of the plant community in the green belt around the city, and determine the principal component factors representing the spatial structure of the plant community; S2: Based on the fire spread characteristics of the plant community in the green belt around the city, determine the key indicators of the surface litter representing the fire resistance of the plant community, and obtain the fire resistance score of the community according to the key indicators; S3: Construct an evaluation model of the fire resistance of the community based on the spatial structure according to the influence of the principal component factors of the community spatial structure on the fire resistance score of the community; S4: Evaluate the fire resistance of the plant community in the green belt around the city according to the evaluation model of the fire resistance of the community based on the spatial structure.

[0029] Selection of plots: Taking the green belt around the city in Shanghai as an example, 21 typical tree communities were selected, including 18 tree species in 14 families. The selection principles are as follows: ① The selected communities frequently appear in the green belt around the city in Shanghai, and the types cover coniferous forests, evergreen broad-leaved forests, deciduous evergreen broad-leaved mixed forests, and deciduous broad-leaved forests; ② The communities show a natural state without obvious traces of artificial management, such as cleaning surface litter, pruning branches and leaves, fertilizing and loosening the soil, etc.; ③ The growth of the trees in the community is stable and good; ④ The geographical characteristics of the community are relatively consistent, the terrain is flat, there is no obvious slope, and there is a certain distance from the water body.

[0030] Sample plot survey: Preliminary experimental investigations have found that the area of the ring-city green belt, as a suburban green belt, is limited by urban construction, and because it has certain recreational functions, the planting plots are divided by roads, and the scale of the community is about 15m. The sample plot scale of 20m and above commonly used in forest surveys is not applicable, so it has been adjusted according to actual conditions. In the ring-city green belt, groundless forest land at a certain distance from the road boundary is selected as the sample plot. This application uses a 15m×15m square sample plot. There are mainly 1-2 tree species in the sample plot. The geographical locations of the four corners of the sample plot are recorded by the GPS locator. In order to better locate the trees and surface litter in the sample plot, a 3m×3m grid system is further constructed in the 15m×15m sample plot, such as Figure 2 As shown, Figure 2 A schematic diagram of a sample plot design is provided in an embodiment of the present application, and the research equipment includes a 50m measuring tape, a marked hemp rope and other tools.

[0031] Surface litter survey: The mass of surface litter was measured with 1m×1m as the minimum unit, and its location information was recorded. However, due to the workload and feasibility of the experiment, a mechanical sampling method was used in each sample plot. The central point of a 3m×3m grid was selected and a 1m×1m range was framed as the reference grid. Figure 3 As shown, Figure 3 A schematic diagram of the weighing points of surface litter provided in the embodiment of the present application. An electronic scale with an accuracy of 1g is used for weighing on site, and the mass of litter in the reference square is recorded. The mass of surface litter in the surrounding 8 1m×1m squares is calculated as follows: the reference square is multiplied by the mass coefficient. The mass coefficient is calculated on site based on the plane distribution and thickness of the surface litter. To increase the accuracy of the mass coefficient, 6-7 groups of measurements and calculations are randomly selected for each 15m×15m sample plot as a calibration reference.

[0032] Determination of community characteristics: record the position and species name of each tree in the sample plot, and measure five parameters including breast diameter, ground diameter, crown width, tree height and height under branches, as shown in Table 1. Table 1 shows the meaning and measurement methods of community characteristic indicators. The experimental instruments used include breast diameter ruler, 5m steel tape measure, and 3m measuring flower rod.

[0033] Table 1 Meaning and measurement methods of community characteristic indicators

[0034] Among them, according to the location of the community trees obtained from the field records, the community plan of the sample plot was drawn using AutoCAD, and the relative coordinate system was used, with the lower left corner of each 15m×15m sample plot as the origin, to quantify the coordinates of each tree:

[0035] In the above formula, Is an arbor The distance between the arbor is in meters, and are respectively the abscissa and ordinate of the arbor ; and are respectively the abscissa and ordinate of the arbor .

[0036] Furthermore, the S1 specifically includes: S101: Select a representative area in the ring green belt for plot planning, investigate the indicators characterizing the spatial structure characteristics of the plant community in the plot, and calculate the correlation between each indicator using the Pearson correlation coefficient model.

[0037] In a possible embodiment, the Pearson correlation coefficient model is selected by SPSS26.0 to analyze the correlation between 8 indicators characterizing the spatial structure characteristics of the community, where the 8 indicators include arbor density, canopy density, basal coverage, breast diameter, ground diameter, crown width, tree height, and height below branches. Calculate the correlation coefficient and significance value between each pair to prepare for the subsequent principal component factor analysis. The correlation between each indicator is shown in Table 2: Table 2 Correlation matrix table of community spatial structure indicators

[0038] Note: *. Correlation is significant at the 0.05 level (two-tailed), **. Correlation is significant at the 0.001 level (two-tailed).

[0039] S102: Based on the correlation between each indicator, perform dimensionality reduction processing on the indicators of the spatial structure characteristics of the community, extract the principal component factors characterizing the spatial structure of the plant community, and obtain the stem form factor, crown cover factor, and density factor of the ring green belt plant community.

[0040] Furthermore, the principal component factors in the S102 specifically include:

[0041]

[0042]

[0043] Among them, , , respectively represent the stem form factor, crown cover factor, and density factor; ~ respectively represent breast diameter, ground diameter, basal coverage, tree height, crown width, height below branches, canopy density, and arbor density.

[0044] S103: Calculate according to the weights of the principal component factors, and use the cluster analysis method to cluster the stem form factors, crown cover factors and density factors of the common plant communities in the green belt around the city.

[0045] In a possible embodiment, calculate according to the three principal component factors of the spatial structure characteristics obtained by principal component analysis, obtain the stem form factors, crown cover factors and density factors of 21 communities, and conduct a systematic cluster analysis on the calculated data. The clustering method used is the between-group linkage method, as Figure 4 shown, Figure 4 This is the cluster pedigree diagram of the spatial structure factors of the plant community in the green belt around the city provided by the embodiment of the present application.

[0046] Furthermore, the S2 specifically includes: S201: Based on the fire spread characteristics of the plant community in the green belt around the city, use the quadrat method and the laboratory combustion method to determine the key indicators characterizing the fire resistance of the plant community, and obtain the mass characteristics, spatial distribution characteristics and combustion characteristics of the surface litter; S202: Based on the mass characteristics, spatial distribution characteristics and combustion characteristics, select multiple fire resistance evaluation indicators for the plant community, and use the CRITIC weight method to construct a comprehensive evaluation system for the fire resistance of the community based on the surface litter; S203: Conduct a fire resistance score for the community based on the comprehensive evaluation system for the fire resistance of the community, and obtain the mass fire resistance score, spatial distribution fire resistance score and combustion fire resistance score.

[0047] Furthermore, the mass characteristics, spatial distribution characteristics and combustion characteristics of the surface litter specifically include: The mass characteristics include the average mass per unit area, mass coefficient of variation, mass skewness and mass kurtosis; The spatial distribution characteristics include the spatial structure range and fractal dimension of the surface litter; The combustion characteristics include the calorific value, combustion time, temperature change and incomplete combustion index of the surface litter.

[0048] As an important combustible in the community, the mass characteristics, spatial distribution characteristics and combustion characteristics of the surface litter comprehensively affect the fire resistance of the community. Therefore, a total of 10 indicators are selected from these three aspects, and the CRITIC weight method is used to construct a comprehensive evaluation system for the fire resistance of the community based on the surface litter, as shown in Table 3.

[0049] Table 3 Comprehensive evaluation indicators and weights for the fire resistance of plant communities

[0050] Furthermore, the comprehensive evaluation system for the fire resistance of the community based on the surface litter is:

[0051] In the formula, ~ represent the average mass per unit area, coefficient of variation of mass, skewness of mass, kurtosis of mass, range of spatial structure, fractal dimension, calorific value, combustion time, temperature change, and incomplete combustion index of surface litter.

[0052] Among them, the treatment of the surface litter includes: A1: Measuring the moisture content of the surface litter:

[0053] In the formula, is the moisture content, is the total weight before drying the sample, is the total weight after drying the sample, is the wet weight of the envelope, is the dry weight of the envelope.

[0054] A2: Calculating the dry weight of the surface litter:

[0055] Among them, is the dry weight of the litter, is the fresh weight.

[0056] In a possible embodiment, Excel and SPSS are used to calculate the average mass per unit area, median, minimum and maximum values, standard deviation, skewness, and kurtosis of 21 communities. The average mass per unit area of the surface litter reflects the overall quantity of the combustibles; the median of the mass per unit area of the surface litter reflects the mass of the litter arranged in the middle position; since the standard deviation is affected by the average value and generally shows an increasing trend with the increase of the average value, the ratio of the standard deviation to the average value is introduced as the coefficient of variation of mass. The coefficient of variation reflects the degree of dispersion of the mass of the litter per unit area. The larger the coefficient of variation, the greater the degree of dispersion, indicating that the quantity gap of the surface litter per unit area is relatively large and the distribution is uneven, and the fire spread is hindered, and the fire resistance of the community is enhanced; skewness describes the symmetry of the data distribution pattern; kurtosis describes the steepness of the data distribution pattern.

[0057] In a possible embodiment, the semi-variance function is used to analyze the spatial distribution characteristics of the surface litter of the community, and two indicators, namely the range of spatial structure and fractal dimension, of 21 communities are obtained respectively.

[0058] Among them, the semi-variance function is:

[0059] In the formula, , and are respectively the observed values at and in spatial position, is the number of point pairs when the sampling interval is

[0060] In a possible embodiment, a ZDHW-10A microcomputer high-precision calorimeter (with a heat capacity of 10169 J) is used to conduct litter combustion experiments according to tree species. After measuring four indexes of the calorific value, combustion time, temperature change, and incomplete combustion index of the surface litter of different tree species, the combustion characteristics of the surface litter of the pure forest community are the same as those of the single tree species that make up the community; for the mixed forest, the combustion characteristic indexes of the surface litter of the community are obtained by weighted calculation according to the mass ratio of the surface litter of different tree species during the research process.

[0061] Further, the specific steps of S3 are as follows: S301: Establish a linear mathematical model between the mass fire resistance score and the community spatial structure:

[0062] wherein, is the mass fire resistance score, is the stem form factor of the community spatial structure; S302: Establish a linear mathematical model between the spatial distribution fire resistance score and the community spatial structure:

[0063] wherein, is the spatial distribution fire resistance score, is the crown cover factor of the community spatial structure, is the density factor of the community spatial structure; S303: Establish a linear mathematical model between the combustion fire resistance score and the community spatial structure:

[0064] wherein, is the combustion fire resistance score; S304: Based on the linear mathematical models of S301, S302, and S303, construct a community fire resistance evaluation model based on the spatial structure:

[0065] wherein, is the comprehensive fire resistance score.

[0066] It can be seen that if the comprehensive evaluation system of the fire resistance of the community using surface litter is used to evaluate the fire resistance of the community, a combustion test needs to be carried out, the index measurement is cumbersome, and the analysis process is complex. Therefore, analyzing the relationship between the spatial structure of the community and its fire resistance, and then constructing a fire resistance evaluation model of the community based on the spatial structure, it is possible to judge the fire resistance of the community by observing easily observable indicators in the field (tree breast diameter, ground diameter, crown width, tree height, and height under branches), which is simpler than measuring the mass characteristics, spatial distribution characteristics, and combustion characteristics of combustibles.

[0067] A method for evaluating the fire resistance of the plant community in the urban green belt based on the spatial structure provided by this application reveals the influence of the spatial structure of the plant community on the fire resistance performance through the comprehensive evaluation of the spatial structure characteristics of the measured plant community and the mass characteristics, spatial distribution characteristics, and combustion characteristics of the surface litter, so as to construct a fire resistance evaluation model of the community based on the spatial structure. This model can quickly judge the fire resistance performance of the community through easily measurable spatial structure indicators of the plant community, without the need for cumbersome measurements and combustion tests on plants, and can regularly evaluate the fire risk of the plant community in the urban green belt, and then take fire prevention measures, thereby reducing the fire incidence rate. It can provide ideas for the configuration of resistant plant communities in other types of urban green spaces, thereby enhancing the resilience of the urban ecological network to climate change and promoting urban safety.

[0068] It should be noted that those of ordinary skill in the art will realize that the embodiments described here are to help readers understand the principles of this application, and it should be understood that the protection scope of this application is not limited to such specific statements and embodiments. Those of ordinary skill in the art can make various other specific deformations and combinations that do not deviate from the essence of this application based on the technical revelations disclosed in this application, and these deformations and combinations are still within the protection scope of this application.

Claims

1. A method for evaluating the fire resistance of a plant community in the green belt around the city based on the spatial structure, characterized in that Including: S1: Adopt the quadrat method to conduct on-site investigations on the spatial structure characteristics of the green belt around the city, and determine the principal component factors characterizing the spatial structure of the plant community; S2: Based on the fire spread characteristics of the plant community in the green belt around the city, determine the key indicators of the surface litter representing the fire resistance of the plant community, and obtain the community fire resistance score according to the key indicators; S3: Construct a community fire resistance evaluation model based on the spatial structure according to the influence of the principal component factors of the community spatial structure on the community fire resistance score; S4: Conduct an evaluation of the fire resistance of the plant community in the green belt around the city according to the community fire resistance evaluation model based on the spatial structure.

2. The method for evaluating the fire resistance of the plant community in the green belt around the city based on the spatial structure according to claim 1, characterized in that The specific content of S1 includes: S101: Select representative areas in the green belt around the city for plot planning, investigate the indicators characterizing the spatial structure characteristics of the plant community in the plots, and use the Pearson correlation coefficient model to calculate the correlation between the indicators; S102: Based on the correlation between the indicators, perform dimensionality reduction processing on the indicators of the community spatial structure characteristics, extract the principal component factors representing the spatial structure of the plant community, and obtain the stem form factor, canopy factor, and density factor of the plant community in the green belt around the city; S103: Calculate according to the weights of the principal component factors, and use the cluster analysis method to cluster the stem form factor, canopy factor, and density factor of the common plant communities in the green belt around the city.

3. The method for evaluating the fire resistance of the plant community in the ring-shaped green belt based on the spatial structure according to claim 2, wherein, The principal component factors in S102 specifically include: Among them, , , respectively represent the stem form factor, crown cover factor, and density factor; ~ respectively represent the diameter at breast height, ground diameter, basal cover, tree height, crown width, height to the lowest live branch, canopy density, and tree density.

4. The method for evaluating the fire resistance of the green belt plant community based on the spatial structure according to claim 1, characterized in that, The specific content of S2 includes: S201: Based on the fire spread characteristics of the plant community in the green belt around the city, use the quadrat method and the laboratory combustion method to determine the key indicators representing the fire resistance of the plant community, and obtain the mass characteristics, spatial distribution characteristics, and combustion characteristics of the surface litter; S202: Based on the mass characteristics, spatial distribution characteristics, and combustion characteristics, select multiple plant community fire resistance evaluation indicators, and use the CRITIC weight method to construct a comprehensive evaluation system for the community fire resistance based on the surface litter; S203: Conduct a community fire resistance score based on the comprehensive evaluation system for the community fire resistance, and obtain the mass fire resistance score, spatial distribution fire resistance score, and combustion fire resistance score.

5. The method for evaluating the fire resistance of the green belt plant community based on the spatial structure according to claim 4, wherein The mass characteristics, spatial distribution characteristics, and combustion characteristics of the surface litter specifically include: The mass characteristics include the average mass per unit area, mass variation coefficient, mass skewness, and mass kurtosis; The spatial distribution characteristics include the spatial structure range and fractal dimension of the surface litter; The combustion characteristics include the calorific value, combustion time, temperature change, and incomplete combustion index of the surface litter.

6. The method for evaluating the fire resistance of the green belt plant community based on the spatial structure according to claim 4, wherein The comprehensive evaluation system for the community fire resistance based on the surface litter is: Among them, ~ are used to represent the average mass per unit area of surface litter, the coefficient of variation of mass, the skewness of mass, the kurtosis of mass, the range of spatial structure, the fractal dimension, the calorific value, the combustion time, the temperature change, and the incomplete combustion index.

7. The method for evaluating the fire resistance of the plant community in the green belt around the city based on the spatial structure according to claim 1, wherein, The specific content of S3 includes: S301: Establish a linear mathematical model between the mass fire resistance score and the community spatial structure: Among them, is the quality fire resistance score, is the stem form factor of the community spatial structure; S302: Establish a linear mathematical model between the spatial distribution fire resistance score and the community spatial structure: Among them, is the spatial distribution fire resistance score, is the canopy factor of the community spatial structure, is the density factor of the community spatial structure; S303: Establish a linear mathematical model between the combustion fire resistance score and the community spatial structure: Among them, is the combustion fire resistance rating; S304: Based on the linear mathematical models of S301, S302, and S303, construct a community fire resistance evaluation model based on the spatial structure: Among them, is the comprehensive fire resistance score.

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