A system and method for evaluating the ecological value of forest ecosystem

Abstract

The present invention discloses a forest ecosystem ecological value assessment system and method, comprising a forest area classification processing module, a comprehensive assessment analysis module and a secondary analysis processing module. The present invention relates to the field of ecological value assessment technology, and solves the problem that the judgment and assessment by carbon flux is one-sided and inaccurate, which will cause errors in the overall assessment and affect the subsequent rectification. The present invention divides the forest into different areas, calculates the ecological carrying capacity and the ecological environment status value according to a variety of index parameters corresponding to the forest, and calculates the assessment values ​​corresponding to different areas according to the calculated data, and then classifies the areas according to the assessment values, and analyzes the normal areas and abnormal areas obtained by the classification, focuses on analyzing the abnormal areas, and performs periodic monitoring and analysis on them to evaluate, collects continuous data for analysis, improves the accuracy of the overall assessment, and reduces the assessment error.

Description

Technical Field

[0001] The present invention relates to the technical field of ecological value assessment, and in particular to a system and method for assessing the ecological value of a forest ecosystem. Background Art

[0002] In order to improve the trend of ecological environment deterioration caused by rapid urban development, the service value of forest ecosystems has received increasing attention, and forest development has become a research hotspot.

[0003] According to the application number CN202410270077.4, a system and method for evaluating the service value of a forest ecosystem is disclosed, including obtaining a diversity index dataset and a carbon flux dataset; taking the scoring value as the target layer, the diversity index and the carbon flux as the criterion layer, and the diversity index dataset and the carbon flux dataset as the scheme layer, confirming the indicator weights of the scheme layer based on the hierarchical analysis method, determining the indicator weights of the criterion layer, and outputting the scoring value of the target layer indicator; evaluating the scoring value based on preset evaluation rules to determine the high-value items of the ecosystem service value in the corresponding target forest area.

[0004] The above patent uses diversity index and carbon flux to quickly judge the outstanding value items in the service value of forest ecosystems, provides a certain scientific basis for management departments to formulate forest protection policies, conducts reliable and effective assessment of the service value of ecosystems, and provides scientific data support for strengthening regional ecosystem construction decisions. However, the assessment and judgment based on carbon flux is inaccurate, and is not combined with the analysis of various data corresponding to the actual forest, resulting in errors in the assessment, which further affects the overall rectification and management of the forest. Summary of the invention

[0005] In view of the deficiencies in the prior art, the present invention provides a system and method for evaluating the ecological value of a forest ecosystem, which solves the problem that the evaluation based on carbon flux is one-sided and inaccurate, causing errors in the overall evaluation and affecting subsequent rectification.

[0006] To achieve the above objectives, the present invention is implemented through the following technical solutions: a forest ecosystem ecological value assessment system, comprising:

[0007] A forest area information collection module, which is used to obtain ecological information of different areas and transmit the ecological information to the forest area classification processing module. The ecological information obtained includes environmental quality information and ecological carrying capacity information;

[0008] The forest area classification processing module is used to calculate the evaluation values ​​of different areas according to the ecological information transmitted by the forest area information collection module, and classify different areas into normal areas and abnormal areas according to the evaluation values, and generate regional classification information at the same time, and then transmit the regional classification information to the comprehensive evaluation and analysis module;

[0009] The comprehensive evaluation and analysis module is used to analyze the abnormal area according to the acquired regional classification information, and classify the abnormal area according to the distribution of the abnormal area to obtain dispersed distribution information and concentrated distribution information, and transmit the dispersed distribution information to the secondary analysis and processing module, and then classify the abnormal area evaluation values ​​corresponding to the concentrated distribution information, and periodically monitor the abnormal area level to generate evaluation information;

[0010] The secondary analysis and processing module is used to analyze the obtained scattered distribution information, judge the adjacent areas of the abnormal area and perform different analysis methods, and generate evaluation information and periodic monitoring signals at the same time. It also analyzes the periodic monitoring signals, judges the changes in the evaluation values ​​in the normal area within the time period and generates regional early warning signals and normal monitoring signals, and then analyzes the generated signals to generate evaluation information, and transmits the evaluation information to the evaluation information output module.

[0011] An evaluation information output module is used to display the acquired evaluation information to the corresponding operator.

[0012] As a further solution of the present invention: the specific method of generating regional classification information by the forest region classification processing module is:

[0013] Different regions are labeled and recorded as i, and i=1, 2, …, j, where j is the number of different regions. The biological richness index Qi, vegetation coverage index Fi, water network density index Si, land degradation index Ti and environmental quality index Hi of different regions i are substituted into the formula Ei=0.25×biological abundance index Qi+0.2×vegetation coverage index Fi+0.2×water network density index Si+0.2×land degradation index Ti+0.15×environmental quality index Hi to calculate the ecological environment status value Ei of the region;

[0014] Then according to the formula The ecological carrying capacity Ui corresponding to region i is calculated, where ef is the per capita ecological footprint; N is the population; aa i is the biological production area converted per capita for the mth type of consumer goods; r j is the equilibrium factor of the jth land type; C i is the per capita consumption of the mth item; P m is the average production capacity of the mth item;

[0015] The ecological carrying value Ui and the ecological environment status value Ei calculated in different regions are summed to obtain the evaluation value Gi. At the same time, the evaluation values ​​of all regions are averaged and the comparison value G is obtained. At the same time, the evaluation value Gi is compared with the comparison value G. When the evaluation value Gi is greater than the comparison value G, the corresponding area is classified as an abnormal area. Conversely, when the evaluation value Gi is less than the comparison value G, the corresponding area is classified as a normal area.

[0016] As a further solution of the present invention: the comprehensive evaluation and analysis module classifies the distribution of abnormal areas to obtain dispersed distribution information and concentrated distribution information, and analyzes the distribution information in the following specific manner:

[0017] Obtain all abnormal areas, and judge the distribution of the abnormal areas and generate corresponding dispersed distribution information and concentrated distribution information, analyze the concentrated distribution information, combine the abnormal areas to obtain abnormal blocks, then sum up the evaluation values ​​of all abnormal areas and calculate the mean, and use the mean as the evaluation standard of the abnormal blocks, and classify the abnormal blocks according to the evaluation standard, specifically, classify the abnormal blocks according to the preset evaluation value level interval;

[0018] Then, with time t as a period, the changes in the evaluation value of the abnormal block are monitored. If the evaluation value of the abnormal block increases within the time period t, a warning signal is generated. Conversely, if the evaluation value of the abnormal block decreases within the time period t, a reduction signal is generated. At the same time, corresponding evaluation information is generated based on the warning signal and the reduction signal, and the evaluation information is transmitted to the evaluation information output module.

[0019] As a further solution of the present invention: the specific method in which the secondary analysis and processing module generates the regional warning signal and the normal monitoring signal is:

[0020] Analyze the scattered distribution information, obtain the abnormal area, and judge the adjacent area of ​​the abnormal area. If the adjacent area of ​​the abnormal area is a normal area, generate a periodic monitoring signal. If the adjacent area of ​​the abnormal area is an abnormal area, merge the abnormal areas and calculate the overall evaluation value after the merger, and generate the evaluation level and evaluation information according to the evaluation value;

[0021] For the generated periodic monitoring signal, the change of the evaluation value of the normal area within the time period t is obtained. If the evaluation value increases, a regional warning signal is generated for the corresponding normal area. If the evaluation value decreases, a normal monitoring signal is generated for the corresponding normal area, and the regional warning signal is analyzed.

[0022] As a further solution of the present invention: the specific method in which the secondary analysis processing module analyzes the regional warning signal is:

[0023] All normal areas that generate regional warning signals are obtained and recorded as analysis areas, and the change in the number of analysis areas within the time period t1 is determined. If the number of analysis areas increases, the sum of the evaluation values ​​of all analysis areas is calculated, and the overall mean is calculated at the same time. The corresponding evaluation level is generated according to the mean, and the evaluation information is generated;

[0024] If the number of analysis areas is reduced, a normal monitoring signal is generated, and then the normal monitoring signal is analyzed, the sum of the evaluation values ​​of all areas is calculated, and the corresponding evaluation value mean is calculated. At the same time, the overall evaluation level is analyzed according to the evaluation value mean to generate evaluation information.

[0025] A method for evaluating the ecological value of a forest ecosystem comprises the following steps:

[0026] Step 1: Calculate the corresponding ecological environment status value and ecological carrying value according to the ecological information of different regions and sum them up to obtain the evaluation value. At the same time, classify the regions according to the evaluation value to obtain classification information, and the classification information includes normal regions and abnormal regions;

[0027] Step 2: Analyze the distribution of abnormal areas to generate distribution information, analyze the concentrated distribution information, combine the abnormal areas to obtain abnormal blocks, and calculate the evaluation criteria of the abnormal blocks. Generate an evaluation grade based on the evaluation criteria, and then generate evaluation information based on the change of the evaluation value;

[0028] Step 3: Analyze the dispersed distribution information, judge the adjacent areas of the abnormal area and perform different analysis methods, and generate evaluation information based on the changes in the corresponding evaluation values ​​over time periods;

[0029] Step 4: Display the generated evaluation information to the corresponding operator.

[0030] Beneficial Effects

[0031] The present invention provides a system and method for evaluating the ecological value of a forest ecosystem. Compared with the prior art, it has the following beneficial effects:

[0032] The present invention divides the forest into different areas, calculates the ecological carrying capacity and the ecological environment status value according to a variety of index parameters corresponding to the forest, and calculates the evaluation values ​​corresponding to different areas according to the calculated data. Then the areas are classified according to the evaluation values, and the normal areas and abnormal areas obtained by the classification are analyzed. The abnormal areas are analyzed in detail and periodically monitored and analyzed for evaluation. Continuous data is collected for analysis, thereby improving the accuracy of the overall evaluation and reducing the evaluation error. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] Figure 1 This is a block diagram of the system principle of the present invention;

[0034] Figure 2 Figure 2 is a diagram of the method of the present invention. DETAILED DESCRIPTION

[0035] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0036] For example, see Figure 1 The present application provides a forest ecosystem ecological value assessment system, including: a forest area information collection module, a forest area classification processing module, a comprehensive assessment and analysis module, a secondary analysis and processing module and an assessment information output module.

[0037] The forest area information collection module is used to obtain ecological information of different areas and transmit the ecological information to the forest area classification processing module. The acquired ecological information includes environmental quality information and ecological carrying capacity information.

[0038] The forest area classification processing module is used to calculate the evaluation values ​​of different areas according to the acquired ecological information, and classify different areas into normal areas and abnormal areas according to the evaluation values, and generate regional classification information at the same time, and then transmit the regional classification information to the comprehensive evaluation and analysis module. The specific method of generating regional classification information is:

[0039] Different regions are numbered and recorded as i, and i=1, 2, …, j, where j is the number of different regions. Then the biological richness index corresponding to region i is obtained and recorded as Qi, vegetation cover index Fi, water network density index Si, land degradation index Ti and environmental quality index Hi. The obtained biological richness index is recorded as Qi, vegetation cover index Fi, water network density index Si, land degradation index Ti and environmental quality index Hi are substituted into the formula Ei=0.25×biological abundance index Qi+0.2×vegetation cover index Fi+0.2×water network density index Si+0.2×land degradation index Ti+0.15×environmental quality index Hi to calculate the ecological environment status value Ei of the region, where the specific acquisition methods of different indexes are as follows:

[0040] Biological richness index Qi: Get all biological species in region i, record it as a, and get the area corresponding to region i, record it as Ki, and then substitute the two into the formula The biological richness index Qi is calculated, where It is a preset proportional coefficient, and the specific value is set by the operator;

[0041] Vegetation coverage index Fi: The vegetation coverage index (Fi) can be calculated by the proportion of forest land, grassland and farmland area in the region to the area of ​​the evaluated region. The specific formula is: Fi = (0.5 × forest area × growing period + 0.3 × grassland area × growing period + 0.2 × farmland area × growing period) / regional area;

[0042] Water network density index Si: Water network density index Si = (Ariv × river length / regional area) + (Alak × lake and reservoir (offshore) area / regional area) + (Ares × water resources / regional area). Among them, Ariv, Alak and Ares are the normalized coefficients of river length, lake and reservoir area and water resources respectively;

[0043] Land degradation index Ti: Land degradation index Ti = Aero × (0.05 × light erosion area + 0.25 × moderate erosion area + 0.70 × severe erosion area) / regional area, where Aero is the normalized coefficient of the land degradation index;

[0044] Specifically, the normalization coefficient is obtained in this application through Z-Score normalization, also known as zero mean normalization or standardization, which converts the data into a distribution with a mean of 0 and a standard deviation of 1. This method is suitable for situations where the data distribution is close to a normal distribution, and the formula is , and (X) is the original data, is the mean of the data, is the standard deviation of the data, is the normalized data. Suppose there is a data set ([1, 2, 3, 4, 5]) with a mean of 3 and a standard deviation of According to the Z-Score normalization method, the normalized data set is ([-1, -0.707, 0, 0.707, 1]). Then the normalized data is differenced and the average of the absolute values ​​of the differences is calculated. The specific calculation formula is -1-0.707-0.707-1=-3.414. Then the average value is calculated to get 0.6828, so the normalization coefficient is 0.6828.

[0045] Environmental quality index Hi: According to the evaluation purpose and regional characteristics, select key indicators that reflect environmental quality, such as PM2.5 concentration, water quality compliance rate, soil heavy metal content, etc. For each indicator, calculate the sub-index based on its value and standard value. For example, the air quality sub-index can be calculated based on the PM2.5 concentration, compare the air quality standards of other regions, convert the values ​​of each indicator into a unified evaluation standard, multiply each sub-index by its corresponding weight, and then sum it up to get the total environmental quality index Hi;

[0046] Combined with actual analysis, for example, for the environmental quality evaluation of a forest, air quality (such as PM2.5 concentration), water quality (such as the compliance rate of drinking water source water quality), soil quality (such as heavy metal content) and noise level (such as the average noise level in the forest) can be selected as evaluation indicators. Assume that after expert scoring and statistical analysis, the weights of each indicator are determined as follows: air quality 0.4, water quality 0.3, soil quality 0.2, noise level 0.1, and collect the environmental indicator data of the forest in the previous year, including the annual average concentration of PM2.5 of 30μg / m³, the compliance rate of drinking water source water quality of 90%, the qualified rate of soil heavy metal content of 85%, and the average noise level of 20 decibels in the forest. All data are normalized and converted into scores from 0 to 100 for easy comparison. For example, normalize the PM2.5 concentration to its percentage in the air quality standard;

[0047] Assuming that the air quality evaluation standard is that PM2.5 concentration below 35μg / m³ is excellent, 35-75μg / m³ is good, and above 75μg / m³ is poor, therefore, the normalized score of the PM2.5 concentration of the forest is 80 points. Similarly, other indicators are also standardized accordingly, resulting in a water quality score of 90 points, a soil quality score of 85 points, and a noise level score of 20 points. According to the weights, the total score of Hi is calculated: Hi = 0.4 × 80 + 0.3 × 90 + 0.2 × 85 + 0.1 × 20 = 78 points.

[0048] Then according to the formula The ecological carrying capacity Ui corresponding to region i is calculated, where ef is the per capita ecological footprint; N is the population; aa i is the biological production area converted per capita for the mth type of consumer goods; r j is the equilibrium factor of the jth land type; C i is the per capita consumption of the mth item; P m is the average production capacity of the mth item;

[0049] The ecological carrying value Ui and the ecological environment status value Ei calculated in different regions are summed to obtain the assessment value Gi, and the assessment values ​​of all regions are averaged to obtain the comparison value G. The assessment value Gi is compared with the comparison value G. When the assessment value Gi is greater than the comparison value G, the corresponding region is classified as an abnormal region. Conversely, when the assessment value Gi is less than the comparison value G, the corresponding region is classified as a normal region.

[0050] Comprehensive evaluation and analysis module, which is used to analyze the abnormal area according to the acquired regional classification information, and classify the abnormal area according to the distribution of the abnormal area to obtain dispersed distribution information and concentrated distribution information, and transmit the dispersed distribution information to the secondary analysis and processing module, and then classify the abnormal area evaluation values ​​corresponding to the concentrated distribution information, and periodically monitor the abnormal area level to generate evaluation information, and the specific method of generating the evaluation information is:

[0051] Obtain all abnormal areas, and judge the distribution of the abnormal areas and generate corresponding distribution information, and the distribution information includes dispersed distribution information and concentrated distribution information. At the same time, analyze the concentrated distribution information, combine the abnormal areas to obtain abnormal blocks, then sum the evaluation values ​​of all abnormal areas and calculate the mean, and use the mean as the evaluation standard of the abnormal blocks, and classify the abnormal blocks according to the evaluation standard. Specifically, the abnormal blocks are classified according to the preset evaluation value level interval, and the specific values ​​of the evaluation value level interval are calculated and set according to historical data;

[0052] Then, with time t as a cycle, the evaluation value of the abnormal block is monitored for changes. If the evaluation value of the abnormal block increases within the time period t, a warning signal is generated. Conversely, if the evaluation value of the abnormal block decreases within the time period t, a reduction signal is generated. At the same time, corresponding evaluation information is generated according to the warning signal and the reduction signal, and the evaluation information is transmitted to the evaluation information output module. The evaluation information generated here is the evaluation level information corresponding to the abnormal block.

[0053] An evaluation information output module is used to display the acquired evaluation information to the corresponding operator.

[0054] Embodiment 2, as Embodiment 2 of the present invention, is implemented on the basis of Embodiment 1, and differs from Embodiment 1 in that.

[0055] The secondary analysis and processing module is used to analyze the obtained scattered distribution information, judge the adjacent areas of the abnormal area and perform different analysis methods, and generate evaluation information and periodic monitoring signals at the same time, and analyze the periodic monitoring signals, judge the changes in the evaluation values ​​in the normal area time period and generate regional early warning signals and normal monitoring signals, and then analyze the generated signals to generate evaluation information, and transmit the evaluation information to the evaluation information output module. The specific method of generating the evaluation information is:

[0056] Analyze the scattered distribution information, obtain the abnormal area, and judge the adjacent area of ​​the abnormal area. If the adjacent area of ​​the abnormal area is a normal area, generate a periodic monitoring signal. If the adjacent area of ​​the abnormal area is an abnormal area, merge the abnormal areas and calculate the overall evaluation value after the merger, and generate the evaluation level and evaluation information according to the evaluation value;

[0057] For the generated periodic monitoring signal, obtain the change of the evaluation value of the normal area within the time period t. If the evaluation value increases, the corresponding normal area generates a regional warning signal. If the evaluation value decreases, the corresponding normal area generates a normal monitoring signal. At the same time, all normal areas that generate regional warning signals are obtained and recorded as analysis areas, and the change in the number of analysis areas within the time period t1 is determined;

[0058] If the number of analysis areas increases, the sum of the evaluation values ​​of all analysis areas is calculated, and the overall mean is calculated at the same time. The corresponding evaluation level is generated based on the mean, and the evaluation information is further generated. If the number of analysis areas decreases, a normal monitoring signal is generated, and then the normal monitoring signal is analyzed, the sum of the evaluation values ​​of all areas is calculated, and the corresponding evaluation value mean is calculated. At the same time, the overall evaluation level is analyzed based on the evaluation value mean to generate evaluation information, and then the evaluation information is transmitted to the evaluation information output module.

[0059] An evaluation information output module is used to display the acquired evaluation information to the corresponding operator.

[0060] Embodiment 3, as the embodiment 3 of the present invention, focuses on combining the implementation processes of embodiment 1 and embodiment 2 for implementation.

[0061] Example 4, please refer to Figure 2 , a method for evaluating the ecological value of a forest ecosystem, the method specifically comprising the following steps:

[0062] Step 1: Calculate the corresponding ecological environment status value and ecological carrying value based on the ecological information of different regions and sum them up to obtain the evaluation value. At the same time, classify the regions according to the evaluation value to obtain classification information, and the classification information includes normal areas and abnormal areas. The specific method of obtaining the classification information here is the same as the processing method of generating classification information by the forest area classification processing module in Example 1.

[0063] Step 2: Analyze the distribution of abnormal areas to generate distribution information, and analyze the concentrated distribution information, combine the abnormal areas to obtain abnormal blocks, and calculate the evaluation criteria of the abnormal blocks at the same time, generate evaluation grades according to the evaluation criteria, and then generate evaluation information according to the changes in the evaluation values. The specific method of generating the evaluation information is the same as the processing method of the comprehensive evaluation and analysis module in Example 1.

[0064] Step three: Analyze the dispersed distribution information, judge the adjacent areas of the abnormal area and perform different analysis methods, and generate evaluation information based on the changes in the evaluation values ​​corresponding to the time period. The specific method of generating the evaluation information is the same as the generation method of the secondary analysis processing module in Example 1.

[0065] Step 4: Display the generated evaluation information to the corresponding operator, and the display method of the evaluation information output module in the first embodiment is the same.

[0066] Meanwhile, the contents not described in detail in this specification belong to the prior art known to those skilled in the art.

[0067] The above embodiments are only used to illustrate the technical method of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical method of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present invention.

Claims

1. A forest ecosystem ecological value assessment system, characterized in that: include: The forest area classification processing module is used to calculate the evaluation values ​​of different areas according to the ecological information transmitted by the forest area information collection module, and classify different areas into normal areas and abnormal areas according to the evaluation values, and generate regional classification information at the same time, and then transmit the regional classification information to the comprehensive evaluation and analysis module. The specific method of generating regional classification information is: Different regions are labeled and recorded as i, and i=1, 2, …, j, where j is the number of different regions. The biological richness index Qi, vegetation coverage index Fi, water network density index Si, land degradation index Ti and environmental quality index Hi of different regions i are substituted into the formula Ei=0.25×biological abundance index Qi+0.2×vegetation coverage index Fi+0.2×water network density index Si+0.2×land degradation index Ti+0.15×environmental quality index Hi to calculate the ecological environment status value Ei of the region; Then according to the formula The ecological carrying capacity Ui corresponding to region i is calculated, where ef is the per capita ecological footprint; N is the population; aa c is the biological production area converted for the cth type of consumer goods per capita; r v is the equilibrium factor of the vth land type; C c is the per capita consumption of the cth item; P c is the average production capacity of the cth item; The ecological carrying value Ui and the ecological environment status value Ei calculated in different regions are summed to obtain the assessment value Gi, and the assessment values ​​of all regions are averaged to obtain the comparison value G. The assessment value Gi is compared with the comparison value G. When the assessment value Gi is greater than the comparison value G, the corresponding region is classified as an abnormal region. Conversely, when the assessment value Gi is less than the comparison value G, the corresponding region is classified as a normal region. The comprehensive evaluation and analysis module is used to analyze the abnormal area according to the acquired regional classification information, and classify the abnormal area according to the distribution of the abnormal area to obtain dispersed distribution information and concentrated distribution information, and transmit the dispersed distribution information to the secondary analysis and processing module, and then classify the abnormal area evaluation values ​​corresponding to the concentrated distribution information, and periodically monitor the abnormal area level to generate evaluation information. The specific processing method is: Obtain all abnormal areas, and judge the distribution of the abnormal areas and generate corresponding dispersed distribution information and concentrated distribution information, analyze the concentrated distribution information, combine the abnormal areas to obtain abnormal blocks, then sum up the evaluation values ​​of all abnormal areas and calculate the mean, and use the mean as the evaluation standard of the abnormal blocks, and classify the abnormal blocks according to the evaluation standard, specifically, classify the abnormal blocks according to the preset evaluation value level interval; Then, the evaluation value of the abnormal block is monitored for changes with time t as a cycle. If the evaluation value of the abnormal block increases within the time period t, a warning signal is generated. Conversely, if the evaluation value of the abnormal block decreases within the time period t, a reduction signal is generated. At the same time, corresponding evaluation information is generated according to the warning signal and the reduction signal, and the evaluation information is transmitted to the evaluation information output module; The secondary analysis and processing module is used to analyze the obtained scattered distribution information, judge the adjacent areas of the abnormal area and perform different analysis methods, and generate evaluation information and periodic monitoring signals. The specific processing methods are as follows: Analyze the scattered distribution information, obtain the abnormal area, and judge the adjacent area of ​​the abnormal area. If the adjacent area of ​​the abnormal area is a normal area, generate a periodic monitoring signal. If the adjacent area of ​​the abnormal area is an abnormal area, merge the abnormal areas and calculate the overall evaluation value after the merger, and generate the evaluation level and evaluation information according to the evaluation value; For the generated periodic monitoring signal, obtain the change of the evaluation value of the normal area within the time period t. If the evaluation value increases, generate a regional warning signal for the corresponding normal area. If the evaluation value decreases, generate a normal monitoring signal for the corresponding normal area, and analyze the regional warning signal. And analyze the periodic monitoring signal, determine the change of the evaluation value within the normal area time period and generate a regional warning signal and a normal monitoring signal, then analyze the generated signal to generate evaluation information, and transmit the evaluation information to the evaluation information output module, and the specific processing method is: All normal areas that generate regional warning signals are obtained and recorded as analysis areas, and the change in the number of analysis areas within the time period t1 is determined. If the number of analysis areas increases, the sum of the evaluation values ​​of all analysis areas is calculated, and the overall mean is calculated at the same time. The corresponding evaluation level is generated according to the mean, and the evaluation information is generated; If the number of analysis areas is reduced, a normal monitoring signal is generated, and then the normal monitoring signal is analyzed, the sum of the evaluation values ​​of all areas is calculated, and the corresponding evaluation value mean is calculated. At the same time, the overall evaluation level is analyzed according to the evaluation value mean to generate evaluation information.

2. A forest ecosystem ecological value assessment system according to claim 1, characterized in that: It also includes a forest area information collection module and an evaluation information output module; A forest area information collection module, which is used to obtain ecological information of different areas and transmit the ecological information to the forest area classification processing module. The ecological information obtained includes environmental quality information and ecological carrying capacity information; An evaluation information output module is used to display the acquired evaluation information to the corresponding operator.

3. A method for evaluating the ecological value of a forest ecosystem, applied to a system for evaluating the ecological value of a forest ecosystem as claimed in any one of claims 1 to 2, characterized in that: The method comprises the following steps: Step 1: Calculate the corresponding ecological environment status value and ecological carrying value according to the ecological information of different regions and sum them up to obtain the evaluation value. At the same time, classify the regions according to the evaluation value to obtain classification information, and the classification information includes normal regions and abnormal regions; Step 2: Analyze the distribution of abnormal areas to generate distribution information, analyze the concentrated distribution information, combine the abnormal areas to obtain abnormal blocks, and calculate the evaluation criteria of the abnormal blocks. Generate an evaluation grade based on the evaluation criteria, and then generate evaluation information based on the change of the evaluation value; Step 3: Analyze the dispersed distribution information, judge the adjacent areas of the abnormal area and perform different analysis methods, and generate evaluation information based on the changes in the corresponding evaluation values ​​over time periods; Step 4: Display the generated evaluation information to the corresponding operator.

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