Forest wetland carbon sink intelligent monitoring and evaluating system and method

Abstract

The invention relates to the technical field of forest wetland carbon sink monitoring and evaluation, and particularly discloses a forest wetland carbon sink intelligent monitoring and evaluation system and method. According to the method, a vegetation carbon sequestration potential evaluation result is obtained by analyzing vegetation structure feature data of forest, water and soil composite ecology of the forest wetland, a water-soil-carbon cooperative evaluation result is obtained by analyzing specific hydrological-soil carbon cycle key elements of the forest wetland, and environmental disturbance response factors are obtained by combining various environmental disturbance factors. Through multi-source data fusion and intelligent modeling, a carbon sink quantitative evaluation value is output, and abnormal feedback is triggered; the problems that in the prior art, adaptability to a forest wetland compound ecological system is insufficient, evaluation refinement is insufficient, and dynamic response is lacked are solved. According to the method, accurate and dynamic monitoring and evaluation of forest wetland carbon sink are realized, carbon sink short plates can be accurately positioned, optimization support is provided, and technical support is provided for protection, restoration and optimization management of forest wetland carbon sink resources.

Description

Technical Field

[0001] This invention relates to the field of intelligent carbon sequestration monitoring and assessment technology, specifically to an intelligent monitoring and assessment system and method for carbon sequestration in forest wetlands. Background Technology

[0002] As important carbon sink carriers that combine the functions of forest and wetland ecosystems, forests and wetlands play an increasingly prominent role in carbon sequestration, climate regulation, and ecological security. However, current carbon sink monitoring and assessment technologies mostly focus on single ecosystem types, such as pure forests, coastal wetlands, or urban green spaces, lacking an integrated and intelligent monitoring and assessment system for the complex ecosystem of forests and wetlands. Significant shortcomings remain, particularly in key areas such as multi-source heterogeneous data fusion, refined simulation of dynamic carbon sink processes, intelligent identification of abnormal carbon flux fluctuations, and collaborative optimization of carbon sink pathways. These shortcomings make it difficult to meet the urgent need for high spatiotemporal resolution, real-time, and systematic assessment of the carbon sink capacity of forests and wetlands.

[0003] For example, Chinese Patent Publication No. CN115937692A discloses a method and system for evaluating the carbon sequestration effect of coastal wetlands. This method identifies wetland type evolution data through remote sensing images and evaluates the carbon sequestration effect by combining the state before and after the evolution. However, this scheme is mainly applicable to coastal wetlands dominated by salt marshes and mangroves, and does not fully consider the complex carbon cycle mechanism formed by the interaction between forest vegetation and hydrological processes in inland forest wetlands. At the same time, it relies on historical remote sensing images for static evolution analysis, lacks the ability to monitor carbon flux in real time, and cannot effectively capture short-term carbon sequestration anomalies caused by factors such as water level fluctuations, vegetation phenological changes, or human disturbances. Therefore, it is difficult to support refined and responsive carbon sequestration management decisions.

[0004] On the other hand, Chinese Patent Publication No. CN116881604A discloses a dynamic carbon sequestration measurement method for carbon sequestration afforestation projects, which automatically collects forest biomass data through IoT sample plots to achieve dynamic updates and value assessment of carbon storage. However, this method is specifically designed for terrestrial forest ecosystems in artificial afforestation projects and does not incorporate key influences of wetland-specific hydrological elements, such as flooding frequency and sediment carbon burial rate, on the carbon sequestration process. Furthermore, its monitoring system fails to cover the complex carbon exchange processes at the "forest-water-soil" interface in forest wetlands. As a result, when applied to forest wetland scenarios, the carbon sequestration accounting model has structural deficiencies, and the assessment results are prone to significant biases.

[0005] In summary, existing carbon sequestration monitoring technologies are insufficient to effectively support the intelligent monitoring and assessment needs of forest wetlands, a unique and complex ecosystem, in terms of ecosystem type adaptability, multi-media coupled carbon cycle process modeling, real-time dynamic sensing capabilities, and anomaly diagnosis and feedback optimization mechanisms. Therefore, there is an urgent need to construct an intelligent monitoring and assessment system for forest wetlands carbon sequestration that integrates multi-source sensing, remote sensing observation, and ground-based measured data. This system should accurately depict the three-dimensional dynamic process of carbon flux across vegetation, water, and soil, and possess intelligent identification of anomaly fluctuations and collaborative optimization capabilities for carbon sequestration pathways. This system would fill the current technological gaps and improve the scientific rigor, accuracy, and response efficiency of carbon sequestration management. Summary of the Invention

[0006] The purpose of this invention is to provide an intelligent monitoring and assessment system and method for carbon sequestration in forest wetlands, in order to solve the problems mentioned in the background.

[0007] The objective of this invention can be achieved through the following technical solution: The first aspect of this invention provides a smart monitoring and assessment system for carbon sequestration in forest wetlands, the system comprising:

[0008] The vegetation carbon sequestration potential evaluation module is used to acquire forest wetland vegetation structure characteristic data and generate forest wetland vegetation carbon sequestration potential evaluation values; among them, forest wetland vegetation structure characteristic data include canopy closure, vegetation coverage, and vertical differentiation index between the tree layer and the shrub and grass layer.

[0009] The water-soil carbon synergy evaluation module is used to acquire carbon cycle data at the water-soil interface in forest wetlands and generate synergy evaluation values ​​for water-soil carbon in forest wetlands. Among them, the water-soil interface carbon cycle data includes the vertical gradient change rate of soil organic carbon, the concentration of dissolved organic carbon in surface water, and the carbon burial rate in sediments.

[0010] The carbon sink baseline estimation module is used to acquire multi-source observation data of forest wetlands and generate a baseline estimation value of forest wetland carbon sink. The multi-source observation data includes the tree layer biomass, the shrub and grass layer dry weight, the soil organic carbon density, the sediment carbon burial amount, and the dissolved organic carbon storage in the surface water of the forest wetland observation area.

[0011] The environmental disturbance analysis module is used to acquire environmental disturbance data of forest wetlands and generate environmental disturbance response factors. Among them, the environmental disturbance data of forest wetlands includes the frequency of extreme rainfall events and water level depth of forest wetlands, light intensity, temperature and humidity of forest wetlands, human activity intensity index of forest wetlands, and invasive alien species coverage rate of forest wetlands.

[0012] The intelligent carbon sequestration assessment module is used to build an intelligent assessment model for forest and wetland carbon sequestration, generate assessment values ​​for forest and wetland carbon sequestration, determine the functional status of forest and wetland carbon sequestration, and provide feedback on any anomalies.

[0013] A second aspect of the present invention provides a method for intelligent monitoring and assessment of carbon sequestration in forest wetlands, the method comprising the following steps:

[0014] S1. Obtain forest wetland vegetation structure characteristic data and generate forest wetland vegetation carbon sequestration potential evaluation value; among which, forest wetland vegetation structure characteristic data include canopy closure, vegetation coverage, and vertical differentiation index between the tree layer and the shrub and grass layer.

[0015] S2. Obtain carbon cycle data at the water-soil interface in forest wetlands and generate a synergistic evaluation value for water-soil carbon in forest wetlands. Among them, the carbon cycle data at the water-soil interface includes the vertical gradient change rate of soil organic carbon, the concentration of dissolved organic carbon in surface water, and the carbon burial rate in sediments.

[0016] S3. Obtain multi-source observation data of forest wetlands and generate a baseline estimate of forest wetland carbon sink; among which, the multi-source observation data includes tree layer biomass, shrub and grass layer dry weight, soil organic carbon density, sediment carbon burial amount, and surface water dissolved organic carbon storage in the forest wetland observation area.

[0017] S4. Obtain environmental disturbance data of forest wetlands and generate environmental disturbance response factors; among which, the environmental disturbance data of forest wetlands includes the frequency of extreme rainfall events and water level depth of forest wetlands, light intensity, temperature and humidity of forest wetlands, human activity intensity index of forest wetlands and invasive alien species coverage rate of forest wetlands.

[0018] S5. Construct an intelligent assessment model for forest wetland carbon sequestration, generate assessment values ​​for forest wetland carbon sequestration, determine the functional status of forest wetland carbon sequestration, and provide feedback on any anomalies.

[0019] The beneficial effects of this invention are:

[0020] This invention analyzes the canopy closure, vegetation cover, and vertical differentiation index between the tree layer and the shrub and grass layer of the forest-wetland complex ecosystem to obtain the evaluation results of the vegetation carbon sequestration potential of the forest wetland. Then, it analyzes the unique hydrological-soil carbon cycle elements of the forest wetland, including the soil organic carbon decay coefficient, dissolved organic carbon concentration in surface water, and sediment carbon burial amount, to obtain the synergistic evaluation results of water and soil carbon in the forest wetland. Furthermore, it combines the impact of environmental disturbance factors such as hydrology, atmosphere, anthropogenic factors, and biological invasion on the carbon sink of the forest wetland to obtain the environmental disturbance response factors of the forest wetland. Based on the baseline estimated value of the carbon sink of the forest wetland, it finally outputs the quantitative assessment value of the carbon sink of the forest wetland and triggers anomaly feedback, thus optimizing the monitoring and assessment of carbon sink in forest wetlands. This fills the gap in the adaptability of existing technologies for carbon sink monitoring in forest wetland complex ecosystems, overcomes the limitation of traditional carbon sink monitoring technologies that only focus on a single ecosystem type, and achieves comprehensive monitoring of this complex ecosystem, improving the accuracy, dynamic responsiveness, and scientific decision-making support capabilities of carbon sink assessment. Attached Figure Description

[0021] The invention will now be further described with reference to the accompanying drawings.

[0022] Figure 1 This is the system architecture diagram of the present invention.

[0023] Figure 2 This is an architecture diagram of the vegetation carbon sequestration potential evaluation module of the present invention.

[0024] Figure 3 This is an architecture diagram of the water, soil, and carbon co-evaluation module of the present invention.

[0025] Figure 4 This is an architecture diagram of the environmental disturbance analysis module of the present invention.

[0026] Figure 5 This is an architecture diagram of the intelligent carbon sink assessment module of the present invention.

[0027] Figure 6 This is a flowchart of the method of the present invention. Detailed Implementation

[0028] 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. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0029] Please see Figure 1 As shown, this invention is an intelligent monitoring and assessment system for carbon sequestration in forest wetlands, which includes:

[0030] The vegetation carbon sequestration potential evaluation module 100 is used to acquire forest wetland vegetation structure characteristic data and generate forest wetland vegetation carbon sequestration potential evaluation values; among them, forest wetland vegetation structure characteristic data include canopy closure, vegetation coverage, and vertical differentiation index between the tree layer and the shrub and grass layer.

[0031] It should be noted that the vegetation structure characteristic data of forest wetlands are presented in the form of average values. For example, sufficient vegetation structure characteristic data samples can be selected from forest wetlands by random sampling or preset rules, such as dividing equal areas and setting fixed sampling intervals. Then, the average value of these sample data can be calculated to obtain the corresponding characteristic data. This method can avoid the data collection difficulties caused by the large area of ​​forest wetlands and can also accurately reflect the vegetation structure characteristics of forest wetlands to a certain extent.

[0032] Please see Figure 2 As shown, preferably, the vegetation carbon sequestration potential evaluation module specifically includes:

[0033] The canopy closure assessment unit 101 is used to obtain the canopy closure of forest wetlands and generate forest wetland canopy closure assessment values.

[0034] Specifically, the canopy closure of forest wetlands is obtained through ground-based lidar scanning or inversion using UAV multispectral cameras. Canopy closure refers to the ratio of the sum of the vertical projection areas of the tree canopies in the forest wetland to the corresponding total area of ​​the forest wetland. The difference between the canopy closure and the median of the standard canopy closure range is calculated to generate the canopy closure deviation. The standard canopy closure range refers to the reasonable range of canopy closure without affecting the ecological functions of the vegetation community (such as photosynthetic carbon sequestration, ventilation and light penetration, and community microclimate stability). It is the optimal range of canopy closure determined by actual observation and verification based on vegetation type and ecosystem characteristics.

[0035] The ratio of the canopy closure deviation to the median of the standard canopy closure range is calculated, and the absolute value is then mapped using a nonlinear decay function to generate the forest wetland canopy closure assessment value; where the nonlinear decay function is... ,in, Represents the empirical coefficient. Indicates a deviation in canopy closure. Indicates the canopy closure assessment value; empirical coefficient. This is the adjustment parameter in the nonlinear decay function for assessing canopy closure. Its function is to adapt to different vegetation types and ecosystem characteristics of forest wetlands. Because the optimal range for canopy closure varies among different vegetation types (such as mangroves and slash pine), the rate of photosynthetic efficiency decline after the canopy closure deviates from the optimal median also differs. For example, mangroves are more tolerant of excessively high canopy closure. The value will be smaller; while slash pine is more sensitive to deviations in canopy closure. The value is even larger, and can be adjusted. The value of the value allows the nonlinear decay function to accurately match the actual ecological response pattern of a specific vegetation type, avoiding evaluation bias caused by uniform parameters.

[0036] The vegetation coverage assessment unit 102 is used to obtain the vegetation coverage of forest wetlands and generate forest wetland vegetation coverage assessment values.

[0037] Specifically, the vegetation cover of forest wetlands is obtained by inverting the NDVI threshold method of satellite remote sensing images. The difference between the vegetation cover and the median of the standard vegetation cover range is calculated to generate the vegetation cover deviation. The standard vegetation cover range refers to the size range of the vegetation cover area in the target area without affecting the photosynthetic carbon fixation function of forest wetland vegetation and the carbon exchange regulation function of water-soil interface.

[0038] The forest wetland vegetation cover assessment value is generated by calculating the ratio of the median of the standard vegetation cover range to the absolute value of the vegetation cover deviation. It should be noted that the specific formula for calculating this ratio is as follows: ,in This is to avoid the formula calculation being meaningless when the vegetation coverage deviation is 0.

[0039] Vertical structure differentiation assessment unit 103 is used to obtain the vertical differentiation index between the tree layer and the shrub and grass layer of the forest wetland and generate the vertical structure differentiation assessment value of the forest wetland.

[0040] Specifically, based on lidar point cloud data, the height distribution information of the tree layer and shrub and grass layer in forest wetlands is extracted, the ratio of the standard deviation of the height distribution of the two layers is calculated, and the vertical differentiation index (VSI) is constructed.

[0041] The difference between the Vertical Differentiation Index (VSI) and the median of the Ideal Structure Differentiation Index range is calculated to generate the Vertical Differentiation Index Deviation. The Ideal Structure Differentiation Index range refers to the numerical range of the ratio of the standard deviation of the height distribution of the tree layer and the shrub and grass layer in forest wetlands without affecting the efficiency of light energy stratification and utilization and the stability of the community microenvironment.

[0042] The vertical differentiation index deviation is calculated as the ratio to the median of the ideal structural differentiation index range, and then normalized using the Sigmoid function to generate the vertical structural differentiation assessment value. The Sigmoid function normalization formula is as follows: ,in, This indicates the vertical differentiation index deviation. This represents the median value of the ideal structure differentiation index. This represents the evaluation value for vertical structural differentiation.

[0043] The carbon sequestration potential generation unit 104 is used to generate a forest wetland vegetation carbon sequestration potential evaluation value by weighting the forest wetland canopy closure assessment value, forest wetland vegetation coverage assessment value, and forest wetland vertical structure differentiation assessment value.

[0044] For example, through a weighted formula Generate an evaluation value for the carbon sequestration potential of forest and wetland vegetation. ;in, This indicates the assessment value of forest and wetland vegetation coverage. These represent the weighting factors corresponding to the forest wetland canopy closure assessment value, forest wetland vegetation coverage assessment value, and forest wetland vertical structure differentiation assessment value, respectively. In this application, The weights are set based on the ecological contribution of each indicator. Canopy closure corresponds to the photosynthetic carbon sequestration capacity of the tree layer in forest wetlands. The tree layer is the core energy-producing layer for carbon sequestration by vegetation in forest wetlands. The canopy is the main carrier for vegetation to capture light energy and fix CO2 through photosynthesis. The rationality of its canopy closure directly determines the photosynthetic area and light energy utilization efficiency of the tree layer. Therefore, canopy closure has the greatest direct contribution to the carbon sequestration potential of vegetation, and its corresponding weight is the highest among the three. Vegetation cover corresponds to the carbon sequestration and carbon cycle regulation capacity of unique aquatic vegetation in forest wetlands. It belongs to the auxiliary supplementary layer. Aquatic vegetation can fix CO2 through its own photosynthesis and also regulate water... Carbon cycling at the soil interface, such as reducing the loss of dissolved organic carbon in water and stabilizing carbon sequestration in sediments, contributes to the core energy production layer. Therefore, vegetation cover's contribution is a supplementary factor, with a lower weight than canopy closure but higher than vertical structural differentiation. Vertical structural differentiation corresponds to the rationality of forest-wetland community structure; it is an indirect support layer. Vertical structural differentiation does not directly participate in photosynthetic carbon sequestration but indirectly improves the carbon sequestration efficiency of the tree and aquatic vegetation layers by optimizing the stratified use of light energy in the community, reducing light competition, and maintaining microclimate stability (such as humidity and temperature). Therefore, the contribution of vertical structural differentiation is an indirect supporting role, with the lowest weight among the three.

[0045] It should be further noted that the evaluation value of vegetation carbon sequestration potential ranges from 0 to 1. The closer the evaluation value of vegetation carbon sequestration potential is to 1, the greater the vegetation carbon sequestration potential.

[0046] The water-soil carbon synergy evaluation module 200 is used to acquire carbon cycle data of the water-soil interface in forest wetlands and generate a synergy evaluation value of water-soil carbon in forest wetlands. Among them, the water-soil interface carbon cycle data includes soil organic carbon decay coefficient, dissolved organic carbon concentration in surface water, and sediment carbon burial amount.

[0047] Please see Figure 3 As shown, preferably, the water, soil, and carbon synergistic evaluation module specifically includes:

[0048] The soil carbon gradient analysis unit 201 is used to obtain the organic carbon attenuation coefficient of forest wetland soil and generate soil carbon gradient evaluation value.

[0049] Specifically, soil organic carbon content at a predetermined depth is measured through stratified sampling. An exponential decay curve of soil organic carbon content with depth is fitted, and the decay coefficient is calculated. The exponential decay curve model is as follows: ,express Soil organic carbon content at depth z This represents the initial content of organic carbon in the topsoil. The attenuation coefficient indicates the rate of decrease. The larger the attenuation coefficient, the faster the soil organic carbon content decreases with depth, the more obvious the enrichment of surface carbon, but the worse the stability of deep carbon. The smaller the attenuation coefficient, the slower the organic carbon decreases with depth, the more abundant the deep carbon reserve, and the stronger the stability.

[0050] The attenuation coefficient difference is calculated by comparing the attenuation coefficient with the attenuation coefficient threshold of a healthy forest wetland; the attenuation coefficient threshold of a healthy forest wetland refers to the maximum attenuation coefficient under standard conditions of a healthy forest wetland.

[0051] The soil carbon gradient evaluation value is generated by ratioing the attenuation coefficient threshold to the attenuation coefficient difference; it should be noted that the specific ratio formula is as follows: ,in The term is omitted to avoid the formula calculation being meaningless when the attenuation coefficient difference is 0. The soil carbon gradient evaluation value is used to characterize the stability of the vertical distribution of soil carbon. The larger the soil carbon gradient evaluation value, the smaller the deviation between the measured attenuation coefficient and the attenuation coefficient threshold of healthy forest wetlands, the closer the vertical distribution of soil carbon is to the state of healthy wetlands, and the stronger the stability. The smaller the soil carbon gradient evaluation value, the greater the deviation and the worse the stability of the vertical distribution of soil carbon.

[0052] The water carbon activity analysis unit 202 is used to obtain the dissolved organic carbon concentration in the surface water of forest wetlands and generate a water carbon activity evaluation value.

[0053] Specifically, the concentration of dissolved organic carbon (DOC) in surface water is measured, and the difference between this concentration and the median range of background DOC concentration in forest wetland water is calculated to generate the DOC bias.

[0054] The DOC deviation is calculated by comparing it with the median of the DOC background concentration range to generate a DOC deviation value.

[0055] The water temperature of forest wetlands was obtained, and a temperature correction factor was generated based on the Q10 model. The Q10 model quantifies the impact of temperature on microbial activity, and the formula for generating the temperature correction factor using the Q10 model is as follows: , Indicates the temperature correction factor. This represents the temperature coefficient (a general ecological parameter, set to 2, indicating that for every 10°C increase in temperature, microbial activity doubles). Indicates water temperature, The reference temperature is usually 20°C, which is the suitable temperature for wetland microbial activity. It should be noted that water temperature affects microbial activity, which in turn affects the decomposition rate of DOC. The higher the water temperature, the stronger the microbial activity, the easier it is to decompose DOC, and the higher the carbon activity in the water. By correcting with the Q10 model, the difference in water temperature can be converted into a quantitative impact on carbon activity, avoiding the one-sidedness of assessing only DOC concentration.

[0056] A water body carbon activity assessment model was established, and the DOC deviation value and water temperature correction factor were substituted into the model to generate a water body carbon activity assessment value. The water body carbon activity evaluation model is as follows: , This indicates the degree of DOC deviation; in the formula, the exponent term... The inhibitory effect of DOC deviation from healthy forest wetland conditions is quantified. A larger DOC deviation value indicates a more abnormal DOC concentration in the water (excessive high DOC leads to sedimentation, while excessively low DOC indicates insufficient carbon carriers), and a poorer suitability for carbon exchange at the water-soil interface. For example, if... (No deviation) The temperature gain is fully effective if (The deviation is relatively large) Temperature gain is weakened, and carbon activity decreases due to DOC abnormalities. The formula shows that when DOC concentration deviates from the healthy baseline, even if the water temperature is suitable, the suitability for carbon exchange will decrease.

[0057] The carbon activity evaluation value of water bodies is used to characterize the intensity of carbon exchange between water bodies and soil. The higher the carbon activity evaluation value of water bodies, the more suitable the carbon exchange activity at the water-soil interface, the more significant the carbon sink contribution, and the more effectively it can support the carbon sink process.

[0058] The sedimentary carbon sequestration analysis unit 203 is used to obtain the amount of sedimentary carbon buried in forest wetlands and generate sedimentary carbon sequestration evaluation values.

[0059] Specifically, the carbon sequestration of forest wetlands is obtained and compared with the regional baseline carbon sequestration to generate relative sequestration strength.

[0060] The method for obtaining sediment carbon burial in forest wetlands is as follows: A sediment column of 50-100 cm depth is collected from sediment-rich areas of the sample plot (such as the bottom of swamps or ditches) using a column sampler, and the sample is cut into layers at 2-5 cm intervals; 210The Pb radiometric dating method was used to determine the depositional age of each sedimentary layer and calculate the depositional rate. The organic carbon content of each sample was determined by an elemental analyzer. Combined with the dry bulk density of the sediment, the carbon burial content of the sediment was calculated according to the formula: sediment carbon burial content = sediment bulk density × organic carbon content × depositional rate × 10.

[0061] A sedimentary carbon sequestration evaluation model was constructed, and the relative sequestration intensity was substituted into the model to generate sedimentary carbon sequestration evaluation values; wherein, the sedimentary carbon sequestration evaluation model is as follows: , This indicates the evaluation value of sedimentary carbon sequestration. This represents the relative carbon sequestration intensity. The formula sets R=1.5 (i.e., the actual carbon sequestration of sediments is 1.5 times the baseline) as the "optimal threshold for the carbon sequestration capacity of sediments". This is because the carbon sequestration capacity of actual forest wetlands cannot be increased indefinitely. It is limited by ecological conditions such as sediment capacity and organic matter input. R=1.5 is already an extremely strong carbon sequestration state that far exceeds the baseline of healthy wetlands. Differences exceeding this value are not very meaningful for distinguishing the carbon sequestration capacity level. Therefore, it is necessary to lock the upper limit of the full score through truncation. By combining logarithmic compression and threshold truncation, we can avoid the overflow of sediment carbon sequestration evaluation value and reasonably characterize the strength of sediment carbon sequestration capacity.

[0062] The sedimentary carbon sequestration evaluation value is used to characterize the carbon sequestration capacity of sediments. The higher the sedimentary carbon sequestration evaluation value, the stronger the carbon burial capacity of the sediments and the better the long-term carbon sequestration effect.

[0063] The water and soil carbon co-evaluation generation unit 204 is used to perform dimensionality reduction and fusion of soil carbon gradient evaluation values, water carbon activity evaluation values ​​and sediment carbon sequestration evaluation values ​​of several sampling areas of forest wetlands using principal component analysis (PCA) to generate a water and soil carbon co-evaluation value for forest wetlands.

[0064] Specifically, soil carbon gradient evaluation values, water carbon activity evaluation values, and sediment carbon sequestration evaluation values ​​are obtained from several sampling areas of the forest wetland to form a data matrix; the data matrix is ​​then standardized to obtain a standardized data matrix.

[0065] The covariance matrix is ​​calculated from the standardized data matrix, and the eigenvalues ​​and eigenvectors of the covariance matrix are solved by matrix operations (eigenvalue decomposition). The covariance matrix reflects the correlation between soil carbon gradient evaluation value, water carbon activity evaluation value and sediment carbon sequestration evaluation value. The larger the eigenvalue, the more information the corresponding eigenvector represents.

[0066] The variance contribution rates of the principal components are accumulated sequentially in descending order of eigenvalues. The top k principal components with a cumulative variance contribution rate of 85% or higher are considered as effective principal components. It should be noted that the variance contribution rate of each principal component is the proportion of its eigenvalue to the sum of all eigenvalues.

[0067] The standardized data matrix is ​​projected onto the directions of each effective principal component to obtain the scores of each effective principal component in several sampling areas. The contribution rate of each effective principal component (i.e., the ratio of the contribution rate of a single principal component to the cumulative contribution rate) is used as the weight to perform weighted fusion of the scores of each effective principal component in several sampling areas to generate the water, soil and carbon synergistic evaluation value of several sampling areas.

[0068] The water-soil carbon synergistic evaluation values ​​of several sampling areas were normalized to generate normalized water-soil carbon synergistic evaluation values ​​for several sampling areas. These normalized values ​​were then averaged to generate the water-soil carbon synergistic evaluation values ​​for forest wetlands. The normalization method used was min-max normalization.

[0069] It should be noted that the above steps, through PCA dimensionality reduction, not only retain the core information of the three sub-evaluation values ​​but also avoid information redundancy between indicators. The final water-soil carbon synergy evaluation value can objectively reflect the overall synergistic efficiency of wetland carbon cycling. The larger the water-soil carbon synergy evaluation value, the more synergistic the carbon cycling processes of forest wetland soil, water, and sediment are, the stronger the synergistic effect of carbon fixation, transmission, and storage, and the more significant the overall carbon sink contribution.

[0070] For example, the above three indicators were measured in 10 sampling areas of forest wetlands, and a standardized data matrix was obtained (example of some areas):

[0071] Sampling area Soil carbon gradient evaluation value Water carbon activity evaluation value Evaluation value of sedimentary carbon sequestration Area 1 0.871 0.495 0.165 Area 2 0.174 -0.495 0.165 Area 9 1.568 1.485 1.485

[0072] The eigenvalues ​​of the covariance matrix after standardization are calculated. Calculate the contribution rates of the three principal components in the example: Contribution rate of Principal Component 1 (PC1): Principal Component 2 (PC2) Contribution Rate: Principal Component 3 (PC3) Contribution Rate: Cumulative contribution rate: First principal component: 60% (<85%); First two principal components: 60% + 30% = 90% (>85%). Therefore, the first two principal components are selected as effective principal components.

[0073] Assume the eigenvectors of the first two principal components in the example are: eigenvector of PC1: ; Eigenvectors of PC2: ;

[0074] Taking region 1 as an example, calculate the principal component score: PC1 score: PC2 score: Similarly, calculate the PC1 and PC2 scores for all regions.

[0075] In the example, the cumulative contribution of the first two principal components is 90%, therefore, the weight of PC1 is: PC2 weights: Taking region 1 as an example, the water, soil, and carbon synergistic evaluation value P 1 h For: P 1 h =0.861×0.667+0.294×0.333≈0.574+0.098=0.672.

[0076] The carbon sink baseline estimation module 300 is used to acquire multi-source observation data of forest wetlands and generate a baseline estimation value of forest wetland carbon sink. The multi-source observation data includes the tree layer biomass, shrub and grass layer dry weight, soil organic carbon density, sediment carbon burial amount, and dissolved organic carbon storage in surface water of the forest wetland observation area.

[0077] Through formula Generate a baseline estimate of forest and wetland carbon sequestration. ; This indicates the tree layer biomass in the observed area. Indicates the dry weight of the shrub and grass layer in the observation area. Indicates the carbon content coefficient of the tree layer. Carbon content coefficient of shrub and grass layer This indicates the soil organic carbon density in the observation area. This indicates the amount of carbon buried in the sediments of the observed area. This indicates the dissolved organic carbon storage in the surface water of the observation area. The term represents the ratio of the observed area of ​​forest wetlands to the total area of ​​forest wetlands. The tree biomass, shrub and grass dry weight, soil organic carbon density, sediment carbon sequestration, and dissolved organic carbon storage in surface water are all normalized or standardized values ​​to eliminate the dimensions of each parameter, thus ensuring the formula is unaffected by dimensions and yields a baseline estimate of forest wetland carbon sequestration.

[0078] It should be noted that the specific method for obtaining the tree layer biomass in the observation area was as follows:

[0079] The diameter at breast height (DBH) and tree height of individual trees in the canopy layer of the forest wetland observation area were obtained, and the biomass of individual trees in the canopy layer was calculated using the allometric growth equation; the allometric growth equation is: ,in, This represents a proportionality coefficient, an empirical parameter for adapting tree species. The index representing the diameter at breast height (DBH) indicates the rate at which biomass changes with DBH. The index representing the tree height indicates the rate at which biomass changes with tree height. It should be noted that the allometric growth equation is established by fitting growth curves based on field measurements of standard tree biomass, and then establishing a fitting equation between diameter at breast height (DBH), tree height, and biomass.

[0080] The average biomass per tree in the tree layer of the forest wetland observation area is generated by summing the biomass of all trees in the tree layer of the observation area and dividing by the total number of trees in the tree layer of the observation area.

[0081] The stand density of the forest wetland observation area is obtained, and the stand density is multiplied by the average biomass per tree in the tree layer to generate the tree layer biomass of the forest wetland observation area. Stand density refers to the ratio of the total number of trees in the tree layer to the total area of ​​the observation area.

[0082] The soil organic carbon density in the observation area was obtained by acquiring the soil organic carbon content, soil bulk density, soil layer thickness, and soil gravel content of each soil layer at a predetermined depth in the forest wetland observation area, and then using the formula... The soil organic carbon density of the forest wetland observation area was calculated. ;k represents the soil layer number, k=1,2,...,m, where m represents the total number of soil layer numbers. This represents the bulk density of the k-th soil layer. This represents the organic carbon content of the k-th soil layer. This represents the thickness of the k-th soil layer. The term represents the gravel content of the i-th soil layer, referring to the volume percentage of gravel (particle size greater than 2 mm) in the soil. It is used to correct for the influence of inactive substances on carbon density. The formula contains... The project aims to exclude the contribution of gravel to organic carbon storage, and 100 represents the unit conversion factor used to convert the units of each parameter to the target unit (tons of carbon per hectare).

[0083] The method for obtaining the dissolved organic carbon storage in the surface water of the observation area is as follows: obtain the organic carbon concentration, surface water distribution area and average depth of the forest wetland observation area, and perform product processing to generate the organic carbon storage in the surface water of the forest wetland observation area.

[0084] The environmental disturbance analysis module 400 is used to acquire environmental disturbance data of forest wetlands and generate environmental disturbance response factors. Among them, the environmental disturbance data of forest wetlands includes the frequency of extreme rainfall events and water level depth of forest wetlands, light intensity, temperature and humidity of forest wetlands, human activity intensity index of forest wetlands, and invasive alien species coverage rate of forest wetlands.

[0085] Please see Figure 5 As shown, preferably, the environmental disturbance analysis module specifically includes:

[0086] The hydrological disturbance analysis unit 401 is used to obtain the frequency of extreme rainfall events and water level depth in forest wetlands, and to generate the hydrological disturbance coefficient of forest wetlands; specifically:

[0087] The extreme rainfall impact value is generated by calculating the ratio between the frequency of extreme rainfall events in forest wetlands and the threshold of the frequency of rainfall disturbance events that allow the ecological environment of forest wetlands.

[0088] The difference between the water level depth of the forest wetland and the allowable water level depth threshold of the forest wetland ecological environment is calculated to generate the water level depth difference; the ratio between the water level depth difference and the allowable water level depth threshold of the forest wetland ecological environment is calculated to generate the water level depth influence value.

[0089] The impact values ​​of extreme rainfall and water level depth are summed to generate the hydrological disturbance coefficient of forest wetlands;

[0090] It should be noted that extreme rainfall events refer to events with rainfall of ≥50mm; the larger the hydrological disturbance coefficient, the greater the frequency of extreme rainfall and the greater the water level depth exceeds the ecological carrying capacity, and the stronger the negative inhibition on carbon sinks.

[0091] Atmospheric disturbance analysis unit 402 is used to acquire light intensity, temperature, and humidity data of forest wetlands and generate atmospheric disturbance coefficients for forest wetlands; specifically:

[0092] The difference between the light intensity of forest wetlands and the standard light intensity of forest wetlands is calculated to generate the light intensity difference; the ratio of the light intensity difference to the standard light intensity of forest wetlands is calculated to generate the light intensity influence value; similarly, the influence values ​​of temperature and humidity are analyzed and obtained. The influence values ​​of light intensity, temperature, and humidity are accumulated to generate the atmospheric disturbance coefficient of forest wetlands.

[0093] Anthropogenic disturbance analysis unit 403 is used to obtain the intensity index of human activities in forest wetlands and generate anthropogenic disturbance coefficients for forest wetlands; specifically:

[0094] The system acquires data on road density, visitor density, land use conversion area ratio, and construction trace area ratio of forest wetlands. These data are converted to lengths according to preset ratios, input into a computer, and processed by a computer program to obtain the human activity intensity index of the forest wetlands. The specific processing steps of the computer program are as follows: a cuboid is constructed using the lengths of road density, visitor density, and land use conversion area ratio as length, width, and height, respectively. A quadrangular pyramid is constructed using the top face of the cuboid as the base and the length of the construction trace area ratio as the height. The volume corresponding to the combination of the cuboid and the quadrangular pyramid is identified, and its volume value is used as the human activity intensity index of the forest wetlands, which is then output. It should be noted that road density refers to the ratio of the total length of roads in the forest wetlands to the total area of ​​the forest wetlands, reflecting the impact of transportation construction on the soil of the forest wetlands. The degree of vegetation cutting and destruction; visitor density refers to the ratio of the total number of visitors to forest wetlands to the total area of ​​forest wetlands, reflecting the direct disturbance of visitors to vegetation and soil carbon pools; the land use conversion area ratio refers to the ratio of the area of ​​forest wetlands converted to other land uses to the total area of ​​forest wetlands, reflecting the intensity of disturbance caused by farmland reclamation, building occupation, etc. to the conversion of wetland ecosystems; the engineering construction trace area ratio refers to the ratio of the area occupied by forest wetland engineering facilities to the total area of ​​forest wetlands, reflecting the degree of damage to wetland hydrology and vegetation caused by projects such as dikes and power transmission lines.

[0095] The ratio of the intensity index of human activities in forest wetlands to the upper limit of ecological carrying capacity is used to generate the human disturbance coefficient; where the upper limit of ecological carrying capacity is the threshold of the maximum intensity of human activities that forest wetlands can withstand.

[0096] It should be noted that the upper limit of ecological carrying capacity refers to the maximum intensity of human disturbance that forests and wetlands can withstand;

[0097] The larger the anthropogenic disturbance coefficient, the greater the degree to which the intensity of human activities exceeds the ecological carrying capacity, and the stronger the negative inhibition on carbon sinks.

[0098] The biological invasion disturbance analysis unit 404 is used to obtain the invasive coverage rate of alien species in forest wetlands, calculate the ratio of the invasive coverage rate of alien species to the standard invasive coverage rate, and generate a biological invasion inhibition coefficient. Specifically, satellite images of forest wetlands are acquired through remote sensing technology, and radiometric calibration, atmospheric correction, and geometric correction are performed on the satellite images using ENVI software to identify invasive species, extract the area occupied by the invasive species, and process the ratio with the total area of ​​forest wetlands to generate the invasive coverage rate of alien species.

[0099] The environmental disturbance response factor generation unit 405 is used to weight the hydrological disturbance coefficient, atmospheric disturbance coefficient, anthropogenic disturbance coefficient and biological invasion inhibition coefficient to generate the forest wetland environmental disturbance response factor.

[0100] For example, through the formula The forest wetland environmental disturbance response factors are generated; among them, Indicates the hydrological disturbance coefficient. This represents the atmospheric disturbance coefficient. Indicates the human interference coefficient. Indicates the biological invasion inhibition coefficient. These represent the weighting factors corresponding to the hydrological disturbance coefficient, atmospheric disturbance coefficient, anthropogenic disturbance coefficient, and biological invasion inhibition coefficient, respectively; in this application, .

[0101] The Carbon Sequestration Intelligent Assessment Module 500 is used to construct an intelligent assessment model for forest and wetland carbon sequestration, generate assessment values ​​for forest and wetland carbon sequestration, determine the functional status of forest and wetland carbon sequestration, and provide feedback on any anomalies.

[0102] Please see Figure 6 As shown, preferably, the intelligent carbon sequestration assessment module specifically includes:

[0103] The carbon sink assessment generation unit 501 is used to establish a smart assessment model for forest wetland carbon sinks. It substitutes the evaluation value of forest wetland vegetation carbon sequestration potential, the evaluation value of forest wetland water and soil carbon synergy, the response factor of forest wetland environmental disturbance, and the baseline estimated value of forest wetland carbon sink into the smart assessment model to generate the assessment value of forest wetland carbon sink.

[0104] The intelligent assessment model for forest wetland carbon sequestration is as follows: ,in, This indicates the synergistic evaluation value of water, soil, and carbon in forests and wetlands. These represent the weighting factors corresponding to the evaluation values ​​of carbon sequestration potential of forest wetlands, the evaluation values ​​of synergistic carbon and water conservation in forest wetlands, and the environmental disturbance response factors of forest wetlands, respectively.

[0105] It should be noted that the assessment value of carbon sink in forest wetlands integrates vegetation carbon sequestration (carbon sink production), water and soil synergy (carbon sink transfer and storage), disturbance correction (carbon sink constraints), and benchmark calibration (carbon sink measurement) for comprehensive analysis, making the carbon sink assessment results more in line with the actual situation.

[0106] The carbon sequestration capacity assessment unit 502 is used to determine whether the carbon sequestration capacity of forest wetlands meets the standards based on the carbon sequestration assessment value, and to generate a carbon sequestration capacity status signal; specifically:

[0107] When the carbon sink assessment value is greater than or equal to the preset carbon sink assessment value threshold, a signal indicating that the carbon sink capacity of the forest wetland meets the standard is generated. The preset carbon sink assessment value threshold is a quantitative judgment standard determined by combining the ecosystem characteristics of the composite forest wetland, the core function requirements of carbon sink, and management objectives, after actual measurement verification and data calibration.

[0108] When the carbon sequestration assessment value is less than the preset carbon sequestration assessment value threshold, a signal indicating that the carbon sequestration capacity of forest wetlands has not met the standard is generated.

[0109] The carbon sequestration anomaly feedback unit 503 is used to provide corresponding carbon sequestration anomaly feedback based on the signal that the carbon sequestration capacity has not met the standard.

[0110] Please see Figure 6 As shown, this invention is a smart monitoring and assessment method for carbon sequestration in forest wetlands, which includes the following steps:

[0111] S1. Obtain forest wetland vegetation structure characteristic data and generate forest wetland vegetation carbon sequestration potential evaluation value; among which, forest wetland vegetation structure characteristic data include canopy closure, vegetation coverage, and vertical differentiation index between the tree layer and the shrub and grass layer.

[0112] S2. Obtain carbon cycle data at the water-soil interface in forest wetlands and generate a synergistic evaluation value for water-soil carbon in forest wetlands. Among them, the carbon cycle data at the water-soil interface includes the vertical gradient change rate of soil organic carbon, the concentration of dissolved organic carbon in surface water, and the carbon burial rate in sediments.

[0113] S3. Obtain multi-source observation data of forest wetlands and generate a baseline estimate of forest wetland carbon sink; among which, the multi-source observation data includes tree layer biomass, shrub and grass layer dry weight, soil organic carbon density, sediment carbon burial amount, and surface water dissolved organic carbon storage in the forest wetland observation area.

[0114] S4. Obtain environmental disturbance data of forest wetlands and generate environmental disturbance response factors; among which, the environmental disturbance data of forest wetlands includes the frequency of extreme rainfall events and water level depth of forest wetlands, light intensity, temperature and humidity of forest wetlands, human activity intensity index of forest wetlands and invasive alien species coverage rate of forest wetlands.

[0115] S5. Construct an intelligent assessment model for forest wetland carbon sequestration, generate assessment values ​​for forest wetland carbon sequestration, determine the functional status of forest wetland carbon sequestration, and provide feedback on any anomalies.

[0116] The above description is merely an example and illustration of the structure of the present invention. Those skilled in the art can make various modifications or additions to the specific embodiments described, or use similar methods to replace them, as long as they do not deviate from the structure of the invention or exceed the scope defined in the claims, all of which should fall within the protection scope of the present invention.

Claims

1. A smart monitoring and assessment system for carbon sequestration in forest wetlands, characterized in that, include: The vegetation carbon sequestration potential evaluation module is used to acquire forest wetland vegetation structure characteristic data and generate forest wetland vegetation carbon sequestration potential evaluation values. The water and soil carbon synergy evaluation module is used to acquire carbon cycle data of the water-soil interface in forest wetlands and generate water and soil carbon synergy evaluation values ​​for forest wetlands. The carbon sink baseline estimation module is used to acquire multi-source observation data of forest wetlands and generate baseline estimation values ​​of forest wetland carbon sinks. The environmental disturbance analysis module is used to acquire environmental disturbance data of forest wetlands and generate environmental disturbance response factors; The intelligent carbon sequestration assessment module is used to build an intelligent assessment model for forest and wetland carbon sequestration, generate assessment values ​​for forest and wetland carbon sequestration, determine the functional status of forest and wetland carbon sequestration, and provide feedback on any anomalies.

2. The intelligent monitoring and assessment system for forest wetland carbon sequestration according to claim 1, characterized in that, The vegetation carbon sequestration potential evaluation module includes: The canopy closure assessment unit is used to obtain the canopy closure of forest wetlands and generate forest wetland canopy closure assessment values. The vegetation cover assessment unit is used to obtain the vegetation cover of forest wetlands and generate forest wetland vegetation cover assessment values. The vertical structure differentiation assessment unit is used to obtain the vertical differentiation index between the tree layer and the shrub and grass layer of forest wetlands and generate the vertical structure differentiation assessment value of forest wetlands. The carbon sequestration potential generation unit is used to generate a forest wetland vegetation carbon sequestration potential evaluation value through weighted processing based on the forest wetland canopy closure assessment value, forest wetland vegetation coverage assessment value, and forest wetland vertical structure differentiation assessment value.

3. The intelligent monitoring and assessment system for forest wetland carbon sequestration according to claim 2, characterized in that, The method for generating the forest wetland canopy closure assessment value is as follows: Obtain the canopy closure of the forest wetland, calculate the difference between the canopy closure and the median of the standard canopy closure range, and generate the canopy closure deviation. The ratio of the canopy closure deviation to the median of the standard canopy closure range is calculated, and the absolute value is then mapped through a nonlinear decay function to generate the forest wetland canopy closure assessment value. The method for generating the forest wetland vegetation coverage assessment value is as follows: Obtain the vegetation cover of forest wetlands, calculate the difference between it and the median value of the standard vegetation cover range, and generate the vegetation cover deviation. The forest wetland vegetation coverage assessment value is generated by calculating the ratio of the median value of the standard vegetation coverage range to the absolute value of the vegetation coverage deviation. The method for generating the forest wetland vegetation coverage assessment value is as follows: The vertical differentiation index between the tree layer and the shrub and grass layer of the forest wetland is obtained. The difference between the vertical differentiation index and the median value of the ideal structural differentiation index range is calculated to generate the vertical differentiation index deviation. The vertical differentiation index deviation is calculated as a ratio to the median of the ideal structural differentiation index range, and then normalized using the Sigmoid function to generate a vertical structural differentiation assessment value.

4. The intelligent monitoring and assessment system for forest wetland carbon sequestration according to claim 1, characterized in that, The water, soil, and carbon co-evaluation module includes: The soil carbon gradient analysis unit is used to obtain the organic carbon attenuation coefficient of forest wetland soil and generate soil carbon gradient evaluation values. The water carbon activity analysis unit is used to obtain the dissolved organic carbon concentration in the surface water of forest wetlands and generate a water carbon activity evaluation value. The sedimentary carbon sequestration analysis unit is used to obtain the amount of sedimentary carbon buried in forest wetlands and generate sedimentary carbon sequestration evaluation values. The water and soil carbon co-evaluation generation unit is used to perform dimensionality reduction and fusion of soil carbon gradient evaluation values, water carbon activity evaluation values, and sediment carbon sequestration evaluation values ​​of several sampling areas of forest wetlands using principal component analysis to generate a co-evaluation value of water and soil carbon in forest wetlands.

5. The intelligent monitoring and assessment system for forest wetland carbon sequestration according to claim 4, characterized in that, The soil carbon gradient evaluation value is generated in the following way: Obtain the organic carbon decay coefficient of forest wetland soil, calculate the difference between the decay coefficient and the decay coefficient threshold of healthy forest wetland, and generate the decay coefficient difference. The soil carbon gradient evaluation value is generated by processing the ratio of the attenuation coefficient threshold to the attenuation coefficient difference. The method for generating the water body carbon activity evaluation value is as follows: The concentration of dissolved organic carbon in the surface water of forest wetlands is obtained, and the difference between it and the median of the background concentration range of DOC in forest wetlands is calculated to generate the DOC deviation; the ratio of the DOC deviation to the median of the background concentration range of DOC is calculated to generate the degree of DOC deviation. Obtain the water temperature of forest wetlands and generate a temperature correction factor based on the Q10 model; A water body carbon activity evaluation model was established, and the DOC deviation value and water temperature correction factor were substituted into the water body carbon activity evaluation model to generate water body carbon activity evaluation value. The method for generating the evaluation value of deposited carbon sequestration is as follows: The sedimentary carbon sequestration of forest wetlands is obtained, and its ratio is calculated with the regional baseline sedimentary carbon sequestration to generate a relative sequestration intensity. A sedimentary carbon sequestration evaluation model is constructed, and the relative sequestration intensity is substituted into the sedimentary carbon sequestration evaluation model to generate a sedimentary carbon sequestration evaluation value. The method for generating the synergistic evaluation value of water, soil and carbon in forest wetlands is as follows: Soil carbon gradient evaluation values, water carbon activity evaluation values, and sediment carbon sequestration evaluation values ​​were obtained from several sampling areas of forest wetlands to form a data matrix; the data matrix was then standardized to obtain a standardized data matrix. Calculate the covariance matrix of the standardized data matrix, and solve for the eigenvalues ​​and eigenvectors of the covariance matrix through matrix operations; The variance contribution rates of the principal components are accumulated sequentially in descending order of eigenvalues, and the top k principal components with a cumulative variance contribution rate of 85% or higher are identified as effective principal components. The standardized data matrix is ​​projected onto the directions of each effective principal component to obtain the scores of each effective principal component in several sampling areas. The contribution rate of each effective principal component is used as the weight to perform weighted fusion of the scores of each effective principal component in several sampling areas to generate the water, soil and carbon synergistic evaluation value of several sampling areas. The water and soil carbon synergistic evaluation values ​​of several sampling areas were normalized to generate normalized water and soil carbon synergistic evaluation values ​​of several sampling areas. Then, the average value of these values ​​was processed to generate the water and soil carbon synergistic evaluation values ​​of forest wetlands.

6. The intelligent monitoring and assessment system for forest wetland carbon sequestration according to claim 1, characterized in that, The estimated baseline value of carbon sinks in generated forest wetlands specifically includes: Through formula Generate a baseline estimate of forest and wetland carbon sequestration. ; This indicates the tree layer biomass in the observed area. Indicates the dry weight of the shrub and grass layer in the observation area. Indicates the carbon content coefficient of the tree layer. This represents the carbon content coefficient of the shrub and grass layer. This indicates the soil organic carbon density in the observation area. This indicates the amount of carbon buried in the sediments of the observed area. This indicates the dissolved organic carbon storage in the surface water of the observation area. The term represents the ratio of the forest wetland observation area to the total forest wetland area.

7. The intelligent monitoring and assessment system for forest wetland carbon sequestration according to claim 1, characterized in that, The environmental disturbance analysis module includes: The hydrological disturbance analysis unit is used to obtain the frequency of extreme rainfall events and water level depth in forest wetlands, and to generate the hydrological disturbance coefficient of forest wetlands. The atmospheric disturbance analysis unit is used to obtain the light intensity, temperature and humidity of forest wetlands and generate the atmospheric disturbance coefficient of forest wetlands. The anthropogenic disturbance analysis unit is used to obtain the anthropogenic activity intensity index of forest wetlands and generate the anthropogenic disturbance coefficient of forest wetlands. The biological invasion disturbance analysis unit is used to obtain the invasive coverage rate of alien species in forest wetlands, calculate the ratio of the invasive coverage rate of alien species to the standard invasive coverage rate, and generate the biological invasion inhibition coefficient. The environmental disturbance response factor generation unit is used to weight the hydrological disturbance coefficient, atmospheric disturbance coefficient, anthropogenic disturbance coefficient, and biological invasion inhibition coefficient to generate forest wetland environmental disturbance response factors.

8. The intelligent monitoring and assessment system for forest wetland carbon sequestration according to claim 7, characterized in that, The method for generating the hydrological disturbance coefficient of the forest wetland is as follows: The extreme rainfall impact value is generated by calculating the ratio between the frequency of extreme rainfall events in forest wetlands and the threshold of the frequency of rainfall disturbance events that allow the ecological environment of forest wetlands. The difference between the water level depth of the forest wetland and the allowable water level depth threshold of the forest wetland ecological environment is calculated to generate the water level depth difference; the ratio between the water level depth difference and the allowable water level depth threshold of the forest wetland ecological environment is calculated to generate the water level depth influence value. The impact values ​​of extreme rainfall and water level depth are summed to generate the hydrological disturbance coefficient of forest wetlands; The atmospheric disturbance coefficient of the forest wetland is generated in the following way: The difference between the light intensity of forest wetlands and the standard light intensity of forest wetland ecological environment is calculated to generate the light intensity difference; The ratio of the light intensity difference to the standard light intensity of the forest wetland ecological environment is calculated to generate the light intensity influence value; Similarly, the influence values ​​of temperature and humidity are obtained through analysis. The influence values ​​of light intensity, temperature, and humidity are then summed to generate the atmospheric disturbance coefficient of forest wetlands. The method for generating the anthropogenic disturbance coefficient of the forest wetland is as follows: The system obtains the road density, visitor density, land use conversion area ratio, and engineering construction trace area ratio of forest wetlands. These data are then converted into lengths according to preset ratios and input into a computer. The computer processes and outputs the human activity intensity index of the forest wetlands. The ratio of the human activity intensity index of the forest wetlands to the upper limit of the ecological carrying capacity is calculated to generate the human interference coefficient.

9. The intelligent monitoring and assessment system for forest wetland carbon sequestration according to claim 1, characterized in that, The intelligent carbon sequestration assessment module includes: The carbon sink assessment generation unit is used to establish an intelligent assessment model for forest and wetland carbon sinks. It substitutes the evaluation value of the carbon sequestration potential of forest and wetland vegetation, the evaluation value of the synergistic effect of water and soil carbon in forest and wetland, the response factor of environmental disturbance in forest and wetland, and the baseline estimated value of carbon sink in forest and wetland into the intelligent assessment model to generate the carbon sink assessment value of forest and wetland. The carbon sequestration capacity assessment unit is used to determine whether the carbon sequestration capacity of forest wetlands meets the standards based on the carbon sequestration assessment value, and to generate a carbon sequestration capacity status signal; specifically: When the carbon sequestration assessment value is greater than or equal to the preset carbon sequestration assessment value threshold, a signal indicating that the carbon sequestration capacity of the forest wetland meets the standard is generated; when the carbon sequestration assessment value is less than the preset carbon sequestration assessment value threshold, a signal indicating that the carbon sequestration capacity of the forest wetland does not meet the standard is generated. The carbon sequestration anomaly feedback unit is used to provide corresponding carbon sequestration anomaly feedback based on the signal that the carbon sequestration capacity has not met the standard.

10. A method for intelligent monitoring and assessment of carbon sequestration in forest wetlands, based on the intelligent monitoring and assessment system for carbon sequestration in forest wetlands as described in claims 1-9, characterized in that, Includes the following steps: S1. Obtain forest wetland vegetation structure characteristic data and generate forest wetland vegetation carbon sequestration potential evaluation value; among which, forest wetland vegetation structure characteristic data include canopy closure, vegetation coverage, and vertical differentiation index between the tree layer and the shrub and grass layer. S2. Obtain carbon cycle data at the water-soil interface in forest wetlands and generate a synergistic evaluation value for water-soil carbon in forest wetlands. Among them, the carbon cycle data at the water-soil interface includes the vertical gradient change rate of soil organic carbon, the concentration of dissolved organic carbon in surface water, and the carbon burial rate in sediments. S3. Obtain multi-source observation data of forest wetlands and generate a baseline estimate of forest wetland carbon sink; among which, the multi-source observation data includes tree layer biomass, shrub and grass layer dry weight, soil organic carbon density, sediment carbon burial amount, and surface water dissolved organic carbon storage in the forest wetland observation area. S4. Obtain environmental disturbance data of forest wetlands and generate environmental disturbance response factors; among which, the environmental disturbance data of forest wetlands includes the frequency of extreme rainfall events and water level depth of forest wetlands, light intensity, temperature and humidity of forest wetlands, human activity intensity index of forest wetlands and invasive alien species coverage rate of forest wetlands. S5. Construct an intelligent assessment model for forest wetland carbon sequestration, generate assessment values ​​for forest wetland carbon sequestration, determine the functional status of forest wetland carbon sequestration, and provide feedback on any anomalies.

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