A remote sensing-based method for monitoring ecosystem carbon sinks

Abstract

The present invention discloses a remote sensing-based ecosystem carbon sink monitoring method, which relates to the field of ecological carbon sink monitoring. The method uses a GIS system and corrected carbon sink data. The method can divide wetlands into different types such as swamps, peatlands and wet grasslands, and calculates the carbon sink amount CW of each region by constructing a carbon sink monitoring model, and finally calculates the overall carbon sink amount CWzt of the overall wetland, and presets a carbon sink threshold T and a preliminary comparative evaluation of the overall carbon sink amount CWzt of the wetland. In addition, combined with a dynamic monitoring formula, the carbon sink change amount △CW(t) is further calculated, and a prediction evaluation is performed with the carbon sink threshold T. The spatial visualization of carbon sink capacity in different regions is realized by using GIS tools, and the seasonal changes and long-term trends of wetland carbon sinks are displayed, so that wetland managers can intuitively understand the carbon sink changes in wetlands, which is conducive to precise management and planning.

Description

Technical Field

[0001] The invention relates to the technical field of ecological carbon sink monitoring, and in particular to an ecosystem carbon sink monitoring method based on remote sensing. Background Art

[0002] Ecosystem carbon sink refers to the process by which ecosystems absorb carbon dioxide from the atmosphere through photosynthesis and store it as organic carbon. It is an important way to mitigate global climate change. Natural ecosystems such as forests, grasslands, and wetlands have significant carbon sink functions. With the advancement of carbon neutrality goals, how to accurately monitor and quantify the carbon sink capacity of ecosystems has become an important issue in climate change research and ecological environmental management. At present, traditional carbon sink monitoring mostly relies on ground sampling and laboratory analysis. Although it has high accuracy, it is difficult to implement in large-scale areas. With the continuous development of remote sensing technology, remote sensing-based carbon sink monitoring methods have become an effective means, but existing methods still need to be improved in the spatiotemporal accuracy of carbon sink estimation, long-term dynamic monitoring, and applicability to multiple ecosystem types.

[0003] At present, ecosystem carbon sink monitoring mainly relies on ground sampling and laboratory analysis. Although this method has high accuracy, it has many difficulties in implementation in large-scale areas. Ecosystems such as wetlands and forests are often widely distributed and have complex terrain. Traditional ground sampling methods are time-consuming and laborious, and it is difficult to achieve large-scale and continuous dynamic monitoring of carbon sinks. In addition, ground sampling methods rely on field operations and fixed-point collection, which easily ignores the spatial heterogeneity in different ecosystem types. This means that existing monitoring methods are difficult to capture the dynamic changes in carbon sink capacity, especially the carbon sink of wetland systems is highly affected by seasonal changes and climatic conditions. Therefore, existing technologies cannot provide timely data support for dynamic changes, affecting the timeliness of scientific decision-making and management;

[0004] The above-mentioned status quo and shortcomings are mainly due to the technical limitations and implementation difficulties of existing monitoring methods. Since traditional monitoring methods rely on the investment of manpower and equipment, especially when conducting long-term monitoring in large areas, the data accuracy is usually reduced due to uneven distribution of sampling points or data lag. At the same time, carbon sequestration capacity is affected by a variety of ecological factors such as vegetation type, soil moisture and nitrogen content, and traditional methods cannot monitor the changes in these parameters in real time. Long-term reliance on manually collected data is also prone to biased results due to human errors. These deficiencies may lead to delays in the management and optimization of wetland carbon sinks, thereby causing the degradation of wetland ecosystem functions, which in turn affects the accurate assessment of carbon sequestration capacity and ultimately weakens the effectiveness of addressing climate change. Summary of the invention

[0005] In view of the deficiencies of the prior art, the present invention provides an ecosystem carbon sink monitoring method based on remote sensing, which solves the problems mentioned in the background technology.

[0006] To achieve the above objectives, the present invention is implemented through the following technical solutions: A remote sensing-based ecosystem carbon sink monitoring method comprises the following steps:

[0007] S1. Remote sensing data of wetland conservation areas are collected in real time by remote sensing satellites and sent to a ground station. The remote sensing data are parsed in the ground station to obtain wetland carbon sink data, and the wetland carbon sink data are corrected and preprocessed to obtain corrected carbon sink data. The corrected carbon sink data are written into a relational database through a write port for data storage;

[0008] S2. Use GIS and corrected carbon sink data to divide the wetland reserve into different wetland types, and then build a carbon sink monitoring model. Extract the corrected carbon sink data in the relational database through the write port, input it into the carbon sink monitoring model, calculate and output the carbon sink amount CW of the current wetland area, and calculate the overall carbon sink amount CWzt of the entire wetland reserve through the obtained carbon sink amount CW;

[0009] S3, then pre-set the carbon sink threshold T and the obtained overall carbon sink amount CWzt for preliminary comparative evaluation, analyze the overall carbon sink capacity of the wetland, and generate carbon sink optimization and management measures based on abnormal results of the preliminary comparative evaluation, prompt the wetland manager to optimize, and obtain wetland optimization data;

[0010] S4. When the initial comparative assessment results show that the status is normal, a dynamic monitoring formula is further introduced to calculate and output the carbon sink change △CW(t), and then the carbon sink change △CW(t) and the carbon sink threshold T are predicted and evaluated. Based on the prediction and evaluation results, an adjustment mechanism is generated, and the carbon sink capacity of different regions is visualized using GIS tools;

[0011] S5. After executing the optimization and management measures, based on the overall carbon sink CWzt and combined with the wetland optimization data, a comprehensive calculation is performed to output the optimized carbon sink CWopt, and then the optimized carbon sink CWopt is compared with the carbon sink threshold T for a second evaluation and analysis of the optimization situation.

[0012] Preferably, S1 includes S11, S12 and S13;

[0013] S11. Collect remote sensing data of wetland reserves in real time through remote sensing satellites, send them to ground stations for analysis, and obtain wetland carbon sink data;

[0014] Remote sensing satellites include Landsat satellites, Sentinel satellites, Sentinel-1 synthetic aperture radar and MODIS satellites;

[0015] Wetland carbon sink data include vegetation coverage NDVI, canopy nitrogen content CCN, soil carbon density SCD, vegetation water content VWC, solar radiation SI, leaf area index LAI, soil respiration Rs and net primary productivity NPP;

[0016] The vegetation coverage NDVI is calculated by using the multispectral sensor of the Landsat satellite to obtain data in the visible and near-infrared bands and the reflectance value of the pixels in the remote sensing image. The specific algorithm formula is: In the formula, NIR represents the reflectivity of the near-infrared band, and RED represents the reflectivity of visible light;

[0017] The canopy nitrogen content CCN is obtained by inverting the canopy nitrogen content CNN through the hyperspectral imaging instrument of the Sentinel satellite;

[0018] Soil carbon density (SCD) uses the microwave technology of Sentinel-1 synthetic aperture radar to obtain the moisture and structure information of the surface soil, and combines the soil organic carbon model and wetland soil characteristics to calculate the soil carbon density through remote sensing image inversion. Synthetic aperture radar is particularly suitable for obtaining data under cloud cover and can penetrate the surface vegetation layer.

[0019] Vegetation water content VWC is obtained by analyzing the thermal radiation of vegetation detected by the thermal infrared band of vegetation collected by MODIS satellite;

[0020] Solar irradiance SI is obtained by monitoring photosynthetically active radiation through the radiation measurement device of the Landsat satellite;

[0021] The leaf area index LAI is obtained by combining the reflectance of the spectral data from the MODIS satellite with the field measurement results and analyzing the reflectance relationship between the red and near-infrared spectra;

[0022] Soil respiration Rs is inverted by combining the infrared band of the MODIS satellite and ground monitoring stations, and analyzing soil temperature and moisture;

[0023] Net primary productivity (NPP) is calculated by using a photosynthesis model of plant growth combined with NDVI data of vegetation coverage.

[0024] S12, based on the collected wetland carbon sink data, performing correction preprocessing, the correction preprocessing including geometric correction, atmospheric correction and radiation correction, to obtain corrected carbon sink data;

[0025] Geometric correction corrects the geometric distortion of remote sensing images to a standard map projection coordinate system; geometric distortion is caused by satellite orbits, terrain undulations and earth curvature. Geometric correction uses geographic registration technology to match pixels in remote sensing images with geographic coordinates. Registration is completed by selecting control points to ensure that remote sensing data from different times and sources are aligned in space, so that they can be superimposed, compared and synthesized in subsequent analysis;

[0026] Atmospheric correction eliminates the influence of water vapor, aerosol, dust, etc. in the atmosphere on remote sensing data through the correction method of radiation transfer model;

[0027] Radiation correction is performed by calibrating with known radiation sources and ground measurement data, comparing the sensitivity differences of sensors, and adjusting the response curve of each sensor to ensure the accuracy of its radiation value;

[0028] S13, constructing a relational database in the ground station server and setting a write port and a write port of the relational database, and writing the obtained corrected carbon sink data into the relational database through the write port.

[0029] Preferably, S2 includes S21, S22 and S23;

[0030] S21. Use GIS equipment to collect GIS data of the wetland reserve in real time, and then divide the wetland reserve into swamps, peatlands and wet grasslands based on the GIS data and the corrected carbon sink data;

[0031] GIS data include the wetland’s geographic boundaries, topography, terrain area, and geological structure;

[0032] The marshland area was identified by analyzing the vegetation cover NDVI and vegetation water content VWC combined with topographic data;

[0033] Peatlands are identified through GIS data soil carbon density SCD data;

[0034] Wet grassland Wet grassland areas were identified through vegetation coverage NDVI and vegetation water content VWC in remote sensing data;

[0035] S22, after the wetland protection area is divided, a carbon sink monitoring model is constructed, and the corrected carbon sink data is extracted through the write port of the relational database and input into the carbon sink monitoring model to calculate and output the carbon sink amount CW of the current wetland area;

[0036] The carbon sink volume CW is calculated and output by the following carbon sink monitoring model;

[0037]

[0038] In the formula, CW irepresents the carbon sink of the i-th type wetland, t1 represents the upper limit of time, t2 represents the lower limit of time, and represents the time period from t1 to t2. The efficiency of photosynthesis. It represents the rate of soil carbon release, a1, a2 and a3 represent the preset weight values ​​of net primary productivity NPP, photosynthesis efficiency and soil carbon release rate respectively, and a1+a2+a3=1, and its specific value is set by the user, and dt represents the differential variable of time t.

[0039] Preferably, S23, by calculating the carbon sink CW output for different types of wetlands, and then obtaining the wetland area A of different types from GIS data i , calculate and output the overall carbon sink CWzt of the entire wetland reserve;

[0040] The overall carbon sink CWzt is calculated using the following algorithm formula:

[0041]

[0042] Where n represents the total number of wetland types, A i Represents the area of ​​the i-th type wetland.

[0043] Preferably, S3 includes S31 and S32;

[0044] S31. Based on the average carbon sink energy of the historical carbon sink monitoring data of the current wetland reserve, a preset carbon sink threshold T is made, and then a preliminary comparative assessment is made with the overall carbon sink volume CWzt to analyze the current carbon sink capacity of the wetland. The specific assessment contents are as follows;

[0045] When the overall carbon sink amount CWzt ≥ the carbon sink threshold T, it means that the carbon sink capacity of the wetland is normal and meets the expected effect, and no management intervention is required at this time;

[0046] When the overall carbon sink amount CWzt is less than the carbon sink threshold T, it means that the carbon sink capacity of the wetland is abnormal and does not meet the expected effect. At this time, an adjustment management warning message is sent to the wetland manager to adjust and optimize the wetland.

[0047] Preferably, S32, generating corresponding optimization measures based on the preliminary comparative evaluation, when the preliminary comparative evaluation shows that the carbon sequestration capacity of the wetland is abnormal, and when the wetland manager receives the adjustment management warning information, the wetland manager implements the optimization measures for the wetland protection area, and the optimization measures include vegetation restoration, hydrological regulation and nitrogen management;

[0048] Vegetation restoration is achieved by enhancing vegetation cover, vegetation coverage NDVI and leaf area index LAI;

[0049] Hydrological regulation adjusts the moisture content of wetlands by diverting or draining water to optimize the vegetation water content (VWC);

[0050] Nitrogen management increases the canopy nitrogen content (CCN) in vegetation through fertilization or improved management practices;

[0051] After the administrator optimizes and adjusts, the optimized wetland carbon sink data is collected again, and combined with the wetland carbon sink data before optimization, the changes are analyzed to obtain wetland optimization data. The wetland optimization data includes leaf area index change △LAI, vegetation water content change △VWC and soil respiration change △Rs;

[0052] Leaf area index change △LAI By comparing the leaf area index LAI before and after optimization, the change is calculated. The specific algorithm formula is: △LAI=LAI t2 -LAI t1 , where LAI t2 Represents the leaf area index at time t2 after optimization, LAI t1 represents the leaf area index at time t1 before optimization;

[0053] The change in vegetation moisture content △VWC is calculated by comparing the vegetation moisture content VWC before and after optimization. The specific algorithm formula is: △VWC=VWC t2 -VWC t1 , where VWC t2 Represents the vegetation moisture content at time t2 after optimization, VWC t1 represents the vegetation moisture content at time t1 before optimization;

[0054] The change in soil respiration △Rs is calculated by comparing the soil respiration Rs before and after optimization. The specific algorithm formula is: △Rs=Rs t2 -Rs t1 , where Rs t2 Represents the optimized vegetation moisture content at time t2, Rs t1 Represents the vegetation moisture content at time t1 before optimization.

[0055] Preferably, S4 includes S41, S42 and S43;

[0056] S41. When the preliminary comparative assessment result is normal, a dynamic monitoring formula is further introduced to calculate the output carbon sink change △CW(t) to dynamically monitor the change of carbon sink over time and seasons;

[0057] The carbon sink change △CW(t) is calculated by the following algorithm formula;

[0058]

[0059] Where d represents the differential variable, Fhuman(t) represents the impact factor of human activities, which is estimated based on remote sensing data and human activity records;

[0060] S42, predicting and evaluating the obtained carbon sink change △CW(t) and the carbon sink threshold T, and analyzing the wetland carbon sink change in the wetland reserve at future times based on the evaluation results. The specific evaluation contents are as follows;

[0061] When the carbon sink change △CW(t) ≥ the carbon sink threshold T, it means that the predicted wetland carbon sink change at time t is normal and no adjustment is required to continue monitoring;

[0062] When the carbon sink change △CW(t) is less than the carbon sink threshold T, it means that the wetland carbon sink change at time t is predicted to be abnormal. At this time, adjustment management warning information is sent to the wetland manager for secondary adjustment and optimization.

[0063] Preferably, S43, based on the obtained corrected carbon sink data combined with GIS data, a carbon sink spatial distribution map is generated using GIS tools, and then a carbon sink change trend map is generated through GIS tools based on the carbon sink change △CW(t), showing the seasonal and long-term changes in carbon sinks in wetland reserves.

[0064] Preferably, S5 includes S51 and S52;

[0065] S51. After each adjustment and optimization, based on the overall carbon sink CWzt, the optimized carbon sink CWopt is output through comprehensive calculation in combination with the wetland optimization data, and the wetland carbon sink is evaluated again;

[0066] The optimized carbon sink CWopt is output through the following algorithm formula;

[0067] CWopt=CWzt+b1·△LAI+b2·△VWC-b3·△Rs;

[0068] Wherein, b1, b2 and b3 represent the preset weight values ​​of leaf area index change △LAI, vegetation water content change △VWC and soil respiration change △Rs, respectively, and b1+b2+b3=1, and the specific values ​​are set by the user.

[0069] Preferably, S52, based on the obtained optimized carbon sink amount CWopt and the carbon sink threshold T, a secondary comparative evaluation is performed to analyze the carbon sink situation of the optimized wetland, and the specific evaluation content is as follows;

[0070] When the optimized carbon sink amount CWopt ≥ the carbon sink threshold T, it means that the optimized wetland carbon sink is normal, and the optimization adjustment measures are stopped and monitoring is continued;

[0071] When the optimized carbon sink amount CWopt is less than the carbon sink threshold T, it means that the wetland carbon sink is abnormal after optimization. At this time, the current optimization adjustment measures should continue to be implemented until the wetland carbon sink returns to normal.

[0072] Beneficial Effects

[0073] The present invention provides a remote sensing-based ecosystem carbon sink monitoring method, which has the following beneficial effects:

[0074] (1) This method uses remote sensing satellites to collect remote sensing data of wetland reserves in real time, such as vegetation coverage NDVI, canopy nitrogen content CCN, and soil carbon density SCD, and then uses ground stations for analysis and correction preprocessing. This real-time data collection and correction preprocessing process greatly improves the timeliness and data accuracy of wetland carbon sink monitoring. Compared with traditional ground monitoring methods, remote sensing technology can obtain high-resolution data over a wide area, and ensure data consistency and accuracy through geometric correction, atmospheric correction, and radiation correction, providing reliable data support for subsequent carbon sink calculation and evaluation.

[0075] (2) This method uses the GIS system and corrected carbon sink data. This method can divide wetlands into different types such as swamps, peatlands and wet grasslands, and calculate the carbon sink CW of each region by constructing a carbon sink monitoring model. Finally, the overall carbon sink CWzt of the entire wetland is calculated, and the carbon sink threshold T is preset for preliminary comparative evaluation of the overall carbon sink CWzt of the wetland. In addition, combined with the dynamic monitoring formula, the carbon sink change △CW(t) is further calculated and predicted and evaluated with the carbon sink threshold T. The spatial visualization of carbon sink capacity in different regions is achieved by using GIS tools, and the seasonal changes and long-term trends of wetland carbon sinks are displayed, so that wetland managers can intuitively understand the carbon sink changes in wetlands, which is conducive to precise management and planning.

[0076] (3) This method can generate optimization and management measures when carbon sequestration capacity is insufficient, including vegetation restoration, hydrological regulation and nitrogen management, and conduct a secondary comparative evaluation of the optimized data. By calculating the leaf area index change △LAI, the vegetation water content change △VWC and the soil respiration change △Rs, the optimized carbon sink volume CWopt is generated and compared with the carbon sink threshold T again. This post-optimization continuous monitoring and feedback mechanism ensures timely adjustments when the wetland carbon sink capacity is abnormal, and gradually improves the wetland carbon sink status through management measures, thereby improving overall management efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0077] Figure 1 The present invention is a schematic diagram of the steps of a remote sensing-based ecosystem carbon sink monitoring method. DETAILED DESCRIPTION

[0078] 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.

[0079] Example 1

[0080] The present invention provides a remote sensing-based ecosystem carbon sink monitoring method, please refer to Figure 1 , including the following steps:

[0081] S1. Remote sensing data of wetland conservation areas are collected in real time by remote sensing satellites and sent to a ground station. The remote sensing data are parsed in the ground station to obtain wetland carbon sink data, and the wetland carbon sink data are corrected and preprocessed to obtain corrected carbon sink data. The corrected carbon sink data are written into a relational database through a write port for data storage;

[0082] S2. Use GIS and corrected carbon sink data to divide the wetland reserve into different wetland types, and then build a carbon sink monitoring model. Extract the corrected carbon sink data in the relational database through the write port, input it into the carbon sink monitoring model, calculate and output the carbon sink amount CW of the current wetland area, and calculate the overall carbon sink amount CWzt of the entire wetland reserve through the obtained carbon sink amount CW;

[0083] S3, then pre-set the carbon sink threshold T and the obtained overall carbon sink amount CWzt for preliminary comparative evaluation, analyze the overall carbon sink capacity of the wetland, and generate carbon sink optimization and management measures based on abnormal results of the preliminary comparative evaluation, prompt the wetland manager to optimize, and obtain wetland optimization data;

[0084] S4. When the initial comparative assessment results show that the status is normal, a dynamic monitoring formula is further introduced to calculate and output the carbon sink change △CW(t), and then the carbon sink change △CW(t) and the carbon sink threshold T are predicted and evaluated. Based on the prediction and evaluation results, an adjustment mechanism is generated, and the carbon sink capacity of different regions is visualized using GIS tools;

[0085] S5. After executing the optimization and management measures, based on the overall carbon sink CWzt and combined with the wetland optimization data, a comprehensive calculation is performed to output the optimized carbon sink CWopt, and then the optimized carbon sink CWopt is compared with the carbon sink threshold T for a second evaluation and analysis of the optimization situation.

[0086] In this embodiment, in step S1 of the method, remote sensing satellites are used to collect wetland data in real time, and the data is analyzed and corrected by the ground station to ensure the accuracy of the data, and the corrected carbon sink data is stored in a relational database. Step S2 divides the wetland types through the GIS system, and uses the carbon sink monitoring model to calculate the carbon sink amount CW in each area, and finally obtains the overall wetland carbon sink amount CWzt, which provides a basis for subsequent evaluation. Step S3 sets the carbon sink threshold T and compares it with the wetland carbon sink amount CWzt. If it is lower than the threshold, an optimized management measure is generated and the manager is prompted to adjust. Step S4 introduces a dynamic monitoring formula to calculate the carbon sink change △CW(t), and combines GIS tools to generate a carbon sink distribution map and trend map to show the spatiotemporal changes of wetland carbon sinks and provide visualization support. Step S5 conducts a secondary evaluation of the carbon sink amount CWopt after the optimization measures are implemented to ensure that the management effect continues to improve. Compared with the traditional ground sampling method, the system realizes large-scale, real-time monitoring through remote sensing technology, and combines dynamic evaluation and optimization mechanisms to improve the timeliness and accuracy of carbon sink monitoring. Through visualization tools, this method provides intuitive decision-making support for wetland managers, ultimately achieving the goal of improving wetland carbon sequestration capacity and optimizing management effects.

[0087] Example 2

[0088] This embodiment is explained in Example 1, please refer to Figure 1 , specifically: S1 includes S11, S12 and S13;

[0089] S11. Collect remote sensing data of wetland reserves in real time through remote sensing satellites, send them to ground stations for analysis, and obtain wetland carbon sink data;

[0090] Remote sensing satellites include Landsat satellites, Sentinel satellites, Sentinel-1 synthetic aperture radar and MODIS satellites;

[0091] Wetland carbon sink data include vegetation coverage NDVI, canopy nitrogen content CCN, soil carbon density SCD, vegetation water content VWC, solar radiation SI, leaf area index LAI, soil respiration Rs and net primary productivity NPP;

[0092] The vegetation coverage NDVI is calculated by using the multispectral sensor of the Landsat satellite to obtain data in the visible and near-infrared bands and the reflectance value of the pixels in the remote sensing image. The specific algorithm formula is: In the formula, NIR represents the reflectivity of the near-infrared band, and RED represents the reflectivity of visible light;

[0093] The canopy nitrogen content CCN is obtained by inverting the canopy nitrogen content CNN through the hyperspectral imaging instrument of the Sentinel satellite;

[0094] Soil carbon density (SCD) uses the microwave technology of Sentinel-1 synthetic aperture radar to obtain the moisture and structure information of the surface soil, and combines the soil organic carbon model and wetland soil characteristics to calculate the soil carbon density through remote sensing image inversion. Synthetic aperture radar is particularly suitable for obtaining data under cloud cover and can penetrate the surface vegetation layer.

[0095] Vegetation water content VWC is obtained by analyzing the thermal radiation of vegetation detected by the thermal infrared band of vegetation collected by MODIS satellite;

[0096] Solar irradiance SI is obtained by monitoring photosynthetically active radiation through the radiation measurement device of the Landsat satellite;

[0097] The leaf area index LAI is obtained by combining the reflectance of the spectral data from the MODIS satellite with the field measurement results and analyzing the reflectance relationship between the red and near-infrared spectra;

[0098] Soil respiration Rs is inverted by combining the infrared band of the MODIS satellite and ground monitoring stations, and analyzing soil temperature and moisture;

[0099] Net primary productivity (NPP) is calculated by using a photosynthesis model of plant growth combined with NDVI data of vegetation coverage.

[0100] S12, based on the collected wetland carbon sink data, performing correction preprocessing, the correction preprocessing including geometric correction, atmospheric correction and radiation correction, to obtain corrected carbon sink data;

[0101] Geometric correction corrects the geometric distortion of remote sensing images to a standard map projection coordinate system; geometric distortion is caused by satellite orbits, terrain undulations and earth curvature. Geometric correction uses geographic registration technology to match pixels in remote sensing images with geographic coordinates. Registration is completed by selecting control points to ensure that remote sensing data from different times and sources are aligned in space, so that they can be superimposed, compared and synthesized in subsequent analysis;

[0102] Atmospheric correction eliminates the influence of water vapor, aerosol, dust, etc. in the atmosphere on remote sensing data through the correction method of radiation transfer model;

[0103] Radiation correction is performed by calibrating with known radiation sources and ground measurement data, comparing the sensitivity differences of sensors, and adjusting the response curve of each sensor to ensure the accuracy of its radiation value;

[0104] S13, constructing a relational database in the ground station server and setting a write port and a write port of the relational database, and writing the obtained corrected carbon sink data into the relational database through the write port.

[0105] In this embodiment, the method systematically completes the collection, correction and storage of wetland carbon sink data through three steps S11, S12 and S13, ensuring the accuracy, consistency and availability of the data. In step S11, remote sensing data of the wetland protection area are collected using a variety of remote sensing satellites and sent to the ground station, where the remote sensing data is parsed to obtain wetland carbon sink data. These data cover the core elements in the wetland carbon sink process. Subsequently, in S12, the system performs geometric correction, atmospheric correction and radiation correction on the collected data, eliminating errors and distortions in the remote sensing data, and ensuring that the data can accurately reflect the actual situation of the wetland carbon sink. Finally, through S13, the corrected carbon sink data is stored in the relational database of the ground station server, and standardized management and storage of the data are achieved through the write port and the write port, which is convenient for subsequent calls.

[0106] Example 3

[0107] This embodiment is explained in Example 2. Please refer to Figure 1 , specifically: S2 includes S21, S22 and S23;

[0108] S21. Use GIS equipment to collect GIS data of the wetland reserve in real time, and then divide the wetland reserve into swamps, peatlands and wet grasslands based on the GIS data and the corrected carbon sink data;

[0109] GIS data include the wetland’s geographic boundaries, topography, terrain area, and geological structure;

[0110] The marshland area was identified by analyzing the vegetation cover NDVI and vegetation water content VWC combined with topographic data;

[0111] Peatlands are identified through GIS data soil carbon density SCD data;

[0112] Wet grassland Wet grassland areas were identified through vegetation coverage NDVI and vegetation water content VWC in remote sensing data;

[0113] S22, after the wetland protection area is divided, a carbon sink monitoring model is constructed, and the corrected carbon sink data is extracted through the write port of the relational database and input into the carbon sink monitoring model to calculate and output the carbon sink amount CW of the current wetland area;

[0114] The carbon sink volume CW is calculated and output by the following carbon sink monitoring model;

[0115]

[0116] In the formula, CW irepresents the carbon sink of the i-th type wetland, t1 represents the upper limit of time, t2 represents the lower limit of time, and represents the time period from t1 to t2. The efficiency of photosynthesis. It represents the rate of soil carbon release, a1, a2 and a3 represent the preset weight values ​​of net primary productivity NPP, photosynthesis efficiency and soil carbon release rate respectively, and a1+a2+a3=1, and its specific value is set by the user, and dt represents the differential variable of time t.

[0117] S23. Calculate the carbon sink CW of different types of wetlands and then obtain the area A of different types of wetlands from GIS data. i , calculate and output the overall carbon sink CWzt of the entire wetland reserve;

[0118] The overall carbon sink CWzt is calculated using the following algorithm formula:

[0119]

[0120] Where n represents the total number of wetland types, A i Represents the area of ​​the i-th type wetland.

[0121] In this embodiment, the method uses GIS technology combined with carbon sink data through three steps S21, S22 and S23 to accurately divide wetland types and calculate wetland carbon sinks. In S21, GIS equipment is used to collect data such as the geographical boundaries and terrain area of ​​the wetland in real time, and the wetland protection area is divided into different types such as swamps, peatlands and wet grasslands in combination with the corrected carbon sink data. By analyzing the vegetation coverage NDVI, vegetation moisture content VWC and soil carbon density SCD, the regional distribution of various types of wetlands can be accurately identified. In step S22, a carbon sink monitoring model is constructed, the corrected carbon sink data is input into the model, and the carbon sink CW of each wetland area is calculated, thereby realizing a quantitative assessment of the carbon sink capacity of the wetland. Step S23 obtains the area of ​​different types of wetlands through GIS data, combines it with the carbon sink CW, and further calculates the overall carbon sink CWzt of the entire wetland protection area. Compared with traditional wetland carbon sink assessment methods, this method significantly improves the accuracy and efficiency of wetland classification and carbon sink calculation through the combination of GIS and remote sensing data. First, this method can collect and process large-scale wetland data in real time, no longer relying on manual surveys, and avoiding the problem of insufficient spatial coverage during ground monitoring. Second, based on the carbon sink monitoring model, the carbon sink capacity of different wetland types can be quickly and accurately evaluated.

[0122] Example 4

[0123] This embodiment is explained in Example 3, please refer to Figure 1, specifically: S3 includes S31 and S32;

[0124] S31. Based on the average carbon sink energy of the historical carbon sink monitoring data of the current wetland reserve, a preset carbon sink threshold T is made, and then a preliminary comparative assessment is made with the overall carbon sink volume CWzt to analyze the current carbon sink capacity of the wetland. The specific assessment contents are as follows;

[0125] When the overall carbon sink amount CWzt ≥ the carbon sink threshold T, it means that the carbon sink capacity of the wetland is normal and meets the expected effect, and no management intervention is required at this time;

[0126] When the overall carbon sink amount CWzt is less than the carbon sink threshold T, it means that the carbon sink capacity of the wetland is abnormal and does not meet the expected effect. At this time, an adjustment management warning message is sent to the wetland manager to adjust and optimize the wetland.

[0127] S32. Generate corresponding optimization measures based on the preliminary comparative evaluation. When the preliminary comparative evaluation shows that the carbon sequestration capacity of the wetland is abnormal, and when the wetland manager receives the early warning information of the adjustment management, the wetland manager implements the optimization measures for the wetland protection area. The optimization measures include vegetation restoration, hydrological regulation and nitrogen management.

[0128] Vegetation restoration is achieved by enhancing vegetation cover, vegetation coverage NDVI and leaf area index LAI;

[0129] Hydrological regulation adjusts the moisture content of wetlands by diverting or draining water to optimize the vegetation water content (VWC);

[0130] Nitrogen management increases the canopy nitrogen content (CCN) in vegetation through fertilization or improved management practices;

[0131] After the administrator optimizes and adjusts, the optimized wetland carbon sink data is collected again, and combined with the wetland carbon sink data before optimization, the changes are analyzed to obtain wetland optimization data. The wetland optimization data includes leaf area index change △LAI, vegetation water content change △VWC and soil respiration change △Rs;

[0132] Leaf area index change △LAI By comparing the leaf area index LAI before and after optimization, the change is calculated. The specific algorithm formula is: △LAI=LAI t2 -LAI t1 , where LAI t2 Represents the leaf area index at time t2 after optimization, LAI t1 represents the leaf area index at time t1 before optimization;

[0133] The change in vegetation moisture content △VWC is calculated by comparing the vegetation moisture content VWC before and after optimization. The specific algorithm formula is: △VWC=VWCt2 -VWC t1 , where VWC t2 Represents the vegetation moisture content at time t2 after optimization, VWC t1 represents the vegetation moisture content at time t1 before optimization;

[0134] The change in soil respiration △Rs is calculated by comparing the soil respiration Rs before and after optimization. The specific algorithm formula is: △Rs=Rs t2 -Rs t1 , where Rs t2 Represents the optimized vegetation moisture content at time t2, Rs t1 Represents the vegetation moisture content at time t1 before optimization.

[0135] In this embodiment, the method realizes the dynamic evaluation and optimization management of wetland carbon sink capacity through two steps S31 and S32. In step S31, the carbon sink threshold T is set based on the historical carbon sink data of the wetland protection area, and a preliminary comparative evaluation is performed with the current overall carbon sink CWzt of the wetland. When the overall carbon sink CWzt is normal, no management intervention is required; when the overall carbon sink CWzt is lower than the carbon sink threshold T, the system automatically sends an early warning to the wetland manager, prompting the need for management optimization. Step S32 improves the carbon sink capacity of the wetland by generating specific optimization measures, and collects optimized wetland optimization data to evaluate the management effect. Through the preset threshold T and real-time comparison mechanism, the method can timely detect wetland carbon sink anomalies and generate targeted optimization measures, greatly improving the initiative and response speed of management. In addition, after optimization, the system performs quantitative evaluation through multiple ecological parameters to ensure that the effect of management adjustment can be tracked and verified. This dynamic evaluation and feedback mechanism not only improves the efficiency of wetland carbon sink management, but also ensures the long-term effectiveness of optimization measures, and ultimately achieves continuous improvement and enhancement of the carbon sink capacity of the wetland ecosystem.

[0136] Example 5

[0137] This embodiment is explained in Example 4. Please refer to Figure 1 , specifically: S4 includes S41, S42 and S43;

[0138] S41. When the preliminary comparative assessment result is normal, a dynamic monitoring formula is further introduced to calculate the output carbon sink change △CW(t) to dynamically monitor the change of carbon sink over time and seasons;

[0139] The carbon sink change △CW(t) is calculated by the following algorithm formula;

[0140]

[0141] Where d represents the differential variable, Fhuman(t) represents the impact factor of human activities, which is estimated based on remote sensing data and human activity records;

[0142] S42, predicting and evaluating the obtained carbon sink change △CW(t) and the carbon sink threshold T, and analyzing the wetland carbon sink change in the wetland reserve at future times based on the evaluation results. The specific evaluation contents are as follows;

[0143] When the carbon sink change △CW(t) ≥ the carbon sink threshold T, it means that the predicted wetland carbon sink change at time t is normal and no adjustment is required to continue monitoring;

[0144] When the carbon sink change △CW(t) is less than the carbon sink threshold T, it means that the wetland carbon sink change at time t is predicted to be abnormal. At this time, adjustment management warning information is sent to the wetland manager for secondary adjustment and optimization.

[0145] S43. Based on the corrected carbon sink data obtained and combined with GIS data, GIS tools are used to generate a carbon sink spatial distribution map. Based on the carbon sink change △CW(t), a carbon sink change trend map is generated through GIS tools to show the seasonal and long-term changes in carbon sinks in wetland reserves.

[0146] In this embodiment, the method further introduces dynamic monitoring and predictive analysis through the three steps of S41, S42 and S43, which significantly improves the continuous tracking and spatial display effect of wetland carbon sink capacity. In step S41, the carbon sink change △CW(t) is calculated by the dynamic monitoring formula, and the changes of wetland carbon sink over time and season are monitored in real time. At the same time, the influencing factors of human activities are considered to make carbon sink monitoring more refined. Step S42 predicts and evaluates the carbon sink change △CW(t) and the carbon sink threshold T to help analyze the future trend of wetland carbon sink changes. When the predicted value is lower than the threshold, the system automatically generates a management warning, prompting the need for re-optimization to ensure the stability of carbon sink capacity. Step S43 combines the corrected carbon sink data and GIS data to generate a carbon sink spatial distribution map, and generates a trend map through GIS tools to show the seasonal and long-term changes of wetland carbon sinks and provide visualization support. Compared with traditional static monitoring methods, this method has achieved significant technical improvements. First, the introduction of dynamic monitoring formulas and predictive evaluation models has enabled wetland carbon sink monitoring to shift from static to dynamic, so that carbon sink changes can be grasped in real time and future development trends can be predicted. Secondly, the use of GIS tools to generate carbon sink distribution maps and trend maps makes wetland carbon sink management more intuitive and visual, improving the scientificity and timeliness of decision-making. This improvement has greatly improved the monitoring efficiency and accuracy of wetland carbon sinks, ensured the long-term effectiveness of management adjustments, and ultimately achieved a steady improvement in wetland carbon sink capacity.

[0147] Example 6

[0148] This embodiment is explained in Example 5. Please refer to Figure 1 , specifically: S5 includes S51 and S52;

[0149] S51. After each adjustment and optimization, based on the overall carbon sink CWzt, the optimized carbon sink CWopt is output through comprehensive calculation in combination with the wetland optimization data, and the wetland carbon sink is evaluated again;

[0150] The optimized carbon sink CWopt is output through the following algorithm formula;

[0151] CWopt=CWzt+b1·△LAI+b2·△VWC-b3·△Rs;

[0152] Wherein, b1, b2 and b3 represent the preset weight values ​​of leaf area index change △LAI, vegetation water content change △VWC and soil respiration change △Rs, respectively, and b1+b2+b3=1, and the specific values ​​are set by the user.

[0153] S52, based on the obtained optimized carbon sink amount CWopt and the carbon sink threshold T, a secondary comparative evaluation is performed to analyze the carbon sink of the optimized wetland. The specific evaluation contents are as follows;

[0154] When the optimized carbon sink amount CWopt ≥ the carbon sink threshold T, it means that the optimized wetland carbon sink is normal, and the optimization adjustment measures are stopped and monitoring is continued;

[0155] When the optimized carbon sink amount CWopt is less than the carbon sink threshold T, it means that the wetland carbon sink is abnormal after optimization. At this time, the current optimization adjustment measures should continue to be implemented until the wetland carbon sink returns to normal.

[0156] In this embodiment, the method realizes the continuous evaluation and improvement of wetland carbon sink optimization measures through two steps S51 and S52. In step S51, after each management adjustment and optimization, the optimized carbon sink CWopt is obtained by comprehensively calculating the overall carbon sink CWzt and combining the wetland optimization data. Through multiple optimizations, gradual adjustments are made to ensure that the wetland carbon sink capacity is steadily improved. In step S52, the optimized carbon sink CWopt is compared and evaluated with the carbon sink threshold T for a second time to confirm whether the optimization has achieved the expected effect. If the optimized carbon sink CWopt reaches or exceeds the carbon sink threshold T, no further intervention is required; if it is lower than the carbon sink threshold T, the optimization adjustment is continued to ensure that the wetland carbon sink capacity reaches the ideal level. Compared with traditional technologies, this method has achieved significant improvements in continuous optimization and feedback mechanisms. Through multiple rounds of optimization calculations and evaluations, combined with real-time data on carbon sink changes, it is ensured that the effects of management measures are fed back in a timely manner, and scientific evaluation is carried out through quantifiable carbon sink data. This mechanism not only improves the accuracy and flexibility of wetland carbon sink management, but also ensures the long-term effectiveness of optimization measures, ultimately achieving the continuous improvement of the carbon sink capacity of wetland ecosystems and enhancing adaptability to environmental changes and management efficiency.

[0157] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and alterations may be made to the embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A remote sensing-based ecosystem carbon sink monitoring method, characterized in that: The following steps are involved: S1. Remote sensing data of the wetland protection area is collected in real time by remote sensing satellites and sent to a ground station. The remote sensing data is parsed in the ground station to obtain wetland carbon sink data, and the wetland carbon sink data is corrected and preprocessed to obtain corrected carbon sink data. The corrected carbon sink data is written into a relational database through a write port for data storage; Said S1 includes S11, S12 and S13; S11. Collect remote sensing data of wetland reserves in real time through remote sensing satellites, send them to ground stations for analysis, and obtain wetland carbon sink data; The remote sensing satellites include Landsat satellites, Sentinel satellites, Sentinel-1 synthetic aperture radar and MODIS satellites; The wetland carbon sink data include vegetation coverage NDVI, canopy nitrogen content CCN, soil carbon density SCD, vegetation water content VWC, solar radiation SI, leaf area index LAI, soil respiration Rs and net primary productivity NPP; The vegetation coverage NDVI is calculated by using the multispectral sensor of the Landsat satellite to obtain data in the visible light and near-infrared bands and the reflectance value of the pixels in the remote sensing image. The specific algorithm formula is: In the formula, NIR represents the reflectivity of the near-infrared band, and RED represents the reflectivity of visible light; The canopy nitrogen content CCN is obtained by inverting the canopy nitrogen content CNN through the hyperspectral imaging instrument of the Sentinel satellite; The soil carbon density (SCD) is obtained by using the microwave technology of Sentinel-1 synthetic aperture radar to obtain the moisture and structure information of the surface soil, and the soil carbon density is calculated by remote sensing image inversion in combination with the soil organic carbon model and wetland soil characteristics; The vegetation water content VWC is obtained by analyzing the thermal radiation of vegetation detected by the thermal infrared band of vegetation collected by the MODIS satellite; The solar irradiance SI is obtained by monitoring photosynthetically active radiation through a radiation measurement device of a Landsat satellite; The leaf area index LAI is obtained by combining the reflectance of the spectral data of the MODIS satellite with the field measurement results and analyzing the reflectance relationship between the red light and near-infrared spectra; The soil respiration Rs is inverted by combining the infrared band of the MODIS satellite and the ground monitoring station, and analyzing the soil temperature and humidity; The net primary productivity (NPP) is calculated by using a photosynthesis model of plant growth combined with NDVI data of vegetation coverage. S12, performing correction preprocessing based on the collected wetland carbon sink data, wherein the correction preprocessing includes geometric correction, atmospheric correction and radiation correction, to obtain corrected carbon sink data; The geometric correction corrects the geometric distortion of the remote sensing image into a standard map projection coordinate system; the geometric correction uses geographic registration technology to match the pixels in the remote sensing image with the geographic coordinates, and completes the registration by selecting control points; The atmospheric correction eliminates the influence of water vapor, aerosol and dust in the atmosphere on remote sensing data by means of correction of the radiation transfer model; The radiation correction is calibrated by using known radiation sources and ground measurement data; S13, constructing a relational database in the ground station server and setting a write port and a write port of the relational database, and writing the obtained corrected carbon sink data into the relational database through the write port; S2. Use GIS and corrected carbon sink data to divide the wetland reserve into different wetland types, and then build a carbon sink monitoring model. Extract the corrected carbon sink data in the relational database through the write port, input it into the carbon sink monitoring model, calculate and output the carbon sink amount CW of the current wetland area, and calculate the overall carbon sink amount CWzt of the entire wetland reserve through the obtained carbon sink amount CW; The S2 includes S21, S22 and S23; S21. Use GIS equipment to collect GIS data of the wetland reserve in real time, and then divide the wetland reserve into swamps, peatlands and wet grasslands based on the GIS data and the corrected carbon sink data; The GIS data includes the geographic boundaries, topography, terrain area and geological structure of the wetland; The swamp area is identified by analyzing the vegetation coverage NDVI and the vegetation water content VWC combined with terrain data; The peatland is identified by using GIS data soil carbon density SCD data; The wet grassland area is identified by using the vegetation coverage NDVI and vegetation water content VWC in remote sensing data; S22, after the wetland protection area is divided, a carbon sink monitoring model is constructed, and the corrected carbon sink data is extracted through the write port of the relational database and input into the carbon sink monitoring model to calculate and output the carbon sink amount CW of the current wetland area; The carbon sink volume CW is calculated and output by the following carbon sink monitoring model; Where CW i represents the carbon sink of the i-th type wetland, t1 represents the upper limit of time, t2 represents the lower limit of time, and represents the time period from t1 to t2. The efficiency of photosynthesis. represents the rate of soil carbon release, a1, a2 and a3 represent the preset weight values ​​of net primary productivity NPP, photosynthesis efficiency and soil carbon release rate respectively, and a1+a2+a3=1, and its specific value is set by the user, and dt represents the differential variable of time t; S3, then pre-set the carbon sink threshold T and the obtained overall carbon sink amount CWzt for preliminary comparative evaluation, analyze the overall carbon sink capacity of the wetland, and generate carbon sink optimization and management measures based on abnormal results of the preliminary comparative evaluation, prompt the wetland manager to optimize, and obtain wetland optimization data; S4. When the initial comparative assessment results show that the status is normal, a dynamic monitoring formula is further introduced to calculate and output the carbon sink change △CW(t), and then the carbon sink change △CW(t) and the carbon sink threshold T are predicted and evaluated. Based on the prediction and evaluation results, an adjustment mechanism is generated, and the carbon sink capacity of different regions is visualized using GIS tools; S5. After implementing the optimization and management measures, based on the overall carbon sink CWzt, combined with the wetland optimization data, a comprehensive calculation is performed to output the optimized carbon sink CWopt, and then the optimized carbon sink CWopt is compared with the carbon sink threshold T for a second evaluation and analysis of the optimization situation; The S5 includes S51 and S52; S51. After each adjustment and optimization, based on the overall carbon sink CWzt, the optimized carbon sink CWopt is output through comprehensive calculation in combination with the wetland optimization data, and the wetland carbon sink is evaluated again; The optimized carbon sink amount CWopt is output through the following algorithm formula; CWopt=CWzt+b1·△LAI+b2·△VWC-b3·△Rs; Wherein, b1, b2 and b3 represent the preset weight values ​​of leaf area index change △LAI, vegetation water content change △VWC and soil respiration change △Rs, respectively, and b1+b2+b3=1, and the specific values ​​are set by the user.

2. The method for monitoring ecosystem carbon sinks based on remote sensing according to claim 1, characterized in that: S23. Calculate the carbon sink CW of different types of wetlands and then obtain the area A of different types of wetlands from GIS data. i , calculate and output the overall carbon sink CWzt of the entire wetland reserve; The overall carbon sink CWzt is calculated by the following algorithm formula: Where n represents the total number of wetland types, A i Represents the area of ​​the i-th type wetland.

3. The method for monitoring ecosystem carbon sinks based on remote sensing according to claim 2, characterized in that: The S3 includes S31 and S32; S31. Based on the average carbon sink energy of the historical carbon sink monitoring data of the current wetland reserve, a preset carbon sink threshold T is made, and then a preliminary comparative assessment is made with the overall carbon sink volume CWzt to analyze the current carbon sink capacity of the wetland. The specific assessment contents are as follows; When the overall carbon sink amount CWzt ≥ the carbon sink threshold T, it means that the carbon sink capacity of the wetland is normal and meets the expected effect, and no management intervention is required at this time; When the overall carbon sink amount CWzt is less than the carbon sink threshold T, it means that the carbon sink capacity of the wetland is abnormal and does not meet the expected effect. At this time, an adjustment management warning message is sent to the wetland manager to adjust and optimize the wetland.

4. The method for monitoring ecosystem carbon sinks based on remote sensing according to claim 1, characterized in that: S32, generating corresponding optimization measures based on the preliminary comparative evaluation, when the preliminary comparative evaluation shows that the carbon sequestration capacity of the wetland is abnormal, and when the wetland manager receives the adjustment management warning information, the wetland manager implements the optimization measures for the wetland protection area, and the optimization measures include vegetation restoration, hydrological regulation and nitrogen management; After the administrator optimizes and adjusts, the optimized wetland carbon sink data is collected again, and combined with the wetland carbon sink data before optimization, the changes are analyzed to obtain wetland optimization data, which includes leaf area index change △LAI, vegetation water content change △VWC and soil respiration change △Rs; The leaf area index change △LAI is calculated by comparing the leaf area index LAI before and after optimization. The specific algorithm formula is: △LAI=LAI t2 -LAI t1 , where LAI t2 Represents the leaf area index at time t2 after optimization, LAI t1 represents the leaf area index at time t1 before optimization; The vegetation moisture content change △VWC is calculated by comparing the vegetation moisture content VWC before and after optimization. The specific algorithm formula is: △VWC=VWC t2 -VWC t1 , where VWC t2 Represents the vegetation moisture content at time t2 after optimization, VWC t1 represents the vegetation moisture content at time t1 before optimization; The soil respiration change ΔRs is calculated by comparing the soil respiration Rs before and after optimization. The specific algorithm formula is: ΔRs = Rs t2 -Rs t1 , where Rs t2 Represents the optimized vegetation moisture content at time t2, Rs t1 Represents the vegetation moisture content at time t1 before optimization.

5. The method for monitoring ecosystem carbon sinks based on remote sensing according to claim 4, characterized in that: The S4 includes S41, S42 and S43; S41. When the preliminary comparative assessment result is normal, a dynamic monitoring formula is further introduced to calculate the output carbon sink change △CW(t) to dynamically monitor the change of carbon sink over time and seasons; The carbon sink change ΔCW(t) is calculated by the following algorithm formula: In the formula, d represents the differential variable, Fhuman(t) represents the impact factor of human activities; S42, predicting and evaluating the obtained carbon sink change △CW(t) and the carbon sink threshold T, and analyzing the wetland carbon sink change in the wetland reserve at future times based on the evaluation results. The specific evaluation contents are as follows; When the carbon sink change △CW(t) ≥ the carbon sink threshold T, it means that the predicted wetland carbon sink change at time t is normal and no adjustment is required to continue monitoring; When the carbon sink change △CW(t) is less than the carbon sink threshold T, it means that the wetland carbon sink change at time t is predicted to be abnormal. At this time, adjustment management warning information is sent to the wetland manager for secondary adjustment and optimization.

6. The method for monitoring ecosystem carbon sinks based on remote sensing according to claim 1, characterized in that: S43. Based on the corrected carbon sink data obtained and combined with GIS data, GIS tools are used to generate a carbon sink spatial distribution map. Based on the carbon sink change △CW(t), a carbon sink change trend map is generated through GIS tools to show the seasonal and long-term changes in carbon sinks in wetland reserves.

7. The method for monitoring ecosystem carbon sinks based on remote sensing according to claim 1, characterized in that: S52, based on the obtained optimized carbon sink amount CWopt and the carbon sink threshold T, a secondary comparative evaluation is performed to analyze the carbon sink of the optimized wetland. The specific evaluation contents are as follows; When the optimized carbon sink amount CWopt ≥ the carbon sink threshold T, it means that the optimized wetland carbon sink is normal, and the optimization adjustment measures are stopped and monitoring is continued; When the optimized carbon sink amount CWopt is less than the carbon sink threshold T, it means that the wetland carbon sink is abnormal after optimization. At this time, the current optimization adjustment measures should continue to be implemented until the wetland carbon sink returns to normal.

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