Carbon sink calculation method based on space-time fusion technology and flux data

Abstract

The invention discloses a carbon sink calculation method based on a space-time fusion technology and flux data, and the method comprises the steps: carrying out the space-time fusion synthesis of a remote sensing image, calculating a leaf area index and chlorophyll concentration data with high space-time resolution, and improving the time and space resolution of carbon sink data; calculating daily net primary productivity data by using a light energy utilization rate model based on the leaf area index data and the meteorological data; correcting parameters of the light energy utilization rate model based on the daily net primary productivity data and the daily flux data; migrating the corrected parameters of the light energy utilization rate model to a flux-free site area based on the ratio of the chlorophyll concentrations to obtain the migrated parameters of the light energy utilization rate model; the migrated parameters of the light energy utilization rate model are transmitted back to the light energy utilization rate model, the net primary productivity is calculated, and the carbon sink data are calculated based on the net primary productivity, so that the carbon sink calculation method is higher in applicability, and reliable technical support is provided for carbon cycle research of an ecological system.

Description

Technical Field

[0001] The present invention relates to the field of remote sensing technology, and in particular to a carbon sink calculation method based on time-space fusion technology and flux data. Background Art

[0002] Vegetation is the hub for the exchange of carbon, water and energy between the earth's surface and the atmosphere. It absorbs carbon dioxide from the atmosphere through photosynthesis and converts it into organic carbon. This process plays an important role in regulating the global carbon cycle and mitigating climate change. However, traditional field measurement methods are limited by time, space and human resources, making it difficult to achieve large-scale, continuous monitoring. Therefore, how to use remote sensing data more efficiently for carbon sink calculation has become a research hotspot.

[0003] At present, the methods for calculating ecosystem carbon sinks mainly include the following categories: 1. Manual survey method: measuring the biomass and carbon content of vegetation through field sampling and laboratory analysis; this method has high accuracy, but is time-consuming and labor-intensive, and it is difficult to achieve large-scale, continuous monitoring; 2. Flux observation method: directly measuring the carbon dioxide flux of the ecosystem based on the eddy covariance flux tower. This method can provide continuous observation data, but the deployment cost of flux towers is high and the spatial coverage is limited, making it difficult to extend to regional or global scales; 3. Top-down carbon satellite method: using satellite remote sensing data to invert atmospheric carbon dioxide concentration and then estimate carbon sinks; this method has the advantage of large-scale coverage, but is limited by the temporal and spatial resolution of remote sensing data, and it is difficult to capture rapid changes in ecosystems; 4. Bottom-up process model: simulating photosynthesis and respiration of vegetation based on eco-physiological processes; this method can reflect the dynamic changes of ecosystems, but the model has many parameters, and many parameters are difficult to obtain accurately, resulting in greater uncertainty in the results; 5. Light energy utilization model: calculating net primary productivity based on photosynthetically active radiation absorbed by vegetation and light energy utilization; this method has few parameters, simple calculations, and can better balance accuracy and efficiency, so it has been widely used in carbon sink estimation at regional and global scales.

[0004] However, the existing light energy utilization model still has the following problems: (1) The key parameters in the model (such as the maximum light energy utilization rate) ) usually rely on empirical values ​​or default values, and fail to fully consider the differences between different ecosystem types, resulting in large deviations in the estimation results; (2) Traditional models are usually not combined with flux observation data, resulting in a lack of verification and optimization of model results with measured data; (3) Existing methods mostly rely on a single remote sensing data source, fail to fully utilize the advantages of high temporal resolution and high spatial resolution remote sensing data, and ignore the potential of multi-source data fusion.

[0005] Therefore, how to improve the temporal and spatial resolution of the light energy utilization model, how to optimize the model parameters to improve accuracy, and how to combine multi-source observation data to achieve more reliable carbon sink estimates have become key issues that need to be addressed urgently. Summary of the invention

[0006] The purpose of the present invention is to provide a carbon sink calculation method based on spatiotemporal fusion technology and flux data, which can effectively solve the problems existing in the above-mentioned prior art.

[0007] In order to solve the above technical problems, the present invention adopts the following technical solution: a carbon sink calculation method based on spatiotemporal fusion technology and flux data, comprising the following steps: The remote sensing images acquired at different times and from different remote sensing image sources are synthesized in time and space to calculate the leaf area index and chlorophyll concentration data with high time and space resolution; Based on leaf area index data and meteorological data, the daily net primary productivity data is calculated using the light energy utilization model; The parameters of the light energy utilization model were modified based on the daily net primary productivity data and daily flux data; Based on the ratio of chlorophyll concentration, the modified light energy utilization model parameters are transferred to the no-flux site area to obtain the parameters of the transferred light energy utilization model; The parameters of the migrated light energy utilization model are input back into the light energy utilization model to calculate the net primary productivity, and the carbon sink data is calculated based on the net primary productivity.

[0008] Preferably, two satellites are selected as remote sensing image sources, one satellite is a remote sensing image source with high temporal resolution, and one satellite is a remote sensing image source with high spatial resolution; and High temporal resolution means obtaining remote sensing images at least once a day, and high spatial resolution means the spatial resolution is no greater than 10 meters; According to the time and longitude and latitude coordinates of the two satellites, the data of the same geographical location at the same time are matched in units of image pixels, and the data of the two satellites are fused through the ratio of different times and different pixels.

[0009] Furthermore, the fused remote sensing image is preprocessed, and the preprocessing includes radiation correction, atmospheric correction and geometric correction; Preferably, the PROSAIL model is used to construct a lookup table to calculate the leaf area index and chlorophyll concentration with high temporal and spatial resolution. The PROSAIL model formula is: ; in, is the canopy reflectance, represents the PROSAIL model operator, is the leaf structure parameter, LCC is the chlorophyll concentration, is the equivalent water thickness, is the dry matter content, is the leaf area index, is the average leaf inclination angle, is the hotspot parameter, is the soil wetness coefficient, is the soil hardness coefficient, To observe the zenith angle, is the solar zenith angle, is the relative azimuth between the sun and the observation; Among them, for the above formula, the variable parameters are , LCC, , , and , and the remaining parameters are fixed values, which are used to construct a lookup table to calculate LAI and LCC.

[0010] Preferably, the meteorological data includes saturated water vapor pressure difference, and the saturated water vapor pressure difference calculation formula is: ; Among them, VPD stands for saturated vapor pressure difference, T stands for temperature, and RH stands for relative humidity.

[0011] Preferably, a spatial interpolation method is used to increase the spatial resolution of the meteorological station data to the level of a high spatial resolution remote sensing image. The spatial interpolation methods include: inverse distance weighted interpolation, bilinear interpolation, Kriging interpolation, and the like.

[0012] Preferably, the net primary productivity data is calculated as follows: ; Among them, NPP stands for net primary productivity; It represents the ratio of net primary productivity of vegetation to total primary productivity, which is generally 0.68; is the maximum light energy utilization rate; f(VPD) and f(T) are the correction factors of saturated vapor-water pressure difference and air temperature, respectively, indicating the influence of saturated vapor-water pressure difference and air temperature on vegetation photosynthesis; PAR indicates photosynthetically active radiation; f(PAR) indicates the proportion of photosynthetically active radiation absorbed by the canopy.

[0013] Preferably, the calculation formula of the saturated steam-water pressure difference and the air temperature correction factor is: ; ; Among them, VPD max , VPD min , T min , Tmax It is a parameter related to vegetation type; VPD max It is the VPD value when NPP reaches the minimum value. If VPD is greater than or equal to VPD max , the photosynthesis of vegetation is reduced due to stomatal closure, and the value of f(VPD) is 0; VPD min is the VPD value when NPP reaches the maximum. If VPD is less than or equal to VPD min , then the photosynthesis of vegetation will no longer be inhibited by VPD, and the value of f(VPD) will be 1; Similarly, Tmin is the T value when NPP reaches the minimum. If T is less than or equal to T min , the photosynthesis of vegetation decreases due to the low air temperature, and the value of f(T) is 0; Tmax is the T value when NPP reaches the maximum. If T is greater than or equal to T max , then the photosynthesis of vegetation is not affected by temperature, and the value of f(T) is 1; The formula for calculating the proportion of photosynthetically active radiation absorbed by the canopy is: ; Among them, k is the extinction coefficient, which is generally taken as 0.5.

[0014] Preferably, the parameters of the light energy utilization model are modified, specifically including: Determine the initial value of maximum light energy utilization according to vegetation type ; Adjust the maximum light energy utilization , The step size is 0.001, and n is the number of optimizations; Calculate the root mean square error RMSE: ; in, represents the daily net primary productivity data, represents the daily flux data, and n represents the actual number of days; when RMSE is the smallest, is the corrected maximum light energy utilization rate.

[0015] Preferably, an area with the same ecological type as the flux site is determined, and the maximum light energy utilization rate is adjusted using the chlorophyll concentration ratio. The calculation formula is: ; in, Represents the maximum light energy utilization rate of the no-flux site area, Represents the maximum light energy utilization rate of the flux site area, represents the chlorophyll concentration in the no-flux station area, Representative flux site regional chlorophyll concentration.

[0016] Preferably, the parameters of the migrated light energy utilization model are input into the light energy utilization model to calculate the net primary productivity, and then the high-precision carbon sink data C is calculated according to the photosynthesis chemical equation: ; Among them, 1.63 is the coefficient of net primary productivity converted into carbon dioxide; 12 / 44 is the coefficient of carbon dioxide converted into carbon.

[0017] Beneficial effect: In the present invention, remote sensing images acquired at different times and from different remote sensing image sources are synthesized by spatiotemporal fusion, which improves the temporal and spatial resolution of carbon sink data, and corrects the light energy utilization model parameters by flux data, making the carbon sink data calculation more accurate. The corrected model parameters are then adjusted to the no-flux site area by chlorophyll concentration, and the parameters of the light energy utilization model are adjusted for a second time. The carbon sink data are then calculated using the parameters of the second-adjusted light energy utilization model, making the carbon sink calculation method more applicable and providing reliable technical support for the study of ecosystem carbon cycle. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The accompanying drawings are used to provide further understanding of the present invention and constitute a part of the specification. They are used to explain the present invention together with the embodiments of the present invention and do not constitute a limitation of the present invention.

[0019] In the attached picture: Figure 1 It is a schematic diagram of the process of the present invention; Figure 2 This is the correction result of the flux data in the present invention. DETAILED DESCRIPTION

[0020] In order to make the purpose and advantages of the present invention more clearly understood, the present invention is specifically described in conjunction with the following embodiments. It should be understood that the following text is only used to describe a carbon sink calculation method based on spatiotemporal fusion technology and flux data or several specific implementation methods of the present invention, and does not strictly limit the scope of protection of the specific request of the present invention.

[0021] Example: Figure 1 As shown, a carbon sink calculation method based on spatiotemporal fusion technology and flux data includes the following steps: S1. Download and fuse remote sensing images with high temporal resolution and high spatial resolution, select satellites with required temporal resolution and spatial resolution as remote sensing image sources, and download remote sensing images; In this embodiment, two satellites are selected as remote sensing image sources, wherein one satellite is a remote sensing image source with high temporal resolution, and one satellite is a remote sensing image source with high spatial resolution. High temporal resolution means that a remote sensing image is obtained at least once a day, and high spatial resolution means that the spatial resolution is not greater than 10 meters. The remote sensing images acquired at different times and from different remote sensing image sources are synthesized in time and space, that is, according to the time and longitude and latitude coordinates of the two satellites, the data at the same geographical location at the same time are matched in units of image pixels, and the data of the two satellites are fused by the ratio of different times and different pixels, and finally remote sensing image data with high temporal resolution and high spatial resolution are obtained; Preferably, in this embodiment, the fused remote sensing image can be preprocessed, and the preprocessing includes radiation correction, atmospheric correction and geometric correction; Based on the fused remote sensing image data, the leaf area index and chlorophyll concentration data with high temporal and spatial resolution are calculated as follows: The PROSAIL model is used to construct a lookup table to calculate the leaf area index and chlorophyll concentration with high temporal and spatial resolution. The PROSAIL model formula is: ; in, is the canopy reflectance, represents the PROSAIL model operator, is the leaf structure parameter, LCC is the chlorophyll concentration, is the equivalent water thickness, is the dry matter content, is the leaf area index, is the average leaf inclination angle, is the hotspot parameter, is the soil wetness coefficient, is the soil hardness coefficient, To observe the zenith angle, is the solar zenith angle, is the relative azimuth between the sun and the observation; The variable parameters are , LCC, , , and , the remaining parameters are fixed values, and a lookup table is constructed to calculate LAI and LCC; S2. Download the meteorological station data, including temperature, relative humidity, photosynthetically active radiation, and calculate the saturated water vapor pressure difference. The calculation formula is: ; Among them, VPD stands for Vapor Pressure Deficit, T stands for air temperature, and RH stands for relative humidity. The resolution is increased to the level of high spatial resolution remote sensing images through spatial interpolation methods; spatial interpolation methods include: inverse distance weighted interpolation, bilinear interpolation, Kriging interpolation, etc. S3, inputting leaf area index data and meteorological data into the light energy utilization model to obtain daily net primary productivity data; In this embodiment, the expression of the MOD17 light energy utilization model is: ; Among them, NPP stands for net primary productivity; It represents the ratio of net primary productivity of vegetation to total primary productivity, which is 0.68; is the maximum light energy utilization rate, which depends on different vegetation types; f(VPD) and f(T) are the correction factors of saturated vapor-water pressure difference and air temperature, respectively, indicating the effects of saturated vapor-water pressure difference and air temperature on vegetation photosynthesis; PAR stands for Photosynthetic Active Radiation, and f(PAR) represents the proportion of photosynthetic active radiation absorbed by the canopy; The calculation formula for the saturated steam-water pressure difference and air temperature correction factor is: ; ; Among them, VPD max , VPD min , T min , T max It is a parameter related to vegetation type; VPD max It is the VPD value when NPP reaches the minimum value. If VPD is greater than or equal to VPD max , the photosynthesis of vegetation is reduced due to stomatal closure, and the value of f(VPD) is 0; VPD min is the VPD value when NPP reaches the maximum. If VPD is less than or equal to VPD min , then the photosynthesis of vegetation will no longer be inhibited by VPD, and the value of f(VPD) will be 1; Similarly, Tmin is the T value when NPP reaches the minimum. If T is less than or equal to T min , the photosynthesis of vegetation decreases due to the low air temperature, and the value of f(T) is 0; Tmax is the T value when NPP reaches the maximum. If T is greater than or equal to T max , then the photosynthesis of vegetation is not affected by temperature, and the value of f(T) is 1; The formula for calculating the proportion of photosynthetically active radiation absorbed by the canopy is: ; Among them, k is the extinction coefficient, which is generally taken as 0.5; LAI is the leaf area index.

[0022] Different vegetation types and VPD max , VPD min , T min , T max As shown in Table 1; Table 1 Parameters of different vegetation types

[0023] S4. Download flux site data: Download flux site data of different ecological types, exclude abnormal data values, and add up the flux data in each time period of the day; Different ecological types include forests, grasslands, farmlands, wetlands, cities, etc.; The parameters of the light energy utilization model were corrected using daily flux data and net primary productivity data; Constantly adjust the maximum light energy utilization , The step size is 0.001, k is the number of optimizations, and the root mean square error RMSE is calculated using the following formula: ; in, represents the daily net primary productivity data, represents daily flux data, and n represents the actual number of days; When RMSE is the smallest, For the corrected maximum light energy utilization, refer to Figure 2 This is the revised result of Qianyanzhou site; S5, using chlorophyll concentration ratios to migrate the modified model parameters to the no-flux station area; In this embodiment, an area with the same ecological type as the flux site is determined, and the maximum light energy utilization rate is adjusted using the chlorophyll concentration ratio. The calculation formula is: ; in, Represents the maximum light energy utilization rate of the no-flux site area, Represents the maximum light energy utilization rate of the flux site area, represents the chlorophyll concentration in the no-flux station area, represents the regional chlorophyll concentration of the flux site; The adjusted maximum light energy utilization rate is brought back to the MOD17 light energy utilization model to calculate the net primary productivity. Then, according to the photosynthesis chemical equation, the high-precision carbon sink data C is calculated. The calculation formula is: ; Among them, 1.63 is the coefficient of net primary productivity converted into carbon dioxide; 12 / 44 is the coefficient of carbon dioxide converted into carbon.

[0024] The embodiments of the present invention are described in detail above in conjunction with the accompanying drawings, but the present invention is not limited to the above embodiments. For ordinary technicians in this technical field, after knowing the contents recorded in the present invention, they can make several equivalent changes and substitutions without departing from the principle of the present invention. These equivalent changes and substitutions should also be regarded as belonging to the protection scope of the present invention.

Claims

1. A carbon sink calculation method based on spatiotemporal fusion technology and flux data, characterized by: The steps include: The remote sensing images acquired at different times and from different remote sensing image sources are synthesized in time and space to calculate the leaf area index and chlorophyll concentration data with high time and space resolution; Based on leaf area index data and meteorological data, the daily net primary productivity data is calculated using the light energy utilization model; The parameters of the light energy utilization model were modified based on the daily net primary productivity data and daily flux data; Based on the ratio of chlorophyll concentration, the modified light energy utilization model parameters are transferred to the no-flux site area to obtain the parameters of the transferred light energy utilization model; The parameters of the migrated light energy utilization model are input back into the light energy utilization model to calculate the net primary productivity, and the carbon sink data is calculated based on the net primary productivity.

2. A carbon sink calculation method based on spatiotemporal fusion technology and flux data according to claim 1, characterized in that: Select two satellites as remote sensing image sources, one satellite is a remote sensing image source with high temporal resolution, and the other satellite is a remote sensing image source with high spatial resolution; As well as high temporal resolution, remote sensing images are acquired at least once a day, and high spatial resolution, spatial resolution is no greater than 10 meters; According to the time and longitude and latitude coordinates of the two satellites, the data of the same geographical location at the same time are matched in units of image pixels, and the data of the two satellites are fused through the ratio of different times and different pixels.

3. A carbon sink calculation method based on spatiotemporal fusion technology and flux data according to claim 2, characterized in that: The PROSAIL model is used to construct a lookup table to calculate the leaf area index and chlorophyll concentration with high temporal and spatial resolution. The PROSAIL model formula is: ； in, is the canopy reflectance, represents the PROSAIL model operator, is the leaf structure parameter, LCC is the chlorophyll concentration, is the equivalent water thickness, is the dry matter content, is the leaf area index, is the average leaf inclination angle, is the hotspot parameter, is the soil wetness coefficient, is the soil hardness coefficient, To observe the zenith angle, is the solar zenith angle, is the relative azimuth between the sun and the observation point.

4. The carbon sink calculation method based on spatiotemporal fusion technology and flux data according to claim 1 is characterized by: Meteorological data includes saturated water vapor pressure difference, and the saturated water vapor pressure difference calculation formula is: ； Among them, VPD stands for saturated vapor pressure difference, T stands for temperature, and RH stands for relative humidity.

5. A carbon sink calculation method based on spatiotemporal fusion technology and flux data according to claim 4, characterized in that: Spatial interpolation methods are used to increase the spatial resolution of meteorological station data to the level of high spatial resolution remote sensing images.

6. The carbon sink calculation method based on spatiotemporal fusion technology and flux data according to claim 1 is characterized by: The formula for calculating net primary productivity data is: ； Among them, NPP stands for net primary productivity; Represents the ratio of net primary productivity of vegetation to total primary productivity; is the maximum light energy utilization rate; f(VPD) and f(T) are the correction factors of saturated vapor-water pressure difference and air temperature, respectively, indicating the influence of saturated vapor-water pressure difference and air temperature on vegetation photosynthesis; PAR indicates photosynthetically active radiation; f(PAR) indicates the proportion of photosynthetically active radiation absorbed by the canopy.

7. A carbon sink calculation method based on spatiotemporal fusion technology and flux data according to claim 6, characterized in that: The calculation formula for the saturated steam-water pressure difference and air temperature correction factor is: ； ； Among them, VPD max is the VPD value when NPP reaches the minimum value, T min is the T value when NPP reaches the minimum; The formula for calculating the proportion of photosynthetically active radiation absorbed by the canopy is: ； Where k is the extinction coefficient.

8. The carbon sink calculation method based on spatiotemporal fusion technology and flux data according to claim 1 is characterized by: Modify the parameters of the light energy utilization model, including: Determine the initial value of maximum light energy utilization according to vegetation type ; Adjust the maximum light energy utilization , The step size is 0.001, and n is the number of optimizations; Calculate the root mean square error RMSE: ； in, represents the daily net primary productivity data, represents daily flux data, and n represents the actual number of days; When RMSE is the smallest, is the corrected maximum light energy utilization rate.

9. A carbon sink calculation method based on spatiotemporal fusion technology and flux data according to claim 8, characterized in that: Determine the area with the same ecological type as the flux site, and use the chlorophyll concentration ratio to adjust the maximum light energy utilization rate. The calculation formula is: ； in, Represents the maximum light energy utilization rate of the no-flux site area, Represents the maximum light energy utilization rate of the flux site area, represents the chlorophyll concentration in the no-flux station area, Representative flux site regional chlorophyll concentration.

10. A carbon sink calculation method based on spatiotemporal fusion technology and flux data according to claim 9, characterized in that: The parameters of the migrated light energy utilization model are input into the light energy utilization model to calculate the net primary productivity, and then the high-precision carbon sink data C is calculated based on the photosynthesis chemical equation: 。

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