Ecological carbon sink monitoring method and system for lake island composite terrain

Abstract

The invention discloses an ecological carbon sink monitoring method and system for a lake island composite terrain. The method comprises the following steps: acquiring multi-source satellite remote sensing data of a lake island composite area; the multi-source satellite remote sensing data comprises satellite observation reflectivity data and solar zenith angle data; constructing a terrain correction model, correcting the multi-source satellite remote sensing data, eliminating the interference of water area reflection, and obtaining the corrected vegetation reflectivity; inverting vegetation biomass and carbon reserve space distribution based on the corrected vegetation reflectivity; constructing a carbon sink dynamic monitoring model in combination with a live-action three-dimensional technology, and generating a space-time distribution map; according to the method, the carbon sink monitoring precision and the space-time continuity of complex scenes such as lakes and islands are improved, and an advanced technical support is provided for realizing accurate accounting and management of carbon sinks in a scenic spot scale.

Description

Technical Field

[0001] This invention belongs to the field of ecological carbon sequestration monitoring technology, and in particular relates to an ecological carbon sequestration monitoring method and system for complex topography of lakes and islands. Background Technology

[0002] Ecological carbon sinks, especially vegetation carbon sinks, play a crucial role in offsetting carbon emissions. Accurately monitoring and assessing regional carbon sink capacity is one of the core tasks of ecological research and environmental management. Remote sensing technology, due to its advantages such as wide coverage and repeatable observation, has become the main means of large-scale carbon sink monitoring. It is usually used to estimate vegetation biomass by inverting vegetation indices (such as NDVI and LAI), and then extrapolate carbon storage.

[0003] However, existing carbon sink monitoring methods face significant challenges in lake-island complex terrain areas. These areas are characterized by fragmented topography, with land (islands) and water (lakes) interspersed. The surface of water (especially in still water environments) exhibits strong specular reflection of sunlight (i.e., "strong water reflection"), which severely interferes with vegetation index calculations for adjacent pixels and even the entire scene. Currently widely used traditional terrain correction models (such as the C model and SCS model) are primarily designed for mountainous terrain, aiming to eliminate the shading effect caused by terrain undulations, and do not fully consider the unique interference source of strong water reflection. Furthermore, existing technologies lack integration with real-world 3D technologies, failing to utilize high-precision 3D models (e.g., generated through oblique photography or LiDAR) for physical space-level interference suppression, resulting in limited correction accuracy. Therefore, directly applying traditional methods for carbon sink monitoring in lake-island areas leads to vegetation index calculations deviating from true values, ultimately causing a significant decrease in the accuracy of carbon storage estimation.

[0004] Furthermore, existing remote sensing carbon sink monitoring methods mostly rely on a single data source, making it difficult to achieve both high spatial and temporal resolution. For example, the Landsat series satellites have high spatial resolution (30 meters), but a long revisit period (16 days), making it difficult to achieve high-frequency dynamic monitoring; while satellites such as MODIS have high temporal resolution, but their spatial resolution is too low (≥250 meters), failing to accurately capture detailed changes in the complex topography of lakes and islands. This contradiction limits their ability to quickly and accurately capture dynamic changes in carbon sinks. While real-scene 3D technology can provide a unified spatial framework, it has not yet been effectively integrated for multi-source data collaboration.

[0005] Therefore, there is an urgent need in this field for a specialized method that can effectively suppress water reflection interference, fuse multi-source remote sensing data, and achieve high spatiotemporal resolution for accurate monitoring, so as to improve the monitoring accuracy and efficiency of ecological carbon sinks in lake-island composite terrain. Summary of the Invention

[0006] Purpose of the invention: The purpose of this invention is to provide an ecological carbon sink monitoring method and system for complex topography of lakes and islands that can improve the accuracy of carbon sink monitoring.

[0007] Technical solution: The present invention provides a method for monitoring ecological carbon sequestration in complex topography of lakes and islands, comprising:

[0008] (1) Acquire multi-source satellite remote sensing data of the lake-island complex area; the multi-source satellite remote sensing data includes satellite observation reflectance data and solar zenith angle data;

[0009] (2) Construct a terrain correction model to correct the multi-source satellite remote sensing data, eliminate the interference of water reflection, and obtain the corrected vegetation reflectance;

[0010] (3) Based on the corrected vegetation reflectance, the spatial distribution of vegetation biomass and carbon storage is inverted;

[0011] (4) Combine real-scene 3D technology to construct a dynamic monitoring model of carbon sink and generate a spatiotemporal distribution map.

[0012] Furthermore, the sources of multi-source satellite remote sensing data mentioned in step (1) include Sentinel series, Landsat series and domestic high-resolution satellite data;

[0013] The multi-source satellite remote sensing data are complemented by spatiotemporal fusion technology to meet the requirements of a spatial resolution of 10 meters × 10 meters and a daily-scale update of temporal resolution.

[0014] Furthermore, the terrain correction model described in step (2) processes reflectance according to the following formula:

[0015] ;

[0016] in, The wavelength of electromagnetic waves, wavelength The corresponding corrected vegetation reflectance; wavelength Corresponding satellite observation reflectivity; wavelength The corresponding pure water reflectance was calibrated using a spectral library; The solar zenith angle; wavelength The corresponding slope aspect / slope topographic factor calculated based on the digital elevation model (DEM); and The weighting coefficients, fitted using the least squares method, are used to ensure a reduction rate of water reflection error ≥ 60%, which is measured by the following formula:

[0017]

[0018] in, This represents the actual reflectance measured on the ground.

[0019] Further, step (3) includes: calculating the normalized vegetation index using the corrected vegetation reflectance. And combined with the measured data from ground sample plots, establish A regression model between vegetation biomass and the model; the regression model uses linear, exponential, or logarithmic forms to ensure inversion accuracy; the biomass estimation formula is as follows:

[0020] ;

[0021] in, For pixels Biomass at the site, in tons per hectare. , and For regression coefficients, This is the corrected NDVI value.

[0022] Furthermore, the carbon storage calculation formula in step (3) is as follows:

[0023] ;

[0024] in, For pixels Carbon reserves at the location, in tons per hectare. , and For regression coefficients, For the corrected value, The carbon conversion factor, This is a vegetation type density correction factor.

[0025] Further, step (4) includes: importing carbon storage data into a three-dimensional GIS platform, constructing a dynamic carbon sink monitoring model, wherein the dynamic carbon sink monitoring model supports the overlay analysis of multi-period remote sensing data, and realizes dynamic tracking and visualization of carbon storage changes.

[0026] Furthermore, step (4) also includes that the carbon sink dynamic monitoring model supports the export of spatial data in a standard format for interfacing with ecological models or policy evaluation systems.

[0027] Based on the same inventive concept, the present invention also provides an ecological carbon sequestration monitoring system for complex lake-island terrain, comprising:

[0028] The data acquisition unit is used to acquire multi-source satellite remote sensing data of the lake-island complex area; the multi-source satellite remote sensing data includes satellite observation reflectance data and solar zenith angle data;

[0029] The terrain correction unit is used to construct a terrain correction model, correct multi-source satellite remote sensing data, eliminate interference from water reflection, and obtain the corrected vegetation reflectance.

[0030] The carbon storage inversion unit is used to invert the spatial distribution of vegetation biomass and carbon storage based on the corrected vegetation reflectance.

[0031] The dynamic modeling unit is used to combine real-scene 3D technology to build a dynamic monitoring model of carbon sinks and generate spatiotemporal distribution maps.

[0032] Based on the same inventive concept, the present invention also provides a computing device, comprising: one or more processors, one or more memories, and one or more programs, the programs being stored in the memory and configured to be executed by the processor, wherein when the programs are loaded onto the processor, they implement the steps of the ecological carbon sink monitoring method for lake-island complex terrain according to any of the preceding claims.

[0033] Based on the same inventive concept, the present invention also provides a storage medium storing a computer program, the computer program including program instructions, which, when executed by a processor, cause the processor to perform the steps of the ecological carbon sink monitoring method for lake-island complex terrain according to any one of the preceding claims.

[0034] Beneficial Effects: Compared with existing technologies, this invention has the following significant advantages: 1. Accurate Elimination of Water Area Interference: It innovatively proposes a terrain correction model for strong water reflection. By introducing water body reflection terms and terrain factors for collaborative correction, and combining the physical occlusion correction method for water reflection using real-scene 3D technology, interference suppression is elevated from the spectral level to the three-dimensional physical space. This significantly suppresses the interference of water reflection on adjacent vegetation pixels. Experimental verification shows that it can reduce water reflection error by more than 60%, greatly improving the accuracy of vegetation index calculation; 2. High Spatiotemporal Resolution: Through the spatiotemporal fusion technology of multi-source remote sensing data (Sentinel, Landsat, Gaofen series), it breaks through the limitations of single data... This method overcomes the limitations of traditional methods by achieving a spatial resolution of 10 meters and a daily temporal resolution, enabling precise capture of rapid dynamic changes in carbon sinks in lake-island composite areas. Leveraging the high-frequency update characteristics of the real-scene 3D model, it precisely captures these rapid dynamic changes. Furthermore, it provides dynamic visualization and decision support by innovatively coupling 3D GIS technology with the carbon sink model. The generated spatiotemporal distribution map visually displays the spatial distribution and temporal trends of carbon sinks, providing strong technical support and visualization tools for ecological management departments. Finally, it offers high accuracy and strong applicability: experiments show that this method improves the carbon sink monitoring accuracy in lake-island areas by more than 35% compared to traditional methods. This method significantly improves the carbon sink monitoring accuracy in lake-island areas, enabling high-frequency dynamic monitoring, and is expected to be applied to the formulation of technical specifications for carbon sink monitoring in lake-type scenic areas in the future. Attached Figure Description

[0035] Figure 1 This is a flowchart of a method according to an embodiment of the present invention;

[0036] Figure 2 This is a schematic diagram of the multi-source satellite remote sensing data preprocessing process according to an embodiment of the present invention;

[0037] Figure 3 This is a schematic diagram of a water area strong reflection interference and terrain correction model according to an embodiment of the present invention;

[0038] Figure 4 This is a flowchart of vegetation index calculation and biomass inversion according to an embodiment of the present invention;

[0039] Figure 5 This is a schematic diagram illustrating the generation and three-dimensional visualization of the spatial distribution map of carbon reserves in an embodiment of the present invention. Detailed Implementation

[0040] To enable those skilled in the art to better understand the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings.

[0041] As attached Figure 1As shown, the ecological carbon sequestration monitoring method for lake-island complex terrain in this embodiment includes:

[0042] (1) Acquire multi-source satellite remote sensing data of the lake-island complex area; the multi-source satellite remote sensing data includes satellite observation reflectance data and solar zenith angle data;

[0043] (2) Construct a terrain correction model to correct the multi-source satellite remote sensing data, eliminate the interference of water reflection, and obtain the corrected vegetation reflectance;

[0044] (3) Based on the corrected vegetation reflectance, the spatial distribution of vegetation biomass and carbon storage is inverted;

[0045] (4) Combine real-scene 3D technology to construct a dynamic monitoring model of carbon sink and generate a spatiotemporal distribution map.

[0046] Specifically, in step (1), multi-source satellite remote sensing data of the lake-island composite area are acquired and preprocessed;

[0047] Specifically, a representative lake-island interspersed area was selected as the study area. This area should include typical vegetation types (such as wetland herbaceous plants, shrub communities, and arbor forests) and large areas of water to ensure topographic complexity and ecological diversity. Remote sensing data sources include Sentinel-2 multispectral imagery (10-meter spatial resolution, 5-day revisit period), Landsat 8 / 9 OLI imagery (30-meter spatial resolution, 16-day revisit period), and imagery from the domestic Gaofen-1 (GF-1) and Gaofen-6 (GF-6) satellites, ensuring coverage of different spatial scales and temporal frequencies. Simultaneously, high-precision 3D real-world data was acquired through oblique photogrammetry (UAV five-lens camera) and airborne LiDAR technology. Software was used to generate a 3D real-world model, which serves as a unified spatial framework for multi-source data fusion and topographic correction.

[0048] The acquired raw remote sensing images undergo radiometric calibration, atmospheric correction (using FLAASH or QUAC algorithms), and geometric correction to eliminate sensor errors and atmospheric effects, obtaining surface reflectance data. Simultaneously, combined with digital elevation model (DEM) data, topographic factors such as slope and aspect are extracted to provide a foundation for subsequent topographic correction. Multi-source images are fused using spatiotemporal fusion techniques (such as the STARFM algorithm) to generate a high spatiotemporal consistency dataset with a spatial resolution of 10 meters and a temporal resolution of 1 day, meeting the needs of high-frequency dynamic monitoring. The multi-source satellite remote sensing data preprocessing workflow is as follows: Figure 2 As shown.

[0049] In step (2), a high-precision terrain correction model is constructed to eliminate the interference of strong water reflection on vegetation index calculation;

[0050] Specifically, addressing the spectral interference caused by strong water reflection in lake-island regions to adjacent vegetation pixels, this invention proposes an improved terrain correction model. Based on traditional terrain correction, this model introduces a pure water reflectance term and terrain factors for collaborative correction. The model formula is as follows:

[0051]

[0052] in, The wavelength of electromagnetic waves, wavelength The corresponding corrected vegetation reflectance; wavelength Corresponding satellite observation reflectivity; wavelength The corresponding pure water reflectance was calibrated using a spectral library; The solar zenith angle; wavelength The corresponding aspect / slope topographic factor calculated based on the digital elevation model (DEM); and The weighting coefficients are fitted using the least squares method, aiming to maximize the reduction rate of water reflection error (≥ 60%).

[0053] By analyzing the viewport of the real-world 3D model, an interference mask is generated to selectively correct satellite imagery, effectively suppressing the combined interference from water reflection and terrain occlusion. Comparison before and after correction shows a significant reduction in vegetation index anomalies in pixels surrounding the water area, resulting in a more continuous and rational spatial distribution of vegetation. The correction principle is as follows: Figure 3 As shown.

[0054] In step (3), based on the corrected vegetation reflectance data, the spatial distribution of vegetation biomass and carbon storage is inverted, such as... Figure 4 As shown;

[0055] Specifically, the Normalized Difference Vegetation Index (NDVI) is calculated using corrected hyperspectral reflectance data, and a regression model between NDVI and vegetation biomass is established by combining this with measured data from ground plots. The regression model can be linear, exponential, or logarithmic to ensure inversion accuracy. The biomass estimation formula is as follows:

[0056]

[0057] in, For pixels Biomass at the site (unit: tons / hectare). , and For regression coefficients, This is the corrected NDVI value.

[0058] Furthermore, biomass is converted into carbon storage using the following formula:

[0059]

[0060] in, Carbon reserves (tons / hectare). The carbon conversion factor (range 0.45–0.5). As a vegetation type density correction factor, it combines real-world 3D models to extract 3D vegetation green volume parameters (such as calculating tree height and canopy volume using lidar point cloud data), thereby upgrading carbon sink monitoring from two-dimensional to three-dimensional and improving inversion accuracy.

[0061] In step (4), a dynamic monitoring model for carbon sinks is constructed by combining three-dimensional geographic information system technology, and a spatiotemporal distribution map is generated;

[0062] Specifically, the carbon storage data obtained in step (3) is imported into a 3D GIS platform (such as ArcGIS Pro or Skyline) to construct a dynamic carbon sink monitoring model. The model supports the overlay analysis of multi-period remote sensing data, enabling dynamic tracking and visualization of carbon storage changes.

[0063] By inputting remote sensing imagery with a set time series (e.g., monthly, quarterly), the model can automatically generate a spatiotemporal distribution map of carbon sinks, displaying the changing trends of carbon storage in different regions and time periods. The map supports 3D rendering, profile analysis, and hotspot identification, facilitating ecological management departments to understand carbon sink dynamics and assisting in the formulation of ecological restoration strategies. Figure 5 As shown.

[0064] Furthermore, the model supports exporting spatial data in standard formats (such as GeoTIFF and Shapefile), facilitating integration with other ecological models or policy evaluation systems and enhancing the system's compatibility and scalability.

[0065] Based on the same inventive concept, this embodiment also provides an ecological carbon sequestration monitoring system for complex terrain of lakes and islands, including:

[0066] The data acquisition unit is used to acquire multi-source satellite remote sensing data of the lake-island complex area; the multi-source satellite remote sensing data includes satellite observation reflectance data and solar zenith angle data;

[0067] The terrain correction unit is used to construct a terrain correction model, correct multi-source satellite remote sensing data, eliminate interference from water reflection, and obtain the corrected vegetation reflectance.

[0068] The carbon storage inversion unit is used to invert the spatial distribution of vegetation biomass and carbon storage based on the corrected vegetation reflectance.

[0069] The dynamic modeling unit is used to combine real-scene 3D technology to build a dynamic monitoring model of carbon sinks and generate spatiotemporal distribution maps.

[0070] Based on the same inventive concept, this embodiment also provides a computing device, including: one or more processors, one or more memories, and one or more programs, the programs being stored in the memory and configured to be executed by the processor, the programs being loaded onto the processor to implement the steps of the ecological carbon sink monitoring method for lake-island composite terrain according to any of the preceding claims.

[0071] Based on the same inventive concept, this embodiment also provides a storage medium storing a computer program, the computer program including program instructions, which, when executed by a processor, cause the processor to perform the steps of the ecological carbon sink monitoring method for lake-island complex terrain according to any one of the preceding claims.

[0072] In summary, this invention effectively suppresses the interference of strong water reflection on vegetation index calculation by constructing a high-precision terrain correction model suitable for lake-island composite terrain. By combining multi-source remote sensing data with 3D GIS technology, it achieves dynamic monitoring of ecological carbon sinks with high spatiotemporal resolution, significantly improving the accuracy and spatial expression capability of carbon storage estimation. It has good prospects for promotion and application value.

Claims

1. A method for monitoring ecological carbon sequestration in complex topography of lakes and islands, characterized in that, include: (1) Acquire multi-source satellite remote sensing data of the lake-island complex area; the multi-source satellite remote sensing data includes satellite observation reflectance data and solar zenith angle data; (2) Construct a terrain correction model to correct the multi-source satellite remote sensing data, eliminate the interference of water reflection, and obtain the corrected vegetation reflectance; (3) Based on the corrected vegetation reflectance, the spatial distribution of vegetation biomass and carbon storage is inverted; (4) Combine real-scene 3D technology to construct a dynamic monitoring model of carbon sink and generate a spatiotemporal distribution map.

2. The method for monitoring ecological carbon sequestration in lake-island composite topography according to claim 1, characterized in that, The sources of multi-source satellite remote sensing data mentioned in step (1) include Sentinel series, Landsat series and domestic high-resolution satellite data; The multi-source satellite remote sensing data are complemented by spatiotemporal fusion technology to meet the requirements of a spatial resolution of 10 meters × 10 meters and a daily-scale update of temporal resolution.

3. The method for monitoring ecological carbon sequestration in lake-island composite topography according to claim 1, characterized in that, The terrain correction model described in step (2) processes reflectance according to the following formula: ； in, The wavelength of electromagnetic waves, wavelength The corresponding corrected vegetation reflectance; wavelength Corresponding satellite observation reflectivity; wavelength The corresponding pure water reflectance was calibrated using a spectral library; The solar zenith angle; wavelength The corresponding slope aspect / slope topographic factor calculated based on the digital elevation model (DEM); and The weighting coefficients, fitted using the least squares method, are used to ensure a reduction rate of water reflection error ≥ 60%, which is measured by the following formula: ； in, This represents the actual reflectance measured on the ground.

4. The method for monitoring ecological carbon sequestration in lake-island composite topography according to claim 1, characterized in that, Step (3) includes: calculating the normalized vegetation index using the corrected vegetation reflectance. And in conjunction with the measured data from ground sample plots, establish A regression model between vegetation biomass and the model; the regression model uses linear, exponential, or logarithmic forms to ensure inversion accuracy; the biomass estimation formula is as follows: ； in, For pixels Biomass at the site, in tons per hectare. , and For regression coefficients, This is the corrected NDVI value.

5. The method for monitoring ecological carbon sequestration in lake-island composite topography according to claim 1, characterized in that, The carbon storage calculation formula in step (3) is as follows: ； in, For pixels Carbon reserves at the location, in tons per hectare. , and For regression coefficients, For the corrected value, The carbon conversion factor, This is a vegetation type density correction factor.

6. The method for monitoring ecological carbon sequestration in lake-island composite topography according to claim 1, characterized in that, Step (4) includes: importing carbon storage data into a three-dimensional GIS platform, constructing a dynamic carbon sink monitoring model, wherein the dynamic carbon sink monitoring model supports the overlay analysis of multi-period remote sensing data, and realizes dynamic tracking and visualization of carbon storage changes.

7. The method for monitoring ecological carbon sequestration in lake-island composite topography according to claim 1, characterized in that, Step (4) also includes that the carbon sink dynamic monitoring model supports the export of spatial data in a standard format for use in connection with ecological models or policy evaluation systems.

8. An ecological carbon sequestration monitoring system for lake-island complex terrain, characterized in that, include: The data acquisition unit is used to acquire multi-source satellite remote sensing data of the lake-island complex area; The multi-source satellite remote sensing data includes satellite observation reflectance data and solar zenith angle data; The terrain correction unit is used to construct a terrain correction model, correct multi-source satellite remote sensing data, eliminate interference from water reflection, and obtain the corrected vegetation reflectance. The carbon storage inversion unit is used to invert the spatial distribution of vegetation biomass and carbon storage based on the corrected vegetation reflectance. The dynamic modeling unit is used to combine real-scene 3D technology to build a dynamic monitoring model of carbon sinks and generate spatiotemporal distribution maps.

9. A computing device, characterized in that, include: One or more processors, one or more memories, and one or more programs, said programs being stored in the memory and configured to be executed by the processor, said programs being loaded onto the processor to implement the steps of the ecological carbon sink monitoring method for lake-island complex topography according to any one of claims 1 to 7.

10. A storage medium, characterized in that, The storage medium stores a computer program, which includes program instructions that, when executed by a processor, cause the processor to perform the steps of the ecological carbon sink monitoring method for lake-island complex topography according to any one of claims 1 to 7.

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