Method and system for screening compliance of afforestation carbon sink project based on multi-source data fusion

Abstract

The application relates to the technical field of afforestation carbon sink, and provides a method and system for screening compliance of an afforestation carbon sink project based on multi-source data fusion, which comprises the following steps: developing a project screening and determining afforestation sub-compartment data boundary reconstruction, improving data integrity and spatial precision; screening land use status of a project graph based on land change survey data, verifying and checking the afforestation project based on high-resolution remote sensing image data, and verifying the afforestation project based on the land change survey field evidence photo database after the remote sensing image data verification; screening afforestation occurrence of a project graph, realizing continuous tracing of historical land use status of a project plot, and finally screening the afforestation project to be a plot range meeting afforestation carbon sink project development conditions. The above method improves the automation and large-scale capacity of afforestation carbon sink project plot identification, significantly reduces project development cost, and improves project development efficiency.

Description

Technical Field

[0001] This application relates to the field of afforestation carbon sink technology, specifically to a method and system for screening compliance of afforestation carbon sink projects based on multi-source data fusion. Background Technology

[0002] In the development of afforestation carbon sink projects, it is necessary to conduct eligibility reviews of project sites. Currently, project developers identify land use status of project sites through on-site surveys or manual interpretation of historical remote sensing images, and then confirm site eligibility by combining this with current land use data. However, these methods have certain shortcomings in practical application. On the one hand, manual interpretation of historical images requires analysis of each site individually, which is labor-intensive and inefficient for large-scale projects. On the other hand, subjective differences may exist among different personnel during image interpretation, affecting the consistency of the judgment results. Furthermore, single remote sensing image data sources often have limitations such as mismatched spatiotemporal resolution, incomplete data coverage, or weather conditions, making it difficult to comprehensively and accurately reflect the dynamic changes in land use of project sites at different times. These problems not only further reduce the efficiency of site eligibility confirmation but may also lead to biased judgment results due to data limitations, failing to meet the accuracy and timeliness requirements of afforestation carbon sink projects for site review, and hindering the standardized development and efficiency of the projects. Summary of the Invention

[0003] This invention aims to address the problems in existing technologies by providing a method and system for screening compliance of afforestation carbon sink projects based on multi-source data fusion. This improves the reliability and accuracy of land use identification results and enhances the efficiency of land parcel screening and judgment while maintaining identification accuracy, thus providing effective technical support for the large-scale and rapid identification of afforestation carbon sink projects. To achieve the above objectives, this application provides a method for compliance screening of afforestation carbon sink projects based on multi-source data fusion, including: All afforestation projects within the development area of ​​the afforestation project, including protective forests, special-purpose forests, and timber forests, were screened, and their corresponding plot vector data were compiled. For afforestation projects lacking plot vector data, boundary reconstruction was performed using geographic registration methods based on topographic map data of the afforestation project area. Based on the latest annual land use change survey data, the plot vector data of each afforestation project were overlaid with the land use change data using spatial analysis methods to extract land use attributes. Afforestation projects with the land use attribute of forest land were screened, and those whose current status did not meet the requirements for forest land status were removed. The afforestation projects were verified based on the latest high-resolution remote sensing image data. First, based on the remote sensing image data, the vegetation type and tree species information within the afforestation project area screened by the land use change survey data were identified. Then, afforestation projects whose vegetation type did not meet the requirements for forest land or whose tree species information was inconsistent with the afforestation operation design were removed. The following steps were taken: Zoning boundaries were corrected; based on the database of field evidence photos from the land use change survey, afforestation projects verified through remote sensing image data were verified through field data, and afforestation projects that did not match the field evidence photos were eliminated; the vector data of small plots of afforestation projects verified through field evidence photos were overlaid with the land use change survey data from the third year prior to the start of the afforestation project, and the land use attributes before the start of the afforestation project were extracted. Afforestation projects that had been continuously forest land for three years prior to the start of the afforestation project were eliminated. The selected afforestation projects were the plots that initially met the conditions for the development of afforestation carbon sink projects. Finally, using the image texture features and vegetation indices extracted from the high-resolution remote sensing image data, the plots that initially met the conditions for the development of afforestation carbon sink projects were classified into forest patches and non-forest patches, and forest patches were selected as the final plots that met the conditions for the development of afforestation carbon sink projects.

[0004] Furthermore, for the afforestation projects lacking small plot vector data, the boundaries are reconstructed using the topographic map data of each afforestation project area as a benchmark, employing a georeferencing method, including: First, using the topographic map data of the afforestation project area with missing sub-block vector data as a benchmark, permanent feature points that have not shifted with afforestation, such as road intersections, irrigation canal inflection points, and field corners on the topographic map, are selected as registration control points, and corresponding points are located on the afforestation project operation design map. Then, geometric registration is performed using an affine transformation model, and the root mean square error is controlled within one pixel by adjusting the position of the control points. Finally, after registration is completed, vector drawing is performed based on the original afforestation project boundary marked on the topographic map data and combined with the spectral characteristics of the remote sensing image data. Topological checks and clipping are then performed on the generated vector polygons to complete the reconstruction of the afforestation project boundary with missing sub-block vector data.

[0005] Furthermore, the boundary correction includes: first, for afforestation projects where the vegetation type does not meet the requirements for forest land or the tree species information is inconsistent with the afforestation operation design, the boundary is corrected using ArcGIS software; then, the normalized vegetation index range and texture features within the corrected afforestation project area are statistically analyzed to determine whether they meet the requirements for forest land or whether the tree species information is consistent with the afforestation operation design. If they do not meet the requirements or are inconsistent, the boundary is corrected again.

[0006] Furthermore, the step of identifying vegetation types and tree species information within the afforestation project area after screening by land change survey data based on remote sensing image data includes: first, statistically analyzing the normalized vegetation index (NVI) range and texture features within the afforestation project area screened as forest land by land change survey data on the remote sensing image data; then, determining tree species information and vegetation types based on the NVI range and texture features.

[0007] Furthermore, the screening of all afforestation projects within the development area of ​​the afforestation carbon sink project includes: obtaining the operation design and acceptance documents of afforestation projects in previous years within the development area of ​​the afforestation carbon sink project, and screening out afforestation projects for protective forests, special-purpose forests and timber forests based on the operation design and acceptance documents.

[0008] Furthermore, the data format of the land change survey data is: a vector area layer, whose attribute fields contain explicit land use type information for identifying the land use attributes of the map patches.

[0009] Furthermore, the high-resolution remote sensing image data source adopts Gaofen-1, Gaofen-2, or Ziyuan-1.

[0010] This application also provides a compliance screening system for afforestation carbon sink projects based on multi-source data fusion, comprising at least a microprocessor and a memory. The microprocessor is programmed or configured to perform the steps of the aforementioned compliance screening method for afforestation carbon sink projects based on multi-source data fusion, or the memory stores a computer program programmed or configured to perform the aforementioned compliance screening method for afforestation carbon sink projects based on multi-source data fusion.

[0011] This application also provides a computer-readable storage medium storing a computer program programmed or configured to perform the above-described method for screening compliance of afforestation carbon sink projects based on multi-source data fusion.

[0012] Compared with the prior art, this application has the following beneficial effects: (1) Significantly reduce the development cost of afforestation carbon sink projects and improve development efficiency.

[0013] This invention comprehensively utilizes multi-source remote sensing imagery and land use data to identify and screen land use status of project sites, effectively reducing reliance on large-scale manual field surveys. Compared to traditional field survey methods, this method can complete the screening and identification of project sites over a large area in a shorter time, significantly reducing manpower, material resources, and time costs, thereby improving the overall efficiency of afforestation carbon sequestration project development.

[0014] (2) Improve the integrity and spatial accuracy of project data.

[0015] This invention comprehensively utilizes remote sensing imagery and topographic map data to accurately reconstruct missing sub-compartment boundaries, effectively solving the vector fault problem caused by missing historical data or incomplete field boundary demarcation. This not only ensures the authenticity and legality of afforestation area statistics but also provides a precise spatial basis for subsequent high-resolution remote sensing imagery-based volume inversion, biomass model estimation, and dynamic carbon storage monitoring. It reduces the uncertainty of carbon sink accounting from the source and significantly improves the compliance and approval rate of project application materials.

[0016] (3) Improve the accuracy and reliability of land use classification for project sites.

[0017] This invention integrates multi-source remote sensing image data, land use data, and historical field evidence image data to comprehensively analyze the current and historical land use categories of project sites. It also verifies the judgment results by cross-validating multi-source data, effectively reducing the limitations of a single data source in terms of spatial resolution, data quality, or temporal coverage, and improving the accuracy and stability of land use category determination results.

[0018] (4) To achieve continuous tracing of the historical land use status of the project site.

[0019] This invention introduces historical remote sensing image data from the three years prior to afforestation implementation and combines it with vegetation index analysis to systematically determine the historical land use attributes of project sites. This effectively identifies sites that were continuously non-forest land for the three years prior to afforestation, providing a reliable basis for determining the eligibility of afforestation carbon sink projects and improving the traceability and standardization of data during project development.

[0020] (5) Enhance the automation and scale of afforestation carbon sink project site identification.

[0021] By constructing a comprehensive judgment process based on remote sensing imagery and land use data, this invention can quickly screen and automatically identify potential project sites in a large area, overcoming the limitations of traditional manual interpretation methods that are inefficient and highly subjective. This provides technical support for the large-scale development of afforestation carbon sink projects at the regional scale or even a larger scale. Attached Figure Description

[0022] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0023] Figure 1 A flowchart illustrating an embodiment of the method of this application is shown schematically. Detailed Implementation

[0024] To facilitate understanding of this application, the following description will be more comprehensive and detailed in conjunction with the accompanying drawings and preferred embodiments, but the scope of protection of this application is not limited to the following specific embodiments.

[0025] Unless otherwise defined, all technical terms used herein have the same meaning as commonly understood by those skilled in the art. The technical terms used herein are for the purpose of describing particular embodiments only and are not intended to limit the scope of this application.

[0026] Please see Figure 1 One implementation method is a compliance screening method for afforestation carbon sink projects based on multi-source data fusion, specifically including: The first step is to develop projects and determine the data boundary reconstruction of afforestation plots.

[0027] Before selecting afforestation carbon sink projects, basic materials of relevant afforestation projects over the years should be collected within the development area of ​​the afforestation project. These materials mainly include: afforestation project issuance documents, afforestation operation design documents, afforestation project construction records, afforestation project acceptance reports, afforestation project ownership information, afforestation project plot vector data, topographic map data, high-resolution remote sensing image data, and land change survey data.

[0028] First, obtain the operational design and acceptance documents for afforestation projects over the years within the development area of ​​the afforestation carbon sink project. Then, based on these documents, select afforestation projects for protective forests, special-purpose forests, and timber forests, and exclude projects for economic forest afforestation, greening of non-forest land, and greening of urban and rural areas and industrial land. Compile the corresponding plot vector data. For afforestation projects lacking plot vector data, use the topographic map data of the afforestation project area as a benchmark and employ georeferencing methods to reconstruct the boundaries.

[0029] The specific method for reconstructing the boundaries of afforestation projects with missing sub-compartment vector data is as follows: First, using the topographic map data of the afforestation project area with missing sub-compartment vector data as a reference, permanent feature points that have not shifted with afforestation, such as road intersections, irrigation canal inflection points, and field corners, are selected as registration control points, and corresponding points are located on the afforestation project operation design map; then, geometric registration is performed using an affine transformation model, and the root mean square error is controlled within one pixel by adjusting the position of the control points; finally, after registration, vector drawing is performed based on the original afforestation project boundary marked on the topographic map data, combined with the spectral characteristics of remote sensing image data, such as using the Normalized Difference Vegetation Index (NDVI), and topological checking and clipping are performed on the generated vector polygons to complete the reconstruction of the afforestation project boundaries with missing sub-compartment vector data, thereby achieving centimeter-level accuracy restoration of the missing sub-compartment boundaries and ensuring seamless splicing of the reconstructed data with the existing database.

[0030] The second step is to screen the current land use status of the project plots.

[0031] Based on the latest annual land change survey data, the vector data of each afforestation project plot is overlaid with the land change data using spatial analysis methods to extract land use attributes. Afforestation projects with land use attributes of forest land are selected, and afforestation projects whose current status does not meet the requirements of forest land status are eliminated.

[0032] The data format of the land use change survey data is: a vector area layer, whose attribute fields contain clear land use type information to identify the land use attributes of the map patches.

[0033] The third step is to verify and check multi-source remote sensing images.

[0034] The afforestation project was validated based on the latest high-resolution remote sensing image data. First, the vegetation type and tree species information in the afforestation project area were identified based on the remote sensing image data and after screening by the land change survey data. Then, the zoning boundary was corrected for afforestation projects whose vegetation type did not meet the requirements of forest land or whose tree species information was inconsistent with the afforestation operation design.

[0035] In this step, the high-resolution remote sensing image data sources include Gaofen-1, Gaofen-2, and Ziyuan-1. The specific steps for identifying vegetation types and tree species within the afforestation project area, after screening by land use change survey data, are as follows: First, on the remote sensing image data, statistically analyze the normalized vegetation index (NVI) range and texture features within the afforestation project area screened as forest land by the land use change survey data; then, determine the tree species information and vegetation type based on the NVI range and texture features.

[0036] The aforementioned zoning boundary correction is mainly used to assist in the verification and inspection of project map features, and to achieve automated screening and verification of project map features. The specific process is as follows: First, for afforestation projects where the vegetation type does not meet the requirements for forest land or the tree species information is inconsistent with the afforestation operation design, ArcGIS software is used to correct the boundaries. Then, the normalized vegetation index range and texture features within the corrected afforestation project area are statistically analyzed to determine whether they meet the requirements for forest land or whether the tree species information is consistent with the afforestation operation design. If they do not meet the requirements or are inconsistent, the boundaries are corrected again.

[0037] The fourth step is to verify the data in the field.

[0038] Based on the database of on-site evidence photos from the land change survey, on-site data verification is conducted on afforestation projects that have been verified through remote sensing image data. Afforestation projects that do not match the on-site evidence photos are eliminated, thereby further improving the accuracy of project patch selection and verification.

[0039] The fifth step is to screen the occurrence of afforestation in the project plots.

[0040] The vector data of the small plots of afforestation projects verified by on-site evidence photos are overlaid with the land change survey data of the three years prior to the start of the afforestation project. The land type attributes before the start of the afforestation project are extracted, and afforestation projects that have been forest land for three consecutive years prior to the start of the afforestation project are eliminated. The selected afforestation projects are the plots that initially meet the development conditions of afforestation carbon sink projects.

[0041] Step 6: Verify and check the multi-source remote sensing images again.

[0042] Using image texture features and vegetation indices extracted from remote sensing image data such as Gaofen-1, Gaofen-2, and Ziyuan-1, the areas of land that initially meet the development conditions for afforestation carbon sink projects are classified into forest map patches and non-forest map patches. Forest map patches are selected as the areas of land that ultimately meet the development conditions for afforestation carbon sink projects.

[0043] This step utilizes high-resolution remote sensing image data to re-verify the areas of land that initially meet the development conditions for afforestation carbon sink projects. Based on image texture characteristics and vegetation cover, mainly the Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EDI), it further verifies whether the project patches belong to non-forest land, thus assisting in the verification and inspection of project patches and realizing automated screening and verification of project patches.

[0044] By combining the multi-source data verification results of project map patches, the screening results of current land use status, the screening results of historical land use status, and the results of project map patch verification report, a project map patch verification report can be issued, providing data support and scientific proof for project development.

[0045] During the development phase of afforestation carbon sink projects, the project sites can be continuously and dynamically monitored through remote sensing monitoring systems and fixed cameras. The main method is to monitor the growth status of trees, pests and diseases, and disasters in the project plots in real time through monthly high-resolution remote sensing images, providing data support for the subsequent monitoring, reporting, and verification of afforestation carbon sink projects.

[0046] This application also provides another embodiment, a compliance screening system for afforestation carbon sink projects based on multi-source data fusion, comprising at least a microprocessor and a memory, wherein the microprocessor is programmed or configured to perform the steps of the above-described compliance screening method for afforestation carbon sink projects based on multi-source data fusion, or the memory stores a computer program programmed or configured to perform the above-described compliance screening method for afforestation carbon sink projects based on multi-source data fusion.

[0047] This application also provides another embodiment, a computer-readable storage medium storing a computer program programmed or configured to perform the above-described method for screening compliance of afforestation carbon sink projects based on multi-source data fusion.

[0048] The above are merely preferred embodiments of this application. It should be noted that this application is not limited to the above embodiments. For those skilled in the art, several improvements and modifications can be made without departing from the principles of this application. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should also be considered within the scope of protection of this application.

Claims

1. A method for compliance screening of afforestation carbon sink projects based on multi-source data fusion, characterized in that, The method includes: All afforestation projects, including protective forests, special-purpose forests, and timber forests, within the development area of ​​the afforestation project were screened, and the corresponding plot vector data were compiled. For afforestation projects with missing plot vector data, the boundaries were reconstructed using the topographic map data of the afforestation project area as a reference and the georeferencing method. Based on the latest annual land change survey data, the vector data of each afforestation project plots are overlaid with the land change data using spatial analysis methods to extract land use attributes, screen afforestation projects with land use attributes of forest land, and eliminate afforestation projects whose current status does not meet the requirements of forest land status. The afforestation project was verified based on the latest high-resolution remote sensing image data. First, the vegetation type and tree species information in the afforestation project area were identified based on the remote sensing image data and after screening by the land change survey data. Then, the zoning boundary was corrected for afforestation projects whose vegetation type did not meet the requirements of forest land or whose tree species information was inconsistent with the afforestation operation design. Based on the database of on-site evidence photos from the land change survey, on-site data verification was conducted on afforestation projects that had been verified through remote sensing image data, and afforestation projects that did not match the on-site evidence photos were eliminated. The vector data of small plots of afforestation projects verified by on-site evidence photos will be overlaid with the land change survey data of the third year before the start of the afforestation project. The land type attributes before the start of the afforestation project will be extracted, and afforestation projects that have been forest land for three consecutive years before the start of the afforestation project will be eliminated. The selected afforestation projects are the plots that initially meet the development conditions of afforestation carbon sink projects. Using the image texture features and vegetation indices extracted from the high-resolution remote sensing image data, the areas of land that initially meet the development conditions for afforestation carbon sink projects are classified into forest map patches and non-forest map patches, and forest map patches are selected as the areas of land that ultimately meet the development conditions for afforestation carbon sink projects.

2. The compliance screening method for afforestation carbon sink projects according to claim 1, characterized in that, For afforestation projects lacking small plot vector data, boundary reconstruction is performed using topographic map data of each afforestation project area as a benchmark, employing a georeferencing method, including: First, based on the topographic map data of the afforestation project area with missing small plot vector data, permanent feature points on the topographic map that have not shifted with afforestation are selected as registration control points, and the corresponding points are located on the afforestation project operation design map. Then, an affine transformation model is used for geometric registration, and the root mean square error is controlled within 1 pixel by adjusting the position of the registration control points. Finally, after registration, vector drawing was performed based on the original afforestation project boundaries marked on the topographic map data and the spectral characteristics of the remote sensing image data. Topological checks and clipping were then performed on the generated vector polygons to reconstruct the afforestation project boundaries for the missing sub-plot vector data.

3. The compliance screening method for afforestation carbon sink projects according to claim 1, characterized in that, The correction of the administrative boundary includes: First, for afforestation projects where the vegetation type does not meet the requirements of forest land or the tree species information is inconsistent with the afforestation operation design, ArcGIS software is used to correct the boundaries. Then, the normalized vegetation index range and texture characteristics within the afforestation project area are statistically corrected to determine whether they meet the forest land requirements or whether the tree species information is consistent with the afforestation operation design. If they do not meet the requirements or are inconsistent, the boundary is corrected again.

4. The compliance screening method for afforestation carbon sink projects according to claim 1, characterized in that, The process of identifying vegetation types and tree species within the afforestation project area based on remote sensing image data, after filtering through land change survey data, includes: First, based on remote sensing image data, the normalized vegetation index range and texture characteristics within the afforestation project area selected as forest land by land change survey data are statistically analyzed. Then, tree species information and vegetation type are determined based on the normalized vegetation index range and texture features.

5. The compliance screening method for afforestation carbon sink projects according to any one of claims 1-4, characterized in that, The screening of all afforestation carbon sink projects within the development area includes: Obtain the operation design and acceptance documents of afforestation projects in previous years within the development area of ​​the afforestation carbon sink project, and select afforestation projects for protective forests, special purpose forests and timber forests based on the operation design and acceptance documents.

6. The compliance screening method for afforestation carbon sink projects according to any one of claims 1-4, characterized in that, The data format of the land use change survey data is: a vector area layer, whose attribute fields contain explicit land use type information to identify the land use attributes of the map patches.

7. The compliance screening method for afforestation carbon sink projects according to any one of claims 1-4, characterized in that, The high-resolution remote sensing image data source can be Gaofen-1, Gaofen-2, or Ziyuan-1.

8. A compliance screening system for afforestation carbon sink projects based on multi-source data fusion, comprising at least a microprocessor and a memory, characterized in that, The microprocessor is programmed or configured to perform the steps of the afforestation carbon sink project compliance screening method based on multi-source data fusion as described in any one of claims 1 to 4, or the memory stores a computer program programmed or configured to perform the afforestation carbon sink project compliance screening method based on multi-source data fusion as described in any one of claims 1 to 4.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that is programmed or configured to perform the afforestation carbon sink project compliance screening method based on multi-source data fusion as described in any one of claims 1 to 4.

Images