Method and system for evaluating mangrove restoration effectiveness based on ecology and service function

Abstract

This invention discloses a method and system for evaluating the effectiveness of mangrove restoration based on ecological and service functions. First, a map model is constructed based on the mangrove area, and the model is divided into multi-level regions according to the restoration area and progress. Vegetation characteristics are analyzed in each level of region using remote sensing data to determine positive migration routes for vegetation. Bird community information is statistically analyzed using UAV imagery to assess changes in bird community characteristics and evaluate positive migration routes. Simultaneously, soil and water environment assessments are conducted to define changes in ecosystem service functions. Then, the overlap rate of migration routes for birds, vegetation, and ecosystem service functions is calculated, and the consistency of migration change characteristics is evaluated. Finally, the evaluation results are mapped to different level regions to generate guidance information for restoration areas. This invention achieves scientific evaluation and precise guidance of mangrove restoration effectiveness through comprehensive analysis of the migration paths of multiple ecological elements.

Description

Technical Field

[0001] This invention relates to the field of ecological restoration, and more specifically, to a method and system for evaluating the effectiveness of mangrove restoration based on ecological and service functions. Background Technology

[0002] As one of the three typical coastal ecosystems, mangroves play a vital role in protecting dikes and banks, preventing wind and waves, purifying seawater, maintaining biodiversity, sequestering and storing carbon, and promoting ecotourism. Their ecological value and service functions have been widely recognized by all sectors of society. In the last century, with population growth and socio-economic development, activities such as land reclamation, aquaculture, and land reclamation in coastal areas led to a significant shrinkage of mangrove areas in my country and a severe decline in their ecosystem service functions.

[0003] However, existing assessment methods lack scientifically effective standards for evaluating the effectiveness of ecological restoration. Furthermore, the large scale and high cost of some afforestation projects have raised concerns about whether these substantial investments have truly achieved the expected restoration results. Therefore, developing easily accessible and operational effectiveness monitoring technologies and constructing a scientifically sound and applicable mangrove ecological restoration effectiveness assessment system has become a crucial task. In addition, existing technologies suffer from several problems: excessive focus on the mangrove plant community itself, lack of evaluation of mangrove ecosystem service functions, complex and difficult-to-operate indicator systems, and limited availability of some indicators. These limitations prevent the scientific and objective reflection of the implementation effects and ecological restoration achievements of mangrove ecological restoration work, hindering efficient work guidance and assessment. Moreover, existing technologies often lack multi-dimensional analysis of ecological characteristic changes, such as changes in bird community characteristics and vegetation features, and lack methods for analyzing the evolution trends of ecological characteristics in multiple regions. This makes it difficult to analyze the positive impacts of restoration projects in specific areas and achieve a comprehensive assessment of mangrove ecosystem service functions. Summary of the Invention

[0004] This invention overcomes the shortcomings of existing technologies and proposes a method and system for evaluating the effectiveness of mangrove restoration based on ecological and service functions.

[0005] The first aspect of this invention provides a method for evaluating the effectiveness of mangrove restoration based on ecological and service functions, comprising:

[0006] S11: Construct a 3D map model based on the target mangrove area information;

[0007] S12: Based on the target mangrove restoration area and restoration progress, divide the mangrove area in the map model to form a multi-level area;

[0008] S13: Using remote sensing data of the target mangrove area, vegetation characteristics are analyzed for each level of area, and the forward migration route of vegetation is analyzed by the direction of vegetation characteristic changes.

[0009] S14: Acquire image sets for each level of region using drones, collect bird community information, analyze the changing characteristics of bird communities in each level of region, and assess bird forward migration routes;

[0010] S15: The monitoring unit conducts soil and water environment assessments for each level of region and sets out the path of change in ecosystem service functions based on changes in ecological characteristics.

[0011] S16: Calculate the overlap rate of bird forward migration routes, vegetation forward migration routes and ecosystem service function change routes. The overlap rate calculation is carried out by decomposing the two routes into N short paths to assess the consistency of migration change characteristics and obtain the first overlap rate and the second overlap rate. The first overlap rate and the second overlap rate are weighted and averaged to assess the restoration effectiveness.

[0012] S17: In the map model, in the consistency assessment of migration change characteristics based on N short paths, the repair effectiveness assessment is mapped to different levels of areas, and repair area guidance information is generated.

[0013] In this solution, S11 specifically includes:

[0014] Acquire information about the target mangrove area, including regional model data of the mangrove based on GIS technology and remote sensing imagery, and information on the progress of restoration projects;

[0015] A map model based on 3D visualization is constructed using regional information.

[0016] In this solution, S12 includes:

[0017] Based on the target mangrove restoration area and restoration progress, the mangrove area is divided into primary, secondary and tertiary areas in the map model;

[0018] In different levels of regions, including multiple unit regions, the repair progress is consistent for each level of region;

[0019] There are multiple areas classified as Level 1, Level 2, and Level 3.

[0020] In this solution, S13 specifically refers to:

[0021] High-resolution geographic remote sensing data of the target mangrove area is obtained, and vegetation information, including NDVI index, total vegetation coverage, and specific plant coverage, is calculated based on the manganese nodule map model of the remote sensing data.

[0022] Vegetation is calculated for each level of region, and the vegetation information is weighted by multiple parameters to obtain a comprehensive vegetation characteristic value.

[0023] Based on the comprehensive vegetation characteristic value, the rate of change of the comprehensive vegetation characteristic value in adjacent areas of different levels is analyzed. If the rate of change is greater than the preset slope and is a positive change, the adjacent area is set as a waypoint, and the positive migration direction in the adjacent area is set based on the positive change direction.

[0024] In the map model, vegetation change path analysis is performed using a two-dimensional planar layer of the region. By combining obstacle information, the third-level region is set as the starting point, and the nearest first-level region of the third-level region is set as the ending point. Combining waypoints and forward migration direction, path search is performed based on the A* shortest path algorithm, and the resulting path is used as the forward migration route of vegetation.

[0025] In this solution, S14 specifically refers to:

[0026] Within a preset acquisition period, images of each region are acquired by drone, and the images are preprocessed by grayscale conversion, noise reduction, and enhancement.

[0027] An image recognition module was introduced to identify and count bird flocks in the image set, with birds as key indicator organisms, and to count bird richness, abundance, Shannon-Weiner diversity index and activity.

[0028] A multi-dimensional community feature vector is generated based on richness, abundance, Shannon-Weiner diversity index, and activity.

[0029] Based on the ideal community characteristics of bird flocks, a target feature vector is defined;

[0030] By introducing Mahalanobis distance, the distance between the community feature vector and the expected feature vector of each level region is calculated to obtain the bird flock deviation value. A certain region is marked as the current region. The difference between the bird flock deviation value of the current region and the adjacent regions in the preset direction is calculated. The direction of the adjacent region with the largest positive difference is marked as the bird flock migration direction of the current region.

[0031] Calculate the migration direction of bird flocks in each region;

[0032] A starting point is set in the map model. The bird flock moves to the next area based on the migration direction of the bird flock in the starting point area. The area movement is repeated and the route is recorded until the route reaches the preset length or map boundary conditions, thus forming the bird flock migration path.

[0033] In this solution, S15 specifically refers to:

[0034] The monitoring unit conducts soil and water environment assessments for each level of area. The soil and water environment assessment includes testing soil pH, organic matter content, nutrient content, dissolved oxygen, chemical oxygen demand, and ammonia nitrogen content parameters, and comparing soil and water parameters with expected parameters to obtain the assessment results for each level of area.

[0035] Based on the assessment results, a repair index is set for each level of region, and the path cost for each level of region is set based on the repair index.

[0036] In the map model, path analysis is performed on a two-dimensional planar layer of the region. A starting point is set, and one or more regions with the largest restoration index are used as the endpoint. Combining path cost, path planning is performed based on the A* shortest path algorithm, and the obtained shortest path is marked as the route of ecological service function change.

[0037] In this solution, S16 specifically refers to:

[0038] From the bird migration routes and the routes of changes in ecosystem service functions, the two routes with the closest endpoints are selected for calculation;

[0039] Based on the two routes, each is decomposed into N short paths of equal distance. The two short paths are compared in direction N times, and the average directional deviation is calculated to obtain the first deviation rate.

[0040] The number of overlapping regions at each level traversed in the two routes is analyzed. The consistency of migration change characteristics is evaluated by the first deviation rate and the number of overlapping regions, and the first overlap rate is calculated.

[0041] The overlap rate between the positive migration route of vegetation and the route of change in ecosystem service function was calculated by video recording, and a second overlap rate was obtained.

[0042] In this solution, S17 specifically refers to:

[0043] In the map model, in the consistency assessment of migration and change characteristics based on N short paths, the comparison of the short path directions and the number of overlapping areas of the route are mapped to the restoration effectiveness assessment of different levels of areas. The restoration effectiveness of mangroves based on bird ecology and vegetation restoration effectiveness are assessed according to the first overlap rate and the second overlap rate, and restoration area guidance information is generated.

[0044] A second aspect of the present invention also provides a mangrove restoration effectiveness evaluation system based on ecological and service functions. The system includes: a memory, a processor, and a data interface. The memory includes a mangrove restoration effectiveness evaluation program based on ecological and service functions. When executed by the processor, the mangrove restoration effectiveness evaluation program based on ecological and service functions performs the following steps:

[0045] S11: Construct a 3D map model based on the target mangrove area information;

[0046] S12: Based on the target mangrove restoration area and restoration progress, divide the mangrove area in the map model to form a multi-level area;

[0047] S13: Using remote sensing data of the target mangrove area, vegetation characteristics are analyzed for each level of area, and the forward migration route of vegetation is analyzed by the direction of vegetation characteristic changes.

[0048] S14: Acquire image sets for each level of region using drones, collect bird community information, analyze the changing characteristics of bird communities in each level of region, and assess bird forward migration routes;

[0049] S15: The monitoring unit conducts soil and water environment assessments for each level of region and sets out the path of change in ecosystem service functions based on changes in ecological characteristics.

[0050] S16: Calculate the overlap rate of bird forward migration routes, vegetation forward migration routes and ecosystem service function change routes. The overlap rate calculation is carried out by decomposing the two routes into N short paths to assess the consistency of migration change characteristics and obtain the first overlap rate and the second overlap rate. The first overlap rate and the second overlap rate are weighted and averaged to assess the restoration effectiveness.

[0051] S17: In the map model, in the consistency assessment of migration change characteristics based on N short paths, the repair effectiveness assessment is mapped to different levels of areas, and repair area guidance information is generated.

[0052] A third aspect of the present invention also provides a computer-readable storage medium comprising a mangrove restoration effectiveness evaluation program based on ecological and service functions, wherein when the mangrove restoration effectiveness evaluation program based on ecological and service functions is executed by a processor, it implements the steps of the mangrove restoration effectiveness evaluation method based on ecological and service functions as described in any of the preceding claims.

[0053] This invention discloses a method and system for evaluating the effectiveness of mangrove restoration based on ecological and service functions. First, a map model is constructed based on the mangrove area, and the model is divided into multi-level regions according to the restoration area and progress. Vegetation characteristics are analyzed in each level of region using remote sensing data to determine positive migration routes for vegetation. Bird community information is statistically analyzed using UAV imagery to assess changes in bird community characteristics and evaluate positive migration routes. Simultaneously, soil and water environment assessments are conducted to define changes in ecosystem service functions. Then, the overlap rate of migration routes for birds, vegetation, and ecosystem service functions is calculated, and the consistency of migration change characteristics is evaluated. Finally, the evaluation results are mapped to different level regions to generate guidance information for restoration areas. This invention achieves scientific evaluation and precise guidance of mangrove restoration effectiveness through comprehensive analysis of the migration paths of multiple ecological elements. Attached Figure Description

[0054] Figure 1 A flowchart of a mangrove restoration effectiveness evaluation method based on ecological and service functions according to the present invention is shown;

[0055] Figure 2 The flowchart of the vegetation characteristic change analysis of the present invention is shown;

[0056] Figure 3 A block diagram of a mangrove restoration effectiveness evaluation system based on ecological and service functions according to the present invention is shown. Detailed Implementation

[0057] To better understand the above-mentioned objectives, features, and advantages of the present invention, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. It is understood that, unless otherwise specified, the embodiments and features described in these embodiments can be combined with each other.

[0058] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and therefore the scope of protection of the invention is not limited to the specific embodiments disclosed below.

[0059] Figure 1 The flowchart of a mangrove restoration effectiveness evaluation method based on ecological and service functions according to the present invention is shown.

[0060] like Figure 1 As shown, the first aspect of this invention provides a method for evaluating the effectiveness of mangrove restoration based on ecological and service functions, comprising:

[0061] S11: Construct a 3D map model based on the target mangrove area information;

[0062] S12: Based on the target mangrove restoration area and restoration progress, divide the mangrove area in the map model to form a multi-level area;

[0063] S13: Using remote sensing data of the target mangrove area, vegetation characteristics are analyzed for each level of area, and the forward migration route of vegetation is analyzed by the direction of vegetation characteristic changes.

[0064] S14: Acquire image sets for each level of region using drones, collect bird community information, analyze the changing characteristics of bird communities in each level of region, and assess bird forward migration routes;

[0065] S15: The monitoring unit conducts soil and water environment assessments for each level of region and sets out the path of change in ecosystem service functions based on changes in ecological characteristics.

[0066] S16: Calculate the overlap rate of bird forward migration routes, vegetation forward migration routes and ecosystem service function change routes. The overlap rate calculation is carried out by decomposing the two routes into N short paths to assess the consistency of migration change characteristics and obtain the first overlap rate and the second overlap rate. The first overlap rate and the second overlap rate are weighted and averaged to assess the restoration effectiveness.

[0067] S17: In the map model, in the consistency assessment of migration change characteristics based on N short paths, the repair effectiveness assessment is mapped to different levels of areas, and repair area guidance information is generated.

[0068] According to an embodiment of the present invention, step S11 specifically includes:

[0069] Acquire information about the target mangrove area, including regional model data of the mangrove based on GIS technology and remote sensing imagery, and information on the progress of restoration projects;

[0070] A map model based on 3D visualization is constructed using regional information.

[0071] It is understandable that restoration project progress information includes the restoration area and the restoration progress. Generally speaking, mangrove restoration projects are relatively long-term. During the restoration process, there are unrestored areas, restored areas, and areas under restoration. Areas at different progress levels often have certain differences in ecological and service functions. This invention proposes a multi-dimensional information characteristic difference analysis method based on ecological and service functions, combined with the comprehensive characteristic difference analysis of mangroves, such as differences in bird flock characteristics, vegetation characteristics, and ecological restoration characteristics, to assess the positive migration characteristics of different areas. This migration characteristic can effectively reflect the regional changes in the restoration effect, thereby assessing the changing trend of ecological service functions in different mangrove restoration areas, and achieving rapid and efficient analysis of differences from the expected restoration status, thus guiding the restoration project and achieving positive restoration feedback.

[0072] According to an embodiment of the present invention, S12 includes:

[0073] Based on the target mangrove restoration area and restoration progress, the mangrove area is divided into primary, secondary and tertiary areas in the map model;

[0074] In different levels of regions, including multiple unit regions, the repair progress is consistent for each level of region;

[0075] There are multiple areas classified as Level 1, Level 2, and Level 3.

[0076] Understandably, based on the progress of the restoration project, the overall mangrove area can be divided into multiple first-level, second-level, and third-level areas. Each area is a unit area, corresponding to a level, and the restoration progress of areas of the same level remains consistent.

[0077] Figure 2 The flowchart of the vegetation characteristic change analysis of the present invention is shown.

[0078] According to an embodiment of the present invention, step S13 specifically includes:

[0079] High-resolution geographic remote sensing data of the target mangrove area is obtained, and vegetation information, including NDVI index, total vegetation coverage, and specific plant coverage, is calculated based on the manganese nodule map model of the remote sensing data.

[0080] Vegetation is calculated for each level of region, and the vegetation information is weighted by multiple parameters to obtain a comprehensive vegetation characteristic value.

[0081] Based on the comprehensive vegetation characteristic value, the rate of change of the comprehensive vegetation characteristic value in adjacent areas of different levels is analyzed. If the rate of change is greater than the preset slope and is a positive change, the adjacent area is set as a waypoint, and the positive migration direction in the adjacent area is set based on the positive change direction.

[0082] In the map model, vegetation change path analysis is performed using a two-dimensional planar layer of the region. By combining obstacle information, the third-level region is set as the starting point, and the nearest first-level region of the third-level region is set as the ending point. Combining waypoints and forward migration direction, path search is performed based on the A* shortest path algorithm, and the resulting path is used as the forward migration route of vegetation.

[0083] Here, obstacle information is typically based on the topography and geological information related to mangroves to define the obstacles to ecological functions. In migration path analysis, since only the migration of ecological characteristics and service functions at the planar level is involved, a two-dimensional planar layer analysis of the region can be used, i.e., path analysis is performed in a two-dimensional plane, eliminating the analysis of the height dimension. To address the path simulation needs of different regions, the planning requirements for waypoints have been improved. In the positive migration route of vegetation, it includes waypoints, and the path direction of the waypoints must be consistent with the positive migration direction. The obtained positive migration routes of vegetation can effectively reflect the migration direction of the positive ecological impact of vegetation service functions on different mangrove regions and ecological ranges at different stages. Generally, the migration direction should be from higher-level areas to lower-level areas, which aligns with the expected project. Through actual vegetation characteristic analysis and migration simulation calculations, the actual migration direction can be compared with the expected direction to determine the restoration effectiveness and achieve regionalized vegetation impact effectiveness assessment, improving the effectiveness of project evaluation. Here, M tertiary regions can be selected as starting points for the study, setting M starting points, ultimately resulting in M ​​paths. In subsequent comparative path analysis, generally speaking, the shortest path can be selected for comparison. For example, in the comparison between the ecosystem service function change route and the bird forward migration route, the two routes with the shortest destination distance can be selected for comparison. The same principle applies to the comparison between the vegetation forward migration route and the ecosystem service function change route.

[0084] Adjacent areas of different levels are selected by filtering out two geographically adjacent areas that are of different levels, such as level one and level two. The starting and ending points are generally set based on the highest-level and lowest-level areas.

[0085] It is understood that the specific plant proportion can be calculated by statistically analyzing the characteristic spectra of multispectral remote sensing data and calculating the vegetation proportion (or coverage). The specific spectrum is the spectrum corresponding to a certain plant in the mangrove ecosystem. This plant is generally an important tree in the mangrove and can be set by the user. The corresponding spectral data is obtained based on the plant type.

[0086] The weighting values ​​for NDVI index, total vegetation coverage, and specific plant coverage can be 2:1:2, with NDVI index and specific plant coverage as the core references for vegetation characteristic analysis.

[0087] According to an embodiment of the present invention, step S14 specifically includes:

[0088] Within a preset acquisition period, images of each region are acquired by drone, and the images are preprocessed by grayscale conversion, noise reduction, and enhancement.

[0089] An image recognition module was introduced to identify and count bird flocks in the image set, with birds as key indicator organisms, and to count bird richness, abundance, Shannon-Weiner diversity index and activity.

[0090] A multi-dimensional community feature vector is generated based on richness, abundance, Shannon-Weiner diversity index, and activity.

[0091] Based on the ideal community characteristics of bird flocks, a target feature vector is defined;

[0092] By introducing Mahalanobis distance, the distance between the community feature vector and the expected feature vector of each level region is calculated to obtain the bird flock deviation value. A certain region is marked as the current region. The difference between the bird flock deviation value of the current region and the adjacent regions in the preset direction is calculated. The direction of the adjacent region with the largest positive difference is marked as the bird flock migration direction of the current region.

[0093] Calculate the migration direction of bird flocks in each region;

[0094] A starting point is set in the map model. The bird flock moves to the next area based on the migration direction of the bird flock in the starting point area. The area movement is repeated and the route is recorded until the route reaches the preset length or map boundary conditions, thus forming the bird flock migration path.

[0095] Understandably, in general, the various levels of regions in a map model can be divided into grids, meaning there are four migration directions: up, down, left, and right. These are preset directions. Furthermore, based on the unit regions in the four directions as adjacent regions, the difference between the bird flock deviation values ​​of the adjacent regions and the current region is evaluated. If the difference is positive, it means that the unit region in the corresponding direction is the possible migration direction of the bird flock in the current region. Here, the direction represented by the adjacent region with the largest positive value is selected as the migration direction of the bird flock in the current region.

[0096] When calculating the difference between the bird flock deviation value of the current area and the adjacent area in the preset direction, the difference is calculated based on the result of (adjacent area - current area) to determine whether it is positive or negative. Here, the starting point of the bird's forward migration route and the ecological service function change route can be set to be consistent and used in the same way. The starting point setting in S13 can be adopted, that is, using the three-level area as the starting point. The number of starting points can be set by the user.

[0097] It is important to understand that this invention uses birds as indicator organisms. Bird community characteristics are represented numerically and vector-wise by richness, abundance, Shannon-Weiner diversity index, and activity. However, existing technologies often use single-dimensional data for comparison based on community characteristics, resulting in weak comprehensive analysis capabilities and difficulty in assessing positive changes in community characteristics. This makes it difficult to analyze the positive impact of restoration projects within the region. Therefore, this invention uses feature vectors for distance calculation, sets a (idealized feature) benchmark vector for evaluation, analyzes the feature deviation values ​​of each unit area, and further infers the migration direction of each area. The greater the positive change in the deviation value, the greater the migration probability. Based on this, a positive impact path analysis of bird flocks is performed on the third-level region (the restored area), obtaining the positive change route based on bird flock characteristic analysis.

[0098] Understandably, the image recognition module can be an algorithm module such as the YOLOv5 algorithm for fast object recognition, used for bird identification and flock statistics in image sets. Activity can be characterized based on the frequency of bird activity in the monitored area over a certain period.

[0099] According to an embodiment of the present invention, S15 specifically includes:

[0100] The monitoring unit conducts soil and water environment assessments for each level of area. The soil and water environment assessment includes testing soil pH, organic matter content, nutrient content, dissolved oxygen, chemical oxygen demand, and ammonia nitrogen content parameters, and comparing soil and water parameters with expected parameters to obtain the assessment results for each level of area.

[0101] Based on the assessment results, a repair index is set for each level of region, and the path cost for each level of region is set based on the repair index.

[0102] In the map model, path analysis is performed on a two-dimensional planar layer of the region. A starting point is set, and one or more regions with the largest restoration index are used as the endpoint. Combining path cost, path planning is performed based on the A* shortest path algorithm, and the obtained shortest path is marked as the route of ecological service function change.

[0103] Understandably, a higher restoration index indicates a better state of the soil and water environment, a lower deviation from expected parameters, and consequently, a lower path cost. Each region level represents a different grade of unit area. Multiple endpoints can be set, ultimately forming multiple pathways for changes in ecosystem service functions.

[0104] In addition, since soil and water environmental data are the most direct parameters reflecting ecosystem service functions, this embodiment uses the simplest path cost form to simulate the path, which can obtain the environmental change migration path that matches the actual ecological situation, that is, the ecosystem service function change route. This route reflects the positive change direction of the actual ecological environment impact, and can be used for subsequent comparison of ecological migration and evaluation of restoration effectiveness.

[0105] According to an embodiment of the present invention, step S16 specifically includes:

[0106] From the bird migration routes and the routes of changes in ecosystem service functions, the two routes with the closest endpoints are selected for calculation;

[0107] Based on the two routes, each is decomposed into N short paths of equal distance. The two short paths are compared in direction N times, and the average directional deviation is calculated to obtain the first deviation rate.

[0108] The number of overlapping regions at each level traversed in the two routes is analyzed. The consistency of migration change characteristics is evaluated by the first deviation rate and the number of overlapping regions, and the first overlap rate is calculated.

[0109] The overlap rate between the positive migration route of vegetation and the route of change in ecosystem service function was calculated by video recording, and a second overlap rate was obtained.

[0110] Understandably, this comparison of bird migration routes and ecosystem service function changes can be conducted by selecting multiple routes with similar endpoint distances and then equalizing the overlap rate for analysis. The number of overlapping regions is the total number of regions that overlap.

[0111] In the calculation of bird migration routes and ecosystem service function change routes, the two routes with the closest endpoint distances are selected. Specifically, the bird migration route with the shortest endpoint distance is compared with the ecosystem service function change route to characterize the overall route overlap. The comparative analysis of vegetation migration routes is similar, and the calculation of the overlap of vegetation migration routes is consistent with the calculation of bird migration routes and ecosystem service function change routes. Here, each route is decomposed into N short paths of equal distance. Specifically, the two routes are decomposed into N short paths of equal length. In the overlap analysis, the direction deviation analysis is performed based on the first to Nth short paths of the two routes. The direction deviation analysis is specifically calculated based on the deviation formed by the direction between the start and end points of the short paths.

[0112] The first and second overlap rates are weighted and averaged with a default weight ratio of 2:1, using bird migration assessment as the primary indicator. The higher the first and second overlap rates, the closer the bird community characteristics and vegetation ecosystem service functions are to expectations.

[0113] The first and second overlap rates are calculated as follows:

[0114] ;

[0115] Where C is the overlap rate. Represents the number of repeating regions. This represents the first deviation rate (i.e., the average directional deviation). The directional deviation of the i-th short path can be reflected by the deviation angle. k1 and k2 represent preset correction coefficients used to correct the analysis weight of bird forward migration routes and vegetation forward migration routes. N is the number of short paths.

[0116] According to an embodiment of the present invention, step S17 specifically includes:

[0117] In the map model, in the consistency assessment of migration and change characteristics based on N short paths, the comparison of the short path directions and the number of overlapping areas of the route are mapped to the restoration effectiveness assessment of different levels of areas. The restoration effectiveness of mangroves based on bird ecology and vegetation restoration effectiveness are assessed according to the first overlap rate and the second overlap rate, and restoration area guidance information is generated.

[0118] Here, by comparing the direction of the short path with the number of overlapping areas of the route, we can understand the overlap of the migration direction (bird flock characteristics or vegetation characteristics) of the corresponding area in each short path, and ensure consistency with the migration direction. We can also mark the unit area where the short path is located with certain restoration effectiveness and provide guidance for restoration projects. For areas with higher effectiveness, we can promote the project. For areas with lower effectiveness, we can adjust monitoring resources to monitor repeated data and adjust the restoration plan to effectively guide the restoration work and provide positive feedback to improve the restoration effect.

[0119] Figure 3 A block diagram of a mangrove restoration effectiveness evaluation system based on ecological and service functions according to the present invention is shown.

[0120] A second aspect of the present invention also provides a mangrove restoration effectiveness evaluation system based on ecological and service functions. The system includes: a memory 101, a processor 103, and a data interface 102. The data interface is used to connect to a user terminal and to send mangrove restoration effectiveness evaluation data to the user terminal and store interactive information. The memory includes a mangrove restoration effectiveness evaluation program based on ecological and service functions. When the processor executes the mangrove restoration effectiveness evaluation program based on ecological and service functions, it performs the following steps:

[0121] S11: Construct a 3D map model based on the target mangrove area information;

[0122] S12: Based on the target mangrove restoration area and restoration progress, divide the mangrove area in the map model to form a multi-level area;

[0123] S13: Using remote sensing data of the target mangrove area, vegetation characteristics are analyzed for each level of area, and the forward migration route of vegetation is analyzed by the direction of vegetation characteristic changes.

[0124] S14: Acquire image sets for each level of region using drones, collect bird community information, analyze the changing characteristics of bird communities in each level of region, and assess bird forward migration routes;

[0125] S15: The monitoring unit conducts soil and water environment assessments for each level of region and sets out the path of change in ecosystem service functions based on changes in ecological characteristics.

[0126] S16: Calculate the overlap rate of bird forward migration routes, vegetation forward migration routes and ecosystem service function change routes. The overlap rate calculation is carried out by decomposing the two routes into N short paths to assess the consistency of migration change characteristics and obtain the first overlap rate and the second overlap rate. The first overlap rate and the second overlap rate are weighted and averaged to assess the restoration effectiveness.

[0127] S17: In the map model, in the consistency assessment of migration change characteristics based on N short paths, the repair effectiveness assessment is mapped to different levels of areas, and repair area guidance information is generated.

[0128] When the system is running, it can implement all the steps of a mangrove restoration effectiveness evaluation method based on ecological and service functions, as described above.

[0129] A third aspect of the present invention also provides a computer-readable storage medium comprising a mangrove restoration effectiveness evaluation program based on ecological and service functions, wherein when the mangrove restoration effectiveness evaluation program based on ecological and service functions is executed by a processor, it implements the steps of the mangrove restoration effectiveness evaluation method based on ecological and service functions as described in any of the preceding claims.

[0130] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are merely illustrative. For example, the division of units is only a logical functional division, and in actual implementation, there may be other division methods, such as: multiple units or components can be combined, or integrated into another system, or some features can be ignored or not executed. In addition, the coupling, direct coupling, or communication connection between the various components shown or discussed can be through some interfaces, and the indirect coupling or communication connection between devices or units can be electrical, mechanical, or other forms.

[0131] The units described above as separate components may or may not be physically separate. The components shown as units may or may not be physical units. They may be located in one place or distributed across multiple network units. Some or all of the units may be selected to achieve the purpose of this embodiment according to actual needs.

[0132] In addition, in the various embodiments of the present invention, each functional unit can be integrated into one processing unit, or each unit can be a separate unit, or two or more units can be integrated into one unit; the integrated unit can be implemented in hardware or in the form of hardware plus software functional units.

[0133] Those skilled in the art will understand that all or part of the steps of the above method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When the program is executed, it performs the steps of the above method embodiments. The aforementioned storage medium includes various media capable of storing program code, such as mobile storage devices, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0134] Alternatively, if the integrated units of this invention are implemented as software functional modules and sold or used as independent products, they can also be stored in a computer-readable storage medium. Based on this understanding, the technical solutions of the embodiments of this invention, or the parts that contribute to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the methods described in the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as mobile storage devices, ROM, RAM, magnetic disks, or optical disks.

[0135] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for evaluating the effectiveness of mangrove restoration based on ecological and service functions, characterized in that, include: S11: Construct a 3D map model based on the target mangrove area information; S12: Based on the target mangrove restoration area and restoration progress, divide the mangrove area in the map model to form a multi-level area; S13: Using remote sensing data of the target mangrove area, vegetation characteristics are analyzed for each level of area, and the forward migration route of vegetation is analyzed by the direction of vegetation characteristic changes. S14: Acquire image sets for each level of region using drones, collect bird community information, analyze the changing characteristics of bird communities in each level of region, and assess bird forward migration routes; S15: The monitoring unit conducts soil and water environment assessments for each level of region and sets out the path of change in ecosystem service functions based on changes in ecological characteristics. S16: Calculate the overlap rate of bird forward migration routes, vegetation forward migration routes and ecosystem service function change routes. The overlap rate calculation is carried out by decomposing the two routes into N short paths to assess the consistency of migration change characteristics and obtain the first overlap rate and the second overlap rate. The first overlap rate and the second overlap rate are weighted and averaged to assess the restoration effectiveness. S17: In the map model, in the consistency assessment of migration change characteristics based on N short paths, the repair effectiveness assessment is mapped to different levels of areas, and repair area guidance information is generated. Specifically, S16 is as follows: From the bird migration routes and the routes of changes in ecosystem service functions, the two routes with the closest endpoints are selected for calculation; Based on the two routes, each is decomposed into N short paths of equal distance. The two short paths are compared in direction N times, and the average directional deviation is calculated to obtain the first deviation rate. The number of overlapping regions in each level of the two routes is analyzed. The consistency of migration change characteristics is evaluated by the first deviation rate and the number of overlapping regions, and the first overlap rate is calculated. The overlap rate between the positive migration route of vegetation and the route of change in ecosystem service function was calculated by video recording, and the second overlap rate was obtained. Specifically, S17 is as follows: In the map model, in the consistency assessment of migration and change characteristics based on N short paths, the comparison of the short path directions and the number of overlapping areas of the route are mapped to the restoration effectiveness assessment of different levels of areas. The restoration effectiveness of mangroves based on bird ecology and vegetation restoration effectiveness are assessed according to the first overlap rate and the second overlap rate, and restoration area guidance information is generated.

2. The method for evaluating the effectiveness of mangrove restoration based on ecological and service functions according to claim 1, characterized in that, S11 specifically includes: Acquire information about the target mangrove area, including regional model data of the mangrove based on GIS technology and remote sensing imagery, and information on the progress of restoration projects; A map model based on 3D visualization is constructed using regional information.

3. The method for evaluating the effectiveness of mangrove restoration based on ecological and service functions according to claim 1, characterized in that, S12 includes: Based on the target mangrove restoration area and restoration progress, the mangrove area is divided into primary, secondary and tertiary areas in the map model; In different levels of regions, including multiple unit regions, the repair progress is consistent for each level of region; There are multiple areas classified as Level 1, Level 2, and Level 3.

4. The method for evaluating the effectiveness of mangrove restoration based on ecological and service functions according to claim 1, characterized in that, Specifically, S13 is as follows: Acquire high-resolution geographic remote sensing data of the target mangrove area, and calculate vegetation information based on the remote sensing data and map model, including NDVI index, total vegetation coverage, and specific plant coverage. Vegetation is calculated for each level of region, and the vegetation information is weighted by multiple parameters to obtain a comprehensive vegetation characteristic value. Based on the comprehensive vegetation characteristic value, the rate of change of the comprehensive vegetation characteristic value in adjacent areas of different levels is analyzed. If the rate of change is greater than the preset slope and is a positive change, the adjacent area is set as a waypoint, and the positive migration direction in the adjacent area is set based on the positive change direction. In the map model, vegetation change path analysis is performed using a two-dimensional planar layer of the region. By combining obstacle information, the third-level region is set as the starting point, and the nearest first-level region of the third-level region is set as the ending point. Combining waypoints and forward migration direction, path search is performed based on the A* shortest path algorithm, and the resulting path is used as the forward migration route of vegetation.

5. The method for evaluating the effectiveness of mangrove restoration based on ecological and service functions according to claim 4, characterized in that, Specifically, S14 is as follows: Within a preset acquisition period, images of each region are acquired by drone, and the images are preprocessed by grayscale conversion, noise reduction, and enhancement. An image recognition module was introduced to identify and count bird flocks in the image set, with birds as key indicator organisms, and to count bird richness, abundance, Shannon-Weiner diversity index and activity. A multi-dimensional community feature vector is generated based on richness, abundance, Shannon-Weiner diversity index, and activity. Based on the ideal community characteristics of bird flocks, a target feature vector is defined; By introducing Mahalanobis distance, the distance between the community feature vector and the expected feature vector of each level region is calculated to obtain the bird flock deviation value. A certain region is marked as the current region. The difference between the bird flock deviation value of the current region and the adjacent regions in the preset direction is calculated. The direction of the adjacent region with the largest positive difference is marked as the bird flock migration direction of the current region. Calculate the migration direction of bird flocks in each level of region; A starting point is set in the map model. The bird flock moves to the next area based on the migration direction of the bird flock in the starting point area. The area movement is repeated and the route is recorded until the route reaches the preset length or map boundary conditions, thus forming the bird flock migration path.

6. The method for evaluating the effectiveness of mangrove restoration based on ecological and service functions according to claim 5, characterized in that, Specifically, S15 is: The monitoring unit conducts soil and water environment assessments for each level of area. The soil and water environment assessment includes testing soil pH, organic matter content, nutrient content, dissolved oxygen, chemical oxygen demand, and ammonia nitrogen content parameters, and comparing soil and water parameters with expected parameters to obtain the assessment results for each level of area. Based on the assessment results, a repair index is set for each level of region, and the path cost for each level of region is set based on the repair index. In the map model, path analysis is performed on a two-dimensional planar layer of the region. A starting point is set, and one or more regions with the largest restoration index are used as the endpoint. Combining path cost, path planning is performed based on the A* shortest path algorithm, and the obtained shortest path is marked as the route of ecological service function change.

7. A mangrove restoration effectiveness evaluation system based on ecological and service functions, characterized in that, The system includes: a memory, a processor, and a data interface. The memory includes a mangrove restoration effectiveness evaluation program based on ecological and service functions. When the processor executes the mangrove restoration effectiveness evaluation program based on ecological and service functions, it implements the steps of the mangrove restoration effectiveness evaluation method based on ecological and service functions as described in claim 1.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a mangrove restoration effectiveness evaluation program based on ecological and service functions. When the mangrove restoration effectiveness evaluation program based on ecological and service functions is executed by a processor, it implements the steps of the mangrove restoration effectiveness evaluation method based on ecological and service functions as described in any one of claims 1 to 6.

Images