A mangrove ecological restoration method based on low-altitude remote sensing and dynamic geomorphologic process

Abstract

The present application provides a kind of method for mangrove ecological restoration based on low-altitude remote sensing and dynamic geomorphology process, including the acquisition of remote sensing data of mangrove restoration area, mangrove tidal flat geomorphology elevation, hydrology, bottom material and climate data, the site selection of suitable forest land in restoration area is evaluated using AHP hierarchical evaluation model;And combined with the factors of power, deposition and geomorphology, the suitable tidal flat forest land is accurately selected and delimited;According to the site selection result, the plane design of mangrove ecological restoration is carried out;Through the mangrove-power-sediment-terrain coupling numerical model, the mangrove restoration process under different plane design conditions is simulated, and the restoration scheme is generated;According to the restoration scheme, the mangrove restoration area is restored.The present application improves the survival rate of mangrove seedlings and the stability of forest land by accurate site selection, restoration area planning and dynamic monitoring;Effectively solve the problems of low survival rate of seedlings, forest land space recession and other problems caused by disordered plane layout design of existing mangrove ecological restoration project.

Description

Technical Field

[0001] This invention relates to the field of wetland ecological restoration technology, and in particular to a mangrove ecological restoration method based on low-altitude remote sensing and dynamic geomorphological processes. Background Technology

[0002] Mangroves, composed mainly of evergreen shrubs or trees, are an important part of tropical and subtropical coastlines, serving multiple ecological functions such as coastal protection, carbon sequestration and emission reduction, and biodiversity maintenance. In recent years, under the dual pressures of human activities and climate change, mangrove areas have decreased dramatically, necessitating strengthened ecological protection and restoration.

[0003] Mangrove ecological protection and restoration mainly includes mangrove vegetation restoration, seedling cultivation, post-disaster management, and monitoring and evaluation of restoration effects. Existing mangrove restoration methods are centered on afforestation techniques, focusing on the selection of suitable tidal flat environments, tree species selection and introduction, and cultivation techniques. The technical content mainly includes mangrove planting techniques, seedling cultivation techniques, pest control techniques, and effect monitoring and evaluation techniques.

[0004] However, existing mangrove restoration technologies neglect the self-recovery of mangroves and their feedback mechanism with dynamic geomorphology, especially the interaction between mangrove growth and development and coastal dynamic geomorphological processes such as hydrology, sedimentation and geomorphology, resulting in a survival rate of less than 20% for mangroves in ecological restoration projects.

[0005] Therefore, it is urgent to consider the feedback effect between mangroves and coastal dynamic geomorphological processes in order to improve the efficiency and effectiveness of mangrove ecological restoration. Summary of the Invention

[0006] To address the shortcomings of existing technologies, this invention provides a mangrove ecological restoration method based on low-altitude remote sensing and dynamic geomorphological processes. This invention can solve the technical problems of low seedling survival rate and forest space degradation caused by the disordered planar layout design of existing mangrove ecological restoration projects and the influence of coastal dynamics.

[0007] The technical solution of this invention is: a method for mangrove ecological restoration based on low-altitude remote sensing and dynamic geomorphological processes, comprising the following steps:

[0008] S1) Collect remote sensing data of mangrove restoration areas to form a data atlas of shoreline, aquaculture areas, mudflats and mangrove distribution in the restoration areas;

[0009] S2) Establish the elevation of mangrove tidal flat landforms in the mangrove restoration area;

[0010] S3) Collect hydrological, substrate, and climate data for mangrove restoration areas;

[0011] S4) Construct an AHP hierarchical evaluation model and use the data obtained in steps S1-S3) as indicators affecting the selection of suitable afforestation sites; use the AHP hierarchical evaluation model to evaluate the weight of each indicator and evaluate the site selection of suitable afforestation sites in the restoration area.

[0012] S5) Based on the ecological suitability analysis results of step S4), combined with dynamic, sedimentary and geomorphological factors, accurately select and delineate suitable tidal flat afforestation areas;

[0013] S6) Based on the site selection results of the tidal flats suitable for afforestation in step S5), determine the mangrove planting area according to the ecological suitability distribution map, and carry out the plan design for mangrove ecological restoration.

[0014] S7) Construct a coupled numerical model of mangrove-dynamic-sediment-topography; and simulate the mangrove restoration process under different planar design conditions using the coupled numerical model of mangrove-dynamic-sediment-topography, and generate restoration schemes;

[0015] S8) The mangrove restoration area is restored according to the restoration plan, and dynamic monitoring is carried out during the restoration process. The evolution of the habitat conditions of the mangrove restoration area is simulated by a coupled numerical model of mangrove-dynamic-sediment-topography. The hydrodynamic and sediment transport characteristics of the mangrove area are assessed, and the impact of mangroves on coastline stability and topographic evolution is analyzed. The restoration plan is adjusted in a timely manner based on monitoring data and simulation results, and the planting strategy is optimized to ensure the survival rate of mangrove seedlings and the spatial stability of the forest land.

[0016] Preferably, in step S1), the collected remote sensing data is preprocessed, including geometric correction, radiometric correction and atmospheric correction, to form a data atlas of shoreline, aquaculture area, mudflat and mangrove distribution in the restoration area.

[0017] Preferably, step S1) also includes acquiring data on land cover types and vegetation types in the mangrove restoration area, including woodland, open beaches, tidal flats, and water bodies; and analyzing the spatiotemporal distribution evolution of mangroves based on time-series data of the mangrove identification index to determine the process and trend of shoreline changes, mangrove distribution and area changes.

[0018] Preferably, in step S2), multiple aerial surveys of the restoration area are conducted using drones to obtain aerial survey data, and point cloud data, digital surface model data, and digital orthophoto datasets are generated based on the aerial survey data. The elevation of the mangrove tidal flat landform in the restoration area is obtained using ArcGIS software with the SFM algorithm.

[0019] Preferably, in step S2), point cloud data, digital surface model data, and digital orthophoto datasets are generated using aerial survey data, specifically including the following steps:

[0020] S211) Based on the acquired aerial survey image data and RTK positioning data, perform image registration and RTK correction to ensure high accuracy and consistency of the data;

[0021] S212) Using ArcGIS software, aerial survey images are processed through structured light SFM technology to generate high-density point cloud data;

[0022] S213) Based on the high-density point cloud data from step S212), digital surface model data is generated and orthorectified, and the aerial survey images are stitched together to form a high-resolution digital orthophoto.

[0023] Preferably, in step S2), the elevation of the mangrove tidal flat landform in the restoration area is obtained using ArcGIS software with the SFM algorithm, specifically including the following steps:

[0024] S221) The digital surface model generated in step S213) is subjected to elevation extraction and analysis to generate elevation contour maps and elevation distribution maps, and the elevation characteristics of mangrove tidal flat landforms are analyzed.

[0025] Preferably, in step S2), the drone is used to collect aerial survey data during a time period in spring or summer when the tide level is low and the angle of sunlight is suitable.

[0026] Preferably, in step S3), the hydrological data includes measurements of flow velocity, flow direction, wave height, wave period, water depth, sediment content, suspended sediment particle size, turbidity, and salinity.

[0027] Preferably, in step S3), the sediment data includes the determination of the particle size and composition of the surface sediments.

[0028] Preferably, in step S3), the climate data includes average temperature and precipitation.

[0029] Preferably, in step S4), the hierarchical evaluation model includes a target layer, a criterion layer, and a scheme layer; wherein, the output of the target layer is the optimal tidal flat suitable for afforestation; the indicators of the criterion layer include hydrological indicators, substrate indicators, geomorphological indicators, and climate indicators; and the scheme layer outputs the optional mangrove restoration areas of the target area.

[0030] Preferably, in step S4), the geomorphological indicators include tidal flat elevation and tidal flat evolution status.

[0031] Preferably, in step S4), the hierarchical evaluation model makes pairwise judgments based on the indicators of the criterion layer and uses Santy's 1-9 scale method to determine the weight of each criterion layer to the target layer; the site selection of suitable afforestation land in the tidal flats of the restoration area is evaluated through the weight assessment.

[0032] As a preferred option, in step S4), the evaluation results of the site selection for suitable afforestation land in the restoration area are divided into four categories: suitable, suitable, moderate and unsuitable.

[0033] Preferably, in step S6), the planar design for mangrove ecological restoration includes the design of planting density and arrangement.

[0034] Preferably, in step S7), a coupled numerical model of mangrove-dynamic-sediment-topography is constructed by introducing a viscous sediment diffusion equation that takes into account the mangrove effect; and the coupled numerical model of mangrove-dynamic-sediment-topography is verified by using the dynamic geomorphological data collected in steps S1-S3), simulating the mangrove restoration process under different planar design conditions, and generating restoration schemes.

[0035] Preferably, in step S7), the construction of the mangrove-dynamic-sediment-topography coupled numerical model specifically includes the following steps:

[0036] S71) Use the Delft3D Grid tool to generate a two-dimensional or three-dimensional computational grid for the mangrove restoration area. Determine the resolution and extent of the grid according to the size of the restoration area to ensure that the grid can fully describe the topographic features of the mangrove area.

[0037] S72) Based on the hydrological data obtained in step S3), set tidal, wave, and runoff boundary conditions, input tidal period, wave parameters, and flow data, and define open and closed boundaries.

[0038] S73) Set hydrodynamic parameters, including Manning roughness, wind field, and viscosity coefficient;

[0039] S74) Input wave parameters, including wave height, period and propagation direction, parameterize mangrove vegetation, add mangrove vegetation, and simulate the impact of mangroves on hydrodynamics by adjusting the roughness coefficient or introducing the vegetation resistance coefficient, and generalize the distribution range and density of mangrove areas.

[0040] S75) Set sediment parameters, including sediment particle size, initial sediment content, and sediment settling velocity, and perform coupled simulation;

[0041] S76) Simulates hydrodynamic, wave and sediment transport processes, outputs simulation results, including flow velocity and direction, wave height, sediment concentration, and topographic changes; compares measured data with simulation results.

[0042] Preferably, in step S8), the dynamic monitoring indicators include monitoring seedling survival rate, soil salinity, and hydrodynamic environment.

[0043] The beneficial effects of this invention are as follows:

[0044] 1. This invention improves the survival rate of mangrove seedlings and the stability of forest land through precise site selection, restoration area planning, and dynamic monitoring;

[0045] 2. This invention effectively solves the problems of low seedling survival rate and forest space degradation caused by the disorderly layout design of existing mangrove ecological restoration projects through the precise site selection and delineation of suitable afforestation areas in tidal flats. Attached Figure Description

[0046] Figure 1 This is a flowchart of the method of the present invention. Detailed Implementation

[0047] The specific embodiments of the present invention will be further described below with reference to the accompanying drawings:

[0048] like Figure 1 As shown, this embodiment provides a mangrove ecological restoration method based on low-altitude remote sensing and dynamic geomorphological processes, including the following steps:

[0049] S1) Collect multi-source, multi-temporal remote sensing data of mangrove restoration areas with cloud cover less than 10% to form a data atlas of shoreline, aquaculture area, mudflat and mangrove distribution in the restoration area;

[0050] In this embodiment, after acquiring remote sensing data, the collected remote sensing data also needs to be preprocessed. The preprocessing includes geometric correction, radiometric correction and atmospheric correction to form a data atlas of shoreline, aquaculture area, mudflat and mangrove distribution in the restoration area.

[0051] This embodiment also includes the acquisition of data on land cover types and vegetation types in the mangrove restoration area, including woodland, open beaches, tidal flats, and water bodies; and analyzes the spatiotemporal distribution evolution of mangroves based on time-series data of the mangrove identification index to determine the process and trend of shoreline changes, mangrove distribution and area changes.

[0052] S2) Establish the elevation of mangrove tidal flat landforms in the mangrove restoration area;

[0053] This embodiment utilizes drones to conduct multiple aerial surveys of the restoration area to acquire aerial survey data, and generates point cloud data, digital surface model data, and digital orthophoto datasets based on the acquired aerial survey data. The elevation of the mangrove tidal flat landform in the restoration area is obtained using ArcGIS software with the SFM algorithm.

[0054] In a preferred embodiment, generating point cloud data, digital surface model data, and digital orthophoto datasets using aerial survey data specifically includes the following steps:

[0055] S211) Based on the acquired aerial survey image data and RTK positioning data, perform image registration and RTK correction to ensure high accuracy and consistency of the data;

[0056] S212) Using ArcGIS software, aerial survey images are processed through structured light SFM technology to generate high-density point cloud data;

[0057] S213) Based on the high-density point cloud data from step S212), digital surface model data is generated and orthorectified, and the aerial survey images are stitched together to form a high-resolution digital orthophoto.

[0058] In a preferred embodiment, the elevation of the mangrove tidal flat landform in the restoration area is obtained using ArcGIS software with the SFM algorithm. Specifically, this includes: extracting and analyzing the elevation of the digital surface model generated in step S213), generating elevation contour maps and elevation distribution maps, and analyzing the elevation characteristics of the mangrove tidal flat landform.

[0059] In addition, in this embodiment, the drone is used to collect aerial survey data during spring or summer when the tide level is low and the angle of sunlight is suitable, and the drone's flight altitude is controlled to be 100-120m.

[0060] S3) Collect hydrological, sediment, and climate data for the mangrove restoration area; wherein the hydrological data includes measurements of flow velocity, flow direction, wave height, wave period, water depth, sediment concentration, suspended sediment particle size, turbidity, and salinity. The sediment data includes measurements of surface sediment particle size and composition. The climate data includes average temperature and precipitation.

[0061] S4) Use the data obtained in steps S1-S3) as indicators affecting the selection of suitable afforestation sites; and use the AHP (Analytic Hierarchy Process) to evaluate the weight of each indicator, construct a hierarchical evaluation model, and evaluate the site selection of suitable afforestation sites in the restoration area through the hierarchical evaluation model.

[0062] In this embodiment, the hierarchical evaluation model includes a target layer, a criterion layer, and a scheme layer. The output of the target layer is the optimal tidal flat suitable for afforestation. The indicators of the criterion layer include hydrological indicators, sediment indicators, geomorphological indicators, and climatic indicators. The geomorphological indicators include tidal flat elevation and tidal flat evolution status. The scheme layer outputs optional mangrove restoration areas within the target region.

[0063] The hierarchical evaluation model uses indicators at the criterion level to make pairwise judgments and employs Santy's 1-9 scale method to determine the weight of each criterion level to the target level; the weights are used to evaluate the site selection of suitable afforestation sites in the remediation area's tidal flats. The evaluation results of the site selection of suitable afforestation sites in the remediation area's tidal flats are divided into four categories: suitable, suitable, moderate, and unsuitable.

[0064] S5) Based on the ecological suitability analysis results of step S4), combined with dynamic, sedimentary and geomorphological factors, accurately select and delineate suitable tidal flat afforestation areas;

[0065] S6) Based on the site selection results of the tidal flat suitable for afforestation in step S5), determine the mangrove planting area according to the ecological suitability distribution map, carry out the plan design of mangrove ecological restoration, and design the planting density and arrangement.

[0066] S7) Constructing a coupled numerical model of mangrove-dynamic-sediment-topography; This embodiment constructs a coupled numerical model of mangrove-dynamic-sediment-topography by introducing a viscous sediment diffusion equation that considers the mangrove effect; and verifies the coupled numerical model of mangrove-dynamic-sediment-topography using the dynamic geomorphological data collected in steps S1-S3), simulating the mangrove restoration process under different planar design conditions, and generating restoration schemes. Specifically, it includes the following steps:

[0067] S71) Use the Delft3D Grid tool to generate a two-dimensional or three-dimensional computational grid for the mangrove restoration area. Determine the resolution and extent of the grid according to the size of the restoration area to ensure that the grid can fully describe the topographic features of the mangrove area.

[0068] S72) Based on the hydrological data obtained in step S3), set tidal, wave, and runoff boundary conditions, input tidal period, wave parameters, and flow data, and define open and closed boundaries.

[0069] S73) Set hydrodynamic parameters, including Manning roughness, wind field, and viscosity coefficient;

[0070] S74) Input wave parameters, including wave height, period and propagation direction, parameterize mangrove vegetation, add mangrove vegetation, and simulate the impact of mangroves on hydrodynamics by adjusting the roughness coefficient or introducing the vegetation resistance coefficient, and generalize the distribution range and density of mangrove areas.

[0071] S75) Set sediment parameters, including sediment particle size, initial sediment content, and sediment settling velocity, and perform coupled simulation;

[0072] S76) Simulates hydrodynamic, wave and sediment transport processes, outputs simulation results, including flow velocity and direction, wave height, sediment concentration, and topographic changes; compares measured data with simulation results.

[0073] S8) The mangrove restoration area is restored according to the restoration plan, and dynamic monitoring is carried out during the restoration process, including monitoring seedling survival rate, soil salinity, and hydrodynamic environment. The evolution of the habitat conditions in the mangrove restoration area is simulated by a coupled numerical model of mangrove-dynamic-sediment-topography, the hydrodynamic and sediment transport characteristics of the mangrove area are assessed, the impact of mangroves on coastline stability and topographic evolution is analyzed, and the restoration plan is adjusted in a timely manner based on monitoring data and simulation results to optimize planting strategies and ensure the survival rate of mangrove seedlings and the spatial stability of the forest land.

[0074] The embodiments and descriptions above are merely illustrative of the principles and preferred embodiments of the present invention. Various changes and modifications may be made to the present invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the present invention as claimed.

Claims

1. A method for mangrove ecological restoration based on low-altitude remote sensing and dynamic geomorphological processes, characterized in that, Includes the following steps: S1) Based on remote sensing data of the mangrove restoration area, a data atlas of shoreline, aquaculture area, mudflats and mangrove distribution in the restoration area is formed; S2) Establish the elevation of mangrove tidal flat landforms in the mangrove restoration area; S3) Collect hydrological, substrate, and climate data for mangrove restoration areas; S4) Construct an AHP hierarchical evaluation model and use the data obtained in steps S1-S3) as indicators affecting the selection of suitable afforestation sites; use the AHP hierarchical evaluation model to evaluate the weight of each indicator and assess the site selection of suitable afforestation sites in the restoration area. S5) Based on the ecological suitability analysis results of step S4), combined with dynamic, sedimentary and geomorphological factors, accurately select and delineate suitable tidal flat afforestation areas; S6) Based on the site selection results of the tidal flats suitable for afforestation in step S5), determine the mangrove planting area according to the ecological suitability distribution map, and carry out the plan design for mangrove ecological restoration. S7) Construct a coupled numerical model of mangrove-dynamic-sediment-topography; The mangrove restoration process under different planar design conditions was simulated using a coupled numerical model of mangrove-dynamic-sediment-topography, and restoration schemes were generated. S8) The mangrove restoration area is restored according to the restoration plan, and dynamic monitoring is carried out during the restoration process. The restoration plan is adjusted in a timely manner based on the monitoring data and simulation results, and the planting strategy is optimized.

2. The mangrove ecological restoration method based on low-altitude remote sensing and dynamic geomorphological processes according to claim 1, characterized in that: The remote sensing data collected in step S1) are processed by geometric correction, radiometric correction and atmospheric correction to form a data atlas of shoreline, aquaculture area, mudflat and mangrove distribution in the restoration area.

3. The mangrove ecological restoration method based on low-altitude remote sensing and dynamic geomorphological processes according to claim 1, characterized in that: Step S1) also includes acquiring data on land cover types and vegetation types in the mangrove restoration area; and analyzing the spatiotemporal distribution evolution of mangroves based on time series data of mangrove identification index to determine the process and trend of shoreline changes, mangrove distribution and area changes.

4. The mangrove ecological restoration method based on low-altitude remote sensing and dynamic geomorphological processes according to claim 1, characterized in that: In step S2), multiple aerial surveys of the restoration area are conducted using drones to obtain aerial survey data. Point cloud data, digital surface model data, and digital orthophoto datasets are generated based on the aerial survey data, and the elevation of the mangrove tidal flat landform in the restoration area is obtained.

5. The mangrove ecological restoration method based on low-altitude remote sensing and dynamic geomorphological processes according to claim 4, characterized in that: In step S2), point cloud data, digital surface models, and digital orthophoto datasets are generated using aerial survey data. This specifically includes the following steps: S211) Based on the acquired aerial survey image data and RTK positioning data, perform image registration and RTK correction to ensure high accuracy and consistency of the data; S212) Using ArcGIS software, aerial survey images are processed through structured light SFM technology to generate high-density point cloud data; S213) Based on the high-density point cloud data from step S212), a digital surface model is generated and orthorectified, and the aerial survey images are stitched together to form a high-resolution digital orthophoto.

6. The mangrove ecological restoration method based on low-altitude remote sensing and dynamic geomorphological processes according to claim 5, characterized in that: In step S2), elevation is extracted and analyzed using a digital surface model to generate elevation contour maps and elevation distribution maps, and the elevation characteristics of mangrove tidal flat landforms are analyzed.

7. The mangrove ecological restoration method based on low-altitude remote sensing and dynamic geomorphological processes according to claim 1, characterized in that: In step S3), the hydrological data includes measurements of flow velocity, flow direction, wave height, wave period, water depth, sediment concentration, suspended sediment particle size, turbidity, and salinity. The sediment data includes measurements of the grain size and composition of surface sediments; The climate data mentioned includes average temperature and precipitation.

8. The mangrove ecological restoration method based on low-altitude remote sensing and dynamic geomorphological processes according to claim 1, characterized in that: In step S4), the hierarchical evaluation model includes a target layer, a criterion layer, and a scheme layer; wherein, the output of the target layer is the optimal tidal flat suitable for afforestation; the indicators of the criterion layer include hydrological indicators, substrate indicators, geomorphological indicators, and climate indicators; and the scheme layer outputs the optional mangrove restoration areas of the target area. The hierarchical evaluation model uses indicators of the criterion layer to make pairwise judgments and uses Santy's 1-9 scale method to determine the weight of each criterion layer to the target layer; the site selection of suitable afforestation land in the restoration area is evaluated through weight assessment; the evaluation results of the site selection of suitable afforestation land in the restoration area are divided into four categories: suitable, suitable, moderate and unsuitable.

9. The mangrove ecological restoration method based on low-altitude remote sensing and dynamic geomorphological processes according to claim 1, characterized in that: In step S7), a coupled numerical model of mangrove-dynamic-sediment-topography is constructed by introducing a viscous sediment diffusion equation that takes into account the mangrove effect. The coupled numerical model of mangrove-dynamic-sediment-topography is verified by using the dynamic geomorphological data collected in steps S1-S3, simulating the mangrove restoration process under different planar design conditions, and generating restoration schemes.

10. A method for mangrove ecological restoration based on low-altitude remote sensing and dynamic geomorphological processes according to claim 9, characterized in that: In step S7), the construction of the coupled numerical model of mangrove-dynamic-sediment-topography specifically includes the following steps: S71) Use the Delft3D Grid tool to generate a two-dimensional or three-dimensional computational grid for the mangrove restoration area. Determine the resolution and extent of the grid according to the size of the restoration area to ensure that the grid can fully describe the topographic features of the mangrove area. S72) Based on the hydrological data obtained in step S3), set tidal, wave, and runoff boundary conditions, input tidal period, wave parameters, and flow data, and define open and closed boundaries. S73) Set hydrodynamic parameters, including Manning roughness, wind field, and viscosity coefficient; S74) Input wave parameters, including wave height, period and propagation direction, parameterize mangrove vegetation, add mangrove vegetation, and simulate the impact of mangroves on hydrodynamics by adjusting the roughness coefficient or introducing the vegetation resistance coefficient, and generalize the distribution range and density of mangrove areas. S75) Set sediment parameters, including sediment particle size, initial sediment content, and sediment settling velocity, and perform coupled simulation; S76) Simulates hydrodynamic, wave and sediment transport processes, outputs simulation results, including flow velocity and direction, wave height, sediment concentration, and topographic changes; compares measured data with simulation results.

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