Yellow River basin heritage area ecological corridor environment design system based on digital twinning

Abstract

The invention discloses a Yellow River basin heritage area ecological corridor environment design system based on digital twinning, belongs to the technical field of ecological corridor environment design, and aims to solve the problem that the Yellow River basin heritage area ecological corridor design is insufficient in accuracy and scientificity. The system comprises a multi-source ecological data acquisition module, an ecological data preprocessing module, a digital twin construction module, an ecological corridor planning design module and a visual output module. According to the method, terrain data, ecological element data and land utilization data are collected and preprocessed, ecological digital twin bodies of the heritage areas of the Yellow River basin are constructed, and in combination with an InVEST model, a minimum cost path algorithm, an RUSLE water and soil loss model and a CASA carbon sink model, ecological node recognition, optimal ecological corridor path planning and corridor environment design simulation are completed, so that the ecological digital twin bodies of the heritage areas of the Yellow River basin are constructed. And visually displaying the result. According to the method, accurate mapping of the ecological scene is achieved, the scientificity of ecological corridor design is improved, and support is provided for ecological corridor construction.

Description

Technical Field

[0001] This invention belongs to the field of ecological corridor environmental design technology, specifically relating to an ecological corridor environmental design system based on digital twins for heritage sites in the Yellow River Basin. Background Technology

[0002] The Yellow River Basin heritage sites bear important ecological functions and natural heritage value. The scientific design of its ecological corridors is crucial to ensuring the ecological connectivity of the basin and protecting the stability of the heritage site's ecosystem. Currently, the design of ecological corridors in the Yellow River Basin heritage sites largely relies on manual on-site surveys and experience-based judgments. Data collection is mainly based on local sampling, and the types of topography, ecology, and land use data covered are limited in variety and accuracy, making it difficult to fully reflect the complex ecological spatial characteristics of the heritage sites. Furthermore, the lack of standardized data processing procedures makes data noise interference easy, resulting in deviations between the design schemes and actual ecological needs, and failing to meet the requirements of refined ecological protection of the heritage sites.

[0003] Meanwhile, existing ecological corridor designs lack high-precision virtual mapping and quantitative simulation methods, making it impossible to construct dynamic models that match physical ecological scenarios. Ecological node identification often relies on subjective judgment or single ecological indicators, making it difficult to accurately select high-value ecological areas. Corridor path planning only considers basic factors such as topography and distance, failing to fully integrate multi-dimensional ecological resistance such as vegetation density and human disturbance intensity, resulting in insufficient ecological connectivity of the paths. Corridor environmental design lacks quantitative assessment, and scheme optimization lacks scientific basis, ultimately leading to a disconnect between design outcomes and actual ecological needs, making it difficult to achieve synergy between ecological protection and corridor functions in the Yellow River Basin heritage sites. Therefore, there is an urgent need for an ecological corridor environmental design system for the Yellow River Basin heritage sites that can integrate multi-source data, construct accurate ecological scenarios, and achieve scientific planning simulation. Summary of the Invention

[0004] The purpose of this invention is to provide an environmental design system for ecological corridors in the Yellow River Basin heritage sites based on digital twins, in order to solve the problems mentioned in the background art.

[0005] To solve the above-mentioned technical problems, the present invention provides the following technical solution:

[0006] The Yellow River Basin Heritage Site Ecological Corridor Environmental Design System based on digital twins includes a multi-source ecological data acquisition module, an ecological data preprocessing module, a digital twin construction module, an ecological corridor planning and design module, and a visualization output module.

[0007] The multi-source ecological data acquisition module acquires topographic data, ecological element data, and land use data of heritage sites in the Yellow River Basin to form an original ecological dataset;

[0008] The ecological data preprocessing module performs data cleaning, data fusion and standardization on the original ecological dataset, and outputs the preprocessed original ecological dataset.

[0009] The digital twin construction module constructs an ecological digital twin of the Yellow River Basin heritage sites based on the preprocessed original ecological dataset;

[0010] The ecological corridor planning and design module calls upon the ecological digital twin of the Yellow River Basin heritage site to conduct ecological node identification, corridor path simulation, and corridor environment design effect simulation, and outputs the optimal ecological corridor path and the optimal ecological corridor path environment design scheme.

[0011] The visualization output module provides a visual representation of the ecological digital twin of the Yellow River Basin heritage sites, the optimal ecological corridor path, and the environmental design scheme for the optimal ecological corridor path.

[0012] The topographic data was acquired using airborne LiDAR equipment with an accuracy of ≤±2cm, covering the entire Yellow River Basin heritage site. The ecological element data includes UAV multispectral imagery and sensor data. The UAV multispectral imagery was acquired by a UAV equipped with a multispectral camera flying along a preset route, with a spatial resolution ≥0.1m, and can extract vegetation cover, community type, and wetland boundary ecological information. The sensor data was acquired in real time through an IoT sensor network deployed in key areas of the Yellow River Basin heritage site. The types of sensors in the IoT sensor network include soil moisture sensors, water quality sensors, infrared sensors, and meteorological sensors, with a sampling frequency ≥1 time / hour. The land use data was obtained from an official GIS database, including land use status maps, administrative division maps, and transportation network vector data, and the land use data update cycle is ≤1 year.

[0013] Preferably, the data cleaning specifically includes: using statistical filtering to remove outliers from laser point clouds in the terrain data to achieve noise reduction; performing radiometric and atmospheric corrections on the UAV multispectral imagery in the ecological element data using the FLAASH atmospheric correction module of ENVI 5.6 software; aligning the sensor data in the ecological element data by standardizing the timestamps at a 1-hour sampling frequency, then using box plots to identify outliers in the time-series aligned sensor data, deleting the outliers, and then interpolating the outliers using linear interpolation; the data fusion involves performing spatiotemporal registration of the cleaned UAV multispectral imagery and sensor data based on WGS84 or UTM projection coordinate systems; the standardization process involves correcting topological errors in the land use map using the topology rule checking function of ArcGIS Pro software, and then uniformly converting the land use type field in the land use map to an 8-digit format according to the "Yellow River Basin Ecological Data Classification and Coding Specification" to complete attribute coding standardization; thereby obtaining a preprocessed original ecological dataset including preprocessed terrain data, preprocessed ecological element data, and preprocessed land use data.

[0014] Preferably, the digital twin construction module integrates ArcGIS Pro 3.1, ENVI 5.6, Cesium 1.110 tool stack and Huawei CloudVR digital twin engine. The tool stack version is not limited to a specific version, but specifically ArcGIS Pro 3.1 or later, ENVI 5.6 or later, and Cesium 1.110 or later. The specific construction process of the Yellow River Basin heritage site ecological digital twin is as follows: through ArcGIS... Pro imports preprocessed terrain data to generate a 3D terrain model with elevation accuracy ≤ ±2cm and including terrain slope and aspect parameters. ENVI performs supervised classification and interpretation of the preprocessed ecological element data to identify vegetation types and calculate vegetation cover. A vegetation model labeled with vegetation type, vegetation cover, and vegetation growth cycle is constructed. Then, Cesium loads the 3D terrain model, vegetation model, and preprocessed land use data in WGS84 or UTM coordinate systems to form a spatially aligned multi-level scene. Combined with the digital twin engine model integration and dynamic data association, an ecological digital twin of the Yellow River Basin heritage site is obtained.

[0015] Preferably, the method for identifying ecological nodes is as follows: Multi-dimensional ecological data is extracted from the constructed ecological digital twin of the Yellow River Basin heritage site. This multi-dimensional ecological data includes vegetation cover, topographic slope, and hydrological connectivity parameters for each spatial unit. The hydrological connectivity parameters are obtained by analyzing the ecological digital twin of the Yellow River Basin heritage site using ArcGIS Pro's hydrological analysis tool. The vegetation cover, topographic slope, and hydrological connectivity parameters of each spatial unit are input into the InVEST habitat quality model with weights of 0.4 for vegetation cover, 0.3 for topographic slope, and 0.3 for hydrological connectivity parameters to calculate the habitat quality index for each spatial unit. All high-value spatial units with habitat quality indices greater than a preset habitat quality index threshold are selected. Spatial connectivity analysis is then conducted using ArcGIS Pro's proximity analysis tool, merging spatially adjacent high-value spatial units to obtain n key ecological node areas.

[0016] The calculation logic of the InVEST habitat quality model is: HQI=∑(Si×Wi);

[0017] Wherein, HQI is the habitat quality index, Si is the vegetation cover, topographic slope or hydrological connectivity parameter, and Wi is the weight of the vegetation cover, topographic slope or hydrological connectivity parameter.

[0018] Preferably, the specific steps of the corridor path simulation are as follows:

[0019] S1. Select m key ecological node areas from n key ecological node areas to form the corridor path planning area. The m key ecological node areas are the key ecological node areas included in the corridor path planning area. Select two key ecological node areas from the m key ecological node areas as the starting point and ending point of the corridor path. At the same time, read the center spatial coordinates of the m key ecological node areas from the ecological digital twin of the Yellow River Basin heritage site using ArcGIS Pro.

[0020] S2. Based on the ecological digital twin of the Yellow River Basin heritage site, extract the topographic slope, vegetation cover, and human disturbance intensity of each spatial unit within the corridor path planning area. Human disturbance intensity is measured using human activity frequency data collected by infrared sensors. Specifically: more than 5 human activities per day indicate high human disturbance intensity; less than 1 human activity per day indicates low human disturbance intensity; otherwise, human disturbance intensity is medium. The topographic slope, vegetation density, and human disturbance intensity are converted into corresponding basic resistance values ​​of 0-10 according to preset rules: topographic slope ≤ 5° = 1; topographic slope 5-15° = 4; topographic slope ≥ 15° = 8; vegetation cover ≥ 5 plants / m². 2 1. Vegetation coverage is 2-5 plants / m²2 4. Vegetation coverage < 2 plants / m² 2 The value is set to 8, with low human disturbance intensity set to 1, medium to 4, and high to 8. Based on this, the grid resistance value of each spatial unit within the corridor path planning area is calculated using the formula: Grid resistance value = Terrain slope basic resistance value × 0.3 + Vegetation density basic resistance value × 0.4 + Human disturbance intensity basic resistance value × 0.3, generating a resistance grid map covering the entire corridor path planning area with resistance values ​​ranging from 0 to 10.

[0021] S3. Call the minimum cost path algorithm, use the resistance value in the resistance grid map as the path weight, and use the center spatial coordinates of the starting point and the ending point as the path start and end points to obtain several candidate corridor paths. Among them, the minimum cost path algorithm is either the A* algorithm or the Dijkstra algorithm.

[0022] S4. For each candidate corridor path, calculate the ecological connectivity index using the formula: Ecological connectivity index = (straight-line distance between the start and end points of the candidate corridor path / actual length of the candidate corridor path) × 0.9. Simultaneously, sum the grid resistance values ​​of each spatial unit in the resistance grid map to obtain the total resistance value. Select the candidate corridor path with the largest ecological connectivity index and the lowest total resistance value as the optimal ecological corridor path.

[0023] Preferably, the specific process of simulating the corridor environment design effect is as follows:

[0024] A corridor environment design parameter library was constructed, including vegetation configuration parameters, buffer zone width parameters, and micro-topographic slope parameters. The vegetation configuration parameter is the ratio of trees:shrubs:herbs, with specific ratios selectable as 3:4:3, 2:5:3, and 1:3:6. The buffer zone width parameter is set with three gradients: 50m, 100m, and 150m. The micro-topographic slope parameter is divided into three ranges: ≤5°, 5°-15°, and ≥15°. An orthogonal experimental design method was used to combine the vegetation configuration parameters, buffer zone width parameters, and micro-topographic slope parameters along the optimal ecological corridor path. The parameters are used to generate at least 5 candidate environmental design schemes. At the same time, dynamic data including soil moisture, vegetation growth cycle and average precipitation are extracted from the ecological digital twin of the Yellow River Basin heritage site. The dynamic data are combined with each candidate environmental design scheme and then input into the RUSLE soil erosion model and CASA carbon sink model respectively to obtain the soil erosion amount and carbon sink capacity of each candidate environmental design scheme. The candidate environmental design scheme with the lowest soil erosion amount and the highest carbon sink capacity is selected as the optimal ecological corridor path environmental design scheme.

[0025] The calculation logic of the RUSLE soil erosion model is as follows:

[0026] SL = R × K × LS × Q × P;

[0027] Wherein, SL is soil erosion, R is rainfall erosivity factor, K is soil erodibility, LS is slope length and gradient factor, Q is vegetation cover management factor, and P is soil and water conservation measures factor; the rainfall erosivity factor is based on average precipitation data P. avg The formula R = 0.013 × P is used. avg The empirical coefficient of rainfall erosivity in the Yellow River Basin is 0.013. The soil erosibility factor is obtained based on soil moisture W using the formula K = K0(1 + 0.02 × W), where K0 is the basic soil erosibility. The slope length factor is determined by the micro-topographic slope parameter. When the micro-topographic slope parameter is ≤5°, then LS = 0.5; when the micro-topographic slope parameter is between 5° and 15°, then LS = 1.5; and when the micro-topographic slope parameter is ≥15°, then LS = 3.0. The vegetation cover... The management factor is determined by the vegetation configuration parameters. When the vegetation configuration parameters are 3:4:3, C = 0.15; when the vegetation configuration parameters are 2:5:3, C = 0.2; and when the vegetation configuration parameters are 1:3:6, C = 0.3. The buffer zone width parameter is determined by the soil and water conservation measures factor. When the buffer zone width parameter is 50m, P = 0.8; when the buffer zone width parameter is 100m, P = 0.5; and when the buffer zone width parameter is 150m, P = 0.3.

[0028] The calculation logic of the CASA carbon sink model is as follows:

[0029] C = ∑(NPP × A × f);

[0030] Where C is carbon sink capacity, NPP is net primary productivity of vegetation, A is carbon sink calculated area, f is carbon conversion coefficient, and the carbon sink calculated area is calculated by the formula A = B × L, where L is the actual length of the optimal ecological corridor path.

[0031] Preferably, the visualization display uses WebGL technology to construct a three-dimensional interactive interface to display the ecological digital twin of the Yellow River Basin heritage site, the optimal ecological corridor path, and the optimal ecological corridor path environmental design scheme.

[0032] Due to the adoption of the above technical solution, the technical progress achieved by this invention compared to the prior art is as follows:

[0033] 1. Existing technologies for designing ecological corridors in the Yellow River Basin heritage sites rely on manual surveys and local sampling. These methods suffer from limited data types, accuracy, and standardized processing, making them susceptible to noise interference and failing to reflect complex ecological characteristics. This invention integrates multiple types of high-precision data through a multi-source ecological data acquisition module. It utilizes specialized equipment to acquire comprehensive topographic data and detailed ecological information, leverages sensor networks to obtain real-time ecological data, and combines this with regularly updated official land use data to form a comprehensive raw dataset. Simultaneously, a standardized process is established through an ecological data preprocessing module to complete data cleaning, spatiotemporal registration and fusion, and standardized coding, effectively solving the data problems of existing technologies and providing a high-quality, standardized data foundation for subsequent work.

[0034] 2. Existing technologies lack high-precision dynamic virtual mapping that matches physical ecological scenes, making it impossible to accurately replicate the ecological characteristics of heritage sites. The digital twin construction module of this invention integrates professional tools and a digital twin engine. First, it generates a 3D terrain model containing key terrain parameters, then constructs a vegetation model annotated with key vegetation information, loads multiple types of data to form a spatially aligned, multi-level scene, and combines the engine to achieve model integration and dynamic data association. Finally, it constructs a digital twin that can dynamically and accurately map physical ecological scenes, filling the gap in existing technologies for dynamic virtual mapping and providing a realistic simulation platform for planning and design.

[0035] 3. Existing technologies rely on subjective judgment or single indicators for ecological node identification, consider only basic factors in corridor path planning, and lack quantitative evaluation in corridor environmental design, resulting in insufficient scientific rigor in the solutions. The ecological corridor planning and design module of this invention achieves full-process quantification: node identification extracts multi-dimensional data, uses professional models to screen and merge high-value spatial units, avoiding subjective bias; path simulation combines multiple types of ecological resistance to generate a resistance map, and uses algorithms to select the optimal path based on key indices; environmental design generates candidate solutions through experiments, combines dynamic data with professional models for quantitative evaluation, and selects the optimal solution, thus addressing the problem of insufficient scientific basis in existing technologies.

[0036] 4. Existing technologies offer limited display formats for design deliverables, primarily consisting of two-dimensional drawings or text, which fails to intuitively present complex scenes and details, hindering project implementation. The visualization output module of this invention utilizes specialized technology to construct a three-dimensional interactive interface, intuitively displaying the digital twin, optimal path, and design scheme. Users can interact to perceive key details, significantly improving the intuitiveness and comprehensibility of the deliverables. This provides a convenient platform for team communication, scheme review, and construction coordination, filling the gaps in the intuitive display capabilities of existing technologies. Attached Figure Description

[0037] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this invention. For those skilled in the art, other drawings can be obtained based on these drawings.

[0038] Figure 1 This is a schematic diagram of the system functional modules of the present invention. Detailed Implementation

[0039] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0040] Examples, such as Figure 1 The aforementioned Yellow River Basin Heritage Site Ecological Corridor Environmental Design System based on digital twins includes a multi-source ecological data acquisition module, an ecological data preprocessing module, a digital twin construction module, an ecological corridor planning and design module, and a visualization output module, which work together to complete the planning and environmental design of the ecological corridor.

[0041] The ecological data preprocessing module performs data cleaning, data fusion and standardization on the original ecological dataset, and outputs the preprocessed original ecological dataset.

[0042] The digital twin construction module constructs an ecological digital twin of the Yellow River Basin heritage sites based on the preprocessed original ecological dataset;

[0043] The ecological corridor planning and design module calls upon the ecological digital twin of the Yellow River Basin heritage site to conduct ecological node identification, corridor path simulation, and corridor environment design effect simulation, and outputs the optimal ecological corridor path and the optimal ecological corridor path environment design scheme.

[0044] The visualization output module provides a visual representation of the ecological digital twin of the Yellow River Basin heritage sites, the optimal ecological corridor path, and the environmental design scheme for the optimal ecological corridor path.

[0045] Furthermore, the working principle of the present invention will be illustrated below using a heritage site in a certain region of the Yellow River as an example:

[0046] The heritage site is located between 110°21′ and 111°11′ east longitude and 34°49′ and 35°17′ north latitude, with a core heritage area of ​​approximately 800 km². 2It covers typical ecological types such as wetlands, woodlands, and riparian zones. The multi-source ecological data acquisition module, ecological data preprocessing module, digital twin construction module, ecological corridor planning and design module, and visualization output module are deployed through a server cluster containing two high-performance computing servers, one data storage server, and one web application server. Data interaction between the modules is achieved through the TCP / IP protocol. The software tools used are ArcGIS Pro 3.1, ENVI 5.6, Cesium 1.110, and Huawei CloudVR digital twin engine, and all software has been authorized and configured.

[0047] The multi-source ecological data acquisition module conducts comprehensive data collection across the heritage site. Topographic data is acquired using an airborne LiDAR device mounted on a fixed-wing aircraft, scanning along a route parallel to the Yellow River (500m spacing, 800m altitude) to obtain laser point cloud data. For ecological element data, multispectral imagery is collected using a DJI M300 RTK drone equipped with a multispectral camera, flying along a preset grid route (1km x 1km grid, 30% overlap), extracting vegetation cover, community type, and wetland boundary information. Sensor data is collected in real-time through an IoT sensor network deployed in key areas of the heritage site, including soil moisture sensors, water quality sensors, infrared sensors, and meteorological sensors, with a sampling frequency of once per hour, acquiring data such as soil moisture, water pH, frequency of human activity, temperature, and precipitation. Land use data is downloaded from the National Geographic Information Public Service Platform (official GIS database), containing the latest 2023 land use status map, administrative division map, and transportation network vector data. The final result is a raw ecological dataset containing topographic data, ecological element data, and land use data, stored on a data storage server.

[0048] The ecological data preprocessing module standardizes the raw ecological dataset. First, data cleaning is performed, using statistical filtering to remove outliers from the airborne LiDAR-acquired laser point cloud data (terrain data), such as anomalies caused by birds or clouds, to preserve ground point cloud data. Then, the FLAASH atmospheric correction module in ENVI 5.6 is used to perform radiometric and atmospheric corrections on the UAV multispectral imagery to eliminate sensor errors, atmospheric scattering, and atmospheric absorption. Simultaneously, sensor data collected by IoT sensors is imported into MATLAB software and time-series aligned using a 1-hour sampling frequency and unified timestamps. Outliers are identified and removed using box plots, and data gaps are filled using linear interpolation. Next, data fusion is performed in ArcGIS Pro 3.1 software, where the cleaned UAV multispectral imagery and sensor data are spatiotemporally registered based on the WGS84 coordinate system to ensure that image data and real-time sensor data correspond and match at the same spatial location. Finally, standardization is performed on land use data using ArcGIS. The Pro's topology rule checking function corrects errors such as overlapping plots and discontinuous boundaries. It also converts the land use type field into an 8-digit number format according to the "Yellow River Basin Ecological Data Classification and Coding Specification" to complete the attribute coding standardization. Finally, it outputs a preprocessed raw ecological dataset containing preprocessed topographic data, preprocessed ecological element data, and preprocessed land use data, which is stored in the data storage server for subsequent modules to call.

[0049] The digital twin construction module builds an ecological digital twin of the heritage site based on the preprocessed raw ecological dataset. First, ArcGIS Pro 3.1 software is launched to import the preprocessed topographic data. The 3D Analyst toolset is used to generate a 3D topographic model that includes topographic slope and aspect parameters and whose elevation accuracy meets the design requirements. Then, in ENVI 5.6 software, supervised classification and interpretation of the preprocessed ecological element data are performed to identify vegetation types within the heritage site, calculate vegetation coverage in each area, and label vegetation growth cycles to construct a vegetation model. Finally, the Cesium 1.110 platform is launched to load the 3D topographic model, vegetation model, and preprocessed land use data in the WGS84 coordinate system to form a spatially aligned multi-level static scene. This static scene is imported into the Huawei CloudVR digital twin engine and simultaneously linked with real-time sensor data collected by the IoT sensor network to achieve the fusion and association of static scene and dynamic data. Finally, an ecological digital twin of the heritage site is constructed that can dynamically present the topographic relief, vegetation distribution, land use status, and real-time ecological element data of the heritage site, and supports zooming and rotation within the engine platform.

[0050] The ecological corridor planning and design module utilizes the digital twin of the heritage site's ecosystem to sequentially complete ecological node identification, corridor path simulation, and corridor environmental design simulation. Ecological node identification first extracts vegetation cover, topographic slope, and hydrological connectivity parameters for each spatial unit (10m×10m grid) from the digital twin. These three parameters are then input into the InVEST habitat quality model with weights of 0.4 for vegetation cover, 0.3 for topographic slope, and 0.3 for hydrological connectivity. The habitat quality index for each spatial unit is calculated, and a threshold of 0.7 is set. High-value spatial units with an index > 0.7 are selected, and spatial connectivity analysis is performed using ArcGIS Pro's proximity analysis tool. Adjacent high-value spatial units are merged to obtain eight key ecological node areas. Corridor path simulation first selects two key ecological node areas from these eight as the starting and ending points of the corridor path planning area. This is then simulated using ArcGIS Pro. Pro reads the central spatial coordinates of the two node regions (starting point coordinates: 110°35′E, 34°58′N; ending point coordinates: 110°52′E, 35°05′N), then extracts the terrain slope, vegetation cover, and human disturbance intensity of each spatial unit within the planning area from the ecological digital twin. These three values ​​are converted into basic resistance values ​​of 0-10 according to preset rules. The resistance value of each spatial unit is calculated using the formula "grid resistance value = terrain slope basic resistance value × 0.3 + vegetation cover basic resistance value × 0.4 + human disturbance intensity basic resistance value × 0.3", generating a resistance grid map covering the planning area. Finally, the A* algorithm is called, using the resistance values ​​in the resistance grid map as path weights, and the central spatial coordinates of the starting and ending points as the starting and ending points, generating 5 candidate corridor paths. For each candidate corridor path, the formula "ecological connectivity index = straight-line distance between the starting and ending points of the candidate corridor path / actual length of the candidate corridor path × 0.9” The ecological connectivity index is calculated, and the resistance values ​​of the spatial units traversed by the candidate corridor path are accumulated to obtain the total resistance value. The candidate corridor path with the highest ecological connectivity index and the lowest total resistance value is selected as the optimal ecological corridor path. This optimal ecological corridor path is approximately 18km long, mainly distributed along the banks of the Yellow River tributaries, avoiding areas with dense human activity. The corridor environment design simulation first constructs a corridor environment design parameter library containing vegetation configuration parameters (3 groups: 3:4:3, 2:5:3, 1:3:6, all representing the ratio of trees:shrubs:herbs), buffer zone width parameters (3 groups: 50m, 100m, 150m), and micro-topographic slope parameters (3 groups: ≤5°, 5-15°, ≥15°). Then, the optimal ecological corridor path is... Six candidate environmental design schemes were generated by combining the above parameters using an orthogonal experimental design method along the route. Scheme 1: vegetation configuration 3:4:3, buffer zone width 50m, and micro-topographic slope ≤5°; Scheme 4: vegetation configuration 2:5:3, buffer zone width 100m, and micro-topographic slope 5-15°, etc. Finally, dynamic data (soil moisture, vegetation growth cycle, and average precipitation data) of the optimal route area were extracted from the ecological digital twin. This dynamic data was then combined with each candidate scheme and input into the RUSLE soil erosion model and the CASA carbon sequestration model, respectively. The RUSLE model was used to calculate the soil erosion rate of each scheme, and the CASA model was used to calculate the carbon sequestration capacity of each scheme. A soil erosion rate of 12t / (km²) was selected. 2 a) Minimum carbon sequestration capacity of 28 tC / (km²) 2 •a) Option 4, the highest option, is the optimal environmental design scheme for the ecological corridor path.

[0051] The visualization output module constructs a 3D interactive interface using WebGL technology. A WebGL visualization program is deployed on a web application server to import the ecological digital twin of the heritage site, the optimal ecological corridor path, and the environmental design scheme of the optimal ecological corridor path into the 3D interactive interface. The ecological digital twin is presented as the basic scene in its entirety. The optimal ecological corridor path is marked with a red highlighted line. Hovering the mouse over it allows users to view parameters such as path length and total resistance. In the optimal environmental design scheme, vegetation configuration is distinguished by different colors for trees, shrubs, and herbs. Buffer zones are marked with blue dashed boxes. Clicking the mouse allows users to view the soil erosion and carbon sequestration capacity of the optimal ecological corridor path. Users can also access this 3D interactive interface through a browser to perform operations such as scene zooming, rotation, and translation, and intuitively view the ecological corridor design results.

[0052] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A digital twin-based environmental design system for ecological corridors in the Yellow River Basin heritage sites, characterized in that: include: The multi-source ecological data acquisition module is used to acquire topographic data, ecological element data, and land use data of heritage sites in the Yellow River Basin to form a raw ecological dataset. The ecological data preprocessing module is used to perform data cleaning, data fusion and standardization on the original ecological dataset, and output the preprocessed original ecological dataset. The digital twin building module is used to construct an ecological digital twin of the Yellow River Basin heritage sites based on the preprocessed raw ecological dataset; The ecological corridor planning and design module is used to call the ecological digital twin of the Yellow River Basin heritage site to carry out ecological node identification, corridor path simulation and corridor environmental design effect simulation, and output the optimal ecological corridor path and the optimal ecological corridor path environmental design scheme. The visualization output module is used to visualize and display the ecological digital twins of heritage sites in the Yellow River Basin, the optimal ecological corridor paths, and the environmental design schemes for the optimal ecological corridor paths.

2. The Yellow River Basin Heritage Site Ecological Corridor Environmental Design System based on digital twins as described in claim 1, characterized in that, The terrain data was acquired using an airborne LiDAR device; the ecological element data included UAV multispectral imagery and sensor data, wherein the UAV multispectral imagery was acquired by a UAV carrying a multispectral camera during flight, and the sensor data was acquired in real time by an Internet of Things sensor network deployed in the Yellow River Basin heritage sites; and the land use data was obtained from an official GIS database.

3. The Yellow River Basin Heritage Site Ecological Corridor Environmental Design System based on digital twins as described in claim 2, characterized in that, The data cleaning includes: denoising the terrain data, performing radiometric and atmospheric correction on the UAV multispectral imagery, and performing time-series alignment and outlier interpolation on the sensor data; the data fusion involves spatiotemporal registration of the data-cleaned UAV multispectral imagery and sensor data; and the standardization process involves topological checking and attribute coding standardization of the land use data.

4. The Yellow River Basin Heritage Site Ecological Corridor Environmental Design System based on digital twins as described in claim 3, characterized in that, The digital twin construction module integrates ArcGIS Pro, ENVI, Cesium tool stack and digital twin engine. It imports pre-processed terrain data through ArcGIS Pro to generate a 3D terrain model, interprets pre-processed ecological element data through ENVI to construct a vegetation model, loads the terrain model, vegetation model and pre-processed land use data through Cesium, and combines them with the digital twin engine to obtain an ecological digital twin of the Yellow River Basin heritage site.

5. The Yellow River Basin Heritage Site Ecological Corridor Environmental Design System based on digital twins as described in claim 4, characterized in that, The method for identifying the ecological nodes is as follows: Multi-dimensional ecological data are extracted from the ecological digital twin of the Yellow River Basin heritage sites. The vegetation cover, topographic slope and hydrological connectivity parameters of each spatial unit are input into the InVEST habitat quality model to calculate the habitat quality index of each spatial unit. All high-value spatial units with habitat quality indices greater than the preset habitat quality index threshold are screened out. Then, spatially adjacent high-value spatial units are merged through spatial connectivity analysis to obtain n key ecological node areas. The multidimensional ecological data includes vegetation cover, topographic slope, and hydrological connectivity parameters for each spatial unit.

6. The Yellow River Basin Heritage Site Ecological Corridor Environmental Design System based on digital twins as described in claim 5, characterized in that, The method for simulating the corridor path includes the following steps: S1. Select m key ecological node areas from n key ecological node areas to plan the corridor path, and select two key ecological node areas from the m key ecological node areas as the starting point and ending point of the corridor path. At the same time, read the central spatial coordinates of the m key ecological node areas from the ecological digital twin of the Yellow River Basin heritage site. S2. Based on the topographic slope, vegetation cover and human disturbance intensity of the corridor path planning area in the ecological digital twin of the Yellow River Basin heritage site, generate a resistance raster map of the corridor path planning area; S3. Call the minimum cost path algorithm, use the resistance value in the resistance grid map as the path weight, and use the center spatial coordinates of the starting point and the ending point as the path start and end points to obtain several candidate corridor paths. S4. For each candidate corridor path, calculate its ecological connectivity index and total resistance value, and select the candidate corridor path with the largest ecological connectivity index and the lowest total resistance value as the optimal ecological corridor path.

7. The Yellow River Basin Heritage Site Ecological Corridor Environmental Design System based on digital twins as described in claim 6, characterized in that, The process of simulating the corridor environment design effect is as follows: A corridor environmental design parameter library was constructed, including vegetation configuration parameters, buffer zone width parameters, and micro-topographic slope parameters. Orthogonal experimental design was used to combine vegetation configuration parameters, buffer zone width parameters, and micro-topographic slope parameters along the optimal ecological corridor path to generate at least 5 candidate environmental design schemes. At the same time, dynamic data of the area along the optimal ecological corridor path was extracted from the ecological digital twin of the Yellow River Basin heritage site. The dynamic data was combined with each candidate environmental design scheme and then input into the RUSLE soil erosion model and the CASA carbon sink model to obtain the soil erosion and carbon sink capacity of each candidate environmental design scheme. The candidate environmental design scheme with the lowest soil erosion and the highest carbon sink capacity was selected as the optimal ecological corridor path environmental design scheme.

8. The Yellow River Basin Heritage Site Ecological Corridor Environmental Design System based on digital twins as described in claim 1, characterized in that, The visualization uses WebGL technology to construct a three-dimensional interactive interface to display the ecological digital twin of the Yellow River Basin heritage site, the optimal ecological corridor path, and the environmental design scheme of the optimal ecological corridor path.

9. The Yellow River Basin Heritage Site Ecological Corridor Environmental Design System based on digital twins as described in claim 6, characterized in that, The minimum cost path algorithm can be either the A* algorithm or the Dijkstra algorithm.

Images