Ecological protection red line foundation investigation method based on territorial space planning

Abstract

The invention relates to the technical field of ecological protection, in particular to an ecological protection red line basic survey method based on territorial space planning, which comprises the following steps of: acquiring data including satellite remote sensing, unmanned aerial vehicle aerial survey, ground sensors and the like; and high-precision spatial data of ecological elements such as vegetation coverage, surface water distribution and soil erosion intensity are obtained. And combining spatial-temporal feature matching and an improved spatial clustering algorithm to dynamically partition the ecological factors to generate a dynamic partition map of the ecological factors. Based on the graph, a three-dimensional ecological sensitivity evaluation model is constructed, and a dynamic threshold adjustment algorithm is adopted to carry out automatic optimization of the red line boundary. And finally, through multi-dimensional verification and evaluation of natural ecological stability, regional economic bearing degree, social acceptance and the like, generating a final ecological protection red line scheme. According to the method, the adaptability and flexibility of red line delimiting are improved, and the method can be widely applied to the fields of ecological protection, territorial space planning, environment management and the like.

Description

Technical Field

[0001] The present invention relates to the technical field of ecological protection, and in particular to a basic investigation method for ecological protection red lines based on territorial spatial planning. Background Art

[0002] In order to effectively protect the ecological environment and ensure ecological security, a series of ecological protection policies have been introduced. One of the most crucial measures is the delineation of ecological protection red lines. The ecological protection red line refers to the ecological space that is demarcated on the basis of scientific assessment and is prohibited from being damaged and must be key protected. Its purpose is to ensure the integrity and functionality of the ecosystem by protecting important ecosystems, ecological functions, and species habitats, so as to provide guarantee for sustainable development.

[0003] At present, the existing methods for delineating ecological protection red lines mostly rely on traditional ecological data collection means, such as ground surveys and limited remote sensing data, lacking sufficient multi-source data support. The data collected by these methods usually have a coarser granularity and a lower update frequency, resulting in difficulties in comprehensively and accurately analyzing the spatial distribution and spatio-temporal dynamics of ecological factors. In addition, the traditional delineation methods also have strong manual intervention. They often delimit the red line boundaries according to fixed rules or experience, are easily affected by human factors, and lack sufficient scientificity and objectivity, which may lead to problems of overprotection or underprotection. In terms of multi-dimensional comprehensive evaluation, the existing technologies have not been able to fully consider the interrelationships among multiple factors such as ecology, economy, and society. Traditional methods mostly focus on ecological protection while ignoring the impacts of regional economic carrying capacity and social acceptance, resulting in that ecological protection measures may impose greater restrictions on local economic activities. Summary of the Invention

[0004] The present invention provides a basic investigation method for ecological protection red lines based on territorial spatial planning.

[0005] A basic investigation method for ecological protection red lines based on territorial spatial planning includes the following steps: S1, data collection: synchronously obtain spatial data of ecological elements through satellite remote sensing, unmanned aerial vehicle aerial survey, and ground sensors, including vegetation coverage, surface water distribution, and soil erosion intensity; S2, dynamic zoning of ecological elements: after matching the spatio-temporal characteristics of the obtained spatial data of ecological elements, combined with the topographic undulation factor, use an improved spatial clustering algorithm to generate a dynamic zoning map of ecological factors; S3, three-dimensional sensitivity modeling: based on the dynamic zoning map of ecological factors in S2, superimpose the elevation gradient correction coefficient, construct a three-dimensional ecological sensitivity evaluation model, evaluate the sensitivity of the ecosystem, and output the three-dimensional sensitivity evaluation result; S4, Red Line Dynamic Demarcation: Based on the three-dimensional sensitivity evaluation results output by S3, use the dynamic threshold adjustment algorithm to demarcate the boundaries of the ecological protection red line and generate a preliminary ecological protection red line plan; S5, Multi-dimensional Verification and Evaluation: Conduct three-dimensional verification and evaluation of the natural ecological stability, regional economic bearing capacity, and social acceptance of the preliminary ecological protection red line plan in S4 to generate the final ecological protection red line plan.

[0006] Optionally, the S1 includes: S11, Satellite Remote Sensing Data Acquisition: Collect spatial data on vegetation coverage, surface water distribution, and soil erosion intensity in the target area through satellite remote sensing equipment; S12, UAV Aerial Survey Data Acquisition: Use UAVs equipped with high-precision sensors for aerial surveys to obtain high-precision three-dimensional spatial data on vegetation coverage, surface water distribution, and soil erosion intensity in the area.

[0007] S13, Ground Sensor Data Acquisition: Deploy ground sensors in the target area for synchronous data acquisition; S14, Temporal and Spatial Matching and Fusion of Synchronous Data: Match and fuse the satellite remote sensing, UAV aerial survey, and ground sensor data obtained in S11, S12, and S13 in terms of time and space to ensure that data from different sources can be accurately docked. Through methods such as data alignment and coordinate transformation, integrate data with different resolutions and formats into a unified three-dimensional spatial data layer for subsequent analysis.

[0008] Optionally, the S2 includes: S21, Temporal and Spatial Feature Matching: Conduct temporal and spatial feature matching on the collected data of vegetation coverage, surface water distribution, and soil erosion intensity; S22, Calculation of Terrain Relief Factor: Calculate the terrain relief factor of the area based on the digital elevation model (DEM) of the area.

[0009] S23, Application of Clustering Algorithm: Use the improved K-means algorithm to conduct clustering analysis on the data in steps S21 and S22.

[0010] Optionally, the S2 further includes: S24, Generation of Dynamic Partition Map: Generate a dynamic partition map of ecological factors based on the clustering analysis results; S25, Verification and Optimization of Partition Map: Verify and optimize the generated dynamic partition map of ecological factors.

[0011] Optionally, the S3 includes: S31, Ecological factor dynamic zoning map: Receive the generated ecological factor dynamic zoning map, which has been spatially clustered based on vegetation coverage, surface water distribution, soil erosion intensity, and topographic relief factors. Each zone represents an area with similar ecological characteristics and contains relevant ecological factor data, including the distribution range and intensity of vegetation coverage, the spatial pattern of surface water distribution, and the spatial variation of soil erosion intensity; S32, Elevation gradient correction coefficient calculation: Calculate the elevation gradient correction coefficient for each spatial unit based on the digital elevation model (DEM) of the target area; S33, Construct a three-dimensional ecological sensitivity evaluation model: Based on the ecological factor data and topographic elevation correction coefficient, construct a three-dimensional ecological sensitivity evaluation model.

[0012] S34, Output of three-dimensional sensitivity evaluation results: Evaluate the sensitivity of the ecological system in the target area according to the constructed three-dimensional ecological sensitivity evaluation model, output the three-dimensional sensitivity evaluation results, and generate a three-dimensional sensitivity evaluation result map.

[0013] Optionally, S3 further includes: S35, Sensitivity level division: Divide the area into several sensitivity levels according to the ecological sensitivity index in the three-dimensional sensitivity evaluation result map; S36, Spatial distribution display: Visualize the areas of each sensitivity level as a three-dimensional map with different colors or shades, facilitating an intuitive understanding of the spatial sensitivity distribution of the ecological system; S37, Result verification and optimization: Verify and optimize the generated three-dimensional ecological sensitivity evaluation results.

[0014] Optionally, S4 includes: S41, Receive the three-dimensional sensitivity evaluation results: Receive the generated three-dimensional sensitivity evaluation results, which include the ecological sensitivity index of each spatial unit, and these indices reflect the ecological vulnerability of each area.

[0015] S42, Determine the red line boundary threshold: Set a preliminary red line boundary threshold according to the ecological protection objectives of the area and the requirements for red line demarcation.

[0016] S43, Dynamic threshold adjustment algorithm: Use the dynamic threshold adjustment algorithm to optimize the preliminarily set red line boundary; S44, Generation of red line boundary and output of preliminary plan: Generate a preliminary ecological protection red line plan according to the optimized red line boundary.

[0017] S45, Review and optimization of the preliminary red line plan: Conduct expert review and optimization of the generated preliminary ecological protection red line plan to ensure that the demarcation results meet the ecological protection objectives.

[0018] Optionally, S5 includes: S51, natural ecological stability assessment: Conduct a natural ecological stability assessment on the preliminary ecological protection red line plan. The natural ecological stability assessment aims to verify whether the ecological systems in the ecological protection red line area can maintain long-term stability and self-repair ability.

[0019] S52, regional economic bearing capacity assessment: Conduct a regional economic bearing capacity assessment on the preliminary ecological protection red line plan. The regional economic bearing capacity assessment is used to evaluate whether economic activities within the red line area will be restricted by the red line boundary and whether it is possible to balance economic development and ecological protection.

[0020] S53, social acceptance assessment: Conduct a social acceptance assessment on the preliminary ecological protection red line plan. The social acceptance assessment aims to determine the social support degree for the red line demarcation area and evaluate the degree of recognition of the red line boundary demarcation by social groups (such as local residents, enterprises, policymakers, etc.).

[0021] S54, three-dimensional comprehensive assessment and optimization: Conduct a comprehensive analysis of the assessment results of natural ecological stability, regional economic bearing capacity, and social acceptance, and output the final ecological protection red line plan.

[0022] Advantages of the present invention: In the present invention, through steps such as data collection, dynamic zoning of ecological factors, three-dimensional ecological sensitivity modeling, and dynamic demarcation of the red line, the demarcation of the ecological protection red line is ensured to be highly accurate and scientific. Specifically, first, core ecological element data such as vegetation coverage, surface water distribution, and soil erosion intensity are synchronously collected through satellite remote sensing, unmanned aerial vehicle aerial survey, and ground sensors to obtain high-precision spatial information of ecological elements. Then, the ecological element data are subjected to spatio-temporal feature matching and zoning in combination with topographic factors and an improved spatial clustering algorithm, and the ecological sensitivity is quantitatively analyzed through a three-dimensional ecological sensitivity evaluation model, providing strong data support for the accurate demarcation of the red line. The red line boundary is optimized through a dynamic adjustment algorithm, making the red line demarcation more in line with the ecological protection goal, ensuring the accuracy and reliability of the red line demarcation result, and providing a practical technical basis for ecological protection.

[0023] In the present invention, a multi-dimensional verification and evaluation mechanism is introduced after the red line is delimited, comprehensively considering factors such as the stability of the natural ecosystem, the economic carrying capacity of the region, and the social acceptance. Through the evaluation of the natural ecosystem stability, it is ensured that the delimited red line area has sufficient ecological self-repair ability and long-term stability, avoiding the imbalance and degradation of the ecosystem; through the evaluation of the regional economic carrying capacity, the needs of ecological protection and economic development are reasonably balanced, preventing the ecological protection measures from imposing excessive restrictions on the regional economy; through the evaluation of social acceptance, it is ensured that the red line plan can obtain extensive support and cooperation from all sectors of society during the actual implementation process, improving the feasibility and implementation success rate of the plan. This multi-dimensional comprehensive evaluation system enables the delimited red line to not only consider the needs of ecological protection, but also take into account the economic sustainable development and the actual situation of society, truly realizing the coordination and balance among the three aspects of ecology, economy, and society. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the drawings in the following description are only those of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0025] Figure 1 It is a schematic flow chart of the method according to an embodiment of the present invention; Figure 2 It is a schematic flow chart of the S3 process according to an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0026] The present invention will be described in detail below with reference to the drawings and specific embodiments. At the same time, it should be noted here that in order to make the embodiments more detailed, the following embodiments are the best and preferred embodiments. For some well-known technologies, those skilled in the art can also adopt other alternative methods for implementation; and the drawings are only for more specifically describing the embodiments, and are not intended to specifically limit the present invention.

[0027] As Figure 1 - Figure 2 shown, a method for basic investigation of the ecological protection red line based on territorial spatial planning includes the following steps: S1, data collection: Synchronously obtain spatial data of ecological elements through satellite remote sensing, unmanned aerial vehicle aerial survey, and ground sensors, including vegetation coverage, surface water distribution, and soil erosion intensity; S2, dynamic zoning of ecological elements: After matching the spatio-temporal characteristics of the obtained spatial data of ecological elements and combining with the topographic undulation factor, an improved spatial clustering algorithm is used to generate a dynamic zoning map of ecological factors; S3, three-dimensional sensitivity modeling: Based on the dynamic zoning map of ecological factors in S2, the elevation gradient correction coefficient is superimposed to construct a three-dimensional ecological sensitivity evaluation model, evaluate the sensitivity of the ecosystem, and output the three-dimensional sensitivity evaluation results; S4, dynamic delineation of red lines: Based on the three-dimensional sensitivity evaluation results output by S3, a dynamic threshold adjustment algorithm is used to delineate the boundaries of the ecological protection red lines and generate a preliminary ecological protection red line plan; S5, multi-dimensional verification and evaluation: Conduct three-dimensional verification and evaluation of the preliminary ecological protection red line plan of S4 in terms of natural ecological stability, regional economic carrying capacity, and social acceptance to generate the final ecological protection red line plan.

[0028] S1 includes: S11, satellite remote sensing data collection: collect spatial data on vegetation coverage, surface water distribution and soil erosion intensity in the target area through satellite remote sensing equipment, use remote sensing sensors (such as optical sensors, radar sensors, etc.) to obtain high-resolution remote sensing images, extract vegetation index (such as NDVI) based on the collected images using image processing methods to estimate vegetation coverage, infer surface water distribution through multi-band remote sensing data, and evaluate soil erosion intensity in combination with soil surface characteristics of remote sensing images; S12, UAV aerial survey data collection: Use UAVs equipped with high-precision sensors to conduct aerial surveys to obtain high-precision three-dimensional spatial data on vegetation coverage, surface water distribution, and soil erosion intensity in the area; When using drones for aerial surveys, the flight path, flight altitude, and image shooting angle are designed based on regional characteristics to ensure data accuracy and coverage. After collection, the images are geometrically and radiometrically corrected, and specific ecological element data are extracted through image analysis.

[0029] S13, ground sensor data collection: deploying ground sensors in the target area to perform synchronous data collection, specifically including: Vegetation coverage measurement: Real-time monitoring of vegetation coverage is carried out through ground-based spectral sensors or infrared sensors to obtain accurate spatial distribution data.

[0030] Surface moisture distribution: Use soil moisture sensors, meteorological sensors, etc. to monitor the moisture distribution on the soil surface and vegetation surface in real time.

[0031] Soil erosion intensity monitoring: By deploying soil erosion intensity sensors, we can monitor the erosion effects of water flow, wind erosion and other factors on the soil and collect soil erosion intensity data; S14, Synchronous Data Spatiotemporal Matching and Fusion: Match and fuse the satellite remote sensing, UAV aerial survey, and ground sensor data obtained in S11, S12, and S13 in terms of time and space to ensure the precise docking of data from different sources. Through methods such as data alignment and coordinate transformation, integrate data with different resolutions and formats into a unified three-dimensional spatial data layer for subsequent analysis.

[0032] S2 includes: S21, Spatiotemporal Feature Matching: Perform spatiotemporal feature matching on the collected data of vegetation coverage, surface water distribution, and soil erosion intensity. First, standardize the timestamps of each type of data to ensure the consistency of data collected at different time periods in terms of time. Second, through spatial alignment methods (such as coordinate transformation and projection transformation), convert data from different platforms (satellites, UAVs, ground sensors) into a unified spatial coordinate system. Finally, perform spatial resolution matching on different data sources through a spatial resolution unification algorithm (such as interpolation algorithm) to ensure that all data is analyzed at the same spatial scale; S22, Calculation of Terrain Relief Factor: Calculate the terrain relief factor of the region based on the digital elevation model (DEM) of the region; First, extract the terrain slope, aspect, and elevation parameters from the DEM data to obtain the terrain features of each pixel point. Then, according to ecological principles, analyze the relationship between terrain features and ecological elements, define the terrain relief factor, and assign it to each spatial unit (pixel or grid). The terrain relief factor will serve as an important weight factor in spatial clustering analysis, reflecting the impact of terrain on the distribution of ecological elements.

[0033] S23, Application of Clustering Algorithm: Use the improved K-means algorithm to perform clustering analysis on the data in steps S21 and S22; Compared with the traditional K-means algorithm, the improved K-means algorithm introduces ecological factors (vegetation coverage, surface water distribution, soil erosion intensity) and terrain relief factors (slope, aspect, etc.) for joint weighting, enhancing the adaptability of the algorithm to complex ecological regions. The specific operation steps of the improved K-means algorithm are as follows: (1) Initialization stage: First, calculate the feature vector of each data point according to ecological elements (vegetation coverage, surface water distribution, soil erosion intensity) and terrain relief factors. The feature vector includes: The numerical values of vegetation coverage, surface water distribution, and soil erosion intensity (after standardization).

[0034] Terrain relief factors, such as slope, aspect, etc. data, are processed using the same standardization method as the ecological element data; Randomly select K initial clustering centers, and the value of K is reasonably set according to the geographical characteristics and ecological diversity of the target area.

[0035] (2) Clustering calculation stage: Calculate distances: For each data point, calculate the distances between its feature vector and the K clustering centers. The distance metric uses the weighted Euclidean distance (or other suitable distance metrics), where the weighting coefficients are set according to the relative importance of each ecological factor and terrain factor.

[0036] For example, when the influence weight of vegetation coverage on ecological zoning is relatively high, a larger weight value can be set for vegetation coverage; the terrain undulation factor is given an appropriate weight according to the influence of different terrains; Reassign data points: Assign each data point to the nearest clustering center to generate K clusters; (3) Update clustering center stage: For the data points within each cluster, calculate the weighted mean of the cluster to update the position of the clustering center. When calculating the weighted mean, consider the weights of each ecological factor and terrain factor to ensure that the new clustering center can better represent the comprehensive ecological characteristics within the cluster.

[0037] Iteratively perform the above clustering and updating steps until the clustering centers no longer change significantly or reach the maximum number of iterations.

[0038] (4) Output of clustering results: Finally, obtain the clustering regions after the joint weighting of K ecological factors and terrain factors. Each region represents an ecological zoning with similar ecological and terrain characteristics. The clustering results reflect the comprehensive differences in vegetation coverage, surface water distribution, soil erosion intensity, and terrain characteristics in different regions.

[0039] The output clustering results will be used as the basis for the subsequent delineation of the ecological protection red line and generate a preliminary dynamic zoning map of ecological factors.

[0040] S2 also includes: S24, Generation of dynamic zoning map: Generate a dynamic zoning map of ecological factors according to the clustering analysis results. Each clustering region will be marked with its main ecological characteristics, such as the average value or range of vegetation coverage, water distribution, and soil erosion intensity. This zoning map will provide a basis for the subsequent delineation of the ecological protection red line and ecological sensitivity assessment. At the same time, the generated dynamic zoning map is used to analyze the variation laws of different ecological factors under different terrain conditions; S25, Verification and optimization of the zoning map: Verify and optimize the generated dynamic zoning map of ecological factors; First, verify the accuracy of the zoning by comparing it with actual ecological data (such as field survey results, historical ecological data, etc.). Secondly, adjust and optimize the zoning map according to criteria such as the stability of the ecological environment and the distribution of biodiversity within the region to ensure that the generated zoning has high ecological significance and protection value.

[0041] S3 includes: S31, Ecological factor dynamic zoning map: Receive the generated ecological factor dynamic zoning map, which has been spatially clustered based on factors such as vegetation coverage, surface water distribution, soil erosion intensity, and terrain undulation. Each zone represents an area with similar ecological characteristics and contains relevant ecological factor data, including the distribution range and intensity of vegetation coverage, the spatial pattern of surface water distribution, and the spatial variation of soil erosion intensity; S32, Elevation gradient correction coefficient calculation: Calculate the elevation gradient correction coefficient for each spatial unit according to the digital elevation model (DEM) of the target area. The specific steps are as follows: Calculate elevation difference: Extract the elevation value of each pixel point from the DEM and calculate the elevation difference between adjacent pixels to obtain the elevation gradient; Elevation gradient correction: Set the elevation gradient correction coefficient based on the impact of terrain on ecological sensitivity. For example, in areas with a larger slope, soil and water loss may be more severe, so its elevation correction coefficient can be appropriately increased; Correction coefficient assignment: Assign the correction coefficient to each spatial unit in the ecological factor dynamic zoning map to obtain a dataset with elevation correction coefficients; S33, Construct a three-dimensional ecological sensitivity evaluation model: Based on the ecological factor data and terrain elevation correction coefficient, construct a three-dimensional ecological sensitivity evaluation model. The basic principle of the three-dimensional ecological sensitivity evaluation model is to combine the ecological factor data and terrain elevation correction coefficient to evaluate the ecological sensitivity of each region. The specific steps are as follows: Model input: Input the ecological factor data (vegetation coverage, surface water distribution, soil erosion intensity) and elevation gradient correction coefficient of each spatial unit.

[0042] Sensitivity calculation: Adopt a weighted comprehensive model, assign different weights to different ecological factors and elevation correction coefficients, and perform weighted calculations according to their impact on the sensitivity of the ecosystem.

[0043] For example, the reduction of vegetation coverage may lead to an increase in ecological sensitivity, so the impact weight of vegetation coverage is relatively large; the relationship between soil erosion intensity and terrain undulation factors will affect the distribution of correction coefficients.

[0044] Calculating the sensitivity index: By means of weighted summation, calculate the ecological sensitivity index for each region to obtain a three-dimensional sensitivity data layer. Each pixel in this layer represents the ecological sensitivity at that location, and the larger the value, the higher the sensitivity of the ecosystem.

[0045] S34, Output of the three-dimensional sensitivity evaluation result: According to the constructed three-dimensional ecological sensitivity evaluation model, evaluate the sensitivity of the ecosystem in the target area, output the three-dimensional sensitivity evaluation result, and generate a three-dimensional sensitivity evaluation result map. This map shows the sensitivity index of each region and can be visualized as different color scales or contour lines for an intuitive display of the spatial distribution of ecological sensitivity within the region.

[0046] S3 also includes: S35, Sensitivity level classification: According to the ecological sensitivity index in the three-dimensional sensitivity evaluation result map, divide the region into several sensitivity levels. The division examples are as follows: Low sensitivity: Sensitivity index < 0.4; Medium sensitivity: 0.4 ≤ sensitivity index < 0.6; High sensitivity: 0.6 ≤ sensitivity index < 0.8; Extremely high sensitivity: Sensitivity index > 0.8; These thresholds are for reference only. In actual use, they should be adjusted in combination with the actual situation of the target area and the statistical distribution of the ecological sensitivity index. For example: In some areas with relatively fragile ecological environments, more conservative thresholds may be adopted, that is, a sensitivity index above 0.6 is considered high sensitivity.

[0047] In relatively robust ecosystems, the thresholds can be appropriately relaxed; Suppose there are three ecological factors: the normalized values corresponding to vegetation coverage, soil erosion intensity, and surface water are: 0.8, 0.6, 0.7, and the weights of each factor are respectively: Vegetation coverage weight 0.4; Soil erosion intensity weight 0.3; Surface water weight 0.3; Sensitivity index: Sensitivity index = (0.8 × 0.4) + (0.6 × 0.3) + (0.7 × 0.3) = 0.32 + 0.18 + 0.21 = 0.71 The sensitivity index of this region is 0.71, indicating that this region is at a high ecological sensitivity level; S36, Spatial distribution display: Visualize the regions of each sensitivity level as a three-dimensional map with different colors or shades, which is convenient for an intuitive understanding of the spatial sensitivity distribution of the ecosystem; S37, Result Verification and Optimization: Verify and optimize the generated three-dimensional ecological sensitivity evaluation results. The specific steps are as follows: Verification: Verify the accuracy of the generated ecological sensitivity results through methods such as on-site investigation, historical ecological data, and expert evaluation.

[0048] Optimization: According to the verification results, adjust the model parameters, optimize the weighting coefficients or model algorithms to further improve the accuracy and applicability of the evaluation results.

[0049] S4 includes: S41, Receive Three-Dimensional Sensitivity Evaluation Results: Receive the generated three-dimensional sensitivity evaluation results. The results include the ecological sensitivity indices of each spatial unit, which reflect the ecological vulnerability of each region. This result can be a three-dimensional raster dataset representing the sensitivity values of each raster, ranging from 0 (low sensitivity) to 1 (extremely high sensitivity).

[0050] S42, Determine the Red Line Boundary Threshold: Set the preliminary red line boundary threshold according to the ecological protection objectives of the region and the requirements for delineating the red line. The selection of the threshold is based on the following factors: Ecological Protection Requirements: Set the threshold according to the ecological protection objectives of the region. If the goal is to protect areas with higher ecological sensitivity, a lower threshold can be selected. Conversely, if areas with lower sensitivity need to be protected, a higher threshold can be chosen.

[0051] Policy Requirements: Combine relevant ecological protection regulations to determine the criteria for delineating the ecological protection red line.

[0052] Three-Dimensional Sensitivity Evaluation Results: Dynamically adjust the threshold according to the three-dimensional sensitivity evaluation results. Specifically, in areas with higher sensitivity indices within the region, the red line threshold can be appropriately lowered, while in areas with lower sensitivity, the threshold can be increased.

[0053] S43, Dynamic Threshold Adjustment Algorithm: Use the dynamic threshold adjustment algorithm to optimize the preliminary set red line boundary to make the red line delineation result more accurate. The specific steps are as follows: Preliminary Red Line Setting: According to the threshold setting, first conduct a preliminary classification of the three-dimensional sensitivity evaluation results and divide the region into different sensitivity levels. For high-sensitivity regions (such as areas where the sensitivity index is higher than a certain threshold), they are initially delineated as ecological protection red line regions.

[0054] Threshold Dynamic Adjustment: For the initially delineated red line boundary, make dynamic adjustments according to the following criteria: Ecological Feature Similarity Adjustment: If the ecological features of adjacent regions have small differences (such as similar sensitivity indices), the red line region can be appropriately expanded or contracted to ensure the rationality of the red line.

[0055] Topographic factor adjustment: Considering the impact of topographic factors on the ecological environment, for example, areas with steeper slopes may face higher risks of soil erosion, the red line boundary should be adjusted according to the correction factors of slope or elevation gradient.

[0056] Spatial clustering analysis adjustment: Through spatial clustering analysis, the ecological sensitivity data within the region is reclustered to further optimize the red line boundary and avoid overly fragmented red line delineation.

[0057] Automated boundary optimization: Further adjust the red line boundary through the simulated annealing algorithm to make the red line area more in line with the requirements of ecological protection while avoiding unreasonable boundary cuts.

[0058] The steps to optimize the red line boundary using the simulated annealing algorithm are as follows: (1) Define the optimization objective function: First, an objective function needs to be defined as the criterion for evaluating the optimization effect of the red line boundary. The objective function usually considers the following factors: Maximize ecological protection value: Ensure that the area covered by the red line has high ecological sensitivity, that is, protect areas with vulnerable and sensitive ecosystems as much as possible.

[0059] Regional connectivity: The optimized red line boundary should avoid fragmentation as much as possible, ensure good connectivity between ecological protection areas, and avoid isolated ecological protection areas.

[0060] Rationality of the red line boundary: The red line boundary should conform to the actual terrain and ecological system characteristics as much as possible, and avoid unnatural cuts.

[0061] The objective function can be expressed as: Ecological value Connectivity Rationality; where, , , are the weights of the corresponding factors to ensure a reasonable balance among the three during the optimization process; (2) Initialize the solution space and state representation: The initial solution of the red line boundary is obtained through the set preliminary red line plan, and this solution can be represented in a rasterized manner, where the state of each raster cell indicates whether the cell belongs to the red line area (for example, 1 indicates that the raster belongs to the red line, and 0 indicates that it does not); The initial solution space is all possible combinations of red line boundaries, and optimization can be carried out through neighborhood search. Each search change will generate a new red line boundary solution.

[0062] (3) Set the temperature and iteration process of simulated annealing: The simulated annealing algorithm gradually reduces the "temperature" by simulating the annealing process of a physical system, enabling the system to gradually transition from the initial state to the global optimal solution.

[0063] (3.1) Initial temperature setting: Set a relatively high initial temperature according to the complexity of the problem (e.g., the initial temperature is 1000). The high temperature helps the algorithm jump out of the local optimal solution and attempt different boundary delimitation schemes.

[0064] (3.2) Temperature decay: Control the search scope by gradually reducing the temperature. The slower the temperature decreases, the more refined the search process, and it finally converges to the global optimal solution. The temperature decay function is: ; where is the current temperature, is the decay factor, usually taking values from 0.9 to 0.99; (3.3) Acceptance criterion: In each iteration, the algorithm generates a new candidate solution and calculates its objective function value. If the new solution is better than the current solution, accept this solution; if the new solution is worse, accept it according to the temperature acceptance probability, and the probability is: ; If this solution is accepted, update the current solution; otherwise, continue to retain the current solution; (4) Neighborhood search and solution adjustment: In each iteration process, the simulated annealing algorithm conducts a neighborhood search on the current solution, that is, generates new candidate solutions by slightly adjusting the current red line boundary. Common neighborhood search methods include: Local area expansion / contraction: Expand or contract part of the red line boundary to increase or decrease the protected area.

[0065] Red line boundary smoothing: Smooth the boundary to avoid overly tortuous boundaries and improve its naturalness.

[0066] Merge / split regions: Merge adjacent red line regions or split larger red line regions to ensure the connectivity of the regions.

[0067] (5) Stopping criterion and output of the optimal solution: The simulated annealing algorithm stops iterating when the temperature drops to a certain level or after reaching the maximum number of iterations. The finally output solution is the optimized red line boundary; S44, Generation of the red line boundary and output of the preliminary plan: According to the optimized red line boundary, generate a preliminary ecological protection red line plan. The specific steps are as follows: Red-line area demarcation: Based on the adjusted sensitivity index threshold, the boundaries of the red line are finally determined, and the ecological protection red-line area is marked. This area is usually a region with relatively high ecological sensitivity that requires priority protection.

[0068] Output of the preliminary red-line plan: Generate a preliminary red-line plan that includes the red-line boundaries. This plan can be visualized as a spatial distribution map of the red line, indicating the specific location, boundaries, and ecological elements included in the red line.

[0069] S45, Review and optimization of the preliminary red-line plan: Conduct expert review and optimization of the generated preliminary ecological protection red-line plan to ensure that the demarcation results meet the ecological protection objectives. The specific steps include: Expert review: Have the preliminary red-line plan reviewed by an expert group to evaluate whether it is reasonable and meets the requirements of ecological protection.

[0070] Adjustment and optimization: Further optimize the red-line boundaries based on the expert review results. Possible optimization directions include: adjusting the boundaries according to ecological data and expert suggestions, and correcting areas with problems in red-line demarcation.

[0071] S5 includes: S51, Assessment of natural ecological stability: Conduct an assessment of the natural ecological stability of the preliminary ecological protection red-line plan. The assessment of natural ecological stability aims to verify whether the ecological systems in the ecological protection red-line area can maintain long-term stability and self-repair ability. The specific steps are as follows: Assessment of ecosystem health: Use data such as vegetation coverage, soil erosion intensity, and surface water to calculate the ecosystem health index of the red-line area, and evaluate the overall stability and recovery ability of the ecosystem. Higher vegetation coverage and good water distribution usually indicate a relatively healthy ecosystem.

[0072] Identification of ecological vulnerability: Identify areas within the red-line area that are ecologically vulnerable, such as areas with high soil erosion intensity and insufficient vegetation coverage. Calculate the proportion of these vulnerable areas in the red-line area, and identify potential ecological risk areas through spatial analysis.

[0073] S52, Assessment of regional economic carrying capacity: Conduct an assessment of the regional economic carrying capacity of the preliminary ecological protection red-line plan. The assessment of regional economic carrying capacity is used to evaluate whether economic activities within the red-line area will be restricted by the red-line boundaries and whether it is possible to balance economic development and ecological protection. The specific steps are as follows: Analysis of the current land use situation: By obtaining the land use data within the region, analyze the current land use types in the red-line area, including agriculture, industry, residential areas, etc. Evaluate the intensity and spatial layout of economic activities within the red-line area based on the current land use situation.

[0074] Analysis of the impact of economic activities: Evaluate the potential impact of economic activities (such as agricultural production, infrastructure construction, etc.) within the red line area on the ecological environment, with a focus on areas that are more sensitive to the ecological environment, and judge the negative impacts that economic activities may have on the ecological protection red line area.

[0075] Calculation of carrying capacity: Through the economic carrying capacity model, combined with economic data such as the GDP and per capita income of the region, calculate the economic carrying capacity of the red line area. This model can evaluate the carrying capacity of regional economic activities and ensure the coordination between the economy and ecological protection.

[0076] S53, Assessment of social acceptance: Conduct an assessment of the social acceptance of the preliminary ecological protection red line plan. The assessment of social acceptance aims to determine the social support for the demarcated red line area, evaluate the degree of recognition of the red line boundary demarcation by social groups (such as local residents, enterprises, policymakers, etc.). The specific steps are as follows: Solicitation of public opinions: Through forms such as questionnaires and symposiums, widely solicit the opinions of the public on the red line demarcation. The survey content includes the ecological value of the demarcated red line area, its impact on economic development, and its impact on residents' lives, etc.

[0077] Assessment of social and economic impacts: Analyze the impact of the red line demarcation on the local economy, residents' living standards, and social employment. For example, evaluate issues such as potential farmland losses, land expropriation problems, and infrastructure construction restrictions caused by the red line demarcation.

[0078] S54, Three-dimensional comprehensive assessment and optimization: Conduct a comprehensive analysis of the assessment results of natural ecological stability, regional economic carrying capacity, and social acceptance, and output the final ecological protection red line plan. The specific steps are as follows: Weighted comprehensive assessment: According to the assessment results of different dimensions, set weights (according to the priority of ecological protection goals), and perform a weighted sum of the assessment results of the three aspects. For example, the weight of ecological stability may be relatively large, while the weight of social acceptance is relatively small.

[0079] Optimization and adjustment: According to the comprehensive assessment results, judge whether the preliminary red line plan needs to be adjusted. If the ecological stability of a certain area is poor, the economic carrying capacity is too high, or the social acceptance is low, then consider adjusting the red line boundary, reducing the demarcation of these areas, and adding other areas that better meet the requirements of ecological protection.

[0080] Output of the final red line plan: Through the optimized and adjusted red line plan, output the final ecological protection red line plan. This plan should achieve a balance among ecological protection, economic development, and social acceptance to ensure feasibility and effectiveness.

[0081] The present invention encompasses any alternatives, modifications, equivalent methods, and solutions that are made within the spirit and scope of the present invention. For the public to have a thorough understanding of the present invention, specific details are described in detail in the following preferred embodiments of the present invention. However, those skilled in the art can fully understand the present invention even without the description of these details. Additionally, well-known methods, processes, flows, components, and circuits, etc. are not described in detail to avoid unnecessary confusion to the essence of the present invention.

[0082] The above description is only a preferred embodiment of the present invention. It should be noted that for those of ordinary skill in the art, without departing from the principle of the present invention, several improvements and refinements can be made, and these improvements and refinements should also be regarded as the protection scope of the present invention.

Claims

1. A basic survey method for ecological protection red lines based on national land space planning, characterized in that: The following steps are involved: S1, data collection: spatial data of ecological elements, including vegetation coverage, surface water distribution and soil erosion intensity, are obtained synchronously through satellite remote sensing, drone aerial survey and ground sensors; S2, dynamic partitioning of ecological factors: after matching the spatial and temporal characteristics of the acquired ecological factor spatial data, combined with the terrain relief factor, an improved spatial clustering algorithm is used to generate a dynamic partitioning map of ecological factors; S3, three-dimensional sensitivity modeling: Based on the dynamic zoning map of ecological factors in S2, the elevation gradient correction coefficient is superimposed to construct a three-dimensional ecological sensitivity evaluation model, evaluate the sensitivity of the ecosystem, and output the three-dimensional sensitivity evaluation results; S4, dynamic delineation of red lines: Based on the three-dimensional sensitivity evaluation results output by S3, a dynamic threshold adjustment algorithm is used to delineate the boundaries of the ecological protection red lines and generate a preliminary ecological protection red line plan; S5, multi-dimensional verification and evaluation: Conduct three-dimensional verification and evaluation of the preliminary ecological protection red line plan of S4 in terms of natural ecological stability, regional economic carrying capacity, and social acceptance to generate the final ecological protection red line plan.

2. According to claim 1, a basic survey method for ecological protection red lines based on national land space planning is characterized in that: The S1 includes: S11, satellite remote sensing data collection: collect spatial data on vegetation coverage, surface water distribution and soil erosion intensity in the target area through satellite remote sensing equipment; S12, UAV aerial survey data collection: Use UAVs equipped with sensors to conduct aerial surveys to obtain three-dimensional spatial data on vegetation coverage, surface water distribution, and soil erosion intensity in the area; S13, ground sensor data collection: deploying ground sensors in the target area to perform synchronous data collection; S14, synchronous data spatiotemporal matching and fusion: match and fuse the satellite remote sensing, UAV aerial survey and ground sensor data obtained in S11, S12 and S13 in time and space, and integrate data of different resolutions and formats into a unified three-dimensional spatial data layer.

3. According to claim 2, a basic survey method for ecological protection red lines based on national land space planning is characterized in that: The S2 includes: S21, temporal and spatial feature matching: Temporal and spatial feature matching of the collected vegetation coverage, surface water distribution and soil erosion intensity data; S22, terrain relief factor calculation: calculate the terrain relief factor of the region according to the digital elevation model of the region; S23, clustering algorithm application: using an improved K-means algorithm to perform cluster analysis on the data in steps S21 and S22.

4. According to claim 3, a basic survey method for ecological protection red lines based on national land space planning is characterized in that: The S2 further includes: S24, dynamic partition map generation: generating a dynamic partition map of ecological factors based on the cluster analysis results; S25, zoning map verification and optimization: verify and optimize the generated dynamic zoning map of ecological factors.

5. According to claim 4, a basic survey method for ecological protection red lines based on national land space planning is characterized in that: The S3 includes: S31, dynamic zoning map of ecological factors: based on the generated dynamic zoning map of ecological factors, extract the relevant ecological factor data in the dynamic zoning map of ecological factors, including the distribution range and intensity of vegetation coverage, the spatial pattern of surface water distribution and the spatial change of soil erosion intensity; S32, calculation of elevation gradient correction coefficient: calculating the elevation gradient correction coefficient of each spatial unit according to the digital elevation model of the target area; S33, constructing a three-dimensional ecological sensitivity evaluation model: constructing a three-dimensional ecological sensitivity evaluation model based on ecological factor data and terrain elevation correction coefficient; S34, three-dimensional sensitivity evaluation result output: according to the constructed three-dimensional ecological sensitivity evaluation model, the sensitivity of the ecosystem in the target area is evaluated, the three-dimensional sensitivity evaluation results are output, and a three-dimensional sensitivity evaluation result map is generated.

6. The basic survey method of ecological protection red line based on national land space planning according to claim 5 is characterized in that: The S3 further includes: S35, sensitivity level division: according to the ecological sensitivity index in the three-dimensional sensitivity assessment result map, the area is divided into several sensitivity levels; S36, spatial distribution display: visualize each sensitivity level area as a three-dimensional map with different colors or shadows; S37, result verification and optimization: Verify and optimize the generated three-dimensional ecological sensitivity assessment results.

7. The basic survey method of ecological protection red line based on national land space planning according to claim 6 is characterized in that: The S4 includes: S41, receiving a three-dimensional sensitivity evaluation result: receiving a generated three-dimensional sensitivity evaluation result, the result including an ecological sensitivity index of each spatial unit; S42, determine the red line boundary threshold: set the preliminary red line boundary threshold according to the regional ecological protection goals and red line delineation requirements; S43, dynamic threshold adjustment algorithm: using a dynamic threshold adjustment algorithm to optimize the initially set red line boundary; S44, red line boundary generation and preliminary plan output: Generate a preliminary ecological protection red line plan based on the optimized red line boundary; S45, Review and optimization of preliminary red line scheme: Expert review and optimization of the generated preliminary ecological protection red line scheme.

8. The basic survey method for ecological protection red lines based on national land space planning according to claim 7 is characterized in that: The S5 includes: S51, Natural Ecological Stability Assessment: Conduct a natural ecological stability assessment on the preliminary ecological protection red line plan. The natural ecological stability assessment aims to verify whether the ecosystem in the ecological protection red line area can maintain long-term stability and self-repair capabilities; S52, Regional Economic Carrying Capacity Assessment: Conduct regional economic carrying capacity assessment on the preliminary ecological protection red line plan. The regional economic carrying capacity assessment is used to assess whether economic activities within the red line area will be restricted by the red line boundary; S53, Social Acceptance Assessment: Conduct a social acceptance assessment on the preliminary ecological protection redline plan. The social acceptance assessment aims to determine the social support for the redline demarcation area and assess the degree of recognition of the redline boundary demarcation by social groups; S54, three-dimensional comprehensive assessment and optimization: Comprehensively analyze the assessment results of natural ecological stability, regional economic carrying capacity, and social acceptance, and output the final ecological protection red line plan.

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