Method and system for accurately identifying structural features of regional landscape ecological network

Abstract

The invention provides a structural feature accurate identification method and system for a regional landscape ecological network, and the method comprises the steps: determining a landscape change feature set through detecting a change pattern spot, carrying out the local updating of a pixel value of a basic ecological resistance surface of a target region according to the landscape change feature set, and obtaining a dynamic ecological resistance surface; performing minimum cumulative resistance analysis through the dynamic ecological resistance surface, and generating a potential ecological corridor in the target area according to an analysis result; performing spatial overlay analysis on the potential ecological corridor and the landscape change feature set, and further identifying ecological obstacle points in the potential ecological corridor; and in a computer-aided design environment, carrying out topology correction on the potential ecological corridor according to the ecological obstacle point to obtain a digitized structural model of the regional landscape ecological network. By adopting the scheme of the invention, fusion perception can be performed on the spatial-temporal dynamic process of the landscape structure so as to accurately identify the structural features.

Description

Technical Field

[0001] This application relates to the field of regional landscape ecological network technology, and more specifically, to a method and system for accurate identification of the structural features of regional landscape ecological networks. Background Technology

[0002] Regional landscape ecological networks refer to a process of integrating discrete natural habitats and ecological elements within a region into a multi-level spatial system with structural connectivity and functional integrity through a series of spatial analysis and planning processes, such as identifying core ecological patches, extracting potential ecological corridors, optimizing landscape connectivity, and simulating ecological process flows. This process aims to achieve a leap from isolated habitat protection to collaborative management of regional ecosystems.

[0003] Traditional methods for identifying regional landscape ecological network structures often rely on static ecological resistance surfaces generated from historical land use data. These methods struggle to effectively respond to and integrate the dynamic evolution of landscape patterns that occurs continuously during the observation period. This leads to a disconnect between the identified network structure features and actual ecological processes, resulting in significant timeliness and accuracy biases. For example, traditional methods may fail to promptly and accurately reflect the surge in local resistance caused by the latest land use changes (such as forest land conversion to construction land or wetland conversion to farmland) onto the resistance surface. Instead, they may still plan theoretically optimal corridors traversing areas with existing high-resistance barriers based on outdated baseline data. These corridor segments, lacking resistance increment superposition and spatial verification based on changing map features, fail to reveal their inherent connectivity defects. Ultimately, this results in false connectivity channels or ineffective ecological investments that do not conform to the current landscape pattern in ecological protection and restoration practices. Therefore, how to integrate and perceive the spatiotemporal dynamic processes of landscape structures to accurately identify structural features has become a challenge for the industry. Summary of the Invention

[0004] This application provides a method and system for accurate identification of the structural features of a regional landscape ecological network, which can integrate and perceive the spatiotemporal dynamic process of landscape structure to accurately identify structural features.

[0005] Firstly, this application provides a method for accurately identifying the structural characteristics of regional landscape ecological networks, comprising the following steps: Detect the changing patches of the target area at different time phases, and then generate a landscape change feature set of the target area; The pixel values ​​of the basic ecological resistance surface in the target area are locally updated based on the landscape change feature set to obtain the dynamic ecological resistance surface. The dynamic ecological resistance surface is used to perform minimum cumulative resistance analysis between preset ecological source areas, and then potential ecological corridors in the target area are generated based on the analysis results. By spatially overlaying the potential ecological corridors with the landscape change feature set, ecological barrier points in the potential ecological corridors can be identified. In a computer-aided design environment, the potential ecological corridors are topologically corrected based on the ecological barrier points to obtain a digital structural model of the regional landscape ecological network.

[0006] In some embodiments, the pixel values ​​of the basic ecological resistance surface of the target area are locally updated based on the landscape change feature set to obtain the dynamic ecological resistance surface, specifically including: Obtain the basic ecological resistance surface of the target area; Based on the vector boundaries of the landscape change feature set change patches and their ecological resistance influence weights, a local ecological resistance change raster layer is generated. The dynamic ecological resistance surface is obtained by performing spatial algebraic operations on the corresponding pixel values ​​of the basic ecological resistance surface through the local ecological resistance change raster layer.

[0007] In some embodiments, performing minimum cumulative resistance analysis between preset ecological source areas using the dynamic ecological resistance surface specifically includes: Obtain preset ecological source vector information in the target area; Based on the dynamic ecological resistance surface and the ecological source vector information, the minimum cumulative resistance value from each ecological source to each pixel in space is determined, and then the cumulative resistance surface is generated. The minimum cost path between different ecological source areas is determined based on the cumulative resistance surface.

[0008] In some embodiments, generating potential ecological corridors in the target area based on the analysis results specifically includes: All minimum cost paths are vectorized and extracted to obtain the initial corridor segments; The initial corridor segments are spatially connected to construct a preliminary corridor network; The preliminary corridor network is topologically smoothed to generate potential ecological corridors in the target area.

[0009] In some embodiments, spatially overlaying the potential ecological corridor with the landscape change feature set to identify ecological barrier points in the potential ecological corridor specifically includes: Spatial intersection analysis is performed on the potential ecological corridors and the set of landscape change features to generate a set of spatial intersection elements. Determine the degree to which the spatial intersection element set hinders corridor connectivity; Ecological obstacle points in the potential ecological corridor are identified based on the degree of obstacle.

[0010] In some embodiments, topological correction of the potential ecological corridors based on the ecological barrier points to obtain a digital structural model of the regional landscape ecological network specifically includes: Based on the spatial location of the ecological barrier points, the potential ecological corridors are topologically segmented to generate multiple disconnected corridor segments. Under the constraint of the dynamic ecological resistance surface, alternative connection paths are generated that bypass the ecological barrier points between all corridor segments. A digital structural model of the regional landscape ecological network is generated by using all corridor segments and all alternative connection paths.

[0011] In some embodiments, the landscape change feature set refers to a vector dataset containing spatial geometric information and attribute information.

[0012] Secondly, this application provides a system for accurately identifying the structural characteristics of regional landscape ecological networks, including: The detection module is used to detect the changing patches of the target area at different time phases, and then generate a landscape change feature set of the target area; The processing module is used to locally update the pixel values ​​of the basic ecological resistance surface of the target area based on the landscape change feature set, so as to obtain the dynamic ecological resistance surface. The processing module is also used to perform minimum cumulative resistance analysis between preset ecological source areas through the dynamic ecological resistance surface, and then generate potential ecological corridors in the target area based on the analysis results. The processing module is also used to perform spatial overlay analysis of the potential ecological corridor and the landscape change feature set, thereby identifying ecological barrier points in the potential ecological corridor. The execution module is used to perform topological correction on the potential ecological corridors based on the ecological barrier points in a computer-aided design environment, so as to obtain a digital structural model of the regional landscape ecological network.

[0013] Thirdly, this application provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps of the above-described method for accurately identifying the structural features of regional landscape ecological networks.

[0014] Fourthly, this application provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the above-described method for accurately identifying the structural features of regional landscape ecological networks.

[0015] The technical solutions provided by the embodiments disclosed in this application have the following beneficial effects: The method and system for accurately identifying the structural characteristics of regional landscape ecological networks provided in this application firstly generates a landscape change feature set by detecting changes in target area patches at different time phases, and then locally updates the pixel values ​​of the basic ecological resistance surface based on this landscape change feature set to obtain a dynamic ecological resistance surface. This process transforms the spatiotemporal dynamic changes of the landscape into quantifiable and spatially quantifiable resistance increment data, thereby transforming the complex and difficult-to-track landscape evolution process into a precise digital surface representation. By dynamically updating the resistance value, it provides a direct data tool and computational basis for responding to the latest landscape patterns at the ecological process level. Subsequently, the dynamic ecological resistance surface is used to perform minimum cumulative resistance analysis in a preset ecological source area to generate potential ecological corridors. Then, the potential ecological corridors are spatially overlaid with the landscape change feature set to identify ecological barrier points. This process can automatically locate and spatially delineate high-resistance areas in the corridor caused by landscape changes, and through overlay analysis, it identifies discrete, mathematically optimal paths. This process transforms the abstract network connectivity problem into a specific spatial segment with real-world connectivity deficiencies, thus converting it into an ecological restoration problem to be solved. Furthermore, with the goal of eliminating ecological barriers and constrained by ecological corridor connectivity, potential ecological corridors are topologically corrected in a computer-aided design environment. This process transforms the two key ecological constraints of barrier elimination and connectivity maintenance from external planning requirements into core operations driving network structure optimization. Topological correction applies direct spatial avoidance or resistance reduction strategies to identified barriers, while connectivity constraints prevent new breaks or detours during the correction process. This process provides bidirectional guidance for the construction of ecological networks, combining real-world adaptability and functional integrity. Finally, a digital structural model of the regional landscape ecological network is obtained through topological correction, ultimately applied to the spatial representation of the ecological network to achieve precise structural identification. In summary, this scheme can achieve fusion perception of the spatiotemporal dynamics of the landscape to accurately identify structural features. Attached Figure Description

[0016] Figure 1 This is a flowchart illustrating a method for accurately identifying the structural features of a regional landscape ecological network according to some embodiments of this application; Figure 2 This is a schematic flowchart illustrating the process of determining a dynamic ecological resistance surface according to some embodiments of this application; Figure 3 This is a flowchart illustrating the determination of the minimum cost path according to some embodiments of this application; Figure 4 This is a structural schematic diagram of a system for accurately identifying the structural features of a regional landscape ecological network, as shown in some embodiments of this application. Figure 5This is an internal structural diagram of a computer device for implementing a method for accurately identifying the structural features of a regional landscape ecological network, according to some embodiments of this application. Detailed Implementation

[0017] To better understand the technical solutions in this embodiment, the technical solutions in this embodiment will be described in detail below with reference to the accompanying drawings and specific implementation methods.

[0018] refer to Figure 1 The figure is a flowchart illustrating a method for accurately identifying the structural features of a regional landscape ecological network according to some embodiments of this application. The method for accurately identifying the structural features of a regional landscape ecological network mainly includes the following steps: In step 101, the changing patches of the target area under different time phases are detected, thereby generating a landscape change feature set of the target area.

[0019] In practice, firstly, high-resolution remote sensing images or land use / cover classification data of the target area at least two different time phases are acquired. Using a Geographic Information System (GIS) platform or remote sensing image processing platform, object-oriented change detection methods or pixel-based post-classification comparison methods are employed to identify land use patches that have undergone type transitions between the two time phases. These changed areas are then initially extracted as change patch units. Next, based on a preset, configurable set of ecological resistance impact rules, ecological impact analysis and assignment are performed on each change patch. This ecological resistance impact rule set is comprehensively formulated based on research findings on the ecological habits of key protected species in the target area, principles of landscape ecology, and a knowledge base of domain experts. It defines, in parametric form, the degree of impact of transitions between different land use types on species migration resistance (for example, the rule set explicitly states: "From high cover..."). The ecological resistance impact weight is +1.8 for converting forest land to transportation construction land and +0.2 for converting dry land to irrigated farmland. Next, for each changed patch, based on its specific conversion category ("from T1 time phase type A to T2 time phase type B"), the ecological resistance impact rule set is queried, and a quantitative ecological resistance impact weight value is assigned. Simultaneously, GIS vectorization tools are used to accurately extract the vector boundary of each changed patch. Finally, the geometric information of the vector boundary of each changed patch is attribute-associated with its corresponding ecological resistance impact weight value, and integrated to form a spatial vector dataset. This dataset is the landscape change feature set.

[0020] It should be noted that the landscape change feature set mentioned in this application refers to a vector dataset containing spatial geometric information and attribute information. Each element (i.e., a polygon) represents a land use type change that occurred during the observation period. Its attribute table contains at least the unique identifier, area, perimeter, and an ecological resistance impact weight field for the land use type change. This weight value quantitatively characterizes the increase or decrease in resistance to ecological processes (such as species dispersal) caused by this change. The changed land use type change refers to a continuous spatial area that has undergone a substantial change in land use or land cover type between two different time points, identified by remote sensing change detection technology. The ecological resistance impact rule set is an external, configurable parameter lookup table or knowledge base. Its core scientific basis comes from in-depth research on the habitat preference, dispersal capacity, and landscape connectivity requirements of specific ecological protection targets (such as a certain indicator species) in the target area. The specific parameter values ​​of the rules can be obtained through literature review, expert scoring, or model calibration based on historical ecological observation data. This application does not limit this.

[0021] In step 102, the pixel values ​​of the basic ecological resistance surface of the target area are locally updated according to the landscape change feature set to obtain the dynamic ecological resistance surface.

[0022] In some embodiments, reference Figure 2 As shown in the figure, this is a schematic diagram of the process for determining the dynamic ecological resistance surface according to some embodiments of this application. The dynamic ecological resistance surface can be obtained by locally updating the pixel values ​​of the basic ecological resistance surface of the target area based on the landscape change feature set through the following steps: First, in step 1021, the basic ecological resistance surface of the target area is obtained; Then, in step 1022, a local ecological resistance change raster layer is generated based on the vector boundary of the landscape change feature set change patch and its ecological resistance influence weight. Finally, in step 1023, spatial algebraic operations are performed on the corresponding pixel values ​​of the basic ecological resistance surface through the local ecological resistance change grid layer to obtain the dynamic ecological resistance surface.

[0023] In specific implementation, a reference raster data layer covering the target area can be generated through a geographic information system platform, and the reference raster data layer is determined as the basic ecological resistance surface. The numerical value of each pixel in the reference raster data layer represents the basic ecological resistance value of the corresponding geographic location under a preset reference state. The determination of the reference state is related to the starting phase of the observation period corresponding to the landscape change feature set or a preset background ecological condition. The setting of the basic ecological resistance value comprehensively considers the combined influence of multiple landscape factors such as land use type, topographic features, and human disturbance distance on the target ecological process under the reference state. Its assignment rules are based on existing ecological research conclusions or expert knowledge bases for key protected species in the target area. The basic ecological resistance surface serves as the spatial base and numerical benchmark for subsequent local updates.

[0024] It should be noted that the basic ecological resistance surface mentioned in this application refers to the ecological resistance raster data layer that characterizes the spatial heterogeneity of the target area under a preset baseline state. The value of each pixel is used to quantify the basic resistance intensity of the corresponding geographical location to the target ecological process, thereby serving as a numerical and spatial baseline for subsequent dynamic updates that incorporate the impact of landscape changes.

[0025] In specific implementation, the generation of a local ecological resistance change raster layer based on the vector boundaries of the changed patches in the landscape change feature set and their ecological resistance influence weights can be achieved in the following way: First, the landscape change feature set is input into a geographic information system; then, a blank raster layer with the same geographic coordinate system, spatial range, and pixel resolution as the basic ecological resistance surface is created as a calculation template; next, the vector polygon boundary of each changed patch in the landscape change feature set is used as the spatial constraint range, and the ecological resistance influence weight value recorded in the attribute table of the changed patch is used as the pixel value to be assigned, and the vector data to raster data conversion operation is performed; during this conversion process, for cases where there is spatial overlap or multiple changed patches within a pixel range, a preset conflict resolution rule is used to determine the final value of the pixel; after completing the conversion of all changed patches, a raster image is obtained that has a non-zero value only in the area where landscape change occurs, that is, the ecological resistance influence weight value, and zero values ​​in the rest of the area, and this raster image is determined as the local ecological resistance change raster layer.

[0026] It should be noted that the local ecological resistance change raster layer mentioned in this application refers to a spatial raster data layer, whose non-zero cell values ​​are used to accurately quantify the increase or decrease in ecological resistance caused by various land use change events recorded by the landscape change feature set.

[0027] In specific implementation, the dynamic ecological resistance surface can be obtained by performing spatial algebraic operations on the corresponding pixel values ​​of the basic ecological resistance surface through the local ecological resistance change raster layer. This can be achieved in the following way: for example, the basic ecological resistance surface and the local ecological resistance change raster layer are superimposed pixel by pixel. The specific rule of the superposition calculation is to perform an addition operation on the original resistance value of each pixel in the basic ecological resistance surface and the resistance change value recorded by the pixel at the same spatial position in the local ecological resistance change raster layer (i.e., the ecological resistance influence weight), and use the calculation result as the output value of the corresponding pixel of the new raster layer. After traversing all pixels and completing the above calculation, a complete raster data layer is generated, and the new raster data layer is used as the dynamic ecological resistance surface. In other embodiments, other methods can also be used, which are not limited here.

[0028] It should be noted that the dynamic ecological resistance surface mentioned in this application refers to a new comprehensive resistance raster data layer generated by performing spatial algebraic operations on the local ecological resistance change raster layer and the basic ecological resistance surface. It is used to characterize the spatial distribution of regional comprehensive ecological resistance with current information after incorporating the latest landscape change information, thereby providing a dynamic and accurate data foundation for subsequent minimum cumulative resistance analysis.

[0029] In step 103, the minimum cumulative resistance analysis is performed between preset ecological source areas using the dynamic ecological resistance surface, and potential ecological corridors in the target area are generated based on the analysis results.

[0030] In some embodiments, the minimum cumulative resistance analysis between preset ecological source areas using the dynamic ecological resistance surface can be achieved through the following steps: Obtain preset ecological source vector information in the target area; Based on the dynamic ecological resistance surface and the ecological source vector information, the minimum cumulative resistance value from each ecological source to each pixel in space is determined, and then the cumulative resistance surface is generated. The minimum cost path between different ecological source areas is determined based on the cumulative resistance surface.

[0031] In practice, the spatial extent of areas with core ecological functions can be extracted from the ecological protection planning map of the target area, the boundary of nature reserves, or high-value habitat areas assessed based on habitat suitability models. The spatial extent of these areas is converted into vector polygon features, and the set of vector polygon features is determined as the vector information of the ecological source areas. The selection of the ecological source areas is based on the importance of their ecosystem services, species diversity, or their key role in maintaining regional landscape connectivity. The vector information includes at least the spatial geometric boundary of each ecological source area and its unique identifier, and is loaded into the geographic information system platform as source data for minimum cumulative resistance analysis.

[0032] It should be noted that the ecological source vector information mentioned in this application refers to a set of spatial regions within the target area that are preset to have core ecological functions or serve as the starting point for species diffusion, expressed in vector data format, and is used to define the source point of ecological flow diffusion in landscape connectivity analysis.

[0033] In specific implementation, the minimum cumulative resistance value from each ecological source to each pixel in space is determined based on the dynamic ecological resistance surface combined with the ecological source vector information. This cumulative resistance surface can be generated in the following way: First, the dynamic ecological resistance surface is used as a resistance grid layer representing spatial heterogeneity, and the pixels covered by all ecological source polygons in the ecological source vector information are used as the calculation source point set. The algorithm starts from each source pixel, simulates the diffusion process to surrounding pixels, and calculates the minimum cumulative resistance value of the path required to reach each non-source pixel in space from the nearest source point. During the calculation, the movement cost between pixels is usually determined based on a preset function (such as the average value) of the resistance values ​​of adjacent pixels. By traversing the entire area, a new grid layer with the same range and resolution as the dynamic ecological resistance surface is finally generated, where the value of each pixel represents the minimum cumulative resistance value from the nearest ecological source to that location, and this new grid layer is used as the cumulative resistance surface.

[0034] It should be noted that the cumulative resistance surface mentioned in this application refers to the raster data layer calculated based on the dynamic ecological resistance surface and the vector information of the ecological source area. The value of each cell is used to quantify the minimum cumulative resistance that needs to be overcome to reach the spatial location from the nearest ecological source area, thereby reflecting the accessibility gradient when spreading from the ecological source area to the surrounding space.

[0035] For specific implementation, refer to Figure 3As shown in the figure, this is a flowchart illustrating the determination of the minimum cost path in some embodiments of this application. The determination of the minimum cost path between different ecological source areas based on the cumulative resistance surface can be achieved in the following ways: First, on the cumulative resistance surface, taking one of the pair of source areas as the target source, calculate the cumulative resistance surface facing that source; then, using a minimum cost path backtracking algorithm, determine the continuous pixel sequence that minimizes the sum of cumulative resistance between the two cumulative resistance surfaces; that is, find the lowest cost valley line connecting two points on the terrain surface formed by the cumulative resistance values; perform the above calculations sequentially to obtain the spatial polyline connecting the lowest resistance channel between different cumulative resistance surfaces as the corresponding minimum cost path. In other embodiments, methods based on circuit theory or the minimum spanning tree principle can also be used to determine the connectivity path between ecological source areas, which is not limited in this application.

[0036] It should be noted that the minimum cost path mentioned in this application refers to a spatially continuous broken line connecting two specific ecological source areas, calculated based on the cumulative resistance surface. Its path orientation is used to characterize the theoretical channel with the minimum cumulative resistance when ecological flow diffuses or migrates between two points under the landscape resistance defined by the dynamic ecological resistance surface.

[0037] In some embodiments, generating potential ecological corridors in a target area based on analysis results can be achieved through the following steps: All minimum cost paths are vectorized and extracted to obtain the initial corridor segments; The initial corridor segments are spatially connected to construct a preliminary corridor network; The preliminary corridor network is topologically smoothed to generate potential ecological corridors in the target area.

[0038] In specific implementation, the initial corridor segment is obtained by vectorizing all minimum cost paths. This can be achieved in the following ways: First, all minimum cost paths obtained from the minimum cumulative resistance analysis are input into a geographic information system (GIS). Then, the raster-to-vector conversion tool in the GIS is used to perform a conversion operation. This tool identifies all connected cell regions with a value of 1, treats each connected region as an independent path, and traces its cell boundary or centerline to convert it into a vector polyline with continuous coordinate points. As a preferred embodiment, in this process, to more accurately characterize the spatial range of the corridor, a preset line width generation tolerance parameter can be introduced. Through distance analysis or buffer generation methods, the vector polyline with a single cell width is expanded into a vector surface with a preset width. The centerline of this buffer surface is then extracted as the final segment to simulate the actual channel width for species migration. After completing the above conversion and optimization of all paths, a line feature dataset containing multiple vector polylines is generated as the initial corridor segment. In other embodiments, a thinning algorithm can also be used to directly extract the centerline of the raster path and then vectorize it. This application does not limit this approach.

[0039] It should be noted that the initial corridor segment mentioned in this application refers to a series of discrete vector line elements obtained by vectorizing and pre-geometrically processing all the minimum cost paths, which are used to record the initial spatial position and geometric shape of the minimum resistance channel generated based on theoretical calculations.

[0040] In specific implementation, the initial corridor segments are spatially connected to construct a preliminary corridor network, which can be achieved in the following ways: First, the initial corridor segment dataset is subjected to topology checks and preprocessing to ensure that the segments are geometrically non-self-intersecting and non-repeating. Then, a preset spatial connection tolerance threshold is set, which is usually determined based on the pixel resolution or data acquisition accuracy of the dynamic ecological resistance surface. Using topology editing or network creation tools in GIS, all segment endpoints are automatically searched, and the spatial distance between any two endpoints is determined. If the distance is less than the tolerance threshold, the two endpoints are captured to the same position (such as the midpoint or the position of one of the endpoints), thereby realizing the physical connection of the segments. Next, all connected segments are broken at their intersections to ensure that there are topological nodes at the intersections. Finally, the planar graph structure formed after the breakage, consisting of defined nodes (segment endpoints and intersections) and connecting edges (segments between nodes), is taken as the preliminary corridor network.

[0041] It should be noted that the preliminary corridor network described in this application refers to a planar network structure formed by spatially connecting and topologically constructing all the initial corridor segments. It consists of nodes and connecting edges and is used to integrate discrete connecting paths in terms of geometric and topological relationships.

[0042] In specific implementation, topological smoothing of the preliminary corridor network to generate potential ecological corridors in the target area can be achieved in the following ways: First, a geometric smoothing algorithm is applied to each connecting edge in the preliminary corridor network. The smoothing algorithm can use spline curve interpolation, specifically: in the vertex sequence of the original polyline, new control points are inserted according to a preset smoothness, and a smooth curve that passes through or approaches the original vertex but whose curvature changes continuously is fitted; or, a moving average method is used to recalculate an average coordinate for each vertex based on several of its adjacent vertices, thereby generating a smoother path; the intensity of the smoothing is controlled by a preset smoothing factor. The larger the smoothing factor, the smoother the generated curve. The smoother the line, the more it deviates from the original polyline. Secondly, while maintaining the network topology connections (i.e., the connectivity between nodes and edges), a line simplification algorithm, such as the Douglas-Puk algorithm, is applied. This algorithm recursively removes vertices whose contribution to the overall shape of the line segment is less than a preset simplification tolerance, thereby reducing data redundancy while preserving the main shape features. The simplification tolerance can be set according to the map output scale or data storage requirements. After completing the above smoothing and simplification processes, the final set of vector line elements with a natural smooth shape and optimized topology is the potential ecological corridor in the target area. In other embodiments, a sliding window-based filtering method or simulated annealing algorithm can also be used for geometric optimization, which is not limited in this application.

[0043] It should be noted that the potential ecological corridors mentioned in this application refer to the final set of vector line elements generated after geometric smoothing and topology optimization of the preliminary corridor network. They are used to intuitively and comprehensively demonstrate the spatial connectivity pattern with the highest theoretical ecological circulation efficiency in the target area after considering the dynamic resistance landscape.

[0044] In step 104, the potential ecological corridor is spatially overlaid with the landscape change feature set to identify ecological barrier points in the potential ecological corridor.

[0045] In some embodiments, spatially overlaying the potential ecological corridor with the landscape change feature set to identify ecological barrier points in the potential ecological corridor can be achieved through the following steps: Spatial intersection analysis is performed on the potential ecological corridors and the set of landscape change features to generate a set of spatial intersection elements. Determine the degree to which the spatial intersection element set hinders corridor connectivity; Ecological obstacle points in the potential ecological corridor are identified based on the degree of obstacle.

[0046] In specific implementation, spatial intersection analysis is performed on the potential ecological corridor and the landscape change feature set to generate a spatial intersection feature set. This can be achieved in the following way: for example, the potential ecological corridor and the landscape change feature set are used as input data, and an "intersection" analysis is performed. This operation calculates the spatial overlap between the two layers and outputs a new vector feature set, where each feature is a line segment intercepted after the intersection of the potential ecological corridor line segment and the change patch polygon in the landscape change feature set. At the same time, this new feature set inherits the attributes from the two input layers, that is, each intersection line segment is associated with the potential ecological corridor identifier it belongs to and the ecological resistance influence weight value of the change patch it passes through. Finally, this new vector dataset, which contains both spatial geometric information and fusion attributes, is used as the spatial intersection feature set.

[0047] It should be noted that the spatial intersection feature set mentioned in this application refers to a vector dataset generated by performing spatial intersection analysis on the potential ecological corridor and the landscape change feature set, wherein each feature is used to record the line segments that overlap spatially with the potential ecological corridor and the specific change patch and their fusion attributes.

[0048] In specific implementation, the degree of obstruction to corridor connectivity caused by the spatial intersection element set can be determined in the following ways: for example, based on the ecological resistance impact weight value associated with each intersection element in the spatial intersection element set, assess the intensity of obstruction to corridor connectivity; set a preset obstacle degree judgment threshold, which can be determined based on the dispersal capacity of the target species, regional ecological protection goals, and through expert consultation or model calibration; compare the ecological resistance impact weight value of each intersection element with the preset obstacle degree judgment threshold: if the weight value is greater than or equal to the threshold, it is determined that the corridor segment where the intersection element is located has a high degree of obstruction, meaning that the landscape change here constitutes a significant blockage to ecological flow; if the weight value is less than the threshold, it is determined to be a low degree of obstruction or no obstruction; finally, assign a classification label representing the degree of obstruction to corridor connectivity for each intersection element, and determine the classification label as the degree of obstruction to corridor connectivity caused by the intersection element.

[0049] It should be noted that the degree of obstruction to corridor connectivity mentioned in this application refers to a classification identifier obtained by comparing the ecological resistance impact weight value of each element in the spatial intersection element set with a preset threshold. It is used to quantitatively or qualitatively assess the level of obstruction intensity caused by a specific landscape change event to the ecological connectivity function of the corridor segment.

[0050] In specific implementation, identifying ecological obstacle points in the potential ecological corridor based on the degree of obstacle can be achieved in the following ways: First, from the set of spatial intersection elements, all intersection elements assessed as having a high degree of obstacle are selected; then, for each intersection element with a high degree of obstacle, its representative location point on the potential ecological corridor is located through spatial calculation. As a preferred embodiment, the geometric center point of the intersection element, or the intersection point of the element with the original corridor line segment to which it belongs, can be determined as the candidate spatial location of the obstacle point; next, all the located candidate spatial location points are created as vector point elements, and each point element is assigned attribute information, including its corridor identifier, corresponding change patch information, and specific obstacle degree value; finally, the generated set of vector point elements is identified as the ecological obstacle point in the potential ecological corridor; in other embodiments, the starting point, ending point, or center of gravity of the high-obstacle intersection element can also be used as the obstacle point according to actual management needs, and this application does not limit this.

[0051] It should be noted that the ecological barrier points mentioned in this application refer to vector point elements identified and located on the potential ecological corridor based on the assessment results of the degree of barrier to corridor connectivity. These points are used to accurately identify key spatial locations where corridor connectivity is significantly damaged or interrupted due to high-intensity landscape changes.

[0052] In step 105, in a computer-aided design environment, the potential ecological corridors are topologically corrected based on the ecological barrier points to obtain a digital structural model of the regional landscape ecological network.

[0053] In some embodiments, topologically correcting the potential ecological corridors based on the ecological barrier points to obtain a digital structural model of the regional landscape ecological network can be achieved through the following steps: Based on the spatial location of the ecological barrier points, the potential ecological corridors are topologically segmented to generate multiple disconnected corridor segments. Under the constraint of the dynamic ecological resistance surface, alternative connection paths are generated that bypass the ecological barrier points between all corridor segments. A digital structural model of the regional landscape ecological network is generated by using all corridor segments and all alternative connection paths.

[0054] In specific implementation, the potential ecological corridor is topologically segmented based on the spatial location of the ecological barrier points to generate multiple disconnected corridor segments. This can be achieved in the following way: for example, by using the line segmentation function in computer-aided design software, the precise coordinates of each ecological barrier point are used as the cutting point to break the potential ecological corridor line segment passing through that point. The breaking operation will divide the original continuous corridor line into two independent line segments at each barrier point. After traversing and processing all ecological barrier points, the original continuous corridor network is divided into multiple shorter vector line segments that are broken at the barrier points. The set of all these segmented line segments is used as the disconnected corridor segments, thus obtaining multiple disconnected corridor segments. It should be noted that each corridor segment inherits the attribute information of its original corridor.

[0055] It should be noted that the disconnected corridor segment mentioned in this application refers to a series of short, discontinuous vector segments generated after the potential ecological corridor is topologically broken by using the ecological barrier point as the dividing point.

[0056] In specific implementation, generating alternative connection paths around ecological barrier points between all corridor segments under the constraint of the dynamic ecological resistance surface can be achieved in the following way: For each pair of adjacent corridor segments that are disconnected due to the same ecological barrier point and need to be reconnected, the endpoints closest to the barrier point are extracted and used as the starting and ending points for calculating alternative paths, respectively; the dynamic ecological resistance surface is used as the cost grid, and a spatial search range that avoids the direct neighborhood of the ecological barrier point is preset as the constraint range; within the constraint range, a new path that connects the starting and ending points and has the minimum cumulative crossing resistance is recalculated using the minimum cost path algorithm, and this path is the alternative connection path around the ecological barrier point; by traversing all corridor segment pairs that need to be reconnected and repeating the above calculation process, a series of new minimum resistance channel segments that avoid the original barrier positions are generated as the corresponding alternative connection paths.

[0057] It should be noted that the alternative connection path mentioned in this application refers to a new vector line element calculated and generated under the spatial constraints of the dynamic ecological resistance surface to bypass the ecological obstacle point and reconnect the disconnected corridor segment. It is used to restore or rebuild the connectivity of the ecological corridor network while avoiding the identified obstacle area.

[0058] In practical implementation, generating a digital structural model of the regional landscape ecological network by combining all corridor segments and all alternative connection paths can be achieved in the following way: First, in a computer-aided design platform, the two vector line layers of the disconnected corridor segments and the alternative connection paths are spatially fused to generate a composite layer containing all line elements; then, topology construction and verification are performed on the composite layer, specifically by defining and applying a set of strict topology rules, such as stipulating that the endpoints of line elements must coincide with each other and there can be no hanging points; the system automatically detects all geometric anomalies according to the rules, and based on preset capture tolerance parameters, automatically snaps unclosed endpoints to the nearest legal endpoint position, thereby achieving geometric alignment of all line segments. The seamless connection forms a continuous network with a tight topological relationship. On this basis, descriptive attributes are added to each element in the constructed network, type, length and average resistance value attributes are added to each edge, and spatial coordinates and connectivity attributes are added to each node. Finally, this integrated network dataset with geometric connection and attribute assignment is constructed as a structural model of the regional landscape ecological network. As a preferred embodiment, the ecological source area and the ecological barrier point can also be integrated into the model as related elements to form a comprehensive spatial database containing complete ecological semantics. In other embodiments, the topology construction can also be completed by spatial data processing scripts or dedicated network modeling tools, which is not limited in this application.

[0059] It should be noted that the regional landscape ecological network digital structure model described in this application refers to a comprehensive vector network dataset formed by integrating the disconnected corridor segments, the alternative connection paths and related ecological elements, and after topological reconstruction and attribute assignment. It is used to accurately and structurally represent the complete spatial configuration and attribute information of the regional landscape ecological network after obstacle point correction in digital form.

[0060] Furthermore, in another aspect of this application, in some embodiments, this application provides a system for accurately identifying the structural features of regional landscape ecological networks, with reference to... Figure 4 The figure is a schematic diagram of the structure of a regional landscape ecological network structural feature accurate identification system according to some embodiments of this application. The regional landscape ecological network structural feature accurate identification system 200 includes: a detection module 201, a processing module 202, and an execution module 203, which are described below: Detection module 201, in this application, is mainly used to detect the changing patches of the target area under different time phases, and then generate a landscape change feature set of the target area; Processing module 202, in this application, is mainly used to locally update the pixel values ​​of the basic ecological resistance surface of the target area according to the landscape change feature set, so as to obtain the dynamic ecological resistance surface; In addition, the processing module 202 in this application is also used to perform minimum cumulative resistance analysis between preset ecological source areas through the dynamic ecological resistance surface, and then generate potential ecological corridors in the target area based on the analysis results. In addition, the processing module 202 in this application is also used to perform spatial overlay analysis on the potential ecological corridor and the landscape change feature set, so as to identify the ecological barrier points in the potential ecological corridor. The execution module 203 in this application is mainly used to perform topological correction on the potential ecological corridors based on the ecological obstacle points in a computer-aided design environment, so as to obtain a digital structural model of the regional landscape ecological network.

[0061] In addition, this application also provides a computer device, which includes a memory and a processor. The memory stores code, and the processor is configured to acquire the code and execute the above-described method for accurately identifying the structural features of regional landscape ecological networks.

[0062] In some embodiments, reference Figure 5 This figure is an internal structural diagram of a computer device for implementing a method for accurately identifying the structural features of regional landscape ecological networks, according to some embodiments of this application. The method for accurately identifying the structural features of regional landscape ecological networks in the above embodiments can... Figure 5 The computer device shown is used to implement this, and the computer device 300 includes at least one processor 301, a communication bus 302, a memory 303, and at least one communication interface 304.

[0063] The processor 301 may be a general-purpose central processing unit (CPU), an application-specific integrated circuit (ASIC), or one or more devices used to control the execution of the method for accurately identifying the structural features of the regional landscape ecological network in this application.

[0064] The communication bus 302 is used to transmit information between the aforementioned components.

[0065] Memory 303 may be a read-only memory (ROM) or other type of static storage device capable of storing static information and instructions, random access memory (RAM) or other type of dynamic storage device capable of storing information and instructions, or electrically erasable programmable read-only memory (EEPROM), compact disc read-only memory (CD-ROM) or other optical disc storage, optical disc storage (including compressed optical discs, laser discs, optical discs, digital versatile optical discs, Blu-ray discs, etc.), magnetic disks or other magnetic storage devices, or any other medium capable of carrying or storing desired program code in the form of instructions or data structures and accessible by a computer, but not limited thereto. Memory 303 may exist independently and be connected to processor 301 via communication bus 302. Memory 303 may also be integrated with processor 301.

[0066] The memory 303 stores program code for executing the scheme of this application, and its execution is controlled by the processor 301. The processor 301 executes the program code stored in the memory 303. The program code may include one or more software modules. The method for accurately identifying the structural features of regional landscape ecological networks in the above embodiments can be implemented by the processor 301 and one or more software modules in the program code in the memory 303.

[0067] Communication interface 304 uses any transceiver-like device to communicate with other devices or communication networks, such as Ethernet, radio access network (RAN), wireless local area networks (WLAN), etc.

[0068] In a specific implementation, as one example, a computer device may include multiple processors, each of which may be a single-core (single-CPU) processor or a multi-core (multi-CPU) processor. Here, a processor may refer to one or more devices, circuits, and / or processing cores for processing data (e.g., computer program instructions).

[0069] The aforementioned computer device can be a general-purpose computer device or a special-purpose computer device. In specific implementations, the computer device may be a desktop computer, a portable computer, a network server, a handheld digital assistant (PDA), a mobile phone, a tablet computer, a wireless terminal device, a communication device, or an embedded device. This application does not limit the type of computer device.

[0070] In addition, this application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method for accurately identifying the structural features of regional landscape ecological networks.

[0071] In summary, the method and system for accurately identifying the structural features of regional landscape ecological networks disclosed in this application detects changes in the target area's patches at different time phases, thereby generating a set of landscape change features for the target area. Based on this set, the pixel values ​​of the basic ecological resistance surface of the target area are locally updated to obtain a dynamic ecological resistance surface. Minimum cumulative resistance analysis is performed between preset ecological source areas using this dynamic ecological resistance surface, and potential ecological corridors in the target area are generated based on the analysis results. The potential ecological corridors are spatially overlaid with the landscape change feature set to identify ecological barrier points within the potential ecological corridors. In a computer-aided design environment, the potential ecological corridors are topologically corrected based on the ecological barrier points to obtain a digital structural model of the regional landscape ecological network. This model enables fusion perception of the spatiotemporal dynamic processes of the landscape structure, allowing for accurate identification of structural features.

[0072] Although preferred embodiments of this application have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments as well as all changes and modifications falling within the scope of this application.

[0073] Obviously, those skilled in the art can make various modifications and variations to this application without departing from the spirit and scope of this application. Therefore, if such modifications and variations fall within the scope of the claims of this application and their equivalents, this application also intends to include such modifications and variations.

Claims

1. A method for accurately identifying the structural characteristics of regional landscape ecological networks, characterized in that, Includes the following steps: Detect the changing patches of the target area at different time phases, and then generate a landscape change feature set of the target area; The pixel values ​​of the basic ecological resistance surface in the target area are locally updated based on the landscape change feature set to obtain the dynamic ecological resistance surface. The dynamic ecological resistance surface is used to perform minimum cumulative resistance analysis between preset ecological source areas, and then potential ecological corridors in the target area are generated based on the analysis results. By spatially overlaying the potential ecological corridors with the landscape change feature set, ecological barrier points in the potential ecological corridors can be identified. In a computer-aided design environment, the potential ecological corridors are topologically corrected based on the ecological barrier points to obtain a digital structural model of the regional landscape ecological network.

2. The method as described in claim 1, characterized in that, The pixel values ​​of the basic ecological resistance surface in the target area are locally updated based on the landscape change feature set to obtain the dynamic ecological resistance surface, which specifically includes: Obtain the basic ecological resistance surface of the target area; Based on the vector boundaries of the landscape change feature set change patches and their ecological resistance influence weights, a local ecological resistance change raster layer is generated. The dynamic ecological resistance surface is obtained by performing spatial algebraic operations on the corresponding pixel values ​​of the basic ecological resistance surface through the local ecological resistance change raster layer.

3. The method as described in claim 1, characterized in that, The minimum cumulative resistance analysis between preset ecological source areas using the dynamic ecological resistance surface specifically includes: Obtain preset ecological source vector information in the target area; Based on the dynamic ecological resistance surface and the ecological source vector information, the minimum cumulative resistance value from each ecological source to each pixel in space is determined, and then the cumulative resistance surface is generated. The minimum cost path between different ecological source areas is determined based on the cumulative resistance surface.

4. The method as described in claim 1, characterized in that, Based on the analysis results, potential ecological corridors in the target area are generated, specifically including: All minimum cost paths are vectorized and extracted to obtain the initial corridor segments; The initial corridor segments are spatially connected to construct a preliminary corridor network; The preliminary corridor network is topologically smoothed to generate potential ecological corridors in the target area.

5. The method as described in claim 1, characterized in that, Spatially overlaying the potential ecological corridors with the landscape change feature set, the ecological barrier points within the potential ecological corridors are identified, specifically including: Spatial intersection analysis is performed on the potential ecological corridors and the set of landscape change features to generate a set of spatial intersection elements. Determine the degree to which the spatial intersection element set hinders corridor connectivity; Ecological obstacle points in the potential ecological corridor are identified based on the degree of obstacle.

6. The method as described in claim 1, characterized in that, Based on the ecological barrier points, the potential ecological corridors are topologically corrected to obtain a digital structural model of the regional landscape ecological network, specifically including: Based on the spatial location of the ecological barrier points, the potential ecological corridors are topologically segmented to generate multiple disconnected corridor segments. Under the constraint of the dynamic ecological resistance surface, alternative connection paths are generated that bypass the ecological barrier points between all corridor segments. A digital structural model of the regional landscape ecological network is generated by using all corridor segments and all alternative connection paths.

7. The method as described in claim 1, characterized in that, The landscape change feature set refers to a vector dataset that contains spatial geometric information and attribute information.

8. A system for accurately identifying the structural characteristics of a regional landscape ecological network, characterized in that, include: The detection module is used to detect the changing patches of the target area at different time phases, and then generate a landscape change feature set of the target area; The processing module is used to locally update the pixel values ​​of the basic ecological resistance surface of the target area based on the landscape change feature set, so as to obtain the dynamic ecological resistance surface. The processing module is also used to perform minimum cumulative resistance analysis between preset ecological source areas through the dynamic ecological resistance surface, and then generate potential ecological corridors in the target area based on the analysis results. The processing module is also used to perform spatial overlay analysis of the potential ecological corridor and the landscape change feature set, thereby identifying ecological barrier points in the potential ecological corridor. The execution module is used to perform topological correction on the potential ecological corridors based on the ecological barrier points in a computer-aided design environment, so as to obtain a digital structural model of the regional landscape ecological network.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method for accurately identifying the structural features of regional landscape ecological networks as described in any one of claims 1 to 7.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the steps of the method for accurate identification of structural features of regional landscape ecological networks as described in any one of claims 1 to 7.

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