Ecological security pattern key area identification method and device, medium and product

Abstract

The invention discloses an ecological security pattern key area identification method and device, a medium and a product, and relates to the field of ecological security pattern construction.The method comprises the steps that according to geospatial data, a morphological spatial pattern identification technology, an area threshold value and connectivity analysis are adopted, and an ecological source land is determined; generating a comprehensive ecological resistance surface of the ecological source land; according to the ecological source land and the comprehensive ecological resistance surface, determining an ecological corridor by adopting a minimum cost path model; constructing an ecological security pattern network diagram based on the ecological source and the ecological corridor; according to the ecological security pattern network diagram, carrying out ecological security pattern network topology feature analysis; determining a comprehensive ecological pressure index according to the ecological pressure index factor; and determining an ecological security pattern partition according to the network topology structure and the comprehensive ecological pressure index. According to the method, the interaction and relation of the ecological security pattern in the local scale can be fully considered.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of ecological security pattern construction, in particular to an ecological security pattern key area identification method, device, medium and product. BACKGROUND

[0002] Ecological security pattern construction is an effective measure to analyze regional ecosystem structure and function and maintain ecosystem services. The existing technical methods mainly focus on the identification of source areas, the extraction of corridors and other ecological security network construction technologies, and pay more attention to geographical entity identification, but lack analysis of the strength and direction of the functional connection between elements, and there is a limitation of insufficient characterization of the coupling and mutual feedback of each ecological element in the spatial pattern and network of the ecological security pattern. At the same time, the ecological security pattern constructed at present is usually regarded as a planar structure, ignoring its inherent hierarchical differentiation (such as the functional gradient between the core protection area and the buffer zone between the core protection area and the human activity area). SUMMARY

[0003] The purpose of the present application is to provide an ecological security pattern key area identification method, device, medium and product, which realizes spatial analysis of regional ecological security pattern, can accurately identify core ecological source areas and ecological corridors that play a key role in the stability and connectivity of the ecological security pattern, and fully considers the interaction and connection of the ecological security pattern at the local scale.

[0004] To achieve the above purpose, the present application provides the following solutions: In a first aspect, the present application provides an ecological security pattern key area identification method, which comprises: Obtaining geographical spatial data of a region to be identified; the geographical spatial data comprises land use data, slope, elevation, water network and road network; According to the geographical spatial data, adopting morphological spatial pattern identification technology, area threshold and connectivity analysis to determine ecological source areas; According to the geographical spatial data, determining resistance factor indexes; and based on the resistance factor indexes, adopting hierarchical analysis to determine the weights of the resistance factor indexes; then performing weighted superposition to generate a comprehensive ecological resistance surface of the ecological source areas; the resistance factor indexes comprise land use type, slope, distance from railway and expressway, elevation and distance from water area; According to the ecological source areas and the comprehensive ecological resistance surface, adopting a minimum cost path model to determine ecological corridors; Based on the ecological source areas and the ecological corridors, constructing an ecological security pattern network graph; the ecological security pattern network graph takes the ecological source areas as network nodes and takes the ecological corridors as edges connecting the network nodes; The ecological security pattern network topology characteristics were analyzed based on the ecological security pattern network diagram, and the analysis results were obtained; the analysis results include the community structure and the core nodes and edge nodes within the community structure; Ecological pressure index factors of ecological source areas are obtained, and a comprehensive ecological pressure index of ecological source areas is determined based on ecological pressure index factors; the ecological pressure index factors include: soil erosion, population concentration pressure factor and land use intensity factor. Based on the network topology of the ecological security pattern network diagram and the comprehensive ecological pressure index, the ecological security pattern zoning of the areas to be identified is determined.

[0005] Optionally, the step of determining the ecological source area based on geospatial data using morphological spatial pattern recognition technology, area thresholds, and connectivity analysis specifically includes: The types of ecological source areas are determined based on land use data; these types include: forest land, grassland, shrubland, water bodies, and wetlands. Based on the type of ecological source area, morphological spatial pattern identification technology is used to determine the core area patches in the ecological space; Core patches are obtained by screening core areas in the ecological space based on area thresholds; Connectivity analysis was performed on the core patches to determine the patch importance index; Ecological source areas are determined based on core patches with a patch importance index greater than 1.

[0006] Optionally, the connectivity analysis of the core plaques to determine the plaque importance index specifically includes: Using formula Determine the plaque importance index dPC; Where PC is the potential connectivity index. , where n is the total number of core plaques. and A represents the area of ​​the i-th and j-th core patches, respectively. L P represents the total area of ​​the region to be identified. ij PCremove represents the maximum product probability of all paths between the i-th and j-th core patches, and PCremove is the probability connectivity index of the remaining core patches after removing a single core patch.

[0007] Optionally, the step of determining ecological corridors based on the ecological source area and the comprehensive ecological resistance surface using a minimum cost path model specifically includes: Using formula Determine the minimum cost path model; Where LCP is the final minimum cost path generated from the j-th ecological source to the i-th ecological source, and D ijR represents the spatial distance traversed from the j-th ecological source area to the i-th ecological source area. i Let represent the ecological resistance value of the i-th ecological source site in a certain direction in space, where m and n refer to the number of rows and columns traversed by the i-th to j-th ecological source sites in the ecological resistance raster data, where m is the number of rows and n is the number of columns. This is a function that takes the minimum value.

[0008] Optionally, the step of performing network topology analysis of the ecological security pattern based on the ecological security pattern network diagram to obtain the analysis results specifically includes: Based on the ecological security pattern network diagram, the GN algorithm is used to determine the community structure; Core-periphery structure analysis is performed on each community structure in the ecological security pattern network diagram to obtain the core nodes and peripheral nodes within the community structure.

[0009] Optionally, the step of obtaining the ecological pressure index factors of the ecological source area and determining the comprehensive ecological pressure index of the ecological source area based on the ecological pressure index factors specifically includes: Using formula Determine the amount of soil erosion; among which, For the soil erosion modulus of the grid, For vegetation coverage, The rainfall erosivity index, The soil erodibility index. Factors related to soil and water conservation measures; Using formula Determine population agglomeration pressure factors Where pd is the population density; Using formula Determine land use intensity factors ;in, Let A be the area of ​​the i-th land use type in the grid, and let A be the area of ​​a single grid cell. Assign a value to the land use intensity of the i-th land use type; Using formula Determine the comprehensive ecological pressure index (EP) of the ecological source area; among which, This is the normalized value of soil erosion. This is the normalized value of the population agglomeration pressure factor. This is the normalized value of the land use intensity factor.

[0010] Optionally, determining the ecological security pattern zoning of the area to be identified based on the network topology of the ecological security pattern network map and the comprehensive ecological pressure index specifically includes: Based on the comprehensive ecological pressure index, the natural discontinuity method is used to classify the ecological pressure levels of ecological source areas. According to the network topology of the ecological security pattern network diagram and the comprehensive ecological pressure index, the ecological source is divided into multiple ecological security clusters according to the ecological security pattern partition principle; The ecological security core area and the ecological security control area are divided in each ecological security cluster; According to the ecological security core area, the ecological security control area and the ecological pressure grade of the ecological source, the ecological fragile area and the ecological sensitive area are determined.

[0011] In the second aspect, the present application provides a computer device, comprising a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to realize the ecological security pattern key area identification method.

[0012] In the third aspect, the present application provides a computer readable storage medium, which stores a computer program, wherein the computer program is executed by a processor to realize the ecological security pattern key area identification method.

[0013] In the fourth aspect, the present application provides a computer program product, comprising a computer program, wherein the computer program is executed by a processor to realize the ecological security pattern key area identification method.

[0014] According to the specific embodiments provided by the present application, the present application has the following technical effects: The present application provides an ecological security pattern key area identification method, device, medium and product, by deeply analyzing the interaction and connection between the ecological source and the ecological corridor, an ecological security pattern network diagram reflecting the different scale structure and mutual relationship of the regional ecological security pattern is constructed. Through the topological characteristics of the ecological security pattern network diagram and the ecological pressure analysis, the spatial analysis of the regional ecological security pattern can be realized. The present application simplifies the ecological security network of the region into a binary structure by analyzing the community structure in the analysis result and the core node and the edge node in the community structure, reveals the spatial self-organization characteristics of the ecological process and the hierarchical characteristics of the elements in the network, helps to quantify the difference in the functional importance between the nodes (i.e. the ecological source) from the perspective of maintaining the stability of the structure of the ecological security pattern network diagram, and determines the interaction and connection of the ecological security pattern at the local scale. And according to the comprehensive ecological pressure index of the ecological source, the influence of human activities on the regional ecological security pattern can be effectively tracked. By comprehensively considering the influence of human activities, the characteristics of the network structure and the dynamic evolution for many years, the present application can accurately identify the core ecological source and the ecological corridor which play a key role in the stability and connectivity of the ecological security pattern, provide a target for differentiated ecological protection and restoration management measures, and effectively reveal the internal mechanism of the evolution or degradation of the ecological network. BRIEF DESCRIPTION OF DRAWINGS

[0015] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the accompanying drawings needed in the embodiments will be briefly introduced as follows. Obviously, the accompanying drawings in the following description only only some embodiments of the present application, and for those skilled in the art, other drawings can be obtained without creative labor on the basis of these drawings.

[0016] Figure 1 For an embodiment of the present application, a flowchart of a key area identification method of an ecological security pattern is shown. Figure 2 For a structure diagram of determining community structure by GN (Girvan-Newman) algorithm (the circles at the bottom represent nodes in the ecological security pattern network). DETAILED DESCRIPTION

[0017] The technical solutions in the embodiments of the present application will be described clearly and completely in the embodiments of the present application in combination with the accompanying drawings. Obviously, the described embodiments are only some of the embodiments of the present application, not all. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present application.

[0018] In order to make the above purposes, features and advantages of the present application more obvious and easy to understand, the present application will be further described in detail in combination with the accompanying drawings and specific embodiments.

[0019] In an exemplary embodiment, as shown in Figure 1 A key area identification method of an ecological security pattern is provided, which comprises the following S101 to S108. Wherein: S101, obtaining geographical spatial data of a region to be identified; the geographical spatial data comprises land use data, slope, elevation, water network and road network; S102, determining an ecological source according to the geographical spatial data by using morphological spatial pattern identification technology, area threshold and connectivity analysis; S102 specifically comprises: S21, determining an ecological source type according to the land use data; the ecological source type comprises forest land, grassland, shrub, water body and wetland; S22, determining a core area patch in the ecological space by using morphological spatial pattern identification technology (MSPA) according to the ecological source type; the core area patch has ecological source potential; S23, screening the core area patch in the ecological space according to an area threshold to obtain a core patch; the area threshold can be 10 square kilometers; S24, performing connectivity analysis on the core patch to determine a patch importance index; S24 specifically comprises: determine the patch importance index dPC by using the formula wherein PC is the possible connectivity index, n is the total number of core patches, and Ai and Aj are the areas of the ith and jth core patches, respectively, A L P is the total area of the region to be identified, P ij represents the maximum product probability of all paths between the ith and jth core patches, and PCremove is the possible connectivity index of the core patches remaining after removal of a single core patch.

[0020] S25, determining the ecological source based on the core patches with patch importance index greater than 1.

[0021] S103, determining the resistance factor indicators based on the geospatial data; and determining the weights of the resistance factor indicators based on the analytic hierarchy process (AHP) method; and then performing weighted superposition to generate a comprehensive ecological resistance surface of the ecological source; the resistance factor indicators include land use type, slope, distance to railway and highway, elevation, and distance to water area; that is, each resistance factor indicator is superimposed based on the weights to obtain the comprehensive ecological resistance surface of the ecological source; S104, determining the ecological corridor based on the ecological source and the comprehensive ecological resistance surface using the least-cost path model; S104 specifically comprises: determining the least-cost path model by using the formula wherein LCP is the final generated least-cost path from the jth ecological source to the ith ecological source, D ij is the spatial distance from the jth ecological source to the ith ecological source, R i is the ecological resistance value of the ith ecological source in a certain direction in space, and m and n are the row and column numbers of the ith ecological source to the jth ecological source in the ecological resistance grid data, m is the row, and n is the column, is the minimum value function.

[0022] S105, constructing an ecological security pattern network graph based on the ecological source and the ecological corridor; the ecological security pattern network graph takes the ecological source as the network node and takes the ecological corridor as the edge connecting the network nodes; S106, performing ecological security pattern network topology feature analysis based on the ecological security pattern network graph to obtain an analysis result; the analysis result includes the community structure and the core nodes and edge nodes within the community structure. ​​S106 specifically includes: S61. Based on the ecological security pattern network diagram, the GN algorithm is used to determine the community structure; The process of determining the structure of a community is as follows: (1) Construct an undirected and unweighted ecological security pattern network graph G=(N,L) based on the ecological source areas and ecological corridors. Ecological source areas are abstracted as network nodes, and the ecological corridors connecting ecological source areas are abstracted as network edges. When there is an ecological corridor connecting any two ecological source areas, the edge value is set to 1; when there is no ecological corridor connecting them, the edge value is set to 0. N is the set of abstracted network nodes in the complex network model G. ,in, Let represent the i-th network node, and L represent the abstract set of network edges. The number of connections between each node and other network nodes satisfies ... .

[0023] (2) Detecting community structure in a graph based on the GN (Girvan-Newman) algorithm. Community structure reflects the clustering characteristics of a network. A community is a subgraph of a graph, where nodes within a community are tightly connected, while connections to external nodes are sparse. Select any node in the graph sequentially, and calculate the Edge Betweenness Centrality (EBC) of all edges based on the shortest path. Edge Betweenness Centrality is defined as the number of shortest paths through an edge in a network, and is an indicator of the importance of edges in the network. For each node in the graph, repeat the above steps, and sum the n EBC values ​​of each edge and divide by 2 to obtain the final EBC value of each edge. Remove the edge with the highest EBC value and calculate the modularity Q of the network community structure. Iterate the above process until no edge can be removed. The final result is represented as a hierarchical clustering tree, and as shown in... Figure 2 As shown. Each independent network structure corresponds to a horizontal division of the dendrogram, in order to... Figure 2 Taking the horizontal line as an example, each branch intersecting the horizontal line represents a community composed of a group of nodes, and all nodes at the bottom of the branch are members of that community. Specifically, the core structure is detected using the `cluster_edge_betweenness()` function in the R language.

[0024] (3) Using the maximum modularity Q-value as the clustering objective, determine the appropriate number of communities m ( Modularity is a method for measuring the strength of a network community structure; a higher value indicates a better community partitioning effect. Modularity is defined as the ratio of the total number of edges within a community to the total number of edges in the network, minus an expected value. This expected value represents the ratio of the total number of edges within a community to the total number of edges in the network when the network is set to random.

[0025] ; where, are the degrees of the points . When the point has edges connected to it, , otherwise . m is the total number of edges in the network. Let denote the two communities in which the points are located, when the point is in a community, , otherwise 0. The specific calculation can be realized by calling the modularity package in python.

[0026] S62, the core-edge structure analysis is performed on each community structure in the ecological safety pattern network diagram, to obtain the core nodes and edge nodes in the community structure.

[0027] The core-edge structure analysis is performed on each community structure in the network, to identify the network nodes in the core position. The core-edge structure is a special structure composed of a group of interconnected nodes, in which the center is closely connected, the edge is sparsely dispersed, and the edge points and the core points are connected. Based on the division result of the community structure, a symmetric binary network of nodes and edges contained in each community structure is constructed . is the network node set of the community i network , , , denotes the edge set inside the community structure i. In the UCINET social network analysis software, the matrix is input, the core-edge structure analysis of each community structure is performed according to the menu path network (N) > core / periphery (Y) > absolute (C), and the nodes contained in the core and the edge of each community structure are output.

[0028] S107, an ecological pressure index factor of the ecological source is obtained, and a comprehensive ecological pressure index of the ecological source is determined according to the ecological pressure index factor; the ecological pressure index factor includes: soil erosion amount, population aggregation pressure factor and land use intensity factor; wherein, the ecological pressure index factor is determined based on climate, population and land use and other spatial resolution of 1km grid data and station data; S107 specifically includes: The soil erosion amount is determined by using the formula . The soil erosion amount is determined according to the basic principle of the general soil and water loss equation, and the indicators such as precipitation erosion force, soil erodibility, slope length and slope, and surface vegetation coverage are selected; wherein, is the soil erosion modulus of the grid, Vegetation coverage, Rainfall erosivity index, Soil erodibility index, Soil conservation measure factor; Wherein, , Normalized difference vegetation index; Information contributed by completely vegetation-covered ground surface, Information contributed by non-vegetation-covered ground surface, And Take the maximum and minimum values (remove negative values) of the NDVI grid data, respectively.

[0029] ; ; In the formula, R is the average annual rainfall erosivity; Rainfall erosivity of the jth half month; j is 24 half months in a year; i is the number of erosive rainfall days in the jth half month, i = 1, 2, …, m; α is a parameter, α = 0.3937 in warm season and α = 0.3101 in cold season. Rainfall of the ith erosive day in the jth half month is obtained by Kriging interpolation from daily rainfall observation data of meteorological stations, and the specific calculation method is completed by ArcGIS software according to the menu path Geostatistical Analyst (geostatistical analysis) > Kriging method to spatialize rainfall.

[0030] ; ; In the formula, Indicates the soil erodibility factor before correction, K indicates the soil erodibility factor after correction, , , And The percentage contents of clay, silt, sand and organic carbon, respectively. The percentage of soil texture can be extracted from the soil data attribute item.

[0031] It is assumed that the pressure of human beings on natural ecosystems increases logarithmically with the increase of population density, and reaches saturation at 1000 people / km 2 . Therefore, the population aggregation pressure factor of the grid with population density greater than 1000 people / km 2 is valued as 10, and the population aggregation pressure factor of the grid with population density less than 1000 people / km 2 is determined by using the formula ; wherein, pd is the population density. Each land use intensity is divided into 5 levels and is assigned a value, i.e., unutilized land is assigned a value of 1; forest land and grassland are assigned a value of 2; water area is assigned a value of 3; cultivated land is assigned a value of 4; and construction land is assigned a value of 5. The land use intensity factor is determined by the formula determining the land use intensity factor ; wherein, is the area of the i-th land use type in the grid, A is the area of one grid, is the land use intensity value of the i-th land use type; When the three types of factors have the same contribution to the ecological pressure index, the three types of factors are normalized, and the comprehensive ecological pressure index score of each grid is the sum of the scores of the three types of indexes: ; wherein, is the normalized value of the soil erosion amount, is the normalized value of the population aggregation pressure factor, is the normalized value of the land use intensity factor.

[0032] S108, according to the network topology structure of the ecological security pattern network diagram and the comprehensive ecological pressure index, determining the ecological security pattern partition of the to-be-identified region.

[0033] S108 specifically includes: S81, according to the comprehensive ecological pressure index, using the natural breakpoint method to divide the ecological source into an ecological pressure level, and then obtaining the ecological pressure level of the ecological source; the ecological pressure level of the ecological source includes: a lower ecological pressure area, a general ecological pressure area and a higher ecological pressure area; S82, according to the network topology structure of the ecological security pattern network diagram and the comprehensive ecological pressure index, using the ecological security pattern partition principle to divide the ecological source into multiple ecological security clusters, i.e., a first-level partition; the ecological security pattern partition principle includes: consistency and heterogeneity of ecological space pattern; high correlation and integrity of ecological network system.

[0034] The consistency and heterogeneity of the ecological space pattern are that, in space, each community structure is relatively consistent in ecological process, ecological function and ecological structure, and the ecological structure and function are significantly different between different communities.

[0035] The high correlation and integrity of the ecological network are that the dynamic evolution and mutual feedback mechanism are the core of the ecological network, and the change of the information state of a node in the network can be transmitted and flowed through the structure of the interaction between nodes, and then cause the change of the whole system.

[0036] S83, dividing the ecological security core area and the ecological security control area in each ecological security cluster, i.e., a second-level partition; The first and second partitions are based on the internal organization law of the ecological security pattern network. According to the local cohesion characteristics of the network community, the ecological security cluster with macro spatial characteristics is identified. Based on the core-edge structure characteristics, the ecological security core area and the ecological security control area in the cluster are identified. The ecological security cluster is formed by multiple spatially adjacent and closely connected collaborative units including ecological sources and ecological corridors, and is the functional module of the regional ecological security pattern. The ecological security core area is composed of nodes in the core structure and connections between the nodes in the network community, and has the characteristics of high connectivity and strong influence, which can play a global control role and is the key unit to maintain the stability, connectivity and function of the ecological security cluster. The ecological security control area is composed of nodes in the edge structure and connections inside the edge structure and connections between the core-edge structure in the network community, and is mostly a transitional zone, which is structurally dependent on the core area and functionally mainly buffering and filtering, and is easily affected by external disturbances.

[0037] S84, according to the ecological pressure level of the ecological security core area and the ecological security control area and the ecological source, the ecological fragile area and the ecological sensitive area are determined, i.e. the third partition.

[0038] The third partition is based on the ecological source, and divides the ecological fragile area and the ecological sensitive area on the basis of the second partition, combined with the influence degree and spatial distribution of ecological pressure. When there is an ecological source in the second partition, and more than 30% of the area is located in the higher ecological pressure area, the ecological source is divided into the ecological fragile area. When the ecological security core area is distributed with the ecological fragile area, other ecological sources in the core area and ecological sources in the ecological security control area in the ecological security cluster are divided into the ecological sensitive area. When the ecological security control area is distributed with the ecological fragile area, the ecological sources in the ecological security core area in the ecological security cluster are divided into the ecological sensitive area.

[0039] In an example embodiment, a computer device is provided, which can be a server or a terminal. The computer device includes a processor, a memory, an input / output interface (I / O) and a communication interface. The processor, the memory and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. The processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for running the operating system and the computer program in the non-volatile storage medium. The input / output interface of the computer device is configured to exchange information between the processor and external devices. The communication interface of the computer device is configured to communicate with external terminals through network connection. The computer program is executed by the processor to implement an ecological safety pattern key area identification method.

[0040] In an example embodiment, a computer device is provided, which includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the steps in the above method embodiments.

[0041] In an example embodiment, a computer readable storage medium is provided, which stores a computer program. The computer program is executed by a processor to implement the steps in the above method embodiments.

[0042] In an example embodiment, a computer program product is provided, which includes a computer program. The computer program is executed by a processor to implement the steps in the above method embodiments.

[0043] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data for analysis, stored data, displayed data, etc.) involved in the present application are all information and data authorized by the user or authorized by all parties, and the collection, use and processing of related data need to comply with relevant regulations.

[0044] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a non-volatile computer readable storage medium, and when the computer program is executed, the processes of the above-mentioned embodiments of the methods can be included. Any reference to memory, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical storage, high-density embedded non-volatile memory, resistive memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration but not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc.

[0045] The database involved in the embodiments provided in the present application can include at least one of a relational database and a non-relational database. The non-relational database can include a distributed database based on a blockchain, etc., without being limited thereto. The processor involved in the embodiments provided in the present application can be a general processor, a central processor, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., without being limited thereto.

[0046] In the present application, all actions of obtaining signals, information or data are performed under the premise of complying with the corresponding data protection regulations and policies of the country where the device is located, and under the premise of obtaining authorization from the owner of the corresponding device.

[0047] The technical features of the above embodiments can be combined arbitrarily. In order to make the description simple, all possible combinations of the technical features in the above embodiments are not described, but as long as the combinations of the technical features do not exist, they should be considered as the scope of the present application.

[0048] The principles and implementation manners of the present application are described herein by using specific examples, and the above examples are only used to help understand the method of the present application and its core idea; meanwhile, for those skilled in the art, according to the idea of the present application, the specific implementation manners and application ranges will have changes. In conclusion, the content of the specification should not be understood as a limitation of the present application.

Claims

1. A method for identifying an ecological security pattern key area, characterized in that, The ecological safety pattern key area identification method comprises: Obtaining geographical space data of a region to be identified; the geographical space data comprises land use data, slope, elevation, water network and road network; According to the geographical space data, an ecological source is determined by using a morphological spatial pattern identification technology, an area threshold and connectivity analysis; Resistance factor indexes are determined according to the geographical space data, and the weights of the resistance factor indexes are determined by using an analytic hierarchy process based on the resistance factor indexes, and then weighted superposition is performed to generate a comprehensive ecological resistance surface of the ecological source; the resistance factor indexes comprise land use types, slope, distance from a railway and an expressway, elevation and distance from water; An ecological corridor is determined by using a minimum cost path model according to the ecological source and the comprehensive ecological resistance surface; An ecological safety pattern network graph is constructed based on the ecological source and the ecological corridor; the ecological safety pattern network graph takes the ecological source as a network node and takes the ecological corridor as an edge connecting the network nodes; Network topology feature analysis of the ecological safety pattern network graph is performed to obtain an analysis result; the analysis result comprises a community structure and core nodes and edge nodes in the community structure; Ecological pressure index factors of the ecological source are obtained, and a comprehensive ecological pressure index of the ecological source is determined according to the ecological pressure index factors; the ecological pressure index factors comprise soil erosion amount, population aggregation pressure factors and land use intensity factors; An ecological safety pattern partition of the region to be identified is determined according to the network topology structure of the ecological safety pattern network graph and the comprehensive ecological pressure index.

2. The method of identifying an ecological security pattern key area according to claim 1, characterized in that, According to the geographical space data, an ecological source is determined by using a morphological spatial pattern identification technology, an area threshold and connectivity analysis, and specifically comprises: An ecological source type is determined according to the land use data; the ecological source type comprises forest land, grassland, shrub, water body and wetland; An ecological space core area patch is determined by using a morphological spatial pattern identification technology according to the ecological source type; The ecological space core area patch is screened according to an area threshold to obtain a core patch; A patch importance index is determined by performing connectivity analysis on the core patch; An ecological source is determined according to the core patch with a patch importance index greater than 1.

3. The method of identifying an ecological security pattern key area according to claim 2, characterized in that, The connectivity analysis on the core patch to determine the patch importance index specifically comprises: Using the formula determining a plaque importance index dPC; where PC is the possible connectivity index, n is the total number of core patches, and Ai and Aj are the areas of the ith and jth core patches, respectively, A L is the total area of the region to be identified, P ij represents the maximum product probability of all paths between the ith and jth core patches, PCremove is the possible connectivity index of the remaining core patches after removal of a single core patch.

4. The method of identifying an ecological security pattern key area according to claim 1, characterized in that, According to the ecological source and the comprehensive ecological resistance surface, an ecological corridor is determined by using a minimum cost path model, and specifically comprises: Using the formula determining a minimum cost path model; wherein LCP is the minimum cost path from the jth ecological source to the ith ecological source, D ij is the spatial distance from the jth ecological source to the ith ecological source, R i is the ecological resistance value of the ith ecological source in a certain direction in space, m and n are the row and column numbers experienced by the ith ecological source to the jth ecological source in the ecological resistance grid data, m is the row, and n is the column, is the minimum value function.

5. The method of identifying an ecological security pattern key area according to claim 1, characterized in that, According to the ecological safety pattern network graph, network topology feature analysis of the ecological safety pattern is performed to obtain an analysis result, and specifically comprises: A community structure is determined by using a GN algorithm according to the ecological safety pattern network graph; Core-edge structure analysis is performed on each community structure in the ecological safety pattern network graph to obtain core nodes and edge nodes in the community structure.

6. The method of identifying an ecological security pattern key area according to claim 1, characterized in that, The ecological pressure index factors of the ecological source are obtained, and a comprehensive ecological pressure index of the ecological source is determined according to the ecological pressure index factors, and specifically comprises: using the formula determining the amount of soil erosion; wherein, is the soil erosion modulus of the grid, is the vegetation coverage, is the rainfall erosivity index, is the soil erodibility index, is the soil and water conservation measure factor; Using the formula Determining the population aggregation pressure factor ; where pd is the population density; Using the formula determining the land use intensity factor ; wherein, is the area of the i-th land use type in the grid, A is the area of a grid, is the land use intensity value of the i-th land use type; The formula is determining the comprehensive ecological pressure index EP of the ecological source region; wherein, is a normalized value of the soil erosion amount, is a normalized value of the population aggregation pressure factor, is a normalized value of the land use intensity factor.

7. The method of identifying an ecological security pattern key area according to claim 1, characterized in that, The ecological security pattern zoning of the to-be-identified region is determined according to the network topology structure of the ecological security pattern network diagram and the comprehensive ecological pressure index, and specifically includes: According to the comprehensive ecological pressure index, the ecological source is divided into ecological pressure grades by using the natural breakpoint method; According to the network topology structure of the ecological security pattern network diagram and the comprehensive ecological pressure index, the ecological source is divided into multiple ecological security clusters by using the ecological security pattern zoning principle; The ecological security core area and the ecological security control area are divided in each ecological security cluster; According to the ecological security core area, the ecological security control area and the ecological pressure grade of the ecological source, the ecological fragile area and the ecological sensitive area are determined.

8. A computer device comprising: The memory, the processor and the computer program stored in the memory and executable on the processor, characterized in that the processor executes the computer program to realize the ecological security pattern key area identification method of any one of claims 1-7.

9. A computer readable storage medium having stored thereon a computer program, characterized in that, The computer program is executed by the processor to realize the ecological security pattern key area identification method of any one of claims 1-7.

10. A computer program product comprising a computer program, characterized in that, The computer program is executed by the processor to realize the ecological security pattern key area identification method of any one of claims 1-7.

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