Marine function space configuration method based on landscape ecology

Abstract

The invention relates to the technical field of ocean space planning, in particular to an ocean function space configuration method based on landscape ecology. The method comprises the following steps: acquiring multi-source geographic space data of a target sea area, and integrating the data to generate a reference marine landscape map; calculating a group of predefined marine landscape pattern indexes according to the reference digital marine landscape map, and quantitatively evaluating the space structure of the map through the marine landscape pattern indexes; an iterative space optimization algorithm is executed, and the spatial layout of the functional area is reconstructed on the premise that constraint conditions are met by taking optimization of an ecological structure as a target; and finally, outputting a marine function space configuration diagram after ecological optimization. According to the method, the limitation of a traditional qualitative zoning method is overcome, a scientific, quantitative and repeatable process is provided for ocean space planning, and therefore the ecological integrity of ocean management planning is effectively improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of marine space planning, in particular to a marine functional space configuration method based on landscape ecology. BACKGROUND

[0002] Marine functional zoning is the core tool of marine spatial planning, which aims to coordinate various sea use activities such as fisheries, ports and shipping, industry and urban construction, tourism and entertainment, and marine protection by reasonably dividing and configuring the sea space, so as to achieve the sustainable use of marine resources. The existing system determines a dominant function for each divided unit, such as an agricultural and fishery area, a port and shipping area, or a marine protection area, which serves as the fundamental basis for sea use management, aiming to solve the sea use conflicts among different industries.

[0003] However, the existing technology has the following problems in practice: first, the current functional zoning method mainly relies on qualitative assessment of natural resources, environmental conditions and social and economic needs of the sea area or comprehensive evaluation based on index system. Although this method can determine the dominant use of each functional zone, it ignores the quantitative analysis of the spatial pattern of the final zoning scheme. Second, the traditional functional zoning tends to regard each functional zone as an independent management unit, focusing on controlling the sea use activities within the zone, while ignoring the ecological process connection between functional zones. Since the existing method does not consider these cross-regional ecological connections, the planning scheme may harm the integrity and connectivity of the marine ecosystem at the macro scale. Ecological connectivity describes the ease of movement of organisms or ecological processes between different habitat patches, which is crucial for maintaining population vitality, gene exchange and ecosystem resilience. The existing zoning may lead to important ecological patches (such as coral reefs and seagrass beds) being isolated by incompatible areas (such as shipping lanes and sewage areas), forming "ecological islands", which will seriously threaten their ecological functions and biodiversity in the long run.

[0004] At the same time, as a discipline that studies the interaction between spatial pattern and ecological process, landscape ecology has developed a mature theoretical system and analysis tools. Its core "pattern-process-scale" theoretical framework and "patch-corridor-matrix" model provide a strong theoretical basis for understanding and quantifying heterogeneous space. Academic research has widely used landscape indices to quantitatively describe the spatial structure of marine habitats and reveal their close relationship with species distribution, community structure and ecosystem function. SUMMARY

[0005] To solve the problems in the prior art, the application provides a marine function space configuration method based on landscape ecology, reconstructs the spatial layout of the marine function area by introducing and applying analysis tools and optimization ideas of landscape ecology, and thus maximizes the ecological integrity of the marine landscape and especially enhances the connectivity of important ecological regions and reduces the fragmentation degree of the important ecological regions under the premise of meeting the sea use demand.

[0006] A marine function space configuration method based on landscape ecology, comprising the following steps: S1, acquiring multi-source geographic spatial data of a target sea area, wherein the multi-source geographic spatial data comprises marine function zoning data; S2, standardizing the multi-source geographic spatial data to a unified geographic coordinate system and projection system, and dividing the sea area into a plurality of analysis units based on the geographic coordinate system; S3, assigning a function zoning type to each analysis unit based on the marine function zoning data to generate a reference digital marine landscape map; S4, calculating a set of predefined marine landscape pattern indices according to the reference digital marine landscape map to quantitatively evaluate the spatial structure, wherein the marine landscape pattern indices comprise a shape index, an intra-patch cohesion index and a diversity index; S5, executing an iterative spatial optimization algorithm to generate an optimized digital marine landscape map by adjusting the function zone type attribution of the analysis units, wherein the objective function of the algorithm is configured to optimize the values of the marine landscape pattern indices to maximize the ecological connectivity under the premise of meeting predefined constraint conditions; S6, outputting the optimized digital marine landscape map.

[0007] Preferably, the sea area is divided into a plurality of analysis units based on the geographic coordinate system, and specifically comprises the following steps: a regular grid system is set for the sea area based on the geographic coordinate system; the lowest spatial resolution in the multi-source geographic spatial data and the spatial scale of an ecological process to be analyzed are acquired; the spatial resolution and the spatial scale are compared, and the smaller value is taken as the size of the analysis unit, i.e., the spatial resolution of the analysis unit; the sea area is divided according to the spatial resolution of the analysis unit.

[0008] Preferably, the function zoning type is assigned to each analysis unit based on the marine function zoning data, and specifically comprises the following steps: a set of function zoning priority standards is preset according to legal regulations, ecological importance and social and economic demands; According to the functional zoning priority criteria, starting from the highest priority, the corresponding functional zoning types are assigned to the analysis units that overlap with the relevant geospatial data layers and have not yet been assigned functions, until all analysis units are assigned a unique functional zoning type.

[0009] Preferably, the method for calculating the shape index is as follows: For a given functional area patch, obtain its total perimeter and total area; Calculate the perimeter of the square with the same total area as the minimum possible perimeter; The value of the landscape shape index is obtained by dividing the total perimeter by the minimum possible perimeter.

[0010] Preferably, the formula for calculating the plaque cohesion index is: ; In the formula, The plaque cohesion index. For the first The perimeter of the j-th patch in each functional area type. For the first The area of ​​the j-th patch in each functional zone type. For the first The total number of plaques of each functional area type This represents the total number of analysis units in the baseline map.

[0011] Preferably, the formula for calculating the diversity index is: ; In the formula, As a diversity index, For the first The area proportion of each functional zone type This represents the number of functional area types.

[0012] Preferably, an ecological connectivity modeling step is further included between step S3 and step S4, the modeling step including: Identify core ecological patches that serve as ecological runoff sources in the benchmark digital marine landscape map; Each of the analysis units is assigned an ecological resistance value to construct an ecological resistance surface; A connectivity evaluation value is calculated based on the aforementioned ecological resistance surface.

[0013] Preferably, the connectivity evaluation value is calculated using a minimum cumulative resistance model.

[0014] Preferably, the iterative spatial optimization algorithm is a simulated annealing algorithm, and the execution process thereof comprises: starting from the digital marine landscape map, randomly modifying the functional zone type attribution of one or more analysis units in each iteration, recalculating the objective function value, and determining whether to retain the modification according to a preset acceptance criterion until a convergence condition is met.

[0015] Compared with the prior art, the present application has the following advantages: The present method provides an objective and scientific basis for the comparison and evaluation of different spatial planning schemes by using standardized landscape indices.

[0016] The spatial configuration scheme generated by the present method can effectively promote the health of the marine ecosystem by actively minimizing the fragmentation of sensitive habitats and maximizing the connectivity therebetween.

[0017] By modeling and optimizing the spatial adjacency relationship of different functional zones, the present method can identify and reduce potential ecological conflicts in the planning stage, such as avoiding the direct adjacency configuration of industrial zones with high pollution risk and protected areas with ecological sensitivity, thereby reducing the risk and cost of future management. BRIEF DESCRIPTION OF DRAWINGS

[0018] Figure 1 A method flowchart of a marine functional spatial configuration method based on landscape ecology is proposed for the present application. DETAILED DESCRIPTION

[0019] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by a person of ordinary skill in the art without creative labor fall within the scope of protection of the present application.

[0020] REFERENCE Figure 1 The specific process of a marine functional spatial configuration method based on landscape ecology for the scheme will be described.

[0021] S1, multi-source data integration and unitization.

[0022] S101, data acquisition: collect geographic spatial data covering the target sea area. These data are derived from remote sensing images, navigation charts, field surveys, government department statistics and other sources. The data types include but are not limited to: Biophysical data: bathymetric data, seafloor bottom type map, marine habitat distribution map (such as important ecosystems such as coral reefs, seagrass beds, mangroves, etc.), spatiotemporal distribution data of hydrological environmental parameters (such as salinity, temperature, chlorophyll concentration, etc.), and ocean current model data.

[0023] Socio-economic data: existing marine functional zoning map, major shipping lane distribution, fishing activity intensity distribution, aquaculture area, offshore wind farm, oil and gas platform location, land-based and marine pollution source location and impact range.

[0024] S102, data standardization: to ensure that all data can be overlaid and analyzed in the same spatial framework, standardization processing is required. This processing is completed in professional GIS software. All vector and raster data are converted to a unified geographic coordinate system and projection system (e.g., WGS84-UTM). Subsequently, all data layers are rasterized to form a data cube composed of analysis units (e.g., 100m x 100m square grid cells). Each grid cell records the attribute values of all data layers corresponding to its location.

[0025] S2, initial functional zoning.

[0026] According to the data cube generated in step S1, a preliminary functional zone type is assigned to each grid cell. The assignment rule is based on the priority principle of overlay analysis. For example, if a cell contains a legally established marine nature reserve, its functional zone type is designated as "marine protection zone" first; if the cell is located in a legal shipping lane, it is designated as "port shipping zone"; if the cell is a major aquaculture area, it is designated as "agriculture and fishery zone". For areas without specific designation, they can be preliminarily classified according to their main natural attributes (such as sandy bottom, rocky reef) or the function of adjacent areas. Through this process, a complete, raster-format baseline functional zoning map covering the entire target sea area is obtained.

[0027] S3, quantitative assessment of marine landscape pattern.

[0028] Adjust the baseline map using landscape pattern indices.

[0029] By calling a special geospatial analysis module, a series of indices reflecting the characteristics of landscape structure are calculated. These indices reveal the ecological significance of the functional zoning scheme in spatial pattern from different dimensions. The core landscape indices used in the embodiments of the present invention include: Patch density index: this index measures the fragmentation degree of the landscape by calculating the number of patches per unit area. Its calculation formula is: ; In the formula, is the patch density, is the total number of patches of a specific functional zone type, This represents the total landscape area. A high PD value indicates that this functional zone type is fragmented into numerous small patches, resulting in severe fragmentation, which is particularly detrimental to marine protected areas that require large areas of continuous habitat.

[0030] Shape Index: This index measures the complexity of a patch's shape by comparing the total length of the actual patch's edges to the edge length of the most compact shape (circle or square) of the same area. Its formula is as follows: ; In the formula, The shape index, The total edge length of the patch. The shape index is the minimum possible edge length of a single square or circular patch with the same area as the total patch area. The shape index is greater than or equal to 1, and the larger the value, the more irregular and complex the patch shape.

[0031] Patch cohesion index: This index measures the physical connectivity and aggregation of similar patches and is an important indicator for assessing habitat connectivity. Its calculation formula is: ; In the formula, The plaque cohesion index. For the first The perimeter of the j-th patch in each functional area type. For the first The area of ​​the j-th patch in each functional zone type. For the first The total number of plaques of each functional area type This represents the total number of analysis units in the baseline map. The index value ranges from 0 to 100; a higher value indicates a higher degree of patch clustering and better physical connectivity for that functional area type.

[0032] Diversity Index: This index measures the richness of functional zone types and the evenness of their area distribution in a landscape. Its calculation formula is as follows: ; In the formula, As a diversity index, For the first The area proportion of each functional zone type This represents the number of functional zone types. A diversity index value of 0 indicates that the entire landscape consists of only one type. As the number of types increases and the area distribution of each type becomes more uniform, the diversity index value also increases. This index reflects the level of heterogeneity in marine functional utilization.

[0033] S4, Ecological Connectivity Modeling.

[0034] S401, identify source and target: In the base map, identify the core ecological patches that are critical to ecological connectivity as the "source" of ecological flow. These sources can be important spawning grounds, nurseries, biodiversity hotspots, or key areas for ecosystem service provision.

[0035] S402, build ecological resistance surface: Create an ecological resistance surface corresponding to the analysis grid. Each grid cell is assigned a resistance value, which represents the "difficulty" of a certain ecological process (such as the dispersal of juvenile fish) crossing the cell. Generally, high resistance values are assigned to areas with high human activity intensity and poor environmental quality, such as busy shipping lanes and industrial discharge sites; low resistance values are assigned to natural corridors or suitable habitats, such as open waters and continuous seagrass beds.

[0036] S403, simulate connectivity: Apply the connectivity model to calculate the potential connection paths and strength between sources. In this embodiment, the minimum cumulative resistance model is used. The calculation process is as follows: first, designate the core ecological patches as "sources", then simulate the minimum cumulative cost or resistance that needs to be overcome from the "source" to each analysis cell. This cost depends not only on the distance but also on the resistance value of each cell on the path. Its formula can be expressed as: ; In the formula, is the minimum cumulative resistance, is the spatial distance from source j to cell i, is the resistance value of cell i, and f is a function representing the positive correlation between cumulative resistance and distance and resistance. The calculation result is a "cost distance" map, where the value of each cell represents the minimum cumulative resistance from that point to the nearest source. Based on this map, the lowest resistance path, i.e. the potential "ecological corridor", can be identified.

[0037] S5, multi-objective spatial optimization.

[0038] Spatial structure rearrangement of a functional zoning scheme to find the optimal spatial pattern of the functional zoning scheme.

[0039] This embodiment uses the simulated annealing algorithm. The execution process of this algorithm is as follows: Step 1, initialization: Take the base map as the initial solution and calculate its initial "energy value", i.e. the value of the constructed comprehensive objective function. At the same time, set an initial "temperature" T and a cooling rate.

[0040] Step 2, iterative disturbance: At the current temperature T, a small random disturbance is made to the current solution (map) to generate a new solution. For example, randomly select two adjacent or non-adjacent analysis cells and exchange their functional zone types.

[0041] Step 3, evaluate new solution: calculate the energy value (new objective function value) of the new solution.

[0042] Step 4, acceptance criterion: compare the energy values of the new and old solutions. If the energy value of the new solution is better, accept the new solution as the starting point for the next iteration. If the energy value of the new solution is worse, the algorithm accepts this "worse solution" with a probability related to the current temperature and the energy difference. This probability decreases as the temperature decreases.

[0043] Step 5, cooling: after a certain number of iterations, reduce the temperature T according to the pre-set cooling rate.

[0044] Step 6, termination: repeat steps 2 to 5 until the temperature is reduced to a pre-set minimum value, or the objective function value no longer improves significantly for several consecutive times, at which point the algorithm converges and the iteration process terminates.

[0045] The constructed comprehensive objective function is a weighted combination of landscape indices and connectivity evaluation values. For example, a simplified objective function can be expressed as: ; In the formula, is the optimization target, is the patch density index of the protected area, is the shape index of the industrial area, is the patch cohesion index of the protected area, is the total resistance value of the corridor in the ecological connectivity modeling, , , and are weight coefficients set according to the relative importance of different objectives.

[0046] The constraints of this scheme mainly come from laws, regulations or planning requirements, such as: The total area of various functional areas must be maintained within the legal or planning upper and lower limits.

[0047] The location of certain functional areas (such as the core area of the port) must remain unchanged.

[0048] It is prohibited to configure certain functional area types (such as industrial areas) in specific sensitive areas.

[0049] The algorithm starts from a base map and iterates thousands of times. In each iteration, the algorithm randomly makes a small change to the map (e.g., swapping the functional zone types of two adjacent grid cells) and then recalculates the objective function value. If the change improves the objective function value, the change is accepted. This process continues until the objective function value no longer improves significantly or a preset iteration limit is reached, at which point the algorithm is considered to have converged.

[0050] S6, optimization scheme generation and verification.

[0051] After the algorithm converges, the final optimized digital marine landscape map is output. At the same time, the system generates a detailed comparative analysis report, and then submits the optimization scheme and its quantitative evaluation report to marine management experts and stakeholders for review and verification Through the above steps, the present scheme constructs a technical closed loop that integrates landscape ecology theory into marine functional zoning practice, overcoming the limitations of traditional qualitative zoning methods and providing a scientific, quantitative, and repeatable process for marine spatial planning, thereby effectively improving the ecological integrity of marine management planning.

[0052] In the description of the present specification, the description referring to the terms "one embodiment", "example", "specific example" and the like means that the specific features, structures, materials or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present invention. In the present specification, the illustrative description of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0053] The preferred embodiments of the present application disclosed above are only used to help explain the present application. The preferred embodiments do not describe all the details and do not limit the present application to the specific embodiments described. Obviously, many modifications and changes can be made according to the content of the present specification. The present specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present application, so that those skilled in the art can well understand and utilize the present application. The present application is limited only by the claims and their full scope and equivalents.

Claims

1. A method for marine functional space configuration based on landscape ecology, characterized in that, The method comprises the following steps: S1, acquiring multi-source geospatial data of a target sea area, wherein the multi-source geospatial data comprises marine functional zoning data; S2, standardizing the multi-source geospatial data to a unified geographic coordinate system and projection system, and dividing the sea area into a plurality of analysis units based on the geographic coordinate system; S3, assigning a functional zoning type to each analysis unit based on the marine functional zoning data to generate a reference digital marine landscape map; S4, calculating a set of predefined marine landscape pattern indices based on the reference digital marine landscape map to quantitatively evaluate the spatial structure thereof, wherein the marine landscape pattern indices comprise a shape index, a patch cohesion index and a diversity index; S5, executing an iterative spatial optimization algorithm to generate an optimized digital marine landscape map by adjusting the functional zoning type attribution of the analysis units, wherein an objective function of the algorithm is configured to optimize the values of the marine landscape pattern indices to maximize ecological connectivity under the premise of meeting predefined constraint conditions; S6, outputting the optimized digital marine landscape map. 2.The method of claim 1, wherein, The sea area is divided into a plurality of analysis units based on the geographic coordinate system, specifically comprising: a regular grid system is set for the sea area based on the geographic coordinate system; the lowest spatial resolution in the multi-source geospatial data and the spatial scale of the ecological process to be analyzed are acquired; the spatial resolution and the spatial scale are compared, and the smaller value is taken as the size of the analysis unit, i.e. the spatial resolution of the analysis unit; the sea area is divided according to the spatial resolution of the analysis unit. 3.The method of claim 1, wherein, Each analysis unit is assigned a functional zoning type based on the marine functional zoning data, specifically comprising: a set of functional zoning priority standards are pre-set according to legal regulations, ecological importance and social and economic needs; according to the functional zoning priority standards, the corresponding functional zoning type is sequentially assigned to the analysis units that overlap with the relevant geospatial data layers and have not been assigned a function, starting from the highest priority, until all analysis units are assigned a unique functional zoning type. 4.The method of claim 1, wherein, The calculation method of the shape index is: for a functional zone patch, the total perimeter and total area thereof are acquired; the perimeter of a square equal to the total area is calculated as the minimum possible perimeter; the total perimeter is divided by the minimum possible perimeter to obtain the value of the landscape shape index.

5. The method according to claim 1, wherein, The calculation formula of the patch cohesion index is: ； In the formula, is the patch cohesion index, is the jth patch in the i th functional area type, is the perimeter of the jth patch in the i th functional area type, is the area of the jth patch in the i th functional area type, is the total number of patches in the i th functional area type, is the total number of patches in the i th functional area type, is the total number of patches in the i th functional area type, is the total number of analysis units in the reference map. 6.The method of claim 1, wherein, The calculation formula of the diversity index is: ； In the formula, is a diversity index, is the area proportion of the first functional area type, is the number of functional area types.

7. The method according to claim 1, wherein, An ecological connectivity modeling step is further included between step S3 and step S4, and the modeling step comprises: core ecological patches serving as ecological flow sources are identified in the reference digital marine landscape map; an ecological resistance value is assigned to each analysis unit to construct an ecological resistance surface; a connectivity evaluation value is calculated based on the ecological resistance surface.

8. The method according to claim 7, wherein, The connectivity evaluation value is calculated using a minimum cumulative resistance model. 9.The method of claim 1, wherein, The iterative space optimization algorithm is a simulated annealing algorithm, and the execution process thereof comprises the following steps: starting from the digital marine landscape map, randomly modifying the functional region type attribution of one or more analysis units in each iteration, recalculating the target function value, and determining whether to retain the modification according to a preset acceptance criterion until a convergence condition is met.

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