Ecological network construction method and device with space dust collection function and electronic equipment

Abstract

This invention provides a method, device, and electronic device for constructing an ecological network with spatial dust retention function, belonging to the field of ecological planning technology. The method includes: correcting the basic PM2.5 diffusion resistance coefficient of each spatial grid in the spatial grid model based on a landscape correction factor to obtain a comprehensive PM2.5 diffusion resistance surface; the basic PM2.5 diffusion resistance coefficient is determined based on the hindering effect of land use type on PM2.5 diffusion; based on the spatial distribution map of PM2.5 pollution sources and the comprehensive PM2.5 diffusion resistance surface, performing minimum cumulative cost analysis and current distribution calculation based on circuit theory to obtain PM2.5 diffusion corridors; and identifying and analyzing key control nodes based on the PM2.5 diffusion corridors to obtain key control nodes for constructing a PM2.5 diffusion control ecological network. This invention realizes a systematic PM2.5 diffusion control ecological network construction scheme integrating landscape ecology source-corridor-node morphology.

Description

Technical Field

[0001] This invention relates to the field of ecological planning technology, and in particular to a method, apparatus and electronic device for constructing an ecological network with spatial dust retention function. Background Technology

[0002] PM2.5 pollution has become a prominent weakness in the sustainable development of megacities, weakening their ability to attract high-end resources.

[0003] Currently, PM2.5 control approaches can be broadly categorized into two types: one is an engineering technology system that focuses on end-of-pipe emission reduction, such as industrial upgrading and traffic restrictions; the other is an air quality improvement strategy based on blue-green space layout, which involves increasing the coverage area of ​​blue-green spaces with dust retention functions and using the constructed ecological network to place the increased blue-green spaces along roadsides or downwind of pollution sources, thus isolating pollution sources from densely populated areas.

[0004] However, in the PM2.5 control path of increasing the layout of blue-green spaces, the placement of the increased blue-green spaces beside roads or downwind of pollution sources is often isolated. This is because the constructed ecological network tends to only characterize the impact of biological information flow resistance, without taking into account the impact of blue-green space layout on PM2.5 diffusion, which makes it impossible to meet the high standards of modern urban agglomeration for refined air quality control. Summary of the Invention

[0005] This invention provides a method, apparatus, and electronic device for constructing an ecological network with spatial dust retention function, which solves the shortcomings of existing technologies that only describe the resistance to biological information flow, and achieves high-standard and precise air quality management.

[0006] This invention provides a method for constructing an ecological network with spatial dust retention function, comprising:

[0007] Obtain a spatial distribution map of PM2.5 pollution sources;

[0008] Based on the landscape correction factor, the basic PM2.5 diffusion resistance coefficient of each spatial grid in the spatial grid model is corrected to obtain the comprehensive PM2.5 diffusion resistance surface; the basic PM2.5 diffusion resistance coefficient is determined based on the hindering effect of land use type of the spatial grid on PM2.5 diffusion;

[0009] Based on the spatial distribution map of PM2.5 pollution sources and the comprehensive resistance surface of PM2.5 diffusion, minimum cumulative cost analysis and current distribution calculation based on circuit theory are performed to obtain PM2.5 diffusion corridors;

[0010] Based on the PM2.5 diffusion corridor, key control nodes are identified and analyzed to obtain key control nodes, so as to construct an ecological network for PM2.5 diffusion control.

[0011] According to the present invention, a method for constructing an ecological network with spatial dust retention function is provided. The method involves correcting the basic PM2.5 diffusion resistance coefficient of each spatial grid in the spatial grid model based on a landscape correction factor to obtain a comprehensive PM2.5 diffusion resistance surface. This includes: correcting the basic PM2.5 diffusion resistance coefficient of each spatial grid in the spatial grid model based on a vegetation coverage factor, a road density factor, and a nighttime light index factor to obtain the comprehensive PM2.5 diffusion resistance surface; the vegetation coverage factor is determined based on the membership degree of vegetation coverage in the land use type; the road density factor is determined based on the membership degree of road density in the land use type; and the nighttime light index factor is determined based on the membership degree of nighttime light index in the land use type.

[0012] According to the present invention, a method for constructing an ecological network with spatial dust retention function, wherein the method involves performing minimum cumulative cost analysis and current distribution calculation based on circuit theory, based on the PM2.5 pollution source spatial distribution map and the PM2.5 diffusion comprehensive resistance surface, to obtain PM2.5 diffusion corridors, includes: determining the grid cost of the spatial grid model based on the PM2.5 diffusion comprehensive resistance surface; for each PM2.5 pollution source grid in the PM2.5 pollution source spatial distribution map, determining the grid cost of the PM2.5 pollution source grid and the PM2.5 diffusion corridor based on the PM2.5 diffusion comprehensive resistance surface; and for each PM2.5 pollution source grid in the PM2.5 pollution source spatial distribution map, determining the grid cost of the PM2.5 pollution source grid and the PM2.5 diffusion corridor based on the PM2.5 diffusion comprehensive resistance surface. 2.5 The grid distance between the PM2.5 pollution source grid and other spatial grids outside the PM2.5 pollution source grid is calculated, and the cumulative cost distance of the PM2.5 pollution source grid is obtained to obtain the cumulative cost distance of all PM2.5 pollution source grids in the PM2.5 pollution source spatial distribution map; using current distribution calculation based on circuit theory, the multipath and superposition effect of PM2.5 diffusion is simulated based on the cumulative cost distance to obtain multiple PM2.5 diffusion paths; vectorization and merging operations are performed on the PM2.5 diffusion paths to obtain the PM2.5 diffusion corridor.

[0013] According to the present invention, a method for constructing an ecological network with spatial dust retention function is provided. The method involves identifying and analyzing key control nodes based on the PM2.5 diffusion corridor to construct a PM2.5 diffusion control ecological network. This includes: identifying key pollution source nodes, floating dust nodes, and dust retention nodes using a key element mapping tool based on the PM2.5 diffusion corridor and the PM2.5 diffusion comprehensive resistance surface; determining the intersection of the resistance peak and the PM2.5 diffusion corridor as potential dust retention nodes; and constructing the PM2.5 diffusion control ecological network based on the key pollution source nodes, floating dust nodes, dust retention nodes, and potential dust retention nodes.

[0014] According to the present invention, an ecological network construction method with spatial dust retention function, after identifying and analyzing key control nodes based on the PM2.5 diffusion corridor to construct a PM2.5 diffusion control ecological network, the method further includes: for the dust retention nodes, delineating ecological control boundaries with the grid centroid of the dust retention node as the geometric center; and for the potential dust retention nodes, formulating graded vegetation restoration plans based on the vegetation coverage factor, bare land rate factor, soil condition factor, and modification feasibility factor of the potential dust retention nodes.

[0015] According to the present invention, an ecological network construction method with spatial dust retention function is provided. The step of obtaining a spatial distribution map of PM2.5 pollution sources includes: calculating the local aggregation statistics of each spatial grid based on the PM2.5 grid concentration data of each spatial grid in the spatial grid model; determining the PM2.5 pollution source hotspot grids based on the local aggregation statistics, their expected value, and coefficient of variation; determining the PM2.5 pollution source core area based on the PM2.5 pollution source hotspot grids; and constructing the PM2.5 pollution source spatial distribution map based on the PM2.5 pollution source core area.

[0016] According to the present invention, an ecological network construction method with spatial dust retention function is provided. The step of determining the core area of ​​PM2.5 pollution sources based on the PM2.5 pollution source hotspot grid includes: overlaying the PM2.5 pollution source hotspot grid with a binary image of built-up land to generate a potential pollution source mask layer; performing morphological spatial pattern analysis on the potential pollution source mask layer, and determining the core area of ​​PM2.5 pollution sources according to the topological connectivity of the spatial grid and the overall structural spatial geometric relationship.

[0017] The present invention also provides an ecological network construction device with spatial dust retention function, comprising:

[0018] The source distribution map acquisition module is used to acquire the spatial distribution map of PM2.5 pollution sources;

[0019] The diffusion resistance surface acquisition module is used to correct the basic PM2.5 diffusion resistance coefficient of each spatial grid in the spatial grid model based on the landscape correction factor, so as to obtain the comprehensive PM2.5 diffusion resistance surface; the basic PM2.5 diffusion resistance coefficient is determined based on the land use type of the spatial grid and its hindering effect on PM2.5 diffusion;

[0020] The diffusion corridor acquisition module is used to perform minimum cumulative cost analysis and current distribution calculation based on circuit theory, based on the PM2.5 pollution source spatial distribution map and the PM2.5 diffusion comprehensive resistance surface, to obtain the PM2.5 diffusion corridor;

[0021] The network construction module is used to identify and analyze key control nodes based on the PM2.5 diffusion corridor, obtain key control nodes, and construct a PM2.5 diffusion control ecological network.

[0022] The present invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and running on the processor, wherein the processor executes the computer program to implement the ecological network construction method with spatial dust retention function as described above.

[0023] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the ecological network construction method with spatial dust retention function as described above.

[0024] The present invention also provides a computer program product, including a computer program that, when executed by a processor, implements the ecological network construction method with spatial dust retention function as described above.

[0025] The present invention provides a method, apparatus, and electronic device for constructing an ecological network with spatial dust retention function. By focusing on PM2.5 pollutant diffusion as the key aspect of ecological network construction, considering the systematic blocking effect of regional landscape continuum on air pollutants, and using landscape correction factors to adjust the effect coefficient of land use type on PM2.5 diffusion, a comprehensive resistance surface for PM2.5 diffusion is obtained, which integrates the influence of landscape on PM2.5 diffusion. Using the comprehensive resistance surface for PM2.5 diffusion and a spatial distribution map of PM2.5 pollution sources, minimum cumulative cost analysis and current distribution calculations based on circuit theory are performed to obtain PM2.5 diffusion corridors. Key control nodes are identified to construct a PM2.5 diffusion control ecological network, improving the accuracy of corridor identification and key node quantification, and realizing a systematic PM2.5 diffusion control ecological network construction scheme that integrates landscape ecology source-corridor-node morphology. Attached Figure Description

[0026] To more clearly illustrate the technical solutions in this invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0027] Figure 1 This is one of the flowcharts illustrating the method for constructing an ecological network with spatial dust retention function provided by the present invention.

[0028] Figure 2 This is the second flowchart of the ecological network construction method with spatial dust retention function provided by the present invention.

[0029] Figure 3 This is a schematic diagram of the structure of the ecological network construction device with spatial dust retention function provided by the present invention.

[0030] Figure 4 This is a schematic diagram of the structure of the electronic device provided by the present invention. Detailed Implementation

[0031] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0032] It should be noted that, in the description of this invention, the term "comprising" or any other variations thereof is intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Those skilled in the art will understand the specific meaning of the above terms in this invention according to the specific circumstances. Furthermore, "and / or" indicates at least one of the connected objects, and the character " / " generally indicates that the preceding and following related objects are in an "or" relationship.

[0033] The following is combined Figures 1-4 This invention describes the method, apparatus, and electronic equipment for constructing an ecological network with spatial dust retention function.

[0034] Figure 1 This is one of the flowcharts illustrating the method for constructing an ecological network with spatial dust retention function provided by the present invention, such as... Figure 1As shown, the method for constructing an ecological network with spatial dust retention function includes, but is not limited to, steps 101 to 104.

[0035] It should be noted that the execution subject of the ecological network construction method with spatial dust retention function provided by the present invention is the corresponding ecological network construction device with spatial dust retention function, which can be an industrial control terminal, server, computer equipment, such as mobile phone, tablet computer, laptop computer, handheld computer, ultra-mobile personal computer (UMPC), netbook or personal digital assistant (PDA), etc.

[0036] Step 101: Obtain a spatial distribution map of PM2.5 pollution sources.

[0037] Among them, the PM2.5 pollution source spatial distribution map is a spatial distribution map of PM2.5 pollution sources on the spatial grid model corresponding to the PM2.5 control area.

[0038] Specifically, multi-temporal PM2.5 concentration data for the PM2.5 control area are acquired in advance or in real time for several periods. Based on the spatial grid model corresponding to the PM2.5 control area, the PM2.5 concentration data are uniformly resampled to the same spatial resolution (e.g., 1 km) using the nearest neighbor interpolation method. This yields the PM2.5 grid concentration data for each spatial grid on the spatial grid model. The PM2.5 grid concentration data is then analyzed and processed, and a spatial distribution map of PM2.5 pollution sources is obtained based on the analysis and processing results.

[0039] Optionally, PM2.5 pollution sources include PM2.5 residential sources and / or PM2.5 production sources.

[0040] Optionally, considering the potential anomalies in PM2.5 from residential and / or production sources at different times (e.g., only residential activities exist while production activities cease during a certain period), for the PM2.5 grid concentration data of each spatial grid, the PM2.5 grid concentration data of the next period is subtracted pixel by pixel from the PM2.5 grid concentration data of that period to obtain the PM2.5 concentration difference. Positive PM2.5 concentration differences are retained as the PM2.5 grid concentration data. Through PM2.5 concentration difference analysis, PM2.5 grid concentration data for each spatial grid is obtained, stripped of abnormal PM2.5 residential or production sources, eliminating the impact of abnormal PM2.5 emissions caused by anomalous events, thereby extracting the long-term stable distribution trend of PM2.5 pollution sources.

[0041] Taking a PM2.5 control area where only daily life activities existed and production activities ceased in 2020 as an example, the PM2.5 grid concentration data for the next period, 2022, was used to subtract the PM2.5 grid concentration data for 2020, and a spatial distribution map of PM2.5 pollution sources was constructed based on the PM2.5 grid concentration data after removing outliers.

[0042] Step 102: Based on the landscape correction factor, correct the basic PM2.5 diffusion resistance coefficient of each spatial grid in the spatial grid model to obtain the comprehensive PM2.5 diffusion resistance surface.

[0043] The basic PM2.5 diffusion resistance coefficient is determined based on the hindering effect of land use type on PM2.5 diffusion in a spatial grid.

[0044] Land use types include, but are not limited to, forest land, shrubland, grassland, farmland, buildings, bare land, and water bodies, which can be determined by the latest remote sensing classification results each year.

[0045] Landscape correction factors are used to correct the basic PM2.5 diffusion resistance coefficient of the spatial grid, including but not limited to vegetation coverage factor, road density factor and nighttime light index factor.

[0046] Specifically, the basic PM2.5 diffusion resistance coefficient of each spatial grid in the spatial grid model is determined in advance based on the hindering effect of land use type on PM2.5 diffusion. Then, the basic PM2.5 diffusion resistance coefficient of each spatial grid is corrected using a landscape correction factor. Based on the corrected basic PM2.5 diffusion resistance coefficient, the comprehensive PM2.5 diffusion resistance surface of the spatial grid model is determined.

[0047] In one embodiment, the step of correcting the basic PM2.5 diffusion resistance coefficient of each spatial grid in the spatial grid model based on the landscape correction factor, and pre-determining the basic PM2.5 diffusion resistance coefficient based on the land use type of the spatial grid includes: using the Delphi expert consultation method, inviting multiple senior researchers engaged in landscape ecology and environmental science to independently score the barrier effect of different land use types in the PM2.5 diffusion process, and using the average score of each senior researcher as the basic PM2.5 diffusion resistance coefficient of the land use type.

[0048] For example, the basic PM2.5 diffusion resistance coefficients of spatial grids for different land use types are 500 for forest, 300 for shrubland, 100 for grassland, 30 for farmland, 10 for buildings, 0 for bare land, and 200 for water bodies.

[0049] Step 103: Based on the spatial distribution map of PM2.5 pollution sources and the comprehensive resistance surface of PM2.5 diffusion, perform minimum cumulative cost analysis (MCA) and current distribution calculation based on circuit theory to obtain PM2.5 diffusion corridors.

[0050] Among them, the PM2.5 diffusion corridor is a "high-flow" corridor used to characterize the actual diffusion trend of PM2.5.

[0051] Specifically, after obtaining the spatial distribution map of PM2.5 pollution sources and the comprehensive resistance surface of PM2.5 diffusion, geographic information system software (such as ArcGIS) is used to perform minimum cumulative cost analysis and current distribution calculation based on circuit theory on the spatial distribution map of PM2.5 pollution sources and the comprehensive resistance surface of PM2.5 diffusion to obtain PM2.5 diffusion corridors. For example, the minimum cumulative cost model and the Circuitscape current field model are used to extract PM2.5 diffusion corridors.

[0052] Step 104: Based on the PM2.5 diffusion corridor, identify and analyze key control nodes to obtain key control nodes, so as to construct a PM2.5 diffusion control ecological network.

[0053] Among them, key control nodes are the key nodes for controlling the spread of PM2.5, including but not limited to at least one of the following: key pollution source nodes, floating dust nodes, dust retention nodes, and potential dust retention nodes.

[0054] Specifically, by using key element mapping tools, key control nodes for controlling PM2.5 diffusion are identified and analyzed based on PM2.5 diffusion corridors, and an ecological network for controlling PM2.5 diffusion is constructed based on these key control nodes, thus creating an ecological network that considers the impact of PM2.5 diffusion on the blue-green space layout.

[0055] The present invention provides an ecological network construction method with spatial dust retention function. By focusing on PM2.5 pollutant diffusion as the key point of ecological network construction, it considers the systematic blocking effect of regional landscape continuum on air pollutants, and uses landscape correction factors to correct the effect coefficient of land use type on PM2.5 diffusion. This yields a comprehensive PM2.5 diffusion resistance surface that integrates the influence of landscape on PM2.5 diffusion. Using the comprehensive PM2.5 diffusion resistance surface and the spatial distribution map of PM2.5 pollution sources, minimum cumulative cost analysis and current distribution calculation based on circuit theory are performed to obtain PM2.5 diffusion corridors. Key control nodes are identified to construct a PM2.5 diffusion control ecological network, which improves the accuracy of corridor identification and the quantification accuracy of key nodes. This realizes a systematic PM2.5 diffusion control ecological network construction scheme that integrates the source-corridor-node morphology of landscape ecology.

[0056] Based on the above embodiments, as an optional embodiment, the step of correcting the basic PM2.5 diffusion resistance coefficient of each spatial grid in the spatial grid model based on the landscape correction factor to obtain the comprehensive PM2.5 diffusion resistance surface includes:

[0057] Based on vegetation coverage factor, road density factor and nighttime light index factor, the basic PM2.5 diffusion resistance coefficient of each spatial grid in the spatial grid model is corrected to obtain the PM2.5 diffusion comprehensive resistance surface.

[0058] The vegetation coverage factor is determined based on the membership degree of vegetation coverage in the land use type; the road density factor is determined based on the membership degree of road density in the land use type; and the nighttime light index factor is determined based on the membership degree of nighttime light index in the land use type.

[0059] Specifically, when constructing a comprehensive resistance surface for PM2.5 diffusion that reflects the impact of landscape heterogeneity, vegetation coverage, road density, nighttime light index, and land use type are used as the source data for landscape resistance. The resistance source data are uniformly resampled to a raster format with a preset spatial resolution (e.g., 1km×1km) to ensure that the spatial scale of the input data is consistent.

[0060] Considering the negative correlation between road density, nighttime light index, and land use type on PM2.5 diffusion, the reciprocals of road density and nighttime light index data (two sources of landscape resistance) are taken and normalized using a maximum-minimum method. These normalized values, along with vegetation cover data (which is directly normalized using a maximum-minimum method), are then input into a fuzzy membership function to generate vegetation cover, road density, and nighttime light index factors that satisfy preset value rules (e.g., mean 1, value range 0-2). Here, the vegetation cover factor represents the membership degree of vegetation cover in a specific land use type; the road density factor represents the membership degree of road density in a specific land use type; and the nighttime light index factor represents the membership degree of nighttime light index in a specific land use type.

[0061] Further utilizing the raster calculator tool in the Geographic Information System (GIS) software, at the cell level, for each spatial raster in the spatial raster model, the basic PM2.5 diffusion resistance coefficient corresponding to the land use type of that spatial raster is weighted and multiplied by the three corresponding landscape correction factors, thus correcting the basic PM2.5 diffusion resistance coefficient of each spatial raster in the spatial raster model. In this case, the larger the landscape correction factor, the larger the corrected PM2.5 diffusion resistance coefficient.

[0062] After correcting the basic PM2.5 diffusion resistance coefficients of all spatial grids in the spatial grid model, the comprehensive PM2.5 diffusion resistance surface is obtained.

[0063] In one embodiment, the calculation formula for the basic PM2.5 diffusion resistance coefficient of each spatial grid in the spatial grid model, based on vegetation cover factor, road density factor, and nighttime light index factor, is as follows:

[0064] ;

[0065] in, This is the corrected PM2.5 diffusion resistance coefficient; The number of land use types; For the first The basic PM2.5 diffusion resistance coefficient for each land use type; For the first Road density factor for different land use types; For the first Nighttime light index factors for various land use types; For the first Vegetation cover factor for each land use type.

[0066] The ecological network construction method with spatial dust retention function provided by this invention considers the systematic blocking effect of regional landscape continuum on air pollutants. It uses three landscape correction factors—vegetation coverage factor, road density factor, and nighttime light index factor—to correct the effect coefficient of land use type on PM2.5 diffusion, and obtains the comprehensive resistance surface of PM2.5 diffusion that integrates the influence of landscape on PM2.5 diffusion. This is used to construct an ecological network for PM2.5 diffusion control, which can further improve the accuracy of corridor identification and the quantification accuracy of key nodes. It realizes a systematic PM2.5 diffusion control ecological network construction scheme that integrates the morphology of landscape ecology sources, corridors, and nodes.

[0067] Based on the above embodiments, as an optional embodiment, the step of performing minimum cumulative cost analysis and current distribution calculation based on circuit theory, based on the PM2.5 pollution source spatial distribution map and the PM2.5 diffusion comprehensive resistance surface, to obtain the PM2.5 diffusion corridor, includes:

[0068] Based on the comprehensive resistance surface for PM2.5 diffusion, the grid cost of the spatial grid model is determined.

[0069] For each PM2.5 pollution source grid in the spatial distribution map of PM2.5 pollution sources, the cumulative cost distance of the PM2.5 pollution source grid is calculated based on the grid cost of the PM2.5 pollution source grid and the grid distance between the PM2.5 pollution source grid and other spatial grids outside the PM2.5 pollution source grid, so as to obtain the cumulative cost distance of all PM2.5 pollution source grids in the spatial distribution map of PM2.5 pollution sources;

[0070] By using current distribution calculations based on circuit theory, and simulating the multipath and superposition effects of PM2.5 diffusion based on the cumulative cost distance, multiple PM2.5 diffusion paths are obtained;

[0071] The PM2.5 diffusion path is vectorized and merged to obtain the PM2.5 diffusion corridor.

[0072] After obtaining the spatial distribution map of PM2.5 pollution sources and the comprehensive resistance surface of PM2.5 diffusion, based on minimum cumulative cost analysis and current distribution calculations based on circuit theory, the PM2.5 diffusion corridors under heterogeneous landscapes are further simulated and constructed using the spatial distribution map of PM2.5 pollution sources and the comprehensive resistance surface of PM2.5 diffusion to identify key control nodes.

[0073] Specifically, the PM2.5 diffusion resistance surface is input into the Geographic Information System (GIS) software. The GIS software then determines the raster cost of each spatial raster in the spatial raster model based on the corrected PM2.5 diffusion resistance coefficient of each spatial raster in the PM2.5 diffusion resistance surface. The corrected PM2.5 diffusion resistance coefficient is positively correlated with the raster cost; the higher the corrected PM2.5 diffusion resistance coefficient, the higher the raster cost.

[0074] Further utilizing the cost distance analysis function in the geographic information system software, and employing the minimum cumulative cost analysis method based on circuit theory, the cumulative cost distance between each source (PM2.5 pollution source grid) and sink (other spatial grid) combination is calculated to identify the optimal path that pollutants need to cross from the source to other locations, thus obtaining the PM2.5 diffusion corridor.

[0075] Specifically, for each PM2.5 pollution source grid in the spatial distribution map of PM2.5 pollution sources, the cost-distance analysis function is based on that PM2.5 pollution source grid. raster cost and the PM2.5 pollution source grid Other spatial grids Grid distance between Calculate the PM2.5 pollution source grid The cumulative cost distance is calculated by repeatedly performing the cumulative cost distance analysis step to obtain the cumulative cost distance for all PM2.5 pollution source grids within the PM2.5 pollution source spatial distribution map. A smaller cumulative cost distance value indicates that the corresponding PM2.5 diffusion path is more easily utilized by PM2.5 particles.

[0076] The Linkage Mapper software is then used to perform current distribution calculations based on circuit theory. The calculated cumulative cost distance is used as the overall drag coefficient and input into the Linkage Mapper software. At this point, PM2.5 pollutants are considered as particles randomly wandering on the landscape resistivity surface. The current intensity of multiple PM2.5 pollution source grids is superimposed to form a current density map. Continuous high-value areas of current density are extracted. The Linkage Mapper software simulates the multipath and superposition effects of PM2.5 pollutant diffusion. The minimum cost gradient is traced back point by point to extract multiple PM2.5 diffusion paths from PM2.5 pollution source grids to other spatial grids. The multiple PM2.5 diffusion paths are then vectorized and merged to obtain the "high-flow corridor" that characterizes the actual diffusion trend of PM2.5, i.e., the PM2.5 diffusion corridor.

[0077] In one embodiment, the formula for calculating the cumulative cost distance of the PM2.5 pollution source grid based on the grid cost of the PM2.5 pollution source grid and the grid distance between the PM2.5 pollution source grid and other spatial grids outside the PM2.5 pollution source grid is as follows:

[0078] ;

[0079] in, For PM2.5 pollutants from the first The PM2.5 pollution source grid spread to the first The cumulative cost distance of each other spatial grid; The number of PM2.5 pollution source grids; This represents the number of other spatial grid cells; For the first The PM2.5 pollution source grid is up to the first The grid distance between other spatial grids; For the first The cost of a PM2.5 pollution source grid; To reflect the cumulative cost distance With variables A monotonically increasing function that is directly proportional to the given information.

[0080] Optionally, the other spatial grids are all grids in the spatial grid model except for the PM2.5 pollution source grids; or, the other spatial grids are the preset boundary grids and / or preset clean grids in the spatial grid model.

[0081] The present invention provides a method for constructing an ecological network with spatial dust retention function. By utilizing the comprehensive resistance surface of PM2.5 diffusion, which integrates the influence of landscape on PM2.5 diffusion, and the spatial distribution map of PM2.5 pollution sources, the method performs minimum cumulative cost analysis and current distribution calculation based on circuit theory to obtain PM2.5 diffusion corridors. This method further identifies key control nodes to construct a PM2.5 diffusion control ecological network, improving the accuracy of corridor identification and the quantification accuracy of key nodes. It realizes a systematic PM2.5 diffusion control ecological network construction scheme that integrates the source-corridor-node morphology of landscape ecology.

[0082] Based on the above embodiments, as an optional embodiment, the step of identifying and analyzing key control nodes based on the PM2.5 diffusion corridor to obtain key control nodes and construct a PM2.5 diffusion control ecological network includes:

[0083] Based on the PM2.5 diffusion corridors and the spatial distribution map of PM2.5 pollution sources, key pollution source nodes, floating dust nodes, and dust retention nodes are identified using key element mapping tools.

[0084] By superimposing the PM2.5 diffusion corridor and the PM2.5 diffusion comprehensive resistance surface, the intersection of the resistance peak and the PM2.5 diffusion corridor is identified as a potential dust retention node.

[0085] Based on the key pollution source nodes, the floating dust nodes, the dust retention nodes, and the potential dust retention nodes, the PM2.5 diffusion control ecological network is constructed.

[0086] Among them, key element mapping tools are tools used to identify, quantify, and visualize the spatial distribution of specific key elements such as centrality nodes, central edges, bottlenecks, and barriers, including but not limited to mapping tools such as Centrality Mapper, Pinchpoint Mapper, and Barrier Mapper.

[0087] Specifically, based on the corridor network of PM2.5 diffusion corridors, on the one hand, three key element mapping tools are used to identify and analyze the PM2.5 diffusion corridors and the spatial distribution map of PM2.5 pollution sources, and to identify key pollution source nodes, floating dust nodes, and dust retention nodes.

[0088] Specifically, the centrality of each PM2.5 pollution source grid is calculated using Centrality Mapper, which is the degree of contribution of each PM2.5 pollution source grid to the current connectivity of the entire PM2.5 diffusion corridor network. The PM2.5 pollution source grids are sorted according to their centrality, and the PM2.5 pollution source grids with the highest centrality or greater than the preset centrality threshold are identified as key pollution source nodes.

[0089] Using Pinchpoint Mapper, a local search was performed on the corridor current density map corresponding to the PM2.5 diffusion corridor to extract bottleneck sections with high current density and obvious corridor contraction. In other words, “transfer nodes” that are conducive to the diffusion of PM2.5 pollutants between PM2.5 pollution source grids were identified as dust nodes.

[0090] By using Barrier Mapper to simulate the rate of change of the overall effective resistance (or total current) of the network after PM2.5 pollution source grids or PM2.5 diffusion paths are blocked, the node blocking effect is quantified, and the nodes with the greatest impact on overall connectivity are identified as dust retention nodes, so that ecological intervention can be prioritized for dust retention nodes.

[0091] On the other hand, by superimposing the resistance coefficient data of PM2.5 diffusion corridors and PM2.5 diffusion comprehensive resistance surfaces, the intersection of the resistance peak and the PM2.5 diffusion corridor is identified as a potential dust retention node, that is, a node that currently has a weak ability to block PM2.5 diffusion but has the potential for structural optimization and ecological improvement.

[0092] Finally, an ecological network for PM2.5 diffusion control was constructed using the identified key pollution source nodes, floating dust nodes, dust retention nodes, and potential dust retention nodes.

[0093] The ecological network construction method with spatial dust retention function provided by this invention, based on PM2.5 diffusion corridors calculated using cumulative cost distance and current distribution based on current theory, uses a variety of key element mapping tools to process PM2.5 diffusion corridors, thereby identifying key control nodes including key pollution source nodes, floating dust nodes, dust retention nodes, and potential dust retention nodes to construct a PM2.5 diffusion control ecological network. This improves the quantitative accuracy of key nodes and realizes a systematic PM2.5 diffusion control ecological network construction scheme that integrates landscape ecology source-corridor-node morphology.

[0094] Based on the above embodiments, as an optional embodiment, after identifying and analyzing key control nodes based on the PM2.5 diffusion corridor to obtain key control nodes and construct a PM2.5 diffusion control ecological network, the method further includes:

[0095] For the dust-trapping nodes, the ecological control boundary is delineated with the grid centroid of the dust-trapping nodes as the geometric center;

[0096] For the potential dust-trapping nodes, a graded vegetation restoration plan is formulated based on the vegetation coverage factor, bare land rate factor, soil condition factor, and transformation feasibility factor of the potential dust-trapping nodes.

[0097] Specifically, after identifying key control nodes and constructing an ecological network for PM2.5 diffusion control, in order to achieve precise governance of key pollution nodes and continuous enhancement of ecological blocking effectiveness, based on the identified dust retention nodes and potential dust retention nodes, differentiated ecological intervention strategies are formulated, targeting the significance of the former's blocking function on PM2.5 diffusion and the latter's potential to enhance the blocking function on PM2.5 diffusion.

[0098] Specifically, on the one hand, for dust-trapping nodes, a ring-shaped buffer zone with a preset radius (e.g., 500 meters) is generated using the grid centroid of the dust-trapping node as the geometric center, and an ecological control boundary is delineated accordingly. Within the ecological control boundary, development activities that weaken vegetation cover, such as new construction land, road hardening, and large-scale vegetation reduction, are prohibited. Priority is given to preserving existing composite landscape elements such as forest land, water bodies, and wetlands. By adjusting land use types and uses, good vegetation connectivity, settlement structure, and the integrity of the forest-water composite pattern are maintained, stabilizing their natural particulate matter interception and settlement functions.

[0099] On the other hand, for potential dust-trapping nodes, a tiered vegetation restoration plan is formulated based on the current vegetation cover level, bare land rate, soil conditions, and restoration feasibility factors corresponding to the vegetation cover factor, bare land rate factor, soil condition factor, and restoration feasibility factor of the potential dust-trapping node. In the tiered vegetation restoration plan, priority is given to selecting high dust-trapping tree species (such as camphor trees and privet) with local adaptability, well-developed root systems, large leaf area, and rough surface for point or strip replanting, combined with herbaceous and shrub plants to enhance vegetation layering and biodiversity; at the same time, a buffer green belt connecting with the urban green corridor system is planned around the potential dust-trapping nodes to strengthen landscape connectivity and pollution barrier capacity, and enhance spatial continuity.

[0100] In one embodiment, after delineating ecological control boundaries and / or formulating and implementing graded vegetation restoration plans, a remote sensing-ground joint monitoring system is constructed to regularly assess key indicators such as vegetation cover changes, measured PM2.5 concentrations (through air quality monitoring equipment), and leaf particle deposition (through leaf sampling analysis) at dust-trapping nodes and potential dust-trapping nodes. If the monitoring results do not reach the target threshold, the land use restriction area, replanting density, or species configuration is adjusted in a timely manner according to the dynamic feedback mechanism to ensure that the blocking capacity of the ecological network continues to improve during the operation period and that dust-trapping nodes and potential dust-trapping nodes are maintained in the optimal ecological blocking state in the long term.

[0101] The ecological network construction method with spatial dust retention function provided by this invention, based on the PM2.5 diffusion corridors calculated by cumulative cost distance and current distribution based on current theory, formulates differentiated ecological intervention strategies according to the dust retention nodes and potential dust retention nodes obtained by further precise identification, which provides strong support for the active blocking of urban air pollution and the fine management of ecological space.

[0102] Based on the above embodiments, as an optional embodiment, obtaining the spatial distribution map of PM2.5 pollution sources includes:

[0103] Based on the PM2.5 grid concentration data of each spatial grid in the spatial grid model, the local clustering statistics of each spatial grid are calculated;

[0104] Based on the local cluster statistics, their expected values, and coefficients of variation, a PM2.5 pollution source hotspot grid is determined.

[0105] Based on the aforementioned PM2.5 pollution source hotspot grid, the core area of ​​PM2.5 pollution sources is determined;

[0106] Based on the core area of ​​the PM2.5 pollution source, a spatial distribution map of the PM2.5 pollution source is constructed.

[0107] Specifically, when acquiring spatial distribution maps of PM2.5 pollution sources, multi-temporal PM2.5 concentration data of the spatial raster model corresponding to the PM2.5 control area is acquired in advance or in real time. After certain processing, the PM2.5 raster concentration data of each spatial raster in the spatial raster model is obtained. For each spatial raster, Getis-Ord Git is executed in the geographic information system software. Spatial statistics calculate the local clustering statistics of a spatial raster within its spatial neighborhood, thereby obtaining the local clustering statistics of all spatial rasters in the spatial raster model. .

[0108] Furthermore, based on the local clustering statistics, the expected value of the local clustering statistics, and the coefficient of variation of the local clustering statistics, the Z score of each spatial grid is calculated. High-value clustering areas are selected as PM2.5 pollution source hotspot grids based on the condition that the Z score is greater than a preset score threshold (e.g., Z>1.65, representing a significance level of 95%).

[0109] Further screening of the identified PM2.5 pollution source hotspot grids yields the PM2.5 pollution source core areas outside the non-core areas, which are then used to construct a spatial distribution map of PM2.5 pollution sources.

[0110] In one embodiment, for each spatial grid, the formula for calculating the local clustering statistics of each spatial grid based on the PM2.5 grid concentration data of each spatial grid in the spatial grid model is as follows:

[0111] ;

[0112] in, For spatial grid Local clustering statistics; For spatial grid The number of grid cells within the spatial neighborhood; For spatial grid With spatial grid The spatial weights between them are based on the spatial grid. With spatial grid The distance between them is determined; For spatial grid PM2.5 grid concentration data.

[0113] In one embodiment, for each spatial grid, the calculation formula for determining the PM2.5 pollution source hotspot grid based on the local clustering statistics, their expected value, and coefficient of variation is as follows:

[0114] ;

[0115] in, For spatial grid Z-score; For spatial grid Local clustering statistics; For spatial grid The mathematical expectation of the local clustering statistics; For spatial grid The coefficient of variation of the local cluster statistics.

[0116] When the Z-value of a spatial grid is greater than 1.65, it is a hot spot and the spatial grid is identified as a PM2.5 pollution source hot spot grid; when the Z-value of a spatial grid is between -1.65 and 1.65, the result is not statistically significant; when the Z-value of a spatial grid is less than -1.65, it is a cold spot.

[0117] The ecological network construction method with spatial dust retention function provided by this invention constructs a PM2.5 pollution source spatial distribution map by selecting PM2.5 pollution source hotspot grids after obtaining PM2.5 grid concentration data of spatial grids by calculating local aggregation statistics and Z scores. This method can more accurately identify PM2.5 pollution sources required for constructing PM2.5 diffusion control ecological network and improve the speed of ecological network construction.

[0118] Based on the above embodiments, as an optional embodiment, determining the core area of ​​PM2.5 pollution sources based on the PM2.5 pollution source hotspot grid includes:

[0119] The PM2.5 pollution source hotspot grid is overlaid with the binary image of the built-up land to generate a potential pollution source mask layer;

[0120] Morphological spatial pattern analysis was performed on the potential pollution source mask layer, and the core area of ​​the PM2.5 pollution source was determined based on the topological connectivity of the spatial grid and the overall structural spatial geometric relationship.

[0121] Among them, the binary image of building land is a binary image in which the building-covered area is assigned the value of "foreground" (e.g., 1) and the other non-building areas are assigned the value of "background" (e.g., 0) at the raster level.

[0122] Specifically, after filtering PM2.5 pollution source hotspot grids based on local cluster statistics and Z-scores, the PM2.5 pollution source hotspot grids are spatially overlaid with the binary image of built-up land to generate a potential pollution source mask layer.

[0123] Further utilizing morphological spatial pattern analysis tools such as Guidos Toolbox, morphological spatial pattern analysis (MSPA) was performed on the potential pollution source mask layer with a preset edge width such as 3 pixels. This included, but was not limited to, performing standard morphological processing procedures such as erosion, dilation, opening, and closing operations in sequence to obtain a clearly structured raster spatial image. Based on the clearly structured raster spatial image, the morphological spatial pattern analysis tool automatically divided the spatial raster into six non-core regions and a core region according to the topological connectivity and overall structural spatial geometric relationship, including edge, bridge, perforation, islet, loop, and branch regions. A total of seven non-overlapping pattern types were identified.

[0124] A core area was selected as the PM2.5 pollution source core area. The area and PM2.5 concentration data of each spatial grid within the PM2.5 pollution source core area were linearly normalized and assigned equally weighted scores to obtain the coverage area and PM2.5 concentration. Adjacent core areas were merged within a preset proximity range. If multiple PM2.5 pollution source core areas were close to each other within a preset proximity range (e.g., 1 km), they could be merged into a single area, and the vector boundary of the single PM2.5 pollution source core area was determined. Finally, the vector boundary, spatial location (the geographical location of the corresponding treatment area of ​​the PM2.5 pollution source core area), coverage area, and PM2.5 concentration were used as attributes of the PM2.5 pollution source core area to construct a spatial distribution map of PM2.5 pollution sources.

[0125] Furthermore, after morphological spatial pattern analysis, the core area of ​​the same PM2.5 pollution source can include more than one spatial grid. In this case, the PM2.5 concentration in the attributes of the core area of ​​the same PM2.5 pollution source is the mean of the PM2.5 grid concentration data of each spatial grid in the core area of ​​the PM2.5 pollution source.

[0126] Optionally, after constructing the spatial distribution map of PM2.5 pollution sources, the method further includes: calculating the centrality (current value) of each PM2.5 pollution source based on Linkage Mapper. The higher the centrality value, the more important the PM2.5 pollution source is to maintain the overall connectivity of the ecological network corresponding to the PM2.5 control area; and automatically classifying the centrality value to obtain the importance level using the natural breakpoint method in the geographic information system software, and using the importance level as the attribute output of the core area of ​​PM2.5 pollution sources in the spatial distribution map of PM2.5 pollution sources, so as to provide source area input for the subsequent construction of the ecological network.

[0127] The ecological network construction method with spatial dust retention function provided by this invention, after screening PM2.5 pollution source hotspot grids by calculating local aggregation statistics and Z-scores, further extracts the core area of ​​PM2.5 pollution sources and constructs a spatial distribution map of PM2.5 pollution sources by superimposing PM2.5 pollution source hotspot grids and binary images of built-up land for morphological spatial pattern analysis. This can further improve the accuracy of identifying PM2.5 pollution sources required for constructing a PM2.5 diffusion control ecological network and increase the construction speed of the PM2.5 diffusion control ecological network.

[0128] In another embodiment, the method for constructing an ecological network with spatial dust retention function further includes: deploying a visualization and interactive module on a WebGIS or desktop management terminal, wherein the visualization and interactive interface in the module displays a spatial distribution map of PM2.5 pollution sources, a comprehensive resistance surface for PM2.5 diffusion, and PM2.5 diffusion corridors; receiving and responding to real-time query inputs from users (such as clients viewing the attributes, monitoring status, and suggested strategies of each node through layer queries and parameter retrieval), and displaying real-time query results on the visualization and interactive interface to meet both research and control needs.

[0129] In another embodiment, the method for constructing an ecological network with spatial dust retention function further includes: establishing a layer management and attribute refresh mechanism to support periodic updates of system data such as node index changes, resistance surface trends and network connectivity efficiency, forming a closed-loop ecological assessment system.

[0130] To better illustrate the overall process of the ecological network construction method with spatial dust retention function provided by the present invention, an embodiment is provided below for detailed description.

[0131] Figure 2 This is the second flowchart illustrating the method for constructing an ecological network with spatial dust retention function provided by the present invention. Figure 2 As shown, the method for constructing an ecological network with spatial dust retention function mainly includes four steps: PM2.5 pollution source identification, PM2.5 diffusion comprehensive resistance surface construction, diffusion path simulation and key node identification, and ecological network construction and ecological intervention strategy formulation.

[0132] Before performing the PM2.5 pollution source identification step, the data access module automatically collects or retrieves data from a remote database and dynamically updates basic heterogeneous data, including multi-temporal PM2.5 grid concentration data, land use classification maps, vegetation coverage, road density, and nighttime light index. The basic heterogeneous data is then imported in batches and standardized and resampled to ensure the timeliness and spatial consistency of the input data.

[0133] In the PM2.5 pollution source identification process, firstly, multi-temporal PM2.5 concentration data of the spatial raster model corresponding to the PM2.5 treatment area are acquired. The PM2.5 concentration data is then resampled and used as the PM2.5 raster concentration data of the spatial raster. When there are anomalies in PM2.5 residential sources and / or PM2.5 production sources at different times (where only residential activities exist while production activities cease at a certain time), the PM2.5 concentration difference is obtained by subtracting the PM2.5 raster concentration data of the next period pixel by pixel from the PM2.5 raster concentration data of the current period. The PM2.5 concentration difference with a positive value is retained as the PM2.5 raster concentration data, accurately classifying residential and production sources to obtain PM2.5 raster concentration data stripped of abnormal PM2.5 residential sources or PM2.5 production sources.

[0134] Further development of Getis-Ord Gi Spatial analysis utilizes PM2.5 concentration data from each spatial raster model to calculate the local clustering statistics for each raster. Based on these statistics, their expected value, and coefficient of variation, the Z-score is calculated to identify PM2.5 pollution source hotspots. Building upon these potential PM2.5 pollution source hotspots, a binary image of built-up land (building map layer) is overlaid to generate a potential pollution source mask layer. This mask layer is then refined based on morphological spatial pattern analysis. By considering the topological connectivity and overall structural spatial geometry of the spatial raster, the core PM2.5 pollution source areas are identified. Finally, a spatial distribution map of PM2.5 pollution sources is determined based on these core areas, enabling precise identification of PM2.5 pollution sources.

[0135] In the process of constructing the comprehensive resistance surface for PM2.5 diffusion, land use, vegetation cover, road density, and nighttime light index are unified into a resistance grid that characterizes the intensity of PM2.5 diffusion obstruction. Specifically, firstly, the basic PM2.5 diffusion resistance coefficients of spatial grids with different use types are set using expert weighting. Then, fuzzy membership functions are used to generate landscape correction factors for road density, nighttime light index, and vegetation cover. Next, the basic PM2.5 diffusion resistance coefficients of each spatial grid are corrected by pixel-level weighted superposition using three landscape correction factors: vegetation cover factor, road density factor, and nighttime light index factor. Using the corrected PM2.5 diffusion resistance coefficients, the comprehensive resistance surface for PM2.5 diffusion, which characterizes the ease of PM2.5 particle propagation and the degree of diffusion obstruction, is determined.

[0136] In the diffusion path simulation and key node identification steps, the grid cost is determined based on the PM2.5 diffusion comprehensive resistance surface. The cumulative cost distance of the PM2.5 pollution source grid is calculated using the minimum cumulative cost analysis (MCR) algorithm. The current distribution calculation based on circuit theory is performed using the Circuitscape current field model or the Linkage Mapper software interface. Based on the cumulative cost distance, the multi-path and superposition effects of PM2.5 diffusion are simulated, and a set of PM2.5 diffusion paths for pollution diffusion is constructed. After merging the PM2.5 diffusion paths in the set of PM2.5 diffusion paths, PM2.5 diffusion corridors are obtained to extract continuous high-current diffusion corridors under multi-source flow, forming the diffusion pathway skeleton.

[0137] After obtaining the PM2.5 diffusion corridors, on the one hand, based on the PM2.5 diffusion corridors and the spatial distribution map of PM2.5 pollution sources, key element mapping tools are used to quantitatively screen key control nodes such as floating dust nodes and stagnant dust nodes. This includes: using Centrality Mapper to calculate the centrality of each PM2.5 pollution source grid, sorting the PM2.5 pollution source grids according to their centrality, and identifying the PM2.5 pollution source grids with the highest centrality or greater than the preset centrality threshold as key pollution source nodes; using Pinchpoint Mapper to perform local search in the corridor current density map corresponding to the PM2.5 diffusion corridor, identifying "transfer nodes" that are conducive to the diffusion of PM2.5 pollutants between PM2.5 pollution source grids as floating dust nodes; and using Barrier Mapper to simulate the rate of change of the overall effective resistance (or total current) of the network after the PM2.5 pollution source grids or PM2.5 diffusion paths are blocked to quantify the node blocking effect, and then identifying the nodes that have the greatest impact on the overall connectivity as stagnant dust nodes. On the other hand, by superimposing the PM2.5 diffusion corridor and the PM2.5 diffusion comprehensive resistance surface, the intersection of the resistance peak and the PM2.5 diffusion corridor is identified as a potential dust retention node (i.e., a potential node).

[0138] In the steps of ecological network construction and ecological intervention strategy formulation, ecological red lines are delineated according to the functional levels of nodes, vegetation restoration is implemented, and a proactive barrier-type ecological network is constructed, laying the foundation for refined ecological intervention design. Specifically, for dust-trapping nodes, ecological control boundaries are delineated with the grid centroid of the dust-trapping node as the geometric center; for potential dust-trapping nodes, graded vegetation restoration plans are formulated based on vegetation coverage factors, bare land rate factors, soil condition factors, and transformation feasibility factors of potential dust-trapping nodes.

[0139] After delineating ecological control boundaries and / or formulating and implementing graded vegetation restoration plans, a remote sensing-ground joint monitoring system is constructed to regularly assess key indicators such as changes in vegetation cover, measured PM2.5 concentration (through air quality monitoring equipment), and leaf particle deposition (through leaf sampling and analysis) at dust-trapping nodes and potential dust-trapping nodes. This ensures that the blocking capacity of the ecological network continues to improve during the operation period and that dust-trapping nodes and potential dust-trapping nodes are maintained in the optimal ecological blocking state in the long term.

[0140] Overall, the ecological network construction method with spatial dust retention function provided by this invention consists of four steps: PM2.5 pollution source identification, PM2.5 diffusion comprehensive resistance surface construction, diffusion path simulation and key node identification, and ecological network construction and ecological intervention strategy formulation. This method accurately identifies pollution sources and high-risk diffusion paths, constructs a resistance model reflecting landscape heterogeneity, extracts key node locations, and formulates differentiated ecological control measures based on their functional differences. This forms an ecological network system with active blocking effectiveness, achieving precise blocking of high-risk PM2.5 diffusion channels and enhancing the dust retention efficiency of key nodes. It promotes the coordinated optimization of air quality and ecological space in urban agglomerations, completing the entire process of spatial blocking-oriented ecological network construction and dust retention function enhancement, providing strong support for the active blocking of urban air pollution and refined ecological space management.

[0141] Figure 3 This is a schematic diagram of the ecological network construction device with spatial dust retention function provided by the present invention, as shown below. Figure 3 As shown, the ecological network construction device with spatial dust retention function includes, but is not limited to, a source distribution map acquisition module 301, a diffusion resistance surface acquisition module 302, a diffusion corridor acquisition module 303, and a network construction module 304.

[0142] The source distribution map acquisition module 301 is used to acquire the spatial distribution map of PM2.5 pollution sources.

[0143] The diffusion resistance surface acquisition module 302 is used to correct the basic PM2.5 diffusion resistance coefficient of each spatial grid in the spatial grid model based on the landscape correction factor, so as to obtain the comprehensive PM2.5 diffusion resistance surface; the basic PM2.5 diffusion resistance coefficient is determined based on the land use type of the spatial grid and its hindering effect on PM2.5 diffusion.

[0144] The diffusion corridor acquisition module 303 is used to perform minimum cumulative cost analysis and current distribution calculation based on circuit theory based on the PM2.5 pollution source spatial distribution map and the PM2.5 diffusion comprehensive resistance surface to obtain PM2.5 diffusion corridors.

[0145] The network construction module 304 is used to identify and analyze key control nodes based on the PM2.5 diffusion corridor to obtain key control nodes and construct a PM2.5 diffusion control ecological network.

[0146] It should be noted that the ecological network construction device with spatial dust retention function provided by the present invention can execute the ecological network construction method with spatial dust retention function described in any of the above embodiments during specific operation, and will not be elaborated on in this embodiment.

[0147] The ecological network construction device with spatial dust retention function provided by this invention focuses on PM2.5 pollutant diffusion as the key point of ecological network construction. It considers the systematic blocking effect of regional landscape continuum on air pollutants, uses landscape correction factors to correct the effect coefficient of land use type on PM2.5 diffusion, and obtains the comprehensive resistance surface of PM2.5 diffusion that integrates the influence of landscape on PM2.5 diffusion. By using the comprehensive resistance surface of PM2.5 diffusion and the spatial distribution map of PM2.5 pollution sources to perform minimum cumulative cost analysis and current distribution calculation based on circuit theory, PM2.5 diffusion corridors are obtained. Key control nodes are identified to construct a PM2.5 diffusion control ecological network, which improves the accuracy of corridor identification and the quantification accuracy of key nodes. It realizes a systematic PM2.5 diffusion control ecological network construction scheme that integrates the source-corridor-node morphology of landscape ecology.

[0148] Figure 4 This is a schematic diagram of the structure of the electronic device provided by the present invention, such as... Figure 4As shown, the electronic device may include: a processor 410, a communications interface 420, a memory 430, and a communications bus 440, wherein the processor 410, the communications interface 420, and the memory 430 communicate with each other through the communications bus 440. The processor 410 can call logic instructions in the memory 430 to execute the ecological network construction method with spatial dust retention function provided in any of the above embodiments. The ecological network construction method with spatial dust retention function includes, but is not limited to, the following steps: obtaining a spatial distribution map of PM2.5 pollution sources; correcting the basic PM2.5 diffusion resistance coefficient of each spatial grid in the spatial grid model based on the landscape correction factor to obtain a comprehensive PM2.5 diffusion resistance surface; the basic PM2.5 diffusion resistance coefficient is determined based on the land use type of the spatial grid and its hindering effect on PM2.5 diffusion; performing minimum cumulative cost analysis and current distribution calculation based on circuit theory based on the spatial distribution map of PM2.5 pollution sources and the comprehensive PM2.5 diffusion resistance surface to obtain PM2.5 diffusion corridors; and performing key control node identification analysis based on the PM2.5 diffusion corridors to obtain key control nodes, thereby constructing a PM2.5 diffusion control ecological network.

[0149] Furthermore, the logical instructions in the aforementioned memory 430 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, essentially, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0150] On the other hand, the present invention also provides a computer program product, which includes a computer program that can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the ecological network construction method with spatial dust retention function provided in any of the above embodiments. The ecological network construction method with spatial dust retention function includes, but is not limited to, the following steps: obtaining a spatial distribution map of PM2.5 pollution sources; correcting the basic PM2.5 diffusion resistance coefficient of each spatial grid in the spatial grid model based on a landscape correction factor to obtain a comprehensive PM2.5 diffusion resistance surface; the basic PM2.5 diffusion resistance coefficient is determined based on the land use type of the spatial grid and its hindering effect on PM2.5 diffusion; performing minimum cumulative cost analysis and current distribution calculation based on circuit theory based on the PM2.5 pollution source spatial distribution map and the comprehensive PM2.5 diffusion resistance surface to obtain PM2.5 diffusion corridors; and performing key control node identification analysis based on the PM2.5 diffusion corridors to obtain key control nodes, thereby constructing a PM2.5 diffusion control ecological network.

[0151] In another aspect, the present invention also provides a non-transitory computer-readable storage medium storing a computer program thereon. When executed by a processor, the computer program implements the method for constructing an ecological network with spatial dust retention function provided in any of the above embodiments. The method for constructing an ecological network with spatial dust retention function includes, but is not limited to, the following steps: obtaining a spatial distribution map of PM2.5 pollution sources; correcting the basic PM2.5 diffusion resistance coefficient of each spatial grid in the spatial grid model based on a landscape correction factor to obtain a comprehensive PM2.5 diffusion resistance surface; the basic PM2.5 diffusion resistance coefficient is determined based on the land use type of the spatial grid and its hindering effect on PM2.5 diffusion; performing minimum cumulative cost analysis and current distribution calculation based on circuit theory based on the spatial distribution map of PM2.5 pollution sources and the comprehensive PM2.5 diffusion resistance surface to obtain PM2.5 diffusion corridors; and performing key control node identification analysis based on the PM2.5 diffusion corridors to obtain key control nodes, thereby constructing a PM2.5 diffusion control ecological network.

[0152] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0153] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0154] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for constructing an ecological network with spatial dust retention function, characterized in that, include: Obtain a spatial distribution map of PM2.5 pollution sources; Based on the landscape correction factor, the basic PM2.5 diffusion resistance coefficient of each spatial grid in the spatial grid model is corrected to obtain the comprehensive PM2.5 diffusion resistance surface; the basic PM2.5 diffusion resistance coefficient is determined based on the hindering effect of land use type of the spatial grid on PM2.5 diffusion; Based on the spatial distribution map of PM2.5 pollution sources and the comprehensive resistance surface of PM2.5 diffusion, minimum cumulative cost analysis and current distribution calculation based on circuit theory are performed to obtain PM2.5 diffusion corridors; Based on the PM2.5 diffusion corridor, key control nodes are identified and analyzed to construct a PM2.5 diffusion control ecological network. This includes: identifying key pollution source nodes, dust nodes, and dust retention nodes using key element mapping tools based on the PM2.5 diffusion corridor and the PM2.5 pollution source spatial distribution map; overlaying the PM2.5 diffusion corridor and the PM2.5 diffusion comprehensive resistance surface, and determining the intersection of the resistance peak and the PM2.5 diffusion corridor as potential dust retention nodes; and constructing the PM2.5 diffusion control ecological network based on the key pollution source nodes, dust nodes, dust retention nodes, and potential dust retention nodes. The method of correcting the basic PM2.5 diffusion resistance coefficient of each spatial grid in the spatial grid model based on landscape correction factors to obtain the comprehensive PM2.5 diffusion resistance surface includes: correcting the basic PM2.5 diffusion resistance coefficient of each spatial grid in the spatial grid model based on vegetation coverage factor, road density factor, and nighttime light index factor to obtain the comprehensive PM2.5 diffusion resistance surface; the vegetation coverage factor is determined according to the membership degree of vegetation coverage in the land use type; the road density factor is determined according to the membership degree of road density in the land use type; and the nighttime light index factor is determined according to the membership degree of nighttime light index in the land use type.

2. The method for constructing an ecological network with spatial dust retention function according to claim 1, characterized in that, Based on the spatial distribution map of PM2.5 pollution sources and the comprehensive resistance surface for PM2.5 diffusion, minimum cumulative cost analysis and current distribution calculations based on circuit theory are performed to obtain PM2.5 diffusion corridors, including: Based on the comprehensive resistance surface for PM2.5 diffusion, the grid cost of the spatial grid model is determined. For each PM2.5 pollution source grid in the spatial distribution map of PM2.5 pollution sources, the cumulative cost distance of the PM2.5 pollution source grid is calculated based on the grid cost of the PM2.5 pollution source grid and the grid distance between the PM2.5 pollution source grid and other spatial grids outside the PM2.5 pollution source grid, so as to obtain the cumulative cost distance of all PM2.5 pollution source grids in the spatial distribution map of PM2.5 pollution sources; By using current distribution calculations based on circuit theory, and simulating the multipath and superposition effects of PM2.5 diffusion based on the cumulative cost distance, multiple PM2.5 diffusion paths are obtained; The PM2.5 diffusion path is vectorized and merged to obtain the PM2.5 diffusion corridor.

3. The method for constructing an ecological network with spatial dust retention function according to claim 1, characterized in that, After identifying and analyzing key control nodes based on the PM2.5 diffusion corridor to construct a PM2.5 diffusion control ecological network, the process further includes: For the dust-trapping nodes, the ecological control boundary is delineated with the grid centroid of the dust-trapping nodes as the geometric center; For the potential dust-trapping nodes, a graded vegetation restoration plan is formulated based on the vegetation coverage rate factor, bare land rate factor, soil condition factor, and transformation feasibility factor of the potential dust-trapping nodes.

4. The method for constructing an ecological network with spatial dust retention function according to claim 1, characterized in that, The acquisition of the spatial distribution map of PM2.5 pollution sources includes: Based on the PM2.5 grid concentration data of each spatial grid in the spatial grid model, the local clustering statistics of each spatial grid are calculated; Based on the local cluster statistics, their expected values, and coefficients of variation, a PM2.5 pollution source hotspot grid is determined. Based on the aforementioned PM2.5 pollution source hotspot grid, the core area of ​​PM2.5 pollution sources is determined; Based on the core area of ​​the PM2.5 pollution source, a spatial distribution map of the PM2.5 pollution source is constructed.

5. The method for constructing an ecological network with spatial dust retention function according to claim 4, characterized in that, The determination of the core area of ​​PM2.5 pollution sources based on the PM2.5 pollution source hotspot grid includes: The PM2.5 pollution source hotspot grid is overlaid with the binary image of the built-up land to generate a potential pollution source mask layer; Morphological spatial pattern analysis was performed on the potential pollution source mask layer, and the core area of ​​the PM2.5 pollution source was determined based on the topological connectivity of the spatial grid and the overall structural spatial geometric relationship.

6. An ecological network construction device with spatial dust retention function, characterized in that, include: The source distribution map acquisition module is used to acquire the spatial distribution map of PM2.5 pollution sources; The diffusion resistance surface acquisition module is used to correct the basic PM2.5 diffusion resistance coefficient of each spatial grid in the spatial grid model based on the landscape correction factor, so as to obtain the comprehensive PM2.5 diffusion resistance surface; the basic PM2.5 diffusion resistance coefficient is determined based on the land use type of the spatial grid and its hindering effect on PM2.5 diffusion; The diffusion corridor acquisition module is used to perform minimum cumulative cost analysis and current distribution calculation based on circuit theory, based on the PM2.5 pollution source spatial distribution map and the PM2.5 diffusion comprehensive resistance surface, to obtain the PM2.5 diffusion corridor; The network construction module is used to identify and analyze key control nodes based on the PM2.5 diffusion corridor to obtain key control nodes and construct a PM2.5 diffusion control ecological network. This includes: identifying key pollution source nodes, dust nodes, and dust retention nodes using a key element mapping tool based on the PM2.5 diffusion corridor and the PM2.5 pollution source spatial distribution map; overlaying the PM2.5 diffusion corridor and the PM2.5 diffusion comprehensive resistance surface, and determining the intersection of the resistance peak and the PM2.5 diffusion corridor as potential dust retention nodes; and constructing the PM2.5 diffusion control ecological network based on the key pollution source nodes, dust nodes, dust retention nodes, and potential dust retention nodes. The method of correcting the basic PM2.5 diffusion resistance coefficient of each spatial grid in the spatial grid model based on landscape correction factors to obtain the comprehensive PM2.5 diffusion resistance surface includes: correcting the basic PM2.5 diffusion resistance coefficient of each spatial grid in the spatial grid model based on vegetation coverage factor, road density factor, and nighttime light index factor to obtain the comprehensive PM2.5 diffusion resistance surface; the vegetation coverage factor is determined according to the membership degree of vegetation coverage in the land use type; the road density factor is determined according to the membership degree of road density in the land use type; and the nighttime light index factor is determined according to the membership degree of nighttime light index in the land use type.

7. An electronic device comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that, When the processor executes the computer program, it implements the ecological network construction method with spatial dust retention function as described in any one of claims 1 to 5.

8. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the ecological network construction method with spatial dust retention function as described in any one of claims 1 to 5.

9. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, it implements the ecological network construction method with spatial dust retention function as described in any one of claims 1 to 5.

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