A method and system for constructing a pollution and carbon reduction coordinated atmospheric security pattern

Abstract

The present application relates to the technical field of ecological data fusion, and more particularly to a pollution and carbon reduction collaborative atmospheric safety pattern construction method and system, comprising: identifying ecological sources of target regions based on multi-source remote sensing data and grading; constructing a comprehensive ventilation resistance surface based on the surface roughness, vegetation roughness and water roughness of the target region, and dividing the resistance levels of the comprehensive ventilation resistance surface based on the spatial game characteristics of the ecological land and construction land in the target region; extracting ventilation corridors and ecological corridors, and setting the widths of the ventilation corridors and ecological corridors respectively; superimposing and analyzing the ecological source grading results, the comprehensive ventilation resistance surface resistance level division results, the paths and widths of the ventilation corridors and the paths and widths of the ecological corridors to construct the safety pattern results of the target region. The present application makes up for the shortcomings of the existing ecological safety pattern content and improves the construction accuracy of the atmospheric safety pattern.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of ecological data fusion, and in particular to a pollution-reducing and carbon-reducing collaborative atmospheric safety pattern construction method and system. BACKGROUND

[0002] In recent years, ecological safety has gradually become a hot topic in international ecosystem research, and it is also an important direction to promote the sustainable development of human society. With the continuous deepening of theoretical exploration and practical application, the ecological safety pattern has been widely recognized as a key tool to coordinate the contradiction between urban space expansion and ecological protection, and to promote the ecological management strategy from traditional end-of-pipe management to more forward-looking systematic management. The research in this field has further promoted the direction of refinement and diversification, and many scholars have focused on specific ecological elements such as water safety, forest safety and land safety, and have constructed an ecological safety evaluation and spatial optimization framework in multiple sub-fields, marking that the ecological safety research has entered a development stage of systematic and accurate.

[0003] At present, although the research on ecological safety pattern has made significant progress, there is still a significant research lag in the aspect of atmosphere, a key natural element. As a basic carrier to maintain the ecological balance and life support of the earth, the atmosphere not only bears the functions of gas circulation and climate regulation, but also plays an important role in alleviating acid rain, floods, droughts and extreme climate events. The existing ecological safety pattern construction is mostly focused on visible surface resources, and lacks systematic and spatial modeling of atmospheric environment. The atmosphere safety is not included in the unified spatial pattern system, especially in dealing with cross-regional, multi-dimensional and complex atmospheric environmental problems, the current technical means is difficult to realize the collaborative control of pollution reduction and carbon reduction, and cannot meet the refined and regional collaborative ecological management needs of the atmosphere, thereby restricting the overall progress of ecological civilization construction at the macro level. SUMMARY

[0004] The present application is to overcome the defects of the above-mentioned prior art lacking of global perspective support, and provides a pollution-reducing and carbon-reducing collaborative atmospheric safety pattern construction method and system.

[0005] To solve the above technical problems, the technical solutions of the present application are as follows:

[0006] A pollution-reducing and carbon-reducing collaborative atmospheric safety pattern construction method, comprising:

[0007] Identifying the ecological source of the target region based on multi-source remote sensing data, and classifying the ecological source through the landscape connectivity index of the ecological source;

[0008] constructing a comprehensive ventilation resistance surface based on ground surface roughness, vegetation roughness and water roughness in the target region, wherein the ground surface roughness is calculated by a windward area density model, and the vegetation roughness and water roughness are respectively represented by a normalized difference vegetation index and a normalized difference water index; and dividing the comprehensive ventilation resistance surface into resistance grades based on spatial game characteristics of ecological land and construction land in the target region;

[0009] extracting ventilation corridors based on the comprehensive ventilation resistance surface, and extracting ecological corridors based on ecological expansion resistance of the target region, and setting widths of the ventilation corridors and the ecological corridors respectively;

[0010] constructing a safety pattern result of the target region based on the hierarchical results of the ecological source, the resistance grade division results of the comprehensive ventilation resistance surface, the paths and widths of the ventilation corridors, and the paths and widths of the ecological corridors.

[0011] As a preferred solution, the step of identifying the ecological source of the target region based on multi-source remote sensing data comprises:

[0012] identifying land classification through remote sensing data;

[0013] determining ecological source candidate areas through morphological spatial pattern analysis based on the classification results;

[0014] collecting vegetation structure parameters in the ecological source candidate areas, and inverting plant chemical components based on spectral data;

[0015] calculating carbon fixation and pollution sinking efficiency based on the vegetation structure parameters and the plant chemical components;

[0016] calculating carbon storage based on the carbon fixation and pollution sinking efficiency, and taking ecological source candidate areas with carbon storage greater than a preset threshold as ecological sources.

[0017] As a preferred solution, the calculation of the ground surface roughness specifically comprises:

[0018] extracting building planar layout and height data to generate a normalized digital surface model;

[0019] constructing a 3D ground surface model based on fused terrain relief data;

[0020] obtaining a ground surface roughness resistance surface by weighted superposition according to actual wind frequency based on FAD calculation results of different wind directions.

[0021] As a preferred solution, the normalized difference vegetation index is calculated based on an infrared band, and the calculation formula is as follows:

[0022]

[0023] wherein, represents a reflection value of a near-infrared band, reflectance value of the red light band;

[0024] The normalized difference water body index is calculated based on the green light band and the infrared band, and the calculation formula is as follows:

[0025]

[0026] wherein, reflectance value of the green light band, reflectance value of the mid-infrared band.

[0027] As a preferred solution, the microclimate correction factor is also introduced when calculating the carbon storage; the calculation formula for calculating the carbon storage is as follows:

[0028]

[0029]

[0030] wherein, carbon storage of the ecosystem type at the moment of t ; i is the baseline value, which is the biomass inverted by LIDAR multiplied by the carbon content coefficient; is a remote sensing correction factor, which is used to correct the normalized difference vegetation index at different time points to improve the accuracy of carbon storage estimation; is a microclimate correction factor, which considers the influence of temperature T and humidity H on vegetation growth and carbon storage; is the carbon fixation and deposition efficiency of plants.

[0031] As a preferred solution, the step of constructing the comprehensive ventilation resistance surface comprises:

[0032] Calculate the spatial heterogeneity index and landscape type consistency index of different roughness at the corresponding spatial scale;

[0033] Based on the spatial heterogeneity index and the landscape type consistency index, dynamic weight distribution is carried out in combination with the preset global reference weight;

[0034] Based on the distributed weight, different roughness is weighted and superimposed to obtain a comprehensive ventilation resistance coefficient, and based on the comprehensive ventilation resistance coefficient, a comprehensive ventilation resistance value is calculated, and based on the comprehensive ventilation resistance value, a comprehensive ventilation resistance surface is constructed; the calculation formula of the comprehensive ventilation resistance value is as follows:

[0035]

[0036]

[0037] wherein, ​is a corrected ecological expansion grid resistance value; is an uncorrected minimum cumulative ecological expansion resistance value; is a grid is a ventilation resistance coefficient at a grid is a grid is an average ventilation resistance coefficient corresponding to a land type; is a corrected urban expansion grid resistance value.

[0038] As a preferred solution, the ventilation corridor is generated based on a GIS minimum cost path algorithm and coupled with WRF wind field simulation data, and the width is determined based on an adaptive threshold; the ecological corridor is identified based on a minimum cost path, the width is determined by calculating the proportion of different land use types and different corridors, and is graded based on a possible connectivity index.

[0039] As a preferred solution, the step of dividing resistance levels of the comprehensive ventilation resistance surface based on the spatial game characteristics of ecological land and construction land in the target region comprises:

[0040] a difference between a minimum cumulative resistance surface of ecological land expansion and a minimum cumulative resistance surface of construction land expansion;

[0041] According to the numerical statistical distribution characteristics of the difference, a mutation threshold for dividing the level interval is determined based on the distribution characteristics;

[0042] The comprehensive ventilation resistance surface is divided by difference based on the mutation threshold.

[0043] As a preferred solution, the step of constructing a safety pattern result of the target region comprises: taking the protection level requirement of the highest safety pattern level of the ecological source land grading result, the comprehensive ventilation resistance surface resistance level division result, the path and width of the ventilation corridor, and the path and width of the ecological corridor as the safety pattern result.

[0044] The present application also proposes an atmospheric safety pattern construction system, the system comprises:

[0045] An ecological source land identification and grading module identifies ecological source land of a target region based on multi-source remote sensing data, and grades the ecological source land through a landscape connectivity index of the ecological source land;

[0046] A ventilation resistance surface construction and grading module is used to construct a comprehensive ventilation resistance surface by comprehensively considering ground surface roughness, vegetation roughness and water roughness, and to grade the comprehensive ventilation resistance surface;

[0047] A corridor extraction and processing module extracts a ventilation corridor based on the comprehensive ventilation resistance surface, and extracts an ecological corridor based on ecological expansion resistance of the target region, and sets the width of the ventilation corridor and the ecological corridor respectively;

[0048] A pattern construction and output module is configured to perform spatial superposition analysis on the graded ecological source, the comprehensive ventilation resistance surface, and the graded ventilation corridor and ecological corridor, and to construct and output a multi-level atmospheric safety pattern.

[0049] Compared with the prior art, the beneficial effects of the technical scheme of the present application are as follows:

[0050] The present application dynamically integrates "atmospheric safety" as a core element into the construction of an ecological safety pattern, uses multi-source data acquisition and comprehensive processing technology to break through the technical bottleneck of original single macro remote sensing image identification in the source identification link, adds the roughness of atmospheric property vegetation and water area to the original construction principle of the ecological safety resistance surface in the resistance surface construction link, constructs a ventilation resistance surface with atmospheric ventilation cooling significance, adds an atmospheric feature ventilation corridor to the existing ecological corridor in the corridor extraction link to form a natural corridor system under the goal of pollution reduction and carbon reduction, and adds the game thinking of ecological land and construction land in the atmospheric safety pattern construction link, positions the mutation interval of ecology and construction based on statistics, and effectively improves the accuracy of the construction of the atmospheric safety pattern. BRIEF DESCRIPTION OF DRAWINGS

[0051] Figure 1 It is a flowchart of the pollution reduction and carbon reduction collaborative atmospheric safety pattern construction method of embodiment 1.

[0052] Figure 2 It is a minimum resistance difference distribution map of ecological expansion and urban expansion of embodiment 1.

[0053] Figure 3 It is a system architecture diagram of the atmospheric safety pattern construction of embodiment 2. DETAILED DESCRIPTION

[0054] The drawings are only used for illustrative description and cannot be understood as a limitation on the patent;

[0055] In order to better illustrate the present embodiment, some parts of the drawings may be omitted, enlarged or reduced, and do not represent the size of the actual product;

[0056] For those skilled in the art, it is understandable that some well-known structures and their descriptions in the drawings may be omitted.

[0057] The technical scheme of the present application will be further described below in combination with the drawings and embodiments.

[0058] Embodiment 1

[0059] A pollution reduction and carbon reduction collaborative atmospheric safety pattern construction method proposed in the present embodiment, as shown in the figure, is a flowchart of the pollution reduction and carbon reduction collaborative atmospheric safety pattern construction method of the present embodiment. Figure 1 A pollution reduction and carbon reduction collaborative atmospheric safety pattern construction method proposed in the present embodiment, as shown in the figure, is a flowchart of the pollution reduction and carbon reduction collaborative atmospheric safety pattern construction method of the present embodiment.

[0060] A method for constructing a pollution-reducing and carbon-reducing collaborative atmospheric safety pattern, comprising:

[0061] S1, identifying an ecological source area of a target region based on multi-source remote sensing data, and grading the ecological source area through a landscape connectivity index of the ecological source area;

[0062] S2, constructing a comprehensive ventilation resistance surface based on the ground roughness, vegetation roughness and water roughness of the target region, wherein the ground roughness is calculated by a windward area density model, and the vegetation roughness and water roughness are respectively represented by a normalized vegetation index and a normalized difference water index; and dividing the resistance levels of the comprehensive ventilation resistance surface based on the spatial game characteristics of the ecological land and the construction land in the target region;

[0063] S3, extracting ventilation corridors based on the comprehensive ventilation resistance surface, and extracting ecological corridors based on the ecological expansion resistance of the target region, and setting the widths of the ventilation corridors and the ecological corridors respectively;

[0064] S4, superimposing and analyzing the results of the ecological source area grading, the results of the comprehensive ventilation resistance surface resistance level division, the paths and widths of the ventilation corridors, and the paths and widths of the ecological corridors, to construct a safety pattern result of the target region.

[0065] In this embodiment, the ecological source area is identified and graded by integrating multi-source data, a comprehensive ventilation resistance surface is constructed, ventilation and ecological corridors are extracted collaboratively, and finally a multi-level safety pattern is constructed through spatial superposition. A systematic and quantifiable technical framework is provided, which expands the traditional ecological safety pattern construction method focusing on biodiversity protection to the atmospheric environment field, realizes the spatial response and planning support for the collaborative goals of pollution reduction and carbon reduction, and provides a design tool for improving regional atmospheric environmental safety.

[0066] In an optional embodiment, the step of identifying the ecological source area of the target region based on multi-source remote sensing data comprises:

[0067] identifying land classification through remote sensing data;

[0068] determining ecological source area candidate regions through morphological spatial pattern analysis based on the classification results;

[0069] collecting vegetation structure parameters in the ecological source area candidate regions, and inversing plant chemical components based on spectral data;

[0070] calculating carbon sequestration and pollution reduction efficiency based on the vegetation structure parameters and the plant chemical components;

[0071] calculating carbon storage based on the carbon sequestration and pollution reduction efficiency, and taking the ecological source area candidate regions with carbon storage greater than a preset threshold as the ecological source area.

[0072] In this embodiment, by comprehensively using the multi-platform heterogeneous data of sky, space and earth, the limitation of single remote sensing data source is broken through, and stereoscopic and high-precision perception of multi-dimensional parameters such as ecological source carbon sink function is realized.

[0073] In an optional embodiment, a microclimate correction factor is introduced when calculating the carbon storage; and the calculation formula for calculating the carbon storage is as follows:

[0074]

[0075]

[0076] Wherein, represents the carbon storage of the ecosystem type t at the moment of i ; is a reference value, which is the biomass inverted by LIDAR multiplied by the carbon content coefficient; is a remote sensing correction factor, which is used to correct the difference of normalized vegetation index at different time points, so as to improve the accuracy of carbon storage estimation; is a microclimate correction factor, which considers the influence of temperature T and humidity H on vegetation growth and carbon storage; is the carbon fixation and deposition efficiency of plants.

[0077] More specifically, the calculation formula of ecological source area classification is as follows:

[0078]

[0079]

[0080] Wherein, PC represents the overall possible connectivity index of all patches in the landscape, PCremove , k represents the possible connectivity index of the remaining patches after removing patch k , represents the relative importance of patch k to the overall landscape connectivity; is the number of core areas; and are the areas of core areas and ; indicates the number of connections between patch and ; represents the total value of the landscape in the study area; 0≤ ≤1, =0, there is no connection between habitat patches; = 1, the whole landscape is habitat patch.

[0081] The higher the connectivity index of the ecological source patch, the more important the patch is. In this section, the ecological sources are divided into three categories: very important, relatively important, and generally important, by using the K-Means method to calculate the results of dPC and IIC.

[0082] In this embodiment, the extreme climate impact is considered by the microclimate correction factor, which improves the accuracy and reliability of the carbon storage estimation.

[0083] In an optional embodiment, the calculation of the surface roughness specifically includes:

[0084] Extract the building layout and height data to generate a normalized digital surface model;

[0085] Based on the fusion terrain relief data, a 3D surface model is constructed;

[0086] Based on the FAD calculation results of different wind directions, the surface roughness resistance surface is obtained by weighted superposition according to the actual wind frequency.

[0087] Further, the windward area density FAD is used to calculate the surface roughness, and the calculation formula is:

[0088]

[0089] wherein, is the windward area of the building perpendicular to a certain wind direction; is the area of the block where the building is located; is a selected direction; is the height increment.

[0090] And a grid calculation model is used to construct a 3D building model library in the study area.

[0091] As an example, the calculation steps are as follows:

[0092] Extraction of the form of building plan layout. Extract the vector data set of urban building roofs, and use the aggregation surface tool in ArcGIS to aggregate buildings with similar attributes. Use the AW3D30 global digital surface model data set to obtain building height from the panchromatic remote sensing stereoscopic survey instrument carried on the advanced land observation satellite.

[0093] In order to extract the building, the approximate value of the ground DEM needs to be determined to separate the non-ground objects from the ground. The difference between the original DSM and the approximate DEM is called normalized DSM (nDSM), which contains the height information of all non-ground objects, and its calculation formula is as follows:

[0094]

[0095] The DEM is generated by using the block minimum filtering method to obtain the minimum elevation in a certain area.

[0096] The The building plane roof coverage area is assigned to each building to separate the building from other objects. The average building height of a single building is calculated by using the zone statistics tool in ArcGIS software.

[0097] The mountain range is extracted, and the focus statistics tool in ArcGIS software is used to extract the mountain range and height data in combination with existing results experience and repeated threshold experiments.

[0098] Based on the above building height and urban terrain data superposition, the FAD of the buildings and terrain in the research range is calculated by importing the GIS plug-in FAD Tools. The FAD is calculated based on the tool:

[0099] ① The value of the height increment Z in the FAD calculation formula is determined: first, the above-mentioned 3D building database is processed by using the data statistics tool in ArcGIS software, and a building height distribution histogram is drawn.

[0100] ② The ground 3D database is imported into the FAD Tools for processing. The addition method of the plug-in is as shown in the FAD calculation results of the research range in 16 wind directions.

[0101] ③ The wind direction and frequency are calculated. The daily maximum and maximum wind direction and frequency of meteorological data are extracted and calculated by using the surface meteorological daily value data set. The final ground roughness resistance surface is obtained by weighted superposition of the 16 wind direction FAD according to the maximum wind speed and wind direction frequency of the whole year.

[0102] In an optional embodiment, the normalized vegetation index is calculated based on the infrared band, and the calculation formula is as follows:

[0103]

[0104] wherein, represents the reflection value of the near-infrared band, is the reflection value of the red light band;

[0105] The normalized difference water body index is calculated based on the green light band and the infrared band, and the calculation formula is as follows:

[0106]

[0107] wherein, represents the reflection value of the green light band, is the reflection value of the medium infrared band.

[0108] In this embodiment, the vegetation index and the water body index are used to construct the ventilation resistance surface, the key surface parameters of atmospheric fluid mechanics are integrated into the resistance model, and the resistance surface can not only reflect the migration cost in the traditional ecological sense, but also accurately simulate the actual dynamic resistance of atmospheric pollutants and greenhouse gases when they diffuse in space.

[0109] In an optional embodiment, the step of constructing the comprehensive ventilation resistance surface comprises:

[0110] calculating the spatial heterogeneity index and the landscape type consistency index of different roughness at the corresponding spatial scale;

[0111] combining the preset global reference weight, and performing dynamic weight distribution based on the spatial heterogeneity index and the landscape type consistency index;

[0112] weighting and superimposing different roughness based on the distributed weight to obtain a comprehensive ventilation resistance coefficient, calculating a comprehensive ventilation resistance value based on the comprehensive ventilation resistance coefficient, and constructing a comprehensive ventilation resistance surface based on the comprehensive ventilation resistance value; the calculation formula of the comprehensive ventilation resistance value is as follows:

[0113]

[0114]

[0115] wherein, is the corrected ecological expansion grid resistance value; is the uncorrected minimum cumulative ecological expansion resistance value; is the ventilation resistance coefficient of the grid ; is the average ventilation resistance coefficient of the land type corresponding to the grid ; is the corrected urban expansion grid resistance value.

[0116] In this embodiment, the dynamic weight distribution based on spatial heterogeneity is used to weight and superimpose different types of roughness, which can adapt to the characteristics of different spatial units, and the calculation result of the comprehensive resistance surface is more suitable for the actual geographical environment.

[0117] In an optional embodiment, the ventilation corridor is generated based on the GIS minimum cost path algorithm and coupled with the WRF wind field simulation data, and the width is determined based on the adaptive threshold; the ecological corridor is identified based on the minimum cost path, the width is determined by calculating the proportion of different land use types and different corridors, and the width is graded based on the possible connectivity index.

[0118] As an example, using the minimum cost path tool of ArcGIS software, the compensation space is taken as the source point and the action space as the destination, the minimum cost path of the airflow between the source point and each destination is calculated respectively; and the ventilation corridor should conform to the city's dominant wind direction as much as possible, and the included angle should not exceed 10°.

[0119] More specifically, after obtaining the ventilation corridor path, a qualitative and quantitative combined method is used for grading, and the city wind channel is divided into main ventilation corridors and other corridors as secondary corridors according to the connection position of the corridor. On this basis, the China Meteorological Element Average Condition Spatial Interpolation Dataset provided by the Resource and Environment Science and Data Center is used to obtain the annual average wind speed grid map in the study area. After extracting the wind speed map in the above main ventilation corridor and calculating the average wind speed, the natural breakpoint method is used to divide the ventilation efficiency of the wind channel into two levels, corresponding to the first and second wind channels respectively, and the other wind channels are divided into the third wind channel.

[0120] More specifically, for the extraction of ecological corridors, the main basis is the ecological expansion resistance, which mainly includes the following steps:

[0121] Corridor identification: The Linkage Pathways module in the Linkage Mapper Toolbox of the geographic information system tool is used to identify the ecological corridor, and the minimum cost path is taken as the optimal ecological corridor to determine the path of the corridor.

[0122] Corridor grading: The probability of connectivity (PC) index in Conefor 2.6 is used to calculate the contribution of the corridor to improve the overall landscape connectivity of the ecosystem, and the specific calculation formula is as follows:

[0123]

[0124]

[0125] Wherein, n represents the number of landscape elements, and respectively represent the area of ecological source i and j, represents the total area of the regional landscape, represents the maximum probability product of all possible paths between ecological source i and j, represents the connectivity of ecological source i itself, represents the PC index after removing ecological source i.

[0126] Width setting, based on the existing corridor width division, set different width of corridor, calculate the proportion of different land use types and different corridor. With the increase of corridor width, the proportion of construction land under human disturbance continues to grow, and the proportion of forest land and grassland decreases. Find the proportion of forest land, grassland and construction land mutation point, which is used as the final width of ecological corridor.

[0127] In an optional embodiment, the step of dividing the resistance level of the comprehensive ventilation resistance surface based on the spatial game characteristics of the ecological land and the construction land in the target area comprises:

[0128] The difference between the minimum cumulative resistance surface of the ecological land expansion and the minimum cumulative resistance surface of the construction land expansion;

[0129] According to the numerical statistical distribution characteristics of the difference value, determine the mutation threshold for dividing the level interval based on the distribution characteristics;

[0130] Difference division is performed on the comprehensive ventilation resistance surface based on the mutation threshold.

[0131] More specifically, the minimum cumulative resistance surface is calculated. The minimum cumulative resistance surface of ecological land expansion and construction land expansion is calculated using the MCR model in the spatial analysis function of ArcGIS.

[0132] To reflect the game relationship between the spatial demand of construction land and the spatial protection of ecological land, this section uses the resistance surface difference of the expansion process of ecological land and construction land to characterize, which is specifically shown as:

[0133]

[0134] Among them, is the minimum cumulative resistance difference, is the minimum cumulative resistance of ecological land expansion, is the minimum cumulative resistance of construction land expansion. For the same grid cell, <0, the resistance of ecological "source" expansion is less than the resistance of construction "source" expansion, then the grid cell land is more suitable to be divided into ecological land; when >0, the resistance of ecological "source" expansion is greater than the resistance of construction "source" expansion, then the grid cell land is more suitable to be divided into construction land; when =0, the resistance of ecological "source" expansion is equal to the resistance of construction "source" expansion.

[0135] In ArcGIS, the resistance difference is obtained by using the grid calculator function. The mutation point can be determined by means of the curve graph of the number of land landscape units and the minimum cumulative resistance difference value.

[0136] As Figure 2As shown in the figure, it is the minimum resistance difference distribution diagram of ecological expansion and urban expansion.

[0137] When the minimum cumulative resistance difference is at point O (the value is 0), the number of land landscape unit grids is the most, and the landscape process changes sharply, which can be used as a turning point for division. In order to more accurately divide the land ecological safety partition, it is necessary to divide the threshold in the positive and negative curves of the minimum cumulative resistance difference. When the minimum cumulative resistance difference is negative, a sudden change occurs at point A, which can be used as the negative partition threshold; when the minimum cumulative resistance difference is positive, a sudden change occurs at point B (the value is 150000), which can be used as the positive partition threshold. The three mutation points A, O and B divide the resistance interpolation surface into four intervals, corresponding to the first to fourth buffer zones. For the construction "source", the expansion difficulty degrees in the first interval and the second interval are very difficult and difficult respectively, and the expansion difficulty degrees in the third interval and the fourth interval are easy and very easy respectively; for the ecological "source", the expansion difficulty degree is opposite to that of the construction "source".

[0138] In an optional embodiment, the step of constructing the safety pattern result of the target region includes: taking the protection level of the ecological source area grading result, the comprehensive ventilation resistance surface resistance level division result, the path and width of the ventilation corridor and the path and width of the ecological corridor as the safety pattern result with the highest protection level requirement.

[0139] In this embodiment, the spatial superposition rule of "taking the protection level highest" is adopted, which has the beneficial effect of following the "conservative principle" or "short board effect" in risk management. And a complete and reliable spatial protection bottom line is constructed.

[0140] As an exemplary illustration, the division standard of the ecological safety pattern is shown in Table 1.

[0141] Table 1: Division standard of ecological safety pattern

[0142]

[0143] Embodiment 2

[0144] This embodiment proposes an atmospheric safety pattern construction system, which applies the atmospheric safety pattern construction method for reducing pollution and carbon reduction synergy proposed in embodiment 1. As shown in the figure, it is the architecture diagram of the atmospheric safety pattern construction system of this embodiment. Figure 3

[0145] This embodiment proposes an atmospheric safety pattern construction system, which includes:

[0146] The ecological source area identification and grading module identifies the ecological source area of the target region based on multi-source remote sensing data, and grades the ecological source area through the landscape connectivity index of the ecological source area; ​

[0147] A ventilation resistance surface construction and grading module is configured to construct and grade a comprehensive ventilation resistance surface by comprehensively considering the surface roughness, vegetation roughness and water roughness;

[0148] A corridor extraction and processing module is configured to extract ventilation corridors and ecological corridors based on the comprehensive ventilation resistance surface and the ecological extension resistance of a target region, and set the widths of the ventilation corridors and the ecological corridors, respectively;

[0149] A pattern construction and output module is configured to perform spatial superposition analysis on the graded ecological source, the comprehensive ventilation resistance surface, and the graded ventilation corridors and ecological corridors, and construct and output a multi-level atmospheric safety pattern.

[0150] It can be understood that the system of the embodiment corresponds to the method of the above-mentioned embodiment 1, and the optional items in the above-mentioned embodiment 1 are also applicable to the embodiment, and therefore are not repeated here.

[0151] Obviously, the above-mentioned embodiments of the present application are only examples for clearly illustrating the present application, and are not intended to limit the implementation modes of the present application. Based on the above-mentioned description, other different forms of changes or variations can be made by those skilled in the art. Here, it is not necessary and also impossible to exhaust all the implementation modes. Any modification, equivalent replacement and improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the claims of the present application.

Claims

1. A method for constructing a pollution-reducing and carbon-reducing collaborative atmospheric security pattern, characterized in that, The method comprises the following steps: identifying ecological sources of a target region based on multi-source remote sensing data, and grading the ecological sources based on a landscape connectivity index of the ecological sources; constructing a comprehensive ventilation resistance surface based on surface roughness, vegetation roughness and water roughness of the target region, wherein the surface roughness is calculated by a windward area density model, and the vegetation roughness and water roughness are respectively represented by a normalized difference vegetation index and a normalized difference water index; and dividing the comprehensive ventilation resistance surface into resistance levels based on spatial game characteristics of ecological land and construction land in the target region; extracting paths and widths of ventilation corridors and ecological corridors based on the comprehensive ventilation resistance surface and ecological expansion resistance of the target region; performing superimposition analysis based on the grading results of the ecological sources, the resistance level division results of the comprehensive ventilation resistance surface, and the paths and widths of the ventilation corridors and the ecological corridors, and constructing a safety pattern result of the target region; the step of dividing the comprehensive ventilation resistance surface into resistance levels based on spatial game characteristics of ecological land and construction land in the target region comprises: calculating a difference between a minimum cumulative resistance surface of ecological land expansion and a minimum cumulative resistance surface of construction land expansion; determining a mutation threshold for dividing level intervals based on the numerical statistical distribution characteristics of the difference; dividing the comprehensive ventilation resistance surface into levels based on the mutation threshold.

2. The method according to claim 1, wherein, The step of identifying ecological sources of a target region based on multi-source remote sensing data comprises: identifying land classification through remote sensing data; determining ecological source candidate areas through morphological spatial pattern analysis based on the classification results; collecting vegetation structure parameters in the ecological source candidate areas, and inversing plant chemical components based on spectral data; calculating carbon fixation and pollution sinking efficiency based on the vegetation structure parameters and the plant chemical components; calculating carbon storage, and regarding ecological source candidate areas with carbon storage greater than a preset threshold as ecological sources.

3. The method according to claim 1, wherein, The calculation of surface roughness specifically comprises: extracting building planar layout and height data to generate a normalized digital surface model; constructing a 3D surface model based on fused terrain relief data; obtaining a surface roughness resistance surface by weighted superimposition according to actual wind frequency based on FAD calculation results of different wind directions.

4. The method of claim 1, wherein, The normalized difference vegetation index Based on the infrared band calculation, the calculation formula is as follows: wherein, represents the reflectance value in the near infrared band, is the reflectance value in the red band; The normalized difference water index Based on the green band and the infrared band, and the calculation formula is as follows: wherein, represents the reflectance value of the green light band, is the reflectance value of the mid-infrared band.

5. The method of claim 2, wherein the method is characterized by, A microclimate correction factor is introduced when calculating the carbon storage; and the calculation formula for calculating the carbon storage is as follows: wherein, represents the carbon storage of the ecosystem type t at the time instant i ; is a baseline value, being the biomass inverted from LIDAR multiplied by the carbon content coefficient; is a remote sensing correction factor, used to correct the difference in normalized vegetation index at different time points, to improve the accuracy of carbon storage estimation; is a microclimate correction factor, considering the influence of temperature T and humidity H on vegetation growth and carbon storage; is the carbon fixation and sedimentation efficiency of the plant.

6. The method according to any one of claims 3-4, wherein, The step of constructing a comprehensive ventilation resistance surface comprises: calculating spatial heterogeneity indexes and landscape type consistency indexes of different roughnesses at corresponding spatial scales; performing dynamic weight distribution based on the spatial heterogeneity indexes and the landscape type consistency indexes in combination with a preset global reference weight; performing weighted superimposition on different roughnesses based on the distributed weights to obtain a comprehensive ventilation resistance coefficient, calculating a comprehensive ventilation resistance value based on the comprehensive ventilation resistance coefficient, and constructing a comprehensive ventilation resistance surface based on the comprehensive ventilation resistance value; and the calculation formula for the comprehensive ventilation resistance value is as follows: wherein, is the modified ecological expansion grid resistance value; is the unmodified minimum cumulative ecological expansion resistance value; is the grid ventilation resistance coefficient at the grid is the grid average ventilation resistance coefficient corresponding to the land type; is the modified urban expansion grid resistance value.

7. The method according to claim 6, wherein, The ventilation corridor is generated based on a GIS minimum cost path algorithm and coupled with WRF wind field simulation data, and the width is determined based on an adaptive threshold; the ecological corridor is identified based on a minimum cost path, the width is determined by calculating the proportion of different land use types and different corridors, and the ecological corridor is graded based on a possible connectivity index.

8. The method of claim 1, wherein the method is characterized by, The step of constructing the safety pattern result of the target area includes: taking the highest protection level of the protection level of the ecological source area grading result, the comprehensive ventilation resistance surface resistance grade division result, the path and width of the ventilation corridor and the ecological corridor as the safety pattern result.

9. An atmospheric safety pattern building system, characterized by, The system comprises: An ecological source area identification and grading module, which identifies the ecological source area of the target area based on multi-source remote sensing data, and grades the ecological source area through a landscape connectivity index of the ecological source area; A ventilation resistance surface construction and grading module, which is used for constructing a comprehensive ventilation resistance surface and grading the comprehensive ventilation resistance surface by comprehensively considering the ground roughness, vegetation roughness and water roughness; A corridor extraction and processing module, which extracts a ventilation corridor based on the comprehensive ventilation resistance surface, extracts an ecological corridor based on the ecological expansion resistance of the target area, and sets the width of the ventilation corridor and the ecological corridor respectively; A pattern construction and output module, which is used for spatial superposition analysis of the graded ecological source area, the comprehensive ventilation resistance surface, and the graded ventilation corridor and ecological corridor, and constructs and outputs a multi-level atmospheric safety pattern.

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