Atmosphere safety pattern construction method and system with cooperation of pollution reduction and carbon reduction

Abstract

The invention relates to the technical field of ecological data fusion, in particular to an atmospheric safety pattern construction method and system with cooperation of pollution reduction and carbon reduction, and the method comprises the steps: recognizing an ecological source land of a target region based on multi-source remote sensing data, and grading the ecological source land; constructing a comprehensive ventilation resistance surface based on the surface roughness, the vegetation roughness and the water area roughness of the target area, and dividing resistance grades of the comprehensive ventilation resistance surface based on the spatial game characteristics of the ecological land and the construction land in the target area; a ventilation corridor and an ecological corridor are extracted, and the width of the ventilation corridor and the width of the ecological corridor are set; and based on the ecological source land grading result, integrating the ventilation resistance surface resistance grading result, the path and width of the ventilation corridor and the path and width of the ecological corridor to carry out overlay analysis, and constructing a safety pattern result of the target area. According to the method, the defects of the existing ecological security pattern content are overcome, and the construction precision of the atmospheric security pattern is improved.

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 for 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 integrated into a 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 prior art described above, which lacks 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: A pollution-reducing and carbon-reducing collaborative atmospheric safety pattern construction method, comprising: identifying ecological sources of a target region based on multi-source remote sensing data, and classifying the ecological sources through a landscape connectivity index of the ecological sources; A comprehensive ventilation resistance surface is constructed based on the surface roughness, vegetation roughness, and water roughness of the target area, where the surface roughness is calculated using a windward area density model, and the vegetation roughness and water roughness are characterized by the Normalized Difference Vegetation Index and the Normalized Difference Water Index, respectively. The comprehensive ventilation resistance surface is divided into resistance levels based on the spatial game characteristics of ecological land and construction land in the target area; Extracting ventilation corridors based on the comprehensive ventilation resistance surface, and extracting ecological corridors based on the ecological expansion resistance of the target area, and setting the widths of the ventilation corridors and ecological corridors respectively; The safety pattern results of the target area are constructed based on the ecological source classification results, the comprehensive ventilation resistance surface resistance level classification results, the path and width of the ventilation corridor, and the path and width of the ecological corridor.

[0006] As a preferred solution, the step of identifying the ecological source of the target area based on multi-source remote sensing data includes: Identify land classifications through remote sensing data; Based on the classification results, the candidate ecological source areas were determined through morphological spatial pattern analysis; Collecting vegetation structure parameters within the candidate ecological source area and inverting plant chemical components based on spectral data; Calculating carbon sequestration efficiency based on the vegetation structural parameters and plant chemical composition; The carbon storage is calculated based on the carbon sequestration efficiency, and the candidate ecological source areas with carbon storage greater than a preset threshold are taken as ecological source areas.

[0007] As a preferred solution, the calculation of surface roughness specifically includes: Extract building layout and height data to generate normalized digital surface models; Construct a 3D surface model based on the fusion of terrain relief data; 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.

[0008] As a preferred solution, the normalized vegetation index is calculated based on the infrared band, and its calculation formula is as follows:

[0009] in, represents the reflectance value of the near-infrared band, is the reflectance value of the red light band; The normalized difference water index is calculated based on the green light band and the infrared band, and its calculation formula is as follows:

[0010] in, Indicates the reflectance value of the green light band, The reflection value is for the mid-infrared band.

[0011] As a preferred solution, a microclimate correction factor is introduced when calculating the carbon storage; the calculation formula for calculating the carbon storage is as follows:

[0012]

[0013] Wherein, represents the carbon storage of the ecosystem type t at the moment 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 difference of normalized 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.

[0014] As a preferred solution, the step of constructing the comprehensive ventilation resistance surface comprises: calculating the spatial heterogeneity index and the landscape type consistency index of different roughness at the corresponding spatial scale; combining the preset global baseline weight, and performing dynamic weight distribution based on the spatial heterogeneity index and the landscape type consistency index; 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:

[0015]

[0016] 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.

[0017] 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 value; 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.

[0018] As a preferred solution, the step of 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 comprises: determining the difference between the minimum cumulative resistance surface of the ecological land expansion and the minimum cumulative resistance surface of the construction land expansion; According to the numerical statistical distribution characteristics of the difference value, a mutation threshold value for dividing the level interval is determined based on the distribution characteristics; The comprehensive ventilation resistance surface is divided by difference based on the mutation threshold value.

[0019] As a preferred solution, the step of constructing the 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.

[0020] The present application also proposes an atmospheric safety pattern construction system, the system comprises: An ecological source land identification and grading module identifies the ecological source land of a target region based on multi-source remote sensing data, and grades the ecological source land through the landscape connectivity index of the ecological source land; A ventilation resistance surface construction and grading module is used to construct a comprehensive ventilation resistance surface by integrating the ground roughness, vegetation roughness and water roughness, and to grade the comprehensive ventilation resistance surface; A corridor extraction and processing module extracts a ventilation corridor based on the comprehensive ventilation resistance surface, and extracts an ecological corridor based on the ecological expansion resistance of the target region, and sets the width of the ventilation corridor and the ecological corridor respectively; A pattern construction and output module is used to perform spatial overlay analysis on the graded ecological source land, the comprehensive ventilation resistance surface, and the graded ventilation corridor and ecological corridor, and to construct and output a multi-level atmospheric safety pattern.

[0021] Compared with the prior art, the technical scheme of the present application has the following beneficial effects: The present invention dynamically integrates "atmospheric safety" as a core element into the construction of the ecological security pattern. In the source identification link, multi-source data collection and comprehensive processing technology is used to break through the technical bottleneck of the original single macro remote sensing image recognition; in the resistance surface construction link, the atmospheric attribute vegetation and water roughness are added to the construction principle of the original ecological safety resistance surface to construct a ventilation resistance surface with atmospheric ventilation and cooling significance; in the corridor extraction link, on the basis of the existing ecological corridor, ventilation corridors with atmospheric characteristics are added to form a natural corridor system under the goal of pollution reduction and carbon reduction; in the atmospheric safety pattern construction link, the game thinking of ecological land and construction land is added, and the mutation intervals of ecology and construction are located based on statistics, which effectively improves the accuracy of the atmospheric safety pattern construction. BRIEF DESCRIPTION OF THE DRAWINGS Figure 1 This is a flow chart of the method for constructing an atmospheric safety framework for coordinated pollution reduction and carbon reduction according to Example 1; Figure 2 This is the distribution map of the minimum resistance difference between ecological expansion and urban expansion in Example 1; Figure 3 Construct a system architecture diagram for the atmospheric safety pattern of Example 2. DETAILED DESCRIPTION

[0022] The accompanying drawings are for illustrative purposes only and are not to be construed as limiting this patent; In order to better illustrate this embodiment, some parts in the drawings may be omitted, enlarged, or reduced, and do not represent the actual product size; It is understandable to those skilled in the art that some well-known structures and descriptions thereof may be omitted in the drawings.

[0023] The technical solution of the present invention is further described below with reference to the accompanying drawings and embodiments.

[0024] Example 1 This embodiment proposes a method for constructing an atmospheric safety pattern that coordinates pollution reduction and carbon reduction, such as Figure 1 , which is a flow chart of a method for constructing an atmospheric safety pattern that coordinates pollution reduction and carbon reduction in accordance with this embodiment.

[0025] A method for constructing an atmospheric safety framework that coordinates pollution reduction and carbon reduction, including: S1. Identify ecological source areas in target areas based on multi-source remote sensing data, and classify the ecological source areas according to their landscape connectivity index; S2. Construct a comprehensive ventilation resistance surface based on the surface roughness, vegetation roughness, and water roughness of the target area, wherein the surface roughness is calculated using a windward area density model, and the vegetation roughness and water roughness are characterized by the Normalized Difference Vegetation Index and the Normalized Difference Water Index, respectively. The comprehensive ventilation resistance surface is divided into resistance levels based on the spatial game characteristics of ecological land and construction land in the target area; S3. Extracting ventilation corridors based on the comprehensive ventilation resistance surface, and extracting ecological corridors based on the ecological expansion resistance of the target area, and setting widths for the ventilation corridors and ecological corridors respectively; S4. Based on the ecological source classification results, the comprehensive ventilation resistance surface resistance level classification results, the paths and widths of ventilation corridors, and the paths and widths of ecological corridors, a superposition analysis is performed to construct the safety pattern results of the target area.

[0026] In this example, a comprehensive ventilation resistance surface is constructed by integrating multi-source data to identify and classify ecological source areas. Ventilation and ecological corridors are then extracted collaboratively, ultimately creating a multi-level security landscape through spatial overlay. This provides a systematic and quantifiable technical framework, extending the traditional ecological security landscape construction method, which focuses on biodiversity conservation, to the atmospheric environment. This approach achieves spatial response and planning support for the coordinated goals of pollution reduction and carbon reduction, providing a design tool for improving regional atmospheric environmental safety.

[0027] In an optional embodiment, the step of identifying the ecological source of the target area based on multi-source remote sensing data includes: Identify land classifications through remote sensing data; Based on the classification results, the candidate ecological source areas were determined through morphological spatial pattern analysis; Collecting vegetation structure parameters within the candidate ecological source area and inverting plant chemical components based on spectral data; Calculating carbon sequestration efficiency based on the vegetation structural parameters and plant chemical composition; The carbon storage is calculated based on the carbon sequestration efficiency, and the candidate ecological source areas with carbon storage greater than a preset threshold are taken as ecological source areas.

[0028] In this embodiment, by comprehensively utilizing heterogeneous data from multiple platforms including the sky, air, and ground, the limitations of a single remote sensing data source are broken through, and three-dimensional, high-precision perception of multi-dimensional parameters such as the carbon sink function of ecological sources is achieved.

[0029] In an optional embodiment, a microclimate correction factor is also introduced when calculating the carbon storage; the calculation formula for calculating the carbon storage is as follows:

[0030]

[0031] in, Indicates t moment, ecosystem type i carbon storage; is the baseline value, which is the biomass retrieved by LIDAR multiplied by the carbon content coefficient; It is a remote sensing correction factor used to correct the differences in normalized vegetation index at different time points to improve the accuracy of carbon storage estimation; is the microclimate correction factor, which takes into account the effects of temperature T and humidity H on vegetation growth and carbon storage; It is the carbon sequestration efficiency of plants.

[0032] More specifically, the calculation formula for ecological source area classification is as follows:

[0033]

[0034] in, PC represents the overall possible connectivity index of all patches in the landscape, PCremove , k Indicates plaque removal k The possible connectivity index of the remaining patches, Indicates plaque k relative importance to overall landscape connectivity; is the number of core areas; and For the core area and area; Finger plaque and The number of connections between Represents the total value of the landscape in the study area; 0≤ ≤1, =0, no connectivity between habitat patches; =1, the entire landscape is a habitat patch.

[0035] The higher the connectivity index of the ecological source patch, the more important the patch is. This section uses the K-Means method to calculate the results of dPC and IIC to divide ecological sources into three categories: very important, relatively important, and generally important.

[0036] In this embodiment, the extreme climate impact is taken into account through the microclimate correction factor, thereby improving the accuracy and reliability of carbon storage estimation.

[0037] In an optional embodiment, the calculation of the surface roughness specifically includes: Extract building layout and height data to generate normalized digital surface models; Construct a 3D surface model based on the fusion of terrain relief data; 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.

[0038] Furthermore, the frontal area density FAD is used to calculate the surface roughness, and the calculation formula is:

[0039] in, It is the windward area of ​​a building perpendicular to a certain wind direction; is the area of ​​the plot where the building is located; It is a chosen direction; It is the height increase.

[0040] A raster computing model is used to construct a 3D building model library within the research scope.

[0041] As an example, the calculation steps are as follows: Morphological extraction of building floor plans. A vector dataset of urban building rooftops was extracted and, using the Aggregate Polygon tool in ArcGIS, buildings with similar attributes were clustered. Building heights were obtained using the AW3D30 Global Digital Surface Model dataset and the panchromatic remote sensing stereo mapper onboard the Advanced Land Observing Satellite.

[0042] In order to extract buildings, an approximate ground DEM is determined to separate non-ground objects from the ground. The difference between the original DSM and the approximate DEM is called the normalized DSM (nDSM), which contains the height information of all non-ground objects and is calculated as follows:

[0043] The block minimum filtering method is used to generate DEM by obtaining the minimum elevation within a certain area.

[0044] Will Assign a rooftop footprint to each building plane to separate the building from other objects. Use the Zonal Statistics tool in ArcGIS software to calculate the average building height of individual buildings.

[0045] Extract the mountain range, use DEM digital elevation model data, with the help of the focus statistics tool in ArcGIS software, combine existing results and experience with repeated experimental thresholds, and extract the mountain range and height data.

[0046] After overlaying the above building height and urban terrain data, the GIS plug-in FAD Tools is imported to calculate the FAD of the buildings and terrain within the study area. Based on this tool, the FAD is calculated: Determine the value of height increment Z in the FAD formula: First, use the ArcGIS software data statistical tool to process the above 3D building database, and draw a building height distribution histogram.

[0047] ②Import the ground 3D database into FAD Tools for processing. The addition method of this plug-in is as shown in the following 16 wind directions to obtain the FAD calculation results in the research range.

[0048] ③Statistical wind direction and frequency. Use the surface meteorological daily value data set to extract and count the daily maximum and maximum wind direction and frequency of meteorological data. According to the maximum wind speed and direction frequency of the whole year, the 16 wind direction FADs are weighted and superimposed to obtain the final ground roughness resistance surface.

[0049] In an optional embodiment, the normalized vegetation index is calculated based on an infrared band, and the calculation formula is as follows:

[0050] Wherein, represents the reflection value of the near-infrared band, is the reflection value of the red light band; 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:

[0051] Wherein, represents the reflection value of the green light band, is the reflection value of the mid-infrared band.

[0052] In this embodiment, the vegetation index and the water body index jointly construct the ventilation resistance surface, and the key ground parameters of atmospheric fluid mechanics are integrated into the resistance model, so that 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.

[0053] In an optional embodiment, the step of constructing the comprehensive ventilation resistance surface comprises: Calculate the spatial heterogeneity index and the landscape type consistency index of different roughness at the corresponding spatial scale; Dynamically allocate weights based on the spatial heterogeneity index and the landscape type consistency index in combination with the preset global reference weight; Based on the allocated weights, the different roughnesses are 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:

[0054]

[0055] in, is the corrected ecological expansion grid resistance value; is the uncorrected minimum cumulative ecological expansion resistance value; For grid The ventilation resistance coefficient at For grid Average ventilation resistance coefficient for the corresponding land type; is the corrected urban expansion grid resistance value.

[0056] In this embodiment, dynamic weight allocation based on spatial heterogeneity is used to perform weighted superposition of different types of roughness, which can adapt to the characteristics of different spatial units and make the calculation result of the comprehensive resistance surface more consistent with the actual geographical environment.

[0057] In an optional embodiment, the ventilation corridor is generated based on the GIS minimum cost path algorithm and coupled with WRF wind field simulation data, and its width is delineated based on an adaptive threshold; the ecological corridor is identified based on the minimum cost path, and its width is delineated by calculating the ratio of different land use types to different corridors, and is graded based on a possible connectivity index.

[0058] As an example, the minimum cost path tool of ArcGIS software is used, with the compensation space as the source point and the action space as the destination, to calculate the minimum cost path of the airflow from the source point to each destination; and the ventilation corridor should try to follow the dominant wind direction of the city, with an angle of no more than 10°.

[0059] More specifically, after identifying the ventilation corridor paths, a combination of qualitative and quantitative methods was used to classify them. Based on their connection locations, urban wind corridors were classified as primary ventilation corridors, with other corridors classified as secondary corridors. Furthermore, a spatial interpolation dataset of average meteorological conditions in China, provided by the Resource and Environmental Science and Data Center, was used to generate a grid map of the average annual wind speed within the study area. The wind speed map within the primary ventilation corridors was extracted, and after calculating the average wind speed, the natural breaks method was used to categorize the ventilation efficiency of the corridors into two levels, corresponding to primary and secondary corridors, respectively. Other corridors were classified as tertiary corridors.

[0060] More specifically, the extraction of ecological corridors is mainly based on ecological expansion resistance and includes the following steps: Corridor identification: The Linkage Pathways module in the Linkage Mapper Toolbox of the geographic information system tool is used to identify ecological corridors, and the path with the minimum cost is used as the optimal ecological corridor to determine the corridor path.

[0061] Corridor classification uses the probability of connectivity (PC) index in Conefor 2.6 to calculate the contribution of corridors to improving the overall landscape connectivity of the ecosystem. The specific calculation formula is as follows:

[0062]

[0063] Where n represents the number of landscape elements, and represent the areas of ecological source areas i and j respectively, represents the total landscape area of ​​the region, represents the maximum probability product of all possible paths between ecological source i and j, represents the connectivity of ecological source i, Represents the PC index after removing ecological source i.

[0064] Width setting: Based on the existing corridor width, corridors of varying widths were created, and the ratios of different land use types to different corridors were calculated. As corridor width increased, the proportion of construction land affected by human interference continued to increase, while the proportions of forestland and grassland decreased. The point at which the ratios of forestland, grassland, and construction land suddenly changed was identified, and this point was used as the final width of the ecological corridor.

[0065] In an optional embodiment, the step of dividing the comprehensive ventilation resistance surface into resistance levels based on the spatial game characteristics of ecological land and construction land in the target area includes: Calculate the difference between the minimum cumulative resistance surface for ecological land expansion and the minimum cumulative resistance surface for construction land expansion; According to the numerical statistical distribution characteristics of the difference, determining the mutation threshold for dividing the grade interval based on the distribution characteristics; The comprehensive ventilation resistance surface is subjected to difference division based on the mutation threshold.

[0066] More specifically, the minimum cumulative resistance surface was calculated using the MCR model in the spatial analysis function of ArcGIS to generate the minimum cumulative resistance surface for ecological land expansion and construction land expansion.

[0067] To reflect the game relationship between the demand for construction land space and the protection of ecological land space, this section uses the difference in resistance surface between the expansion of ecological land and the expansion of construction land to represent it. The specific expression is as follows:

[0068] in, is the minimum cumulative resistance difference, The minimum cumulative resistance to ecological land expansion, is the minimum cumulative resistance to the expansion of construction land. For the same grid unit, when When <0, the resistance to the expansion of ecological “source” is less than the resistance to the expansion of construction “source”, and the land of this grid unit is more suitable to be divided into ecological land; when When >0, the resistance to the expansion of ecological “sources” is greater than the resistance to the expansion of construction “sources”, and the land in this grid unit is more suitable to be divided into construction land; when =0, the resistance to the expansion of the ecological "source" is equal to the resistance to the expansion of the construction "source".

[0069] The resistance difference was obtained using the raster calculator function in ArcGIS. The mutation point can be determined by plotting the number of landscape units against the minimum cumulative resistance difference.

[0070] like Figure 2 Shown is the distribution map of the minimum resistance difference between ecological expansion and urban expansion.

[0071] When the minimum cumulative resistance difference is at point O (value 0), the number of land landscape units is at its highest, and the landscape process undergoes a dramatic change, which can be used as a turning point. To more accurately delineate land ecological security zones, thresholds are drawn within 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 serves as a negative zoning threshold. When the minimum cumulative resistance difference is positive, a sudden change occurs at point B (value 150,000), which serves as a positive zoning threshold. The resistance interpolation surface is divided into four intervals using the three sudden change points (A, O, and B), corresponding to Level I to Level IV buffer zones. For source construction, the expansion difficulty in Level I and Level II intervals is very difficult and difficult, respectively, while the expansion difficulty in Level III and Level IV intervals is easy and very easy, respectively. For ecological sources, the expansion difficulty is the opposite of that for source construction.

[0072] In an optional embodiment, the step of constructing the safety pattern result of the target area includes: taking the safety pattern level with the highest protection level requirement as the safety pattern result for the ecological source classification results, the comprehensive ventilation resistance surface resistance level classification results, the path and width of the ventilation corridor, and the path and width of the ecological corridor.

[0073] In this embodiment, the spatial superposition rule of "taking the highest protection level" is adopted. Its beneficial effect is that it follows the "conservative principle" or "shortest board effect" in risk management, and builds a complete and reliable spatial protection bottom line.

[0074] As an example, the classification criteria for the ecological security pattern are shown in Table 1.

[0075] Table 1: Classification criteria of ecological safety pattern

[0076] Embodiment 2 This embodiment proposes an atmospheric safety pattern construction system, which applies the atmospheric safety pattern construction method for pollution and carbon reduction synergy proposed in Embodiment 1. As shown in the figure, it is an architecture diagram of an atmospheric safety pattern construction system of this embodiment. Figure 3

[0077] This embodiment proposes an atmospheric safety pattern construction system, which includes: An ecological source identification and grading module, which identifies ecological sources of a target region based on multi-source remote sensing data, and grades the ecological sources through a landscape connectivity index of the ecological sources; A ventilation resistance surface construction and grading module, which is used to construct a comprehensive ventilation resistance surface and grade it by comprehensively considering surface roughness, vegetation roughness and water roughness; A corridor extraction and processing module, which extracts ventilation corridors based on the comprehensive ventilation resistance surface, and extracts ecological corridors based on ecological expansion resistance of the target region, and sets the width of the ventilation corridors and the ecological corridors respectively; A pattern construction and output module, which is used to perform spatial overlay analysis on the graded ecological sources, the comprehensive ventilation resistance surface, and the graded ventilation corridors and ecological corridors, and construct and output a multi-level atmospheric safety pattern.

[0078] It can be understood that the system of this embodiment corresponds to the method of Embodiment 1 described above, and the optional items in Embodiment 1 described above are also applicable to this embodiment, so they will not be described again here.

[0079] Obviously, the above embodiments of the present application are merely examples for clearly illustrating the present application, and are not intended to limit the implementation modes of the present application. Based on the above description, other different forms of changes or variations can be made by those skilled in the art. Here, it is not necessary and impossible to exhaust all the implementation modes. Any modification, equivalent replacement and improvement 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 an atmospheric safety pattern that coordinates pollution reduction and carbon reduction, characterized in that: The following steps are involved: Identify ecological sources in target areas based on multi-source remote sensing data and classify the ecological sources using their landscape connectivity index; A comprehensive ventilation resistance surface is constructed based on the surface roughness, vegetation roughness, and water roughness of the target area, where the surface roughness is calculated using a windward area density model, and the vegetation roughness and water roughness are characterized by the Normalized Difference Vegetation Index and the Normalized Difference Water Index, respectively. The comprehensive ventilation resistance surface is divided into resistance levels based on the spatial game characteristics of ecological land and construction land in the target area; Extracting the path and width of the ventilation corridor based on the comprehensive ventilation resistance surface, and extracting the path and width of the ecological corridor based on the ecological expansion resistance of the target area; Based on the ecological source classification results, the comprehensive ventilation resistance surface resistance level classification results, and the paths and widths of ventilation corridors and ecological corridors, a superposition analysis was performed to construct the safety pattern results of the target area.

2. The method for constructing an atmospheric safety framework for coordinated pollution reduction and carbon reduction according to claim 1 is characterized in that: The step of identifying the ecological source of the target area based on multi-source remote sensing data includes: Identify land classifications through remote sensing data; Based on the classification results, the candidate ecological source areas were determined through morphological spatial pattern analysis; Collecting vegetation structure parameters within the candidate ecological source area and inverting plant chemical components based on spectral data; Calculating carbon sequestration efficiency based on the vegetation structural parameters and plant chemical composition; The carbon storage is calculated based on the carbon sequestration efficiency, and the candidate ecological source areas with carbon storage greater than a preset threshold are taken as ecological source areas.

3. The method for constructing an atmospheric safety framework for coordinated pollution reduction and carbon reduction according to claim 1 is characterized in that: The calculation of surface roughness specifically includes: Extract building layout and height data to generate normalized digital surface models; Construct a 3D surface model based on the fusion of terrain relief data; 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.

4. The method for constructing an atmospheric safety framework for coordinated pollution reduction and carbon reduction according to claim 1 is characterized in that: Normalized Difference Vegetation Index Based on infrared band calculation, the calculation formula is as follows: in, represents the reflectance value of the near-infrared band, is the reflectance value of the red light band; Normalized Difference Water Index Based on the calculation of green light band and infrared band, the calculation formula is as follows: in, Indicates the reflectance value of the green light band, is the reflectance value in the mid-infrared band.

5. The method for constructing an atmospheric safety framework for coordinated pollution reduction and carbon reduction according to claim 2 is characterized in that: The microclimate correction factor is also introduced when calculating the carbon storage; the calculation formula for calculating the carbon storage is as follows: in, Indicates t moment, ecosystem type i carbon storage; is the baseline value, which is the biomass inverted by LIDAR multiplied by the carbon content coefficient; It is a remote sensing correction factor used to correct the differences in the normalized vegetation index at different time points to improve the accuracy of carbon storage estimation; is the microclimate correction factor, taking into account the temperature T and humidity H impacts on vegetation growth and carbon storage; It is the carbon sequestration efficiency of plants.

6. The method for constructing an atmospheric safety framework for coordinated pollution reduction and carbon reduction according to any one of claims 3 to 4, characterized in that: The steps of constructing the comprehensive ventilation resistance surface include: Calculate the spatial heterogeneity index and landscape type consistency index of different roughness at corresponding spatial scales; Combined with the preset global benchmark weight, dynamic weight allocation is performed based on the spatial heterogeneity index and the landscape type consistency index; Based on the assigned weights, different roughnesses are weighted and superimposed to obtain a comprehensive ventilation resistance coefficient. A comprehensive ventilation resistance value is calculated based on the comprehensive ventilation resistance coefficient, and a comprehensive ventilation resistance surface is constructed based on the comprehensive ventilation resistance value. The calculation formula for the comprehensive ventilation resistance value is as follows: in, is the corrected ecological expansion grid resistance value; is the uncorrected minimum cumulative ecological expansion resistance value; For grid The ventilation resistance coefficient at For grid Average ventilation resistance coefficient for the corresponding land type; is the revised urban expansion grid resistance value.

7. The method for constructing an atmospheric safety framework for coordinated pollution reduction and carbon reduction according to claim 6 is characterized in that: The ventilation corridor is generated based on the GIS minimum cost path algorithm and coupled with WRF wind field simulation data, and its width is delineated based on an adaptive threshold. The ecological corridor is identified based on the minimum cost path, and its width is delineated by calculating the ratio of different land use types to different corridors, and is graded based on the possible connectivity index.

8. The method for constructing an atmospheric safety framework for coordinated pollution reduction and carbon reduction according to claim 1 is characterized in that: The step of dividing the comprehensive ventilation resistance surface into resistance levels based on the spatial game characteristics of ecological land and construction land in the target area includes: Calculate the difference between the minimum cumulative resistance surface for ecological land expansion and the minimum cumulative resistance surface for construction land expansion; According to the numerical statistical distribution characteristics of the difference, determining the mutation threshold for dividing the grade interval based on the distribution characteristics; The comprehensive ventilation resistance surface is subjected to difference division based on the mutation threshold.

9. The method for constructing an atmospheric safety framework for coordinated pollution reduction and carbon reduction according to claim 8 is characterized in that: The step of constructing the safety pattern result of the target area includes: taking the safety pattern level with the highest protection level requirement as the safety pattern result for the ecological source classification results, the comprehensive ventilation resistance surface resistance level classification results, and the paths and widths of the ventilation corridors and ecological corridors.

10. An atmospheric safety pattern construction system, characterized in that: The method for constructing an atmospheric safety pattern for coordinated pollution reduction and carbon reduction according to any one of claims 1 to 9 is applied, wherein the system comprises: The ecological source identification and classification module identifies ecological sources in the target area based on multi-source remote sensing data and classifies the ecological sources according to their landscape connectivity index; The ventilation resistance surface construction and classification module is used to integrate the surface roughness, vegetation roughness and water roughness to construct a comprehensive ventilation resistance surface and classify it; a corridor extraction and processing module, which extracts ventilation corridors based on the comprehensive ventilation resistance surface, and extracts ecological corridors based on the ecological expansion resistance of the target area, and sets the widths of the ventilation corridors and ecological corridors respectively; The pattern construction and output module is used to perform spatial superposition analysis on the classified ecological source areas, the comprehensive ventilation resistance surface, and the classified ventilation corridors and ecological corridors, and to construct and output a multi-level atmospheric safety pattern.

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