Residential environment monitoring platform and method based on unmanned aerial vehicle image acquisition

Abstract

The application belongs to the technical field of residential environment monitoring, and in particular relates to a residential environment monitoring platform and method based on unmanned aerial vehicle image acquisition, which comprises a water environment evaluation module, a vegetation environment evaluation module and a pollution evaluation determination module, wherein water runoff traces, vegetation coverage data and near-ground suspended particulate matter concentration distribution data are identified from unmanned aerial vehicle multispectral images, pollution bearing factors and basic pollution coefficients are respectively calculated, and finally the final pollution coefficient is obtained by correcting the basic pollution coefficient through the pollution bearing factor; different emission weights are given based on the attributes of each residential area, and the comprehensive environmental pollution degree of the residential area is output after weighted summation. The application highlights the pollution emission intensity of different attribute residential areas through differentiated weights, obtains the comprehensive environmental pollution degree, makes the mitigation evaluation result close to the actual situation, and provides data support for subsequent environmental governance.

Description

Technical Field

[0001] This invention belongs to the field of residential environment monitoring technology, and more specifically, relates to a residential environment monitoring platform and method based on UAV image acquisition. Background Technology

[0002] Residential environment monitoring is an important part of urban construction. In order to obtain all spatial distribution information of urban residential area environmental data, it is usually necessary to collect images of the residential environment by drones equipped with cameras, so as to provide data support for environmental pollution monitoring and assessment.

[0003] Existing residential environment monitoring platforms generally assess air quality and green coverage, but fail to comprehensively consider the interactive effects of multiple environmental factors such as surface runoff, water distribution, and particulate matter diffusion, as well as the ability of surface runoff to migrate pollution. As a result, the environmental monitoring and assessment results cannot truly reflect the overall state and spatial differentiation characteristics of environmental pollution.

[0004] Furthermore, there are differences in the environmental functions and pollution carrying capacity between living areas and production areas within a residential area. However, existing technologies, when monitoring and assessing the environment, do not take into account the differentiated impact of different attributes on the contribution of pollution emissions, and only use a uniform assessment and quantification method, which leads to the final environmental assessment results deviating from the actual pollution situation. Summary of the Invention

[0005] In view of this, in order to solve the above problems, a residential environment monitoring platform based on UAV image acquisition is proposed.

[0006] The objective of this invention can be achieved through the following technical solution: This invention provides a residential environment monitoring platform based on UAV image acquisition. The system includes: an aquatic environment assessment module, a vegetation environment assessment module, and a pollution assessment and determination module.

[0007] The aquatic environment assessment module acquires images of water runoff in each residential area corresponding to the target residential area collected by drones, identifies water runoff traces from them, calculates the surface runoff path connectivity and water distribution density of each residential area, and combines the two to construct a pollution carrying capacity factor that reflects the ability of surface hydrology to migrate and diffuse pollutants.

[0008] The vegetation environment assessment module identifies vegetation cover data from the image and, in conjunction with near-ground suspended particulate matter concentration distribution data, calculates the air pollution level of each residential area and calculates the basic pollution coefficient of each residential area based on a preset suspended particulate matter purification coefficient.

[0009] The pollution assessment and determination module corrects the basic pollution coefficient by using the pollution carrying capacity factor to obtain the final pollution coefficient of each residential area. Based on the attributes of each residential area, it assigns different emission weights, and performs a weighted summation of the final pollution coefficients of each residential area to output the comprehensive environmental pollution level of the residential area.

[0010] This invention also provides a method for monitoring the residential environment based on UAV image acquisition. The method includes: acquiring images of water runoff in each residential area corresponding to the target residential area collected by the UAV, identifying water runoff traces from them, calculating the surface runoff path connectivity and water distribution density of each residential area, and combining the two to construct a pollution carrying capacity factor that reflects the ability of surface hydrology to migrate and diffuse pollutants.

[0011] Vegetation cover data is identified from the images, and combined with near-ground suspended particulate matter concentration distribution data, the air pollution level of each residential area is calculated, and the basic pollution coefficient of each residential area is calculated based on a preset suspended particulate matter purification coefficient.

[0012] The baseline pollution coefficient is corrected by the pollution carrying capacity factor to obtain the final pollution coefficient of each residential area. Based on the attributes of each residential area, different emission weights are assigned, and the final pollution coefficients of each residential area are weighted and summed to output the comprehensive environmental pollution degree of the residential area.

[0013] Compared with the prior art, the beneficial effects of the present invention are as follows: (1) The present invention comprehensively evaluates the living environment by means of water flow traces, vegetation cover data and near-ground suspended particulate matter concentration distribution data, thereby integrating the basic pollution coefficient after vegetation purification with the pollution carrying factor of water flow, so that the final pollution coefficient can truly reflect the actual pollution situation of the living area under the interaction of multiple factors, and make the evaluation results consistent with reality.

[0014] (2) This invention obtains the pollution carrying capacity factor of water runoff in each residential area by means of surface runoff path connectivity and water distribution density, and corrects the basic pollution coefficient to obtain the final pollution coefficient, thereby accurately quantifying the migration and absorption potential of water runoff for pollutants, correcting the one-sidedness of the basic pollution coefficient, restoring the actual impact of pollution, and thus providing an accurate basis for regional pollution quantification for comprehensive environmental pollution degree calculation.

[0015] (3) Based on the living and production attributes of residential areas, this invention assigns differentiated emission weights and performs weighted summation of the final pollution coefficients of each residential area, so that the comprehensive environmental pollution level can accurately quantify the pollution emissions of centralized pollution sources in production areas, while also reflecting the distribution characteristics of decentralized pollution sources in residential areas, so that the assessment results can provide data support for subsequent environmental governance. Attached Figure Description

[0016] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 This is a schematic diagram of the system module connections of the present invention.

[0018] Figure 2 This is a schematic diagram of the process for identifying the blocked region in this invention.

[0019] Figure 3 This is a schematic diagram of the calculation process for emission weights in this invention.

[0020] Figure 4 This is a schematic diagram of the overall implementation process of the present invention.

[0021] Attached label: 1. Upstream monitoring point; 2. Depression point; 3. Downstream monitoring point; 4. Upstream dividing boundary; 5. Downstream dividing boundary; 6. Sub-channel; Arrow direction indicates river flow direction. Detailed Implementation

[0022] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0023] For details, please refer to [link / reference]. Figure 1 As shown, the present invention provides a residential environment monitoring platform based on UAV image acquisition. The system includes: an aquatic environment assessment module, a vegetation environment assessment module, and a pollution assessment and determination module.

[0024] The aforementioned vegetation environment assessment module is connected to the water environment assessment module and the pollution assessment and determination module, respectively.

[0025] The aquatic environment assessment module acquires images of water runoff in each residential area corresponding to the target residential area collected by drones, identifies water runoff traces from them, calculates the surface runoff path connectivity and water distribution density of each residential area, and combines the two to construct a pollution carrying capacity factor that reflects the ability of surface hydrology to migrate and diffuse pollutants.

[0026] It should be added that the specific process of obtaining images of water flow in each residential area corresponding to the target residential area collected by the drone is as follows: the location of water flow in each residential area is obtained through GIS geographic map, and the starting and ending positions of water flow are identified. The direction from the starting to the ending position is used as the drone's collection path direction. The drone is controlled to fly along the collection path direction, and during the flight, the high-definition camera on the drone is used to collect real-time images of water flow. The collected images are stitched together according to time sequence to obtain images of water flow in each residential area.

[0027] Specifically, the calculation process for the connectivity of surface runoff paths includes: segmenting the water runoff to obtain each runoff segment, and obtaining the water runoff traces of each runoff segment.

[0028] Identify the maximum and minimum runoff widths from the runoff traces in the same runoff segment, and simultaneously identify the maximum and minimum runoff depths.

[0029] Calculate the ratio of the minimum runoff width to the maximum runoff width for each runoff segment, and use it as the width passage factor for that runoff segment.

[0030] Similarly, the depth passage coefficient for each runoff section is calculated using the same method as the width ratio calculation.

[0031] The mean of the width passage coefficient and the depth passage coefficient of the corresponding runoff segment is calculated and used as the path passage capacity of each runoff segment. The minimum value is selected from the path passage capacities of all runoff segments of the water body and used as the path passage capacity of the corresponding water body.

[0032] Identify the blocked areas on the runoff path, calculate the ratio of the total area of ​​all blocked areas in each runoff path to the surface area of ​​the runoff path to obtain the blockage rate, and take the difference between 1 and the blockage rate as the runoff flow rate of the corresponding water area.

[0033] Please see Figure 2 As shown, the edge contours of each runoff segment are identified from the images of each runoff segment. Based on the edge contours of each runoff segment, edge contour curves of each runoff segment are constructed. Monitoring points are arranged in the edge contour curves at equal intervals. The monitoring points are sorted according to the river flow direction, and the width of the runoff segment where each monitoring point is located is extracted to construct a runoff segment width sequence.

[0034] Each depression point is identified from the edge contour curve. The runoff segment is further divided using the adjacent upstream monitoring point and the adjacent downstream monitoring point corresponding to the depression point as the dividing boundary to obtain each sub-runoff segment. The width of the runoff segment where the adjacent upstream monitoring point and the adjacent downstream monitoring point are located are respectively taken as the upstream width and downstream width of the corresponding sub-runoff segment.

[0035] Compare the width of the flow segment at the depression point with the upstream width and the downstream width, and determine whether all of the following conditions are met: the width of the flow segment at the depression point is less than the upstream width and the width of the flow segment at the depression point is less than the downstream width.

[0036] The upstream width is greater than the downstream width.

[0037] If all the above conditions are met, the sub-channel flow segment where the depression is located is determined to be a blockage area.

[0038] Thus, the blockage area of ​​each runoff segment is obtained.

[0039] Multiply the connectivity rate by the path capacity of water flow to obtain the comprehensive path capacity of each water flow, and select the one with the largest comprehensive path capacity as the surface runoff path connectivity of the corresponding residential area.

[0040] On the one hand, the actual capacity of a runoff segment for carrying water flow and pollutants is not determined by the maximum cross-sectional size, but rather by the minimum cross-sectional size. The minimum width and minimum depth within a runoff segment directly limit the flow velocity and pollutant transport flux. Even if other cross-sectional sizes are larger, the overall capacity cannot exceed the upper limit of the minimum cross-sectional constraint. Therefore, by calculating the width capacity coefficient by the ratio of the minimum runoff width to the maximum runoff width within the same runoff segment, and by calculating the depth capacity coefficient by the ratio of the minimum runoff depth to the maximum runoff depth, the cross-sectional uniformity and actual bottleneck degree of the runoff segment can be intuitively quantified. This allows for a more accurate reflection of the actual hydrological transport status of the runoff segment and prevents distortion in subsequent connectivity calculations due to overestimation of the capacity of a single runoff segment. The capacity coefficient transforms the capacity of runoff segments of different sizes and shapes into standardized values ​​in the range of 0 to 1, enabling horizontal comparison of the capacity between different runoff segments.

[0041] On the other hand, there are a large number of invalid runoff paths with unobstructed sections but not connected to water bodies, such as dead-end ditches. These paths cannot participate in the migration and diffusion of pollutants. Therefore, this invention eliminates the interference of invalid paths by using the blockage rate, so that the calculation results reflect the runoff's own flow potential.

[0042] Specifically, the calculation process for the water distribution density includes: for each residential area, obtaining the total surface water area and the total land area of ​​the residential area through a GIS geographic map.

[0043] The ratio of the total surface water area to the total land area of ​​the residential area is calculated to obtain the water distribution density of the corresponding residential area.

[0044] Specifically, the calculation process of the pollution carrying capacity factor includes: when the surface runoff path connectivity of a residential area is greater than a first preset connectivity threshold, the pollution carrying capacity factor of the corresponding residential area is assigned a value of 1.

[0045] When the surface runoff path connectivity of a residential area is greater than the second preset connectivity threshold and less than the first preset connectivity threshold, the water distribution density of each residential area is multiplied by the surface runoff path connectivity of the corresponding residential area to obtain the pollution carrying capacity factor of the corresponding residential area. The first preset connectivity threshold is greater than the second preset connectivity threshold.

[0046] When the surface runoff path connectivity of a residential area is less than the second preset connectivity threshold, the pollution carrying capacity factor of the corresponding residential area will be assigned to 0.

[0047] It should be added that the second preset connectivity threshold is set as follows: Under normal circumstances, the connectivity of a river channel that is unobstructed and in the high-water season may be close to 0.8 to 1. In this invention, 0.9 is preferred as the baseline connectivity, that is, the 75th quantile and 25th quantile of the baseline connectivity are set as the first preset connectivity threshold and the second preset connectivity threshold, respectively. The value of the first preset connectivity threshold is 0.6, and the value of the second preset connectivity threshold is 0.2.

[0048] It should be added that the above-mentioned pollution carrying capacity factors are used to quantify the supporting capacity of surface hydrology for the migration and diffusion of pollutants.

[0049] Surface runoff pathway connectivity characterizes the smoothness of surface runoff pathways and the efficiency of pollutant migration and transport. The higher the value, the better the connectivity of the runoff pathway, the less resistance there is to pollutants migrating to the water body through runoff, and the faster the transport speed.

[0050] Water distribution density characterizes the basic capacity of a water body; the greater the capacity, the greater the potential of the water body to carry and absorb pollutants.

[0051] The higher the connectivity, the easier it is for pollutants to be absorbed into the water body through runoff. If the runoff path is blocked and the connectivity is poor, even if the water density is high, pollutants will have difficulty migrating effectively, and the hydrological carrying capacity will be greatly reduced.

[0052] In summary, the pollution carrying capacity is mainly determined by the connectivity of the runoff path, and the final pollution carrying capacity needs to be determined by combining the water distribution density.

[0053] It should be noted that currently, water quality is usually used as the object of environmental monitoring, and water quality monitoring data is used as the basis for environmental assessment. However, the role of surface hydrology in the migration and diffusion of pollutants, and the distribution density of water bodies and the connectivity of runoff paths together determine the dilution capacity of pollutants. Therefore, this invention analyzes water runoff traces and uses pollution carrying capacity factors to truly reflect the synergistic effect of runoff transport and water dilution, making the pollution assessment results of residential areas more realistic.

[0054] Furthermore, this invention calculates the flow rate by using all obstructed areas within each runoff path, thereby accurately quantifying the actual flow potential of the runoff path and reflecting the weakening effect of obstructed areas on runoff flow, thus ensuring that the pollution carrying capacity is consistent with the surface hydrology's ability to support the migration and diffusion of pollutants.

[0055] The vegetation environment assessment module identifies vegetation cover data from the image and, in conjunction with near-ground suspended particulate matter concentration distribution data, calculates the air pollution level of each residential area and calculates the basic pollution coefficient of each residential area based on a preset suspended particulate matter purification coefficient.

[0056] It should be added that the above-mentioned near-ground suspended particulate matter concentration distribution data were obtained through meteorological monitoring instruments deployed in residential areas.

[0057] Specifically, the calculation process for air pollution levels includes: obtaining a concentration distribution dataset of a target particle size range from near-ground suspended particulate matter concentration distribution data of each residential area, wherein the target particle size range is... and .

[0058] The concentration of suspended particulate matter for each target particle size is obtained from the concentration distribution dataset.

[0059] Calculate the relative deviation between the suspended particulate matter concentration of each target particle size and the corresponding preset suspended particulate matter concentration threshold to obtain the pollution degree coefficient of the corresponding target particle size.

[0060] It should be noted that the aforementioned preset suspended particulate matter concentration thresholds are set based on residential ambient air quality standards. The preset threshold for suspended particulate matter concentration is 35 micrograms per cubic meter. The preset threshold for suspended particulate matter concentration is 75 micrograms per cubic meter.

[0061] The air pollution level of each residential area is obtained by weighted summation of the pollution degree coefficients for each target particle size.

[0062] It should be added that the pollution degree coefficient weights for the above-mentioned target particle sizes are set based on the impact of suspended particulate matter concentration on human health. The specific setting process is as follows: due to fine particulate matter... Fine particulate matter is more easily inhaled by the human body and has a greater impact on human health, thus posing a higher degree of harm to the environment and health. A higher weighting percentage is preferred in this invention. The weight of the pollution level coefficient is 0.6. The weight of the pollution level coefficient is 0.4. The weight of the pollution degree coefficient and The total weight of the pollution degree coefficient is 1.

[0063] Specifically, the calculation process of the basic pollution coefficient includes: extracting the actual planting area of ​​each vegetation type in each residential area from the vegetation cover data, and simultaneously retrieving the suspended particulate matter purification coefficient per unit area corresponding to each type of vegetation.

[0064] Among them, the suspended particulate matter purification coefficient per unit area for each type of vegetation was obtained through the plant leaf area dust retention table. The plant leaf area dust retention is an empirical value in the urban greening plant industry. The leaf area dust retention directly reflects the efficiency of leaf capture of particulate matter and is positively correlated with the purification coefficient per unit area of ​​vegetation.

[0065] It should be noted that since this invention is an environmental monitoring and assessment platform for residential areas, used to comprehensively quantify the regional pollution status rather than to accurately calculate the microscopic dust retention efficiency of a single plant, the unit leaf area is equated to the unit area.

[0066] The purification capacity of the vegetation in a residential area is obtained by multiplying the suspended particulate matter purification coefficient by the total actual planting area of ​​each type of vegetation in each residential area.

[0067] The purification capacity of vegetation in each residential area was normalized to obtain a normalized purification capacity index.

[0068] It should be noted that the above-mentioned minimum-maximum linear normalization is existing technology and will not be described in detail in this invention. The minimum value used for normalization is the minimum total purification capacity of vegetation in each residential area, and the maximum value is the maximum total purification capacity of vegetation in each residential area.

[0069] The air pollution level is corrected based on the purification capacity index to obtain the basic pollution coefficient for each residential area.

[0070] Among them, the above-mentioned basic pollution coefficient The corrected calculation formula is as follows: In the formula, This is a purification capacity index. This refers to the degree of air pollution.

[0071] The pollution assessment and determination module corrects the basic pollution coefficient by using the pollution carrying capacity factor to obtain the final pollution coefficient of each residential area. Based on the attributes of each residential area, it assigns different emission weights, and performs a weighted summation of the final pollution coefficients of each residential area to output the comprehensive environmental pollution level of the residential area.

[0072] Specifically, the calculation process of the final pollution coefficient includes: taking the difference between 1 and the pollution carrying capacity factor as a weakening factor, calculating the product of the weakening factor and the basic pollution coefficient of each residential area, and using it as the final pollution coefficient of the corresponding residential area.

[0073] It should be added that the above-mentioned pollution carrying capacity characterizes the ability of surface water runoff to migrate, diffuse and absorb pollutants. Its value ranges from [0, 1]. The closer the value is to 1, the denser the distribution of water bodies in the area and the smoother the runoff path, and the stronger the weakening effect on air pollution. The closer the value is to 0, the weaker the weakening effect of water runoff on pollutants.

[0074] The baseline pollution coefficient represents the air pollution potential of a residential area after vegetation purification, reflecting the purification effect of vegetation on suspended particulate matter. It is obtained by combining the pollution carrying capacity factor (1) with the baseline pollution coefficient as a weakening factor to arrive at the final pollution level.

[0075] Specifically, the calculation process of the comprehensive environmental pollution level includes: obtaining the attributes of each residential area, wherein the attributes include at least living and production aspects.

[0076] When the attribute of a residential area is solely for living purposes, the emission weight of the corresponding residential area will be assigned a value. .

[0077] It should be noted that the above The value ranges from 0.2 to 0.5. Preferably, when the residential area is an urban area, The possible value is 0.45, especially when the residential area is in the suburbs. The possible value is 0.35.

[0078] When the only attribute of a residential area is production, the emission weight of the corresponding residential area is assigned a value of 1.

[0079] It should be added that, since the pollution emissions from centralized production sources in production areas are higher than those from decentralized residential sources in living areas, the pollution contribution intensity of production areas is used as a quantitative benchmark, that is, the emission weight of residential areas in production areas is assigned a value of 1.

[0080] When a residential area is classified as both a living and a production area, the emission weight of the corresponding residential area is calculated by combining the proportion of the living area and the proportion of the production area.

[0081] Based on the emission weights of each residential area, the final pollution coefficients of the corresponding areas are linearly weighted and summed to obtain the comprehensive environmental pollution level of the residential area.

[0082] It should be added that current environmental monitoring and assessment methods do not distinguish between the actual emission contributions of residential and production areas when calculating the overall environmental pollution level. This leads to the underestimation of the high emission contributions of production areas and the overestimation of the low emission contributions of residential areas, resulting in a discrepancy between the calculation of total pollution and actual emissions. This invention sets different emission weights for residential areas that are only for living, residential areas that are only for production, and residential areas where both production and living exist. This allows for the accurate quantification of the emission contribution differences between areas with different attributes, thus ensuring that the overall environmental pollution level truly reflects the environmental conditions of residential areas.

[0083] Please see Figure 3 As shown, specifically, the process of calculating the emission weight of the corresponding residential area by combining the proportion of living area and the proportion of production area includes: obtaining the area of ​​each living area and each production area in the same residential area, and calculating the total area of ​​the living area and the total area of ​​the production area in each residential area.

[0084] Calculate the ratio of the total area of ​​the living area and the total area of ​​the production area to the total land area of ​​the respective residential areas to obtain the proportion of the living area and the proportion of the production area.

[0085] Emission weights based solely on residential areas as defined by their attributes. The emission weight of a residential area is calculated by combining the emission weight of the residential area with the emission weight of the production area, which is 1, with the emission weight of the production area.

[0086] Among them, the emission weights of the aforementioned residential areas The calculation formula is: In the formula, The proportion of living areas. This represents the percentage of production areas.

[0087] It should be added that the pollution contribution intensity of residential areas with the attribute of both living and production is positively correlated with their proportion of land area within the corresponding residential area. The higher the proportion of production area, the greater the pollution contribution; conversely, the higher the proportion of production area, the greater the pollution contribution. Therefore, the emission weights of residential areas with the attribute of only living can be used to determine the pollution contribution. The emission weight of a residential area with only production attributes is 1. The emission weight of the corresponding residential area is calculated by combining the proportion of living areas and the proportion of production areas, so that the emission weight of the corresponding residential area truly reflects its emission contribution.

[0088] Please see Figure 4As shown, a method for monitoring the residential environment based on UAV image acquisition is described. The method includes: S1, acquiring images of each residential area corresponding to the target residential area collected by the UAV, identifying the runoff traces of each water body, calculating the surface runoff path connectivity and water distribution density of each residential area, and combining the two to construct a pollution carrying capacity factor that reflects the ability of surface hydrology to migrate and diffuse pollutants.

[0089] S2. Identify vegetation cover data from the image, and combine it with near-ground suspended particulate matter concentration distribution data to calculate the air pollution level of each residential area. Based on the preset suspended particulate matter purification coefficient, calculate the basic pollution coefficient of each residential area.

[0090] S3. Correct the basic pollution coefficient by the pollution carrying capacity factor to obtain the final pollution coefficient of each residential area, and assign different emission weights based on the attributes of each residential area. Then, perform a weighted summation of the final pollution coefficients of each residential area to output the comprehensive environmental pollution degree of the residential area.

[0091] The above content is merely an example and illustration of the concept of the present invention. Those skilled in the art can make various modifications or additions to the specific embodiments described, or use similar methods to replace them, as long as they do not deviate from the concept of the invention or exceed the scope defined by the present invention, and all such modifications and additions should fall within the protection scope of the present invention.

Claims

1. A residential environment monitoring platform based on UAV image acquisition, characterized in that, The system includes: The aquatic environment assessment module acquires images of water flow in each residential area corresponding to the target residential area collected by drones, identifies the runoff traces of each water flow, calculates the surface runoff path connectivity and water distribution density of each residential area, and combines the two to construct a pollution carrying capacity factor that reflects the ability of surface hydrology to migrate and diffuse pollutants. The vegetation environment assessment module identifies vegetation cover data from the image and, in conjunction with near-ground suspended particulate matter concentration distribution data, calculates the air pollution level of each residential area and, based on a preset suspended particulate matter purification coefficient, calculates the basic pollution coefficient of each residential area. The pollution assessment and determination module corrects the basic pollution coefficient by using the pollution carrying capacity factor to obtain the final pollution coefficient of each residential area. Based on the attributes of each residential area, it assigns different emission weights, and performs a weighted summation of the final pollution coefficients of each residential area to output the comprehensive environmental pollution level of the residential area.

2. The residential environment monitoring platform based on UAV image acquisition as described in claim 1, characterized in that: The calculation process for the surface runoff path connectivity includes: The water flow is divided into segments to obtain each flow segment, and the water flow traces of each flow segment are obtained. Identify the maximum and minimum runoff widths from water flow traces, and simultaneously identify the maximum and minimum runoff depths; Calculate the ratio of the minimum runoff width to the maximum runoff width of each runoff segment as the width passage factor for that runoff segment. Similarly, calculate the depth passage factor for each runoff segment using the same method as the width ratio. The mean of the width passage coefficient and the depth passage coefficient of the corresponding runoff segment is calculated as the path passage capacity of each runoff segment. The minimum value is selected from the path passage capacity of all runoff segments of the water body and used as the path passage capacity of the corresponding water body. Identify the blocking areas on each runoff path, calculate the ratio of the total area of ​​all blocking areas in each runoff path to the surface area of ​​the runoff path, and obtain the blocking rate. The difference between 1 and the blocking rate is taken as the runoff flow rate of the corresponding water area. Multiply the connectivity rate by the path capacity of water flow to obtain the comprehensive path capacity of each water flow, and select the one with the largest comprehensive path capacity as the surface runoff path connectivity of the corresponding residential area.

3. The residential environment monitoring platform based on UAV image acquisition as described in claim 1, characterized in that: The calculation process for the water distribution density includes: For each residential area, the total surface water area and the total land area of ​​the residential area are obtained through GIS geographic map. The ratio of the total surface water area to the total land area of ​​the residential area is calculated to obtain the water distribution density of the corresponding residential area.

4. The residential environment monitoring platform based on UAV image acquisition as described in claim 1, characterized in that: The calculation process for the pollution carrying capacity factor includes: When the surface runoff path connectivity of a residential area is greater than the first preset connectivity threshold, the pollution carrying capacity factor of the corresponding residential area will be assigned a value of 1. When the surface runoff path connectivity of a residential area is greater than the second preset connectivity threshold and less than the first preset connectivity threshold, the water distribution density of each residential area is multiplied by the surface runoff path connectivity of the corresponding residential area to obtain the pollution carrying capacity factor of the corresponding residential area. The first preset connectivity threshold is greater than the second preset connectivity threshold. When the surface runoff path connectivity of a residential area is less than the second preset connectivity threshold, the pollution carrying capacity factor of the corresponding residential area will be assigned to 0.

5. The residential environment monitoring platform based on UAV image acquisition as described in claim 1, characterized in that: The calculation process for the air pollution level includes: Obtain the concentration distribution dataset of the target particle size range from the near-ground suspended particulate matter concentration distribution data of each residential area; Obtain the suspended particulate matter concentration for each target particle size from the concentration distribution dataset; Calculate the relative deviation between the suspended particulate matter concentration of each target particle size and the corresponding preset suspended particulate matter concentration threshold, and use the relative deviation as the pollution degree coefficient. The air pollution level of each residential area is obtained by weighted summation of the pollution degree coefficients for each target particle size.

6. The residential environment monitoring platform based on UAV image acquisition as described in claim 1, characterized in that: The calculation process for the basic pollution coefficient includes: Extract the actual planting area of ​​each vegetation type in each residential area from the vegetation cover data, and simultaneously retrieve the suspended particulate matter purification coefficient per unit area for each type of vegetation. The purification capacity of the vegetation in a residential area is obtained by multiplying the suspended particulate matter purification coefficient by the total actual planting area of ​​each type of vegetation in each residential area. The purification capacity of vegetation in each residential area is normalized to obtain a normalized purification capacity index. The air pollution level is corrected based on the purification capacity index to obtain the basic pollution coefficient for each residential area.

7. The residential environment monitoring platform based on UAV image acquisition as described in claim 1, characterized in that: The calculation process for the final pollution coefficient includes: The difference between 1 and the pollution carrying capacity factor is used as the weakening factor. The product of the weakening factor and the basic pollution coefficient of each residential area is calculated and used as the final pollution coefficient of the corresponding residential area.

8. The residential environment monitoring platform based on UAV image acquisition as described in claim 1, characterized in that: The calculation process for the comprehensive environmental pollution level includes: Obtain the attributes of each residential area, including at least living and production attributes; When the attribute of a residential area is solely for living purposes, the emission weight of the corresponding residential area will be assigned a value. ; When the only attribute of a residential area is production, the emission weight of the corresponding residential area is assigned a value of 1; When a residential area is classified as both living and production, the emission weight of the corresponding residential area is calculated by combining the proportion of living area and the proportion of production area. Based on the emission weights of each residential area, the final pollution coefficients of the corresponding areas are linearly weighted and summed to obtain the comprehensive environmental pollution level of the residential area.

9. The residential environment monitoring platform based on UAV image acquisition as described in claim 8, characterized in that: The calculation process for the emission weights of residential areas, which are defined as living and production areas, includes: Obtain the area of ​​each living area and each production area in the same residential area, and calculate the total area of ​​the living area and the total area of ​​the production area in each residential area. Calculate the ratios of the total area of ​​the living area and the total area of ​​the production area to the total land area of ​​the respective residential areas to obtain the proportions of the living area and the production area. Emission weights based solely on residential areas as defined by their attributes. The emission weight of a residential area is calculated by combining the emission weight of the residential area with the emission weight of the production area, which is 1, with the emission weight of the production area.

10. A method for monitoring living environment based on UAV image acquisition, characterized in that, The method includes: The system acquires images of water flow in each residential area of ​​the target residential area collected by drones, identifies the runoff traces of each water flow, calculates the surface runoff path connectivity and water distribution density of each residential area, and combines the two to construct a pollution carrying capacity factor that reflects the ability of surface hydrology to migrate and diffuse pollutants. Vegetation cover data is identified from the images, and combined with near-ground suspended particulate matter concentration distribution data, the air pollution level of each residential area is calculated, and the basic pollution coefficient of each residential area is calculated based on the preset suspended particulate matter purification coefficient. The baseline pollution coefficient is corrected by the pollution carrying capacity factor to obtain the final pollution coefficient of each residential area. Based on the attributes of each residential area, different emission weights are assigned, and the final pollution coefficients of each residential area are weighted and summed to output the comprehensive environmental pollution degree of the residential area.

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