City carbon tracking analysis method and system, and storage medium

Abstract

A city carbon tracking analysis method and system, and a storage medium. A three-dimensional visualization-based city model is constructed on the basis of basic information; region division is performed on a target city to form a plurality of city sub-regions; a carbon emission monitoring plan is formulated on the basis of city region characteristics; carbon emission change analysis within a preset period is performed on each city sub-region on the basis of obtained city monitoring data by using a linear regression method, and carbon emission change trend data of each city sub-region is obtained; carbon emission route tracking is performed on the basis of the carbon emission change trend data, and a current carbon tracking route and a carbon prediction route are formed by means of a preset ant colony algorithm; and a monitoring corrected plan is generated on the basis of the current carbon tracking route and the carbon prediction route. Accurate carbon emission analysis and carbon emission prediction for a certain region of a city is realized, accurate city carbon tracking is realized, and a scientific carbon monitoring plan is generated.

Description

Urban carbon tracking analysis method, system and storage medium

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS

[0002] This application claims priority to the Chinese patent application with application number 202311763901.1 filed with the Chinese Patent Office on December 21, 2023, entitled "A Method, System and Storage Medium for Urban Carbon Tracking Analysis," the entire contents of which are incorporated by reference into this application. Technical Field

[0003] The present invention relates to the field of carbon pollution analysis, and more specifically, to a city carbon tracking analysis method, system and storage medium. Background Art

[0004] With the acceleration of urbanization and the continuous development of industrial production, carbon emissions in cities are also increasing. The impact of carbon pollution on cities is becoming increasingly significant, not only affecting the health and quality of life of urban residents, but also posing a serious threat to the sustainable development of cities.

[0005] However, due to the limitations of traditional technologies, the current carbon emission analysis and pollution forecasting within cities are relatively weak. It is difficult to achieve accurate carbon emission analysis and carbon emission forecasting in certain areas of the city, and it is difficult to achieve accurate carbon tracking and scientific carbon monitoring in cities. Summary of the Invention

[0006] The present invention overcomes the defects of the prior art and proposes a city carbon tracking analysis method, system and storage medium.

[0007] A first aspect of the present invention provides a city carbon tracking and analysis method, comprising:

[0008] Obtaining basic information of a target city, and constructing a three-dimensional visualized city model based on the basic information;

[0009] Based on the regional information of the target city and combined with the urban model, the target city is divided into regions to form multiple urban sub-regions;

[0010] Formulate a carbon emission monitoring plan based on the regional characteristics of each urban sub-region, conduct urban monitoring based on the monitoring plan, and obtain urban monitoring data within a preset period;

[0011] Based on the urban monitoring data, a carbon emission change analysis is conducted for each urban sub-region within a preset period, the change analysis is based on a linear regression method, and carbon emission change trend data for each urban sub-region is obtained;

[0012] Tracking the carbon emission route based on the carbon emission change trend data, and combining it with a preset ant colony algorithm to form a current carbon tracking route and a carbon prediction route;

[0013] A monitoring correction plan is generated based on the current carbon tracking route and the carbon prediction route.

[0014] In this solution, the basic information of the target city is obtained, and a three-dimensional visualized city model is constructed based on the basic information, specifically:

[0015] Obtaining basic information of the target city, including city map outline, city area, and city region information;

[0016] The urban area information includes the distribution information of urban industrial, agricultural and residential areas;

[0017] Constructing a city model according to the city map outline and the city area;

[0018] The urban area information is imported into the urban model for regional division to form three major areas: industry, agriculture, and residential areas.

[0019] In this solution, based on the regional information of the target city and combined with the city model, the target city is divided into regions to form multiple urban sub-regions, specifically:

[0020] Based on the urban model, the three major areas of industry, agriculture and residential areas are divided into sub-regions;

[0021] The division is based on the distribution density of industry, agriculture and residence to obtain N urban sub-areas;

[0022] The N urban sub-regions include an industrial sub-region, an agricultural sub-region, and a residential sub-region, and the area and shape of the urban sub-region are within a preset range.

[0023] In this solution, a carbon emission monitoring plan is formulated based on the regional characteristics of each urban sub-region, and urban monitoring is carried out based on the monitoring plan to obtain urban monitoring data within a preset period, specifically:

[0024] Based on urban area information and combined with urban models, the distribution density of urban industrial, agricultural and residential areas is analyzed to obtain the distribution density information of urban industrial, agricultural and residential areas;

[0025] Based on the industrial, agricultural, and residential density information of the city and in combination with the city model, the number and distribution of carbon pollution monitoring points in multiple urban sub-regions are analyzed to obtain a carbon emission monitoring plan;

[0026] Conduct urban carbon monitoring according to the carbon emission monitoring plan and obtain urban monitoring data within a preset period;

[0027] The city monitoring data includes a plurality of sub-region monitoring data.

[0028] In this solution, based on the city monitoring data, the carbon emission change analysis within a preset period is performed for each urban sub-region. The change analysis is based on the linear regression method, and the carbon emission change trend data of each urban sub-region is obtained, specifically:

[0029] Taking a city sub-region as the analysis unit, the corresponding sub-region monitoring data is obtained from the city monitoring data;

[0030] Performing a linear change analysis on carbon emissions based on the sub-region monitoring data to obtain a first carbon emissions change curve for a city sub-region in a current preset period;

[0031] According to the first carbon emission change curve graph, data prediction is performed based on a linear regression prediction method to form a prediction curve for the next cycle, which is marked as a second carbon emission change curve graph;

[0032] Analyze all urban sub-regions and obtain a first carbon emission change curve graph and a second carbon emission change curve graph for each urban sub-region;

[0033] The carbon emission change trend data includes a first carbon emission change curve graph and a second carbon emission change curve graph.

[0034] In this solution, the carbon emission route tracking is performed based on the carbon emission change trend data, and a preset ant colony algorithm is combined to form a current carbon tracking route and a carbon prediction route, which previously includes:

[0035] A city sub-region is used as the unit of analysis and is labeled as the current sub-region;

[0036] Calculate the average change curvature of the first carbon emission change curve of the current sub-region according to the curve, and use the average change curvature as the change trend index;

[0037] Based on the city model, obtain K neighboring sub-regions of the current sub-region;

[0038] Calculate the change trend index of each adjacent sub-region and obtain K change trend indices;

[0039] Taking the current sub-region change trend index as the benchmark value and combining it with the preset maximum deviation value, a reasonable change range for the current sub-region is constructed;

[0040] The values ​​of K change trend indices that meet the reasonable change interval are screened and extracted, and the adjacent sub-regions corresponding to the change trend indices that meet the interval are marked as correlation sub-regions;

[0041] Among all the correlation sub-areas, the sub-areas with the largest and smallest change trend indices are screened to obtain the first sub-area and the second sub-area respectively;

[0042] Sequentially connect the first sub-region, the current sub-region, and the second sub-region to form a carbon emission tracking direction for the current sub-region;

[0043] Analyze all urban sub-regions and obtain the carbon emission tracking direction of each urban sub-region.

[0044] In this solution, the carbon emission route tracking based on the carbon emission change trend data is combined with a preset ant colony algorithm to form a current carbon tracking route and a carbon prediction route, and further includes:

[0045] Based on the carbon emission tracking direction of each urban sub-region, an overall carbon tracking direction analysis is conducted through the urban model, and a city carbon tracking route is formed;

[0046] Obtain a second carbon emission change curve graph for all urban sub-regions, calculate a corresponding change trend index based on the second carbon emission change curve graph, and mark the change trend index calculated based on the second carbon emission change curve graph as a predicted carbon trend index;

[0047] Based on all urban sub-regions, obtain corresponding N predicted carbon trend indices;

[0048] According to the city model, a path model based on ant colony algorithm is constructed. In the path model, sub-regions are used as the movement path units.

[0049] N pheromone gain amounts are calculated based on N predicted carbon trend indices, and the pheromone gain amounts are proportional to the predicted carbon trend indices;

[0050] Determine the predicted carbon trend index of the urban sub-regions, screen the urban sub-regions whose predicted carbon trend index is lower than the preset minimum index, and mark them as starting sub-regions;

[0051] In the path model based on the ant colony algorithm, the starting point sub-area is used as the starting point of the ants, and the same preset data volume of ants is set at each starting point to initialize the pheromone of each moving path unit;

[0052] Based on N pheromone gains, perform pheromone secondary initialization on each moving path unit;

[0053] The ant colony path simulation is repeated multiple times and the path pheromone is updated in real time until the optimal path is formed. The optimal path is marked in combination with the city model to obtain the city carbon prediction route.

[0054] In this solution, the monitoring correction plan is generated based on the current carbon tracking route and the carbon prediction route, specifically:

[0055] According to the carbon tracking route, the carbon emission movement trend of each urban sub-region is analyzed, and based on the carbon emission movement trend, the carbon emission impact rating of each urban sub-region is obtained. The higher the rating, the greater the carbon emission impact;

[0056] Based on the urban sub-regions and their corresponding ratings, the number and distribution of secondary carbon pollution monitoring points in multiple urban sub-regions are analyzed, and the carbon emission monitoring plan is dynamically revised to generate a carbon emission monitoring revision plan for the next preset period;

[0057] Based on the carbon prediction route and combined with the urban model, carbon pollution prediction analysis and control index generation are carried out for the three major areas of industry, agriculture, and residential in the city, and control index information corresponding to the three major areas of industry, agriculture, and residential is obtained.

[0058] A second aspect of the present invention further provides a city carbon tracking and analysis system, comprising: a memory and a processor, wherein the memory includes a city carbon tracking and analysis program, and when the city carbon tracking and analysis program is executed by the processor, the following steps are implemented:

[0059] Obtaining basic information of a target city, and constructing a three-dimensional visualized city model based on the basic information;

[0060] Based on the regional information of the target city and combined with the urban model, the target city is divided into regions to form multiple urban sub-regions;

[0061] Formulate a carbon emission monitoring plan based on the regional characteristics of each urban sub-region, conduct urban monitoring based on the monitoring plan, and obtain urban monitoring data within a preset period;

[0062] Based on the urban monitoring data, a carbon emission change analysis is conducted for each urban sub-region within a preset period, the change analysis is based on a linear regression method, and carbon emission change trend data for each urban sub-region is obtained;

[0063] Tracking the carbon emission route based on the carbon emission change trend data, and combining it with a preset ant colony algorithm to form a current carbon tracking route and a carbon prediction route;

[0064] A monitoring correction plan is generated based on the current carbon tracking route and the carbon prediction route.

[0065] The third aspect of the present invention further provides a computer-readable storage medium, which includes a city carbon tracking analysis program. When the city carbon tracking analysis program is executed by a processor, it implements the steps of the city carbon tracking analysis method as described in any one of the above items.

[0066] The present invention discloses a city carbon tracking and analysis method, system, and storage medium. A city model based on three-dimensional visualization is constructed based on basic information; the target city is divided into regions to form multiple city sub-regions; a carbon emission monitoring plan is formulated based on the nature of the city region, and based on the acquired city monitoring data, a carbon emission change analysis is performed on each city sub-region within a preset period. The change analysis is based on a linear regression method, and carbon emission change trend data for each city sub-region is obtained; carbon emission routes are tracked based on the carbon emission change trend data, and a current carbon tracking route and a carbon prediction route are formed in combination with a preset ant colony algorithm; a monitoring correction plan is generated based on the current carbon tracking route and the carbon prediction route. Through the present invention, precise carbon emission analysis and carbon emission prediction of a certain area of ​​the city are achieved, and precise carbon tracking and scientific carbon monitoring plans are generated for the city. BRIEF DESCRIPTION OF THE DRAWINGS

[0067] FIG1 shows a flow chart of a city carbon tracking and analysis method according to the present invention;

[0068] FIG2 shows a flow chart of constructing a city model according to the present invention;

[0069] FIG3 shows a flow chart of the city sub-region division according to the present invention;

[0070] FIG4 shows a block diagram of a city carbon tracking and analysis system according to the present invention. DETAILED DESCRIPTION

[0071] In order to more clearly understand the above-mentioned objects, features and advantages of the present invention, the present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be noted that, in the absence of conflict, the embodiments of the present application and the features therein can be combined with each other.

[0072] In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention may also be implemented in other ways different from those described herein. Therefore, the scope of protection of the present invention is not limited to the specific embodiments disclosed below.

[0073] FIG1 shows a flow chart of a city carbon tracking and analysis method according to the present invention.

[0074] As shown in FIG1 , the first aspect of the present invention provides a city carbon tracking analysis method, comprising:

[0075] S102, obtaining basic information of a target city, and constructing a three-dimensional visualized city model based on the basic information;

[0076] S104, based on the regional information of the target city and in combination with the city model, the target city is divided into regions to form multiple city sub-regions;

[0077] S106, formulating a carbon emission monitoring plan based on the regional characteristics of each urban sub-region, performing urban monitoring based on the monitoring plan, and obtaining urban monitoring data within a preset period;

[0078] S108, performing a carbon emission change analysis for each urban sub-region within a preset period based on the urban monitoring data, using a linear regression method to obtain carbon emission change trend data for each urban sub-region;

[0079] S110, tracking the carbon emission route based on the carbon emission change trend data, and forming a current carbon tracking route and a carbon prediction route by combining a preset ant colony algorithm;

[0080] S112: Generate a monitoring correction plan based on the current carbon tracking route and the carbon prediction route.

[0081] It should be noted that the city model is a visual data carrier, and subsequent carbon tracking routes and other analytical data can be visualized through the city model.

[0082] FIG2 shows a flow chart of constructing a city model according to the present invention.

[0083] According to an embodiment of the present invention, obtaining basic information of a target city and constructing a three-dimensional visualized city model based on the basic information specifically includes:

[0084] S202, obtaining basic information of the target city, wherein the basic information includes a city map outline, city area, and city region information;

[0085] S204, the urban area information includes distribution information of urban industrial, agricultural, and residential areas;

[0086] S206, constructing a city model based on the city map outline and the city area;

[0087] S208: Import the urban area information into the urban model for regional division to form three major areas: industrial, agricultural, and residential areas.

[0088] It should be noted that in the map model, the distribution information of urban industrial, agricultural and residential areas can be visualized, allowing users to more intuitively understand urban carbon pollution.

[0089] FIG3 shows a flow chart of the urban sub-region division according to the present invention.

[0090] According to an embodiment of the present invention, the target city is divided into regions based on the regional information of the target city in combination with the city model to form multiple city sub-regions, specifically:

[0091] S302, based on the urban model, divide the three major areas of industry, agriculture and residential into sub-areas;

[0092] S304, the division is based on the distribution density of industry, agriculture, and residence to obtain N urban sub-regions;

[0093] S306, the N urban sub-regions include industrial sub-regions, agricultural sub-regions, and residential sub-regions, and the areas and shapes of the urban sub-regions are within a preset range.

[0094] It should be noted that the preset range includes the area range and shape limitation criteria. By dividing the sub-regions, it is possible to conduct precise monitoring and carbon tracking analysis of the city.

[0095] According to an embodiment of the present invention, formulating a carbon emission monitoring plan based on the regional properties of each urban sub-region, performing urban monitoring based on the monitoring plan, and obtaining urban monitoring data within a preset period are specifically as follows:

[0096] Based on urban area information and combined with urban models, the distribution density of urban industrial, agricultural and residential areas is analyzed to obtain the distribution density information of urban industrial, agricultural and residential areas;

[0097] Based on the industrial, agricultural, and residential density information of the city and in combination with the city model, the number and distribution of carbon pollution monitoring points in multiple urban sub-regions are analyzed to obtain a carbon emission monitoring plan;

[0098] Conduct urban carbon monitoring according to the carbon emission monitoring plan and obtain urban monitoring data within a preset period;

[0099] The city monitoring data includes a plurality of sub-region monitoring data.

[0100] It should be noted that the distribution density information includes the unit density distribution corresponding to industry, agriculture, and residence. For example, the industrial distribution density corresponds to the density distribution of factories in the region, the agricultural distribution density corresponds to the density distribution of urban planting areas, and the residential distribution density corresponds to the residential unit density and population density distribution. The carbon emission monitoring plan includes the number and distribution of carbon monitoring equipment. An urban sub-region includes at least one carbon monitoring device. The specific number is determined by the analysis of the urban industrial, agricultural, and residential distribution density information. For example, in an urban sub-region (set as an industrial sub-region), the greater the industrial distribution density, the more monitoring equipment there is. The carbon monitoring equipment mainly monitors pollutants such as carbon dioxide (CO2), methane (CH4), nitrous oxide (N2O), and carbon monoxide (CO) in the air.

[0101] According to an embodiment of the present invention, based on the city monitoring data, a carbon emission change analysis is performed on each urban sub-region within a preset period. The change analysis is based on a linear regression method, and carbon emission change trend data for each urban sub-region is obtained, specifically:

[0102] Taking a city sub-region as the analysis unit, the corresponding sub-region monitoring data is obtained from the city monitoring data;

[0103] Performing a linear change analysis on carbon emissions based on the sub-region monitoring data to obtain a first carbon emissions change curve for a city sub-region in a current preset period;

[0104] According to the first carbon emission change curve graph, data prediction is performed based on a linear regression prediction method to form a prediction curve for the next cycle, which is marked as a second carbon emission change curve graph;

[0105] Analyze all urban sub-regions and obtain a first carbon emission change curve graph and a second carbon emission change curve graph for each urban sub-region;

[0106] The carbon emission change trend data includes a first carbon emission change curve graph and a second carbon emission change curve graph.

[0107] It should be noted that the preset cycle duration is set by the user.

[0108] According to an embodiment of the present invention, the carbon emission route tracking based on the carbon emission change trend data is combined with a preset ant colony algorithm to form a current carbon tracking route and a carbon prediction route, which includes:

[0109] A city sub-region is used as the unit of analysis and is labeled as the current sub-region;

[0110] Calculate the average change curvature of the first carbon emission change curve of the current sub-region according to the curve, and use the average change curvature as the change trend index;

[0111] Based on the city model, obtain K neighboring sub-regions of the current sub-region;

[0112] Calculate the change trend index of each adjacent sub-region and obtain K change trend indices;

[0113] Taking the current sub-region change trend index as the benchmark value and combining it with the preset maximum deviation value, a reasonable change range for the current sub-region is constructed;

[0114] The values ​​of K change trend indices that meet the reasonable change interval are screened and extracted, and the adjacent sub-regions corresponding to the change trend indices that meet the interval are marked as correlation sub-regions;

[0115] Among all the correlation sub-areas, the sub-areas with the largest and smallest change trend indices are screened to obtain the first sub-area and the second sub-area respectively;

[0116] Sequentially connect the first sub-region, the current sub-region, and the second sub-region to form a carbon emission tracking direction for the current sub-region;

[0117] Analyze all urban sub-regions and obtain the carbon emission tracking direction of each urban sub-region.

[0118] It should be noted that the adjacent sub-region is the region adjacent to the current sub-region, that is, the surrounding area. The average change curvature is specifically to select a preset number of curve points to calculate the curvature and average the data. The reasonable change interval uses the reference value as the middle value of the interval, and the positive and negative preset maximum deviation values ​​of the reference value as the maximum and minimum values ​​of the interval. The first sub-region and the second sub-region are sub-regions with consistent change trends with the current sub-region, and have a certain difference in change trends. The present invention analyzes the change trend within a preset period and selects the corresponding related sub-regions for connection. It can obtain a carbon emission tracking route that accurately reflects the current sub-region, and through the calculation and analysis of the change trend index, it can propose non-correlated sub-regions to achieve accurate carbon emission tracking analysis of the sub-regions.

[0119] The direction obtained by sequentially connecting the first sub-region, the current sub-region, and the second sub-region corresponds to a route direction with starting point and focus attributes. For example, when the first sub-region and the second sub-region are the upper and lower regions of the current sub-region respectively, the route direction is from top to bottom, corresponding to the route of carbon emissions.

[0120] According to an embodiment of the present invention, the carbon emission route tracking based on the carbon emission change trend data, combined with a preset ant colony algorithm to form a current carbon tracking route and a carbon prediction route, further includes:

[0121] Based on the carbon emission tracking direction of each urban sub-region, an overall carbon tracking direction analysis is conducted through the urban model, and a city carbon tracking route is formed;

[0122] Obtain a second carbon emission change curve graph for all urban sub-regions, calculate a corresponding change trend index based on the second carbon emission change curve graph, and mark the change trend index calculated based on the second carbon emission change curve graph as a predicted carbon trend index;

[0123] Based on all urban sub-regions, obtain corresponding N predicted carbon trend indices;

[0124] According to the city model, a path model based on ant colony algorithm is constructed. In the path model, sub-regions are used as the movement path units.

[0125] N pheromone gain amounts are calculated based on N predicted carbon trend indices, and the pheromone gain amounts are proportional to the predicted carbon trend indices;

[0126] Determine the predicted carbon trend index of the urban sub-regions, screen the urban sub-regions whose predicted carbon trend index is lower than the preset minimum index, and mark them as starting sub-regions;

[0127] In the path model based on the ant colony algorithm, the starting point sub-area is used as the starting point of the ants, and the same preset data volume of ants is set at each starting point to initialize the pheromone of each moving path unit;

[0128] Based on N pheromone gains, perform pheromone secondary initialization on each moving path unit;

[0129] The ant colony path simulation is repeated multiple times and the path pheromone is updated in real time until the optimal path is formed. The optimal path is marked in combination with the city model to obtain the city carbon prediction route.

[0130] It should be noted that the pheromone gain is equal to the predicted carbon trend index multiplied by a preset correction coefficient. The pheromone secondary initialization is to perform pheromone gain on each moving path unit, and the gain amount is the pheromone gain amount. Each urban sub-region corresponds to a predicted carbon trend index, a moving path unit, and a pheromone gain amount. The present invention is based on the path model of the (improved) ant colony algorithm, which sets multiple starting points but does not set an end point to simulate the movement law and movement trend of predicted carbon emissions in different moving paths. Furthermore, by means of pheromone gain, the initial path selection of each sub-region is changed, which can be more in line with the actual trend of the carbon emission tracking path in each area of ​​the actual city, thereby obtaining a high-precision prediction route, and the pheromone gain is related to the predicted carbon trend index. In addition, the model parameters and corresponding initialization parameters can be adjusted in real time under different cycles to adapt to different urban carbon emission conditions.

[0131] In the present invention, the carbon tracking route is obtained based on the current monitoring data and is used to evaluate the real-time impact of current carbon emissions, while the carbon prediction route is obtained based on the analysis of the predicted data. It is a prediction route used to evaluate the impact on future carbon emissions and provide data support for corresponding urban carbon pollution planning and management.

[0132] Through the present invention, the efficiency of carbon emission monitoring can be improved, the monitoring cost of the city can be reduced, the monitoring and analysis accuracy can be improved, and a more accurate tracking and analysis of the city's carbon trends can be achieved, further realizing the scientific management of the city's carbon emissions.

[0133] According to an embodiment of the present invention, the generation of a monitoring correction plan based on the current carbon tracking route and the carbon prediction route is specifically as follows:

[0134] According to the carbon tracking route, the carbon emission movement trend of each urban sub-region is analyzed, and based on the carbon emission movement trend, the carbon emission impact rating of each urban sub-region is obtained. The higher the rating, the greater the carbon emission impact;

[0135] Based on the urban sub-regions and their corresponding ratings, the number and distribution of secondary carbon pollution monitoring points in multiple urban sub-regions are analyzed, and the carbon emission monitoring plan is dynamically revised to generate a carbon emission monitoring revision plan for the next preset period;

[0136] Based on the carbon prediction route and combined with the urban model, carbon pollution prediction analysis and control index generation are carried out for the three major areas of industry, agriculture, and residential in the city, and control index information corresponding to the three major areas of industry, agriculture, and residential is obtained.

[0137] It should be noted that the carbon emission impact rating of each urban sub-region has a higher level, the greater the carbon emission impact, and the corresponding carbon pollution is more serious. The carbon emission movement trend of each urban sub-region is analyzed, that is, through the carbon tracking route, which sub-regions are more likely to accumulate carbon pollutants and which sub-regions are not easily affected by carbon emissions. The carbon prediction route can, to a certain extent, reflect the future trend of the city's carbon emissions, and based on this trend, it can scientifically and reasonably regulate the city's carbon emissions and generate carbon emission indicators, forming scientific, effective and practical regulation indicator information. Based on the complex situation of the city, urban regulation indicators and regulation plans can be obtained by combining the current carbon emission monitoring data analysis. Through the regulation indicator information, it is possible to scientifically and effectively achieve a gradual reduction in urban carbon emissions and carry out effective regulation step by step.

[0138] FIG4 shows a block diagram of a city carbon tracking and analysis system according to the present invention.

[0139] A second aspect of the present invention further provides a city carbon tracking and analysis system 4, comprising: a memory 41 and a processor 42. The memory includes a city carbon tracking and analysis program, and when the city carbon tracking and analysis program is executed by the processor, the following steps are implemented:

[0140] Obtaining basic information of a target city, and constructing a three-dimensional visualized city model based on the basic information;

[0141] Based on the regional information of the target city and combined with the urban model, the target city is divided into regions to form multiple urban sub-regions;

[0142] Formulate a carbon emission monitoring plan based on the regional characteristics of each urban sub-region, conduct urban monitoring based on the monitoring plan, and obtain urban monitoring data within a preset period;

[0143] Based on the urban monitoring data, a carbon emission change analysis is conducted for each urban sub-region within a preset period, the change analysis is based on a linear regression method, and carbon emission change trend data for each urban sub-region is obtained;

[0144] Tracking the carbon emission route based on the carbon emission change trend data, and combining it with a preset ant colony algorithm to form a current carbon tracking route and a carbon prediction route;

[0145] A monitoring correction plan is generated based on the current carbon tracking route and the carbon prediction route.

[0146] It should be noted that the city model is a visual data carrier, and subsequent carbon tracking routes and other analytical data can be visualized through the city model.

[0147] According to an embodiment of the present invention, obtaining basic information of a target city and constructing a three-dimensional visualized city model based on the basic information specifically includes:

[0148] Obtaining basic information of the target city, including city map outline, city area, and city region information;

[0149] The urban area information includes the distribution information of urban industrial, agricultural and residential areas;

[0150] Constructing a city model according to the city map outline and the city area;

[0151] The urban area information is imported into the urban model for regional division to form three major areas: industry, agriculture, and residential areas.

[0152] It should be noted that in the map model, the distribution information of urban industrial, agricultural and residential areas can be visualized, allowing users to more intuitively understand urban carbon pollution.

[0153] According to an embodiment of the present invention, the target city is divided into regions based on the regional information of the target city in combination with the city model to form multiple city sub-regions, specifically:

[0154] Based on the urban model, the three major areas of industry, agriculture and residential areas are divided into sub-regions;

[0155] The division is based on the distribution density of industry, agriculture and residence to obtain N urban sub-areas;

[0156] The N urban sub-regions include an industrial sub-region, an agricultural sub-region, and a residential sub-region, and the area and shape of the urban sub-region are within a preset range.

[0157] It should be noted that the preset range includes the area range and shape limitation criteria. By dividing the sub-regions, it is possible to conduct precise monitoring and carbon tracking analysis of the city.

[0158] According to an embodiment of the present invention, formulating a carbon emission monitoring plan based on the regional properties of each urban sub-region, performing urban monitoring based on the monitoring plan, and obtaining urban monitoring data within a preset period are specifically as follows:

[0159] Based on urban area information and combined with urban models, the distribution density of urban industrial, agricultural and residential areas is analyzed to obtain the distribution density information of urban industrial, agricultural and residential areas;

[0160] Based on the industrial, agricultural, and residential density information of the city and in combination with the city model, the number and distribution of carbon pollution monitoring points in multiple urban sub-regions are analyzed to obtain a carbon emission monitoring plan;

[0161] Conduct urban carbon monitoring according to the carbon emission monitoring plan and obtain urban monitoring data within a preset period;

[0162] The city monitoring data includes a plurality of sub-region monitoring data.

[0163] It should be noted that the distribution density information includes the unit density distribution corresponding to industry, agriculture, and residence. For example, the industrial distribution density corresponds to the density distribution of factories in the region, the agricultural distribution density corresponds to the density distribution of urban planting areas, and the residential distribution density corresponds to the residential unit density and population density distribution. The carbon emission monitoring plan includes the number and distribution of carbon monitoring equipment. An urban sub-region includes at least one carbon monitoring device. The specific number is determined by the analysis of the urban industrial, agricultural, and residential distribution density information. For example, in an urban sub-region (set as an industrial sub-region), the greater the industrial distribution density, the more monitoring equipment there is. The carbon monitoring equipment mainly monitors pollutants such as carbon dioxide (CO2), methane (CH4), nitrous oxide (N2O), and carbon monoxide (CO) in the air.

[0164] According to an embodiment of the present invention, based on the city monitoring data, a carbon emission change analysis is performed on each urban sub-region within a preset period. The change analysis is based on a linear regression method, and carbon emission change trend data for each urban sub-region is obtained, specifically:

[0165] Taking a city sub-region as the analysis unit, the corresponding sub-region monitoring data is obtained from the city monitoring data;

[0166] Performing a linear change analysis on carbon emissions based on the sub-region monitoring data to obtain a first carbon emissions change curve for a city sub-region in a current preset period;

[0167] According to the first carbon emission change curve graph, data prediction is performed based on a linear regression prediction method to form a prediction curve for the next cycle, which is marked as a second carbon emission change curve graph;

[0168] Analyze all urban sub-regions and obtain a first carbon emission change curve graph and a second carbon emission change curve graph for each urban sub-region;

[0169] The carbon emission change trend data includes a first carbon emission change curve graph and a second carbon emission change curve graph.

[0170] It should be noted that the preset cycle duration is set by the user.

[0171] According to an embodiment of the present invention, the carbon emission route tracking based on the carbon emission change trend data is combined with a preset ant colony algorithm to form a current carbon tracking route and a carbon prediction route, which includes:

[0172] A city sub-region is used as the unit of analysis and is labeled as the current sub-region;

[0173] Calculate the average change curvature of the first carbon emission change curve of the current sub-region according to the curve, and use the average change curvature as the change trend index;

[0174] Based on the city model, obtain K neighboring sub-regions of the current sub-region;

[0175] Calculate the change trend index of each adjacent sub-region and obtain K change trend indices;

[0176] Taking the current sub-region change trend index as the benchmark value and combining it with the preset maximum deviation value, a reasonable change range for the current sub-region is constructed;

[0177] The values ​​of K change trend indices that meet the reasonable change interval are screened and extracted, and the adjacent sub-regions corresponding to the change trend indices that meet the interval are marked as correlation sub-regions;

[0178] Among all the correlation sub-areas, the sub-areas with the largest and smallest change trend indices are screened to obtain the first sub-area and the second sub-area respectively;

[0179] Sequentially connect the first sub-region, the current sub-region, and the second sub-region to form a carbon emission tracking direction for the current sub-region;

[0180] Analyze all urban sub-regions and obtain the carbon emission tracking direction of each urban sub-region.

[0181] It should be noted that the adjacent sub-region is the region adjacent to the current sub-region, that is, the surrounding area. The average change curvature is specifically to select a preset number of curve points to calculate the curvature and average the data. The reasonable change interval uses the reference value as the middle value of the interval, and the positive and negative preset maximum deviation values ​​of the reference value as the maximum and minimum values ​​of the interval. The first sub-region and the second sub-region are sub-regions with consistent change trends with the current sub-region, and have a certain difference in change trends. The present invention analyzes the change trend within a preset period and selects the corresponding related sub-regions for connection. It can obtain a carbon emission tracking route that accurately reflects the current sub-region, and through the calculation and analysis of the change trend index, it can propose non-correlated sub-regions to achieve accurate carbon emission tracking analysis of the sub-regions.

[0182] The direction obtained by sequentially connecting the first sub-region, the current sub-region, and the second sub-region corresponds to a route direction with starting point and focus attributes. For example, when the first sub-region and the second sub-region are the upper and lower regions of the current sub-region respectively, the route direction is from top to bottom, corresponding to the route of carbon emissions.

[0183] According to an embodiment of the present invention, the carbon emission route tracking based on the carbon emission change trend data, combined with a preset ant colony algorithm to form a current carbon tracking route and a carbon prediction route, further includes:

[0184] Based on the carbon emission tracking direction of each urban sub-region, an overall carbon tracking direction analysis is conducted through the urban model, and a city carbon tracking route is formed;

[0185] Obtain a second carbon emission change curve graph for all urban sub-regions, calculate a corresponding change trend index based on the second carbon emission change curve graph, and mark the change trend index calculated based on the second carbon emission change curve graph as a predicted carbon trend index;

[0186] Based on all urban sub-regions, obtain corresponding N predicted carbon trend indices;

[0187] According to the city model, a path model based on ant colony algorithm is constructed. In the path model, sub-regions are used as the movement path units.

[0188] N pheromone gain amounts are calculated based on N predicted carbon trend indices, and the pheromone gain amounts are proportional to the predicted carbon trend indices;

[0189] Determine the predicted carbon trend index of the urban sub-regions, screen the urban sub-regions whose predicted carbon trend index is lower than the preset minimum index, and mark them as starting sub-regions;

[0190] In the path model based on the ant colony algorithm, the starting point sub-area is used as the starting point of the ants, and the same preset data volume of ants is set at each starting point to initialize the pheromone of each moving path unit;

[0191] Based on N pheromone gains, perform pheromone secondary initialization on each moving path unit;

[0192] The ant colony path simulation is repeated multiple times and the path pheromone is updated in real time until the optimal path is formed. The optimal path is marked in combination with the city model to obtain the city carbon prediction route.

[0193] It should be noted that the pheromone gain is equal to the predicted carbon trend index multiplied by a preset correction coefficient. The pheromone secondary initialization is to perform pheromone gain on each moving path unit, and the gain amount is the pheromone gain amount. Each urban sub-region corresponds to a predicted carbon trend index, a moving path unit, and a pheromone gain amount. The present invention is based on the path model of the ant colony algorithm, and by setting multiple starting points and not setting end points, it is used to simulate the movement patterns and movement trends of predicted carbon emissions in different moving paths. Furthermore, by means of pheromone gain, the initial path selection of each sub-region is changed, which can be more in line with the actual trend of the carbon emission tracking path in each area of ​​the actual city, thereby obtaining a highly accurate predicted route, and the pheromone gain is related to the predicted carbon trend index. In addition, the model parameters and corresponding initialization parameters can be adjusted in real time under different cycles to adapt to different urban carbon emission conditions.

[0194] In the present invention, the carbon tracking route is obtained based on the current monitoring data and is used to evaluate the real-time impact of current carbon emissions, while the carbon prediction route is obtained based on the analysis of the predicted data. It is a prediction route used to evaluate the impact on future carbon emissions and provide data support for corresponding urban carbon pollution planning and management.

[0195] Through the present invention, the efficiency of carbon emission monitoring can be improved, the monitoring cost of the city can be reduced, the monitoring and analysis accuracy can be improved, and a more accurate tracking and analysis of the city's carbon trends can be achieved, further realizing the scientific management of the city's carbon emissions.

[0196] According to an embodiment of the present invention, the generation of a monitoring correction plan based on the current carbon tracking route and the carbon prediction route is specifically as follows:

[0197] According to the carbon tracking route, the carbon emission movement trend of each urban sub-region is analyzed, and based on the carbon emission movement trend, the carbon emission impact rating of each urban sub-region is obtained. The higher the rating, the greater the carbon emission impact;

[0198] Based on the urban sub-regions and their corresponding ratings, the number and distribution of secondary carbon pollution monitoring points in multiple urban sub-regions are analyzed, and the carbon emission monitoring plan is dynamically revised to generate a carbon emission monitoring revision plan for the next preset period;

[0199] Based on the carbon prediction route and combined with the urban model, carbon pollution prediction analysis and control index generation are carried out for the three major areas of industry, agriculture, and residential in the city, and control index information corresponding to the three major areas of industry, agriculture, and residential is obtained.

[0200] It should be noted that the carbon emission impact rating of each urban sub-region has a higher level, the greater the carbon emission impact, and the corresponding carbon pollution is more serious. The carbon emission movement trend of each urban sub-region is analyzed, that is, through the carbon tracking route, which sub-regions are more likely to accumulate carbon pollutants and which sub-regions are not easily affected by carbon emissions. The carbon prediction route can, to a certain extent, reflect the future trend of the city's carbon emissions, and based on this trend, it can scientifically and reasonably regulate the city's carbon emissions and generate carbon emission indicators, forming scientific, effective and practical regulation indicator information. Based on the complex situation of the city, urban regulation indicators and regulation plans can be obtained by combining the current carbon emission monitoring data analysis. Through the regulation indicator information, it is possible to scientifically and effectively achieve a gradual reduction in urban carbon emissions and carry out effective regulation step by step.

[0201] The third aspect of the present invention further provides a computer-readable storage medium, which includes a city carbon tracking analysis program. When the city carbon tracking analysis program is executed by a processor, it implements the steps of the city carbon tracking analysis method as described in any one of the above items.

[0202] The present invention discloses a city carbon tracking and analysis method, system, and storage medium. A city model based on three-dimensional visualization is constructed based on basic information; the target city is divided into regions to form multiple city sub-regions; a carbon emission monitoring plan is formulated based on the nature of the city region, and based on the acquired city monitoring data, a carbon emission change analysis is performed on each city sub-region within a preset period. The change analysis is based on a linear regression method, and carbon emission change trend data for each city sub-region is obtained; carbon emission routes are tracked based on the carbon emission change trend data, and a current carbon tracking route and a carbon prediction route are formed in combination with a preset ant colony algorithm; a monitoring correction plan is generated based on the current carbon tracking route and the carbon prediction route. Through the present invention, precise carbon emission analysis and carbon emission prediction of a certain area of ​​the city are achieved, and precise carbon tracking and scientific carbon monitoring plans are generated for the city.

[0203] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are merely schematic. For example, the division of the units is merely a logical function division. In actual implementation, there may be other division methods, such as: multiple units or components can be combined, or can be integrated into another system, or some features can be ignored or not executed. In addition, the coupling, direct coupling, or communication connection between the components shown or discussed can be through some interfaces, and the indirect coupling or communication connection of the devices or units can be electrical, mechanical or other forms.

[0204] The units described above as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units; they may be located in one place or distributed across multiple network units; some or all of the units may be selected according to actual needs to achieve the purpose of the scheme of this embodiment.

[0205] In addition, all functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may be separately used as a unit, or two or more units may be integrated into one unit; the above-mentioned integrated units may be implemented in the form of hardware or in the form of hardware plus software functional units.

[0206] Those skilled in the art will appreciate that all or part of the steps of the above-mentioned method embodiments may be implemented by hardware associated with program instructions, and the aforementioned program may be stored in a computer-readable storage medium. When the program is executed, the program executes the steps of the above-mentioned method embodiments. The aforementioned storage medium includes various media that can store program codes, such as mobile storage devices, read-only memories (ROMs), random access memories (RAMs), magnetic disks, or optical disks.

[0207] Alternatively, if the above-mentioned integrated unit of the present invention is implemented in the form of a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the embodiment of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes a number of instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the methods described in each embodiment of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as mobile storage devices, ROM, RAM, magnetic disks or optical disks.

[0208] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any modifications or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be based on the scope of protection of the claims.

Claims

1. A city carbon tracking analysis method, characterized in that: include: Obtaining basic information of a target city, and constructing a three-dimensional visualized city model based on the basic information; Based on the regional information of the target city and combined with the city model, the target city is divided into regions to form multiple urban sub-regions; Based on the regional characteristics of each urban sub-region, a carbon emission monitoring plan is formulated, and based on the monitoring plan, urban monitoring is performed and urban monitoring data within a preset period is obtained; Based on the city monitoring data, a carbon emission change analysis is performed on each city sub-region within a preset period, the change analysis is based on a linear regression method, and the carbon emission change trend data of each city sub-region is obtained; Tracking the carbon emission route based on the carbon emission change trend data, and combining with a preset ant colony algorithm to form a current carbon tracking route and a carbon prediction route; A monitoring correction plan is generated based on the current carbon tracking route and the carbon prediction route.

2. The urban carbon tracking analysis method according to claim 1, characterized in that: The obtaining of basic information of the target city and constructing a three-dimensional visualized city model based on the basic information specifically includes: Obtaining basic information of the target city, the basic information including city map outline, city area, and city region information; The urban area information includes the distribution information of urban industrial, agricultural and residential areas; Constructing a city model according to the city map outline and the city area; The urban area information is imported into the urban model for regional division to form three major areas: industry, agriculture, and residence.

3. The urban carbon tracking and analysis method according to claim 1, characterized in that: Based on the regional information of the target city and in combination with the city model, the target city is divided into regions to form multiple city sub-regions, specifically: Based on the urban model, the three major areas of industry, agriculture and residential areas are divided into sub-areas; The division is based on the distribution density of industry, agriculture and residence to obtain N urban sub-areas; The N urban sub-regions include industrial sub-regions, agricultural sub-regions, and residential sub-regions, and the areas and shapes of the urban sub-regions are within a preset range.

4. The urban carbon tracking analysis method according to claim 3 is characterized in that: The carbon emission monitoring plan is formulated based on the regional characteristics of each urban sub-region, and the urban monitoring is carried out based on the monitoring plan to obtain the urban monitoring data within a preset period, specifically: Based on the urban area information and combined with the urban model, the distribution density of urban industrial, agricultural and residential areas is analyzed to obtain the distribution density information of urban industrial, agricultural and residential areas; Based on the industrial, agricultural and residential distribution density information of the city, combined with the city model, the number and distribution of carbon pollution monitoring points in multiple urban sub-regions are analyzed, and a carbon emission monitoring plan is obtained; Conduct urban carbon monitoring according to the carbon emission monitoring plan and obtain urban monitoring data within a preset period; The city monitoring data includes a plurality of sub-area monitoring data.

5. The urban carbon tracking analysis method according to claim 4, characterized in that: According to the city monitoring data, the carbon emission change analysis is performed on each city sub-region within a preset period. The change analysis is based on the linear regression method, and the carbon emission change trend data of each city sub-region is obtained, specifically: Taking a city sub-region as the analysis unit, the corresponding sub-region monitoring data is obtained from the city monitoring data; Performing a linear change analysis on carbon emissions based on the sub-region monitoring data to obtain a first carbon emission change curve graph of a city sub-region in a current preset period; According to the first carbon emission change curve graph, data prediction is performed based on a linear regression prediction method, and a prediction curve for the next cycle is formed and marked as a second carbon emission change curve graph; Analyze all urban sub-regions and obtain a first carbon emission change curve graph and a second carbon emission change curve graph for each urban sub-region; The carbon emission change trend data includes a first carbon emission change curve graph and a second carbon emission change curve graph.

6. The urban carbon tracking analysis method according to claim 5, characterized in that: The carbon emission route tracking is performed based on the carbon emission change trend data, and a preset ant colony algorithm is combined to form a current carbon tracking route and a carbon prediction route, which includes: A city sub-region was used as the unit of analysis and was labeled as the current sub-region; Calculate the average change curvature of the curve according to the first carbon emission change curve of the current sub-region, and use the average change curvature as the change trend index; Based on the city model, obtain K neighboring sub-regions of the current sub-region; Calculate the change trend index of each adjacent sub-region and obtain K change trend indexes; Taking the current sub-region change trend index as the benchmark value and combining it with the preset maximum deviation value, a reasonable change range for the current sub-region is constructed; The values ​​of K change trend indices that meet the reasonable change interval are screened and extracted, and the adjacent sub-regions corresponding to the change trend indices that meet the interval are marked as correlation sub-regions; Among all the correlation sub-areas, the sub-areas with the largest and smallest change trend indexes are screened to obtain the first sub-area and the second sub-area respectively; Sequentially connect the first sub-region, the current sub-region, and the second sub-region to form a carbon emission tracking direction for the current sub-region; Analyze all urban sub-regions and obtain the carbon emission tracking direction of each urban sub-region.

7. A city carbon tracking analysis method according to claim 6, characterized in that: The carbon emission route tracking based on the carbon emission change trend data, combined with a preset ant colony algorithm, forms a current carbon tracking route and a carbon prediction route, and further includes: According to the carbon emission tracking direction of each urban sub-region, an overall carbon tracking direction analysis is performed through the urban model, and an urban carbon tracking route is formed; Obtain a second carbon emission change curve graph for all urban sub-regions, calculate a corresponding change trend index based on the second carbon emission change curve graph, and mark the change trend index calculated based on the second carbon emission change curve graph as a predicted carbon trend index; Based on all urban sub-regions, the corresponding N predicted carbon trend indices are obtained; According to the city model, a path model based on ant colony algorithm is constructed. In the path model, sub-areas are used as moving path units. N pheromone gain amounts are calculated based on N predicted carbon trend indices, and the pheromone gain amounts are proportional to the predicted carbon trend indices; Determine the predicted carbon trend index of the urban sub-region, screen the urban sub-regions whose predicted carbon trend index is lower than the preset minimum index, and mark them as starting sub-regions; In the path model based on the ant colony algorithm, the starting point sub-area is used as the ant starting point, and the same preset data volume of ants is set at each starting point to initialize the pheromone of each mobile path unit; Based on N pheromone gain amounts, perform pheromone secondary initialization on each moving path unit; The ant colony path simulation is repeated multiple times and the path pheromone is updated in real time until the optimal path is formed. The optimal path is marked in combination with the city model to obtain the city carbon prediction route.

8. The urban carbon tracking and analysis method according to claim 7, characterized in that: The generation of the monitoring correction scheme based on the current carbon tracking route and the carbon prediction route is specifically: According to the carbon tracking route, the carbon emission movement trend of each urban sub-region is analyzed, and based on the carbon emission movement trend, the carbon emission impact rating of each urban sub-region is obtained. The larger the rating, the greater the carbon emission impact; Based on the urban sub-regions and the corresponding ratings, the number and distribution of secondary carbon pollution monitoring points in multiple urban sub-regions are analyzed, and the carbon emission monitoring plan is dynamically revised to generate a carbon emission monitoring correction plan for the next preset period; Based on the carbon prediction route and combined with the city model, carbon pollution prediction analysis and control index generation are carried out for the three major industrial, agricultural and residential areas of the city, and control index information corresponding to the three major industrial, agricultural and residential areas is obtained.

9. A city carbon tracking and analysis system, characterized in that: The system includes: a memory and a processor. The memory includes a city carbon tracking and analysis program. When the city carbon tracking and analysis program is executed by the processor, the following steps are implemented: Obtaining basic information of a target city, and constructing a three-dimensional visualized city model based on the basic information; Based on the regional information of the target city and combined with the city model, the target city is divided into regions to form multiple urban sub-regions; Based on the regional characteristics of each urban sub-region, a carbon emission monitoring plan is formulated, and based on the monitoring plan, urban monitoring is performed and urban monitoring data within a preset period is obtained; Based on the city monitoring data, a carbon emission change analysis is performed on each city sub-region within a preset period, the change analysis is based on a linear regression method, and the carbon emission change trend data of each city sub-region is obtained; Tracking the carbon emission route based on the carbon emission change trend data, and combining with a preset ant colony algorithm to form a current carbon tracking route and a carbon prediction route; A monitoring correction plan is generated based on the current carbon tracking route and the carbon prediction route.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a city carbon tracking analysis program, and when the city carbon tracking analysis program is executed by a processor, the steps of the city carbon tracking analysis method according to any one of claims 1 to 8 are implemented.

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