CN117893099A

CN117893099A - Urban ecological environment comprehensive analysis method, device, equipment and storage medium

Info

Publication number: CN117893099A
Application number: CN202410248896.9A
Authority: CN
Inventors: 万斯斯; 康洋鸣; 王亚晨; 李世杰; 罗宁; 陈丛笑
Original assignee: Institute Of Geographical Sciences Henan Academy Of Sciences
Current assignee: Institute Of Geographical Sciences Henan Academy Of Sciences
Priority date: 2024-03-05
Filing date: 2024-03-05
Publication date: 2024-04-16

Abstract

The application provides a comprehensive analysis method, device, equipment and storage medium for urban ecological environment, and relates to the technical field of urban ecological environment quality assessment. The method comprises the following steps: extracting target environment parameters of the corresponding target city from the environment parameter set of the target city according to the target city category; scoring the ecological environment quality of the target city according to the target environment parameters to generate an ecological quality score; combining the ecological quality score and the historical ecological quality score to generate an ecological quality change trend of the target city; acquiring relevant influence factors corresponding to the target environment parameters, and generating a change trend of the target environment parameters according to the relevant influence factors; and combining the ecological quality change trend of the target city and the change trend of the target environment parameter to generate an ecological environment quality prediction result of the target city. The technical effect that this application had is: the method can be used for more accurately and long-term prediction of the urban ecological environment change.

Description

Urban ecological environment comprehensive analysis method, device, equipment and storage medium

Technical Field

The application relates to the technical field of urban ecological environment quality assessment, in particular to an urban ecological environment comprehensive analysis method, an urban ecological environment comprehensive analysis device, urban ecological environment comprehensive analysis equipment and a storage medium.

Background

In the process of urbanization, urban ecological environment faces many challenges due to the influence of various factors such as industrial development, population growth and resource consumption. Maintenance and improvement of ecological environment quality is key to achieving sustainable urban development. Thus, long-term prediction of urban ecological environment becomes extremely important.

Current methods of ecological environmental assessment generally rely on traditional statistical data and monitoring metrics, which are relatively effective for capturing real-time or short-term environmental conditions. However, when the method is used for long-term prediction of the urban ecological environment, the prediction is usually performed through historical and instant data, and as the urban ecological system is highly dynamic and nonlinear, the new changes and trends possibly occurring in the future of the urban ecological environment cannot be captured by simply relying on the historical and instant data, so that the long-term prediction result of the urban ecological environment is inaccurate.

Disclosure of Invention

The application provides a comprehensive analysis method, device, equipment and storage medium for urban ecological environment, which are used for realizing more accurate and long-term prediction of urban ecological environment change.

In a first aspect, the present application provides a method for comprehensively analyzing urban ecological environment, the method comprising: acquiring a target city category, and extracting a target environment parameter corresponding to the target city from an environment parameter set of the target city according to the target city category; scoring the ecological environment quality of the target city according to the target environment parameters to generate an ecological quality score; acquiring a historical ecological quality score of the target city, and generating an ecological quality change trend of the target city by combining the ecological quality score and the historical ecological quality score; acquiring relevant influence factors corresponding to the target environment parameters, and generating a change trend of the target environment parameters according to the relevant influence factors; and combining the ecological quality change trend of the target city and the change trend of the target environment parameter to generate an ecological environment quality prediction result of the target city.

By adopting the technical scheme, the corresponding target environment parameters are extracted in a targeted manner after the target city category is acquired, so that the evaluation parameters are more in line with the actual conditions of different cities, and the grading result is more accurate. The method not only can generate the current ecological quality score, but also can analyze the change trend of ecological quality by combining the historical ecological quality score of the target city, and the evaluation result is more dynamic. In addition, the influence factors of the target environmental parameters are analyzed, the parameter change trend is predicted, and then the ecological quality change trend is combined, so that the urban ecological environment quality can be comprehensively predicted and analyzed. The technical scheme realizes more accurate and long-term prediction of urban ecological environment change.

Optionally, the target city category includes one of a resource city, an industrial city, a travel city, a hub city, an innovative city, and a financial city, and extracting, according to the target city category, a target environmental parameter corresponding to the target city from an environmental parameter set of the target city includes: determining a city function classification result corresponding to the target city category according to the target city category; and extracting the target environment parameters corresponding to the target city from the environment parameter set of the target city according to the city function classification result.

By adopting the technical scheme, when determining the category of the target city, the city is subdivided into different types such as resource type, industrial type, travel type and the like, the corresponding city function classification result is determined according to the city category, and then the target environment parameter matched with the city function is extracted from the environment parameter set. The technical means for carrying out customized parameter selection by combining city types and functions can enable the selected parameters to be more in line with actual main environmental problems of different cities, and enable the evaluation result to be more accurate and have strong pertinence. The method fully utilizes the difference information of city types and functions, realizes the personalized and customized selection of parameters, and ensures that the whole evaluation prediction process can be better suitable for the actual conditions of different types of cities.

Optionally, the scoring the ecological environment quality of the target city according to the target environment parameter, generating an ecological quality score, includes: acquiring the target environment parameters of the target city, wherein the target environment parameters comprise a plurality of target parameters; determining the weight of each target parameter according to the influence degree of each target parameter on the ecological environment quality of the target city; combining the size of each target parameter with the weight of each target parameter to obtain the quality score of each target parameter; and arithmetically adding the quality scores of the target parameters to obtain ecological quality scores.

By adopting the technical scheme, when the ecological environment quality score is obtained, after a plurality of target parameters are obtained, the parameter weight is determined according to the influence degree of each parameter on the ecological environment quality, the quality score of each parameter is calculated by combining the actual monitoring value of the parameter and the preset weight, and finally the quality scores of all the parameters are added together arithmetically to obtain the total ecological quality score. The technical means of adding the parameter weights and carrying out weighted scoring can reflect different contributions of different parameters to the ecological environment quality more comprehensively and objectively. The scoring mode considering the parameter weights can reasonably distinguish the importance of each parameter, avoid excessive influence of certain parameters on scoring results, and enable the final ecological quality scoring results to be more scientific and reasonable and to be higher in evaluation accuracy.

Optionally, the obtaining the relevant influence factor corresponding to the target environmental parameter, and generating the change trend of the target environmental parameter according to the relevant influence factor includes: inquiring related influence factors corresponding to the target environment parameters, wherein the related influence factors comprise policy planning, an industrial structure, population density and surrounding environment; and generating a change trend of the target environmental parameter according to the policy planning, the industrial structure, the population density and the surrounding environment.

By adopting the technical scheme, the influence of various factors such as policy planning, industrial structure, population density and surrounding environment can be comprehensively considered when the change trend of the target environmental parameter is predicted. The multi-factor comprehensive analysis technical means can judge the trend of parameter change more comprehensively and accurately. Because the change of the environmental parameters is often the result of the combined action of multiple factors, the change trend of the environmental parameters is difficult to be completely reflected by a single factor. According to the method and the device, the influence of each factor is comprehensively considered by inquiring the data of the related influence factors, so that the future change prediction of the environmental parameters is more approximate to the actual situation.

Optionally, the generating the trend of the target environmental parameter according to the policy plan, the industry structure, the population density and the surrounding environment includes: predicting a change rate of the industrial structure of the target city according to the industrial structure of the target city and the policy plan, and predicting a first influence rate of the change rate of the industrial structure on the target environmental parameter according to the change rate of the industrial structure of the target city; acquiring the population density of the target city, determining the population growth rate of the target city according to the population density, and predicting the second influence rate of the population growth rate on the target environmental parameter according to the population growth rate of the target city; and generating a change trend of the target environment parameter by combining the first influence rate, the second influence rate and the surrounding environment.

Through adopting above-mentioned technical scheme, this application is when predicting environmental parameter variation trend, has not only considered the influence of industrial structure and policy planning to the industrial structure change to population density to population growth, has still quantized the influence degree of these two types of factors to environmental parameter, calculates first influence rate and second influence rate respectively. The technical means for quantitatively analyzing the influence of different factors can enable the parameter change trend prediction to be more quantitative and accurate, and the comprehensive prediction of the parameter change can be realized by combining the surrounding environment factors.

Optionally, the generating the ecological environment quality prediction result of the target city by combining the ecological quality variation trend of the target city and the variation trend of the target environment parameter includes: according to the ecological quality change trend of the target city, primarily predicting the ecological environment quality of the target city to obtain a primary prediction result; and adjusting the preliminary prediction result according to the change trend of the target environment parameter to obtain an ecological environment quality prediction result of the target city.

By adopting the technical scheme, when the final ecological environment quality prediction result is generated, the preliminary prediction is firstly carried out according to the ecological quality change trend, and then the preliminary result is adjusted and optimized by combining the target environment parameter change trend. And the historical change information of the ecological quality score is fully utilized to predict the overall quality change, and then the prediction result is refined and adjusted through the change of the environmental parameters. The prediction technology driven by the historical score and the parameter change can make the final result more accurate and reliable. And the initial prediction determines the overall change trend, and the parameter adjustment reflects the latest change condition. The method combines the two, can improve the scientificity and accuracy of prediction, better reflect the change of urban ecological environment and provide effective support for government decision.

Optionally, after generating the ecological environment quality prediction result of the target city, the method further includes: comparing the ecological environment quality prediction result of the target city with the preset target ecological environment quality to obtain a comparison result; judging whether the ecological environment quality of the target city meets the standard or not according to the comparison result; and if the ecological environment quality of the target city does not reach the standard, generating a treatment scheme aiming at the target environment parameters.

By adopting the technical scheme, the technical steps of comparing with the preset target are further arranged after the ecological environment quality prediction result is generated. Whether the predicted result meets the standard requirement can be intuitively judged, and accurate diagnosis can be performed. If the problem parameters do not reach the standard, the technical scheme can also generate a treatment scheme aiming at the problem parameters. The technical means of prediction and comparison can be used for realizing the pre-judgment of the quality change of the future ecological environment of the city, and meanwhile, when the quality change does not meet the requirements, the problems can be rapidly determined and the treatment plan can be provided. The technical scheme has the effects of strengthening prediction effect and realizing environment closed-loop management, and has important technical significance for improving the quality of urban ecological environment.

In a second aspect, the present application provides an urban ecological environment comprehensive analysis device, the device comprising: the device comprises an acquisition module, a first generation module, a second generation module, a third generation module and an output module; wherein,

the acquisition module is used for acquiring a target city category, and extracting target environment parameters corresponding to the target city from the environment parameter set of the target city according to the target city category; the first generation module is used for scoring the ecological environment quality of the target city according to the target environment parameter to generate an ecological quality score; the second generation module is used for obtaining the historical ecological quality score of the target city and generating the ecological quality change trend of the target city by combining the ecological quality score and the historical ecological quality score; the third generation module is configured to obtain a relevant influence factor corresponding to the target environmental parameter, and generate a variation trend of the target environmental parameter according to the relevant influence factor; the output module is used for combining the ecological quality change trend of the target city and the change trend of the target environment parameter to generate an ecological environment quality prediction result of the target city.

In a third aspect, the present application provides an electronic device, which adopts the following technical scheme: the system comprises a processor, a memory, a user interface and a network interface, wherein the memory is used for storing instructions, the user interface and the network interface are used for communicating with other devices, and the processor is used for executing the instructions stored in the memory so as to enable the electronic device to execute the computer program of the urban ecological environment comprehensive analysis method.

In a fourth aspect, the present application provides a computer readable storage medium, which adopts the following technical solutions: a computer program capable of being loaded by a processor and executing any one of the urban ecological environment comprehensive analysis methods described above is stored.

In summary, the present application includes at least one of the following beneficial technical effects:

1. the urban ecological environment change is predicted more accurately and for a long time;

2. and step, predicting to determine the overall change trend, and adjusting parameters to reflect the latest change condition. The method combines the two, can improve the scientificity and accuracy of prediction, better reflect the change of urban ecological environment and provide effective support for government decision.

Drawings

FIG. 1 is a schematic flow chart of a comprehensive analysis method for urban ecological environment according to an embodiment of the present application;

FIG. 2 is a schematic structural diagram of an integrated analysis device for urban ecological environment according to an embodiment of the present application;

fig. 3 is a schematic structural diagram of an electronic device according to an embodiment of the present application.

Reference numerals illustrate: 1000. an electronic device; 1001. a processor; 1002. a communication bus; 1003. a user interface; 1004. a network interface; 1005. a memory.

Detailed Description

In order to make the technical solutions in the present specification better understood by those skilled in the art, the technical solutions in the embodiments of the present specification will be clearly and completely described below with reference to the drawings in the embodiments of the present specification, and it is obvious that the described embodiments are only some embodiments of the present application, but not all embodiments.

In the description of embodiments of the present application, words such as "exemplary," "such as" or "for example" are used to mean serving as an example, instance, or illustration. Any embodiment or design described herein as "illustrative," "such as" or "for example" is not necessarily to be construed as preferred or advantageous over other embodiments or designs. Rather, the use of words such as "illustratively," "such as" or "for example," etc., is intended to present related concepts in a concrete fashion.

Fig. 1 is a schematic flow chart of a comprehensive analysis method for urban ecological environment according to an embodiment of the present application. It should be understood that, although the steps in the flowchart of fig. 1 are shown in sequence as indicated by the arrows, the steps are not necessarily performed in sequence as indicated by the arrows; the steps are not strictly limited to the order of execution unless explicitly recited herein, and the steps may be executed in other orders; and at least some of the steps in fig. 1 may include a plurality of sub-steps or stages that are not necessarily performed at the same time, but may be performed at different times, nor does the order in which the sub-steps or stages are performed necessarily occur in sequence, but may be performed alternately or alternately with at least some of the other steps or sub-steps of other steps.

The application discloses a comprehensive analysis method for urban ecological environment, which comprises S101-S105 as shown in figure 1.

S101, obtaining a target city category, and extracting target environment parameters of a corresponding target city from an environment parameter set of the target city according to the target city category.

In one example, an environmental parameter set refers to a set of environmental parameters related to urban ecological environmental quality assessment. These environmental parameters may reflect the ecological environment of a city. The environmental parameter set typically includes parameters such as air quality parameters (e.g., PM2.5, PM10, sulfur dioxide, nitrogen dioxide, etc.), water quality parameters (e.g., COD, ammonia nitrogen, etc.), noise parameters, solid waste parameters, green land coverage, etc. The specific composition of the environmental parameter sets may vary from city to city, depending on the prevailing environmental problems and the protection emphasis of the city. For example, for an industrial city, the environmental parameter set may contain more parameters of air and wastewater related to industrial pollution, and for a tourism city, may contain more parameters reflecting noise and greenbelt.

The target city class is obtained in order to extract the key environmental parameters of interest for different types of cities. The target city category may include industrial cities, commercial cities, tourism cities, etc., where different types of cities have differences in the factors that influence their ecological environment and key parameters that need attention.

For example, for an industrial city, the environmental parameter set may include COD (chemical oxygen demand), ammonia nitrogen, sulfur dioxide, inhalable particulate matter (PM 10), and the like. After the category that the target city is an industrial city is obtained, COD, ammonia nitrogen, sulfur dioxide and PM10 can be extracted from the environmental parameter set as the target environmental parameters of the city. These parameters are extracted because contaminants that may be generated during industrial production are what these parameters represent, which are critical for assessing the quality of the industrial urban ecological environment.

For another example, for a tourist city, the environmental parameter set may include parameters such as COD, ammonia nitrogen, noise, greenbelt rate, etc. After the target city is determined to be the tourism city, the noise and the greenbelt rate can be extracted as the target environment parameters. Because the ecological environment that is of greater concern in tourist cities is noise pollution and natural resource conservation.

By acquiring the category of the target city, the target environment parameters are extracted in a targeted manner, so that the subsequent ecological environment scoring is focused on the core parameters of the type of city, and the evaluation result is more targeted, thereby providing basis for subsequent ecological environment management.

On the basis of the above embodiment, as an alternative embodiment, the target city category includes one of a resource type city, an industrial type city, a travel type city, a hub type city, an innovative type city, and a financial type city, in S101: according to the category of the target city, extracting the target environment parameters of the corresponding target city from the environment parameter set of the target city specifically comprises:

Determining a city function classification result corresponding to the target city category according to the target city category; and extracting the target environment parameters of the corresponding target city from the environment parameter set of the target city according to the city function classification result.

In one example, target environmental parameters are extracted from the set of environmental parameters in a targeted manner, depending on the class of the target city, in order to focus subsequent evaluation of the quality of the ecological environment for different types of cities on the primary environmental issue.

In practice, the first step is to identify the category of the target city, such as an industrial city or a travel city. The second step is to find the corresponding main city function class according to the city class, for example, the main function of the industrial city is industrial production, and the tourist city is a tourist leisure service. And thirdly, searching the environment parameters related to the main function in all candidate environment parameter sets of the city according to the function classification result, and finally extracting the parameters with the most representative and evaluation values as target environment parameters.

For example, for industrial cities, it is possible to extract parameters such as COD, ammonia nitrogen, smoke and the like related to industrial emissions from the parameter set; for a tourist city, parameters such as noise and greenbelt rate may be selected. The targeted extraction mode can make the evaluation focus on the main ecological environment problem of the city, and the grading result is more reliable.

S102, scoring the ecological environment quality of the target city according to the target environment parameters, and generating an ecological quality score.

In one example, if the target city is an industrial city, the target environmental parameters of the industrial city, i.e., COD, ammonia nitrogen, sulfur dioxide, PM10, are obtained. The scoring range is then determined based on environmental quality criteria for each parameter. For example, the environmental quality standard of COD is 30mg/L, and the COD is less than or equal to 30mg/L and can be set to be good, and 5 minutes are given; 30mg/L < COD less than or equal to 60mg/L is light pollution, and 3 points are given; 60mg/L < COD less than or equal to 100mg/L is moderate pollution, and is given a score of 2; COD >100mg/L is heavy pollution and gives 1 minute. Other parameters similarly set scoring criteria.

And then, acquiring the average value of the monitoring data of COD, ammonia nitrogen, sulfur dioxide and PM10 of the target city in the last year, and sequentially carrying out calculation scores according to the parameter scoring standard. Finally, the weights of the parameters are multiplied by the scores of the parameters, and the scores of the ecological environment quality are generated through summation.

Therefore, quantitative scoring standards are set for key parameters, the ecological environment quality condition of one city can be intuitively reflected, and the differences of pollution with different degrees are considered by each parameter scoring, so that the scoring result is more reasonable. The scoring result can provide basis for subsequent environment management, and can also be compared with the historical scoring result to judge the ecological environment quality trend.

On the basis of the above embodiment, as an alternative embodiment, in S102: scoring the ecological environment quality of the target city according to the target environment parameters, wherein the generating the ecological quality score specifically comprises the following steps:

acquiring target environment parameters of a target city, wherein the target environment parameters comprise a plurality of target parameters; determining the weight of each target parameter according to the influence degree of each target parameter on the quality of the ecological environment of the target city; combining the size of each target parameter and the weight of each target parameter to obtain the quality score of each target parameter; and arithmetically adding the quality scores of the target parameters to obtain the ecological quality score.

In one example, the ecological environment quality score needs to take into account the scoring contributions of the target parameters, while the impact of different parameters on the environment quality varies, so the weights of the parameters need to be determined.

In the specific implementation, firstly, target parameters of an industrial city, such as COD, ammonia nitrogen, smoke dust and the like, are obtained, and historical data are inquired to obtain monitoring values of the parameters. Then, a scoring rule is set according to the environmental standard of the parameters, and the original quality score of each parameter is calculated. Then, according to historical data or experience, the parameter weights, such as COD weight 0.3, ammonia nitrogen weight 0.2 and smoke weight 0.1, are determined. And finally, multiplying the weights of the parameters by the quality scores of the parameters respectively, and summing to obtain the final ecological environment quality comprehensive score of the city. The scoring mode of introducing the parameter weight can consider different influence degrees of different parameters on the environmental quality, so that the scoring result is more reasonable and objective. Compared with the direct average grading, the method reflects the overall ecological environment condition of the city more comprehensively and can provide better guidance for subsequent treatment.

And S103, acquiring a historical ecological quality score of the target city, and generating an ecological quality change trend of the target city by combining the ecological quality score and the historical ecological quality score.

In one example, in a first step, the target city's eco-environment quality score data is collected over the last few years (e.g., 3 years), which may be obtained through the previous steps. And secondly, analyzing the historical scoring data, and calculating the scoring change trend, such as the scoring change rate of two adjacent years, so as to reflect whether the scoring is rising or falling. Thirdly, comprehensively analyzing the environmental quality scoring result of the current year to obtain the trend of the environmental quality change of the target city in recent years, for example: overall smooth, declining year by year, current rising back, etc. Through analysis of historical scoring change trend, the dynamic situation that the urban ecological environment quality is better or worse can be prompted. If the environmental quality is continuously deteriorated, the reason is found out and the treatment countermeasure is put forward; if the current score rises, the latest treatment measures are possibly effective, and an important basis is provided for the next ecological environment management decision.

S104, acquiring relevant influence factors corresponding to the target environment parameters, and generating the change trend of the target environment parameters according to the relevant influence factors.

In one example, relevant influencing factors for the target environmental parameters are obtained for analysis of the causes of the parameter variations, which influencing factors may include industry structure, energy structure, vehicle inventory, population density, etc. The specific implementation steps comprise: firstly, for sulfur dioxide which is a target parameter of an industrial city, the main influencing factors are determined to be an industrial structure, an energy structure and an automobile conservation amount. Then, the urban industrial structure change data of the last 3 years are collected, such as the specific gravity of the steel industry is reduced from 35% to 30%; collecting energy structure data, such as the reduction of the specific gravity of the coal from 60% to 50%; and collecting data of the automobile keeping amount, such as the automobile keeping amount is increased from 20 ten thousand to 25 ten thousand. Finally, the influence of each influence factor on sulfur dioxide is analyzed, for example, the reduction of the iron and steel industry leads to the reduction of industrial emission, the reduction of smoke emission due to the reduction of fire coal, and the increase of automobiles leads to the increase of automobile exhaust emission. The comprehensive factors change, and the generated sulfur dioxide generally shows a slow descending trend.

On the basis of the above embodiment, as an alternative embodiment, in S104: acquiring relevant influence factors corresponding to the target environment parameters, and generating the change trend of the target environment parameters according to the relevant influence factors specifically comprises:

Inquiring related influencing factors corresponding to the target environment parameters, wherein the related influencing factors comprise policy planning, industrial structure, population density and surrounding environment; predicting the change rate of the industrial structure of the target city according to the industrial structure and policy planning of the target city, and predicting the first influence rate of the change rate of the industrial structure on the target environmental parameter according to the change rate of the industrial structure of the target city; acquiring population density of a target city, determining population growth rate of the target city according to the population density, and predicting second influence rate of the population growth rate on the target environmental parameter according to the population growth rate of the target city; and generating a change trend of the target environment parameter by combining the first influence rate, the second influence rate and the surrounding environment.

In one example, multiple factors affecting parameter variation are collected and analyzed to comprehensively determine the cause of the parameter variation, so that the environmental management countermeasures formulated later are more targeted.

The method specifically comprises the following steps: firstly, relevant influencing factors of industrial and urban sulfur dioxide are queried, mainly including an industrial structure, population density, policy planning and surrounding environment, the dimension can be automatically increased or reduced according to actual conditions, other conditions can refer to the embodiment, and detailed description is omitted herein specifically according to actual conditions. Then, predicting a possible change trend according to the urban industrial structure, and judging the influence of the possible change trend on sulfur dioxide; while taking into account the effects of population growth. Then, the influence degree of the change of the industrial structure, the influence degree of population growth, and the factors of environmental policies and surrounding areas are combined to obtain the change trend of sulfur dioxide in a future period of time.

Therefore, the factors in all aspects are collected, quantitative or qualitative influence prediction is carried out, and the reasons of parameter change can be judged more comprehensively. Compared with the method which only considers a single factor, the multi-factor comprehensive analysis can enable the judgment of the parameter trend to be more accurate, and the environmental management measures formulated later to be more targeted.

Suppose that the trend of change of PM2.5 in a certain city needs to be predicted. Its influencing factors can be considered from several aspects:

and (5) an energy source structure. The total annual coal consumption data of the city is collected, and the coal consumption is analyzed to be possibly reduced by 5% in the next 3 years, so that PM2.5 emission is reduced.

An industrial structure. Querying the number of enterprises in the urban steel, cement and other air pollution industries, predicting future industrial structure adjustment, wherein the industries are reduced by 10 percent, and PM2.5 is correspondingly reduced.

The amount of the vehicle is kept. And counting the annual growth rate of the maintenance quantity of the urban motor vehicle, predicting the future growth by 5%, and increasing the PM2.5 emission of automobile exhaust.

Weather conditions. And collecting the annual precipitation and wind speed data of the city, and analyzing the influence of meteorological conditions on the diffusion condition of PM 2.5.

Policy impact. Considering the air pollution control policy coming out of the stage in recent years, the pollution control is enhanced.

By combining the factors, it can be judged that the Beijing PM2.5 concentration will show about 5% decreasing trend in the next 3 years. Therefore, the prediction is carried out by fusing multiple factors, the result is more accurate, and references are provided for formulating environmental management policies.

S105, combining the ecological quality change trend of the target city and the change trend of the target environment parameter to generate an ecological environment quality prediction result of the target city.

In one example, generating the ecological environmental quality prediction results is based on summarizing past environmental quality and trends in key parameters, and looking up and judging environmental quality over a period of time in the future to provide a prospective reference for subsequent environmental management decisions.

The method specifically comprises the following steps: firstly, ecological environment quality scoring data and scoring change trend of the target city in the past few years need to be collected, and environmental quality is predicted to be good or poor; secondly, collecting historical monitoring data of all key environmental parameters such as COD and ammonia nitrogen, and analyzing the change trend of the parameters; finally, the ecological environment quality of the next year is predicted by combining two factors, namely the ecological quality change trend and the environment parameter change trend. For example, if the ecological quality score continues to rise for the last two years with decreasing COD and ammonia nitrogen concentrations, it can be judged that the ecological environment quality is improving and it is predicted that the environmental quality will continue to improve for the next year.

The prediction combines the past state and the change trend, comprehensively analyzes different factors, has reliable prediction results, and can provide important references for government environment management departments to formulate subsequent treatment strategies so as to continuously improve the urban ecological environment.

On the basis of the above embodiment, as an alternative embodiment, in S105: combining the ecological quality change trend of the target city with the change trend of the target environment parameter, the generating the ecological environment quality prediction result of the target city specifically comprises the following steps:

according to the ecological quality change trend of the target city, primarily predicting the ecological environment quality of the target city to obtain a primary prediction result; and adjusting the preliminary prediction result according to the change trend of the target environment parameter to obtain the ecological environment quality prediction result of the target city.

In one example, ecological environment quality prediction needs to take into account two factors, namely past quality trend and various parameter trend. Performing two-stage adjustments may improve the accuracy of the predictions.

The specific steps can be as follows: firstly, according to the change trend of the quality scores of the ecological environment of the city in the past 3 years, the quality score result of the next year can be preliminarily predicted, and the preliminary result is assumed to be improved by 2 points. And then, the preliminary results are adjusted and perfected by combining the change trend of each key environmental parameter such as COD and ammonia nitrogen. For example, the COD trend indicates a possible 5% decrease, and the quality score prediction result can be adjusted to be raised by 2.5 minutes in consideration of this.

The two-step prediction mode can be fully combined with the historical scoring trend, and the change of each parameter is also considered to adjust and optimize the result. Compared with the method which only considers a single angle, the adjusted prediction can more comprehensively reflect the complexity of the urban environment quality change, so that the result is more accurate and reliable. And a more scientific basis is provided for the subsequent establishment of environmental management measures.

Suppose that it is necessary to predict an environmental quality score for an industrial city year-round.

In the first step, the ecological environment quality score of the city over the last 3 years is: 2019: 62 minutes, 2020: 65 minutes, 2021: 68 minutes.

The trend of the rise of the ecological environment quality year by year can be seen. From this trend, it can be primarily predicted that the 2022 environmental quality score will be 71 points.

Secondly, checking the change of two key parameters COD and sulfur dioxide in the industrial city: COD 2019-2021 showed a steady downward trend, and it is expected that 2022 would be reduced by 3%. Sulfur dioxide was essentially leveled in years 2019-2021 and was also expected to be unchanged in year 2022. The COD change trend indicates that the preliminary prediction result can be correspondingly improved by taking the forward factor into consideration. By combining the two-step analysis, the environmental quality score of 2022 years in this industrial city can be predicted to be 72 points, which is increased by 1 point compared with the preliminary prediction considering only trends.

After generating the ecological environment quality prediction result of the target city, the method further comprises the following steps: comparing the ecological environment quality prediction result of the target city with the preset target ecological environment quality to obtain a comparison result; judging whether the ecological environment quality of the target city meets the standard or not according to the comparison result; and if the ecological environment quality of the target city does not reach the standard, generating a treatment scheme aiming at the target environment parameters.

In one example, a quality score of 71 for an industrial city environment in the open is first obtained from a predictive model. Then, the urban environment quality planning target value is referred to be more than 75 minutes. And then, comparing the predicted result with the target value, and judging that the urban environment quality does not reach the planning target. Finally, aiming at the main environmental parameter COD causing the city not to reach the standard, adopting a treatment scheme for increasing the investment of treatment facilities, and quantitatively setting a treatment target to reduce the COD concentration by x% according to a plan so as to reach the standard of environmental quality.

Based on the method, the application also discloses an urban ecological environment comprehensive analysis device, as shown in fig. 2, and fig. 2 is a schematic structural diagram of the urban ecological environment comprehensive analysis device provided by the embodiment of the application.

The device comprises: the device comprises an acquisition module, a first generation module, a second generation module, a third generation module and an output module; the acquisition module is used for acquiring the category of the target city and extracting the target environment parameters of the corresponding target city from the environment parameter set of the target city according to the category of the target city; the first generation module is used for scoring the ecological environment quality of the target city according to the target environment parameters to generate an ecological quality score; the second generation module is used for obtaining the historical ecological quality score of the target city and generating the ecological quality change trend of the target city by combining the ecological quality score and the historical ecological quality score; the third generation module is used for acquiring relevant influence factors corresponding to the target environment parameters and generating the change trend of the target environment parameters according to the relevant influence factors; and the output module is used for generating an ecological environment quality prediction result of the target city by combining the ecological quality change trend of the target city and the change trend of the target environment parameter.

It should be noted that: in the device provided in the above embodiment, when implementing the functions thereof, only the division of the above functional modules is used as an example, in practical application, the above functional allocation may be implemented by different functional modules according to needs, that is, the internal structure of the device is divided into different functional modules, so as to implement all or part of the functions described above. In addition, the embodiments of the apparatus and the method provided in the foregoing embodiments belong to the same concept, and specific implementation processes of the embodiments of the method are detailed in the method embodiments, which are not repeated herein.

Referring to fig. 3, a schematic structural diagram of an electronic device is provided in an embodiment of the present application. As shown in fig. 3, the electronic device 1000 may include: at least one processor 1001, at least one network interface 1004, a user interface 1003, a memory 1005, at least one communication bus 1002.

Wherein the communication bus 1002 is used to enable connected communication between these components.

The user interface 1003 may include a Display screen (Display) and a Camera (Camera), and the optional user interface 1003 may further include a standard wired interface and a wireless interface.

The network interface 1004 may optionally include a standard wired interface, a wireless interface (e.g., WI-FI interface), among others.

Wherein the processor 1001 may include one or more processing cores. The processor 1001 connects various parts within the entire server using various interfaces and lines, performs various functions of the server and processes data by executing or executing instructions, programs, code sets, or instruction sets stored in the memory 1005, and calling data stored in the memory 1005. Alternatively, the processor 1001 may be implemented in at least one hardware form of digital signal processing (Digital Signal Processing, DSP), field programmable gate array (Field-Programmable Gate Array, FPGA), programmable logic array (Programmable Logic Array, PLA). The processor 1001 may integrate one or a combination of several of a central processing unit (Central Processing Unit, CPU), an image processor (Graphics Processing Unit, GPU), and a modem, etc. The CPU mainly processes an operating system, a user interface, an application program and the like; the GPU is used for rendering and drawing the content required to be displayed by the display screen; the modem is used to handle wireless communications. It will be appreciated that the modem may not be integrated into the processor 1001 and may be implemented by a single chip.

The Memory 1005 may include a random access Memory (Random Access Memory, RAM) or a Read-Only Memory (Read-Only Memory). Optionally, the memory 1005 includes a non-transitory computer readable medium (non-transitory computer-readable storage medium). The memory 1005 may be used to store instructions, programs, code, sets of codes, or sets of instructions. The memory 1005 may include a stored program area and a stored data area, wherein the stored program area may store instructions for implementing an operating system, instructions for at least one function (such as a touch function, a sound playing function, an image playing function, etc.), instructions for implementing the above-described respective method embodiments, etc.; the storage data area may store data or the like involved in the above respective method embodiments. The memory 1005 may also optionally be at least one storage device located remotely from the processor 1001. As shown in fig. 3, an operating system, a network communication module, a user interface module, and an application program of an integrated analysis method of urban ecological environment may be included in the memory 1005 as a computer storage medium.

In the electronic device 1000 shown in fig. 3, the user interface 1003 is mainly used for providing an input interface for a user, and acquiring data input by the user; and processor 1001 may be configured to invoke an application in memory 1005 that stores an urban ecological environment analysis method that, when executed by one or more processors, causes the electronic device to perform the method as described in one or more of the embodiments above.

An electronic device readable storage medium storing instructions. When executed by one or more processors, cause an electronic device to perform the method as described in one or more of the embodiments above.

It should be noted that, for simplicity of description, the foregoing method embodiments are all expressed as a series of action combinations, but it should be understood by those skilled in the art that the present application is not limited by the order of actions described, as some steps may be performed in other order or simultaneously in accordance with the present application. Further, those skilled in the art will also appreciate that the embodiments described in the specification are all preferred embodiments, and that the acts and modules referred to are not necessarily required in the present application.

In the foregoing embodiments, the descriptions of the embodiments are emphasized, and for parts of one embodiment that are not described in detail, reference may be made to related descriptions of other embodiments.

In the several embodiments provided herein, it should be understood that the disclosed apparatus may be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative, such as the division of the units, merely a logical function division, and there may be additional manners of dividing the actual implementation, such as multiple units or components may be combined or integrated into another system, or some features may be omitted, or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be through some service interface, device or unit indirect coupling or communication connection, electrical or otherwise.

The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

In addition, each functional unit in each embodiment of the present application may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.

The integrated units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable memory. Based on such understanding, the technical solution of the present application may be embodied in essence or a part contributing to the prior art or all or part of the technical solution in the form of a software product stored in a memory, including several instructions for causing a computer device (which may be a personal computer, a server or a network device, etc.) to perform all or part of the steps of the method described in the embodiments of the present application. And the aforementioned memory includes: various media capable of storing program codes, such as a U disk, a mobile hard disk, a magnetic disk or an optical disk.

The foregoing is merely exemplary embodiments of the present disclosure and is not intended to limit the scope of the present disclosure. That is, equivalent changes and modifications are contemplated by the teachings of this disclosure, which fall within the scope of the present disclosure. Other embodiments of the disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the disclosure herein. This application is intended to cover any adaptations, uses, or adaptations of the disclosure following, in general, the principles of the disclosure and including such departures from the present disclosure as come within known or customary practice within the art to which the disclosure pertains. It is intended that the specification and examples be considered as exemplary only, with a scope and spirit of the disclosure being indicated by the claims.

Claims

1. An urban ecological environment comprehensive analysis method is characterized by comprising the following steps:

acquiring a target city category, and extracting a target environment parameter corresponding to the target city from an environment parameter set of the target city according to the target city category;

scoring the ecological environment quality of the target city according to the target environment parameters to generate an ecological quality score;

acquiring a historical ecological quality score of the target city, and generating an ecological quality change trend of the target city by combining the ecological quality score and the historical ecological quality score;

Acquiring relevant influence factors corresponding to the target environment parameters, and generating a change trend of the target environment parameters according to the relevant influence factors;

and combining the ecological quality change trend of the target city and the change trend of the target environment parameter to generate an ecological environment quality prediction result of the target city.

2. The urban ecological environment comprehensive analysis method according to claim 1, wherein the target city category comprises one of a resource type city, an industrial type city, a travel type city, a hub type city, an innovative type city, and a financial type city, and the extracting the target environmental parameter corresponding to the target city from the environmental parameter set of the target city according to the target city category comprises:

determining a city function classification result corresponding to the target city category according to the target city category;

and extracting the target environment parameters corresponding to the target city from the environment parameter set of the target city according to the city function classification result.

3. The method of claim 1, wherein scoring the quality of the ecological environment of the target city according to the target environmental parameter to generate an ecological quality score comprises:

Acquiring the target environment parameters of the target city, wherein the target environment parameters comprise a plurality of target parameters;

determining the weight of each target parameter according to the influence degree of each target parameter on the ecological environment quality of the target city;

combining the size of each target parameter with the weight of each target parameter to obtain the quality score of each target parameter;

and arithmetically adding the quality scores of the target parameters to obtain ecological quality scores.

4. The method for comprehensively analyzing urban ecological environment according to claim 1, wherein said obtaining the relevant influencing factors corresponding to the target environmental parameters, and generating the trend of the change of the target environmental parameters according to the relevant influencing factors, comprises:

inquiring related influence factors corresponding to the target environment parameters, wherein the related influence factors comprise policy planning, an industrial structure, population density and surrounding environment;

and generating a change trend of the target environmental parameter according to the policy planning, the industrial structure, the population density and the surrounding environment.

5. The method of claim 4, wherein generating the trend of the target environmental parameter according to the policy plan, the industry structure, the population density, and the surrounding environment comprises:

Predicting a change rate of the industrial structure of the target city according to the industrial structure of the target city and the policy plan, and predicting a first influence rate of the change rate of the industrial structure on the target environmental parameter according to the change rate of the industrial structure of the target city;

acquiring the population density of the target city, determining the population growth rate of the target city according to the population density, and predicting the second influence rate of the population growth rate on the target environmental parameter according to the population growth rate of the target city;

and generating a change trend of the target environment parameter by combining the first influence rate, the second influence rate and the surrounding environment.

6. The method for comprehensively analyzing urban ecological environment according to claim 1, wherein the generating the ecological environment quality prediction result of the target city by combining the ecological quality variation trend of the target city and the variation trend of the target environment parameter comprises:

according to the ecological quality change trend of the target city, primarily predicting the ecological environment quality of the target city to obtain a primary prediction result;

And adjusting the preliminary prediction result according to the change trend of the target environment parameter to obtain an ecological environment quality prediction result of the target city.

7. The method for comprehensively analyzing urban ecological environment according to claim 1, further comprising, after generating the ecological environment quality prediction result of the target city:

comparing the ecological environment quality prediction result of the target city with the preset target ecological environment quality to obtain a comparison result;

judging whether the ecological environment quality of the target city meets the standard or not according to the comparison result;

and if the ecological environment quality of the target city does not reach the standard, generating a treatment scheme aiming at the target environment parameters.

8. An urban ecological environment comprehensive analysis device, characterized in that the device comprises: the device comprises an acquisition module, a first generation module, a second generation module, a third generation module and an output module; wherein,

the acquisition module is used for acquiring a target city category, and extracting target environment parameters corresponding to the target city from the environment parameter set of the target city according to the target city category;

the first generation module is used for scoring the ecological environment quality of the target city according to the target environment parameter to generate an ecological quality score;

The second generation module is used for obtaining the historical ecological quality score of the target city and generating the ecological quality change trend of the target city by combining the ecological quality score and the historical ecological quality score;

the third generation module is configured to obtain a relevant influence factor corresponding to the target environmental parameter, and generate a variation trend of the target environmental parameter according to the relevant influence factor;

the output module is used for combining the ecological quality change trend of the target city and the change trend of the target environment parameter to generate an ecological environment quality prediction result of the target city.

9. An electronic device comprising a processor, a memory, a user interface, and a network interface, the memory for storing instructions, the user interface and the network interface for communicating to other devices, the processor for executing the instructions stored in the memory to cause the electronic device to perform the method of any of claims 1-7.

10. A computer readable storage medium, characterized in that a computer program is stored which can be loaded by a processor and which performs the method according to any of claims 1-7.