Urban vegetation health real-time evaluation and early warning system

Abstract

The invention discloses a real-time evaluation and early warning system for urban vegetation health, which belongs to the technical field of vegetation health monitoring and comprises an image acquisition module for acquiring vegetation image information of each planting area; the data acquisition module is used for acquiring related associated data information of the planting area; the evaluation center is used for analyzing and processing the acquired information to evaluate whether the health condition of the vegetation has a problem or not, and further analyzing the health condition of the vegetation and judging whether the vegetation has a hidden health problem or not when judging that the health condition of the vegetation does not have the problem, so as to generate a corresponding alarm instruction; and the early warning module is used for carrying out corresponding alarm reminding on the appearing health problems. According to the method, comprehensive analysis can be carried out according to the vegetation soil condition, the vegetation growth condition and the vegetation carbon sequestration condition to judge whether the normal vegetation has hidden or potential health problems or not, corresponding alarms are given to the vegetation or areas with the hidden health problems, and the health problems of the vegetation are avoided.

Description

Technical Field

[0001] The invention belongs to the technical field of vegetation health monitoring, and in particular relates to a real-time assessment and early warning system for urban vegetation health. Background Art

[0002] As people's quality of life improves and they pay more attention to the ecological environment, multiple green areas will be reserved in urban construction plans for planting vegetation, which can not only beautify the city, but also purify the air and protect the ecological environment.

[0003] Since there are a large number of vegetation in the city, in order to ensure the normal growth of vegetation, special management personnel are needed to monitor and manage the health status of vegetation. The existing health management of vegetation is mostly done by inspectors analyzing the health status of vegetation by observing the condition of vegetation. This method consumes too many human resources, and manual inspections are not accurate enough. In addition, this method can only detect vegetation that has already had health problems, but cannot detect vegetation with potential health problems, which can easily cause vegetation loss. Summary of the invention

[0004] The purpose of the present invention is to provide a real-time urban vegetation health assessment and early warning system to solve the problems faced by the above-mentioned background technology.

[0005] The purpose of the present invention can be achieved through the following technical solutions:

[0006] A real-time urban vegetation health assessment and early warning system, the system comprising:

[0007] An image acquisition module, which is used to acquire vegetation image information of each planting area and upload it to an evaluation center;

[0008] A data collection module, which is used to obtain relevant data information of the planting area and upload it to the evaluation center;

[0009] An evaluation center is used to analyze and process the acquired information to evaluate whether there is a problem with the health status of the vegetation. When it is determined that there is a problem with the health status of the vegetation, a corresponding alarm instruction is generated. At the same time, when it is determined that there is no problem with the health status of the vegetation, the health status of the vegetation is further analyzed to determine whether there is a hidden health problem in the vegetation, thereby generating a corresponding alarm instruction;

[0010] The early warning module issues corresponding alarm reminders for health problems according to the alarm instructions generated by the assessment center.

[0011] Furthermore, the method by which the assessment center assesses whether there is a problem with the health status of vegetation includes:

[0012] After the acquired image information is corrected, cropped, and denoised, image processing technology is used to obtain various feature information of the image, and the acquired feature information is input into the neural network model trained with a large amount of annotated image data in the evaluation center to obtain the feature representative values ​​of various feature information;

[0013] Compare the obtained representative values ​​of each feature with the standard representative value intervals of the same period set by each feature. When the obtained representative value of the feature does not fall into the corresponding standard representative value interval, it indicates that there is a problem with the health status of urban vegetation, and a corresponding alarm instruction is generated;

[0014] Furthermore, the method for the assessment center to assess whether there is a problem with the health status of vegetation also includes:

[0015] After assigning certain weights to each characteristic representative value, cumulative analysis is performed to obtain a comprehensive representative value R, and it is determined whether the obtained comprehensive representative value R is within the preset standard comprehensive representative value interval [R x , R y ], when the comprehensive representative value R is not within the preset standard comprehensive representative value interval [R x , R y ], it indicates that there is a problem with the health of urban vegetation and a corresponding alarm instruction is generated.

[0016] Furthermore, the method used by the assessment center to determine whether the vegetation has hidden health problems is:

[0017] Through the formula VHI = τ*(α 1 *E S +α 2 *E G +α 3 *E P ) to obtain the health assessment index VHI;

[0018] When VHI>VHI th When the vegetation is judged to have hidden health problems, an alarm instruction is generated;

[0019] Among them, τ is the characteristic influence value, E S is the soil condition value, E G is the vegetation index, E P is the purification status value, α 1 , α 2 and α 3 For their respective preset coefficients, VHI th is the set health assessment coefficient threshold.

[0020] Furthermore, the method for obtaining the characteristic influence value τ is:

[0021] When it is determined that there is no problem with the health of vegetation, obtain the comprehensive representative value R collected daily for n consecutive days. i , so that through the formula Get the daily characteristic representative deviation value Dv i ;

[0022] So through the formula Obtain the characteristic influence value τ;

[0023] Among them, R(x) is the proposed comprehensive representative value R changing with the number of days x, R 0 (x) is the preset standard curve of comprehensive representative value changing with the number of days, x 1 is the number of days from the start of monitoring, x 2 is the number of days when monitoring ends, and i∈(1,n).

[0024] Furthermore, the soil condition value E S , vegetation index E G And the purification status value E P The method to obtain it is:

[0025] When judging that there is no problem with the health of vegetation, obtain the pH value of vegetation soil collected for n consecutive days W pH , nutrient content W nc , Pollutant content in vegetation soil pe , respectively, to develop soil pH value, nutrient content, pollutant content with the number of days curve W pH (x), W nc (x), W pe (x);

[0026] Thus through The soil condition influence value E is obtained S ;

[0027] in, They are respectively the preset standard curves of soil pH value and nutrient content changing with days;

[0028] When it is determined that there is no problem with the health of the vegetation, the chlorophyll changes of the vegetation over n consecutive days are obtained, so as to formulate a curve of the change of chlorophyll content with the number of days, and based on the historical growth data of the same vegetation in the local area, a standard curve of the change of chlorophyll content with the number of days is preset;

[0029] In the same coordinate system, the area below the preset chlorophyll content changing with days standard curve and above the proposed chlorophyll content changing with days curve is defined as S Y ;

[0030] At the same time, get the vegetation coverage rate on the first day and vegetation coverage on the last day

[0031] By formula The vegetation index E G ;

[0032] If the vegetation health status is judged to be normal, obtain the average CO2 content of the vegetation area every day for n consecutive days. 2 Content, and draw up a curve of content changing with days 2 (x);

[0033] The curve CO 2 (x) is divided into two segments, and the slope k of each segment is obtained respectively. 1 , k 2 ;

[0034] So through the formula The purification status value E is obtained P ;

[0035] Among them, z 0 , and k 0 These are the reference values ​​for comparison set by each party.

[0036] Furthermore, the alarm instructions include real-time alarms and real-time warnings. A real-time alarm is generated when it is determined that there is a problem with the health status of urban vegetation, and a real-time warning is generated when it is determined that there are hidden health problems in the vegetation.

[0037] Beneficial effects of the present invention:

[0038] The present invention first obtains vegetation image information of each planting area, and performs corresponding analysis and processing to obtain multiple feature information about the vegetation, so as to intuitively analyze and judge whether there is any obvious abnormality in the health status of the vegetation based on the feature information. The present invention can automatically analyze and complete the detection without the need for patrol personnel to conduct patrol inspections, which can greatly improve the accuracy of judgment and save human resource costs.

[0039] The present invention can conduct a comprehensive analysis based on the vegetation soil conditions, vegetation growth conditions, and vegetation carbon fixation conditions to determine whether normal vegetation has hidden or potential health problems, and issue corresponding alarms for vegetation or areas with hidden health problems. This can provide timely warnings and interventions to avoid health problems in vegetation and ensure the normal growth of vegetation.

[0040] Of course, any product implementing the present invention does not necessarily need to achieve all of the advantages described above at the same time. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for describing the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0042] Figure 1 It is a system block diagram of the present invention. DETAILED DESCRIPTION

[0043] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0044] In one embodiment, a real-time urban vegetation health assessment and early warning system is disclosed. Figure 1 As shown in the figure, the early warning system mainly includes:

[0045] An image acquisition module is used to acquire vegetation image information of each planting area and upload it to the evaluation center;

[0046] Data collection module: The data collection module is used to obtain relevant data information of the planting area and upload it to the evaluation center. The relevant data information includes soil pH value, soil nutrient content, vegetation soil pollutant content and CO 2 content;

[0047] The evaluation center is used to analyze and process the acquired information to evaluate whether there are any problems with the health status of the vegetation. When it is determined that there are problems with the health status of the vegetation, a corresponding alarm instruction is generated. At the same time, when it is determined that there are no problems with the health status of the vegetation, the health status of the vegetation is further analyzed to determine whether there are any hidden health problems in the vegetation, thereby generating a corresponding alarm instruction;

[0048] The early warning module issues corresponding alarm reminders for health problems based on the alarm instructions generated by the assessment center.

[0049] Through the above technical solution, the present application first obtains the vegetation image information of each planting area every day through the image acquisition module and uploads it to the evaluation center. After being processed by the evaluation center, multiple feature information about the vegetation can be obtained, so as to intuitively analyze and judge whether the health status of the vegetation is obviously abnormal based on the feature information. The analysis can be completed automatically without the need for patrol personnel to conduct patrol inspections, which can greatly improve the accuracy of judgment and save human resource costs. At the same time, the data acquisition module also obtains relevant associated data information of the planting area, including soil pH value, soil nutrient content, vegetation soil pollutant content, and CO2 in the vegetation area. 2 The content is uploaded to the assessment center, and the vegetation with no health problems is further analyzed in combination with the characteristics of the vegetation to determine whether the vegetation has hidden health problems. This will allow early warning of vegetation or vegetation areas with hidden health problems, thereby reducing the occurrence of obvious health problems in vegetation, ensuring the normal growth of vegetation, and reducing vegetation losses.

[0050] As an embodiment of the present invention, the method for the assessment center to assess whether there is a problem with the health status of vegetation includes: after correcting, cutting, and denoising the acquired image information, using image processing technology to obtain various feature information of the image, and inputting the acquired feature information into a neural network model trained by using a large amount of annotated image data in the assessment center to obtain feature representative values ​​of various feature information;

[0051] Compare the obtained representative values ​​of each feature with the standard representative value intervals of the same period set by each feature. When the obtained representative value of the feature does not fall into the corresponding standard representative value interval, it indicates that there is a problem with the health status of urban vegetation, and a corresponding alarm instruction is generated;

[0052] The method for the assessment center to assess whether there is a problem with the health of vegetation also includes: assigning certain weights to the obtained characteristic representative values ​​and then accumulating and analyzing them to obtain a comprehensive representative value R, and judging whether the obtained comprehensive representative value R is within the preset standard comprehensive representative value interval [R x , R y ], when the comprehensive representative value R is not within the preset standard comprehensive representative value interval [R x , R y ], it indicates that there is a problem with the health of urban vegetation and a corresponding alarm instruction is generated.

[0053] Through the above technical solution, this embodiment provides a specific method for the assessment center to judge whether there is a problem with the health status of vegetation based on the acquired image information. First, multiple images of the vegetation area are acquired through a high-definition camera or other shooting equipment in the vegetation area, and then the images are corrected, cropped, spliced, denoised, etc. to obtain a precision image. The precision image is subjected to image processing technology to obtain various feature information of the image, such as color, texture, shape, size and other feature information. The acquired feature information is input into a neural network model trained with a large amount of labeled image data to obtain feature representative values ​​corresponding to various feature information. Since each feature has a A normal standard interval is formed, and therefore each obtained feature representative value is compared with the standard feature representative value interval set in the same period. When the obtained feature representative value does not fall into the corresponding standard feature representative value interval, it indicates that there is a problem with the health status of the urban vegetation in the planting area, and a corresponding alarm instruction is generated to issue a reminder alarm. For example, when the detected color feature representative value is not within the preset standard color feature representative value interval, it indicates that the vegetation growth is abnormal, and it is judged that there is a problem with the health of the vegetation. In this way, by analyzing and processing the obtained vegetation images, it is possible to judge whether there is a problem with the health of the vegetation more quickly and accurately based on the feature information of each vegetation image.

[0054] In addition, since the various characteristic information of vegetation may affect each other, a single analysis may have errors. For example, when the various characteristic information does not indicate that there is a problem with the health of the vegetation, if the various characteristic information has changed, the possibility of health problems is also greater. Therefore, the assessment center also provides another judgment method: first give a certain weight to the representative values ​​of each characteristic, and then perform cumulative analysis to obtain a comprehensive representative value R, and judge whether the comprehensive representative value R is within the preset standard comprehensive representative value interval [R x , R y ], when the comprehensive representative value R is not within the preset standard comprehensive representative value interval [R x , R y ], it indicates that there is a problem with the health of urban vegetation, and a corresponding alarm instruction is generated; in this way, a comprehensive analysis can be conducted by combining multiple feature information, which can greatly reduce monitoring errors, improve detection accuracy, and better monitor the health of vegetation.

[0055] In the above technical solution, the standard characteristic representative value interval and the standard comprehensive representative value interval in the same period can be obtained based on the historical planting data of the corresponding area.

[0056] As an implementation of the present invention, the method by which the assessment center determines whether vegetation has hidden health problems is as follows:

[0057] Through the formula VHI = τ*(α 1 *E S +α 2 *E G +α 3 *E P ) to obtain the health assessment index VHI;

[0058] When VHI>VHI th When the vegetation is judged to have hidden health problems, an alarm instruction is generated;

[0059] Among them, τ is the characteristic influence value, E S is the soil condition value, E G is the vegetation index, E P is the purification status value, α 1 , α 2 and α 3 For their respective preset coefficients, VHI th is the health assessment coefficient threshold set;

[0060] The method for obtaining the characteristic impact value τ is as follows: when it is determined that there is no problem with the health of the vegetation, obtain the comprehensive representative value R collected daily for n consecutive days. i , so that through the formula Get the daily characteristic representative deviation value Dv i ;

[0061] So through the formula Obtain the characteristic influence value τ;

[0062] Among them, R(x) is the proposed comprehensive representative value R changing with the number of days x, R 0 (x) is the preset standard curve of comprehensive representative value changing with the number of days, x 1 is the number of days from the start of monitoring, x 2 is the number of days when monitoring ends, and i∈(1,n);

[0063] The soil condition value E S , vegetation index E G And the purification status value E P The method of obtaining the pH value is as follows: when it is determined that there is no problem with the health of the vegetation, obtain the pH value of the vegetation soil collected for n consecutive days W pH , nutrient content W nc , Pollutant content in vegetation soil pe Since there are multiple nutrients or pollutants in the soil, the nutrient content and pollutant content can be determined by accumulating the weighted parameters and respectively proposing the soil pH value, nutrient content, and pollutant content change curves with the number of days W. pH (x), Wnc (x), W pe (x);

[0064] Thus through The soil condition influence value E is obtained S ;

[0065] in, They are respectively the preset standard curves of soil pH value and nutrient content changing with days;

[0066] When it is determined that there is no problem with the health of the vegetation, the chlorophyll changes of the vegetation in the consecutive n days are obtained, so as to formulate the chlorophyll content change curve with the number of days, and according to the historical growth data of the same vegetation in the local area, the standard change curve of the chlorophyll content of the vegetation with the number of days is preset. In the same coordinate system, the area below the preset standard change curve of the chlorophyll content with the number of days and the area above the proposed chlorophyll content change curve with the number of days is defined as S Y ; At the same time, get the vegetation coverage rate on the first day and vegetation coverage on the last day By formula The vegetation index E G , where chlorophyll content and vegetation coverage can be determined based on image processing technology;

[0067] If the vegetation health status is judged to be normal, obtain the average CO2 content of the vegetation area every day for n consecutive days. 2 Content, and draw up a curve of content changing with days 2 (x), the curve CO 2 (x) is divided into two segments, and the slope k of each segment is obtained respectively. 1 , k 2 , so that through the formula The purification status value E is obtained P ;

[0068] Among them, z 0 , and k 0 These are the reference values ​​for comparison set by each party.

[0069] Through the above technical solution, this embodiment provides a method for analyzing and judging hidden monitoring problems of vegetation. Since the health problems of vegetation are closely related to the vegetation soil, in general, the soil must have a suitable pH value and nutrients and the pollutants in the soil must be small enough to ensure the normal growth of vegetation. Therefore, when it is judged that there is no problem with the health of the vegetation, the pH value of the vegetation soil collected for n consecutive days is obtained. pH , nutrient content W nc, Pollutant content in vegetation soil pe , respectively, to develop soil pH value, nutrient content, pollutant content with the number of days curve W pH (x), W nc (x), W pe (x), thus The soil condition influence value E is obtained S ; From the formula, it can be seen that when the difference between the change in soil pH value and the change in standard soil pH value is smaller, the difference between the change in soil nutrient content and the change in standard soil nutrient content is smaller, or the content of pollutants in the soil is less, that is, when the soil condition affects the value E S The smaller it is, the more conducive it is to vegetation growth, and the less likely it is to have health problems. Similarly, the hidden health problems of vegetation can also be judged from the growth of vegetation. For example, if the detected chlorophyll content of vegetation is less than the standard chlorophyll content, or the vegetation coverage rate does not reach the warning coverage rate, it can also indicate that the vegetation has hidden health problems. Therefore, when it is judged that there is no problem with the health of vegetation, the chlorophyll changes of vegetation for n consecutive days are obtained, so as to formulate the chlorophyll content change curve with the number of days, and according to the historical growth data of the same vegetation in the local area, the standard change curve of the chlorophyll content of vegetation with the number of days is preset. In the same coordinate system, the area below the preset standard change curve of the chlorophyll content with the number of days and the area above the proposed chlorophyll content change curve with the number of days is defined as S. Y ; At the same time, get the vegetation coverage rate on the first day and vegetation coverage on the last day By formula The vegetation index E G From the formula, we can know that when the vegetation index E G The smaller the value, the less likely the vegetation is to have health problems. In addition, the health of vegetation can be judged based on the carbon fixation of vegetation. If the carbon fixation is gradually decreasing over a period of time, it means that it is more likely to have health problems. Therefore, if it is judged that there is no problem with the health of vegetation, the average CO2 content of the vegetation area is obtained every day for n consecutive days. 2 Content, and draw up a curve of content changing with days 2 (x), the curve CO 2 (x) is divided into two segments, and the slope k of each segment is obtained respectively. 1 , k 2 , so that through the formula The purification status value E is obtained P ; From the formula, we can know that when the purification status value E P The smaller the vegetation is, the better the carbon fixation is, and the less likely it is to have health problems. Therefore, the formula VHI = τ*(α1 *E S +α 2 *E G +α 3 *E P ) is used for comprehensive analysis to judge the hidden health problems of vegetation, and τ is the characteristic impact value: when it is judged that there is no problem with the health of vegetation, the comprehensive representative value R collected daily for n consecutive days is obtained. i , so that through the formula Get the daily characteristic representative deviation value Dv i , so that through the formula The characteristic influence value τ is obtained; from the formula, it can be known that if the difference between the characteristic representative deviation values ​​obtained every day within n days is smaller, it means that within n days, the volatility of vegetation growth is smaller, which means that its growth is better, and the possibility of health problems is smaller, otherwise, the health assessment coefficient VHI is compared with the set health assessment coefficient threshold. When VHI>VHI th If the vegetation is found to have hidden health problems, an alarm command will be generated to provide a reminder. In this way, a comprehensive analysis can be conducted based on the soil conditions, growth conditions, and carbon fixation conditions of the vegetation to determine whether normal vegetation has hidden or potential health problems, and corresponding alarms can be issued for vegetation or areas with hidden health problems. This will allow for timely warnings and interventions to avoid health problems in vegetation and ensure the normal growth of vegetation.

[0070] In the above technical solution, the preset coefficient α 1 , α 2 and α 3 , set the health assessment coefficient threshold VHI th , respectively set the comparison reference value z 0 , and k 0 All of them can be determined based on historical data combined with empirical data, and the preset standard curve R0(x) of the comprehensive representative value changing with the number of days, the preset standard curve of soil pH value and nutrient content changing with the number of days It can be formulated based on the data in relevant scenarios in big data and the actual situation, which will not be elaborated here.

[0071] As an embodiment of the present invention, the alarm instruction includes real-time alarm and real-time warning. When it is determined that there is a problem with the health status of urban vegetation, a real-time alarm is generated, and when it is determined that the vegetation has hidden health problems, a real-time warning is generated.

[0072] When it is judged that there is a problem with the health status of urban vegetation, a real-time alarm is generated, indicating that the vegetation has health problems. When it is judged that the vegetation has hidden health problems, a real-time warning is generated, indicating that the vegetation has hidden or potential health problems. In this way, the alarms can be distinguished, making it easier for managers to better handle the vegetation.

[0073] It should be noted that the calculation formulas and various parameters involved in the calculations in the present invention have been dimensionally processed in advance, and the process of dimensionless processing is well known in the industry and will not be described here.

[0074] The above contents are merely examples and explanations of the concept of the present invention. The technicians in this technical field may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the concept of the invention or exceed the scope defined by the claims, they should all fall within the protection scope of the present invention.

Claims

1. A real-time assessment and early warning system for urban vegetation health, characterized in that: The system comprises: An image acquisition module, which is used to acquire vegetation image information of each planting area and upload it to an evaluation center; A data collection module, which is used to obtain relevant data information of the planting area and upload it to the evaluation center; An evaluation center is used to analyze and process the acquired information to evaluate whether there is a problem with the health status of the vegetation. When it is determined that there is a problem with the health status of the vegetation, a corresponding alarm instruction is generated. At the same time, when it is determined that there is no problem with the health status of the vegetation, the health status of the vegetation is further analyzed to determine whether there is a hidden health problem in the vegetation, thereby generating a corresponding alarm instruction; The early warning module issues corresponding alarm reminders for health problems according to the alarm instructions generated by the assessment center.

2. The urban vegetation health real-time assessment and early warning system according to claim 1 is characterized in that: The methods used by the assessment center to assess whether there are any problems with the health of vegetation include: After the acquired image information is corrected, cropped, and denoised, image processing technology is used to obtain various feature information of the image, and the acquired feature information is input into the neural network model trained with a large amount of annotated image data in the evaluation center to obtain the feature representative values ​​of various feature information; The obtained representative values ​​of each feature are compared with the standard representative value intervals of the same period set by each. When the obtained representative value of the feature does not fall into the corresponding standard representative value interval, it indicates that there is a problem with the health status of the urban vegetation, and a corresponding alarm instruction is generated.

3. The urban vegetation health real-time assessment and early warning system according to claim 2 is characterized in that: The method for the assessment center to assess whether there is a problem with the health status of vegetation also includes: After assigning certain weights to each characteristic representative value, cumulative analysis is performed to obtain a comprehensive representative value R, and it is determined whether the obtained comprehensive representative value R is within the preset standard comprehensive representative value interval [R x , R y ], when the comprehensive representative value R is not within the preset standard comprehensive representative value interval [R x , R y ], it indicates that there is a problem with the health of urban vegetation and a corresponding alarm instruction is generated.

4. The urban vegetation health real-time assessment and early warning system according to claim 3 is characterized in that: The method used by the assessment center to determine whether vegetation has hidden health problems is: Through the formula VHI = τ*(α1*E S +α2*E G +α3*E P ) to obtain the health assessment index VHI; When VHI>VHI th When the vegetation is judged to have hidden health problems, an alarm instruction is generated; Among them, τ is the characteristic influence value, E S is the soil condition value, E G is the vegetation index, E P is the purification status value, α1, α2 and α3 are the respective preset coefficients, VHI th is the set health assessment coefficient threshold.

5. The urban vegetation health real-time assessment and early warning system according to claim 4 is characterized in that: The method for obtaining the characteristic influence value τ is: When it is determined that there is no problem with the health of vegetation, obtain the comprehensive representative value R collected daily for n consecutive days. i , so that through the formula Get the daily characteristic representative deviation value Dv i ; So through the formula Obtain the characteristic influence value τ; Among them, R(x) is the proposed comprehensive representative value R changing with the number of days x, R0(x) is the preset standard curve of the comprehensive representative value changing with the number of days, x1 is the number of days when monitoring starts, x2 is the number of days when monitoring ends, and i∈(1,n).

6. The urban vegetation health real-time assessment and early warning system according to claim 4 is characterized in that: The soil condition value E S , vegetation index E G And the purification status value E P The method to obtain it is: When judging that there is no problem with the health of vegetation, obtain the pH value of vegetation soil collected for n consecutive days W pH , nutrient content W nc , Pollutant content in vegetation soil pe , respectively, to develop soil pH value, nutrient content, pollutant content with the number of days curve W pH (x), W nc (x), W pe (x); Thus through The soil condition influence value E is obtained S ; in, They are respectively the preset standard curves of soil pH value and nutrient content changing with days; When it is determined that there is no problem with the health of the vegetation, the chlorophyll changes of the vegetation over n consecutive days are obtained, so as to formulate a curve of the change of chlorophyll content with the number of days, and based on the historical growth data of the same vegetation in the local area, a standard curve of the change of chlorophyll content with the number of days is preset; In the same coordinate system, the area below the preset chlorophyll content changing with days standard curve and above the proposed chlorophyll content changing with days curve is defined as S Y ; At the same time, get the vegetation coverage rate on the first day and vegetation coverage on the last day By formula The vegetation index E G ; If the health of the vegetation is judged to be healthy, the average CO2 content of the vegetation area is obtained every day for n consecutive days, and a curve of CO2(x) with the change of content over the number of days is drawn up; Divide the curve CO2(x) into two segments evenly, and obtain the slopes k1 and k2 in each segment respectively; So through the formula The purification status value E is obtained P ; Among them, z0, And k0 are the comparison reference values ​​set respectively.

7. The urban vegetation health real-time assessment and early warning system according to claim 6 is characterized in that: The alarm instructions include real-time alarms and real-time warnings. A real-time alarm is generated when it is determined that there is a problem with the health status of urban vegetation, and a real-time warning is generated when it is determined that there is a hidden health problem in the vegetation.

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