A method for evaluating the health of landscape plants

Abstract

The present invention relates to the field of resource assessment technology, and in particular to a method for assessing the health of garden landscape plants. The method obtains an environmental tolerance factor based on the change correlation between the physiological parameter assessment value and the environmental assessment value of the sample plant in the historical time period, combined with the distribution stability of the physiological parameter assessment value; obtains the abnormal growth disorder coefficient based on the growth rate of the sample plant and the degree of change of the environmental assessment value; obtains the health status from the deviation change of the chlorophyll content of the sample plant; obtains the assessment index and obtains the health assessment result based on the current environmental assessment value and the environmental tolerance factor, the abnormal growth disorder coefficient and the health status coefficient. The present invention obtains a more accurate health assessment by analyzing the environmental interference of the plant itself, combined with the rate abnormality and state changes during the growth process, and improves the reliability of the results of the plant health assessment.

Description

Technical Field

[0001] The present invention relates to the technical field of resource assessment, and in particular to a method for assessing the health of garden landscape plants. Background Art

[0002] The design, construction and maintenance of landscapes are important components of urban planning and management. During the landscape maintenance phase, landscape plant health assessment is a systematic process used to assess and monitor the health of plants in the garden. By real-time assessment of the health of garden plants, pests and diseases, malnutrition or other plant growth problems can be discovered and dealt with in a timely manner, thereby maintaining the overall beauty and quality of the landscape and ensuring the sustainable development of the landscape.

[0003] The general health assessment of landscape plants relies on the processing and analysis of data collected by sensors. It usually extracts features and builds models to analyze plant growth trends, identify diseases, and respond to environmental changes, and then sets thresholds to screen and warn of abnormal plant conditions. However, since different plants are subject to different environmental interference during their growth, the degree to which their own changes are interfered with by the external environment is also different, resulting in a high degree of environmental interference in general abnormal assessments, and the accuracy of health assessment results is low. Summary of the invention

[0004] In order to solve the technical problem of inaccurate plant health assessment in the prior art, the purpose of the present invention is to provide a method for evaluating the health of landscape plants. The technical solution adopted is as follows:

[0005] The present invention provides a method for evaluating the health of garden plants, the method comprising:

[0006] Obtain the physiological parameter evaluation values, environmental evaluation values, growth rate and chlorophyll content of the sample plants at each sampling moment in the historical period;

[0007] According to the correlation between the physiological parameter evaluation value and the environmental evaluation value of the sample plant in the historical period, as well as the distribution stability of the physiological parameter evaluation value, the environmental tolerance factor of the sample plant is obtained;

[0008] According to the unstable changes in the growth rate of the sample plants in the historical period, as well as the degree of change of the environmental assessment value and the environmental tolerance factor, the growth abnormality disorder coefficient of the sample plants is obtained;

[0009] According to the deviation of the chlorophyll content of the sample plant at the current moment and in the historical time period, the health status coefficient of the sample plant is obtained;

[0010] The evaluation index of the sample plant is obtained by combining the environmental evaluation value of the sample plant at the current moment, as well as the environmental tolerance factor, the abnormal growth disorder coefficient and the health status coefficient; and the health evaluation result of the sample plant is obtained based on the evaluation index of the sample plant.

[0011] Furthermore, the method for obtaining the environmental tolerance factor includes:

[0012] The information entropy of the physiological parameter evaluation values ​​of the sample plants at all sampling moments is used as the change sensitivity of the sample plants;

[0013] Arrange all physiological parameter evaluation values ​​of the sample plants in the historical time period in chronological order to obtain a physiological parameter sequence; arrange all environmental evaluation values ​​of the sample plants in the historical time period in chronological order to obtain an environmental sequence; calculate the correlation between the physiological parameter sequence and the environmental sequence to obtain the change correlation of the sample plants;

[0014] The environmental tolerance factor of the sample plants is obtained by combining the change sensitivity and change correlation of the sample plants.

[0015] Furthermore, the method for obtaining the growth abnormality disorder coefficient includes:

[0016] Divide the historical time period into a preset number of local time periods;

[0017] In each local time period, according to the number and degree of change of the environmental assessment value of the sample plant and the environmental tolerance factor, the environmental correction weight of the sample plant in each local time period is obtained;

[0018] The frequency of changes in the growth rate of the sample plant in each local time period is used as the disorder abnormality degree of the sample plant in each local time period;

[0019] The abnormal growth coefficient of the sample plants is obtained by weighting the abnormal disorder degree with the environmental correction weight of each local time period and averaging the results.

[0020] Furthermore, the method for obtaining the environment correction weight includes:

[0021] In any local time period, when the environmental assessment value at each sampling moment is different from the previous sampling moment in the time series, the sampling moment is regarded as the change moment;

[0022] Count the number of change moments in the local time period as the number of environment changes in the local time period;

[0023] In the local time period, the difference between the environmental evaluation value at each change moment and the environmental evaluation value at the previous sampling moment in the time series is taken as the change degree at each change moment; the environmental deviation degree of the local time period is obtained by combining the change degrees of all change moments in the local time period;

[0024] Combining the number of environmental changes and the environmental deviation in the local time period, obtaining the environmental change index in the local time period;

[0025] According to the environmental change index of the local time period and the environmental tolerance factor of the sample plant, the environmental correction weight of the local time period is obtained.

[0026] Furthermore, obtaining the environmental correction weight of the local time period according to the environmental change index of the local time period and the environmental tolerance factor of the sample plant includes:

[0027] The ratio of the environmental change index and the environmental tolerance factor in the local time period is negatively correlated and normalized to obtain the environmental correction weight of the local time period.

[0028] Furthermore, the method for obtaining the disorder abnormality degree includes:

[0029] When the growth rate of the sampling moment in each local time period is different from the growth rate of the previous sampling moment in the time series, the corresponding sampling moment is regarded as an abnormal moment;

[0030] The total number of abnormal moments in each local time period is counted as the disorder abnormality degree of each local time period.

[0031] Furthermore, the method for obtaining the health status coefficient includes:

[0032] Obtain the periodicity of chlorophyll content changes over a historical period; use the difference between the periodicity of the changes and the preset periodicity as a period deviation indicator for the sample plants;

[0033] According to the difference between the chlorophyll content at each sampling moment in the historical time period and the current moment, the state deviation index of the sample plant is obtained;

[0034] The health status coefficient of the sample plant is obtained by combining the period deviation index and the state deviation index of the sample plant.

[0035] Furthermore, the method for obtaining the state deviation indicator includes:

[0036] For any sampling moment in the historical time period, the difference in chlorophyll content between the sampling moment and the current moment is used to obtain the deviation value of the sampling moment; the time interval between the sampling moment and the current moment is negatively correlated to obtain the interval weight of the sampling moment;

[0037] The deviation value is weighted and averaged by the spacing weight at each sampling moment to obtain the state deviation index of the sample plant.

[0038] Furthermore, the method for obtaining the evaluation index includes:

[0039] The product of the value of negative correlation mapping of the growth abnormal disorder coefficient of the sample plant and the health status coefficient is used as the status indicator of the sample plant;

[0040] Normalize the product of the environmental tolerance factor of the sample plant and the environmental assessment value at the current moment to obtain the environmental adjustment index of the sample plant;

[0041] The product of the state index of the sample plant and the environmental adjustment index is normalized to obtain the evaluation index of the sample plant.

[0042] Furthermore, the health assessment result of the sample plant obtained based on the assessment index of the sample plant includes:

[0043] When the evaluation index is greater than the preset first health index, the health evaluation result of the sample plant is recorded as healthy;

[0044] When the evaluation index is less than or equal to the preset first health index and greater than the preset second health index, the health evaluation result of the sample plant is recorded as sub-healthy;

[0045] When the evaluation index is less than or equal to the preset second health index, the health evaluation result of the sample plant is recorded as unhealthy;

[0046] The preset first health indicator is greater than the preset second health indicator.

[0047] The present invention has the following beneficial effects:

[0048] The present invention analyzes the change correlation between the physiological parameter evaluation value of the sample plant itself and the environmental evaluation value in the historical time period, and obtains the environmental tolerance factor in combination with the distribution of the physiological parameter evaluation value, thereby analyzing the degree of interference resistance of each plant to environmental changes, so as to reduce the degree of influence of the environment when the subsequent analysis is abnormal. Further combined with the abnormal growth rate of the sample plant under the influence of environmental changes, the abnormal growth disorder coefficient is obtained, thereby adjusting the abnormal growth rate analysis process in combination with the environmental situation to reduce the interference of environmental effects. Further, the health status of the growth supply is reflected from the stage change of the chlorophyll content of the sample plant, so as to facilitate the subsequent comprehensive analysis of accurate plant health. Finally, based on the current environmental evaluation value and the environmental tolerance factor, the abnormal growth disorder coefficient and the health status coefficient, the evaluation of the plant is comprehensively reflected, the evaluation index is obtained and the health evaluation result is obtained. The present invention analyzes the environmental interference of the plant itself, combines the rate abnormality and state changes in the growth process, and comprehensively obtains a more accurate health assessment, thereby improving the reliability of the results of the plant health assessment. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0050] Figure 1 A flow chart of a method for evaluating the health of landscape plants provided by one embodiment of the present invention;

[0051] Figure 2 A flow chart of a method for obtaining a growth abnormality disorder coefficient provided by one embodiment of the present invention;

[0052] Figure 3 A flow chart of a method for obtaining a health status coefficient provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0053] In order to further explain the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the following is a detailed description of a garden landscape plant health assessment method proposed by the present invention, its specific implementation method, structure, characteristics and effects, in conjunction with the accompanying drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" does not necessarily refer to the same embodiment. In addition, specific features, structures or characteristics in one or more embodiments may be combined in any suitable form.

[0054] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

[0055] The specific scheme of the garden landscape plant health assessment method provided by the present invention is described in detail below with reference to the accompanying drawings.

[0056] See also Figure 1 , which shows a flow chart of a garden landscape plant health assessment method provided by an embodiment of the present invention, the method comprising the following steps:

[0057] S1: Obtain the physiological parameter evaluation values, environmental evaluation values, growth rate and chlorophyll content of the sample plants at each sampling time in the historical time period.

[0058] Since the growth environment of landscape plants is dynamically changing, the plants themselves will also change their state when they are disturbed by the external environment. For example, under extremely high temperature conditions, plants may adapt to the environment by slowing down their growth rate or changing the shape of their leaves. For example, the leaves of some plants may become thicker to reduce water evaporation, or the growth cycle may be shortened to complete the life cycle faster and avoid excessive stress under high temperatures.

[0059] These adaptive changes are strategies for plants to maintain a healthy state in adverse conditions, which are different from abnormal growth caused by pests and diseases. By comprehensively considering environmental factors and plant adaptability, the health status of plants can be more accurately assessed. Therefore, through comprehensive analysis of data from different dimensions of sample plants over historical time periods, the growth status of plants and the growth environment can be analyzed from multiple aspects.

[0060] In some possible implementations of the embodiments of the present invention, both the physiological parameter evaluation values ​​and the environmental evaluation values ​​are obtained through a trained neural network model. This embodiment uses the trained neural network model to evaluate the growth status of the plant, collects plant images and plant multispectral data at each sampling moment, and inputs them into the neural network model, and outputs the physiological parameter evaluation value at each sampling moment. The physiological parameter evaluation value is a score between 1-10, and the higher the value, the more the physiological parameter is within the normal range of plant growth.

[0061] In this embodiment, an integrated sensor group is arranged around sample plants in the garden landscape to obtain environmental data of the sample plants. Environmental data such as monitoring data such as light, temperature and humidity are input into the trained neural network model for environmental assessment, and the environmental assessment value of each sampling moment is output. The environmental assessment value is a score between 1 and 10. The higher the value, the more suitable the overall environmental data is for plant growth.

[0062] In this embodiment, a group of RGB cameras are installed around the sample plants to ensure that the cameras can capture the growth conditions of the plants at different angles, obtain growth image data of the sample plants at each sampling moment, and use image feature extraction and tracking based on the difference between the growth image data at the previous sampling moment to obtain the growth rate of the sample plants at each sampling moment.

[0063] This embodiment uses chlorophyll phosphors to obtain the chlorophyll content of the sample plant at each sampling time.

[0064] In a specific implementation method of an embodiment of the present invention, the historical time period is set to one month, and the time interval between sampling moments is set to 6 hours. The specific numerical values ​​can be adjusted by the implementer and are not limited here. It should be noted that all collected data are de-dimensionalized to avoid dimensional influence. The specific data collection process and de-dimensionalization are technical processes well known to technical personnel in this field and will not be elaborated here.

[0065] S2: Obtain the environmental tolerance factor of the sample plant based on the correlation between the physiological parameter evaluation value and the environmental evaluation value of the sample plant in the historical time period, as well as the distribution stability of the physiological parameter evaluation value.

[0066] During the process of plant growth and survival, each plant has unique physiological mechanisms and decisions to adapt to the environment. Each plant has a different degree of tolerance to environmental changes. When the plant's tolerance to environmental changes is low, the abnormal changes in the plant are most likely made to adapt to the environment.

[0067] Therefore, the correlation changes between the physiological parameters of the sample plants and the environment over historical time reflect the direct degree of environmental influence. When there is a strong correlation between the physiological parameter evaluation value and the environmental evaluation value, it means that the plants have obvious changes in response to environmental changes.

[0068] Whether the physiological parameters of the sample plants themselves are stable can further reflect the stability of the physiological parameters of the plants themselves under different time and environment conditions. The more unstable the distribution of the physiological parameter evaluation values ​​is, the more changes there are in the plants under different time or environmental conditions, and the higher the sensitivity of the changes in the plant physiological parameters is.

[0069] The environmental tolerance factor is obtained by comprehensively considering the correlation between the physiological parameter evaluation values ​​and the environmental evaluation values, as well as the distribution stability of the physiological parameter evaluation values, which reflects the extent to which the physiological parameters of the sample plants are affected by external environmental interference.

[0070] S3: According to the unstable changes in the growth rate of the sample plants in the historical time period, as well as the degree of change of the environmental assessment value and the environmental tolerance factor, the abnormal growth disorder coefficient of the sample plants is obtained.

[0071] Under stable environmental conditions, the same plant will show a relatively stable growth rate during the same growth stage. However, when the plant encounters health problems, such as disease or malnutrition, its growth rate is often affected and shows an abnormal growth rate.

[0072] At the same time, in actual situations, changes in external environmental factors will also cause changes in plant growth rates. Therefore, abnormal plant growth rates may be the result of the combined effects of environmental factors and their own diseases. Therefore, when analyzing abnormal growth rates, it is necessary to consider the possibility that plants may be disturbed by the external environment.

[0073] The unstable change of growth rate reflects the abnormal degree of plant growth rate change. The more unstable the growth rate change is, the higher the possibility that the sample plant is unhealthy. At the same time, the change degree of environmental assessment value is combined with environmental tolerance factor to reflect the instability of the environment of the sample plant in the time period and the degree to which the sample plant will be affected. The growth rate change is corrected and finally the growth abnormality disorder coefficient is obtained, which can better characterize the abnormal degree of growth rate caused by the abnormality of the sample plant itself.

[0074] S4: Obtain the health status coefficient of the sample plant according to the change deviation of the chlorophyll content of the sample plant at the current moment and in the historical time period.

[0075] The chlorophyll content in plants usually reflects the level of photosynthesis activity in plants, and explains the growth and health status of plants at every moment. Under normal growth and health conditions, plants receive sufficient light and appropriate nutrition, and their chlorophyll content is relatively stable and does not vary greatly. In addition, the chlorophyll content shows a certain periodicity during the alternation of day and night. Therefore, by analyzing the variation characteristics of the chlorophyll content of sample plants, the physiological health status of the target plants can be more accurately measured.

[0076] Therefore, the overall deviation analysis of the chlorophyll content at the current moment and the chlorophyll content in the historical time period reflects the health status of chlorophyll changes and characterizes the health status of the sample plants in terms of growth supply.

[0077] S5: Combine the environmental assessment value of the sample plant at the current moment, as well as the environmental tolerance factor, the abnormal growth disorder coefficient and the health status coefficient to obtain the evaluation index of the sample plant; obtain the health assessment result of the sample plant based on the evaluation index of the sample plant; obtain the health assessment result of the sample plant based on the evaluation index of the sample plant.

[0078] After comprehensive analysis, the growth disorder coefficient evaluates the abnormal degree of change in the growth rate of plants within a certain period of time, which may be caused by factors such as nutrient levels or pests and diseases. The health status coefficient evaluates the health of the plant's growth supply, which can be reflected in aspects such as leaf color, morphology or growth structure. By combining the evaluation of the two aspects, the growth health of the plant can be more comprehensively characterized.

[0079] At the same time, we also consider the abnormal analysis interference caused by the environment. If the plant is in a favorable environment, such as sufficient water and appropriate light, the health problems analyzed at this time will fully represent the abnormal health status of the plant itself. Or, although the plant is in a bad environment, the plant itself has a high resistance to the environment. At this time, the health problems analyzed can also significantly represent the abnormal health status of the plant itself. When the environment in which the plant itself is located is more unfavorable and the plant is greatly affected by environmental factors, the analyzed health problems will have some abnormal conditions caused by the environment and need to be corrected.

[0080] Therefore, the growth disorder coefficient and health status coefficient of the sample plants are combined with the current environmental assessment value and environmental tolerance factor to obtain more accurate assessment indicators. The sample plants can be evaluated for health based on the current assessment indicators to obtain health assessment results. Subsequently, targeted management suggestions and measures can be proposed based on the health assessment results of garden plants, making the health assessment of garden landscape plants more valuable for practical application and helping to maintain and improve the overall quality and sustainability of garden landscapes.

[0081] In summary, the present invention analyzes the change correlation between the physiological parameter evaluation value and the environmental evaluation value of the sample plant in the historical time period, and obtains the environmental tolerance factor in combination with the distribution of the physiological parameter evaluation value, thereby analyzing the degree of interference resistance of each plant to environmental changes, so as to reduce the degree of influence of the environment when the subsequent analysis is abnormal. Further combined with the abnormal growth rate of the sample plant under the influence of environmental changes, the abnormal growth disorder coefficient is obtained, thereby adjusting the abnormal growth rate analysis process in combination with the environmental conditions to reduce the interference of environmental effects. Further, the health status of the growth supply is reflected from the stage changes of the chlorophyll content of the sample plant, so as to facilitate the subsequent comprehensive analysis of accurate plant health. Finally, based on the current environmental evaluation value and the environmental tolerance factor, the abnormal growth disorder coefficient and the health status coefficient, the evaluation of the plant is comprehensively reflected, the evaluation index is obtained and the health evaluation result is obtained. The present invention analyzes the environmental interference of the plant itself, combines the rate abnormality and state changes during the growth process, and comprehensively obtains a more accurate health assessment, thereby improving the reliability of the results of the plant health assessment.

[0082] Preferably, in some possible implementations of the embodiments of the present invention, the method for obtaining the environmental tolerance factor includes:

[0083] Firstly, the information entropy of the physiological parameter evaluation values ​​of the sample plants at all sampling moments is taken as the change sensitivity of the sample plants. The distribution stability of the physiological parameter evaluation values ​​is reflected from the calculation of the information entropy. The larger the information entropy, the more complex and changeable the physiological parameter evaluation values ​​in the historical time period are. Therefore, it reflects that the plants are more sensitive to environmental changes at different times, and therefore the greater the change sensitivity.

[0084] Furthermore, all physiological parameter evaluation values ​​of the sample plants in the historical time period are arranged in chronological order to obtain a physiological parameter sequence, and all environmental evaluation values ​​of the sample plants in the historical time period are arranged in chronological order to obtain an environmental sequence. Both the physiological parameter evaluation values ​​and the environmental evaluation values ​​are sorted in chronological order to facilitate correlation analysis.

[0085] The correlation between the physiological parameter sequence and the environmental sequence is further calculated to obtain the change correlation of the sample plant. In the embodiment of the present invention, the absolute value of the Pearson correlation coefficient between the physiological parameter sequence and the environmental sequence is used to obtain the change correlation. The greater the change correlation, the stronger the linear correlation between the physiological parameter evaluation value and the environmental evaluation value. It should be noted that the method of calculating the sequence correlation of the Pearson correlation coefficient is a technical means well known to those skilled in the art and will not be described in detail here.

[0086] Finally, the environmental tolerance factor of the sample plants was obtained by combining the change sensitivity and change correlation of the sample plants. The environmental tolerance of the sample plants in the historical time period was measured by comprehensively considering the stability of the physiological parameter evaluation values ​​of the sample plants in the historical time period, as well as the related properties of the changes in the physiological parameters and the environment. The greater the change sensitivity and the greater the change correlation, the more disordered the physiological parameter evaluation values ​​of the sample plants were in the historical time period, and there was a strong correlation between the physiological parameter evaluation values ​​and the environmental conditions, which means that the sample plants were more affected by environmental disturbances and had lower tolerance.

[0087] In an embodiment of the present invention, the product of the change sensitivity and the change correlation of the sample plant is negatively correlated to obtain the environmental tolerance factor of the sample plant. It should be noted that the negative correlation mapping represents a mapping relationship, and when the independent variable decreases, the dependent variable increases. The negative correlation mapping method is a technical means well known to those skilled in the art, and can adopt inverse proportion or negative exponential idempotence, which is not limited here.

[0088] Preferably, in some possible implementations of the embodiments of the present invention, the method for obtaining the growth abnormality disorder coefficient is as follows: Figure 2 , which shows a flow chart of a method for obtaining a growth abnormality disorder coefficient provided by an embodiment of the present invention, the method comprising the following steps:

[0089] S301: Divide the historical time period into a preset number of local time periods.

[0090] Taking into account the stage-by-stage nature of the stability situation, the historical time periods are divided and analyzed, and anomaly analysis is performed through the stability changes in each local time period after division. In the embodiment of the present invention, the preset number is set to 7, and the implementer can adjust the specific numerical setting according to the specific implementation scenario, which is not limited here.

[0091] S302: In each local time period, according to the number of changes and degree of changes in the environmental assessment value of the sample plant and the environmental tolerance factor, the environmental correction weight of the sample plant in each local time period is obtained.

[0092] For each local time period, the instability of the changes in the environmental assessment values ​​is analyzed, and combined with the environmental tolerance factor, it reflects the significance of the abnormal growth rate of the sample plants due to environmental factors in the local time period. When the instability is high and the environmental tolerance is poor, the possibility of abnormal growth of the sample plants due to environmental factors in the local time period is higher. Therefore, the environmental correction weight is obtained through the instability and environmental tolerance factor for subsequent regulation.

[0093] Preferably, in the embodiment of the present invention, in any local time period, when each sampling moment is different from the environmental assessment value of the previous sampling moment in the time sequence, the sampling moment is taken as the change moment, and the change moment that has changed is first determined by the degree of similarity between the values ​​of each sampling moment and the previous sampling moment. It should be noted that only the case where there is a previous sampling moment in the local time period is screened, and the first sampling moment without a previous sampling moment is not analyzed as a change moment.

[0094] Furthermore, the number of change moments in the local time period is counted as the number of environmental changes in the local time period. The greater the number of change moments, the more unstable the environmental change is.

[0095] Furthermore, within the local time period, the difference between the environmental evaluation value at each change moment and the environmental evaluation value at the previous sampling moment in the time series is used as the degree of change at each change moment, characterizing the degree of change deviation each time a change occurs. The degree of change of all change moments within the local time period is combined to obtain the environmental deviation degree of the local time period, reflecting the overall degree of change deviation over the time period. In an embodiment of the present invention, the sum of the degrees of change of all change moments within the local time period is used as the environmental deviation degree of the local time period, and is combined in an accumulated form.

[0096] Furthermore, the number of environmental changes and the degree of environmental deviation in the local time period are combined to obtain the environmental change index of the local time period. The greater the number of environmental changes and the degree of environmental deviation, the higher the degree of instability and the greater the degree of change in the local time period, which reflects that the external environment has a high impact. In an embodiment of the present invention, the product of the number of environmental changes and the degree of environmental deviation in the local time period is used as the environmental change index of the local time period, and is combined in the form of multiplication.

[0097] Finally, the environmental correction weight of the local time period is obtained based on the environmental change index of the local time period and the environmental tolerance factor of the sample plants. When the environmental change index is larger and the environmental tolerance factor is smaller, the change is more significant when the plant is affected by a higher environment. At this time, the possibility that the abnormal growth rate in the local time period is caused by the environment is higher.

[0098] In an embodiment of the present invention, the ratio of the environmental change index to the environmental tolerance factor of the local time period is negatively correlated and normalized to obtain the environmental correction weight of the local time period. The ratio of the environmental change index to the environmental tolerance factor is used to reflect the possibility of abnormalities caused by the environment. When the ratio is larger, the influence of environmental factors is greater, and the degree of growth rate abnormality caused by the plant itself is smaller. Therefore, a smaller environmental correction weight is given to the local time period through negative correlation mapping to reduce the impact ratio in subsequent abnormality analysis.

[0099] As an example, the expression for the environmental correction weight is: ; In the formula, Expressed as The environmental correction weight for each local time period, Expressed as The number of environmental changes in a local time period, Expressed as The environmental deviation degree of a local time period, Indicates the environmental tolerance factor of the sample plant, Expressed as Environmental change indicators for a local time period, Expressed as an exponential function with a natural constant as base.

[0100] S303: The frequency of changes in the growth rate of the sample plant in each local time period is used as the disorder abnormality degree of the sample plant in each local time period.

[0101] The degree of abnormality is reflected by the unstable changes in the growth rate in the local time period. The higher the number of changes, the higher the degree of abnormality of the growth rate. Preferably, in an embodiment of the present invention, when the growth rate at the sampling moment in each local time period is different from the growth rate at the previous sampling moment in time series, the corresponding sampling moment is taken as the abnormal moment, and the moment when the growth rate changes is determined.

[0102] The total number of abnormal moments in each local time period is further counted as the disorder abnormality of each local time period. The more abnormal moments there are, the more unstable the growth rate distribution is, and thus the greater the disorder abnormality is.

[0103] S304: Weighting the disorder anomaly degree by the environmental correction weight of each local time period and calculating the average value to obtain the growth abnormal disorder coefficient of the sample plant.

[0104] By adjusting the environmental correction weights, the local time periods with high possibility of abnormalities caused by environmental factors have lower proportion of disorder abnormality, and the weighted average of sampling is used to obtain the growth disorder coefficient that characterizes the possibility of abnormal changes caused by the sample plants' own diseases.

[0105] In an embodiment of the present invention, the product of the environmental correction weight and the disorder abnormality of each local time period is used as the corrected abnormality of each local time period, and the mean of the corrected abnormality of all local time periods is calculated to obtain the growth abnormal disorder coefficient of the sample plant.

[0106] Preferably, in some possible implementations of the embodiments of the present invention, the method for obtaining the health status coefficient can be found in Figure 3 , which shows a flow chart of a method for obtaining a health status coefficient provided by an embodiment of the present invention, the method comprising the following steps:

[0107] S401: Obtain the periodicity of the change of chlorophyll content in the historical time period; and use the difference between the periodicity of the change and the preset periodicity as a period deviation indicator of the sample plant.

[0108] Considering that the chlorophyll content has a certain periodicity, a periodic analysis of the chlorophyll content in the historical time period is conducted. When the periodicity in the historical time period is closer to the ideal periodicity, it means that the change of chlorophyll is more normal and good, and the growth state of the sample plants is healthier.

[0109] In one embodiment of the present invention, a curve fitting is performed on the chlorophyll contents arranged in chronological order over a historical time period to obtain a chlorophyll change curve, which reflects the changing state of chlorophyll over time. An autocorrelation function is used to extract periodicity from the chlorophyll change curve to obtain the periodicity of the change of chlorophyll content over the historical time period, which reflects the periodic changes in the historical time period.

[0110] The difference between the changing periodicity and the preset periodicity is further used as a period deviation index of the sample plant. The preset periodicity is the ideal chlorophyll content changing period. The greater the difference between the changing periodicity and the preset periodicity, the more likely it is that the chlorophyll content change in the sample plant is irregular, that is, the change is less likely to be periodic.

[0111] In a specific implementation method of the embodiment of the present invention, the preset periodicity is set to 12 hours, and the specific value is not limited. It should be noted that the method of curve fitting and extracting periodicity from the autocorrelation function is a well-known technical means well known to those skilled in the art, and will not be described in detail here.

[0112] S402: Obtain a state deviation index of the sample plant according to the difference between the chlorophyll content at each sampling moment in the historical time period and the current moment.

[0113] Considering the possibility that the normal chlorophyll content of plants may change to a certain extent at different growth stages, when conducting deviation analysis on the chlorophyll at the current moment, the closer the time is to the sampling moment, the higher the credibility of the analysis deviation degree.

[0114] Preferably, in an embodiment of the present invention, for any sampling moment in the historical time period, the difference in chlorophyll content between the sampling moment and the current moment is used to obtain the deviation value of the sampling moment, reflecting the degree of chlorophyll deviation at the sampling moment. The time interval between the sampling moment and the current moment is negatively correlated to obtain the spacing weight of the sampling moment. By the time interval, the shorter the time interval of the sampling moment, the heavier the deviation value analysis ratio.

[0115] The deviation value is further weighted and averaged by the spacing weight at each sampling moment to obtain the state deviation index of the sample plant. The sampling weighted average is used to comprehensively obtain the state deviation index that characterizes the overall deviation level of chlorophyll content in the sample plant over the time period.

[0116] In the embodiment of the present invention, the product of the spacing weight and the deviation value at each sampling moment is used as the adjusted deviation value at each sampling moment, and the mean of the adjusted deviation values ​​at all sampling moments is calculated to obtain the state deviation index of the sample plant.

[0117] S403: Combining the period deviation index and the state deviation index of the sample plant, obtaining the health state coefficient of the sample plant.

[0118] Taking into account the deviation of the periodic changes of chlorophyll and the deviation of the numerical value of the historical data content, the larger the periodic deviation index and the state deviation index, the more significant the periodic deviation of the chlorophyll content in the historical time period and the more significant the overall numerical deviation, which indicates that the health status of the sample plants is worse, that is, the smaller the health status coefficient is.

[0119] In the embodiment of the present invention, the product of the period deviation index and the state deviation index of the sample plant is negatively correlated and normalized to obtain the health state coefficient of the sample plant. As an example, the expression of the health state coefficient is:

[0120] ; In the formula, Expressed as the health status coefficient of the sample plants, Expressed as a period deviation index of the sample plants, Expressed as the state deviation index of the sample plant, It is expressed as a normalization function. It should be noted that normalization is a technical means well known to those skilled in the art. The normalization function can be linear normalization or standard normalization, etc. The specific normalization method is not limited here.

[0121] Preferably, in some possible implementation methods of the embodiments of the present invention, the method for obtaining the evaluation index includes:

[0122] First, the product of the negative correlation mapping value of the abnormal growth disorder coefficient of the sample plant and the health status coefficient is used as the status indicator of the sample plant. The smaller the abnormal growth disorder coefficient is and the larger the health status coefficient is, the healthier the growth status of the sample plant is and the larger the status indicator is.

[0123] Furthermore, the product of the environmental tolerance factor of the sample plant and the environmental assessment value at the current moment is normalized to obtain the environmental adjustment index of the sample plant. The higher the environmental assessment value of the sample plant at the current moment and the higher the environmental tolerance factor, the less the sample plant is affected by the environment, and the degree of retention of the health status analysis results is higher, so the environmental adjustment index is larger.

[0124] Finally, the product of the state index of the sample plant and the environmental adjustment index is normalized to obtain the evaluation index of the sample plant. The larger the evaluation index is, the healthier the state of the sample plant is.

[0125] Preferably, in some possible implementations of the embodiments of the present invention, obtaining a health assessment result of the sample plant based on the assessment index of the sample plant includes:

[0126] Based on the evaluation index, the health evaluation of the plant is judged by setting a threshold. In this embodiment, the health evaluation results are divided into three levels: healthy, sub-healthy and unhealthy. The division is performed by presetting two thresholds. In a specific implementation method of the present invention, the preset first health index is set to be greater than the preset second health index. The preset first health index is 0.6, and the preset second health index is 0.3. The specific numerical values ​​can be adjusted by the implementer according to the specific implementation scenario.

[0127] When the evaluation index is greater than the preset first health index, it means that the evaluation index value is higher and the plant state is healthier, and the health evaluation result of the sample plant is recorded as healthy.

[0128] When the evaluation index is less than or equal to the preset first health index and greater than the preset second health index, it means that the evaluation index value is average, the plant may have certain health problems, and the health evaluation result of the sample plant is recorded as sub-health.

[0129] When the evaluation index is less than or equal to the preset second health index, it means that the evaluation index value is small, the plant has a major health problem, and the health evaluation result of the sample plant is recorded as unhealthy.

[0130] It should be noted that the sequence of the above embodiments of the present invention is only for description and does not represent the advantages and disadvantages of the embodiments. The processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0131] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referenced to each other, and each embodiment focuses on the differences from other embodiments.

Claims

1. A method for evaluating the health of landscape plants, characterized in that: The method comprises: Obtain the physiological parameter evaluation values, environmental evaluation values, growth rate and chlorophyll content of the sample plants at each sampling moment in the historical period; According to the correlation between the physiological parameter evaluation value and the environmental evaluation value of the sample plant in the historical period, as well as the distribution stability of the physiological parameter evaluation value, the environmental tolerance factor of the sample plant is obtained; According to the unstable changes in the growth rate of the sample plants in the historical period, as well as the degree of change of the environmental assessment value and the environmental tolerance factor, the growth abnormality disorder coefficient of the sample plants is obtained; According to the deviation of the chlorophyll content of the sample plant at the current moment and in the historical time period, the health status coefficient of the sample plant is obtained; Combining the environmental assessment value of the sample plant at the current moment, as well as the environmental tolerance factor, the abnormal growth disorder coefficient and the health status coefficient, the assessment index of the sample plant is obtained; based on the assessment index of the sample plant, the health assessment result of the sample plant is obtained; The method for obtaining the environmental tolerance factor includes: The information entropy of the physiological parameter evaluation values ​​of the sample plants at all sampling moments is used as the change sensitivity of the sample plants; Arrange all physiological parameter evaluation values ​​of the sample plants in the historical time period in chronological order to obtain a physiological parameter sequence; arrange all environmental evaluation values ​​of the sample plants in the historical time period in chronological order to obtain an environmental sequence; calculate the correlation between the physiological parameter sequence and the environmental sequence to obtain the change correlation of the sample plants; Combining the change sensitivity and change correlation of the sample plants, the environmental tolerance factor of the sample plants is obtained; The method for obtaining the growth abnormality disorder coefficient comprises: Divide the historical time period into a preset number of local time periods; In each local time period, according to the number and degree of change of the environmental assessment value of the sample plant and the environmental tolerance factor, the environmental correction weight of the sample plant in each local time period is obtained; The frequency of changes in the growth rate of the sample plant in each local time period is used as the disorder abnormality degree of the sample plant in each local time period; The disorder anomaly degree is weighted and averaged by the environmental correction weight of each local time period to obtain the growth abnormal disorder coefficient of the sample plant; The method for obtaining the environment correction weight includes: In any local time period, when the environmental assessment value at each sampling moment is different from the previous sampling moment in the time series, the sampling moment is regarded as the change moment; Count the number of change moments in the local time period as the number of environment changes in the local time period; In the local time period, the difference between the environmental evaluation value at each change moment and the environmental evaluation value at the previous sampling moment in the time series is taken as the change degree at each change moment; the environmental deviation degree of the local time period is obtained by combining the change degrees of all change moments in the local time period; Combining the number of environmental changes and the environmental deviation in the local time period, obtaining the environmental change index in the local time period; According to the environmental change index of the local time period and the environmental tolerance factor of the sample plant, the environmental correction weight of the local time period is obtained; The step of obtaining the environmental correction weight of the local time period according to the environmental change index of the local time period and the environmental tolerance factor of the sample plant comprises: The ratio of the environmental change index and the environmental tolerance factor in the local time period is negatively correlated and normalized to obtain the environmental correction weight of the local time period.

2. A method for evaluating the health of landscape plants according to claim 1, characterized in that: The method for obtaining the disorder abnormality degree includes: When the growth rate of the sampling moment in each local time period is different from the growth rate of the previous sampling moment in the time series, the corresponding sampling moment is regarded as an abnormal moment; The total number of abnormal moments in each local time period is counted as the disorder abnormality degree of each local time period.

3. A method for evaluating the health of landscape plants according to claim 1, characterized in that: The method for obtaining the health status coefficient includes: Obtain the periodicity of chlorophyll content changes over a historical period; use the difference between the periodicity of the changes and the preset periodicity as a period deviation indicator for the sample plants; According to the difference between the chlorophyll content at each sampling moment in the historical time period and the current moment, the state deviation index of the sample plant is obtained; The health status coefficient of the sample plant is obtained by combining the period deviation index and the state deviation index of the sample plant.

4. A method for evaluating the health of landscape plants according to claim 3, characterized in that: The method for obtaining the state deviation indicator includes: For any sampling moment in the historical time period, the difference in chlorophyll content between the sampling moment and the current moment is used to obtain the deviation value of the sampling moment; the time interval between the sampling moment and the current moment is negatively correlated to obtain the interval weight of the sampling moment; The deviation value is weighted and averaged by the spacing weight at each sampling moment to obtain the state deviation index of the sample plant.

5. A method for evaluating the health of landscape plants according to claim 1, characterized in that: The method for obtaining the evaluation index includes: The product of the value of negative correlation mapping of the growth disorder coefficient of the sample plant and the health status coefficient is used as the status indicator of the sample plant; Normalize the product of the environmental tolerance factor of the sample plant and the environmental assessment value at the current moment to obtain the environmental adjustment index of the sample plant; The product of the state index of the sample plant and the environmental adjustment index is normalized to obtain the evaluation index of the sample plant.

6. A method for evaluating the health of landscape plants according to claim 1, characterized in that: The health assessment result of the sample plant obtained based on the assessment index of the sample plant includes: When the evaluation index is greater than the preset first health index, the health evaluation result of the sample plant is recorded as healthy; When the evaluation index is less than or equal to the preset first health index and greater than the preset second health index, the health evaluation result of the sample plant is recorded as sub-healthy; When the evaluation index is less than or equal to the preset second health index, the health evaluation result of the sample plant is recorded as unhealthy; The preset first health indicator is greater than the preset second health indicator.

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