Distributed data monitoring platform for natural ecological landscape

Abstract

The invention belongs to the technical field of landscape monitoring management, and particularly relates to a natural ecological landscape distributed data monitoring platform which comprises a natural ecological landscape monitoring unit, a distributed storage unit, a landscape form analysis unit, a growth environment evaluation unit and a landscape management terminal. According to the invention, the natural ecological landscape is monitored in real time through the natural ecological landscape monitoring unit, the landscape form analysis unit judges whether a landscape form abnormal signal is generated through landscape form analysis, causes are investigated and analyzed when the landscape form abnormal signal is generated, and reasonable improvement measures are taken for the natural ecological landscape. When the landscape form abnormity signal is generated, the relevance between the natural ecological landscape abnormity and the growth environment is judged through growth environment evaluation analysis, and when the growth environment abnormity signal is generated, monitoring management on the environment where the natural ecological landscape is located is enhanced, so that the natural ecological landscape is prevented from being damaged; and the supervision difficulty of the natural ecological landscape is obviously reduced.

Description

Technical Field

[0001] The invention relates to the technical field of landscape monitoring and management, in particular to a distributed data monitoring platform for natural ecological landscapes. Background Art

[0002] As environmental problems become increasingly severe, the monitoring and protection of natural ecological landscapes has become particularly important. A Chinese invention patent with publication number CN103678707A discloses a roadside tree ecological landscape monitoring system and method. The invention combines field surveys to collect information, database processing health monitoring, and interactive methods such as mouse and keyboard operations. It can provide real-time information correction and browsing query functions, and promptly and quickly provide more intuitive and vivid digital images, thereby providing a more effective and reliable reference basis for the planning, design, maintenance, monitoring, and management of roadside trees, thereby improving work efficiency. However, the above invention technical solution is limited to the management of street trees in actual application, and cannot effectively monitor a certain area involving natural ecological landscape and judge its landscape morphological changes. When judging that the landscape morphological changes are abnormal, it is difficult to reasonably analyze its relevance to the growth environment. The management personnel cannot make reasonable response measures in time, which is not conducive to avoiding damage to the natural ecological landscape, and the supervision of the natural ecological landscape is difficult. In view of the above technical defects, a solution is now proposed. Summary of the invention

[0003] The purpose of the present invention is to provide a distributed data monitoring platform for natural ecological landscapes, which solves the problem that the prior art cannot effectively monitor a certain area involving natural ecological landscapes and judge their landscape morphological changes, and it is difficult to reasonably analyze their correlation with the growth environment when judging abnormal landscape morphological changes, which is not conducive to avoiding damage to natural ecological landscapes and makes supervision difficult.

[0004] To achieve the above object, the present invention provides the following technical solutions: A distributed data monitoring platform for natural ecological landscapes, comprising a natural ecological landscape monitoring unit, a distributed storage unit, a landscape morphology analysis unit, a growth environment assessment unit and a landscape management terminal; the natural ecological landscape monitoring unit forms a data collection network through various sensors deployed in the natural ecological landscape, is responsible for real-time collection of various indicator data of the ecological environment, and sends the collected data to the distributed storage unit for storage; The landscape morphology analysis unit retrieves the monitoring image of the natural ecological landscape from the distributed storage unit, performs landscape morphology analysis based on the monitoring image, and judges whether to generate a landscape morphology abnormality signal accordingly, and sends the landscape morphology abnormality signal to the landscape management terminal and the growth environment assessment unit when the landscape morphology abnormality signal is generated; When the growth environment assessment unit receives a landscape morphology abnormality signal, it determines the correlation between the natural ecological landscape abnormality and the growth environment through growth environment assessment analysis, and generates a growth environment qualified signal or a growth environment abnormality signal based on this. When the growth environment abnormality signal is generated, it is sent to the landscape management terminal; when the landscape management terminal receives the landscape morphology abnormality signal or the growth environment abnormality signal, it issues an early warning.

[0005] Furthermore, the specific analysis process of landscape morphology analysis is as follows: A number of monitoring areas are demarcated in the natural ecological landscape, and the corresponding monitoring areas are marked as layout objects i, where i is a natural number greater than 1; the distribution area of ​​plants in a withered state in the layout object i is collected based on monitoring images, and the ratio of the distribution area to the total distribution area of ​​plants is marked as a withered distribution occupancy value, and the withered distribution occupancy value is numerically compared with a preset withered distribution occupancy threshold value. If the withered distribution occupancy value exceeds the preset withered distribution occupancy threshold value, the layout object i is marked as a shape abnormal object; The number ratio of the abnormal objects in the natural ecological landscape is obtained and marked as the abnormal detection value, and the abnormal detection value is compared with the preset abnormal detection threshold. If the abnormal detection value exceeds the preset abnormal detection threshold, a landscape morphological abnormality signal is generated; if the abnormal detection value does not exceed the preset abnormal detection threshold, the withering distribution occupancy values ​​of all monitoring areas are averaged to obtain the withering assessment value, and the withering distribution occupancy value with the largest value is marked as the withering amplitude; The landscape morphology change coefficient is calculated by weighted summation of the shape anomaly detection value, withering assessment value and withering table amplitude, and the landscape morphology change coefficient is numerically compared with the preset landscape morphology change coefficient threshold. If the landscape morphology change coefficient exceeds the preset landscape morphology change coefficient threshold, a landscape morphology anomaly signal is generated.

[0006] Furthermore, the specific analysis process of the growth environment assessment analysis is as follows: A detection period is set, and the sunshine duration, average sunshine intensity, average atmospheric temperature and average atmospheric humidity of the natural ecological landscape on the corresponding date within the detection period are collected. The deviation value of sunshine duration from the corresponding preset sunshine duration standard value is marked as the sunshine duration measurement value. Similarly, the sunshine intensity measurement value, atmospheric temperature measurement value and atmospheric humidity measurement value are obtained. The upper-level impact value is calculated by weighted summation of the sunshine duration measurement value, sunshine intensity measurement value, atmospheric temperature measurement value and atmospheric humidity measurement value. The upper layer impact value is numerically compared with the preset upper layer impact threshold. If the upper layer impact value exceeds the preset upper layer impact threshold, the corresponding date is marked as a landscape harmful day; if the upper layer impact value does not exceed the preset upper layer impact threshold, soil damage detection and analysis are performed to determine whether the corresponding date is a landscape harmful day; The percentage of harmful days in the landscape during the detection period is obtained and marked as the harmful day detection value, and the harmful day detection value is numerically compared with the preset harmful day detection threshold. If the harmful day detection value exceeds the preset harmful day detection threshold, an abnormal growth environment signal is generated.

[0007] Furthermore, the specific analysis process of soil damage detection and analysis is as follows: Toxic substances and fertility substances that need to be monitored in the soil of the natural ecological landscape are obtained, and the concentrations of various toxic substances and fertility substances are collected. The concentrations of various toxic substances are multiplied by the corresponding preset hazard weight values, and the multiplication results of each group are summed up to calculate the soil toxicity coefficient. Similarly, the soil fertility coefficient is calculated; the soil toxicity coefficient and the soil fertility coefficient are numerically compared with the preset soil toxicity coefficient threshold and the preset soil fertility coefficient threshold, respectively. If the soil toxicity coefficient exceeds the preset soil toxicity coefficient threshold or the soil fertility coefficient does not exceed the preset soil fertility coefficient threshold, the corresponding date is marked as a landscape harmful day; If the soil toxicity coefficient does not exceed the preset soil toxicity coefficient threshold and the soil fertility coefficient exceeds the preset soil fertility coefficient threshold, the deviation value of the soil temperature compared to the set standard temperature is marked as the soil temperature characteristic value, and the soil moisture characteristic value is obtained similarly; the lower layer impact value is obtained by numerically calculating the soil toxicity coefficient, soil fertility coefficient, soil temperature characteristic value and soil moisture characteristic value, and the lower layer impact value is numerically compared with the preset lower layer impact threshold. If the lower layer impact value exceeds the preset lower layer impact threshold, the corresponding date is marked as a landscape harmful day.

[0008] Furthermore, the landscape management terminal is connected to the fire risk prediction alarm unit and the behavior risk monitoring unit in communication. The fire risk prediction alarm unit analyzes the fire risk in the natural ecological landscape, determines whether to generate a fire risk alarm signal through the analysis, and sends the fire risk alarm signal to the landscape management terminal when it is generated. The landscape management terminal issues an early warning when it receives the fire risk alarm signal. The behavior risk monitoring unit monitors and analyzes people entering the natural ecological landscape based on the surveillance images in the natural ecological landscape, and determines whether to generate a behavior alarm signal through analysis. When the behavior alarm signal is generated, it is sent to the landscape management terminal, and the landscape management terminal issues an early warning when receiving the behavior alarm signal.

[0009] Furthermore, the specific analysis process of the fire risk prediction alarm unit is as follows: The temperature of the external environment where the natural ecological landscape is located is collected and marked as the external temperature detection value T, and the humidity of the external environment where the natural ecological landscape is located is collected, and the value a is calculated by ratio with the humidity of the external environment where the natural ecological landscape is located to obtain the external humidity detection value H, and the wind speed of the external environment where the natural landscape is located is collected and marked as the external wind detection value W; The fire alarm coefficient FWI is calculated by substituting the above data into the formula FWI=0.5T+0.3H+0.2W. The fire alarm coefficients are compared in real time. If the fire alarm coefficient FWI is greater than 4.0 for three consecutive hours, a fire alarm signal is generated.

[0010] Furthermore, the specific analysis process of the behavior risk monitoring unit includes: Acquire all types of bad behaviors that need to be monitored in natural ecological landscapes and mark them as optimal monitoring behaviors, mark the corresponding optimal monitoring behaviors as k, and k is a natural number greater than 1; based on monitoring images, capture all optimal monitoring behaviors occurring in natural ecological landscapes in real time, and start timing when optimal monitoring behaviors are identified in natural ecological landscapes. When the occurrence duration of the corresponding optimal monitoring behaviors exceeds the corresponding preset occurrence duration threshold, generate a behavior alarm signal; If there is no excellent monitoring behavior whose occurrence duration exceeds the corresponding preset occurrence duration threshold within a unit time, the number of occurrences of the excellent monitoring behavior k within a unit time is marked as the behavior frequency, and the duration of each occurrence of the excellent monitoring behavior k within a unit time is summed up to obtain the behavior duration, and the behavior frequency and behavior duration are weightedly summed up to obtain the behavior control anomaly value, and the behavior control anomaly value is ratio-calculated with the corresponding preset behavior control anomaly threshold, thereby obtaining the behavior control evaluation value; If the behavior management evaluation value is ≥ 1, the optimal monitoring behavior k is marked as a strong management behavior; if there is a strong management behavior within a unit time, a behavior alarm signal is generated.

[0011] Furthermore, if there is no forced control behavior within a unit time, a set of preset behavior hidden danger weight values ​​corresponding to each type of optimal monitoring behavior is set in advance, and the behavior control evaluation value of the optimal monitoring behavior k is multiplied by the corresponding preset behavior hidden danger weight value to obtain the behavior risk measurement value; the behavior risk measurement values ​​of all types of optimal monitoring behaviors occurring within a unit time are summed up and calculated to obtain the total behavior risk value, and the total behavior risk value is numerically compared with the preset behavior total risk threshold value; if the total behavior risk value exceeds the preset behavior total risk threshold value, a behavior alarm signal is generated.

[0012] Furthermore, if the total behavior risk value does not exceed the preset total behavior risk threshold, the real-time number of people in the natural ecological landscape is obtained and marked as the actual value of the population density, and the actual value of the population density is numerically compared with the preset actual value of the population density threshold. If the actual value of the population density exceeds the preset actual value of the population density threshold, it is determined that the natural ecological landscape is in a viewing overload state; The total duration of the natural ecological landscape in the viewing overload state per unit time is obtained and marked as the overload detection value, and the average of all the measured values ​​of personnel density per unit time is calculated to obtain the density assessment value, and the overload detection value and the density assessment value are numerically compared with the preset overload detection threshold and the preset density assessment threshold respectively. If the overload detection value or the density assessment value exceeds the corresponding preset threshold, a behavioral alarm signal is generated.

[0013] Compared with the prior art, the present invention has the following beneficial effects: 1. In the present invention, the natural ecological landscape is comprehensively monitored in real time by the natural ecological landscape monitoring unit, the landscape morphology analysis unit determines whether a landscape morphology abnormality signal is generated by the landscape morphology analysis, and when the landscape morphology abnormality signal is generated, the cause investigation and analysis are conducted and reasonable improvement measures are taken for the natural ecological landscape, and when the landscape morphology abnormality signal is generated, the correlation between the natural ecological landscape abnormality and the growth environment is determined by the growth environment assessment analysis, and when the growth environment abnormality signal is generated, the monitoring and management of the environment in which the natural ecological landscape is located is strengthened, which is conducive to avoiding damage to the natural ecological landscape and significantly reducing the difficulty of supervising the natural ecological landscape; 2. In the present invention, the fire risk in the natural ecological landscape is analyzed by the fire risk prediction alarm unit to determine whether to generate a fire risk alarm signal. When the fire risk alarm signal is generated, fire monitoring and prevention are strengthened to avoid fires in the natural ecological landscape area. In addition, the personnel entering the natural ecological landscape are monitored and analyzed by the behavior risk monitoring unit to determine whether to generate a behavior alarm signal. When the behavior alarm signal is generated, the behavior management of the personnel in the natural ecological landscape is strengthened and the publicity of behavior norms is increased, so as to further ensure the safety of the natural ecological landscape and reduce the difficulty of its supervision. The intelligent level is high. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] In order to facilitate understanding by those skilled in the art, the present invention is further described below in conjunction with the accompanying drawings; Figure 1 This is a system block diagram of Embodiment 1 of the present invention; Figure 2 This is a system block diagram of Embodiment 2 and Embodiment 3 of the present invention. DETAILED DESCRIPTION

[0015] 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.

[0016] Embodiment 1: Figure 1 As shown, a distributed data monitoring platform for natural ecological landscapes proposed by the present invention includes a natural ecological landscape monitoring unit, a distributed storage unit, a landscape morphology analysis unit, a growth environment assessment unit and a landscape management terminal; Among them, the natural ecological landscape monitoring unit forms a data collection network through various sensors deployed in the natural ecological landscape (such as temperature and humidity sensors, soil moisture sensors, air quality sensors, water quality sensors, image sensors, etc.), which is responsible for real-time collection of various indicator data of the ecological environment, and sends the collected data to the distributed storage unit for storage; It should be noted that the distributed storage unit stores data in multiple nodes by adopting distributed storage technology, achieving high availability, fault tolerance and scalability of data, supporting the storage and management of massive data, and providing a basis for subsequent data analysis.

[0017] The landscape morphology analysis unit retrieves the monitoring image of the natural ecological landscape from the distributed storage unit, performs landscape morphology analysis based on the monitoring image, and judges whether to generate a landscape morphology abnormality signal accordingly, and sends the landscape morphology abnormality signal to the landscape management terminal and the growth environment assessment unit when the landscape morphology abnormality signal is generated; When the landscape management terminal receives an abnormal signal of landscape morphology, it issues an early warning to remind management personnel to promptly conduct cause investigation and analysis, make reasonable improvement measures for the natural ecological landscape, and strengthen the subsequent monitoring and management of the natural ecological landscape, thus significantly reducing the difficulty of supervising the natural ecological landscape. The specific analysis process of landscape morphology analysis is as follows: Several monitoring areas are demarcated in the natural ecological landscape, and the corresponding monitoring areas are marked as layout objects i, where i is a natural number greater than 1; the distribution area of ​​plants in a withered state in the layout object i is collected based on monitoring images, and its ratio to the total distribution area of ​​plants is marked as the withered distribution occupancy value; The withering distribution occupancy value is numerically compared with a preset withering distribution occupancy threshold value. If the withering distribution occupancy value exceeds the preset withering distribution occupancy threshold value, it indicates that the growth condition of the plant in the layout object i is poor, and the layout object i is marked as a shape-abnormal object; The number ratio of abnormal objects in the natural ecological landscape is obtained and marked as the abnormal shape detection value, and the abnormal shape detection value is numerically compared with the preset abnormal shape detection threshold. If the abnormal shape detection value exceeds the preset abnormal shape detection threshold, it indicates that the plant growth condition in the natural ecological landscape is poor, and a landscape morphological abnormality signal is generated; if the abnormal shape detection value does not exceed the preset abnormal shape detection threshold, the withering distribution occupancy values ​​of all monitoring areas are averaged to obtain the withering assessment value, and the withering distribution occupancy value with the largest value is marked as the withering amplitude; The landscape morphological change coefficient is calculated by weighted summing the shape difference detection value, the withering assessment value and the withering table amplitude, that is, the shape difference detection value, the withering assessment value and the withering table amplitude are respectively assigned corresponding preset weight coefficients, the shape difference detection value, the withering assessment value and the withering table amplitude are respectively multiplied by the corresponding preset weight coefficients, and the sum of the three sets of multiplication results is marked as the landscape morphological change coefficient, and the larger the value of the landscape morphological change coefficient is, the worse the overall growth condition of plants in the natural ecological landscape is; The landscape morphology change coefficient is numerically compared with the preset landscape morphology change coefficient threshold. If the landscape morphology change coefficient exceeds the preset landscape morphology change coefficient threshold, it indicates that the plant growth condition in the natural ecological landscape is generally poor, and a landscape morphology abnormality signal is generated.

[0018] When the growth environment assessment unit receives the landscape morphology abnormality signal, it determines the correlation between the natural ecological landscape abnormality and the growth environment through the growth environment assessment analysis, and generates a growth environment qualified signal or a growth environment abnormality signal accordingly, and sends the growth environment abnormality signal to the landscape management terminal when it is generated; When the landscape management terminal receives an abnormal growth environment signal, it issues an early warning to remind managers that the probability of poor natural ecological landscape morphology due to environmental factors is high, and timely strengthens the monitoring and management of the environment in which the natural ecological landscape is located in the future, which is conducive to ensuring the good growth of plants in the natural ecological landscape; the specific analysis process of growth environment assessment and analysis is as follows: Set a detection period, collect the sunshine duration, average sunshine intensity, average atmospheric temperature and average atmospheric humidity of the natural ecological landscape on the corresponding date during the detection period, mark the deviation between the sunshine duration and the corresponding preset sunshine duration standard value as the sunshine duration measurement value, and similarly obtain the sunshine intensity measurement value, atmospheric temperature measurement value and atmospheric humidity measurement value; The upper layer impact value is calculated by weighted summing the light duration measurement value, light intensity measurement value, atmospheric temperature measurement value and atmospheric humidity measurement value; that is, the light duration measurement value, light intensity measurement value, atmospheric temperature measurement value and atmospheric humidity measurement value are respectively assigned corresponding preset weight coefficients, and the light duration measurement value, light intensity measurement value, atmospheric temperature measurement value and atmospheric humidity measurement value are respectively multiplied by the corresponding preset weight coefficients, and the sum of the four groups of product results is marked as the upper layer impact value; and the larger the value of the upper layer impact value, the worse the external atmospheric environment condition of the natural ecological landscape is in general; The upper layer impact value is numerically compared with the preset upper layer impact threshold. If the upper layer impact value exceeds the preset upper layer impact threshold, it indicates that the external atmospheric environment conditions of the natural ecological landscape on the corresponding date are generally poor, and the corresponding date is marked as a landscape harmful day; If the upper impact value does not exceed the preset upper impact threshold, the toxic substances and fertility substances (such as substances related to nitrogen, phosphorus and potassium elements) that need to be monitored in the soil of the natural ecological landscape are obtained, and the concentrations of various toxic substances and fertility substances are collected. Each toxic substance is set in advance to correspond to a set of preset hazard weight values ​​greater than zero, and the greater the harm caused by the corresponding toxic substance to plant growth, the greater the value of the preset hazard weight value that matches it; the concentrations of various toxic substances are multiplied by the corresponding preset hazard weight values, and the sum of the multiplication results of each group is calculated to obtain the soil toxicity coefficient; Similarly, the soil fertility coefficient is obtained by calculation; that is, each fertility substance is set in advance to correspond to a set of preset beneficial weight values ​​greater than zero, and the more important the corresponding fertility substance is to plant growth, the greater the value of the preset beneficial weight value matched with it; the concentration of each fertility substance is multiplied by the corresponding preset beneficial weight value, and the sum of the product results of each group is calculated to obtain the soil fertility coefficient; The soil toxicity coefficient and the soil fertility coefficient are numerically compared with the preset soil toxicity coefficient threshold and the preset soil fertility coefficient threshold, respectively. If the soil toxicity coefficient exceeds the preset soil toxicity coefficient threshold or the soil fertility coefficient does not exceed the preset soil fertility coefficient threshold, it indicates that the soil condition on the corresponding date is poor and is not conducive to the growth of plants in the natural ecological landscape, and the corresponding date is marked as a landscape harmful day; If the soil toxicity coefficient does not exceed the preset soil toxicity coefficient threshold and the soil fertility coefficient exceeds the preset soil fertility coefficient threshold, the deviation value of the soil temperature compared to the set standard temperature is marked as the soil temperature characteristic value, and the soil moisture characteristic value is obtained in the same way; The soil toxicity coefficient Z, soil fertility coefficient G, soil temperature characteristic value N and soil moisture characteristic value P are numerically calculated by Yew=(c1×Z+c3×N+c4×P) / (c2×G+1)to obtain the lower layer impact value Yew; wherein c1, c2, c3 and c4 are preset proportional coefficients with values ​​greater than zero, and the larger the value of the lower layer impact value Yew is, the worse the soil condition on the corresponding date is in general, and the less conducive it is to the growth of plants in the natural ecological landscape; The above formula is a dimensionless numerical calculation. The formula is a formula obtained by collecting a large amount of data and performing software simulation to obtain the most recent real situation. The preset parameters in the formula are set by technicians in this field according to actual conditions. The lower layer impact value Yew is numerically compared with the preset lower layer impact threshold. If the lower layer impact value Yew exceeds the preset lower layer impact threshold, it indicates that the soil condition on the corresponding date is generally poor and is not conducive to the growth of plants in the natural ecological landscape, and the corresponding date is marked as a landscape harmful day; The percentage of harmful days in the landscape during the detection period is obtained and marked as the harmful day detection value. The harmful day detection value is compared with the preset harmful day detection threshold. If the harmful day detection value exceeds the preset harmful day detection threshold, it indicates that the environmental conditions of the natural ecological landscape in the detection period are poor, and the probability of poor natural ecological landscape morphology due to environmental factors is high. It is necessary to strengthen the monitoring and management of the environment in which the natural ecological landscape is located in the future, which is conducive to ensuring the good growth of plants in the natural ecological landscape, and an abnormal growth environment signal is generated.

[0019] Embodiment 2: Figure 2 As shown, the difference between this embodiment and the first embodiment is that the landscape management terminal is connected to the fire risk prediction alarm unit in communication. The fire risk prediction alarm unit analyzes the fire risk in the natural ecological landscape, determines whether to generate a fire risk alarm signal through analysis, and sends the fire risk alarm signal to the landscape management terminal when it is generated. When the landscape management terminal receives the fire risk alarm signal, it issues an early warning to remind the management personnel to strengthen fire monitoring and prevention, avoid fires in the natural ecological landscape area, and help ensure the safety of the natural ecological landscape. The specific analysis process of the fire risk prediction alarm unit is as follows: The temperature of the external environment where the natural ecological landscape is located is collected and marked as the external temperature detection value T, and the humidity of the external environment where the natural ecological landscape is located is collected, and the value a (where a represents the judgment value of the humidity of the external environment, and the value of a is greater than 1) and the humidity of the external environment where the natural ecological landscape is located are calculated by ratio to obtain the external humidity detection value H, and the wind speed of the external environment where the natural landscape is located is collected and marked as the external wind detection value W; The fire alarm coefficient FWI is calculated by substituting the above data into the formula FWI=0.5T+0.3H+0.2W. The fire alarm coefficients are compared in real time. If the fire alarm coefficient FWI is greater than 4.0 for three consecutive hours, a fire alarm signal is generated.

[0020] Embodiment 3: Figure 2 As shown, the difference between this embodiment and the first and second embodiments is that the landscape management terminal is connected to the behavior risk monitoring unit in communication. The behavior risk monitoring unit monitors and analyzes the personnel entering the natural ecological landscape based on the monitoring images in the natural ecological landscape, and determines whether to generate a behavior alarm signal through analysis. When the behavior alarm signal is generated, it is sent to the landscape management terminal. When the landscape management terminal receives the behavior alarm signal, it issues an early warning to remind the management personnel to strengthen the management of the personnel behavior in the natural ecological landscape and increase the publicity of the behavior norms, further ensure the safety of the natural ecological landscape and reduce the difficulty of its supervision. The intelligent level is high. The specific analysis process of the behavior risk monitoring unit is as follows: All types of bad behaviors that need to be monitored in natural ecological landscapes (such as trampling and kicking plants in natural ecological landscapes, etc.) are obtained and marked as excellent monitoring behaviors, and the corresponding excellent monitoring behaviors are marked as k, where k is a natural number greater than 1; all excellent monitoring behaviors occurring in natural ecological landscapes are captured in real time based on monitoring images, and timing is performed when excellent monitoring behaviors are identified in natural ecological landscapes. When the occurrence duration of the corresponding excellent monitoring behaviors exceeds the corresponding preset occurrence duration threshold, a behavior alarm signal is generated; If there is no preferred monitoring behavior within a unit time whose occurrence duration exceeds the corresponding preset occurrence duration threshold, the number of occurrences of the preferred monitoring behavior k within a unit time is marked as the behavior frequency, and the duration of each occurrence of the preferred monitoring behavior k within a unit time is summed up to obtain the behavior duration, and the behavior frequency and the behavior duration are weighted and summed up to obtain the behavior control outlier value, that is, the behavior frequency and the behavior duration are respectively assigned corresponding preset weight coefficients, the behavior frequency and the behavior duration are respectively multiplied by the corresponding preset weight coefficients, and the sum of the two sets of product results is marked as the behavior control outlier value; and the larger the value of the behavior control outlier value, the more it is necessary to strengthen the control of the corresponding preferred monitoring behavior; The behavior control anomaly value is calculated by ratio with the corresponding preset behavior control anomaly threshold, and the behavior control evaluation value is obtained accordingly; if the behavior control evaluation value ≥ 1, it indicates that the control of the corresponding optimal monitoring behavior is not good, and the optimal monitoring behavior k is marked as a strong control behavior; if there is a strong control behavior in a unit time, it indicates that it is necessary to strengthen the supervision of personnel behavior in the natural ecological landscape area, and a behavior alarm signal is generated; If there is no strong control behavior within a unit time, then each type of optimal monitoring behavior is set in advance to correspond to a set of preset behavior hazard weight values ​​greater than zero (the higher the potential risk of the optimal monitoring behavior k to the natural ecological landscape, the greater the value of the preset behavior hazard weight value that matches it), and the behavior management evaluation value of the optimal monitoring behavior k is multiplied by the corresponding preset behavior hazard weight value to obtain the behavior risk measurement value; The behavioral risk measurement values ​​of all types of monitored behaviors occurring in unit time are summed up to obtain the total behavioral risk value, and the total behavioral risk value is numerically compared with the preset total behavioral risk threshold. If the total behavioral risk value exceeds the preset total behavioral risk threshold, it indicates that it is necessary to strengthen the supervision of human behavior in the natural ecological landscape area, and a behavioral alarm signal is generated.

[0021] Furthermore, if the total behavior risk value does not exceed the preset total behavior risk threshold, the real-time number of people in the natural ecological landscape is obtained and marked as the actual value of the population density, and the actual value of the population density is compared with the preset actual value of the population density threshold. If the actual value of the population density exceeds the preset actual value of the population density threshold, it indicates that the natural ecological landscape area is crowded with people, which may cause damage to the natural ecological landscape, and the natural ecological landscape is judged to be in a viewing overload state; The total duration of the natural ecological landscape in the viewing overload state per unit time is obtained and marked as the overload detection value, and the average of all the measured values ​​of personnel density per unit time is calculated to obtain the density assessment value, and the overload detection value and the density assessment value are numerically compared with the preset overload detection threshold and the preset density assessment threshold respectively. If the overload detection value or the density assessment value exceeds the corresponding preset threshold, indicating that the personnel management of the natural ecological landscape area needs to be strengthened, a behavioral alarm signal is generated.

[0022] The working principle of the present invention is as follows: when in use, the natural ecological landscape monitoring unit collects various indicator data of the ecological environment in real time and sends them to the distributed storage unit for storage, providing a basis for subsequent data analysis; the landscape morphology analysis unit performs landscape morphology analysis based on the monitoring image, and judges whether to generate a landscape morphology abnormality signal accordingly; when the landscape morphology abnormality signal is generated, a cause investigation and analysis is performed, and reasonable improvement measures are made for the natural ecological landscape; when the landscape morphology abnormality signal is generated, a growth environment assessment analysis is performed through the growth environment assessment unit to judge the correlation between the natural ecological landscape abnormality and the growth environment; when the growth environment abnormality signal is generated, the monitoring and management of the environment in which the natural ecological landscape is located is strengthened, which is conducive to ensuring the good growth of plants in the natural ecological landscape, significantly reducing the difficulty of supervising the natural ecological landscape, and having a high level of intelligence.

[0023] The preferred embodiments of the present invention disclosed above are only used to help explain the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to only specific implementation methods. Obviously, many modifications and changes can be made according to the content of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that those skilled in the art can understand and use the present invention well. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. A distributed data monitoring platform for natural ecological landscapes, characterized in that: It includes a natural ecological landscape monitoring unit, a distributed storage unit, a landscape morphology analysis unit, a growth environment assessment unit and a landscape management terminal; the natural ecological landscape monitoring unit collects various indicator data of the ecological environment in real time, and sends the collected data to the distributed storage unit for storage; the landscape morphology analysis unit performs landscape morphology analysis based on the monitoring image from the distributed storage unit, and sends the landscape morphology abnormal signal to the landscape management terminal and the growth environment assessment unit when it generates it; When the growth environment assessment unit receives a landscape morphology abnormality signal, it determines the correlation between the natural ecological landscape abnormality and the growth environment through growth environment assessment analysis, and generates a growth environment qualified signal or a growth environment abnormality signal based on this. When the growth environment abnormality signal is generated, it is sent to the landscape management terminal; when the landscape management terminal receives the landscape morphology abnormality signal or the growth environment abnormality signal, it issues an early warning.

2. A distributed data monitoring platform for natural ecological landscapes according to claim 1, characterized in that: The specific analysis process of landscape morphology analysis is as follows: if the shape difference detection value exceeds the preset shape difference detection threshold, a landscape morphology anomaly signal is generated; otherwise, the shape difference detection value, withering assessment value and withering table amplitude are weighted and summed to obtain the landscape morphology change coefficient. If the landscape morphology change coefficient exceeds the preset landscape morphology change coefficient threshold, a landscape morphology anomaly signal is generated.

3. A distributed data monitoring platform for natural ecological landscapes according to claim 2, characterized in that: The specific analysis process of the growth environment assessment and analysis is as follows: if the upper-layer impact value exceeds the preset upper-layer impact threshold, the corresponding date is marked as a landscape-harmful day; if the upper-layer impact value does not exceed the preset upper-layer impact threshold, soil damage detection and analysis is performed to determine whether the corresponding date is a landscape-harmful day; the number of landscape-harmful days in the detection period is obtained and marked as a harmful day inspection value; if the harmful day inspection value exceeds the preset harmful day inspection threshold, a growth environment abnormality signal is generated.

4. A distributed data monitoring platform for natural ecological landscapes according to claim 3, characterized in that: The specific analysis process of soil damage detection and analysis is as follows: If the soil toxicity coefficient exceeds the preset soil toxicity coefficient threshold or the soil fertility coefficient does not exceed the preset soil fertility coefficient threshold, the corresponding date will be marked as a landscape harmful day; otherwise, the soil toxicity coefficient, soil fertility coefficient, soil temperature characteristic value and soil moisture characteristic value will be numerically calculated to obtain the lower layer impact value. If the lower layer impact value exceeds the preset lower layer impact threshold, the corresponding date will be marked as a landscape harmful day.

5. A distributed data monitoring platform for natural ecological landscapes according to claim 1, characterized in that: The landscape management terminal is connected to the fire risk prediction alarm unit and the behavior risk monitoring unit in communication. The fire risk prediction alarm unit analyzes the fire risk in the natural ecological landscape, determines whether to generate a fire risk alarm signal through the analysis, and sends the fire risk alarm signal to the landscape management terminal when it is generated; The behavior risk monitoring unit monitors and analyzes the personnel entering the natural ecological landscape based on the monitoring images in the natural ecological landscape, and determines whether to generate a behavior alarm signal through analysis. When a behavior alarm signal is generated, it is sent to the landscape management terminal.

6. A distributed data monitoring platform for natural ecological landscapes according to claim 5, characterized in that: The specific analysis process of the fire risk prediction alarm unit is as follows: The fire risk alarm coefficient FWI is calculated by using the formula FWI=0.5T+0.3H+0.2W and substituting the outside temperature detection value T, the outside humidity detection value H and the outside wind detection value W. The fire risk alarm coefficient is compared in real time. If the fire risk alarm coefficient FWI is greater than 4.0 for three consecutive hours, a fire risk alarm signal is generated.

7. A distributed data monitoring platform for natural ecological landscapes according to claim 5, characterized in that: The specific analysis process of the behavioral risk monitoring unit includes: All types of bad behaviors that need to be monitored in the natural ecological landscape are obtained and marked as optimal monitoring behaviors, and the corresponding optimal monitoring behaviors are marked as k, where k is a natural number greater than 1; when the occurrence duration of the corresponding optimal monitoring behavior exceeds the corresponding preset occurrence duration threshold, a behavior alarm signal is generated; If there is no preferred monitoring behavior whose occurrence duration exceeds the corresponding preset occurrence duration threshold within a unit time, the number of occurrences of the preferred monitoring behavior k within a unit time is marked as the behavior frequency, and the occurrence duration of each preferred monitoring behavior k within a unit time is summed up to obtain the behavior duration, the behavior frequency and the behavior duration are weightedly summed up to obtain the behavior control anomaly value, the behavior control anomaly value is ratio-calculated with the corresponding preset behavior control anomaly threshold, and the behavior control evaluation value is obtained accordingly; if the behavior control evaluation value is ≥1, the preferred monitoring behavior k is marked as a strong control behavior; if there is a strong control behavior within a unit time, a behavior alarm signal is generated.

8. A distributed data monitoring platform for natural ecological landscapes according to claim 7, characterized in that: If there is no forced control behavior within a unit time, the behavior risk measurement values ​​of all types of monitored behaviors occurring within the unit time are summed up to obtain the total behavior risk value. If the total behavior risk value exceeds the preset total behavior risk threshold, a behavior alarm signal is generated.

9. A distributed data monitoring platform for natural ecological landscapes according to claim 8, characterized in that: If the total behavior risk value does not exceed the preset total behavior risk threshold, the real-time number of people in the natural ecological landscape is obtained and marked as the actual measured value of the population density, and the actual measured value of the population density is numerically compared with the preset actual measured value of the population density threshold. If the actual measured value of the population density exceeds the preset actual measured value of the population density threshold, it is judged that the natural ecological landscape is in a viewing overload state; the total duration of the natural ecological landscape in the viewing overload state per unit time is obtained and marked as the overload detection value, and the average of all the actual measured values ​​of the population density per unit time is calculated to obtain the density assessment value; the overload detection value and the density assessment value are numerically compared with the preset overload detection threshold and the preset density assessment threshold respectively. If the overload detection value or the density assessment value exceeds the corresponding preset threshold, a behavior alarm signal is generated.

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