Forest rehabilitation activity suitability evaluation system

Abstract

The invention discloses a forest health care activity suitability evaluation system, and belongs to the technical field of environment monitoring and health service. Comprising a health-care element analysis unit used for generating a health-care element peak level, a health-care element judgment module used for judging whether health-care elements are superior to historical data, and an air data analysis unit used for generating air data evaluation indexes. The health-care activity suitability evaluation basic index generation module is used for generating health-care activity suitability evaluation basic indexes, and the air state judgment module is used for judging whether forest air meets requirements of health-care activities or not. The suitability comprehensive evaluation unit is used for generating a suitability comprehensive evaluation index; the suitability judgment module is used for generating a suitability evaluation signal of the forest health care activity; according to the method, the objectivity and reliability of the evaluation result are improved through multi-dimensional comprehensive consideration of the forest health and care environment, accurate guidance is provided for planning and management of forest health and care activities, and the healthy development of the forest health and care industry is promoted.

Description

Technical Field

[0001] The present invention belongs to the technical field of environmental monitoring and health services, and in particular to a forest health care activity suitability evaluation system. Background Art

[0002] With people's pursuit of a healthy lifestyle and increasing attention to the natural environment, forest health activities are gradually gaining popularity.

[0003] There are various existing evaluation methods for forest health care activities, including evaluation based on participants' subjective feelings, evaluation based on physiological indicators, evaluation based on behavioral observation, and evaluation based on the quality of forest health care forests.

[0004] However, among the existing evaluation methods, the evaluation methods based on forest health forest quality usually rely on the static analysis of a single environmental indicator (such as air quality or temperature), and lack comprehensive consideration of multi-dimensional data (such as PM concentration, negative ion concentration, vegetation coverage, noise intensity, etc.); in addition, the method fails to combine historical data for dynamic comparison, resulting in the evaluation results being not objective and accurate enough, making it difficult to effectively guide the planning and management of forest health activities. Summary of the invention

[0005] In view of the deficiencies in the prior art, the present invention provides a forest health care activity suitability evaluation system to solve the above-mentioned problems.

[0006] To achieve the above objectives, the present invention is implemented through the following technical solutions: a forest health care activity suitability evaluation system, comprising: Health and wellness factor analysis unit: used to obtain health and wellness factor data of forests and generate peak levels of health and wellness factors; among them, health and wellness factor data include PM 2.5 Concentration, PM 10 concentration, air negative ion concentration and oxygen content; among them, the acquisition scope of forest health care element data includes current health care element data and historical health care element data; Health and wellness factor judgment module: used to judge whether the health and wellness factors of the current forest are better than historical data based on the peak level of health and wellness factors; Air data analysis unit: if the current forest health care elements are better than historical data, the air data analysis unit is used to obtain the current forest air data for analysis and generate an air data evaluation index; wherein the air data includes air temperature, air humidity and wind speed; Health and wellness activity suitability evaluation basic index generation module: used to generate the health and wellness activity suitability evaluation basic index according to the peak level of health and wellness elements and the air data evaluation index; Air status judgment module: used to judge whether the current forest air meets the requirements of health care activities according to the basic index of health care activity suitability evaluation; Suitability comprehensive evaluation unit: If the current forest air meets the requirements of health care activities, the suitability comprehensive evaluation unit is used to obtain the environmental evaluation data of the current forest, establish a suitability comprehensive evaluation model, and generate a suitability comprehensive evaluation index; wherein the environmental evaluation data includes the vegetation coverage evaluation value, the number of tourists evaluation value, and the noise intensity evaluation value; Suitability judgment module: used to judge the suitability of forest health care activities according to the comprehensive suitability evaluation index, and generate suitability evaluation signals for forest health care activities; the suitability evaluation signals include very suitable signals, suitable signals and unsuitable signals.

[0007] On the basis of the above technical solution, the present invention also provides the following optional technical solution: Further technical solution: The health care element analysis unit specifically includes the following modules: Data acquisition module: used to obtain PM of the forest in current and historical periods 2.5 Concentration, PM 10 concentration, air negative ion concentration and oxygen content; Data classification module: for PM analysis of current and historical forest periods 2.5 Concentration, PM 10 The concentration, air negative ion concentration and oxygen content are analyzed and divided into positive correlation data and negative correlation data; among them, the positive correlation data is the air negative ion concentration, and the negative correlation data is PM 2.5 Concentration, PM 10 concentration and oxygen content; Positive correlation data processing module: used to normalize the positive correlation data respectively to generate a collection of positive correlation data evaluation values; wherein the collection of positive correlation data evaluation values ​​includes an evaluation value of air negative ion concentration; Negative correlation data processing module: used to perform Min-max normalization processing on negative correlation data and generate a collection of negative correlation data evaluation values; wherein, the collection of negative correlation data evaluation values ​​includes PM 2.5 Concentration evaluation value, PM 10 Concentration assessment values ​​and oxygen content assessment values; Health and wellness factor peak level generation module: used to perform weighted processing on all positive correlation data evaluation values ​​and all negative correlation data evaluation values ​​to generate health and wellness factor peak levels.

[0008] Further technical solution: The method for generating the positive correlation data evaluation value collection is specifically as follows: By formula: ; Generate a collection of positive correlation data evaluation values ; In the formula, It indicates the current concentration of negative ions in the air. It represents the minimum value of negative air ion concentration in the historical period. It represents the maximum value of negative air ion concentration in the historical period; The negative correlation data evaluation value collection is generated in the following manner: By formula: ; Generate a collection of negative correlation data evaluation values ; In the formula, It represents the current negative correlation data. It represents the maximum value of negative correlation data in the historical period. It represents the minimum value of negative correlation data in the historical period; The peak level of health care elements is generated in the following way: By formula: ; Generate the peak level g of health and wellness elements; In the formula, It indicates the estimated value of negative ion concentration in the air. It means PM 2.5 Concentration estimation value, It means PM 10 Concentration estimation value, It represents the oxygen content assessment value, and a1, a2, a3, and a4 are all weight coefficients.

[0009] Further technical solution: The judgment method of the health care element judgment module is specifically as follows: Compare the peak level of health-care elements with the peak level threshold of health-care elements. If the peak level of health-care elements is greater than the peak level threshold of health-care elements, it means that the larger the peak level of health-care elements, the better the health-care elements of the current forest. It is judged that the health-care elements of the current forest are better than the historical data.

[0010] Further technical solution: The air data analysis unit specifically includes the following modules: Air data acquisition module: If the current forest health care elements are better than historical data, the air data acquisition module is used to obtain the current forest air data; wherein the air data includes air temperature, air humidity and wind speed; Temperature analysis module: used to generate the current forest air temperature evaluation value according to the current forest air temperature; Humidity analysis module: used to generate the current forest air humidity assessment value according to the current forest air humidity; Wind speed analysis module: used to generate the wind speed assessment value of the current forest according to the current wind speed of the forest; Air data evaluation index generation module: used to perform weighted processing on the air temperature evaluation value of the current forest, the air humidity evaluation value of the previous forest and the wind speed evaluation value of the current forest to generate an air data evaluation index.

[0011] Further technical solution: The current forest air temperature evaluation value is generated in the following manner: Compare the current forest air temperature with the standard temperature range for human activities. If the current forest air temperature is not within the standard temperature range for human activities, it means that the current forest air temperature does not meet the standards for human activities, and the current forest air temperature is marked as abnormal temperature. The abnormal temperature is subtracted from the near end point of the standard temperature range for human activities to generate an air temperature difference value; The air temperature difference value is compared with the near end point of the standard temperature range for human activities to generate the current forest air temperature assessment value; The current forest air humidity assessment value is generated in the following manner: Compare the current forest air humidity with the standard humidity range for human activities. If the current forest air humidity is not within the standard humidity range for human activities, it means that the current forest air humidity does not meet the standards for human activities, and the current forest air humidity is marked as abnormal humidity. The abnormal humidity is processed with the near end point of the standard humidity range for human activities to generate the air humidity difference value; The air humidity difference value is compared with the near end point of the standard humidity range for human activities to generate the current forest air humidity assessment value; The wind speed assessment value of the current forest is generated in the following manner: Compare the current forest wind speed with the standard wind speed range for human activities. If the current forest wind speed is not within the standard wind speed range for human activities, it means that the current forest wind speed does not meet the standards for human activities, and the current forest wind speed is marked as abnormal wind speed. Perform difference processing between the abnormal wind speed and the near end point of the standard wind speed range for human activities to generate a wind speed difference value; The wind speed difference value is compared with the proximal end point of the standard wind speed range for human activities to generate the current forest wind speed assessment value.

[0012] Further technical solution: The method for generating the basic index for evaluating the suitability of health care activities is specifically as follows: By formula: ; Generate the basic index CI for evaluating the suitability of health and wellness activities; In the formula, AQI represents the air data evaluation index, and g represents the peak level of health and wellness elements.

[0013] Further technical solution: The judgment method of the air state judgment module is specifically as follows: Compare the basic index CI of health and wellness activity suitability evaluation with the threshold of the basic index of health and wellness activity suitability evaluation; If the basic index CI for suitability evaluation of health and wellness activities is less than or equal to the threshold value of the basic index CI for suitability evaluation of health and wellness activities, it means that the smaller the basic index CI for suitability evaluation of health and wellness activities is, the better the current forest air condition is, and it is judged that the current forest air meets the requirements of health and wellness activities.

[0014] Further technical solution: The suitability comprehensive evaluation unit specifically includes the following modules: Environmental evaluation data acquisition module: If the current forest air meets the requirements of health care activities, the environmental evaluation data acquisition module is used to obtain the environmental evaluation data of the current forest; wherein the environmental evaluation data includes the vegetation coverage evaluation value, the number of tourists evaluation value and the noise intensity evaluation value; Evaluation model building module: used to establish a comprehensive suitability evaluation model; Suitability comprehensive evaluation index generation module: used to substitute the current forest environmental evaluation data and health and wellness activity suitability evaluation basic index into the suitability comprehensive evaluation model to generate a suitability comprehensive evaluation index; Among them, the expression of the comprehensive evaluation model of suitability is: ; Generate the comprehensive suitability evaluation index FCASI; In the expression, CI represents the basic index for evaluating the suitability of health care activities, P score It represents the vegetation coverage evaluation value, M score It represents the evaluation value of the number of tourists, N score It represents the noise intensity evaluation value; The vegetation coverage evaluation value is obtained in the following way: Divide the current forest into several areas and obtain the vegetation coverage rate of each area; The forest greening rate refers to the ratio of the area of ​​forest land covered by vegetation to the total area of ​​forest land; The vegetation coverage rate of each area is compared with the minimum requirement value of vegetation coverage rate for health and wellness activities. If the vegetation coverage rate is less than the minimum requirement value of vegetation coverage rate for health and wellness activities, the area is marked as a low vegetation coverage area; Obtain the number of areas with low vegetation coverage, and perform ratio processing on the number of areas with low vegetation coverage and the total number of areas to generate the percentage of areas with low vegetation coverage; The vegetation coverage rate of the area with low vegetation coverage rate is processed by difference with the minimum requirement value of vegetation coverage rate for health care activities to generate the vegetation coverage rate deviation value; The vegetation coverage deviation value is compared with the minimum requirement value of the vegetation coverage for health and wellness activities to generate the vegetation coverage deviation ratio; All vegetation coverage deviation ratios are averaged to generate the vegetation coverage deviation percentage; The percentage of areas with low vegetation coverage and the percentage of vegetation coverage deviation are weighted and summed to generate the vegetation coverage evaluation value; The method for obtaining the evaluation value of the number of tourists is specifically as follows: Divide the current forest into several areas and obtain the number of tourists in each area; Compare the number of tourists in each area with the tourist number threshold. If the number of tourists is greater than or equal to the tourist number threshold, mark the area as a tourist-dense area. The tourist number threshold refers to the maximum number of tourists that a single area can accommodate under comfortable conditions; Obtain the number of tourist-dense areas, and perform ratio processing on the number of tourist-dense areas and the total number of areas to generate the ratio of tourist-dense areas; The number of tourists in the tourist-dense area is subtracted from the tourist number threshold to generate a tourist number deviation value; The tourist number deviation value is compared with the tourist number threshold value to generate a tourist number deviation ratio; All the deviation ratios of the number of tourists are averaged to generate the deviation ratio of the number of tourists; The proportion of tourist-dense areas and the proportion of tourist quantity deviation are weighted and summed to generate a tourist quantity evaluation value; The noise intensity evaluation value is obtained in the following manner: Divide the current forest into several areas and obtain the noise intensity of each area; Compare the noise intensity of each area with the noise intensity threshold, and if the noise intensity is greater than or equal to the noise intensity threshold, mark the area as a noise interference area; The noise intensity threshold refers to the maximum noise intensity that can occur in a single area under comfortable conditions; Obtain the number of noise interference areas, perform ratio processing on the number of noise interference areas and the total number of areas, and generate the ratio of the number of noise interference areas; Performing difference processing on the noise intensity of the noise interference area and the noise intensity threshold to generate a noise intensity excess value; The noise intensity excess value is processed by ratio with the noise intensity threshold to generate a noise intensity excess ratio; All noise intensity excess ratios are averaged to generate the noise intensity excess percentage; The noise intensity evaluation value is generated by taking the weighted sum of the proportion of noise interference areas and the proportion of noise intensity exceeding the limit.

[0015] Further technical solution: The judgment method of the suitability judgment module is specifically as follows: The suitability comprehensive evaluation index is compared with the suitability comprehensive evaluation index range; the minimum value of the suitability comprehensive evaluation index range is marked as the first threshold, and the maximum value of the suitability comprehensive evaluation index range is marked as the second threshold; If the comprehensive suitability evaluation index is less than or equal to the first threshold, it means that the smaller the comprehensive suitability evaluation index is, the higher the suitability of forest health care activities is, and a very suitable signal is generated; If the comprehensive suitability evaluation index is greater than the first threshold and less than the second threshold, it means that the comprehensive suitability evaluation index is within the comprehensive suitability evaluation index range, and a suitable signal is generated; If the comprehensive evaluation index of suitability is greater than or equal to the second threshold, it means that the larger the comprehensive evaluation index of suitability is, the lower the suitability of forest health care activities is, and an unsuitable signal is generated.

[0016] The present invention provides a forest health care activity suitability evaluation system, which has the following beneficial effects compared with the prior art: The present invention obtains current and historical forest health factor data, generates peak levels through normalization and standardization processing; generates an air data evaluation index by combining air temperature, humidity and wind speed; further integrates vegetation coverage, visitor density and noise intensity to construct a comprehensive evaluation model, and outputs a suitability evaluation signal; the present invention constructs a comprehensive dynamic evaluation system to achieve multi-dimensional comprehensive consideration of the forest health environment, improves the objectivity and reliability of the evaluation results, provides precise guidance for the planning and management of forest health activities, and helps promote the healthy development of the forest health industry. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 A schematic diagram of the structure of a forest health care activity suitability evaluation system provided by the present invention.

[0018] Figure 2 This is a module block diagram of the health care element analysis unit provided by the present invention.

[0019] Figure 3 This is a module block diagram of the air data analysis unit provided by the present invention.

[0020] Figure 4 This is a module block diagram of the comprehensive suitability evaluation unit provided by the present invention.

[0021] Figure 5 A schematic flow chart of the determination method of the suitability determination module provided by the present invention. DETAILED DESCRIPTION

[0022] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0023] The specific implementation of the present invention is described in detail below in conjunction with specific embodiments.

[0024] See also Figure 1 , a forest health care activity suitability evaluation system provided by an embodiment of the present invention, comprising: Health and wellness factor analysis unit: used to obtain health and wellness factor data of forests and generate peak levels of health and wellness factors; among them, health and wellness factor data include PM 2.5 Concentration, PM 10 concentration, air negative ion concentration and oxygen content; among them, the acquisition scope of forest health care element data includes current health care element data and historical health care element data; Health and wellness factor judgment module: used to judge whether the health and wellness factors of the current forest are better than historical data based on the peak level of health and wellness factors; Air data analysis unit: if the current forest health care elements are better than historical data, the air data analysis unit is used to obtain the current forest air data for analysis and generate an air data evaluation index; wherein the air data includes air temperature, air humidity and wind speed; Health and wellness activity suitability evaluation basic index generation module: used to generate the health and wellness activity suitability evaluation basic index according to the peak level of health and wellness elements and the air data evaluation index; Air status judgment module: used to judge whether the current forest air meets the requirements of health care activities according to the basic index of health care activity suitability evaluation; Suitability comprehensive evaluation unit: If the current forest air meets the requirements of health care activities, the suitability comprehensive evaluation unit is used to obtain the environmental evaluation data of the current forest, establish a suitability comprehensive evaluation model, and generate a suitability comprehensive evaluation index; wherein the environmental evaluation data includes the vegetation coverage evaluation value, the number of tourists evaluation value, and the noise intensity evaluation value; Suitability judgment module: used to judge the suitability of forest health care activities according to the comprehensive suitability evaluation index, and generate suitability evaluation signals for forest health care activities; the suitability evaluation signals include very suitable signals, suitable signals and unsuitable signals.

[0025] See also Figure 2 As a preferred embodiment of the present invention, the health care element analysis unit specifically includes the following modules: Data acquisition module: used to obtain PM of the forest in current and historical periods 2.5 Concentration, PM 10 concentration, air negative ion concentration and oxygen content; Data classification module: for PM analysis of current and historical forest periods 2.5 Concentration, PM 10 The concentration, air negative ion concentration and oxygen content are analyzed and divided into positive correlation data and negative correlation data; among them, the positive correlation data is the air negative ion concentration, and the negative correlation data is PM 2.5 Concentration, PM 10 concentration and oxygen content; It should be explained that positive correlation means the larger the better, and negative correlation means the smaller the better. In practical applications, the oxygen content in forests is generally not lower than the minimum standard content of oxygen content for humans. This is because the plants in the forest release a large amount of oxygen through photosynthesis, making the forest an environment with high oxygen content; therefore, the current oxygen content needs to be at the lowest level when analyzing historical data; in addition, PM 2.5 Concentration, PM 10 The classification of concentration and negative air ion concentration is well known to relevant personnel in the field and will not be repeated here; Positive correlation data processing module: used to normalize the positive correlation data respectively to generate a collection of positive correlation data evaluation values; wherein the collection of positive correlation data evaluation values ​​includes an evaluation value of air negative ion concentration; Negative correlation data processing module: used to perform Min-max normalization processing on negative correlation data and generate a collection of negative correlation data evaluation values; wherein, the collection of negative correlation data evaluation values ​​includes PM 2.5 Concentration evaluation value, PM 10 Concentration assessment values ​​and oxygen content assessment values; Health and wellness factor peak level generation module: used to perform weighted processing on all positive correlation data evaluation values ​​and all negative correlation data evaluation values ​​to generate health and wellness factor peak levels.

[0026] As a preferred embodiment of the present invention, the positive correlation data evaluation value collection is generated in the following manner: By formula: ; Generate a collection of positive correlation data evaluation values ; In the formula, It indicates the current concentration of negative ions in the air. It represents the minimum value of negative air ion concentration in the historical period. It represents the maximum value of negative air ion concentration in the historical period.

[0027] As a preferred embodiment of the present invention, the negative correlation data evaluation value collection is generated in the following manner: By formula: ; Generate a collection of negative correlation data evaluation values ; In the formula, It represents the current negative correlation data. It represents the maximum value of negative correlation data in the historical period. It represents the minimum value of negative correlation data in the historical period.

[0028] As a preferred embodiment of the present invention, the peak level of the health care factor is generated in the following manner: By formula: ; Generate the peak level g of health and wellness elements; In the formula, It indicates the estimated value of negative ion concentration in the air. It means PM 2.5 Concentration estimation value, It means PM 10 Concentration estimation value, It represents the oxygen content assessment value, and a1, a2, a3, and a4 are all weight coefficients; It should be explained that the values ​​of a1, a2, a3, and a4 are generated through expert consultation combined with the hierarchical analysis method.

[0029] As a preferred embodiment of the present invention, the judgment method of the health care element judgment module is specifically as follows: Compare the peak level of the health-care factor with the peak level threshold of the health-care factor. If the peak level of the health-care factor is less than or equal to the peak level threshold of the health-care factor, it means that the smaller the peak level of the health-care factor, the worse the health-care factor of the current forest is, and it is determined that the health-care factor of the current forest is worse than the historical data. If the peak level of the health-care factor is greater than the peak level threshold of the health-care factor, it means that the greater the peak level of the health-care factor, the better the health-care factor of the current forest, and it is determined that the health-care factor of the current forest is better than the historical data; It should be explained that the value of the peak level threshold of health and wellness elements is set by relevant personnel in this field; in addition, the peak level threshold of health and wellness elements can be a range value, which is divided into one or more ranges according to different standards.

[0030] See also Figure 3 As a preferred embodiment of the present invention, the air data analysis unit specifically includes the following modules: Air data acquisition module: If the current forest health care elements are better than historical data, the air data acquisition module is used to obtain the current forest air data; wherein the air data includes air temperature, air humidity and wind speed; Temperature analysis module: used to generate the current forest air temperature evaluation value according to the current forest air temperature; Humidity analysis module: used to generate the current forest air humidity assessment value according to the current forest air humidity; Wind speed analysis module: used to generate the wind speed assessment value of the current forest according to the current wind speed of the forest; Air data evaluation index generation module: used to perform weighted processing on the current forest air temperature evaluation value, the current forest air humidity evaluation value and the current forest wind speed evaluation value to generate an air data evaluation index; For example, by the formula: ; Generate air quality index AQI; In the formula, T current It represents the current forest air temperature assessment value, H current It represents the current forest air humidity assessment value, V current It represents the current forest wind speed assessment value, α, β, and γ are all proportional coefficients; It should be explained that the values ​​of α, β, and γ are determined by a linear regression equation in a linear regression method, which is an existing algorithm and will not be described in detail here.

[0031] As a preferred embodiment of the present invention, the current forest air temperature evaluation value is generated in the following manner: Compare the current forest air temperature with the standard temperature range for human activities. If the current forest air temperature is within the standard temperature range for human activities, it means that the current forest air temperature meets the standards for human activities, and the current forest air temperature is marked as a comfortable temperature. If the current forest air temperature is not within the standard temperature range for human activities, it means that the current forest air temperature does not meet the standards for human activities, and the current forest air temperature is marked as abnormal temperature; The abnormal temperature is subtracted from the near end point of the standard temperature range for human activities to generate an air temperature difference value; The air temperature difference value is compared with the near end point of the standard temperature range for human activities to generate the current forest air temperature assessment value; It should be explained that the proximal end point of the standard temperature range for human activities refers to the end point in the standard temperature range for human activities that is shortest away from the abnormal temperature.

[0032] As a preferred embodiment of the present invention, the current forest air humidity assessment value is generated in the following manner: Compare the current forest air humidity with the standard humidity range for human activities. If the current forest air humidity is within the standard humidity range for human activities, it means that the current forest air humidity meets the standards for human activities, and the current forest air humidity is marked as comfortable humidity. If the current forest air humidity is not within the standard humidity range for human activities, it means that the current forest air humidity does not meet the standards for human activities, and the current forest air humidity is marked as abnormal humidity; The abnormal humidity is processed with the near end point of the standard humidity range for human activities to generate the air humidity difference value; The air humidity difference value is compared with the near end point of the standard humidity range for human activities to generate the current forest air humidity assessment value; It should be explained that the proximal end point of the standard humidity range for human activities refers to the end point in the standard humidity range for human activities that is shortest away from the abnormal humidity.

[0033] As a preferred embodiment of the present invention, the wind speed evaluation value of the current forest is generated in the following manner: Compare the current forest wind speed with the standard wind speed range for human activities. If the current forest wind speed is within the standard wind speed range for human activities, it means that the current forest wind speed meets the standards for human activities, and the current forest wind speed is marked as a comfortable wind speed. If the current wind speed in the forest is not within the standard wind speed range for human activities, it means that the current wind speed in the forest does not meet the standards for human activities, and the current wind speed in the forest is marked as abnormal wind speed; Perform difference processing between the abnormal wind speed and the near end point of the standard wind speed range for human activities to generate a wind speed difference value; The wind speed difference value is compared with the near end point of the standard wind speed range for human activities to generate the wind speed assessment value of the current forest; It should be explained that the proximal end point of the standard wind speed range for human activities refers to the end point in the standard humidity range for human activities with the shortest distance to the abnormal wind speed.

[0034] As a preferred embodiment of the present invention, the method for generating the basic index for evaluating the suitability of health care activities is specifically as follows: By formula: ; Generate the basic index CI for suitability evaluation of health and wellness activities; In the formula, AQI represents the air data evaluation index, and g represents the peak level of health and wellness elements.

[0035] As a preferred embodiment of the present invention, the judgment method of the air state judgment module is specifically as follows: Compare the basic index CI of health and wellness activity suitability evaluation with the threshold of the basic index of health and wellness activity suitability evaluation; If the basic index CI for health and wellness activity suitability evaluation is less than or equal to the basic index threshold for health and wellness activity suitability evaluation, it means that the smaller the basic index CI for health and wellness activity suitability evaluation is, the better the current forest air condition is, and it is determined that the current forest air meets the requirements of health and wellness activities; If the basic index CI for health and wellness activity suitability evaluation is greater than the basic index threshold for health and wellness activity suitability evaluation, it means that the larger the basic index CI for health and wellness activity suitability evaluation is, the worse the current forest air condition is, and it is determined that the current forest air does not meet the requirements of health and wellness activities; It needs to be explained that the method of obtaining the threshold of the basic index for evaluating the suitability of health and wellness activities is consistent with the method of obtaining the basic index CI for evaluating the suitability of health and wellness activities, and its value is set by relevant personnel in this field.

[0036] See also Figure 4 As a preferred embodiment of the present invention, the suitability comprehensive evaluation unit specifically includes the following modules: Environmental evaluation data acquisition module: If the current forest air meets the requirements of health care activities, the environmental evaluation data acquisition module is used to obtain the environmental evaluation data of the current forest; wherein the environmental evaluation data includes the vegetation coverage evaluation value, the number of tourists evaluation value and the noise intensity evaluation value; Evaluation model building module: used to establish a comprehensive suitability evaluation model; Suitability comprehensive evaluation index generation module: used to substitute the current forest environmental evaluation data and health and wellness activity suitability evaluation basic index into the suitability comprehensive evaluation model to generate a suitability comprehensive evaluation index; Among them, the expression of the comprehensive evaluation model of suitability is: ; Generate the comprehensive suitability evaluation index FCASI; In the expression, CI represents the basic index for evaluating the suitability of health care activities, P score It represents the vegetation coverage evaluation value, M score It represents the evaluation value of the number of tourists, N score It represents the noise intensity evaluation value.

[0037] As a preferred embodiment of the present invention, the vegetation coverage evaluation value is obtained in the following manner: Divide the current forest into several areas and obtain the vegetation coverage rate of each area; The forest greening rate refers to the ratio of the area of ​​forest land covered by vegetation to the total area of ​​forest land; The vegetation coverage rate of each area is compared with the minimum requirement value of vegetation coverage rate for health and wellness activities. If the vegetation coverage rate is less than the minimum requirement value of vegetation coverage rate for health and wellness activities, the area is marked as a low vegetation coverage area; Obtain the number of areas with low vegetation coverage, and perform ratio processing on the number of areas with low vegetation coverage and the total number of areas to generate the percentage of areas with low vegetation coverage; The vegetation coverage rate of the area with low vegetation coverage rate is processed by difference with the minimum requirement value of vegetation coverage rate for health care activities to generate the vegetation coverage rate deviation value; The vegetation coverage deviation value is compared with the minimum requirement value of the vegetation coverage for health and wellness activities to generate the vegetation coverage deviation ratio; All vegetation coverage deviation ratios are averaged to generate the vegetation coverage deviation percentage; The weighted sum of the proportion of areas with low vegetation coverage and the proportion of vegetation coverage deviation is taken to generate the vegetation coverage evaluation value.

[0038] As a preferred embodiment of the present invention, the method for obtaining the evaluation value of the number of tourists is specifically as follows: Divide the current forest into several areas and obtain the number of tourists in each area; Compare the number of tourists in each area with the tourist number threshold. If the number of tourists is greater than or equal to the tourist number threshold, mark the area as a tourist-dense area. It should be explained that the threshold number of tourists refers to the maximum number of tourists that a single area can accommodate under comfortable conditions; Obtain the number of tourist-dense areas, and perform ratio processing on the number of tourist-dense areas and the total number of areas to generate the ratio of tourist-dense areas; The number of tourists in the tourist-dense area is subtracted from the tourist number threshold to generate a tourist number deviation value; The tourist number deviation value is compared with the tourist number threshold value to generate a tourist number deviation ratio; All the deviation ratios of the number of tourists are averaged to generate the deviation ratio of the number of tourists; The weighted sum of the proportion of tourist-dense areas and the proportion of tourist number deviation is taken to generate a tourist number evaluation value.

[0039] As a preferred embodiment of the present invention, the noise intensity evaluation value is obtained in the following manner: Divide the current forest into several areas and obtain the noise intensity of each area; Compare the noise intensity of each area with the noise intensity threshold, and if the noise intensity is greater than or equal to the noise intensity threshold, mark the area as a noise interference area; It should be explained that the noise intensity threshold refers to the maximum noise intensity that can occur in a single area under comfortable conditions; in addition, noise refers to the sound intensity caused by human activities, such as car horns, mobile phone speakers, and crowd noise; Obtain the number of noise interference areas, perform ratio processing on the number of noise interference areas and the total number of areas, and generate the ratio of the number of noise interference areas; Performing difference processing on the noise intensity of the noise interference area and the noise intensity threshold to generate a noise intensity excess value; The noise intensity excess value is processed by ratio with the noise intensity threshold to generate a noise intensity excess ratio; All noise intensity excess ratios are averaged to generate the noise intensity excess percentage; The noise intensity evaluation value is generated by taking the weighted sum of the proportion of noise interference areas and the proportion of noise intensity exceeding the limit.

[0040] See also Figure 5 As a preferred embodiment of the present invention, the determination method of the suitability determination module is specifically as follows: The suitability comprehensive evaluation index is compared with the suitability comprehensive evaluation index range; the minimum value of the suitability comprehensive evaluation index range is marked as the first threshold, and the maximum value of the suitability comprehensive evaluation index range is marked as the second threshold; It should be explained that the range of the comprehensive evaluation index of suitability is the range for evaluating the suitability of forest health care activities, and its value is set by relevant personnel in this field; If the comprehensive suitability evaluation index is less than or equal to the first threshold, it means that the smaller the comprehensive suitability evaluation index is, the higher the suitability of forest health care activities is, and a very suitable signal is generated; If the comprehensive suitability evaluation index is greater than the first threshold and less than the second threshold, it means that the comprehensive suitability evaluation index is within the comprehensive suitability evaluation index range, and a suitable signal is generated; If the comprehensive evaluation index of suitability is greater than or equal to the second threshold, it means that the larger the comprehensive evaluation index of suitability is, the lower the suitability of forest health care activities is, and an unsuitable signal is generated.

[0041] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A forest health care activity suitability evaluation system, characterized in that: include: Health and wellness factor analysis unit: used to obtain health and wellness factor data of forests and generate peak levels of health and wellness factors; among them, health and wellness factor data include PM 2.5 Concentration, PM 10 concentration, air negative ion concentration and oxygen content; among which, the acquisition scope of forest health care element data includes current health care element data and historical health care element data; Health and wellness factor judgment module: used to judge whether the health and wellness factors of the current forest are better than historical data based on the peak level of health and wellness factors; Air data analysis unit: if the current forest health care elements are better than historical data, the air data analysis unit is used to obtain the current forest air data for analysis and generate an air data evaluation index; wherein the air data includes air temperature, air humidity and wind speed; Health and wellness activity suitability evaluation basic index generation module: used to generate the health and wellness activity suitability evaluation basic index according to the peak level of health and wellness elements and the air data evaluation index; Air status judgment module: used to judge whether the current forest air meets the requirements of health care activities according to the basic index of health care activity suitability evaluation; Suitability comprehensive evaluation unit: If the current forest air meets the requirements of health care activities, the suitability comprehensive evaluation unit is used to obtain the environmental evaluation data of the current forest, establish a suitability comprehensive evaluation model, and generate a suitability comprehensive evaluation index; wherein the environmental evaluation data includes the vegetation coverage evaluation value, the number of tourists evaluation value, and the noise intensity evaluation value; Suitability judgment module: used to judge the suitability of forest health care activities according to the comprehensive suitability evaluation index, and generate suitability evaluation signals for forest health care activities; the suitability evaluation signals include very suitable signals, suitable signals and unsuitable signals.

2. A forest health care activity suitability evaluation system according to claim 1, characterized in that: The health care element analysis unit specifically includes the following modules: Data acquisition module: used to obtain PM of the forest in current and historical periods 2.5 Concentration, PM 10 concentration, air negative ion concentration and oxygen content; Data classification module: for PM analysis of current and historical forest periods 2.5 Concentration, PM 10 The concentration, air negative ion concentration and oxygen content are analyzed and divided into positive correlation data and negative correlation data; among them, the positive correlation data is the air negative ion concentration, and the negative correlation data is PM 2.5 Concentration, PM 10 concentration and oxygen content; Positive correlation data processing module: used to normalize the positive correlation data respectively to generate a collection of positive correlation data evaluation values; wherein the collection of positive correlation data evaluation values ​​includes an evaluation value of air negative ion concentration; Negative correlation data processing module: used to perform Min-max normalization processing on negative correlation data and generate a collection of negative correlation data evaluation values; wherein, the collection of negative correlation data evaluation values ​​includes PM 2.5 Concentration evaluation value, PM 10 Concentration assessment values ​​and oxygen content assessment values; Health and wellness factor peak level generation module: used to perform weighted processing on all positive correlation data evaluation values ​​and all negative correlation data evaluation values ​​to generate health and wellness factor peak levels.

3. A forest health care activity suitability evaluation system according to claim 2, characterized in that: The method for generating the positive correlation data evaluation value collection is specifically as follows: By formula: ； Generate a collection of positive correlation data evaluation values ; In the formula, It indicates the current concentration of negative ions in the air. It represents the minimum value of negative air ion concentration in the historical period. It represents the maximum value of negative air ion concentration in the historical period; The negative correlation data evaluation value collection is generated in the following manner: By formula: ； Generate a collection of negative correlation data evaluation values ; In the formula, It represents the current negative correlation data. It represents the maximum value of negative correlation data in the historical period. It represents the minimum value of negative correlation data in the historical period; The peak level of health care elements is generated in the following way: By formula: ； Generate the peak level g of health and wellness elements; In the formula, It indicates the estimated value of negative ion concentration in the air. It means PM 2.5 Concentration estimation value, It means PM 10 Concentration estimation value, It represents the assessed value of oxygen content, and a1, a2, a3, and a4 are all weight coefficients.

4. A forest health care activity suitability evaluation system according to claim 2, characterized in that: The judgment method of the health care element judgment module is specifically as follows: Compare the peak level of health-care elements with the peak level threshold of health-care elements. If the peak level of health-care elements is greater than the peak level threshold of health-care elements, it means that the larger the peak level of health-care elements, the better the health-care elements of the current forest. It is judged that the health-care elements of the current forest are better than the historical data.

5. A forest health care activity suitability evaluation system according to claim 1, characterized in that: The air data analysis unit specifically includes the following modules: Air data acquisition module: If the current forest health care elements are better than historical data, the air data acquisition module is used to obtain the current forest air data; wherein the air data includes air temperature, air humidity and wind speed; Temperature analysis module: used to generate the current forest air temperature evaluation value according to the current forest air temperature; Humidity analysis module: used to generate the current forest air humidity assessment value according to the current forest air humidity; Wind speed analysis module: used to generate the wind speed assessment value of the current forest according to the current wind speed of the forest; Air data evaluation index generation module: used to perform weighted processing on the air temperature evaluation value of the current forest, the air humidity evaluation value of the previous forest and the wind speed evaluation value of the current forest to generate an air data evaluation index.

6. A forest health care activity suitability evaluation system according to claim 5, characterized in that: The current forest air temperature assessment value is generated in the following manner: Compare the current forest air temperature with the standard temperature range for human activities. If the current forest air temperature is not within the standard temperature range for human activities, it means that the current forest air temperature does not meet the standards for human activities, and the current forest air temperature is marked as abnormal temperature. The abnormal temperature is subtracted from the near end point of the standard temperature range for human activities to generate an air temperature difference value; The air temperature difference value is compared with the near end point of the standard temperature range for human activities to generate the current forest air temperature assessment value; The current forest air humidity assessment value is generated in the following manner: Compare the current forest air humidity with the standard humidity range for human activities. If the current forest air humidity is not within the standard humidity range for human activities, it means that the current forest air humidity does not meet the standards for human activities, and the current forest air humidity is marked as abnormal humidity. The abnormal humidity is processed with the near end point of the standard humidity range for human activities to generate the air humidity difference value; The air humidity difference value is compared with the near end point of the standard humidity range for human activities to generate the current forest air humidity assessment value; The wind speed assessment value of the current forest is generated in the following manner: Compare the current forest wind speed with the standard wind speed range for human activities. If the current forest wind speed is not within the standard wind speed range for human activities, it means that the current forest wind speed does not meet the standards for human activities, and the current forest wind speed is marked as abnormal wind speed. Perform difference processing between the abnormal wind speed and the near end point of the standard wind speed range for human activities to generate a wind speed difference value; The wind speed difference value is compared with the proximal end point of the standard wind speed range for human activities to generate the current forest wind speed assessment value.

7. A forest health care activity suitability evaluation system according to claim 1, characterized in that: The method for generating the basic index for evaluating the suitability of health care activities is as follows: By formula: ； Generate the basic index CI for suitability evaluation of health and wellness activities; In the formula, AQI represents the air data evaluation index, and g represents the peak level of health and wellness elements.

8. A forest health care activity suitability evaluation system according to claim 7, characterized in that: The determination method of the air state determination module is specifically as follows: Compare the basic index CI of health and wellness activity suitability evaluation with the threshold of the basic index of health and wellness activity suitability evaluation; If the basic index CI for suitability evaluation of health and wellness activities is less than or equal to the threshold value of the basic index CI for suitability evaluation of health and wellness activities, it means that the smaller the basic index CI for suitability evaluation of health and wellness activities is, the better the current forest air condition is, and it is judged that the current forest air meets the requirements of health and wellness activities.

9. A forest health care activity suitability evaluation system according to claim 7, characterized in that: The suitability comprehensive evaluation unit specifically includes the following modules: Environmental evaluation data acquisition module: If the current forest air meets the requirements of health care activities, the environmental evaluation data acquisition module is used to obtain the environmental evaluation data of the current forest; wherein the environmental evaluation data includes the vegetation coverage evaluation value, the number of tourists evaluation value and the noise intensity evaluation value; Evaluation model building module: used to establish a comprehensive suitability evaluation model; Suitability comprehensive evaluation index generation module: used to substitute the current forest environmental evaluation data and health and wellness activity suitability evaluation basic index into the suitability comprehensive evaluation model to generate a suitability comprehensive evaluation index; Among them, the expression of the comprehensive evaluation model of suitability is: ； Generate the comprehensive suitability evaluation index FCASI; In the expression, CI represents the basic index for evaluating the suitability of health care activities, P score It represents the vegetation coverage evaluation value, M score It represents the evaluation value of the number of tourists, N score It represents the noise intensity evaluation value; The vegetation coverage evaluation value is obtained in the following way: Divide the current forest into several areas and obtain the vegetation coverage rate of each area; The forest greening rate refers to the ratio of the area of ​​forest land covered by vegetation to the total area of ​​forest land; The vegetation coverage rate of each area is compared with the minimum requirement value of vegetation coverage rate for health and wellness activities. If the vegetation coverage rate is less than the minimum requirement value of vegetation coverage rate for health and wellness activities, the area is marked as a low vegetation coverage area; Obtain the number of areas with low vegetation coverage, and perform ratio processing on the number of areas with low vegetation coverage and the total number of areas to generate the percentage of areas with low vegetation coverage; The vegetation coverage rate of the area with low vegetation coverage rate is processed by difference with the minimum requirement value of vegetation coverage rate for health care activities to generate the vegetation coverage rate deviation value; The vegetation coverage deviation value is compared with the minimum requirement value of the vegetation coverage for health and wellness activities to generate the vegetation coverage deviation ratio; All vegetation coverage deviation ratios are averaged to generate the vegetation coverage deviation percentage; The percentage of areas with low vegetation coverage and the percentage of vegetation coverage deviation are weighted and summed to generate the vegetation coverage evaluation value; The method for obtaining the evaluation value of the number of tourists is specifically as follows: Divide the current forest into several areas and obtain the number of tourists in each area; Compare the number of tourists in each area with the tourist number threshold. If the number of tourists is greater than or equal to the tourist number threshold, mark the area as a tourist-dense area. The tourist number threshold refers to the maximum number of tourists that a single area can accommodate under comfortable conditions; Obtain the number of tourist-dense areas, and perform ratio processing on the number of tourist-dense areas and the total number of areas to generate the ratio of tourist-dense areas; The number of tourists in the tourist-dense area is subtracted from the tourist number threshold to generate a tourist number deviation value; The tourist number deviation value is compared with the tourist number threshold value to generate a tourist number deviation ratio; All the deviation ratios of the number of tourists are averaged to generate the deviation ratio of the number of tourists; The proportion of tourist-dense areas and the proportion of tourist quantity deviation are weighted and summed to generate a tourist quantity evaluation value; The noise intensity evaluation value is obtained in the following manner: Divide the current forest into several areas and obtain the noise intensity of each area; Compare the noise intensity of each area with the noise intensity threshold, and if the noise intensity is greater than or equal to the noise intensity threshold, mark the area as a noise interference area; The noise intensity threshold refers to the maximum noise intensity that can occur in a single area under comfortable conditions; Obtain the number of noise interference areas, perform ratio processing on the number of noise interference areas and the total number of areas, and generate the ratio of the number of noise interference areas; Performing difference processing on the noise intensity of the noise interference area and the noise intensity threshold to generate a noise intensity excess value; The noise intensity excess value is processed by ratio with the noise intensity threshold to generate a noise intensity excess ratio; All noise intensity excess ratios are averaged to generate the noise intensity excess percentage; The noise intensity evaluation value is generated by taking the weighted sum of the proportion of noise interference areas and the proportion of noise intensity exceeding the limit.

10. A forest health care activity suitability evaluation system according to claim 9, characterized in that: The determination method of the suitability determination module is specifically as follows: The suitability comprehensive evaluation index is compared with the suitability comprehensive evaluation index range; the minimum value of the suitability comprehensive evaluation index range is marked as the first threshold, and the maximum value of the suitability comprehensive evaluation index range is marked as the second threshold; If the comprehensive evaluation index of suitability is less than or equal to the first threshold, it means that the smaller the comprehensive evaluation index of suitability is, the higher the suitability of forest health care activities is, and a very suitable signal is generated; If the comprehensive suitability evaluation index is greater than the first threshold and less than the second threshold, it means that the comprehensive suitability evaluation index is within the comprehensive suitability evaluation index range, and a suitable signal is generated; If the comprehensive evaluation index of suitability is greater than or equal to the second threshold, it means that the larger the comprehensive evaluation index of suitability is, the lower the suitability of forest health care activities is, and an unsuitable signal is generated.

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