Street space thermal comfort assessment method and system based on multi-index coupling and storage medium

Abstract

The invention provides a street space thermal comfort assessment method and system based on multi-index coupling, and a storage medium, and relates to the technical field of thermal comfort assessment, and the method specifically comprises the steps: collecting a plurality of representative places as to-be-assessed streets, and collecting the meteorological parameters and environmental parameters of the to-be-assessed streets; deriving a universal thermal climate index UTCI by using RayMan software, and calculating a thermal stress index and an air cooling effect index according to the parameters subjected to dimensionless processing; determining the correlation among the indexes by using a Pearson's correlation coefficient method, and calculating a comprehensive thermal comfort score in combination with an analysis result; according to the method, multiple indexes are integrated, so that the one-sidedness and limitation in a traditional evaluation method are effectively solved, and a more comprehensive and scientific street thermal comfort evaluation framework is provided. By dividing thermal stress grades and making specific improvement measures for each grade, the thermal stress level in the area can be reduced in a targeted manner, and the microclimate of the street space is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of thermal comfort assessment, and in particular to a street space thermal comfort assessment method, system and storage medium based on multi-index coupling. Background Art

[0002] With the acceleration of global climate change and urbanization, urban thermal environment issues have become an important factor affecting the quality of life of residents and the sustainable development of cities. The urban heat island effect causes the temperature inside the city to be significantly higher than that in the surrounding rural areas. Especially in summer, high temperature weather has a serious impact on people's health, comfort and quality of life. Existing thermal comfort assessment methods mostly rely on single meteorological parameters such as temperature and humidity, while ignoring the comprehensive effects of environmental factors such as wind speed, radiation intensity and green coverage. This one-sided assessment method cannot fully reflect the changes in thermal comfort in different areas of the city, nor can it reveal the mechanism of the effect of environmental parameters on thermal comfort under different climatic conditions. In addition, many traditional research methods lack systematicity and comprehensiveness, and often only conduct local analysis on specific indicators, resulting in limitations and insufficient applicability of the assessment results, and cannot provide effective decision-making support for urban management.

[0003] In the existing technology, although some studies have tried to incorporate multiple factors into thermal comfort assessment, they usually lack sufficient scientificity and practicality. For example, some studies may only rely on simulation software for calculations, without fully considering the impact of actual meteorological conditions and environmental changes on the simulation results, resulting in a large deviation between the evaluation results and the actual situation. What's more, the existing methods are often lacking in specificity in practical applications, and the specific characteristics of different cities or regions are difficult to fully reflect, which makes it difficult for urban planners and managers to formulate measures to improve the thermal environment. Therefore, there is an urgent need for a new method that can comprehensively consider multiple meteorological and environmental parameters and systematically evaluate the thermal comfort of street spaces to scientifically guide the improvement and management of the urban thermal environment.

[0004] The above information disclosed in this Background section is only for enhancement of understanding of the background of the present disclosure and therefore it may contain information that does not constitute the prior art that is already known to one of ordinary skill in the art. Summary of the invention

[0005] The purpose of the present invention is to provide a street space thermal comfort evaluation method, system and storage medium based on multi-index coupling to solve the problems raised in the above background technology.

[0006] To achieve the above object, the present invention provides the following technical solutions:

[0007] A street space thermal comfort assessment method based on multi-index coupling, the specific steps include:

[0008] Step 1: Obtain the meteorological parameters and environmental parameters of the street to be evaluated, wherein the meteorological parameters are atmospheric temperature, humidity, wind speed and surface temperature, and the environmental parameters are radiation data and green coverage rate; Step 2: Use RayMan software to derive the universal thermal climate index UTCI, calculate the heat stress index based on the dimensionless UTCI, surface temperature, radiation and green coverage rate, and calculate the wind cooling effect index based on the dimensionless temperature, humidity and wind speed;

[0009] Step 3: Use the Pearson correlation coefficient method to analyze the correlation between UTCI, heat stress index, wind chill effect index and comprehensive thermal comfort score, and combine the correlation analysis results to calculate the comprehensive thermal comfort score;

[0010] Step 4: Based on the comprehensive thermal comfort score, divide the street space into multiple heat stress levels and formulate corresponding improvement measures for each level.

[0011] Furthermore, the city's central business district, historical and cultural protection areas, parks, residential areas, schools and educational institutions, and transportation hubs in the streets to be evaluated are taken as representative locations, the meteorological parameters and environmental parameters of each representative location are obtained, and the average values ​​are taken as the meteorological parameters and environmental parameters of the streets to be evaluated.

[0012] Furthermore, meteorological parameters and environmental parameters are obtained, specifically:

[0013] Use sensors to collect the atmospheric temperature, humidity, wind speed, surface temperature, direct radiation and scattered radiation of the street to be evaluated. The atmospheric temperature is recorded as T, the humidity is recorded as S, the wind speed is recorded as V, the surface temperature is recorded as U, and the direct radiation is recorded as I. direct , scattered radiation is recorded as I diffuse ;

[0014] The radiation data is the total solar radiation, which is calculated according to the following formula:

[0015] I total =I direct +I diffuse

[0016] Among them, I total is the total solar radiation, I direct is direct radiation, i.e. direct light from the sun, I diffuse It is scattered radiation, that is, radiation scattered by clouds, gas and particles in the atmosphere;

[0017] Collect the total area of ​​the street to be evaluated and the area of ​​the green area, and calculate the green coverage rate:

[0018]

[0019] Among them, G is the green coverage rate, A green is the area of ​​the street greening area to be evaluated. The greening area refers to the area covered by plants. total The total area refers to the total area of ​​the street to be assessed, including green and non-green areas.

[0020] Furthermore, the calculation of the thermal stress index is based on the following formula:

[0021]

[0022] Among them, HSI is the heat stress index, UTCI is the universal thermal climate index, U is the surface temperature, I is total is the total solar radiation, G is the green coverage rate;

[0023] The formula for calculating the wind chill effect index is as follows:

[0024] WCI=13.12+0.6215*T-11.37*V 0.16 +0.3965*T*V 0.16 -k*S

[0025] Where WCI is the wind chill index, T is the atmospheric temperature, V is the wind speed, S is the humidity, and k is the humidity correction factor, which is used to adjust the impact of the wind chill effect.

[0026] Furthermore, the Pearson correlation coefficient method was used to analyze the correlation between UTCI, heat stress index, wind chill effect index and comprehensive thermal comfort score. The specific logic is as follows:

[0027] The Pearson correlation coefficient is a statistic that measures the strength and direction of the linear relationship between two variables. Its value range is: [-1, +1]. The specific steps are as follows:

[0028] Collect a set of historical key parameters and corresponding comprehensive thermal comfort scores of streets, the key parameters are heat stress index, wind chill effect index and UTCI;

[0029] The Pearson correlation coefficient is calculated according to the following formula:

[0030]

[0031] Among them, r is the Pearson correlation coefficient, X i represents the key parameter of the i-th sample, that is, the heat stress index or wind chill effect index, or UTCI in the i-th sample, which is used to perform correlation analysis with the corresponding comprehensive thermal comfort score, Y i represents the comprehensive thermal comfort score of the i-th sample, is the mean value of the key parameter, is the mean of the comprehensive thermal comfort score;

[0032] The calculated Pearson correlation coefficient value r is used to analyze the relationship between each key parameter and the comprehensive thermal comfort score:

[0033] When r>0, it indicates that there is a positive correlation between the parameter and the comprehensive thermal comfort score, which means that when the parameter increases, the comprehensive thermal comfort score also increases;

[0034] When r < 0, it indicates that there is a negative correlation between the parameter and the comprehensive thermal comfort score, which means that when the parameter increases, the comprehensive thermal comfort score decreases instead;

[0035] When r = 0, there is no correlation, which means that there is no linear relationship between this parameter and the comprehensive thermal comfort score;

[0036] Among them, the closer |r| is to 1, the stronger the correlation is.

[0037] Furthermore, combined with the analysis results of the correlation, the comprehensive thermal comfort score is calculated, and the specific logic is as follows:

[0038] TSV=ω1*UTCI+ω2*HSI+ω3*WCI

[0039] Among them, TSV is the comprehensive thermal comfort score, UTCI is the universal thermal climate index, HSI is the heat stress index, WCI is the wind chill effect index, and ω1, ω2, and ω3 are proportional coefficients set according to the results of correlation analysis. Furthermore, the comprehensive thermal comfort score is compared with the preset threshold value to divide the street space into multiple heat stress levels:

[0040] When TSV ≥ 0.8, it is classified as Level 1 (comfort zone), maintaining the existing green cover and water bodies, and regularly inspecting and maintaining green areas;

[0041] When 0.6≤TSV<0.8, it is classified as Level 2 (mild heat stress area), and trees and vegetation are added, road material selection is improved, and spray cooling facilities are added;

[0042] When 0.4≤TSV<0.6, it is classified as Level 3 (moderate heat stress area), and more greening projects are implemented, water area is increased, and building layout is optimized to reduce the heat island effect;

[0043] When TSV<0.4, it is classified as Level 4 (severe heat stress area), and an urban thermal environment transformation plan is formulated to increase green coverage, use reflective materials and green roof technology, and add cooling facilities.

[0044] The present invention further provides a street space thermal comfort evaluation system based on multi-index coupling, which is used to execute the above-mentioned street space thermal comfort evaluation method based on multi-index coupling, comprising:

[0045] The parameter acquisition module is used to obtain the meteorological parameters and environmental parameters of the street to be evaluated, wherein the meteorological parameters are atmospheric temperature, humidity, wind speed and surface temperature, and the environmental parameters are radiation data and green coverage rate; the data processing module is used to derive the universal thermal climate index UTCI using RayMan software, calculate the thermal stress index according to the dimensionless processed UTCI, surface temperature, radiation and green coverage rate, and calculate the wind cooling effect index according to the dimensionless processed temperature, humidity and wind speed;

[0046] The correlation analysis module is used to analyze the correlation between UTCI, heat stress index, wind chill effect index and comprehensive thermal comfort score respectively using the Pearson correlation coefficient method, and calculate the comprehensive thermal comfort score based on the correlation analysis results;

[0047] The comprehensive analysis module is used to divide the street space into multiple thermal stress levels according to the comprehensive thermal comfort score, and formulate corresponding improvement measures for each level.

[0048] Compared with the prior art, the present invention has the following beneficial effects:

[0049] The present invention effectively solves the one-sidedness and limitations of traditional evaluation methods by integrating multiple indicators, and provides a more comprehensive and scientific street thermal comfort evaluation framework. By dividing the thermal stress levels and formulating specific improvement measures for each level, the thermal stress level in the area can be reduced in a targeted manner and the microclimate of the street space can be improved. This not only improves the comfort of the urban environment, but also provides strong support for more efficient urban management and planning, thereby promoting sustainable development and enhancing the city's adaptability and risk resistance. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] Figure 1 It is a schematic diagram of the overall method flow of the present invention;

[0051] Figure 2 It is a schematic diagram of the overall system module of the present invention. DETAILED DESCRIPTION

[0052] In order to make the objectives, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with specific embodiments.

[0053] It should be noted that, unless otherwise defined, the technical terms or scientific terms used in the present invention should be understood by people with ordinary skills in the field to which the present invention belongs. The words "first", "second" and similar words used in the present invention do not indicate any order, quantity or importance, but are only used to distinguish different components. "Include" or "comprise" and similar words mean that the elements or objects appearing before the word include the elements or objects listed after the word and their equivalents, without excluding other elements or objects. "Connect" or "connected" and similar words are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. "Up", "down", "left", "right" and the like are only used to indicate relative positional relationships. When the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0054] Example:

[0055] See also Figure 1 , the present invention provides a technical solution:

[0056] A street space thermal comfort assessment method based on multi-index coupling, the specific steps include:

[0057] Step 1: Obtain meteorological parameters and environmental parameters of the street to be evaluated, wherein the meteorological parameters are atmospheric temperature, humidity, wind speed and surface temperature, and the environmental parameters are radiation data and green coverage rate;

[0058] Get meteorological parameters and environmental parameters, specifically:

[0059] Use sensors to collect the atmospheric temperature, humidity, wind speed, surface temperature, direct radiation and scattered radiation of the street to be evaluated. The temperature is recorded as T, the humidity is recorded as S, the wind speed is recorded as V, the surface temperature is recorded as U, and the direct radiation is recorded as I. direct , scattered radiation is recorded as I diffuse ;

[0060] The atmospheric temperature is the temperature at a height of 2-10 meters above the ground;

[0061] The radiation data is the total solar radiation, which is calculated according to the following formula:

[0062] I total =I direct +I diffuse

[0063] Among them, I total is the total solar radiation, I direct is direct radiation, i.e. direct light from the sun, I diffuse It is scattered radiation, that is, radiation scattered by clouds, gas and particles in the atmosphere;

[0064] Collect the total area of ​​the street to be evaluated and the area of ​​the green area, and calculate the green coverage rate:

[0065]

[0066] Among them, G is the green coverage rate, A green is the area of ​​the street greening area to be evaluated. The greening area refers to the area covered by plants. total The total area refers to the total area of ​​the street to be assessed, including green and non-green areas.

[0067] As another embodiment, the city's central business district, historical and cultural protection areas, parks, residential areas, schools and educational institutions, and transportation hubs in the street to be evaluated are taken as representative locations, the meteorological parameters and environmental parameters of each representative location are obtained, and the average value is taken as the meteorological parameters and environmental parameters of the street to be evaluated. By collecting data at multiple points and calculating the average value, the actual situation of the street to be evaluated can be comprehensively reflected and accidental errors can be reduced.

[0068] The advantage of step 1 is that it can provide a comprehensive data basis for thermal comfort assessment by systematically collecting meteorological and environmental parameters of representative locations. By considering multiple key factors such as atmospheric temperature, humidity, wind speed, surface temperature, radiation data, and green coverage, this step can fully reflect the thermal environment characteristics of the street space. Compared with the one-sidedness and limitations of existing technologies, this multi-dimensional data collection method can more accurately reveal the changing laws of thermal comfort under different environmental conditions, thereby providing a reliable basis for subsequent analysis and evaluation.

[0069] Compared with the prior art, the beneficial effect of step 1 is mainly reflected in the comprehensiveness and representativeness of its data. Through comprehensive data collection for specific streets, the specific impact of different environmental factors on thermal comfort can be effectively identified and quantified, thereby providing scientific and effective decision-making support for urban planning and management. This systematic data analysis method helps to formulate targeted improvement measures, optimize the urban microclimate environment, and improve the quality of life of residents. In this patent scheme, the use of this step can play an important role in promoting the overall scheme. By establishing a scientific and comprehensive data foundation, step 1 provides the necessary parameter support for the subsequent UTCI derivation, the calculation of the heat stress index and the wind chill effect index, thereby ensuring the accuracy and reliability of the comprehensive thermal comfort score. In addition, the implementation of this step can lay a solid foundation for the classification of thermal comfort in street spaces and the formulation of improvement measures, promote the effective operation of the entire evaluation system, and ultimately achieve systematic optimization of the urban thermal environment.

[0070] Step 2: Use RayMan software to derive the universal thermal climate index UTCI, calculate the heat stress index based on the dimensionless UTCI, surface temperature, radiation and green coverage, and calculate the wind chill effect index based on the dimensionless temperature, humidity and wind speed;

[0071] In this embodiment, the formula for calculating the thermal stress index is as follows:

[0072]

[0073] Among them, HSI is the heat stress index, UTCI is the universal thermal climate index, U is the surface temperature, I is total is the total solar radiation, G is the green coverage rate; UTCI is an important indicator for evaluating thermal comfort, and its increase usually indicates a deterioration in the thermal environment, which will lead to an increase in HSI. Since an increase in HSI means that people are facing greater heat stress, an increase in HSI will lead to a decrease in the comprehensive thermal comfort score; an increase in surface temperature U will increase the HSI value, because UTCI and U are averaged in the HSI formula, and an increase in surface temperature will increase heat stress, thereby causing a decrease in the comprehensive thermal comfort score. On the contrary, a decrease in surface temperature will lead to a decrease in HSI, thereby increasing TSV; total solar radiation I total The increase of will also lead to the increase of HSI. The increase of radiation intensity will increase thermal stress, resulting in a decrease in the comprehensive thermal comfort score; the increase of green coverage rate G will reduce the value of HSI. Green coverage helps to improve the thermal environment, reduce thermal stress, and thus improve the comprehensive thermal comfort score. This shows that UTCI, U, I total It is positively correlated with HSI, and G is negatively correlated with HSI.

[0074] The formula for calculating the wind chill effect index is as follows:

[0075] WCI=13.12+0.6215*T-11.37*V 0.16 +0.3965*T*V 0.16 -k*S

[0076] Among them, WCI is the wind chill effect index, T is the atmospheric temperature, V is the wind speed, S is the humidity, and k is the humidity correction factor, which is used to quantify the impact of humidity on the perceived temperature. It reflects the degree of correction of the wind chill effect on the overall comfort under certain humidity conditions. The specific value range of k is usually between 0.1 and 1.0. In an environment with low humidity, the value range of k is [0.1, 0.3], which means that the effect of humidity on the perceived temperature is small and the wind chill effect is strong; in a warm and humid environment, the value range of k is (0.3, 0.6], at which time the effect of humidity on the perceived temperature begins to be significant; when it is a high humidity environment, the value range of k is (0.6, 1], which means that humidity significantly reduces the effectiveness of the wind chill effect.

[0077] In the formula, the constant term 13.12 is the value introduced for the base perceived temperature, which is intended to provide a starting point for the calculation. This is an empirical setting based on historical data and human physiological responses; the term 0.6215*T, the atmospheric temperature, represents a positive impact on the perceived temperature. As the temperature rises, the temperature felt by the human body will also increase accordingly, so a positive coefficient of -11.37*V is added. 0.16 The term represents the negative effect of wind speed on the perceived temperature. As the wind speed increases, the wind will accelerate the heat away from the human body surface, resulting in a decrease in the perceived temperature. Therefore, this term is a negative value, and the wind speed appears in the form of 0.16, reflecting the nonlinear relationship between the effect of wind speed on the perceived temperature, that is, the effect is relatively small when the wind speed is low, and the effect is significant when the wind speed is high. 0.3965*T*V 0.16 The term considers the combined effect of temperature and wind speed. The acceleration effect of wind may be different at high and low temperatures, so the interaction between temperature and wind speed is introduced. It shows that the effect of wind speed will be more significant in lower temperature environments.

[0078] When the wind speed V increases, it can effectively reduce the perceived temperature and make people feel cooler, so the WCI will increase. The increase in humidity S usually reduces the wind cooling effect, because a high humidity environment will make the human body feel hotter, thus reducing the WCI value. Conversely, a decrease in humidity will increase the WCI and enhance the wind cooling effect.

[0079] The advantage of step 2 is that the RayMan software is used to derive the general thermal climate index, and the heat stress index and wind chill effect index are calculated based on dimensionless meteorological and environmental parameters. This process can quantify various factors affecting thermal comfort, provide a systematic evaluation framework, and ensure the scientificity and accuracy of thermal comfort evaluation. This method can not only objectively reflect the changes in the thermal environment of the street space, but also effectively reveal the interaction between different environmental factors, thereby providing more comprehensive data support for subsequent analysis.

[0080] Compared with the prior art, the beneficial effect of step 2 is that it can comprehensively consider multiple indicators that affect thermal comfort, rather than relying on a single factor. This multi-index coupled evaluation method overcomes the limitations of traditional evaluation methods, making the evaluation of thermal comfort more comprehensive and accurate. By calculating the UTCI, heat stress index and wind chill effect index, the impact of different environmental factors on thermal comfort can be analyzed and understood more deeply, providing urban managers with more targeted improvement plans, thereby effectively addressing urban thermal environment problems. In this patent solution, the use of this step can play a key role in promoting the overall solution. Step 2 not only provides the necessary input data for the calculation of the comprehensive thermal comfort score, but also lays the foundation for subsequent correlation analysis and thermal stress level classification. Through precise index calculation, the solution can achieve in-depth analysis of the thermal environment of the street space, ensure the scientificity and practicality of the evaluation results, and then promote the formulation of practical improvement measures to improve the thermal comfort of the urban environment.

[0081] Step 3: Use the Pearson correlation coefficient method to analyze the correlation between UTCI, heat stress index, wind chill effect index and comprehensive thermal comfort score, and combine the correlation analysis results to calculate the comprehensive thermal comfort score;

[0082] In this embodiment, the Pearson correlation coefficient method is used to analyze the correlation between UTCI, heat stress index, wind chill effect index and comprehensive thermal comfort score, and the specific logic is as follows:

[0083] The Pearson correlation coefficient is a statistic that measures the strength and direction of the linear relationship between two variables. Its value range is: [-1, +1]. The specific steps are as follows:

[0084] Collect a set of historical key parameters of the streets and the corresponding comprehensive thermal comfort scores. The more comfortable the street environment is, the higher the corresponding comprehensive thermal comfort score is. The key parameters are heat stress index, wind chill effect index and UTCI.

[0085] The method for obtaining the comprehensive thermal adaptability score is as follows: according to the following four intervals and their values, a comprehensive comfort score table is created, and the expert group is asked to score the historical heat stress index, wind chill effect index and UTCI combination to obtain the comprehensive comfort score under each historical heat stress index, wind chill effect index and UTCI combination;

[0086] Furthermore, through questionnaire surveys, passers-by were also allowed to participate in the scoring, and the weights of the expert group's scores and the passer-by's scores were set. Since experts are more able to score accurately than passers-by, the weight of the expert group's scores is greater than the weight of the passer-by's scores. For example, the weight of the expert group's scores was set to 0.7, and the weight of the passer-by's scores was set to 0.3. Through the weighted summation method, the expert group's scores and the passer-by's scores under the same combination of heat stress index, wind chill effect index and UTCI were weighted and summed to obtain the final comprehensive thermal adaptability score under the combination of historical heat stress index, wind chill effect index and UTCI.

[0087] The Pearson correlation coefficient is calculated according to the following formula:

[0088]

[0089] Among them, r is the Pearson correlation coefficient, X i represents the key parameter of the i-th sample, that is, the heat stress index or wind chill effect index, or UTCI in the i-th sample, which is used to perform correlation analysis with the corresponding comprehensive thermal comfort score, Y i represents the comprehensive thermal comfort score of the i-th sample, is the mean value of the key parameter, is the mean of the comprehensive thermal comfort score;

[0090] The calculated Pearson correlation coefficient value r is used to analyze the relationship between each key parameter and the comprehensive thermal comfort score:

[0091] When r>0, it indicates that there is a positive correlation between the parameter and the comprehensive thermal comfort score, which means that when the parameter increases, the comprehensive thermal comfort score also increases;

[0092] When r < 0, it indicates that there is a negative correlation between the parameter and the comprehensive thermal comfort score, which means that when the parameter increases, the comprehensive thermal comfort score decreases instead;

[0093] When r = 0, there is no correlation, which means that there is no linear relationship between this parameter and the comprehensive thermal comfort score;

[0094] Among them, the closer |r| is to 1, the stronger the correlation is.

[0095] Combined with the analysis results of the correlation, the comprehensive thermal comfort score is calculated, and the specific logic is as follows:

[0096] TSV=ω1*UTCI+ω2*HSI+ω3*WCI

[0097] Among them, TSV is the comprehensive thermal comfort score, UTCI is the universal thermal climate index, HSI is the heat stress index, WCI is the wind chill effect index, v1, ω2, ω3 are the proportional coefficients set according to the correlation analysis results, the Pearson correlation coefficient between the universal thermal climate index and the comprehensive thermal comfort score is named r1, the Pearson correlation coefficient between the heat stress index and the comprehensive thermal comfort score is named r2, and the Pearson correlation coefficient between the wind chill effect index and the comprehensive thermal comfort score is named r3. With the constraint condition that the sum of the absolute values ​​after scaling is equal to 1, r1, r2, and r3 are scaled in the same proportion, and the scaled r1, r2, and r3 are respectively used as ω1, ω2, and ω3. UTCI is an index that comprehensively considers multiple meteorological factors such as temperature, humidity, wind speed, and radiation, and reflects the physiological response of the human body to the thermal environment. An increase in UTCI usually indicates a deterioration of the thermal environment, which causes a decrease in the comprehensive thermal comfort score. Conversely, if UTCI decreases, it means that the thermal environment has improved, and the corresponding TSV will increase. The heat stress index mainly reflects the physiological heat stress caused by high temperature or other environmental factors. An increase in HSI generally indicates that people may face greater heat stress under such environmental conditions, so the comprehensive thermal comfort score will decrease. If the HSI decreases, it means that the heat stress is reduced and the TSV increases accordingly. The wind chill effect index is used to evaluate the impact of wind speed on thermal comfort. An increase in WCI generally indicates a stronger wind chill effect, which helps to reduce the perceived temperature and thus improve the thermal comfort score. Correspondingly, a decrease in WCI means that the wind chill effect is weakened, resulting in a decrease in the comprehensive thermal comfort score.

[0098] The advantage of step 3 is that it systematically analyzes the correlation between UTCI, heat stress index, wind chill effect index and comprehensive thermal comfort score by using the Pearson correlation coefficient method. This statistical analysis method can quantitatively evaluate the impact of each index on thermal comfort, thereby revealing the intrinsic connection between different environmental factors. The application of this method enhances the scientific nature of the evaluation, so that the evaluation results not only have quantitative support, but also provide a basis for subsequent improvement measures.

[0099] Compared with the prior art, the beneficial effect of step 3 is reflected in its in-depth exploration of the relationship between multidimensional indicators. Traditional evaluation methods often lack systematic correlation analysis, resulting in the impact of each indicator being viewed in isolation. Through the analysis of the Pearson correlation coefficient, step 3 can identify the most significant influencing factors, providing more accurate guidance for the evaluation and management of the urban thermal environment, thereby improving the effectiveness of urban planning and decision-making. In this patent scheme, the use of this step can play an important role in promoting the overall scheme. By establishing a clear relationship between the comprehensive thermal comfort score and each related index, step 3 provides a solid basis for the subsequent classification of thermal stress levels and the formulation of targeted improvement measures. This systematic analysis not only helps to optimize the effectiveness of the improvement plan, but also ensures the scientificity and operability of the overall plan in practical applications, thereby more effectively promoting the improvement of the urban thermal environment.

[0100] Step 4: Divide the street space into multiple heat stress levels based on the comprehensive thermal comfort score, and formulate corresponding improvement measures for each level;

[0101] In this embodiment, the comprehensive thermal comfort score is compared with a preset threshold value to divide the street space into multiple thermal stress levels:

[0102] When TSV ≥ 0.8, it is classified as Level 1 (comfort zone), maintaining the existing green cover and water bodies, and regularly inspecting and maintaining green areas;

[0103] When 0.6≤TSV<0.8, it is classified as Level 2 (mild heat stress area), and trees and vegetation are added, road material selection is improved, and spray cooling facilities are added;

[0104] When 0.4≤TSV<0.6, it is classified as Level 3 (moderate heat stress area), and more greening projects are implemented, water area is increased, and building layout is optimized to reduce the heat island effect;

[0105] When TSV<0.4, it is classified as Level 4 (severe heat stress area), and an urban thermal environment transformation plan is formulated to increase green coverage, use reflective materials and green roof technology, and add cooling facilities.

[0106] The advantage of step 4 is that it divides the street space into different thermal comfort levels by comprehensively analyzing the calculation results of various thermal comfort-related indexes. This classification method can not only intuitively display the thermal environment characteristics of different areas, but also provide clear goals and strategies for subsequent urban planning and design. The implementation of this step helps to better identify areas that need to be improved, thereby providing a scientific basis for improving overall thermal comfort.

[0107] Compared with the existing technology, the beneficial effect of step 4 is that it can present complex thermal environment data in an easy-to-understand way, so that urban managers and relevant stakeholders can quickly obtain key information. Traditional technology often only provides a single environmental data, while step 4 takes into account the influence of multiple factors through the division of thermal comfort levels, enhances the practicality and operability of the evaluation results, and thus provides a more reasonable reference for policy formulation and resource allocation. In this patent scheme, the use of this step can play a key role in promoting the overall scheme. Through the clear division of thermal comfort levels, step 4 not only provides priority sorting for subsequent improvement measures, but also effectively guides the direction of urban planning and design, thereby improving the thermal comfort of urban space. This systematic grading method will help to achieve more accurate thermal environment management and lay a good foundation for the sustainable development of cities.

[0108] See also Figure 2 , a street space thermal comfort evaluation system based on multi-index coupling, including:

[0109] The parameter acquisition module is used to obtain the meteorological parameters and environmental parameters of the street to be evaluated, wherein the meteorological parameters are atmospheric temperature, humidity, wind speed and surface temperature, and the environmental parameters are radiation data and green coverage rate; the data processing module is used to derive the universal thermal climate index UTCI using RayMan software, calculate the thermal stress index according to the dimensionless processed UTCI, surface temperature, radiation and green coverage rate, and calculate the wind cooling effect index according to the dimensionless processed temperature, humidity and wind speed;

[0110] The correlation analysis module is used to analyze the correlation between UTCI, heat stress index, wind chill effect index and comprehensive thermal comfort score respectively using the Pearson correlation coefficient method, and calculate the comprehensive thermal comfort score based on the correlation analysis results;

[0111] The comprehensive analysis module is used to divide the street space into multiple thermal stress levels according to the comprehensive thermal comfort score, and formulate corresponding improvement measures for each level.

[0112] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters in the formula are set by technicians in this field according to actual conditions.

[0113] The above embodiments may be implemented in whole or in part by software, hardware, firmware or any other combination thereof. When implemented by software, the above embodiments may be implemented in whole or in part in the form of a computer program product. Those skilled in the art may appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein may be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed by hardware or software methods depends on the specific application and design constraints of the technical solution.

[0114] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, and may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0115] The above description is only a specific implementation manner of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application.

Claims

1. A street space thermal comfort assessment method based on multi-index coupling, characterized in that: The specific steps include: Step 1: Obtain meteorological parameters and environmental parameters of the street to be evaluated, wherein the meteorological parameters are atmospheric temperature, humidity, wind speed and surface temperature, and the environmental parameters are radiation data and green coverage rate; Step 2: Use RayMan software to derive the universal thermal climate index UTCI, calculate the heat stress index based on the dimensionless UTCI, surface temperature, radiation and green coverage, and calculate the wind chill effect index based on the dimensionless temperature, humidity and wind speed; Step 3: Use the Pearson correlation coefficient method to analyze the correlation between UTCI, heat stress index, wind chill effect index and comprehensive thermal comfort score, and combine the correlation analysis results to calculate the comprehensive thermal comfort score; Step 4: Based on the comprehensive thermal comfort score, divide the street space into multiple heat stress levels and formulate corresponding improvement measures for each level.

2. The street space thermal comfort assessment method based on multi-index coupling according to claim 1 is characterized by: The city’s central business district, historical and cultural protection areas, parks, residential areas, schools and educational institutions, and transportation hubs in the streets to be evaluated are taken as representative locations. The meteorological parameters and environmental parameters of each representative location are obtained, and the average values ​​are taken as the meteorological parameters and environmental parameters of the streets to be evaluated.

3. The street space thermal comfort assessment method based on multi-index coupling according to claim 1 is characterized by: Collect meteorological parameters and environmental parameters, specifically: Use sensors to collect the atmospheric temperature, humidity, wind speed, surface temperature, direct radiation and scattered radiation of the street to be evaluated. The atmospheric temperature is recorded as T, the humidity is recorded as S, the wind speed is recorded as V, the surface temperature is recorded as U, and the direct radiation is recorded as I. direct , scattered radiation is recorded as I diffuse ; The radiation data is the total solar radiation, which is calculated according to the following formula: I total =I direct +i diffuse Among them, i total is the total solar radiation, I direct is direct radiation, that is, direct light from the sun, i diffuse It is scattered radiation, that is, radiation scattered by clouds, gas and particles in the atmosphere; Collect the total area of ​​the street to be evaluated and the area of ​​the green area, and calculate the green coverage rate: Among them, G is the green coverage rate, A is green A is the area of ​​green areas in the street to be evaluated. Green areas refer to areas covered by plants. total The total area refers to the total area of ​​the street to be assessed, including green and non-green areas.

4. The street space thermal comfort assessment method based on multi-index coupling according to claim 3 is characterized by: The formula for calculating the thermal stress index is as follows: Among them, HSI is the heat stress index, UTCI is the universal thermal climate index, U is the surface temperature, I is total is the total solar radiation, G is the green coverage rate; The formula for calculating the wind chill effect index is as follows: WCI=13.12+0.6215*T-11.37*V 0.16 +0.3965*T*V 0.16 -k*S Where WCI is the wind chill index, T is the atmospheric temperature, V is the wind speed, S is the humidity, and k is the humidity correction factor, which is used to adjust the impact of the wind chill effect.

5. The method for evaluating thermal comfort of street space based on multi-index coupling according to claim 4 is characterized by: The Pearson correlation coefficient method was used to analyze the correlation between UTCI, heat stress index, wind chill effect index and comprehensive thermal comfort score. The specific logic is as follows: The Pearson correlation coefficient is a statistic that measures the strength and direction of the linear relationship between two variables. Its value range is: [-1, +1]. The specific steps are as follows: Collect a set of historical key parameters and corresponding comprehensive thermal comfort scores of streets, the key parameters are heat stress index, wind chill effect index and UTCI; The Pearson correlation coefficient is calculated according to the following formula: Among them, r is the Pearson correlation coefficient, X i represents the key parameter of the i-th sample, that is, the heat stress index or wind chill effect index, or UTCI in the i-th sample, which is used to perform correlation analysis with the corresponding comprehensive thermal comfort score, Y i represents the comprehensive thermal comfort score of the i-th sample, is the mean value of the key parameter, is the mean of the comprehensive thermal comfort score; The calculated Pearson correlation coefficient value r is used to analyze the relationship between each key parameter and the comprehensive thermal comfort score: When r>0, it indicates that there is a positive correlation between the parameter and the comprehensive thermal comfort score, which means that when the parameter increases, the comprehensive thermal comfort score also increases; When r < 0, it indicates that there is a negative correlation between the parameter and the comprehensive thermal comfort score, which means that when the parameter increases, the comprehensive thermal comfort score decreases instead; When r = 0, there is no correlation, which means that there is no linear relationship between this parameter and the comprehensive thermal comfort score; Among them, the closer |r| is to 1, the stronger the correlation is.

6. The street space thermal comfort assessment method based on multi-index coupling according to claim 1 is characterized by: Combined with the analysis results of the correlation, the comprehensive thermal comfort score is calculated, and the specific logic is as follows: TSV=ω1*UTCI+ω2*HSI+ω3*WCI Among them, TSV is the comprehensive thermal comfort score, UTCI is the universal thermal climate index, HSI is the heat stress index, WCI is the wind chill effect index, and ω1, ω2, and ω3 are proportional coefficients set according to the correlation analysis results.

7. The street space thermal comfort assessment method based on multi-index coupling according to claim 1 is characterized by: The composite thermal comfort score is compared with preset thresholds to classify street spaces into multiple heat stress levels: When TSV ≥ 0.8, it is classified as Level 1 (comfort zone), maintaining the existing green cover and water bodies, and regularly inspecting and maintaining green areas; When 0.6≤TSV<0.8, it is classified as Level 2 (mild heat stress area), and trees and vegetation are added, road material selection is improved, and spray cooling facilities are added; When 0.4≤TSV<0.6, it is classified as Level 3 (moderate heat stress area), and more greening projects are implemented, water area is increased, and building layout is optimized to reduce the heat island effect; When TSV<0.4, it is classified as Level 4 (severe heat stress area), and an urban thermal environment transformation plan is formulated to increase green coverage, use reflective materials and green roof technology, and add cooling facilities.

8. A street space thermal comfort assessment system based on multi-index coupling, characterized by: The street space thermal comfort evaluation system based on multi-index coupling is used to execute the street space thermal comfort evaluation method based on multi-index coupling according to any one of claims 1 to 7, comprising: The parameter acquisition module is used to obtain the meteorological parameters and environmental parameters of the street to be evaluated, wherein the meteorological parameters are atmospheric temperature, humidity, wind speed and surface temperature, and the environmental parameters are radiation data and green coverage rate; the data processing module is used to derive the universal thermal climate index UTCI using RayMan software, calculate the thermal stress index according to the dimensionless processed UTCI, surface temperature, radiation and green coverage rate, and calculate the wind cooling effect index according to the dimensionless processed temperature, humidity and wind speed; The correlation analysis module is used to analyze the correlation between UTCI, heat stress index, wind chill effect index and comprehensive thermal comfort score respectively using the Pearson correlation coefficient method, and calculate the comprehensive thermal comfort score based on the correlation analysis results; The comprehensive analysis module is used to divide the street space into multiple thermal stress levels according to the comprehensive thermal comfort score, and formulate corresponding improvement measures for each level.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method for evaluating thermal comfort of a street space based on multi-index coupling as described in any one of claims 1 to 7 is implemented.

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