A measurement path planning method for evaluating urban outdoor thermal comfort

Abstract

The present invention discloses a measurement path planning method for evaluating urban outdoor thermal comfort, which selects representative spaces in the area to be measured as measurement point spaces, obtains outdoor thermal environment data of the measurement point spaces; calculates physiological equivalent temperature based on the outdoor thermal environment data; calculates the average value of the physiological equivalent temperature of each measurement point space at different measurement times; calculates the accuracy of the physiological equivalent temperature of each measurement point space at each time; establishes an optimization platform for the accuracy of measurement point space, time, and physiological equivalent temperature; calculates all continuous paths that take into account all times in the optimization platform; and selects a measurement path based on the number of measurement point spaces. The present invention is used to solve the problem of low measurement accuracy of the outdoor thermal environment in the prior art when the number and arrangement of sensors are limited, and to provide a scientific and reasonable path planning means for mobile measurement of the outdoor thermal environment, and to improve the measurement accuracy and efficiency.

Description

Technical Field

[0001] The invention relates to the field of urban thermal environment evaluation, and in particular to a measurement path planning method for evaluating urban outdoor thermal comfort. Background Art

[0002] With the development of global climate change, high temperature heat waves and urban heat island effects are becoming more and more serious, causing great negative impacts on the environment, economy, society and other aspects. In particular, the harm to human health is becoming increasingly serious. High temperature has become one of the most deadly weather-related disasters in many countries. Extreme high temperature will increase morbidity and mortality. Hot weather makes the outdoor thermal environment extremely uncomfortable, increasing the risk of people engaging in outdoor activities and easily causing cardiovascular disease, respiratory disease, mental illness and other diseases. Under the trend of global warming and urbanization, urban heat problems will challenge and threaten more cities more frequently and more strongly. Therefore, it is urgent to help scholars make accurate judgments on the outdoor thermal environment through quantitative evaluation of outdoor thermal comfort, so as to reduce the harm of urban high temperature to human health.

[0003] At present, the quantitative assessment of urban outdoor thermal comfort adopts remote sensing, numerical simulation and ground meteorological observation methods, each of which has different advantages and purposes. Remote sensing includes satellite remote sensing, aerial remote sensing and ground remote sensing, which are usually used to monitor urban and regional surface temperatures. Numerical simulation based on modeling systems such as ENVI-met and WRF has been widely adopted to estimate climate at different scales according to different resolution requirements. Ground meteorological observation includes fixed measurement and mobile measurement, which can measure microclimate parameters such as air temperature, wind speed, relative humidity, solar radiation intensity and radiation temperature within the scope of cities, blocks and streets. More importantly, ground meteorological observation is the result collected at the pedestrian level, which can be directly used to evaluate the quality of outdoor thermal comfort and thermal environment. Ground meteorological observation has been widely used to monitor and evaluate the outdoor thermal environment of cities, blocks, streets, etc.

[0004] However, during the measurement process, the high price of equipment sensors limits the number and layout of equipment. Due to the heterogeneity of urban outdoor spaces, the thermal environment of different space types may vary greatly. In addition, the heat dissipation of air conditioners in summer streets and the air conditioning refrigeration of shopping malls open to the public will also lead to significant changes in the local outdoor thermal environment. If the number and layout of equipment sensors are limited, the measurement accuracy will be reduced in the absence of scientific considerations, thereby underestimating or overestimating the local outdoor thermal environment. This will cause urban decision makers to make incorrect judgments about the risks of the outdoor thermal environment, causing people to engage in outdoor activities without taking adequate mitigation and adaptation measures, which will cause serious harm to their health. Summary of the invention

[0005] The present invention provides a measurement path planning method for evaluating urban outdoor thermal comfort, so as to solve the problem of low measurement accuracy of outdoor thermal environment when the number and arrangement of sensors are limited in the prior art, so as to provide a scientific and reasonable path planning means for mobile measurement of outdoor thermal environment, and improve the measurement accuracy and efficiency.

[0006] The present invention is achieved through the following technical solutions:

[0007] A measurement path planning method for evaluating urban outdoor thermal comfort includes the following steps:

[0008] Select a representative space in the area to be measured as the measuring point space to obtain the outdoor thermal environment data of the measuring point space;

[0009] Calculate physiological equivalent temperature based on outdoor thermal environment data;

[0010] Calculate the average value of the physiological equivalent temperature of each measuring point space at different measuring times;

[0011] Calculate the accuracy of physiological equivalent temperature at each measuring point space at each moment;

[0012] Establish an optimization platform for the accuracy of measurement point space, time, and physiological equivalent temperature;

[0013] All continuous paths at all times are calculated in the optimization platform;

[0014] Select the measurement path based on the number of measurement point spaces.

[0015] In view of the problem that the existing technology has low measurement accuracy of the outdoor thermal environment when the number and arrangement of sensors are limited, the present invention proposes a measurement path planning method for evaluating urban outdoor thermal comfort. The method first selects a representative space in the area to be measured as a measuring point space to obtain the outdoor thermal environment data of each measuring point space. Based on the obtained outdoor thermal environment data, the physiological equivalent temperature PET (Physiological Equivalent Temperature) corresponding to each group of data is calculated, and then the PET value of each measuring point space is averaged to obtain the average PET corresponding to each measuring point space. Then, based on the average PET, the accuracy of the PET value at each moment in all measuring point spaces is calculated.

[0016] Based on the above calculations and preparations, this method continues to establish an optimization platform related to the measurement point space, time, and the above accuracy, and calculates all paths that take into account all times in this optimization platform; for reasonable planning, the continuity of the path must be maintained in this process. Finally, the optimal measurement path can be selected according to the number of measurement point spaces required for actual measurement; this path is used as the mobile path of the mobile observation method in the ground meteorological observation of urban outdoor thermal comfort.

[0017] Compared with the prior art, the present application: (1) solves the problem of low measurement accuracy of the outdoor thermal environment when the number and arrangement of sensors are limited, provides a scientific and reasonable path planning method for mobile measurement of the outdoor thermal environment, fills the gap in the prior art, and provides a scientific and rigorous reference and support for research on heat-related urban environments and urban cooling measures; (2) calculates the physiological equivalent temperature related to the outdoor thermal comfort evaluation through outdoor thermal environment data, and constructs an optimization platform to quickly obtain an accurate measurement path. While ensuring the accuracy of outdoor thermal environment measurement, it significantly improves the accuracy and efficiency of outdoor thermal environment measurement and reduces the risk of danger to people's health caused by incorrect assessment; (3) comprehensively considers the average value of PET at different measuring points at different times, takes the accuracy of each measuring point at different times as the basis, and considers the impact of spatiotemporal heterogeneity on the outdoor thermal environment, which is conducive to obtaining more accurate measurement results.

[0018] Furthermore, the outdoor thermal environment data of the measuring point space is obtained by actual measurement or numerical simulation. If the experimental conditions / equipment are sufficient, the initial outdoor thermal environment data can be obtained by actual measurement, and if the experimental conditions / equipment are relatively insufficient, the data can be obtained by numerical simulation.

[0019] Furthermore, the outdoor thermal environment data includes: air temperature, relative humidity, globe temperature, and wind speed.

[0020] Further, the method for calculating the physiological equivalent temperature includes:

[0021] Calculate the average radiation temperature of each measuring point space at different measuring times;

[0022] Based on the geographical location, air temperature, mean radiation temperature, relative humidity, wind speed, and human physiological properties of the measuring point space, the physiological equivalent temperature of each measuring point space is calculated.

[0023] The physiological equivalent temperature (PET) is an outdoor thermal comfort evaluation index based on the Munich human heat balance model, which comprehensively considers the impact of the human body's own physiological factors and meteorological factors on thermal comfort. It can be understood as the physiological equilibrium temperature under a given environment, and its value is equal to the temperature corresponding to the outdoor thermal state in a typical indoor environment. This application uses PET as the main evaluation parameter, which can meet the accurate evaluation of the comprehensive level of the outdoor environment under the complex shading conditions of a large number of buildings in the city. The specific calculation process and formula of the physiological equivalent temperature PET are prior art in this field. For example, the calculation method is clearly recorded in "Man and Thermal Environment" published by Science Press, which will not be repeated here.

[0024] Furthermore, the average radiation temperature is calculated by the following formula:

[0025]

[0026] Where MRT is the mean radiation temperature, T g is the black ball temperature, v is the wind speed, ε is the black ball emissivity, D is the black ball diameter, T a is the air temperature.

[0027] Furthermore, the accuracy of the physiological equivalent temperature is calculated by the following formula:

[0028]

[0029] Where AI is the accuracy of the physiological equivalent temperature of a certain measuring point space at a certain moment, λ is the physiological equivalent temperature value of the measuring point space at that moment, and μ is the average value of the physiological equivalent temperature of the measuring point space.

[0030] This solution realizes a measurement process that takes into account both temporal and spatial heterogeneity and accuracy, effectively avoiding the influence of uneven thermal environment caused by individual measuring point spaces (nearby cold and heat sources) or special moments (sudden exposure to sunlight), which leads to inaccurate measurements.

[0031] Further, the method of calculating all continuous paths taking into account all the time periods includes:

[0032] On the time vector, divide the data into several time periods;

[0033] Randomly assign the time corresponding to each time period;

[0034] The corresponding measuring point space at each moment is randomly selected to establish the path, discontinuous paths are eliminated, and continuous paths are retained.

[0035] This scheme combines the spatial classification method, comprehensively considers the impact of temporal and spatial heterogeneity on the outdoor thermal environment, and can accurately judge the measurement accuracy, thereby finding a highly accurate moving path for the mobile observation method of urban thermal comfort. Compared with the existing technology, it overcomes the interference of temporal and spatial heterogeneity.

[0036] Furthermore, the method of selecting a measurement path based on the number of measurement point spaces includes:

[0037] Determine the initial number of measuring point space;

[0038] The initial number of measuring point spaces and the accuracy of the physiological equivalent temperature of each measuring point space at different measuring times are input into the optimization platform to obtain the optimization path;

[0039] Determine whether the optimized path meets the accuracy requirements: if so, output the path; if not, increase the number of measurement point spaces and input it into the optimization platform again until the optimized path meets the accuracy requirements.

[0040] This solution further optimizes the measurement path based on the optimization platform, where the initial number of measurement point spaces can be set or specified manually to meet the minimum measurement requirements as the basic condition. The accuracy of the physiological equivalent temperature of each measurement point space at different measurement times is obtained by the above calculation process.

[0041] After the initial number of measuring point spaces is input into the optimization platform, the platform calculates the optimization path that meets the number requirements, and then determines whether the path meets the accuracy requirements. The accuracy requirements here refer to the accuracy of the physiological equivalent temperature calculated above. The specific accuracy requirements can be manually set thresholds or automatically determined by the software.

[0042] Furthermore, the Thermal Comfort Indices calculator of Ladybug software was used to calculate the physiological equivalent temperature.

[0043] Furthermore, the optimization platform was established using the Wallacei plug-in of the parametric software Rhino-Grasshopper.

[0044] Compared with the prior art, the present invention has the following advantages and beneficial effects:

[0045] 1. The present invention provides a measurement path planning method for evaluating urban outdoor thermal comfort, which solves the problem of low measurement accuracy of outdoor thermal environment when the number and arrangement of sensors are limited, provides a scientific and reasonable path planning method for mobile measurement of outdoor thermal environment, fills the gap in the prior art, and provides a scientific and rigorous basis for research on heat-related urban environment and urban cooling measures.

[0046] 2. The present invention provides a measurement path planning method for evaluating urban outdoor thermal comfort. The physiological equivalent temperature related to the outdoor thermal comfort evaluation is calculated through outdoor thermal environment data, and an optimization platform is constructed to finally quickly obtain an accurate measurement path. While ensuring the accuracy of outdoor thermal environment measurement, the accuracy and efficiency of outdoor thermal environment measurement are significantly improved, and the risk of danger to people's health due to incorrect evaluation is reduced.

[0047] 3. The present invention provides a measurement path planning method for evaluating urban outdoor thermal comfort, which comprehensively considers the average values ​​of PET at different measuring points at different times, takes the accuracy of each measuring point at different times as the basis, and considers the impact of spatiotemporal heterogeneity on the outdoor thermal environment, which is conducive to obtaining more accurate measurement results.

[0048] 4. The present invention provides a measurement path planning method for evaluating urban outdoor thermal comfort, which introduces a parameterized platform into the field of street thermal environment measurement, visualizes the path finally obtained by the meteorological mobile observation method, and improves the display effect. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] The drawings described herein are used to provide a further understanding of the embodiments of the present invention, constitute a part of this application, and do not constitute a limitation of the embodiments of the present invention. In the drawings:

[0050] Figure 1 It is a schematic diagram of the steps of a specific embodiment of the present invention;

[0051] Figure 2 It is a schematic diagram of a flow chart of a specific embodiment of the present invention;

[0052] Figure 3 It is a schematic diagram of the platform optimization result in a specific embodiment of the present invention;

[0053] Figure 4 It is a schematic diagram of the path obtained in a specific embodiment of the present invention. DETAILED DESCRIPTION

[0054] In order to make the objects, technical solutions and advantages of the present invention clearer, the present invention is further described in detail below in conjunction with the examples and drawings. The schematic embodiments of the present invention and their description are only used to explain the present invention and are not intended to limit the present invention. In the description of the present application, it should be understood that the orientation or positional relationship indicated by the terms "front", "rear", "left", "right", "up", "down", "vertical", "horizontal", "high", "low", "inside", "outside", etc. is based on the orientation or positional relationship shown in the accompanying drawings, and is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the scope of protection of the present application.

[0055] Embodiment 1:

[0056] like Figure 1 A measurement path planning method for evaluating urban outdoor thermal comfort is shown, comprising the following steps:

[0057] S1. Select a representative space in the area to be measured as the measuring point space to obtain the outdoor thermal environment data of the measuring point space.

[0058] The representative space needs to consider both the universal / general spatial locations and the special / abnormal spatial locations in the area to be tested.

[0059] The outdoor thermal environment data can be obtained through actual measurement and / or numerical simulation.

[0060] Outdoor thermal environment data include: air temperature, relative humidity, black globe temperature, and wind speed.

[0061] S2. Calculate the physiological equivalent temperature based on outdoor thermal environment data:

[0062] Calculate the average radiation temperature MRT of each measuring point space at different measuring times:

[0063]

[0064] Where, T g is the black ball temperature, v is the wind speed, ε is the black ball emissivity, D is the black ball diameter, T a is the air temperature.

[0065] Based on the geographical location, air temperature, mean radiation temperature, relative humidity, wind speed, and human physiological properties of the measuring point space, the physiological equivalent temperature of each measuring point space is calculated.

[0066] S3, calculating the average value of the physiological equivalent temperature of each measuring point space at different measuring times;

[0067] S4, calculating the accuracy AI of the physiological equivalent temperature of each measuring point space at each moment;

[0068]

[0069] Where AI is the accuracy of the physiological equivalent temperature of a certain measuring point space at a certain moment, λ is the physiological equivalent temperature value of the measuring point space at that moment, and μ is the average value of the physiological equivalent temperature of the measuring point space.

[0070] S5. Establish an optimization platform for the accuracy of measurement point space, time, and physiological equivalent temperature;

[0071] S6. Calculate all continuous paths at all times in the optimization platform:

[0072] On the time vector, divide the data into several time periods;

[0073] Randomly assign the time corresponding to each time period;

[0074] The corresponding measuring point space at each moment is randomly selected to establish the path, discontinuous paths are eliminated, and continuous paths are retained.

[0075] S7. Select the measurement path based on the number of measurement point spaces:

[0076] Determine the initial number of measuring point space;

[0077] The initial number of measuring point spaces and the accuracy of the physiological equivalent temperature of each measuring point space at different measuring times are input into the optimization platform to obtain the optimization path;

[0078] Determine whether the optimized path meets the accuracy requirements: if so, output the path; if not, increase the number of measurement point spaces and input it into the optimization platform again until the optimized path meets the accuracy requirements.

[0079] Embodiment 2:

[0080] like Figure 2 The measurement path planning method for evaluating urban outdoor thermal comfort is shown in the embodiment. This method is explained by taking the street thermal environment measurement of JX slope in Chongqing as an example.

[0081] Step 1: Data Acquisition

[0082] Select representative spaces in the site as measurement points to measure the outdoor thermal environment, including air temperature (T a ), relative humidity (Rh), globe temperature (T g ), wind speed (v), time interval for data collection (determined according to the point change time).

[0083] In this embodiment, six measuring points A to G are set on the JX slope. The following table shows part of the data collected at the B measuring point from 8:00 to 19:30 at half-hour intervals.

[0084] Table 1 Partial measurement data of point B

[0085]

[0086] Step 2: Analysis and calculation

[0087] (1) The “Calculate Mean Radiant Temperature MRT” battery pack is constructed using the Rhino&Grasshopper platform. The calculation formula is as follows:

[0088]

[0089] Where MRT is the mean radiation temperature, T g is the black ball temperature, v is the wind speed, ε is the black ball emissivity, D is the black ball diameter, T a is the air temperature.

[0090] (2) Use Ladybug's Thermal Comfort Indices to build a "calculated PET" battery pack, connect the required parameters (geographic location, air temperature, radiant temperature, relative humidity, wind speed, and human physiological attributes) to the battery pack, and output the PET value. The following table shows some PET values ​​at measurement point B:

[0091] Table 2 Some PET values ​​at point B

[0092]

[0093] (3) Calculate the average value of PET at different times in the measurement point space A~G respectively. Taking time 1 as an example, the calculation formula can be expressed as:

[0094]

[0095] The calculation formula for other moments is the same as above.

[0096] Step 3: Determine the value

[0097] Calculate the accuracy AI of PET at different measurement points at each time:

[0098]

[0099] AI is the accuracy of the physiological equivalent temperature of a certain measuring point space at a certain moment; λ is the physiological equivalent temperature value of the measuring point space at that moment, in (°C); μ is the average value of the physiological equivalent temperature of the measuring point space, in (°C).

[0100] The calculation results of this embodiment are as follows:

[0101] Table 3 PET accuracy at each measuring point at different times

[0102] 8:00 8:30 9:00 9:30 10:00 10:30 11:00 11:30 12:00 12:30 13:00 13:30 14:00 14:30 15:00 15:30 16:00 16:30 17:00 17:30 18:00 18:30 19:00 19:30 A 0.98 0.97 0.96 0.93 0.86 0.81 0.80 0.77 0.77 0.76 0.77 0.82 0.78 0.79 0.82 0.82 0.85 0.84 0.84 0.87 0.90 0.90 0.93 0.92 B 1.00 0.98 0.97 0.94 0.87 0.82 0.82 0.79 0.79 0.94 0.91 0.92 0.94 0.92 0.87 0.87 0.90 0.89 0.92 0.94 0.93 0.94 0.95 0.96 C 0.99 0.98 0.98 0.96 0.92 0.88 0.89 0.89 0.93 0.88 0.84 0.84 0.86 0.87 0.90 0.89 0.96 0.95 0.98 0.99 0.96 0.97 0.96 0.95 D 0.99 0.97 0.94 0.94 0.89 0.65 0.66 0.62 0.69 0.64 0.74 0.74 0.70 0.79 0.76 0.76 0.96 0.98 0.98 0.95 0.96 0.97 0.96 0.96 E 0.99 0.97 0.97 1.00 0.97 0.94 0.89 0.88 0.89 0.86 0.85 0.82 0.87 0.86 0.91 0.91 0.97 0.98 0.98 0.98 0.99 0.99 1.00 1.00 F 0.99 0.99 0.99 0.89 0.73 0.80 0.73 0.72 0.70 0.80 0.81 0.82 0.88 0.81 0.73 0.73 0.72 0.67 0.74 0.89 0.92 0.92 0.96 0.98

[0103] Step 4: Build the platform

[0104] The measurement points, time and the corresponding PET accuracy were established in the optimization platform (Rhino & Grasshopper platform Wallacei), and the corresponding values ​​were input into the platform.

[0105] Step 5: Determine the continuity of the path

[0106] The platform automatically filters out the battery group of all paths that are taken into account at all times and obtains the results. The specific steps are as follows:

[0107] (1) Using the “Random Reduce” battery in the optimization platform, the data on the time vector is divided into m segments;

[0108] (2) Also using the “Random Reduce” battery, randomly assign the time corresponding to each period of time;

[0109] (3) Use the “Random” and “Random Reduce” batteries to randomly select the corresponding measurement points at that moment to ensure the continuity of the path.

[0110] Step 6: After determining the number of measurement points, select the path with the best accuracy

[0111] For mobile measurement, the number of measuring devices is 1. The number of initial measuring points set in this embodiment is 2. The number of measuring points is input into the platform and the path optimization calculation is performed. After obtaining the optimized data, check whether the accuracy meets the requirements. If not, increase the number of measuring points appropriately and perform the optimization calculation again until a satisfactory accuracy is obtained. Finally, the path is drawn in combination with the visualized battery pack to obtain a measurement path with satisfactory accuracy.

[0112] Preferably, for situations where the accuracy is not met, the number of measurement points can be increased one by one for trial.

[0113] The platform optimization results in this embodiment are as follows Figure 3 As shown, after expanding and beautifying the scheme, we can get the following Figure 4 The path diagram shown in the figure can be used as a basis for mobile observation of the thermal environment of the site.

[0114] The specific implementation methods described above further illustrate the objectives, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above description is only a specific implementation method of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

[0115] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In addition, the term "connected" used in this article can be directly connected or indirectly connected via other components without special explanation.

Claims

1. A measurement path planning method for evaluating urban outdoor thermal comfort, characterized in that: The following steps are involved: Select a representative space in the area to be measured as the measuring point space to obtain the outdoor thermal environment data of the measuring point space; The outdoor thermal environment data include: air temperature, relative humidity, black globe temperature, wind speed; Calculate the physiological equivalent temperature based on the outdoor thermal environment data; the method for calculating the physiological equivalent temperature includes: calculating the average radiation temperature of each measuring point space at different measuring times; calculating the physiological equivalent temperature of each measuring point space based on the geographical location of the measuring point space, air temperature, average radiation temperature, relative humidity, wind speed, and human physiological attributes; Calculate the average value of the physiological equivalent temperature of each measuring point space at different measuring times; Calculate the accuracy of the physiological equivalent temperature at each measuring point space at each time; the accuracy of the physiological equivalent temperature is calculated by the following formula: Wherein, AI is the accuracy of the physiological equivalent temperature of a certain measuring point space at a certain moment, λ is the physiological equivalent temperature value of the measuring point space at that moment, and μ is the average value of the physiological equivalent temperature of the measuring point space; Establish an optimization platform for the accuracy of measurement point space, time, and physiological equivalent temperature; All continuous paths that take into account all moments are calculated in the optimization platform; the method for calculating all continuous paths that take into account all moments includes: dividing the data into several time periods on the time vector; randomly assigning the moment corresponding to each time period; randomly selecting the measurement point space corresponding to each moment to establish a path, eliminating discontinuous paths, and retaining continuous paths; A measurement path is selected based on the number of measurement point spaces; the method for selecting a measurement path based on the number of measurement point spaces includes: determining the initial number of measurement point spaces; inputting the initial number of measurement point spaces and the accuracy of the physiological equivalent temperature of each measurement point space at different measurement times into an optimization platform to obtain an optimized path; judging whether the optimized path meets the accuracy requirements: if so, outputting the path; if not, increasing the number of measurement point spaces and inputting it into the optimization platform again until the optimized path meets the accuracy requirements.

2. A measurement path planning method for evaluating urban outdoor thermal comfort according to claim 1, characterized in that: The outdoor thermal environment data of the measuring point space is obtained by actual measurement or numerical simulation.

3. A measurement path planning method for evaluating urban outdoor thermal comfort according to claim 1, characterized in that: The average radiation temperature is calculated by the following formula: Where MRT is the mean radiation temperature, T g is the black ball temperature, v is the wind speed, ε is the black ball emissivity, D is the black ball diameter, T a is the air temperature.

4. A measurement path planning method for evaluating urban outdoor thermal comfort according to claim 1, characterized in that: Use the Thermal Comfort Indices calculator in Ladybug software to calculate physiological equivalent temperature.

5. A measurement path planning method for evaluating urban outdoor thermal comfort according to claim 1, characterized in that: The optimization platform was established using the Wallacei plug-in of the parametric software Rhino-Grasshopper.

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