Method and device for predicting urban outdoor thermal comfort, terminal equipment and medium

Abstract

The application is suitable for the technical field of urban design and building environment, and provides a prediction method and device for urban outdoor thermal comfort, a terminal device and a medium. The prediction method divides the hemisphere sky corresponding to a to-be-measured point into multiple sky elements, then scans the multiple sky elements by using a full-sky scanner, obtains a sky visibility factor of the to-be-measured point based on the measured data of the full-sky scanner, collects environmental data in a preset area range containing the to-be-measured point, obtains spatial index data of the to-be-measured point according to the environmental data, obtains a thermal comfort evaluation index of the to-be-measured point according to the sky visibility factor and the spatial index, and finally predicts the thermal comfort of the to-be-measured point according to the thermal comfort evaluation index. The application can improve the accuracy of thermal comfort prediction.

Description

Technical Field

[0001] This application belongs to the field of urban design and built environment technology, and in particular relates to methods, devices, terminal equipment and media for predicting urban outdoor thermal comfort. Background Technology

[0002] With social development, the process of urbanization is accelerating, and thermal comfort is an influencing factor that cannot be ignored in the process of urbanization. It affects the lives of residents and is an important reference in the planning and design of urban renewal.

[0003] Current methods for predicting thermal comfort primarily rely on social questionnaires to collect residents' subjective feelings about thermal comfort, and then use this information to make predictions. These methods are extremely complex and require significant human, material, and financial resources. In addition, some researchers obtain meteorological data by setting up weather stations and then analyze and infer predicted thermal comfort values ​​based on this data. This method is highly dependent on hardware, requires a large number of weather stations, and has relatively low accuracy in predicting thermal comfort levels. Summary of the Invention

[0004] This application provides a method, device, terminal equipment, and medium for predicting urban outdoor thermal comfort, which can solve the problem of low accuracy in current thermal comfort prediction methods.

[0005] In a first aspect, this application provides a method for predicting urban outdoor thermal comfort, including:

[0006] The hemispherical sky corresponding to the point to be measured is divided into multiple sky elements; where the center of the hemispherical sky is the point to be measured, and the radius of the hemispherical sky is a pre-set value.

[0007] Multiple sky elements are scanned using an all-sky scanner, and the sky visibility factor of the measured point is obtained based on the measured data from the all-sky scanner.

[0008] Collect environmental data within a preset area, including the measurement point, and obtain spatial index data for the measurement point based on the environmental data; spatial indexes include building area ratio, building height deviation, wall area ratio, building density, green space volume ratio, and hard paving area ratio.

[0009] Based on sky visibility factors and spatial indicators, thermal comfort evaluation indices are obtained for the test points. Thermal comfort evaluation indices include physiological equivalent temperature indices, predicted average voting indices, and general thermal climate indices.

[0010] Based on thermal comfort evaluation indicators, predict the thermal comfort level at the test point.

[0011] Optionally, the all-sky scanner measurement data includes the number of illuminated sky cells (LK) and the number of unilluminated sky cells (NLK);

[0012] Optionally, an all-sky scanner is used to scan multiple sky elements, and based on the measured data from the all-sky scanner, the sky visibility factor of the point to be measured is obtained, including:

[0013] Through calculation formula Obtain the sky visibility factor (SVF).

[0014] Optional environmental data include building footprint, number of floors, building height, total wall area, number of buildings, vegetation cover area, and hard paving area.

[0015] Collect environmental data within a preset area, including the measurement point, and obtain spatial index data for the measurement point based on the environmental data, including:

[0016] Through calculation formula The building area ratio (FAR) is obtained; where A i Let represent the footprint of the i-th building, where i = 1, 2, ..., M, and M represents the total number of buildings. R represents the number of floors in the i-th building, and R represents the pre-set radius;

[0017] Through calculation formula

[0018]

[0019]

[0020] The building height deviation HD is obtained; where H i This represents the height of the i-th building;

[0021] Through calculation formula The wall area ratio is WAR; where Wall i This represents the total wall area of ​​the i-th building;

[0022] Through calculation formula Calculate the building density BD;

[0023] Through calculation formula

[0024]

[0025] A green =∑(A tree ×LAI tree )+∑(A grass ×LAI grass )+∑(A shrub ×LAIshrub )

[0026] The green space floor area ratio GnPR is obtained; where A green A represents the vegetation cover area. tree A represents the area covered by trees. grass Indicates grassland coverage area, A shrub LAI indicates shrub cover area. tree LAI represents the leaf area index of trees. grass The leaf area index (LAI) represents the area of ​​herbaceous plants. shrub Indicates the leaf area index of shrubs;

[0027] Through calculation formula The area ratio of hard paving to PAR is obtained; where A pvmt This indicates the area of ​​hard paving.

[0028] Optionally, based on sky visibility factors and spatial indicators, thermal comfort evaluation indices for the measurement point can be obtained, including:

[0029] Through calculation formula

[0030] PET=(-4.685×FAR)+(2.863×WAR)+(18.934×SVF)-(1.071×HD)+(0.093×PAR×100)+(0.051×BD×100)-(0.002×GnPR×100)+58.703

[0031] The physiologically equivalent temperature index PET was obtained.

[0032] Through calculation formula

[0033] PMV=(-0.792×FAR)+(0.266×WAR)+(2.399×SVF)-(0.166×HD)+(0.025×PAR×100)+(0.022×BD×100)-(0.004×GnPR×100)+5.698

[0034] The predicted average voter metric, PMV, was obtained.

[0035] Through calculation formula

[0036] UTCI=(-1.735×FAR)+(0.702×WAR)+(4.357×SVF)-(0.261×HD)+(0.049×PAR×100)+(0.043×BD×100)-(0.005×GnPR×100)+44.606

[0037] The Universal Thermal Climate Index (UTCI) was obtained.

[0038] Optionally, based on thermal comfort evaluation indices, the thermal comfort level at the measurement point can be predicted, including:

[0039] Through calculation formula The predicted thermal comfort index (TCI) of the measured point is obtained.

[0040] Optionally, before predicting the thermal comfort level at the test point based on thermal comfort evaluation indices, the method for predicting urban outdoor thermal comfort provided in this application further includes:

[0041] Standardize and normalize the thermal comfort evaluation indicators.

[0042] Secondly, this application provides a device for predicting urban outdoor thermal comfort, comprising:

[0043] The Sky Element Division Module is used to divide the hemispherical sky corresponding to the point to be measured into multiple sky elements; where the center of the hemispherical sky is the point to be measured, and the radius of the hemispherical sky is a pre-set value.

[0044] The sky element scanning module is used to scan multiple sky elements using a full-sky scanner and obtain the sky visibility factor of the point to be measured based on the measured data of the full-sky scanner.

[0045] The spatial index calculation module is used to collect environmental data within a preset area, including the measurement point, and obtain spatial index data for the measurement point based on the environmental data. The spatial indexes include building area ratio, building height deviation, wall area ratio, building density, green space volume ratio, and hard paving area ratio.

[0046] The thermal comfort evaluation index module is used to obtain the thermal comfort evaluation index of the test point based on the sky visibility factor and spatial index; the thermal comfort evaluation index includes the physiological equivalent temperature index, the predicted average voting index, and the general thermal climate index.

[0047] The thermal comfort prediction module is used to predict the thermal comfort level at the test point based on thermal comfort evaluation indicators.

[0048] Thirdly, this application provides a terminal device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the above-mentioned method for predicting urban outdoor thermal comfort.

[0049] Fourthly, this application provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method for predicting urban outdoor thermal comfort.

[0050] The above-mentioned solution in this application has the following beneficial effects:

[0051] This application divides the hemispherical sky corresponding to the test point into multiple sky elements, scans these sky elements using a whole-sky scanner, and obtains the sky visibility factor of the test point based on the measured data from the whole-sky scanner. Then, environmental data within the radius of the test point is collected, and spatial index data of the test point is obtained based on the environmental data. Finally, a thermal comfort evaluation index for the test point is obtained based on the sky visibility factor and spatial index, and the thermal comfort level of the test point is predicted based on the thermal comfort evaluation index. In particular, obtaining the thermal comfort evaluation index based on the sky visibility factor and spatial index, and thus predicting the thermal comfort level of the test point, reveals the quantitative relationship between urban spatial renewal and thermal comfort. It comprehensively considers the impact of different thermal comfort evaluation indices on thermal comfort prediction, thereby improving the accuracy of thermal comfort prediction.

[0052] Other beneficial effects of this application will be described in detail in the following detailed description section. Attached Figure Description

[0053] To more clearly illustrate the technical solutions in the embodiments of this application, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0054] Figure 1 A flowchart illustrating a method for predicting urban outdoor thermal comfort according to an embodiment of this application;

[0055] Figure 2 A schematic diagram of the structure of a device for predicting urban outdoor thermal comfort provided in an embodiment of this application;

[0056] Figure 3 This is a schematic diagram of the structure of a terminal device provided in an embodiment of this application. Detailed Implementation

[0057] In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of this application. However, those skilled in the art will understand that this application may also be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods have been omitted so as not to obscure the description of this application with unnecessary detail.

[0058] It should be understood that, when used in this application specification and the appended claims, the term "comprising" indicates the presence of the described features, integrals, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or a collection thereof.

[0059] It should also be understood that the term “and / or” as used in this application specification and the appended claims means any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

[0060] As used in this application specification and the appended claims, the term "if" may be interpreted, depending on the context, as "when," "once," "in response to determination," or "in response to detection." Similarly, the phrase "if determined" or "if detected [the described condition or event]" may be interpreted, depending on the context, as meaning "once determined," "in response to determination," "once detected [the described condition or event]," or "in response to detection [the described condition or event]."

[0061] Furthermore, in the description of this application and the appended claims, the terms "first," "second," "third," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0062] References to "one embodiment" or "some embodiments" as described in this specification mean that one or more embodiments of this application include a specific feature, structure, or characteristic described in connection with that embodiment. Therefore, the phrases "in one embodiment," "in some embodiments," "in other embodiments," "in still other embodiments," etc., appearing in different parts of this specification do not necessarily refer to the same embodiment, but rather mean "one or more, but not all, embodiments," unless otherwise specifically emphasized. The terms "comprising," "including," "having," and variations thereof mean "including but not limited to," unless otherwise specifically emphasized.

[0063] To address the low accuracy of current thermal comfort prediction methods, this application provides a method, apparatus, terminal equipment, and medium for predicting urban outdoor thermal comfort. The method divides the hemispherical sky corresponding to the test point into multiple sky elements, scans these elements using a whole-sky scanner, and obtains the sky visibility factor of the test point based on the measured data. Then, environmental data within a preset area including the test point is collected, and spatial index data for the test point is obtained based on this data. Finally, a thermal comfort evaluation index for the test point is obtained based on the sky visibility factor and spatial index, and the thermal comfort level of the test point is predicted based on this evaluation index. The method of obtaining the thermal comfort evaluation index based on the sky visibility factor and spatial index, thereby predicting the thermal comfort level of the test point, reveals the quantitative relationship between urban spatial renewal and thermal comfort, comprehensively considers the impact of different thermal comfort evaluation indices on thermal comfort prediction, and improves the accuracy of thermal comfort prediction.

[0064] like Figure 1 As shown, the method for predicting urban outdoor thermal comfort provided in this application includes the following steps:

[0065] Step 11: Divide the hemispherical sky corresponding to the point to be measured into multiple sky elements.

[0066] In this system, the center of the hemispherical sky is the point to be measured, and the radius of the hemispherical sky is a pre-set value.

[0067] Specifically, the hemispherical sky is composed of several horizontal subdivisions and several vertical subdivisions. The area enclosed by two adjacent horizontal subdivisions and two adjacent vertical subdivisions is a sky element. In the embodiments of this application, it is also necessary to reasonably set the spacing between each subdivision to make the area of ​​each sky element equal, so as to ensure the accuracy of the sky visibility factor.

[0068] Step 12: Use an all-sky scanner to scan multiple sky elements, and obtain the sky visibility factor of the point to be measured based on the measured data of the all-sky scanner.

[0069] In the embodiments of this application, an all-sky scanner is placed at the point to be measured to receive light from all directions in the hemispherical sky at the point to be measured. If no light enters a region of the hemispherical sky, the sky element corresponding to that region is designated as an unlit sky element; if light enters a region of the hemispherical sky, the sky element corresponding to that region is designated as an illuminated sky element. The number of illuminated sky elements (LK) and the number of unlit sky elements (NLK) are counted to obtain the measured data of the all-sky scanner.

[0070] Based on measured data from the all-sky scanner, it can be calculated using the formula... The Sky View Factor (SVF) is obtained. SVF is an indicator used to describe the visibility of the sky around buildings in an urban environment. It refers to the ratio of the visible area from the ground to the sky at a specific point to the total sky area. A higher SVF value indicates a higher level of sky visibility around that point, and a more open and transparent urban environment.

[0071] Step 13: Collect environmental data within a preset area including the test point, and obtain spatial index data of the test point based on the environmental data.

[0072] In the embodiments of this application, the aforementioned preset area range refers to a circular area formed with the point to be measured as the center and the radius being the radius of the hemispherical sky in step 11. When performing step 13, environmental data in this circular area is collected.

[0073] The aforementioned environmental data includes building footprint, number of floors, building height, total wall area, number of buildings, vegetation cover area, and hard paving area. In one embodiment of this application, the aforementioned environmental data can be obtained through actual measurement or other methods. In another embodiment of this application, a three-dimensional model can be constructed based on image data (e.g., satellite image data) covering a preset range including the points to be measured, and the aforementioned environmental data can be obtained based on the ratio between the three-dimensional model and the actual object.

[0074] The aforementioned spatial indicators include building area ratio, building height deviation, wall area ratio, building density, green space ratio, and hard paving area ratio. In the embodiments of this application, the building area ratio represents the ratio of the total floor area of ​​all buildings (including the area of ​​each floor) within a preset area to the area of ​​the preset area; the building height deviation represents the difference between the actual height of a building and the average height of buildings within the preset area; the wall area ratio represents the ratio of the total wall area of ​​all buildings within the preset area to the area of ​​the preset area; the building density represents the ratio of the total floor area of ​​all buildings (including only the floor area of ​​the first floor) to the area of ​​the preset area; the green space ratio represents the ratio of the area covered by trees, shrubs, and grass within the preset area to the area of ​​the preset area; and the hard paving area ratio represents the ratio of the area of ​​hard paving (such as roads) within the preset area to the area of ​​the preset area.

[0075] Step 14: Based on the sky visibility factor and spatial indicators, obtain the thermal comfort evaluation index of the test point.

[0076] Thermal comfort evaluation indicators include physiological equivalent temperature indicators, predicted average voting indicators, and general thermal climate indicators.

[0077] It is worth mentioning that this application obtains thermal comfort evaluation indices for the test point based on sky visibility factors and spatial indicators, thereby predicting the thermal comfort of the test point, revealing the quantitative relationship between urban spatial renewal and thermal comfort, comprehensively considering the impact of different thermal comfort evaluation indices on thermal comfort prediction, and improving the accuracy of thermal comfort prediction.

[0078] After performing step 14, the method for predicting urban outdoor thermal comfort provided in this application also includes standardizing and normalizing the thermal comfort evaluation index, which avoids the influence of different thermal comfort evaluation indices on the predicted thermal comfort value due to different dimensions and other issues, thereby improving the accuracy of thermal comfort prediction.

[0079] Step 15: Predict the thermal comfort level of the test point based on the thermal comfort evaluation index.

[0080] Specifically, through the calculation formula The predicted thermal comfort index (TCI) for the measurement point is obtained. Here, PET represents the physiologically equivalent temperature index, PWV represents the predicted average vote index, and UTCI represents the universal thermal climate index.

[0081] Thermal comfort prediction values ​​can provide planners, designers, or urban planning and design management departments with a scientific basis for decision-making, thereby realizing "immediate modeling, immediate evaluation, immediate optimization, and immediate improvement" in the process of urban renewal planning and design.

[0082] The following is an exemplary description of the specific process of step 13 (collecting environmental data within a preset range including the point to be measured, and obtaining spatial index data of the point to be measured based on the environmental data).

[0083] Step 13.1, using the calculation formula The building area ratio (FAR) is obtained.

[0084] Among them, A i Let represent the footprint of the i-th building, where i = 1, 2, ..., M, and M represents the total number of buildings. R represents the number of floors in the i-th building, and R represents the pre-set radius.

[0085] Step 13.2, using the calculation formula

[0086]

[0087]

[0088] The building height deviation (HD) is obtained.

[0089] Among them, H i This represents the height of the i-th building.

[0090] Step 13.3, through the calculation formula The wall area is obtained as a percentage of WAR.

[0091] Among them, Wall i This represents the total wall area of ​​the i-th building.

[0092] Step 13.4, using the calculation formula The building density BD is obtained.

[0093] Step 13.5, using the calculation formula

[0094]

[0095] A green =∑(A tree ×LAI tree )+∑(A grass ×LAI grass )+∑(A shrub ×LAI shrub )

[0096] The green space floor area ratio FnPR is obtained.

[0097] Among them, A green A represents the vegetation cover area. tree A represents the area covered by trees. grass Indicates grassland coverage area, A shrub LAI indicates shrub cover area. tree LAI represents the leaf area index of trees. grass The leaf area index (LAI) represents the area of ​​herbaceous plants. shrub This represents the leaf area index of shrubs. Leaf area index (LAI) is an important parameter for measuring the leaf area of ​​vegetation. It is defined as the sum of the projected areas of vegetation leaves per unit area of ​​land. The formula for calculating LAI is:

[0098] LAI = Total surface area of ​​vegetation leaves / Land area

[0099] It should be noted that the higher the LAI value, the larger the leaf area of ​​the vegetation and the greater the degree of light shading.

[0100] Step 13.6, using the calculation formula The area ratio of hard paving to PAR is obtained.

[0101] Among them, A pvmt This indicates the area of ​​hard paving.

[0102] The following is an exemplary description of the specific process layer of step 14 (obtaining the thermal comfort evaluation index of the test point based on the sky visibility factor and spatial index).

[0103] Step 14.1, using the calculation formula

[0104] PET=(-4.685×FAR)+(2.863×WAR)+(18.934×SVF)-(1.071×HD)+(0.093×PAR×100)+(0.051×BD×100)-(0.002×GnPR×100)+58.703

[0105] The physiologically equivalent temperature index PET was obtained.

[0106] Step 14.2, using the calculation formula

[0107] PMV=(-0.792×FAR)+(0.266×WAR)+(2.399×SVF)-(0.166×HD)+(0.025×PAR×100)+(0.022×BD×100)-(0.004×GnPR×100)+5.698

[0108] The predicted average voter metric, PMV, was obtained.

[0109] Step 14.3, using the calculation formula

[0110] UTCI=(-1.735×FAR)+(0.702×WAR)+(4.357×SVF)-(0.261×HD)+(0.049×PAR×100)+(0.043×BD×100)-(0.005×GnPR×100)+44.606

[0111] The Universal Thermal Climate Index (UTCI) was obtained.

[0112] The following is an exemplary description of a device for predicting urban outdoor thermal comfort provided in this application.

[0113] like Figure 2 As shown, the urban outdoor thermal comfort prediction device 200 includes:

[0114] Sky element division module 201 is used to divide the hemispherical sky corresponding to the point to be measured into multiple sky elements; wherein, the center of the hemispherical sky is the point to be measured, and the radius of the hemispherical sky is a preset value.

[0115] Sky element scanning module 202 is used to scan multiple sky elements using a full-sky scanner and obtain the sky visibility factor of the point to be measured based on the measured data of the full-sky scanner.

[0116] The spatial index calculation module 203 is used to collect environmental data within a preset area, including the point to be measured, and to obtain spatial index data of the point to be measured based on the environmental data. The spatial indexes include building area ratio, building height deviation, wall area ratio, building density, green space volume ratio, and hard paving area ratio.

[0117] The thermal comfort evaluation index module 204 is used to obtain the thermal comfort evaluation index of the test point based on the sky visibility factor and spatial index; the thermal comfort evaluation index includes the physiological equivalent temperature index, the predicted average voting index and the general thermal climate index.

[0118] The thermal comfort prediction module 205 is used to predict the thermal comfort level of the test point based on thermal comfort evaluation indicators.

[0119] It should be noted that the information interaction and execution process between the above-mentioned devices / units are based on the same concept as the method embodiments of this application. For details on their specific functions and technical effects, please refer to the method embodiments section, and they will not be repeated here.

[0120] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is merely an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit. Furthermore, the specific names of the functional units and modules are only for easy differentiation and are not intended to limit the scope of protection of this application. The specific working process of the units and modules in the above system can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0121] like Figure 3 As shown, embodiments of this application provide a terminal device, such as... Figure 3 As shown, the terminal device D10 of this embodiment includes: at least one processor D100 ( Figure 3 The diagram shows only one processor, a memory D101, and a computer program D102 stored in the memory D101 and executable on the at least one processor D100, wherein the processor D100 executes the computer program D102 to implement the steps in any of the above method embodiments.

[0122] Specifically, when the processor D100 executes the computer program D102, it divides the hemispherical sky corresponding to the test point into multiple sky elements, scans these sky elements using a full-sky scanner, and obtains the sky visibility factor of the test point based on the measured data from the full-sky scanner. Then, it collects environmental data within a preset area including the test point, and obtains spatial index data for the test point based on the environmental data. Finally, it obtains the thermal comfort evaluation index for the test point based on the sky visibility factor and spatial index, and predicts the thermal comfort level of the test point based on the thermal comfort evaluation index. The method of obtaining the thermal comfort evaluation index based on the sky visibility factor and spatial index, thereby predicting the thermal comfort level of the test point, reveals the quantitative relationship between urban spatial renewal and thermal comfort. It comprehensively considers the impact of different thermal comfort evaluation indices on thermal comfort prediction, thus improving the accuracy of thermal comfort prediction.

[0123] The processor D100 can be a central processing unit (CPU), or it can be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor can be a microprocessor or any conventional processor.

[0124] In some embodiments, the memory D101 may be an internal storage unit of the terminal device D10, such as a hard disk or memory of the terminal device D10. In other embodiments, the memory D101 may be an external storage device of the terminal device D10, such as a plug-in hard disk, smart media card (SMC), secure digital card (SD), flash card, etc., equipped on the terminal device D10. Furthermore, the memory D101 may include both internal and external storage units of the terminal device D10. The memory D101 is used to store the operating system, applications, bootloader, data, and other programs, such as the program code of the computer program. The memory D101 can also be used to temporarily store data that has been output or will be output.

[0125] This application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps described in the various method embodiments above.

[0126] This application provides a computer program product that, when run on a terminal device, enables the terminal device to implement the steps described in the various method embodiments above.

[0127] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include at least: any entity or device capable of carrying the computer program code to a predictive device / terminal device for urban outdoor thermal comfort, a recording medium, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunication signal, and a software distribution medium. Examples include USB flash drives, portable hard drives, magnetic disks, or optical disks. In some jurisdictions, according to legislation and patent practice, computer-readable media cannot be electrical carrier signals or telecommunication signals.

[0128] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail or recorded in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0129] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0130] In the embodiments provided in this application, it should be understood that the disclosed apparatus / network devices and methods can be implemented in other ways. For example, the apparatus / network device embodiments described above are merely illustrative. For instance, the division of modules or units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.

[0131] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0132] The advantages of the urban outdoor thermal comfort prediction method provided in this application are as follows:

[0133] This application introduces a microclimate performance-based design approach into urban design. Utilizing a research method combining morphological typology analysis and microclimate environment simulation, it reveals the quantitative relationship between urban spatial renewal and spatial thermal comfort, and establishes a thermal comfort prediction model. It summarizes and derives the correlation patterns and threshold values ​​of correlation parameters for thermal comfort in three urban renewal models (preservation, remediation, and reconstruction). Furthermore, it constructs an integrated platform for automatic thermal comfort evaluation and evolutionary optimization in urban renewal design, achieving "immediate modeling—immediate evaluation—immediate optimization—immediate optimization" during the urban renewal design process. These innovative achievements provide a technical platform for in-depth exploration of the "two-way feedback" relationship between urban design and the microclimate environment, and also provide a theoretical foundation and scientific basis for urban design scheme review and evidence-based design, which has practical significance for improving the traditional human living environment.

[0134] The above description is the preferred embodiment of this application. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principles described in this application, and these improvements and modifications should also be considered within the scope of protection of this application.

Claims

1. A method for predicting urban outdoor thermal comfort, characterized in that, include: The hemispherical sky corresponding to the point to be measured is divided into multiple sky elements; wherein the center of the hemispherical sky is the point to be measured, and the radius of the hemispherical sky is a preset value. The multiple sky elements are scanned using an all-sky scanner, and the sky visibility factor of the measured point is obtained based on the measured data from the all-sky scanner. The measured data from the all-sky scanner includes the number of illuminated sky elements. And the number of unlit sky elements ; The process of scanning the multiple sky elements using an all-sky scanner and obtaining the sky visibility factor of the measured point based on the all-sky scanner's measured data includes: Through calculation formula The sky visibility factor is obtained. ; Collect environmental data within a preset area including the point to be measured, and obtain spatial index data for the point to be measured based on the environmental data; the spatial index includes building area ratio, building height deviation, wall area ratio, building density, green space volume ratio, and hard paving area ratio, wherein the environmental data includes building footprint, number of building floors, building height, total wall area of ​​the building, number of buildings, vegetation coverage area, and hard paving area; The process of collecting environmental data within a preset area, including the point to be measured, and obtaining spatial index data for the point to be measured based on the environmental data includes: Through calculation formula The building area ratio is obtained. ;in, Indicates the first The floor area of ​​each building, , Indicates the total number of buildings. Indicates the first The number of floors in a building. This indicates a pre-set radius; Through calculation formula The building height deviation was obtained. ;in, Indicates the first The height of the building; Through calculation formula The wall area ratio is obtained. ;in, Indicates the first The total wall area of ​​the building; Through calculation formula The building density is obtained. ; Through calculation formula The green space plot ratio is obtained. ;in, This represents the vegetation coverage area. Indicates the area covered by trees. Indicates grassland coverage area. Indicates the area covered by shrubs. Indicates the leaf area index of trees. Indicates the leaf area index of herbaceous plants. Indicates the leaf area index of shrubs; Through calculation formula The area ratio of the hard paving was obtained. ;in, This indicates the area of ​​the hard paving; Based on the sky visibility factor and the spatial index, the thermal comfort evaluation index of the test point is obtained; the thermal comfort evaluation index includes the physiological equivalent temperature index, the predicted average voting index, and the general thermal climate index. The process of obtaining the thermal comfort evaluation index for the test point based on the sky visibility factor and the spatial index includes: Through calculation formula The physiological equivalent temperature index was obtained. ; Through calculation formula The predicted average voting index is obtained. ; Through calculation formula The general thermal climate index was obtained. ; Predict the thermal comfort level of the test point based on the thermal comfort evaluation index. The step of predicting the thermal comfort level of the test point based on the thermal comfort evaluation index includes: Through calculation formula The predicted thermal comfort value of the measured point is obtained. ; Before predicting the thermal comfort level of the measured point based on the thermal comfort evaluation index, the prediction method further includes: The thermal comfort evaluation indexes are standardized and normalized.

2. A device for predicting urban outdoor thermal comfort, used to execute the method for predicting urban outdoor thermal comfort as described in claim 1, characterized in that, include: The sky element division module is used to divide the hemispherical sky corresponding to the point to be measured into multiple sky elements; wherein the center of the hemispherical sky is the point to be measured, and the radius of the hemispherical sky is a preset value. The sky element scanning module is used to scan the multiple sky elements using a full-sky scanner, and to obtain the sky visibility factor of the point to be measured based on the measured data of the full-sky scanner. The spatial index calculation module is used to collect environmental data within a preset area including the point to be measured, and to obtain spatial index data of the point to be measured based on the environmental data; the spatial index includes building area ratio, building height deviation, wall area ratio, building density, green space volume ratio, and hard paving area ratio. The thermal comfort evaluation index module is used to obtain the thermal comfort evaluation index of the test point based on the sky visibility factor and the spatial index; the thermal comfort evaluation index includes the physiological equivalent temperature index, the predicted average voting index, and the general thermal climate index. The thermal comfort prediction module is used to predict the thermal comfort level of the test point based on the thermal comfort evaluation index.

3. A terminal device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the method for predicting urban outdoor thermal comfort as described in claim 1.

4. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the method for predicting urban outdoor thermal comfort as described in claim 1.

Images