An urban park thermal comfort evaluation method combining physical and psychological paths

Abstract

This invention provides a method for evaluating the thermal comfort of urban parks by integrating physical and psychological pathways. It relates to the field of park comfort evaluation technology and includes: acquiring physical environment data, landscape feature data, psychological perception data, and thermal environment experience data of preset sampling points in the urban park to be evaluated; inputting the physical environment data into a physical environment assessment path model constructed based on the human body thermal balance theory, outputting an objective thermal load index to characterize the objective thermal load level of the human body; inputting the landscape feature data and psychological perception data into a predetermined psychological perception assessment path model, outputting a thermal comfort estimate considering the psychological adjustment effect; and using the objective thermal load index and the thermal comfort estimate as feature vectors, inputting them into a comprehensive evaluation regression model, outputting the comprehensive thermal comfort evaluation result for each sampling point. This invention solves the problem that existing technologies struggle to comprehensively and quantitatively evaluate thermal comfort based on both physical environment and psychological perception, leading to inaccurate evaluation results.

Description

Technical Field

[0001] This invention relates to the field of park comfort evaluation technology, and in particular to a method for evaluating the thermal comfort of urban parks that integrates physical and psychological pathways. Background Technology

[0002] Thermal comfort is a key factor influencing the user experience and spatial vitality of urban parks. Traditional thermal comfort assessments primarily rely on measuring physical environmental parameters such as temperature, humidity, wind speed, and solar radiation, and using thermodynamic indicators such as PET and UTCI for quantitative analysis. These methods are based on the assumption of thermal equilibrium between the human body and the environment, and have certain applicability in building interiors or homogeneous climate environments.

[0003] However, as a complex outdoor space, the thermal environment of urban parks is influenced not only by physical climatic conditions but also significantly by landscape features and users' psychological perceptions. For example, well-shaded trees, water features, rich visual layers, and a pleasant acoustic environment can significantly improve users' subjective thermal sensations, even under similar physical environmental parameters. Existing technical solutions mostly focus on modeling and simulating the objective physical environment, failing to systematically incorporate psychological factors such as landscape vision, spatial perception, and environmental preferences. This leads to discrepancies between assessment results and actual human experience, making it difficult to comprehensively and accurately reflect users' thermal comfort in real-world scenarios. Summary of the Invention

[0004] The embodiments of the present invention provide a method for evaluating the thermal comfort of urban parks by integrating physical and psychological pathways, aiming to solve the problem that existing technologies are unable to comprehensively and quantitatively evaluate thermal comfort based on both physical environment and psychological perception, resulting in inaccurate evaluation results.

[0005] To achieve the above objectives, in a first aspect, the present invention provides a method for evaluating the thermal comfort of urban parks by integrating physical and psychological pathways, comprising the following steps: Obtain physical environment data, landscape feature data, psychological perception data, and thermal environment experience data from pre-set sampling points in the urban park to be evaluated; The physical environment data is input into a physical environment assessment path model constructed based on the human body thermal balance theory, and the output is an objective heat load index used to characterize the objective heat load level of the human body; the objective heat load index is physiological equivalent temperature, general thermal climate index and / or standard effective temperature; The landscape feature data and psychological perception data are used as independent variables to input into a predetermined psychological perception assessment path model, and the output is a thermal comfort estimate after considering the psychological adjustment effect. The objective heat load index and the psychologically adjusted thermal comfort estimate are used as feature vectors and input into a comprehensive evaluation regression model based on machine learning. The comprehensive thermal comfort evaluation results for each sampling point are then output.

[0006] Furthermore, the physical environment data includes air temperature, relative humidity, wind speed, surface radiation temperature, and / or light intensity.

[0007] Furthermore, the landscape feature data is obtained by semantic segmentation of the panoramic images of the sampling points, including sky visibility, green visibility, and / or water visibility.

[0008] Furthermore, the psychological perception data includes sensory perception data, cognitive evaluation data, and / or emotional response data; wherein, the sensory perception data includes visual pleasure, landscape clarity, sense of shade, auditory comfort, proportion of natural sound, and / or noise interference level, used to characterize an individual's direct sensory feedback to the environment; the cognitive evaluation data includes a sense of security, order, nature, and / or belonging in the scene, used to characterize an individual's psychological identification with the attributes of the space and their safety threshold; the emotional response data includes positive and negative emotions, used to characterize the emotional fluctuations of respondents in the current hot environment; the psychological perception data is scored using a five- or seven-point Likert scale through questionnaires or digital evaluation terminals, and the scoring results are normalized.

[0009] Furthermore, the thermal environment experience data includes thermal sensation voting values, thermal comfort voting values, thermal acceptability and / or thermal preference voting values; the thermal environment experience data is quantified using the ASHRAE standard seven-point scale or five-point rating scale, and is used as training labels for the comprehensive evaluation regression model.

[0010] Furthermore, the comprehensive thermal comfort assessment result includes a comprehensive thermal comfort index and / or a comprehensive thermal comfort level; wherein, the comprehensive thermal comfort index is calculated using the following formula: , in, This indicates the overall thermal comfort index; This is the function for calculating the comprehensive thermal comfort index. As an objective heat load index, The estimated value of thermal comfort after psychological adjustment. and The dynamic weights are automatically learned by the model. The comprehensive thermal comfort level is determined by constructing a comprehensive thermal comfort level mapping table. Based on the numerical distribution of the comprehensive thermal comfort index, a threshold range is set using the equidistant division method or cluster analysis method, and the evaluation results are divided into five levels: extremely uncomfortable, uncomfortable, neutral, comfortable, and extremely comfortable.

[0011] Furthermore, the comprehensive thermal comfort assessment results also include a spatial optimization feedback step, specifically including: identifying key factors of physical environment data or landscape feature data that contribute the most to thermal comfort by performing partial dependency analysis or feature importance assessment on the comprehensive assessment regression model; and automatically generating urban design optimization suggestions, including increasing shading, adjusting the proportion of water bodies, and / or optimizing the density of plant configuration, based on the sensitivity analysis results of the key factors.

[0012] Secondly, the present invention provides a device for evaluating the thermal comfort of urban parks by integrating physical and psychological dual pathways, including a memory and a processor. The memory stores at least one program, which is executed by the processor to implement the method for evaluating the thermal comfort of urban parks by integrating physical and psychological dual pathways as described above.

[0013] Thirdly, the present invention provides a computer-readable storage medium storing at least one program, which is executed by a processor to implement the urban park thermal comfort evaluation method as described above, which integrates physical and psychological pathways.

[0014] Fourthly, the present invention provides a computer program product, including a computer program that, when executed by a processor, implements the steps of the urban park thermal comfort evaluation method as described above, which integrates physical and psychological dual paths.

[0015] The above technical solution has the following technical effects: This invention acquires physical environment data, landscape feature data, psychological perception data, and thermal environment experience data from pre-defined sampling points in the urban park to be evaluated. The physical environment data is input into a physical environment assessment path model constructed based on the human body thermal balance theory, outputting an objective thermal load index characterizing the objective thermal load level of the human body. The landscape feature data and psychological perception data are input into a pre-defined psychological perception assessment path model, outputting a thermal comfort estimate considering the psychological adjustment effect. The objective thermal load index and the thermal comfort estimate are used as feature vectors and input into a comprehensive assessment regression model, outputting the comprehensive thermal comfort assessment results for each sampling point. This invention solves the problem of inaccurate assessment results caused by the difficulty in comprehensively and quantitatively assessing thermal comfort based on both physical environment and psychological perception in existing technologies. Attached Figure Description

[0016] Figure 1 This is a flowchart illustrating a method for evaluating the thermal comfort of urban parks that integrates physical and psychological pathways, according to an embodiment of the present invention. Figure 2 This is a schematic diagram of the structure of a city park thermal comfort evaluation device that integrates physical and psychological pathways according to an embodiment of the present invention. Detailed Implementation

[0017] To further illustrate the various embodiments, the present invention provides accompanying drawings. These drawings are part of the disclosure of the present invention, primarily used to illustrate the embodiments and to explain the operating principles of the embodiments in conjunction with the relevant descriptions in the specification. With reference to these drawings, those skilled in the art should be able to understand other possible implementations and the advantages of the present invention. Components in the drawings are not drawn to scale, and similar component symbols are generally used to represent similar components.

[0018] The present invention will now be further described in conjunction with the accompanying drawings and specific embodiments.

[0019] Example 1: Figure 1 This is a flowchart illustrating a method for evaluating urban park thermal comfort that integrates physical and psychological pathways, according to an embodiment of the present invention. Figure 1 As shown, the method of this embodiment includes the following steps: Obtain physical environment data, landscape feature data, psychological perception data, and thermal environment experience data from pre-set sampling points in the urban park to be evaluated; In one specific implementation, portable environmental monitoring devices are deployed at predetermined sampling points in urban parks to collect physical environmental parameters related to thermal comfort, including air temperature (Ta), relative humidity (RH), wind speed (Va), surface radiation temperature (Tmrt or converted via black sphere temperature), and / or light intensity (LUX). The sampling frequency is 1–5 seconds, adjustable according to device performance; the sampling duration is no less than 3 minutes to reduce transient disturbances; the monitoring devices are positioned 1.1–1.5 meters above the ground, consistent with human perception height; the collected data is used for subsequent physical heat load evaluation and joint analysis with psychological data.

[0020] In one specific implementation, landscape feature data includes sky openness, green visibility (GVI), and / or water visibility (WVI). Specifically, visual structural features of the environment are collected simultaneously to reflect the moderating effect of the landscape on human psychological thermal perception. Sky openness (SVF) is obtained by capturing hemispherical images using a fisheye lens and calculating the proportion of sky pixels using an image segmentation algorithm. Green visibility (GVI) is calculated by classifying pixels in the wide-angle forward-looking images captured on-site and calculating the proportion of green pixels. Water visibility (WVI) is calculated by identifying water bodies through image semantic segmentation and calculating the proportion of water pixels. Acquisition requirements include: using fixed angles such as a horizontal viewing angle of 0° and an elevation angle of 60°; using the same shooting equipment and settings; and performing automated calculations after on-site imaging.

[0021] In one specific implementation, psychological perception data reflects human subjective experience and feelings about the environment, including sensory perception data, cognitive evaluation data, and / or emotional response data. Sensory perception data includes visual pleasure, landscape clarity, shading, auditory comfort, proportion of natural sound, and / or noise interference. Cognitive evaluation data includes a sense of security, order, nature, and / or belonging in the scene. Emotional response data includes positive and negative emotions, used to characterize the respondent's emotional fluctuations in the current hot environment. The psychological perception data is obtained through questionnaires or digital evaluation terminals, using a five- or seven-point Likert scale to score the above indicators. The quantitative scoring results are mapped to continuous variables or normalized feature vectors within the [0, 1] interval, serving as input feature values ​​for the psychological perception assessment path model.

[0022] In one specific implementation, psychological perception data can be obtained through questionnaires, mini-programs, or digital evaluation terminals.

[0023] In one specific implementation, user evaluations of the thermal environment are collected simultaneously, i.e., thermal environment experience data, including: thermal sensation voting value, thermal comfort voting value, thermal acceptability and / or thermal preference voting value; the thermal environment experience data is quantified using the ASHRAE standard seven-level scale or five-level rating scale, and is used as training labels for the comprehensive evaluation regression model.

[0024] In one specific implementation, the collected data undergoes missing value processing, noise filtering, standardization between different units, and time synchronization alignment. Among these, physical data, images, and questionnaires need to be unified according to timestamps to ensure consistency and comparability in subsequent evaluations.

[0025] The physical environment data is input into the physical environment assessment path model based on the human body thermal balance theory. The objective heat load index used to characterize the objective heat load level of the human body is calculated based on air temperature, relative humidity, wind speed and radiation environment parameters. In one specific implementation, the objective heat load index is at least one of physiological equivalent temperature (PET), universal thermal climate index (UTCI) or standard effective temperature (SET). Landscape feature data and psychological perception data are used as independent variables to input a predetermined psychological perception assessment path model, and the output is a thermal comfort estimate after considering the psychological adjustment effect. In one specific implementation, the psychological perception assessment path model is trained with thermal environment experience data as supervised labels to establish a nonlinear relationship between landscape psychology and thermal comfort. In another specific implementation, landscape feature data is used as an environmental input variable of the psychological perception assessment path model to adjust the individual's tolerance threshold to the thermal environment.

[0026] The objective heat load index and the predicted thermal comfort value after psychological adjustment are used as feature vectors and input into a comprehensive evaluation regression model based on machine learning. By calculating the weight mapping between the two types of evaluation results and the actual thermal comfort experience, the weight parameters are determined based on supervised learning. Based on the weight parameters, predictions are made and the comprehensive thermal comfort evaluation results of each sampling point are output.

[0027] In one specific implementation, the comprehensive thermal comfort assessment result includes a comprehensive thermal comfort index and / or a comprehensive thermal comfort level; wherein, the comprehensive thermal comfort index (C-TCI) is a continuous evaluation index calculated by weighted fusion, regression analysis, or machine learning models based on objective heat load indicators and psychologically adjusted thermal comfort estimates, and its calculation formula is expressed as follows: , in, This indicates the overall thermal comfort index; This is the function for calculating the comprehensive thermal comfort index. As an objective heat load index, The estimated value of thermal comfort after psychological adjustment. and The dynamic weights are automatically learned by the model. A comprehensive thermal comfort level mapping table is constructed. Based on the numerical distribution of the comprehensive thermal comfort index, the threshold range is set using the equidistant division method or cluster analysis method, and the evaluation results are divided into at least five levels, including extremely uncomfortable, uncomfortable, neutral, comfortable, and extremely comfortable.

[0028] In one specific implementation, the comprehensive thermal comfort assessment results also include a spatial optimization feedback step: by performing a biased dependency analysis or feature importance assessment on the comprehensive assessment model, the physical or landscape factors that contribute the most to thermal comfort are identified; based on the sensitivity analysis results of the physical or landscape factors, urban design optimization suggestions, including increasing shading, adjusting the proportion of water bodies, or optimizing the density of plant configuration, are automatically generated.

[0029] In one specific implementation, the comprehensive thermal comfort assessment results also include the contributions of the physical environment assessment path model and the psychological perception assessment path model, the moderating effects of different physical environment data and different psychological perception data, and optimization suggestions for urban design. Specifically, the comprehensive thermal comfort assessment results can be used as a decision-making basis for urban park planning and design: during park planning optimization, comparative analysis of the spatial distribution of the comprehensive thermal comfort index and its components in different areas is used to identify key areas with insufficient thermal comfort and to assist in determining the optimization direction for green space layout, spatial openness, and shading configuration; during facility layout strategy formulation, the differences in comprehensive thermal comfort levels and the contributions of physical and psychological paths at different sampling points guide the site selection and combination configuration of rest facilities, activity areas, and service facilities; during thermal environment improvement simulation, the comprehensive thermal comfort assessment results are used as evaluation indicators or constraints to compare and evaluate the thermal comfort improvement effects of different design schemes or control measures; and in the digital twin city system, the comprehensive thermal comfort assessment results are used as one of the evaluation outputs of multi-source environmental perception data to support the dynamic assessment and scenario simulation analysis of the park's thermal environment status.

[0030] Example 2: Figure 2 This is a schematic diagram of the structure of a physical-psychological dual-pathway fusion urban park thermal comfort evaluation device according to an embodiment of the present invention, as shown below. Figure 2 As shown, the device includes a processor 201, a memory 202, a bus 203, and a computer program stored in the memory 202 and executable on the processor 201. The processor 201 includes one or more processing cores. The memory 202 is connected to the processor 201 via the bus 203. The memory 202 is used to store program instructions. When the processor executes the computer program, it implements the steps in the above-described method embodiment of Embodiment 1 of the present invention.

[0031] Furthermore, as an executable solution, the urban park thermal comfort evaluation device integrating physical and psychological pathways can be a computer unit, which can be a desktop computer, laptop, handheld computer, or cloud server, etc. The computer unit may include, but is not limited to, a processor and memory. Those skilled in the art will understand that the above-described structure of the computer unit is merely an example and does not constitute a limitation on the computer unit. It may include more or fewer components, or combine certain components, or use different components. For example, the computer unit may also include input / output devices, network access devices, buses, etc., which are not limited in this embodiment of the invention.

[0032] Furthermore, as an executable solution, the processor can be a Central Processing Unit (CPU), or 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. The general-purpose processor can be a microprocessor or any conventional processor, etc. The processor is the control center of the computer unit, connecting various parts of the entire computer unit via various interfaces and lines.

[0033] The memory can be used to store the computer programs and / or modules. The processor implements various functions of the computer unit by running or executing the computer programs and / or modules stored in the memory and by calling data stored in the memory. The memory may mainly include a program storage area and a data storage area. The program storage area may store the operating system and at least one application program required for a function; the data storage area may store data created based on the use of the mobile phone, etc. In addition, the memory may include high-speed random access memory and may also include non-volatile memory, such as hard disk, RAM, plug-in hard disk, smart media card (SMC), secure digital card (SD card), flash card, at least one disk storage device, flash memory device, or other volatile solid-state storage device.

[0034] Example 3: The present invention also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the method described in the embodiments of the present invention.

[0035] If the modules / units integrated in the computer unit are implemented as software functional units and sold or used as independent products, they 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 also 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: any entity or device capable of carrying the computer program code, recording media, USB flash drives, portable hard drives, magnetic disks, optical disks, computer memory, read-only memory (ROM), random access memory (RAM), and software distribution media, etc. It should be noted that the content contained in the computer-readable medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction.

[0036] Example 4: The present invention also provides a computer program product, including a computer program that, when executed by a processor, implements the steps of the urban park thermal comfort evaluation method as described above, which integrates physical and psychological dual paths.

[0037] Although the invention has been specifically shown and described in conjunction with preferred embodiments, those skilled in the art should understand that various changes in form and detail may be made to the invention without departing from the spirit and scope of the invention as defined in the appended claims, all of which shall be within the scope of protection of the invention.

Claims

1. A method for evaluating the thermal comfort of urban parks that integrates physical and psychological pathways, characterized in that, Includes the following steps: Obtain physical environment data, landscape feature data, psychological perception data, and thermal environment experience data from pre-set sampling points in the urban park to be evaluated; The physical environment data is input into a physical environment assessment path model constructed based on the human body thermal balance theory, and the output is an objective heat load index used to characterize the objective heat load level of the human body; the objective heat load index is physiological equivalent temperature, general thermal climate index and / or standard effective temperature; The landscape feature data and psychological perception data are used as independent variables to input into a predetermined psychological perception assessment path model, and the output is a thermal comfort estimate after considering the psychological adjustment effect. The objective heat load index and the psychologically adjusted thermal comfort estimate are used as feature vectors and input into a comprehensive evaluation regression model based on machine learning. The comprehensive thermal comfort evaluation results for each sampling point are then output.

2. The method for evaluating urban park thermal comfort by integrating physical and psychological pathways as described in claim 1, characterized in that, The physical environment data includes air temperature, relative humidity, wind speed, surface radiation temperature, and / or light intensity.

3. The method for evaluating urban park thermal comfort by integrating physical and psychological pathways as described in claim 1, characterized in that, The landscape feature data is obtained by semantic segmentation of panoramic images of sampling points, including sky openness, green visibility, and / or water visibility.

4. The method for evaluating urban park thermal comfort by integrating physical and psychological pathways as described in claim 1, characterized in that, The psychological perception data includes sensory perception data, cognitive evaluation data, and / or emotional response data. The sensory perception data includes visual pleasure, landscape clarity, sense of shade, auditory comfort, proportion of natural sound, and / or noise interference level, used to characterize an individual's direct sensory feedback to the environment. The cognitive evaluation data includes a sense of security, order, nature, and / or belonging in the scene, used to characterize an individual's psychological identification with the attributes of the space and their safety threshold. The emotional response data includes positive and negative emotions, used to characterize the respondent's emotional fluctuations in the current hot environment. The psychological perception data is obtained through questionnaires or digital evaluation terminals, using a five- or seven-point Likert scale, and the scoring results are normalized.

5. The method for evaluating urban park thermal comfort by integrating physical and psychological pathways according to claim 1, characterized in that, The thermal environment experience data includes thermal sensation voting values, thermal comfort voting values, thermal acceptability and / or thermal preference voting values; the thermal environment experience data is quantified using the ASHRAE standard seven-point scale or five-point rating scale, and is used as training labels for the comprehensive evaluation regression model.

6. The method for evaluating urban park thermal comfort by integrating physical and psychological pathways according to claim 1, characterized in that, The comprehensive thermal comfort assessment result includes a comprehensive thermal comfort index and / or a comprehensive thermal comfort level; wherein, the comprehensive thermal comfort index is calculated using the following formula: in, This indicates the overall thermal comfort index; This is the function for calculating the comprehensive thermal comfort index. As an objective heat load index, The estimated value of thermal comfort after psychological adjustment. and The dynamic weights are automatically learned by the model. The comprehensive thermal comfort level is determined by constructing a comprehensive thermal comfort level mapping table. Based on the numerical distribution of the comprehensive thermal comfort index, a threshold range is set using the equidistant division method or cluster analysis method, and the evaluation results are divided into five levels: extremely uncomfortable, uncomfortable, neutral, comfortable, and extremely comfortable.

7. The method for evaluating urban park thermal comfort by integrating physical and psychological pathways according to claim 1, characterized in that, The comprehensive thermal comfort assessment results also include a spatial optimization feedback step, specifically including: identifying key factors of physical environment data or landscape feature data that contribute the most to thermal comfort by performing partial dependency analysis or feature importance assessment on the comprehensive assessment regression model; and automatically generating urban design optimization suggestions, including increasing shading, adjusting the proportion of water bodies, and / or optimizing the density of plant configuration, based on the sensitivity analysis results of the key factors.

8. A device for evaluating the thermal comfort of urban parks that integrates physical and psychological pathways, characterized in that, The system includes a memory and a processor, the memory storing at least one program, which is executed by the processor to implement the urban park thermal comfort evaluation method that integrates physical and psychological pathways as described in any one of claims 1-7.

9. A computer-readable storage medium, characterized in that, The storage medium stores at least one program segment, which is executed by a processor to implement the urban park thermal comfort evaluation method that integrates physical and psychological pathways as described in any one of claims 1-7.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, it implements the steps of the urban park thermal comfort evaluation method that integrates physical and psychological dual paths as described in any one of claims 1-7.

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