Urban canopy wind speed rapid estimation method and system
By obtaining urban building morphological parameters and suburban wind speed, and combining WRF mode for numerical simulation, the estimation coefficient of urban canopy wind speed is solved, and the problem of difficulty in estimating urban canopy wind speed in traditional methods is achieved, and fast and accurate wind speed estimation is achieved, reducing costs.
Patent Information
- Application Number
- CN202411724584.7
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-11-28
- Publication Date
- 2025-03-21
AI Technical Summary
The prior art is difficult to accurately and quickly estimate urban canopy wind speeds, and traditional observation methods rely on high-density automatic meteorological station networks, which are costly and cumbersome to maintain.
By obtaining the morphological parameters of the city's building area and the suburban wind speed, numerical simulation was performed in combination with the WRF mode, the estimated coefficient Y of the urban canopy wind speed was obtained, and the formula was used: urban canopy wind speed = suburban wind speed × Y, and the urban canopy wind speed was quickly calculated.
It realizes rapid and accurate estimation of urban canopy wind speed without relying on high-density weather station networks, reducing economic costs and improving the efficiency and applicability of the estimation.
Smart Images
Figure CN119669606A_ABST
Abstract
Description
Technical Field
[0001] The invention relates to urban meteorology, and in particular to a method for quickly estimating urban canopy wind speed. Background Art
[0002] The urban canopy (generally refers to the area above the urban surface and below the top of the building layer) is the place where human activities are most concentrated. The wind speed in the urban canopy has a very important impact on human comfort, pollutant diffusion efficiency, and low-altitude aircraft safety. The urban canopy is composed of multiple factors such as buildings, roads, and vegetation in the city. There are many buildings in the urban canopy, and these buildings are of different heights, shapes, materials, and orientations. In addition, various other types of artificial underlying surfaces are scattered in urban areas. These underlying surface types continue to appear alternately, resulting in extremely complex internal urban morphology. Therefore, the urban canopy is complex and diverse, with rapid spatial switching and drastic changes, and has very strong uneven characteristics. More importantly, the climate characteristics of a location in the urban canopy are only affected by the mixed effects of surface properties within a radius of several hundred meters, and these effects decay sharply with increasing distance.
[0003] Due to the influence of the uneven characteristics of the urban underlying surface, the canopy wind speed in different locations in the city also shows great differences. The wind speed characteristics in different locations in the city are directly affected by the underlying surface. As the most important component of the city, the building form is closely related to the characteristics of the urban canopy wind speed. The main reason for the influence of urban buildings on canopy wind speed is that the increase in urban surface roughness reduces the urban canopy wind speed through the drag effect; at the same time, the heat storage and other effects of the city will also cause urban warming, and the turbulent exchange between the upper and lower layers of the atmosphere will be enhanced, resulting in the downward transfer of upper layer momentum, which will increase the urban canopy wind speed. The characteristics of urban canopy wind speed are affected by the combined effects of these two effects, which have opposite effects. At present, there is a lack of quantitative description of these two mechanisms.
[0004] How to accurately describe the distribution characteristics of urban canopy wind speed has always been a hot topic in urban meteorological research. This is because it is difficult to estimate urban canopy wind speed through non-observational methods. At present, urban canopy wind speed still mainly relies on ground observations. A large number of automatic weather stations are deployed in urban areas to obtain canopy wind speed characteristics at different locations in the city. There is no good alternative.
[0005] However, although the traditional urban canopy wind speed observation method based on the meteorological automatic station network can obtain the canopy wind speed in real time, this wind speed data is greatly affected by the surrounding environment and the quality of the observation data is limited. At the same time, since the automatic station can only measure the wind speed at each observation point, in order to obtain the canopy wind speed in the entire urban area, a large number of meteorological automatic stations must be deployed, which requires a lot of construction funds, and the subsequent maintenance of these automatic stations also consumes a lot of manpower and material resources. Summary of the invention
[0006] The present invention aims to solve one of the technical problems existing in the related art at least to a certain extent.
[0007] An object of the present invention is to provide a method for quickly estimating urban canopy wind speed, which can accurately and quickly estimate urban canopy wind speed without relying on the construction of a high-density urban automatic weather station network.
[0008] Another object of the present invention is to provide a rapid estimation system for urban canopy wind speed.
[0009] In order to achieve the above-mentioned object, the present invention provides a method for quickly estimating urban canopy wind speed, comprising:
[0010] Obtain the morphological parameters of the entire building area of the city; and determine the wind speed in the suburbs corresponding to the city;
[0011] The WRF model coupled with morphological parameters is used to perform a refined numerical simulation of the long-term urban series, and the estimated coefficient Y of the urban canopy wind speed is obtained by fitting.
[0012] The urban canopy wind speed can be quickly calculated using the formula: urban canopy wind speed = suburban wind speed × Y.
[0013] A further preferred technical solution of the present invention is that the acquisition of the total building area morphological parameters of the city specifically includes:
[0014] Download the building vector data corresponding to the city;
[0015] Based on the building vector data, urban morphological parameters including the total building area are calculated.
[0016] Preferably, the method of performing a long-time series of refined numerical simulation of the city by coupling the WRF model with morphological parameters, and fitting to obtain the estimated coefficient Y of the city canopy wind speed comprises:
[0017] Based on the WRF model coupled with morphological parameters, a detailed numerical simulation of long-term urban series is conducted, and two examples with and without buildings are set;
[0018] Based on the difference between the two examples, the fitting curve f(lb) of the influence function of the total building area on the canopy wind speed and the fitting curve f(Δ UHI );
[0019] Combining the influence of the total building area and the urban heat island intensity on the canopy wind speed, the estimated coefficient Y of the urban canopy wind speed is obtained, which is expressed as:
[0020] Y=―f(lb)+1+f(Δ UHI);
[0021] Preferably, obtaining the fitting curve f(lb) of the influence function of the total building area on the canopy wind speed comprises:
[0022] In the long-term refined numerical simulation data, the time with larger background wind speed is selected. Under the condition of large wind speed, the urban buildings are mainly driven by dynamic effects, and the heat island effect is ignored. At this time, the difference in canopy wind speed between the two groups of examples is the result of the influence of building dynamic effects.
[0023] The relationship between the total building area and wind speed is fitted to obtain the fitting curve of the influence function of the total building area on the canopy wind speed.
[0024] Among them, a is a constant. When lb=0, that is, there are no buildings, Y=1, and there is no significant difference in wind speed between the city and the suburbs. As the number of buildings gradually increases, Y becomes smaller and smaller, and the wind speed in the urban canopy becomes smaller and smaller.
[0025] Preferably, the fitting curve f(Δ UHI ),include:
[0026] In the long-term refined numerical simulation data, as the background wind speed decreases, the thermal effect of urban buildings on canopy wind speed gradually becomes apparent;
[0027] The dynamic effect of buildings on canopy wind speed is regarded as a constant value, and the relationship between urban heat island intensity and canopy wind speed is fitted to obtain the fitting curve f(Δ UHI )=b*Δ UHI c ;
[0028] Among them, b and c are constants, Δ UHI is the heat island intensity.
[0029] Another aspect of the present invention provides a system for quickly estimating urban canopy wind speed, comprising:
[0030] The data collection module is used to obtain the morphological parameters of the entire building area of the city; and collect the measured wind speed of the suburbs corresponding to the city;
[0031] The estimation coefficient acquisition module is used to perform a refined numerical simulation of the long-term series of the city through the WRF model coupled with morphological parameters, and to obtain the estimation coefficient Y of the urban canopy wind speed by fitting;
[0032] The wind speed estimation module is used to quickly calculate the urban canopy wind speed based on the obtained suburban wind speed and the estimation coefficient Y through the formula: urban canopy wind speed = suburban wind speed × Y.
[0033] Furthermore, the estimation coefficient acquisition module includes:
[0034] Numerical simulation module, used to set up two cases with and without buildings, and to conduct a detailed numerical simulation of the city over a long time series using the WRF model coupled with morphological parameters;
[0035] The fitting curve calculation module is used to obtain the fitting curve f(lb) of the influence function of the total building area on the canopy wind speed and the fitting curve f(Δ UHI ).
[0036] Yet another aspect of the present invention provides a non-transitory computer-readable storage medium having computer instructions stored thereon, the computer instructions enabling a computer to execute the above-mentioned method for rapidly estimating urban canopy wind speed.
[0037] Yet another aspect of the present invention provides an electronic device, comprising: a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory communicate with each other via the communication bus, and the processor calls logic instructions in the memory to execute the above-mentioned method for rapid estimation of urban canopy wind speed.
[0038] Another aspect of the present invention provides a computer program product, which includes a computer program stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer executes the above-mentioned method for quickly estimating urban canopy wind speed.
[0039] Beneficial effects: The present invention proposes a new technical method for rapidly estimating urban canopy wind speed by combining the total building area, a typical urban morphological parameter, with the urban heat island intensity. The method can rapidly estimate the canopy wind speed at any location in the city without relying on a high-density urban automatic station network, thus filling the gap in the rapid estimation method of urban canopy wind speed. This method not only improves the accuracy and efficiency of the estimation, but also reduces the economic cost, and has broad application prospects.
[0040] The method and system for quickly estimating urban canopy wind speed of the present invention have the following features:
[0041] 1. Real-time: It can provide real-time wind speed data for the entire urban area, which helps to monitor and respond to sudden meteorological changes in a timely manner.
[0042] 2. Spatial coverage: Compared with the traditional wind speed observation method based on urban automatic station network, this method does not rely on meteorological equipment and can provide canopy wind speed estimation in a larger range, which is suitable for wind speed monitoring in different areas of the city.
[0043] 3. Efficiency: Compared with traditional large-scale data collection, the rapid estimation method can quickly provide wind speed information, and this method only relies on a simple formula model and is easy to implement and operate.
[0044] 4. Economical: This method does not require a large number of meteorological observation equipment, large-scale data processing, and manual maintenance, which reduces economic costs.
[0045] 5. Applicability: The method of the present invention can be adjusted and optimized according to the specific conditions of different cities. It has strong adaptability and is suitable for multiple application scenarios such as urban planning, architectural design, environmental monitoring, disaster warning, etc.
[0046] 6. Reliability: The method of the present invention has been verified by a large amount of measured data over a long period of time and has a high degree of credibility. It can also optimize and improve the estimation model based on the observation data already obtained in different cities, thereby improving the performance and effect of the estimation method. BRIEF DESCRIPTION OF THE DRAWINGS
[0047] Figure 1 It is a flowchart of the method for quickly estimating urban canopy wind speed of the present invention;
[0048] Figure 2 A distribution diagram of urban building vector data in an embodiment of the present invention;
[0049] Figure 3 This is a fitting curve diagram of canopy wind speed and total building area under different heat island conditions in an embodiment of the present invention. DETAILED DESCRIPTION
[0050] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the drawings in the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments, and they should not be understood as limitations on the present invention. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention. In the description of the present invention, it should be understood that the terms used are only for descriptive purposes and cannot be understood as indicating or implying relative importance.
[0051] Combine the following Figure 1-Figure 3 The invention describes a method and system for quickly estimating urban canopy wind speed.
[0052] Embodiment 1: This embodiment provides a method for quickly estimating urban canopy wind speed. The overall process is as follows: Figure 1 As shown, including:
[0053] Obtain the morphological parameters of the entire building area of the city; and determine the wind speed in the suburbs corresponding to the city;
[0054] The WRF model coupled with morphological parameters is used to perform a refined numerical simulation of the long-term urban series, and the estimated coefficient Y of the urban canopy wind speed is obtained by fitting.
[0055] The urban canopy wind speed can be quickly calculated using the formula: urban canopy wind speed = suburban wind speed × Y.
[0056] In this embodiment, the city of Shanghai is taken as an example to illustrate the complete implementation process and verification results of the method.
[0057] First, collect detailed building vector data in Shanghai, such as Figure 2 As shown in Figure 2, these data can be obtained from the morphological parameter set of major cities in China, which is available at the Harvard University Data Sharing Center.
[0058] The data are openly shared on the website of Beijing Institute of Urban Meteorology (https: / / doi.org / 10.7910 / DVN / VZH1QY) and can be downloaded for free. The urban morphological parameters of Shanghai area are calculated, which can characterize the complex morphology of urban buildings.
[0059] Then, based on the WRF (Weather Research and Forecasting Model) model coupled with high-resolution morphological parameters, a long-term refined numerical simulation of Shanghai from 2016 to 2020 was carried out, and sensitivity tests with and without buildings were set up. The difference between the two groups of examples was used to study the impact mechanism of urban buildings on canopy wind speed.
[0060] In order to separate the dynamic and thermal effects of buildings on canopy wind speed, we first select the time when the background wind speed is larger in the long-term simulation data. Under high wind speed conditions, urban buildings are mainly affected by dynamic effects, and the heat island effect can be ignored. At this time, the difference in canopy wind speed between the two groups of examples can be considered as the result of the dynamic effect of the building. Through the fitting curve between wind speed attenuation and the total area of the building, we can get This is the dynamic equation of the impact of buildings on canopy wind speed. When lb=0, that is, there are no buildings, Y=1, and there is no significant difference in wind speed between the city and the suburbs. As the number of buildings gradually increases, Y becomes smaller and smaller, and the urban canopy wind speed becomes smaller and smaller.
[0061] As the background wind speed decreases, the thermal effect of urban buildings on canopy wind speed gradually becomes apparent. We compared the fitting curves of the effect of buildings on canopy wind speed under different heat island conditions, such as Figure 3As shown in the figure, the results show that the dynamic influence of buildings on canopy wind speed is basically constant. The relationship between urban heat island intensity and canopy wind speed is fitted to obtain the fitting curve f(Δ UHI )=0.05*Δ UHI 2.13 .
[0062] At this time, combined with the influence of the total building area and the urban heat island intensity on the canopy wind speed, the estimated coefficient Y of the urban canopy wind speed is obtained, which is expressed as:
[0063]
[0064] In order to evaluate this method of rapid estimation of urban canopy wind speed, this embodiment is verified using long-term meteorological automatic station observation data in Shanghai. The results show that this method can well estimate the canopy wind speed at different locations in the city, with an accuracy of about 90%. In high wind conditions, especially during typhoons, the accuracy exceeds 95%. Other cities can also use this method to quickly estimate urban canopy wind speed. The dynamic effect of buildings on canopy wind speed is the same in all cities, and the thermal effect f(Δ UHI ) may be affected by local terrain and may have slight differences in different cities. In specific applications, corresponding adjustments can be made based on the data.
[0065] The above embodiment separates the dynamic effect and thermal effect of urban buildings on canopy wind speed through the typical urban morphological parameter of total building area, and gives a quantitative expression function of the two mechanisms on canopy wind speed. The results show that the influence of building form on urban canopy wind speed is mainly dynamic, and the dynamic effect of building form on urban canopy wind speed is basically constant, which can make the wind speed attenuate by about 50%; the thermal effect of urban buildings on canopy wind speed increases with the increase of urban heat island intensity, and the thermal effect can increase the wind speed by about 30% under strong heat island conditions. The relative contribution of the dynamic and thermal effects of urban buildings to canopy wind speed changes with the change of background wind speed. As the wind speed increases, the contribution of urban buildings to the thermal effect of canopy wind speed gradually decreases, while the contribution of urban buildings to the dynamic effect of canopy wind speed remains basically unchanged.
[0066] Embodiment 2: This embodiment provides a system for quickly estimating urban canopy wind speed, comprising:
[0067] The data collection module is used to obtain the morphological parameters of the entire building area of the city; and collect the measured wind speed of the suburbs corresponding to the city;
[0068] The estimation coefficient acquisition module is used to perform a refined numerical simulation of the long-term series of the city through the WRF model coupled with morphological parameters, and to obtain the estimation coefficient Y of the urban canopy wind speed by fitting;
[0069] The estimation coefficient acquisition module comprises:
[0070] Numerical simulation module, used to set up two cases with and without buildings, and to conduct a detailed numerical simulation of the city over a long time series using the WRF model coupled with morphological parameters;
[0071] The fitting curve calculation module is used to obtain the fitting curve f(lb) of the influence function of the total building area on the canopy wind speed and the fitting curve f(Δ UHI ).
[0072] The wind speed estimation module is used to quickly calculate the urban canopy wind speed based on the obtained suburban wind speed and the estimation coefficient Y through the formula: urban canopy wind speed = suburban wind speed × Y.
[0073] Embodiment 3: This embodiment provides a non-transitory computer-readable storage medium having computer instructions stored thereon, the computer instructions causing a computer to execute a method for rapidly estimating urban canopy wind speed, the method comprising the following steps:
[0074] Obtain the morphological parameters of the entire building area of the city; and determine the wind speed in the suburbs corresponding to the city;
[0075] The WRF model coupled with morphological parameters is used to perform a refined numerical simulation of the long-term urban series, and the estimated coefficient Y of the urban canopy wind speed is obtained by fitting.
[0076] The urban canopy wind speed can be quickly calculated using the formula: urban canopy wind speed = suburban wind speed × Y.
[0077] Embodiment 4: This embodiment provides an electronic device, which may include: a processor, a communications interface, a memory, and a communication bus, wherein the processor, the communications interface, and the memory communicate with each other via the communication bus. The processor may call the logic instructions in the memory to execute a method for quickly estimating urban canopy wind speed, the method comprising the following steps:
[0078] Obtain the morphological parameters of the entire building area of the city; and determine the wind speed in the suburbs corresponding to the city;
[0079] The WRF model coupled with morphological parameters is used to perform a refined numerical simulation of the long-term urban series, and the estimated coefficient Y of the urban canopy wind speed is obtained by fitting.
[0080] The urban canopy wind speed can be quickly calculated using the formula: urban canopy wind speed = suburban wind speed × Y.
[0081] In addition, the logic instructions in the above-mentioned memory can be implemented in the form of software functional units and can be stored in a computer-readable storage medium when sold or used as an independent product. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.
[0082] Embodiment 5: This embodiment provides a computer program product, which includes a computer program. The computer program can be stored in a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute a method for quickly estimating urban canopy wind speed. The method includes the following steps:
[0083] Obtain the morphological parameters of the entire building area of the city; and determine the wind speed in the suburbs corresponding to the city;
[0084] The WRF model coupled with morphological parameters is used to perform a refined numerical simulation of the long-term urban series, and the estimated coefficient Y of the urban canopy wind speed is obtained by fitting.
[0085] The urban canopy wind speed can be quickly calculated using the formula: urban canopy wind speed = suburban wind speed × Y.
[0086] The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative labor.
[0087] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.
[0088] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.
Claims
1. A method for rapid estimation of urban canopy wind speed, characterized in that: include: Obtain the morphological parameters of the entire building area of the city; And determine the suburban wind speed corresponding to the city; The WRF model coupled with morphological parameters is used to perform a refined numerical simulation of the long-term urban series, and the estimated coefficient Y of the urban canopy wind speed is obtained by fitting. The urban canopy wind speed can be quickly calculated using the formula: urban canopy wind speed = suburban wind speed × Y.
2. The method for rapid estimation of urban canopy wind speed according to claim 1, characterized in that: The obtaining of the total building area morphological parameters of the city specifically includes: Download the building vector data corresponding to the city; Based on the building vector data, urban morphological parameters including the total building area are calculated.
3. The method for rapid estimation of urban canopy wind speed according to claim 1, characterized in that: The method involves performing a long-term refined numerical simulation of the city by coupling the WRF model with morphological parameters, and fitting to obtain the estimated coefficient Y of the city canopy wind speed; including: Based on the WRF model coupled with morphological parameters, a detailed numerical simulation of long-term urban series is conducted, and two examples with and without buildings are set; Based on the difference between the two examples, the fitting curve f(lb) of the influence function of the total building area on the canopy wind speed and the fitting curve f(Δ UHI ); Combining the influence of the total building area and the urban heat island intensity on the canopy wind speed, the estimated coefficient Y of the urban canopy wind speed is obtained, which is expressed as: T=―f(lb)+1+f(Δ UHI )。 4. The method for rapid estimation of urban canopy wind speed according to claim 3, characterized in that: The method of obtaining the fitting curve f(lb) of the influence function of the total building area on the canopy wind speed includes: In the long-term refined numerical simulation data, the time with larger background wind speed is selected. Under the condition of large wind speed, the urban buildings are mainly driven by dynamic effects, and the heat island effect is ignored. At this time, the difference in canopy wind speed between the two groups of examples is the result of the influence of building dynamic effects. The relationship between the total building area and wind speed is fitted to obtain the fitting curve of the influence function of the total building area on the canopy wind speed. Among them, a is a constant. When lb=0, that is, there are no buildings, Y=1, and there is no significant difference in wind speed between the city and the suburbs. As the number of buildings gradually increases, Y becomes smaller and smaller, and the wind speed in the urban canopy becomes smaller and smaller.
5. The method for rapid estimation of urban canopy wind speed according to claim 3, characterized in that: The fitting curve f(Δ UHI ),include: In the long-term refined numerical simulation data, as the background wind speed decreases, the thermal effect of urban buildings on canopy wind speed gradually becomes apparent; The dynamic effect of buildings on canopy wind speed is regarded as a constant value, and the relationship between urban heat island intensity and canopy wind speed is fitted to obtain the fitting curve f(Δ UHI )=b*Δ UHI c ; Among them, b and c are constants, Δ CHI is the heat island intensity.
6. A rapid estimation system for urban canopy wind speed, characterized in that: include: Data collection module, used to obtain the morphological parameters of the entire building area of the city; And collect the suburban wind speed corresponding to the measured city; The estimation coefficient acquisition module is used to perform a refined numerical simulation of the long-term series of the city through the WRF model coupled with morphological parameters, and to obtain the estimation coefficient Y of the urban canopy wind speed by fitting; The wind speed estimation module is used to quickly calculate the urban canopy wind speed based on the obtained suburban wind speed and the estimation coefficient Y through the formula: urban canopy wind speed = suburban wind speed × Y.
7. The rapid estimation system for urban canopy wind speed according to claim 6, characterized in that: The estimation coefficient acquisition module comprises: Numerical simulation module, used to set up two cases with and without buildings, and to conduct a detailed numerical simulation of the city over a long time series using the WRF model coupled with morphological parameters; The fitting curve calculation module is used to obtain the fitting curve f(lb) of the influence function of the total building area on the canopy wind speed and the fitting curve f(Δ UHI ).
8. A non-transitory computer-readable storage medium having computer instructions stored thereon, the computer instructions enabling a computer to execute the method for rapidly estimating urban canopy wind speed according to any one of claims 1 to 5.
9. An electronic device, comprising: A processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory communicate with each other via the communication bus, and the processor calls the logic instructions in the memory to execute the method for quickly estimating urban canopy wind speed as described in any one of claims 1-5.
10. A computer program product, comprising a computer program stored on a non-transitory computer-readable storage medium, wherein when the computer program is executed by a processor, the computer executes the method for rapidly estimating urban canopy wind speed according to any one of claims 1 to 5.