A Smart Method for Excavating Urban Ventilation Corridors Based on High-Precision Oblique Photogrammetry

Abstract

This invention discloses an intelligent method for excavating urban ventilation corridors based on high-precision oblique photogrammetry, comprising the following steps: Step S1: Oblique photogrammetry is used to acquire oblique photogrammetry images of the target city via aerial photography to obtain a Digital Surface Model (DSM) and a Digital Elevation Model (DEM); Step S2: The difference between the DSM and DEM is used to extract the three-dimensional surface data of the target city; Step S3: Multiple prevailing wind directions of the target city are acquired, and the windward area density of each prevailing wind direction is calculated based on the three-dimensional surface data obtained in Step S2; Step S4: A template is designed based on the prevailing wind direction information, and template matching is performed based on the windward area density of the prevailing wind direction to find the continuous area within the windward area density range as urban ventilation corridors; Step S5: Based on Step S4, the urban ventilation corridors are automatically excavated to extract urban ventilation corridors that meet preset requirements.

Description

Technical Field

[0001] This invention relates to the field of image processing technology, and in particular to a method for intelligent excavation of urban ventilation corridors based on high-precision oblique photographic images. Background Technology

[0002] With the advancement of urbanization and the impact of industrial pollution, urban ventilation has become an increasingly important issue. Research on urban ventilation corridors is a hot topic in urban planning. It is predicted that China's urbanization rate will reach over 70% by 2050. Rapid urbanization has powerfully promoted the sustained development of the economy and society and the overall improvement of the living standards of urban and rural residents. However, rapid urbanization has also led to urban environmental problems such as the deterioration of the microclimate and the severe urban heat island effect. Related research shows that good urban ventilation can promote urban air circulation and reduce air pollution. Improving the urban ventilation environment and constructing urban ventilation corridors (VCs) are effective measures to enhance urban air circulation capacity and alleviate urban environmental problems.

[0003] Research techniques for urban ventilation corridors mainly fall into three categories: field measurement, physical simulation experiments, and computer numerical simulation analysis. Relatively speaking, computer analysis techniques based on urban spatial data models are low-cost and quick to implement in ventilation corridor planning and design. Furthermore, by setting conditions and allowing for parameter studies for evaluation, these techniques will undoubtedly play a significant role in supporting decisions that improve overall urban ventilation efficiency.

[0004] In recent years, many scholars have conducted research in this field. Zeng Suiping (2016), Wang Qun (2017), and others have explored the planning and design of wind corridors in some central urban areas using CFD (Computational Fluid Dynamics) software simulation, remote sensing image inversion, and GIS analysis. However, the research lacks systematicity

[11] . At the same time, the research also lacks a systematic thinking to solve urban environmental and ecological problems from a planning perspective. Yuan Zhong (2017) proposed using a WRF model with coupled single-layer urban canopy parameters to construct two-level wind corridors at certain city scales. Zhang Yunlu (2017) used high-resolution urban geographic information data and adopted RS and GIS integration to extract surface information and spatial information of the central urban area of ​​Jinzhong City, and finally obtained the urban roughness pattern map of the central urban area of ​​the city. However, in general, these studies lack in-depth exploration of the detailed morphology of the city and are insufficient in exploring the intelligence and redundancy of urban ventilation corridors.

[0005] Therefore, given the shortcomings of existing technologies, it is necessary to propose a technical solution to address the technical problems existing in the current technologies. Summary of the Invention

[0006] In view of this, it is indeed necessary to provide a method for intelligently excavating urban ventilation corridors based on high-precision oblique photogrammetry. This method utilizes a high-resolution five-view oblique aerial camera mounted on a large brown bear aircraft to acquire oblique image data. Digital terrain model (DSM) and digital elevation model (DEM) maps are extracted from the multi-view oblique images. Based on historical statistical data from meteorological departments, the prevailing wind direction of the target city is analyzed. The DSM-DEM map is processed to obtain data such as urban buildings. By projecting the prevailing wind direction, a windward area density (FAD) map is calculated. Image processing techniques such as template matching are performed on the FAD map to calculate urban ventilation corridor data. Finally, based on empirical standards for urban ventilation corridors, the ventilation corridors of the target city are extracted. Experimental results show that the method of this invention can quickly excavate urban ventilation corridors and can serve as a reference for urban planning.

[0007] In order to solve the technical problems existing in the prior art, the technical solution of the present invention is as follows:

[0008] A method for intelligently excavating urban ventilation corridors based on high-precision oblique photogrammetry includes the following steps:

[0009] Step S1: Oblique photogrammetry is used to obtain oblique photogrammetric images of the target city through aerial photography to obtain the digital surface model (DSM) and digital elevation model (DEM);

[0010] Step S2: Extract the 3D surface data of the target city using the difference between the DSM and DEM;

[0011] Step S3: Obtain multiple prevailing wind direction information for the target city, and calculate the windward area density for each prevailing wind direction by combining the three-dimensional surface data obtained in Step S2.

[0012] Step S4: Design a template based on the prevailing wind direction information, and perform template matching calculation based on the windward area density of the prevailing wind direction to find the continuous area in the windward area density range as the urban ventilation corridor.

[0013] Step S5: Based on step S4, automatically excavate urban ventilation corridors to extract urban ventilation corridors that meet preset requirements.

[0014] As a further improvement, in step S5, the optimal ventilation corridor for each prevailing wind direction is extracted according to preset conditions and synthesized to obtain the optimal ventilation corridor for the target city.

[0015] As a further improvement, in step S5, the optimal ventilation corridor for each prevailing wind direction is obtained through the following steps:

[0016] Step S51: Set the length of the ventilation corridor;

[0017] Step S52: Set the initial value and step size of the ventilation corridor width;

[0018] Step S53: Generate a grid network map of the target city based on the width of the ventilation corridors;

[0019] Step S54: Calculate the windward area density of each grid cell under the prevailing wind direction to obtain the FAD map, where the grid pixel value is the windward area density of its corresponding single grid cell.

[0020] Step S55: Perform template matching calculation on the FAD diagram obtained in step S54 based on the prevailing wind direction template, and extract the ventilation corridors;

[0021] Step S56: Calculate the ventilation corridor area and determine if it decreases compared to the previous step. If so, extract the optimal ventilation corridor; otherwise, increase the ventilation corridor width by step size and repeat step S53.

[0022] As a further improvement, the windward area density (FAD) value of each grid cell in the excavated ventilation corridor is less than or equal to 0.35.

[0023] As a further improvement, the orientation of the excavated ventilation corridor is such that the angle θ between it and the prevailing wind direction is less than or equal to 45°.

[0024] As a further improvement, in step S61, the length of the ventilation corridor is set to 500 meters or 1000 meters.

[0025] As a further improvement, in step S62, the initial width of the ventilation corridor is 30 meters, with a step size of 20 meters.

[0026] As a further improvement, in step S3, the windward area density is calculated using the following formula:

[0027]

[0028] Where A(θ)proj(z) is the windward area of ​​the building perpendicular to a certain wind direction; AT is the area of ​​the land on which the building is located; θ is a selected direction; and z is the height increment.

[0029] As a further improvement, in step S3, the daily average wind speed and wind direction information of the target city over the past 10 years are obtained and a wind rose diagram is generated to obtain the dominant wind direction information.

[0030] As a further improvement, in step S4, the template is designed as a matrix, with due north as the reference, and the element values ​​that match the prevailing wind path are set to 1, while the element values ​​that do not match the prevailing wind path are set to 0.

[0031] Traditional research on ventilation corridors primarily focuses on qualitative or simulation studies of urban climate issues such as the exacerbation of the urban heat island effect, severe environmental pollution, and insufficient climate adaptability. Compared to existing technologies, this invention addresses the potential urban ventilation corridor problem by extracting multi-view oblique imagery DSM and DEM maps based on high-resolution data obtained from aerial oblique photography. Building elevations derived from the DSM-DEM difference map are used to calculate the prevailing wind direction (FAD) map. Image processing techniques such as binarization and template matching are employed to identify urban ventilation corridors of varying widths and lengths, providing technical support for the scientific and rational planning of cities. Furthermore, experiments in Deqing County, Zhejiang Province, China, have demonstrated the effectiveness of this method. It can comprehensively uncover urban ventilation corridors, providing virtual reality technology support for precise urban microclimate planning and design. Attached Figure Description

[0032] Figure 1 This is a flowchart of a method for intelligently excavating urban ventilation corridors based on high-precision oblique photographic images, according to the present invention.

[0033] Figure 2 The image shows the winter monsoon (left) and summer monsoon (right) roses of Deqing City, generated based on meteorological data.

[0034] Figure 3 This is a map showing the windward area density of Deqing City in summer and winter. Figure 3 (Left) Summer windward area density map Figure 3 (Right) Winter windward area density diagram.

[0035] Figure 4 This is a schematic diagram showing the relationship between windward area density and wind speed ratio.

[0036] Figure 5 This is a schematic diagram of the template matching mechanism.

[0037] Figure 6 This is a schematic diagram of the template design for a winter corridor with a length of 9 in the present invention, under the three prevailing wind directions. Figure 6 (a) Template with prevailing wind direction of -67.5 degrees. Figure 6 (b) is a template with a prevailing wind direction of -45 degrees. Figure 6 (c) is a template with a prevailing wind direction of 0 degrees.

[0038] Figure 7 This is a flowchart of the automatic excavation process for ventilation corridors in this invention.

[0039] Figure 8 This is a flowchart illustrating the optimal width of automatic excavation for urban ventilation corridors in a preferred embodiment of the present invention.

[0040] Figure 9 To extract a schematic diagram of the corridor flow based on the optimal corridor width.

[0041] Figure 10 To illustrate the ventilation conditions of corridors of various widths in the prevailing winter wind direction of a target city using the method of this invention, wherein... Figure 10 (a) Ventilation conditions of corridors of various widths in a wind direction of -67.5 degrees. Figure 10 (b) Ventilation conditions of corridors of various widths in a -45 degree wind direction. Figure 10 (c) Ventilation conditions of corridors of various widths in a 0-degree wind direction.

[0042] Figure 11 This is a schematic diagram showing the results of automatic excavation of a 100-meter-wide and 500-meter-long corridor using the method of this invention.

[0043] Figure 12 This is a schematic diagram showing the results of automatic excavation of a 70-meter-wide and 500-meter-long corridor using the method of this invention.

[0044] Figure 13 This is a schematic diagram showing the results of automatic excavation of a 30-meter-wide and 500-meter-long corridor using the method of this invention.

[0045] The following specific embodiments will further illustrate the present invention in conjunction with the above-described accompanying drawings. Detailed Implementation

[0046] The technical solution provided by the present invention will be further described below with reference to the accompanying drawings.

[0047] See Figure 1 The diagram shown is a flowchart of the intelligent excavation method for urban ventilation corridors based on high-precision oblique photogrammetry provided by the present invention, which includes the following steps:

[0048] Step S1: Oblique photogrammetry is used to acquire oblique photogrammetric images of the target city via aerial photography to obtain a Digital Surface Model (DSM) and a Digital Elevation Model (DEM). In this step, oblique photogrammetry is used to acquire oblique photogrammetric images via aerial photography, and field control points are collected to assist in aerial triangulation. The digital surface model is then extracted and edited, and the images undergo light and color homogenization processing to finally obtain the oblique photogrammetric digital surface model (DSM). The DSM is a simulation of the ground surface, including vegetation surfaces and building surfaces. The DSM is processed by removing information about buildings, vegetation, etc., to form a digital elevation model (DEM).

[0049] Step S2: Extract the three-dimensional surface data of the target city using the difference between DSM and DEM; This invention uses the difference between DSM and DEM to extract the height of surface roughness such as buildings, rivers, lakes, and vegetation.

[0050] Step S3: Obtain multiple prevailing wind direction information for the target city, and calculate the windward area density for each prevailing wind direction by combining the three-dimensional surface data obtained in Step S2.

[0051] Step S4: Design a template based on the prevailing wind direction information, and perform template matching calculation based on the windward area density of the prevailing wind direction to find the continuous area in the windward area density range as the urban ventilation corridor.

[0052] Step S5: Based on step S4, automatically excavate urban ventilation corridors to extract urban ventilation corridors that meet preset requirements.

[0053] In step S3 above, multiple dominant wind direction information of the target city must first be obtained. In a preferred embodiment, the daily average wind speed and wind direction information of the target city over the past 10 years are obtained and a wind rose diagram is generated to obtain the dominant wind direction information.

[0054] Wind rose diagrams, as a professional statistical chart of wind, are used to quantitatively analyze the wind direction and speed characteristics of a location over a period of time. This invention obtained daily average wind speed and direction data at a height of 10 meters from the Deqing City Meteorological Department for the past 10 years, and performed average statistical analysis of wind direction frequencies in 16 directions. (See [link to relevant documentation]). Figure 2 The image shows the winter monsoon (left) and summer monsoon (right) rose diagrams of Deqing City generated based on meteorological data.

[0055] like Figure 2 As shown in the left figure, the prevailing wind direction in Deqing during winter is northwest. The frequencies of the three wind directions NNW, NW and N are 11.8%, 11.13% and 10.43% respectively, with a total frequency of 33.36%. Figure 2 As shown in the right figure, Deqing experiences two dominant wind directions in summer: southerly and easterly. The frequencies of the SSW and S wind directions are 11.45% and 11.19% respectively, with a combined frequency of 22.64%. The frequencies of the E, ENE, and ESE wind directions are 8.85%, 8.09%, and 6.48% respectively, with a combined frequency of 23.42%. Based on the above analysis, multiple dominant wind direction information for the target city can be obtained.

[0056] In step S3 above, the windward area density is calculated using the following formula:

[0057]

[0058] Where A(θ)proj(z) is the windward area of ​​the building perpendicular to a certain wind direction; AT is the area of ​​the land on which the building is located; θ is a selected direction; and z is the height increment.

[0059] Buildings are the most important influencing factors for urban ventilation, and the ventilation evaluation mainly adopts the comprehensive frontal area density method. The urban frontal area density (FAD) represents the ratio of the frontal area of buildings to the area of the plot where the buildings are located under a specific wind direction at a certain height increment. The frontal area density can reflect the obstruction effect of the urban form on the wind in a specific direction, that is, it can reflect the ventilation ability of the wind in a specific direction within the urban area.

[0060] When calculating the building frontal density of the dominant wind directions in winter and summer in the target city, classify and count the heights of urban buildings to determine the height increment. Using the generated model data above (including the spatial distribution and height data information of all buildings), for example, generate grid data of 100m×100m. According to the dominant wind directions in winter and summer, through coordinate transformation, generate the raster image of the city. Select the high-frequency wind direction angles of a wind rose diagram of the city, calculate the vertical area of the city in this wind direction, that is, perform the image projection calculation of the height increment, and automatically calculate the frontal area density of each raster to obtain the FAD map. Using the above method, the frontal area densities of the target city in summer and winter can be calculated as follows Figure 3 as shown, where Figure 3 (left) is the summer frontal area density map, Figure 3 (right) is the winter frontal area density map.

[0061] The frontal area density calculated above represents the smoothness of the movement of natural wind in the city. See Figure 4 , which shows the schematic diagram of the relationship between the frontal area density and the wind speed ratio. A large number of practical experiences show that: FAD <= 0.35 indicates that the movement of natural wind is smooth; 0.35 < FAD <= 0.45 indicates that the flow of natural wind is not smooth enough; 0.45 < FAD <= 0.6 indicates that there is an obstruction to the movement of natural wind; FAD > 0.6 indicates that there is a greater obstruction to the movement of natural wind.

[0062] The present invention takes the frontal area density as the main calculation factor, and the urban ventilation corridor refers to the continuous area within the numerical range of the frontal area density. Therefore, the present invention creatively proposes the intelligent excavation of urban ventilation corridors based on templates. That is, first, design a template according to the dominant wind direction information, and then perform template matching operations based on the frontal area density in the dominant wind direction to find the continuous area within the numerical range of the frontal area density as the urban ventilation corridor.

[0063] The template operation is a convolution operation, and each pixel in the image area used is multiplied by each element of the convolution kernel (weight matrix) respectively, and the sum of all products is used as the new value of the pixel at the center of the area.

[0064] The implementation mechanism of the template operation is as Figure 5As shown. In Figure 5(a), the 3×3 (i.e., M=3) dashed black frame is as follows. Figure 5 As shown in (b): H(s,t) (s,t∈[-1,+1]) is the 3×3 template coefficient value.

[0065] The template moves point by point in the image as follows: It moves to the right until the last column of pixels in the template overlaps with the rightmost column of pixels in the image; it moves down until the bottom row of pixels in the template overlaps with the bottom row of pixels in the image. This is defined as:

[0066]

[0067] The values ​​of k and l depend on the size of the selected neighborhood, and k = l. Generally, the values ​​of k and l are odd numbers. Figure 5 In this case, both k and l are 1.

[0068] In the above calculation process,

[0069] 1) For formula 1 and Figure 5 The result of the operation will result in the "loss" of 2 × (M / 2) rows and columns. To avoid losing rows and columns, the following method is used: If the image size is N×N, first expand the rightmost part of the original image by M-1 rows and the bottommost part by M-1 columns, and then perform the corresponding template operation to directly obtain the N×N result.

[0070] 2) Generally speaking, considering an N×N graph f(i,j), we have {i,j∈[0,N-1]}; for an M×M template {H(s,t)}, we have {s,t∈[0,M-1]}. Therefore, in the calculation formula, the range of values ​​for s and t can be [0,M-1] respectively, thus modifying Formula 1 into Formula 2.

[0071]

[0072] In this invention, a template is designed based on the prevailing wind direction. In a preferred embodiment, in step S4, the designed template is a matrix or vector, with true north as the reference. Elements matching the prevailing wind path are set to 1, while elements not matching the prevailing wind path are set to 0. Furthermore, the template design rule is defined as follows: the length of the lines connecting elements with a value of 1 in the template is the template length; specifically, the horizontal or vertical distance is 1 unit, and the diagonal distance is...

[0073] The design process will be briefly introduced below using the template example in Table 1.

[0074] Table 1 Template Design Examples

[0075] 0 0 0 1 1 0 0 0 1 0 0 0 1 0 0 0 1 0 0 0 1 1 0 0 0

[0076] First, number this template as shown in Table 2 below.

[0077] Table 2 Template Number

[0078] 0 0 0 ⑥ ⑦ 0 0 0 ⑤ 0 0 0 ④ 0 0 0 ③ 0 0 0 ① ② 0 0 0

[0079] The distance from the bottom left corner to the top right corner: ① to ② is 1 because it's a horizontal direction; ② to ③ is 1 because it's a vertical direction; ③ to ④ is... Because it's a diagonal direction; similarly, the distance from ④ to ⑤ is... The distance from ⑤ to ⑥ is 1, and the distance from ⑥ to ⑦ is 1. Therefore, the total distance of this template is:

[0080] The direction angle θ can be calculated using this template, since sin(θ) = 5 / 6.828, that is, θ = 47.0778 degrees.

[0081] Using the above template design approach, taking the excavation of ventilation corridors in winter as an example, based on the wind rose diagram of the target city over the past 10 years, the frequencies of north-northwest winds (NNW), northwest winds (NW), and north winds (N) in winter are 11.8%, 11.13%, and 10.43%, respectively, with a sum of 33.36%. This satisfies the condition that a dominant wind direction exists in more than 30% of the time. Therefore, the dominant wind directions in winter for this city are north-northwest winds (NNW) (-67.5 degrees Celsius), northwest winds (NW) (-45 degrees Celsius), and north winds (N) (0 degrees Celsius). The design for the dominant wind directions is as follows: Figure 6 The template shown is an example with a length of 9. Among them, Figure 6 (a) Template with prevailing wind direction of -67.5 degrees. Figure 6 (b) is a template with a prevailing wind direction of -45 degrees. Figure 6 (c) is a template with a prevailing wind direction of 0 degrees.

[0082] In step S5, the optimal ventilation corridor for each prevailing wind direction is extracted according to preset conditions and then synthesized to obtain the optimal ventilation corridor for the target city. That is, the optimal ventilation corridor for each prevailing wind direction that meets the preset conditions is first automatically extracted, and then the optimal ventilation corridor for each prevailing wind direction is synthesized to obtain the optimal ventilation corridor for the target city.

[0083] In a preferred embodiment, the preset conditions of the present invention are as follows: under the premise that FAD <= 0.35, the following three conditions are selected as empirical standards for urban ventilation corridors:

[0084] (1) VC length >= 500m; preferably, the length of the ventilation corridor is usually set to 500m or 1000m.

[0085] (2) VC width >= 30m; Preferably, this invention, in conjunction with the specific target city, divides urban ventilation corridors into three levels according to VC width: CCⅠ (VC width >= 100m), CCⅡ (70m <= VC width < 100m), and CCⅢ (30m <= VC width < 70m). In practice, the initial value of the ventilation corridor width is 30 meters, with a step size of 20 meters. Thus, ventilation corridors of different width levels can be automatically excavated.

[0086] (3) The angle between the direction of VC and the prevailing wind direction is θ<=45°.

[0087] In a preferred embodiment, see Figure 7 The diagram shows the flowchart of the automatic excavation of ventilation corridors in this invention. In step S5, the optimal ventilation corridor for each prevailing wind direction is obtained through the following steps:

[0088] Step S51: Set the length of the ventilation corridor;

[0089] Step S52: Set the initial value and step size of the ventilation corridor width;

[0090] Step S53: Generate a grid network map of the target city based on the width of the ventilation corridors;

[0091] Step S54: Calculate the windward area density of each grid cell under the prevailing wind direction to obtain the FAD map, where the grid pixel value is the windward area density of its corresponding single grid cell.

[0092] Step S55: Perform template matching calculation on the FAD diagram obtained in step S54 based on the prevailing wind direction template, and extract the ventilation corridors;

[0093] Step S56: Calculate the ventilation corridor area and determine if it decreases compared to the previous step. If so, extract the optimal ventilation corridor; otherwise, increase the ventilation corridor width by step size and repeat step S53.

[0094] In the above technical solution, the present invention generates a grid network map of the target city based on the width of the ventilation corridor, thereby enabling the rapid discovery of ventilation corridors with the optimal width.

[0095] In summary, this invention uses DSM-DEM data from oblique imagery to calculate the windward area density for a given prevailing wind direction based on urban height information and wind characteristics, thereby generating a FAD map. Ventilation corridors are then identified through template matching using empirical values ​​for ventilation corridor classification. In a preferred embodiment, see the following... Figure 8 The diagram shown is a flowchart of the automatic excavation of the optimal width of urban ventilation corridors in a preferred embodiment of the present invention.

[0096] The above-mentioned automated excavation process for ventilation corridors:

[0097] a) When excavating the corridor, the length of the corridor is determined first. As mentioned above in this invention: the corridor length is >= 500 meters or more, and generally a corridor length of 500 or 1000 meters is taken.

[0098] b) Initially preset the optimal corridor widths width1, width2, and width3 for the three extracted wind directions alpha1, alpha2, and alpha3.

[0099] c) Select the corridor width for one of the wind directions, use the template for that wind direction to match the windward area density map (FAD), and you can obtain the corridor for the alpah1 wind direction and calculate the total corridor area (i.e., corridor width multiplied by corridor length).

[0100] d) Repeat step c) to complete the template matching for alpha2 and alpha3 wind directions, and find the optimal ventilation corridor. See also Figure 9 The figure shows the specific process of extracting corridors based on the optimal corridor width.

[0101] To verify the technical effect of the present invention, in the experiment, a high-definition oblique aerial camera was used to acquire oblique image data of Deqing City. After verification, oblique image DSM and DEM maps from multiple perspectives were extracted. Global Mapper was used to generate urban building height and ground roughness data from the DSM-DEM map. According to the prevailing wind direction of Deqing City's 10-year wind characteristics statistics, the prevailing wind direction was projected onto the DSM-DEM map to calculate the FAD map. Image processing techniques such as binarization, dilation, erosion, and template matching were then performed to finally achieve automatic acquisition of urban ventilation corridor maps of various specified widths or lengths.

[0102] In the experiment, corridors of different widths and lengths were excavated for the prevailing winter wind directions (-67.5 degrees, -45 degrees, and 0 degrees) in the target city, and the maximum effective width of the corridors was calculated. (See [link to relevant documentation]). Figure 10 The figure shows the ventilation conditions of corridors of various widths in the prevailing winter wind direction of the target city, as determined by the method of this invention. Figure 10 (a) Ventilation conditions of corridors of various widths in a wind direction of -67.5 degrees. Figure 10 (b) Ventilation conditions of corridors of various widths in a -45 degree wind direction. Figure 10 (c) Ventilation conditions of corridors of various widths in a 0-degree wind direction.

[0103] from Figure 10It can be seen that when the corridor width increases from 30 meters to 70 meters for prevailing wind directions of -67.5 degrees and 0 degrees, the ventilation level of corridors of given lengths (0.5 km, 1 km, 1.5 km, 2 km) gradually increases, but remains relatively stable once the width reaches 70 meters. When the prevailing wind direction is -45 degrees, the ventilation level remains relatively stable once the width reaches 100 meters. Therefore, it can be concluded that the maximum effective corridor width is 70 meters when the wind direction is -67.5 degrees and 0 degrees, and 100 meters when the wind direction is -45 degrees.

[0104] Furthermore, this invention selects a winter prevailing wind direction and a minimum length of 500 meters as an example, extracting ventilation corridors with widths of 100, 70, and 30 meters respectively. See also Figure 11 The diagram shows the results of automatic excavation of a 100-meter-wide and 500-meter-long corridor using the method of this invention. The program automatically excavated five ventilation corridors with a width of 100 meters or more, which can be used as a reference for the primary ventilation ducts of the urban ventilation system. Deqing is dominated by northwest winds in winter. The primary ventilation corridors follow the prevailing wind direction to introduce natural wind into the urban area (corridors 1 and 3 do not run through the entire urban area). The spatial carriers of corridors 1, 3, and 4 are railway lines and main urban roads. Corridor 2 runs from the High-tech Industrial Development Zone to the County People's Government, and from the city park to low-density residential land. Corridor 5 enters the city from the industrial park land along urban roads.

[0105] See Figure 12 The diagram shows the results of automatic excavation of a 70-meter-wide and 500-meter-long corridor using the method of this invention. It can be seen that three new 70-meter-wide ventilation corridors for introducing natural wind have been added, which can serve as references for secondary ventilation ducts in the urban ventilation system. At the same time, several extension lines of primary ventilation ducts have been added. The secondary ventilation ducts rely on urban roads as their spatial carriers.

[0106] comprehensive Figure 11 and Figure 12 As can be seen, the program failed to excavate ventilation corridors in the densely populated southern part of the city. Therefore, the method of this invention was used to excavate at a smaller scale (30 meters wide). See [link to relevant documentation]. Figure 13 The diagram shows the results of automatic excavation of a 30-meter-wide and 500-meter-long corridor using the method of this invention. The results show that there are still potential level 3 wind corridors in these densely populated areas, and the three newly added 30-meter-wide corridors all rely on urban roads.

[0107] To verify the practical effectiveness of the ventilation corridors discovered by this invention, three experts specializing in urban planning independently drew a three-tiered corridor system after analyzing high-resolution imagery of Deqing City and conducting on-site investigations. Comparison showed that the average percentages of the three-tiered corridors drawn by the experts being identical to those automatically extracted in this paper were 93.1%, 91.6%, and 90.25%, respectively. This demonstrates that the method of this invention can discover urban ventilation corridors of different widths and lengths, providing technical support for the scientific and rational planning of cities. Experiments in Deqing County, Zhejiang Province, China, have proven the effectiveness of the method presented in this paper. It can comprehensively discover urban ventilation corridors, providing virtual reality technology support for the precise planning and design of urban microclimate environments.

[0108] The above description of the embodiments is only for the purpose of helping to understand the method and core ideas of the present invention. It should be noted that those skilled in the art can make several improvements and modifications to the present invention without departing from the principles of the present invention, and these improvements and modifications also fall within the protection scope of the claims of the present invention.

[0109] The above description of the disclosed embodiments enables those skilled in the art to make or use the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for intelligently excavating urban ventilation corridors based on high-precision oblique photogrammetry, characterized in that, Includes the following steps: Step S1: Oblique photogrammetry is used to obtain oblique photogrammetric images of the target city through aerial photography to obtain the digital surface model (DSM) and digital elevation model (DEM); Step S2: Extract the 3D surface data of the target city using the difference between the DSM and DEM; Step S3: Obtain multiple prevailing wind direction information for the target city, and calculate the windward area density for each prevailing wind direction by combining the three-dimensional surface data obtained in Step S2. Step S4: Design a template based on the prevailing wind direction information, and perform template matching calculation based on the windward area density of the prevailing wind direction to find the continuous area in the windward area density range as the urban ventilation corridor. Step S5: Based on step S4, automatically excavate urban ventilation corridors to extract urban ventilation corridors that meet preset requirements; In step S4, the designed template is a matrix or vector, with due north as the reference. Elements that match the prevailing wind path are set to 1, while elements that do not match the prevailing wind path are set to 0. At the same time, the length of the line with a value of 1 in the template is defined as the template length. In step S5, the optimal ventilation corridor for each prevailing wind direction is extracted and synthesized according to preset conditions to obtain the optimal ventilation corridor for the target city. The optimal ventilation corridor for each prevailing wind direction is obtained through the following steps: Step S51: Set the length of the ventilation corridor; Step S52: Set the initial value and step size of the ventilation corridor width; Step S53: Generate a grid network map of the target city based on the width of the ventilation corridors; Step S54: Calculate the windward area density of each grid cell under the prevailing wind direction to obtain the FAD map, where the grid pixel value is the windward area density of its corresponding single grid cell. Step S55: Perform template matching calculation on the FAD diagram obtained in step S54 according to the designed template, and extract the ventilation corridor; Step S56: Calculate the ventilation corridor area and determine if it decreases compared to the previous step. If so, extract the optimal ventilation corridor; otherwise, increase the ventilation corridor width by step size and repeat step S53. The template matching operation is a convolution operation.

2. The intelligent excavation method for urban ventilation corridors based on high-precision oblique photogrammetry as described in claim 1, characterized in that, In the excavated ventilation corridor, the windward area density (FAD) value of each grid cell it passes through is <=0.

35.

3. The intelligent excavation method for urban ventilation corridors based on high-precision oblique photogrammetry as described in claim 1, characterized in that, The ventilation corridors that were excavated had an angle θ<=45º with the prevailing wind direction.

4. The intelligent excavation method for urban ventilation corridors based on high-precision oblique photogrammetry as described in claim 1, characterized in that, In step S61, the length of the ventilation corridor is set to 500 meters or 1000 meters.

5. The intelligent excavation method for urban ventilation corridors based on high-precision oblique photogrammetry as described in claim 1, characterized in that, In step S62, the initial width of the ventilation corridor is 30 meters, with a step size of 20 meters.

6. The intelligent excavation method for urban ventilation corridors based on high-precision oblique photogrammetry as described in claim 1, characterized in that, In step S3, the windward area density is calculated using the following formula: ； Where A(θ)proj(z) is the windward area of ​​the building perpendicular to a certain wind direction; A T θ is the area of ​​the land where the building is located; θ is a selected direction; z is the height increment.

7. The intelligent excavation method for urban ventilation corridors based on high-precision oblique photogrammetry as described in claim 1, characterized in that, In step S3, the daily average wind speed and wind direction information of the target city over the past 10 years are obtained and a wind rose diagram is generated to obtain the dominant wind direction information.

Images