Landscape-first low altitude airport flight route selection method

Abstract

The invention relates to a landscape-first low-altitude airline flight route selection method, which comprises the following steps of: performing map rasterization on a low-altitude airline flight space, and forming a frequent obstacle avoidance visual raster map in combination with basic data of the low-altitude airline flight space; establishing a ground landscape evaluation system and a low-altitude landscape attraction evaluation system of the low-altitude airport travel airspace, and obtaining a comprehensive landscape attraction visual map according to the ground landscape evaluation system and the low-altitude landscape attraction evaluation system; establishing an inevitable point coordinate system according to the high-attraction scenic spots of the low-altitude airport travel airspace; and based on the frequent obstacle avoidance visual grid map, the landscape attraction visual map and the inevitable point coordinate system are integrated to generate a low-altitude language travel main channel path. The flight path considering the obstacle avoidance demand and the landscape experience improves the experience and efficiency of low-altitude travel flight, and creates additional value for the urban travel industry. The calculation burden is relieved, the planning time is shortened, and the requirements of tourists for visual experience in a travel scene can be met.

Description

Technical Field

[0001] The present invention relates to the technical field of cultural tourism route planning, and specifically to a method for selecting a low-altitude cultural tourism flight route with landscape priority. Background Art

[0002] The rapid development of low-altitude tourism and urban air traffic has led to higher demands for the scenic value of flight routes, and the demand for low-altitude flight route planning is increasing. Traditional flight route planning focuses primarily on flight safety, obstacle avoidance, and path minimization, but pays insufficient attention to utilizing low-altitude scenic resources and improving the flight experience. Consequently, there is a lack of landscape-first route planning techniques.

[0003] The existing technology discloses a method for urban air traffic route network planning for eVTOL. Based on the low-altitude airspace division and the establishment of the eVTOL operation airspace structure model, the divided low-altitude airspace altitude layer is rasterized and modeled. Through the urban low-altitude risk assessment model, the unit grid risk cost is calculated and a visual risk grid map is constructed. The take-off and landing point locations are obtained based on K-means, and the A* algorithm improved with the repeated path penalty factor is used to construct a route network suitable for eVTOL.

[0004] It has the following technical problems:

[0005] The algorithm is highly complex. After the improved A* algorithm introduces risk cost and penalty factors, it needs to perform multiple calculations and evaluations on each grid unit. At the same time, it also needs to perform multi-path searches, which increases the computational burden and leads to longer planning time. Secondly, the algorithm focuses more on obstacle avoidance and risk cost optimization, lacks landscape-oriented path optimization, and cannot meet the visual experience needs of tourists in cultural and tourism scenarios. Summary of the Invention

[0006] In response to the problems existing in the prior art, the purpose of the present invention is to provide a low-altitude cultural and tourism flight route selection method that prioritizes landscape, has a short planning time, can achieve landscape-oriented path optimization, and meet the visual experience needs of tourists in cultural and tourism scenes.

[0007] In order to achieve the above object, the present invention adopts the following technical solutions:

[0008] A method for selecting a low-altitude cultural tourism flight route with landscape priority, comprising the following steps:

[0009] Rasterize the low-altitude cultural and tourism airspace and combine the basic data of the low-altitude cultural and tourism airspace to form a conventional obstacle avoidance visualization raster map;

[0010] Establish a ground landscape evaluation system and a low-altitude landscape attractiveness evaluation system for low-altitude cultural and tourism airspace, and obtain a comprehensive landscape attractiveness visualization map based on the ground landscape evaluation system and the low-altitude landscape attractiveness evaluation system;

[0011] Establish a coordinate system of must-go points based on the highly attractive scenic spots in the low-altitude cultural and tourism airspace;

[0012] The main route of low-altitude cultural tourism is generated based on the conventional obstacle avoidance visualization raster map, the comprehensive landscape attraction visualization map and the coordinate system of the must-pass points.

[0013] Furthermore, the conventional obstacle avoidance visualization grid map adopts a differentiated grid division strategy: a 50m×50m fine grid is used in areas with dense high-rise buildings; a 100m×100m medium grid is used in areas with medium complexity; and a 200m×200m standard grid is used in other areas.

[0014] Furthermore, the ground landscape evaluation system is established based on the greenway system, blueway system and social and cultural system. The greenway system uses vegetation coverage as a quantitative indicator, the blueway system quantifies indicators by evaluating water area and water morphology, and the social and cultural system includes three indicators: the distribution of ground cultural attractions, the population heat of festival activities, and the night light index.

[0015] Furthermore, the low-altitude landscape attractiveness evaluation system is established by selecting landscape aesthetic value, dynamic viewing value, humanistic perception value and environmental compatibility value as indicator factors of low-altitude landscape attractiveness, obtaining standardized data of the indicator factors and using the hierarchical analysis method to calculate the weights of the indicator factors, and calculating the low-altitude landscape attractiveness value based on the weights of the indicator factors and the standardized data of the indicator factors to form a visual raster map of the low-altitude landscape attractiveness evaluation.

[0016] Furthermore, the method for obtaining the comprehensive landscape attraction visualization map is to superimpose the ground landscape evaluation system and the low-altitude landscape attraction evaluation system, use the expert scoring method, calculate the scoring results using the mean square root, obtain the weight ratio of the ground landscape and the low-altitude landscape, and calculate the comprehensive landscape attraction visualization map based on the weight ratio.

[0017] Furthermore, the method of establishing the coordinate system of the must-pass points includes obtaining the geographical coordinates, altitude h, and preset flight altitude H of the highly attractive scenic spots, and calculating the horizontal offset distance D between the scenic spots and the must-pass points based on the human eye pitch angle constraint and the visual composition ratio using the following formula:

[0018]

[0019] Where: D is the horizontal offset distance between the must-pass point and the scenic spot;

[0020] H is the current flight altitude of the aircraft;

[0021] h is the altitude of the scenic spot;

[0022] α is the passenger’s vertical field of view, α∈[8°, 10°].

[0023] Furthermore, the coordinate system of the necessary points adopts a dynamic adaptation strategy for scenic spots at different heights. For high-rise scenic spots with h>H, the lower limit of the comfortable elevation angle of the human eye α=8° is used to calculate the horizontal offset distance; for low-rise scenic spots with h≤H, the upper limit of the comfortable depression angle of the human eye α=10° is used to calculate the horizontal offset distance; within the radius of the horizontal offset distance D, the obstacle avoidance zone is superimposed and checked, and the flyable nodes are selected to obtain the necessary points of the route, providing high-confidence node support for the subsequent generation of a coherent and smooth main channel.

[0024] Furthermore, the method for generating the low-altitude cultural and tourism main channel path includes loading the coordinate system of the starting point, end point, and must-pass point on the conventional obstacle avoidance visualization grid map, obtaining the comprehensive landscape score based on the comprehensive landscape attraction visualization map, and associating the comprehensive landscape score with the grid corresponding to the conventional obstacle avoidance visualization grid map; connecting the starting point, must-pass point, and end point in sequence to obtain multiple continuous sub-paths, updating the actual cost of each sub-path according to the movement cost, so that each sub-path passes through as many grids with high comprehensive scores as possible, thereby generating a low-altitude cultural and tourism main channel route with landscape priority.

[0025] Furthermore, when generating low-altitude cultural and tourism flight routes, the aircraft flies within ±50m of the center line of the main channel. The route from the take-off and landing point to the main channel follows the principle of the shortest distance between two points. When detour is required, local optimization is performed according to the principle of the shortest detour path or a dynamic shortcut mechanism is adopted in different time periods to detour. At the same time, conventional obstacle avoidance and dynamic obstacle avoidance mechanisms are established.

[0026] Furthermore, the dynamic obstacle avoidance mechanism includes triggering 200m path reconstruction when encountering sudden obstacles; initiating emergency avoidance and feedback of instant information when encountering disaster-level obstacles; and triggering 50m radius avoidance when encountering landing obstacles.

[0027] In general, the present invention has the following advantages:

[0028] 1. Coordinated optimization of safety and landscape: Under the premise of ensuring flight safety, a differentiated grid division strategy is used. By establishing a ground and low-altitude landscape attractiveness evaluation system and a mechanism for passing through important landscape nodes, a flight path that takes into account obstacle avoidance needs and landscape experience is generated to enhance the experience and efficiency of low-altitude cultural tourism flights.

[0029] 2. Exploring the economic value of cultural tourism: On the basis of establishing a ground and low-altitude landscape evaluation system, by establishing a mechanism for passing through important landscape nodes, highly attractive landscape nodes are connected in series in the main low-altitude cultural tourism channel, thereby enhancing the immersiveness and narrative nature of low-altitude sightseeing and creating added value for the city's cultural tourism industry.

[0030] 3. Improve dynamic adaptability by establishing flight route selection optimization guidelines that include main channel priority, shortest distance between two points, and graded obstacle avoidance. This supports dynamic adjustment of flight paths and enhances the ability to respond to sudden environmental changes.

[0031] 4. The algorithm of the present invention does not introduce risk costs and penalty factors, and does not require multiple calculations, evaluations, and multi-path searches for each grid cell, which reduces the computational burden, shortens the planning time, and can meet the visual experience needs of tourists in cultural and tourism scenarios. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Figure 1 Schematic diagram of the process of the present invention.

[0033] Figure 2 It is a low-altitude cultural and tourism airspace grid map of an embodiment.

[0034] Figure 3 A conventional obstacle avoidance visualization map is provided for an embodiment.

[0035] Figure 4 This is a table of ground landscape evaluation system.

[0036] Figure 5 Schematic diagram of the low-altitude landscape attractiveness evaluation system, where (a) is the classification of index factors for low-altitude landscape attractiveness, and (b) is the weight value of the index factors for low-altitude landscape attractiveness.

[0037] Figure 6 This is a visualization map of the ground landscape evaluation results of the embodiment.

[0038] Figure 7 This is a visualization map of the low-altitude landscape attractiveness evaluation results for the embodiment.

[0039] Figure 8 This is a visualization map of the comprehensive landscape evaluation results for the example.

[0040] Figure 9 It is a schematic diagram of the main low-altitude cultural tourism channel of the embodiment.

[0041] Figure 10 Schematic diagram of the route optimization principles for low-altitude cultural tourism flight route selection, where (a) is a schematic diagram of conventional obstacle avoidance, fire avoidance, and landing obstacle avoidance, and (b) is a schematic diagram of the path from the take-off point to the main channel and the path between the starting and ending points. DETAILED DESCRIPTION

[0042] The present invention will be described in further detail below.

[0043] With the rapid development of the urban low-altitude economy (such as eVTOL aircraft), low-altitude cultural tourism has become the first focus of the low-altitude economy. This invention proposes a low-altitude flight route selection method with landscape priority, which optimizes the route to enhance the passenger's landscape experience while ensuring flight safety. The invention includes the following contents:

[0044] 1. Division of low-altitude cultural and tourism airspace

[0045] Among the primary applications of the low-altitude economy, low-altitude tourism primarily utilizes manned aircraft such as eVTOLs (electric vertical take-off and landing vehicles). Considering aircraft classification and usage scenarios, eVTOLs typically operate below 300 meters, falling within the low- to medium-altitude airspace. While altitudes below 120 meters fall within the operating range of cargo transport drones, the low-altitude cultural tourism airspace discussed in this example is defined as 120-300 meters.

[0046] The embodiment of the present invention only discusses the method for selecting low-altitude cultural tourism flight routes with landscape priority. If the flight airspace altitude changes, the method of the present invention is still applicable.

[0047] 2. Basic data collection

[0048] The embodiment selects the Guangzhou Tower area that best represents the modern urban landscape of Guangzhou. The building environment and flight conditions in this area are relatively complex in the flight airspace of 120-300m. The embodiment of the present invention gives priority to collecting basic data through GIS and big data, including building distribution and height, scenic spot POI and other data, to support raster modeling of urban airspace height layers.

[0049] 3. Convert the map of the study area into raster

[0050] The map of the core area of ​​10km×10km in Zhujiang New Town, the modern central axis of Guangzhou, was rasterized. Based on basic data and systematic obstacle avoidance principles, a differentiated grid division strategy was adopted: 50m×50m fine grids were preferred in areas with dense high-rise buildings, taking into account both flight safety and landscape resource protection; 100m×100m grids were selected in areas with medium complexity; and 200m×200m standard grids were used in other areas. A multi-scale spatial analysis model was constructed through a three-level grid system to achieve flight path planning that accurately avoids obstacles and coordinates optimization of landscape views, such as Figure 2 .

[0051] 4. Conventional obstacle avoidance map generation

[0052] According to the flight altitude and flight safety requirements of eVTOL, a safe obstacle avoidance area with a vertical distance of 30 meters and a horizontal distance of 50 meters is delineated. Therefore, buildings with a height greater than 90 meters in the basic data are extracted, and obstacle avoidance areas are delineated according to a safe range with a radius of 50 meters to form a conventional obstacle avoidance map, such as Figure 3 ,Within this obstacle avoidance range, no matter how high the landscape attractiveness evaluation score is,,flying is not allowed.

[0053] 5. Establishment of an evaluation system based on ground and low-altitude landscapes

[0054] On the premise of ensuring flight safety, an evaluation system including ground and low-altitude landscapes is designed to improve the landscape quality of flight routes in low-altitude cultural and tourism application scenarios and the flight experience of tourists.

[0055] (1) Ground landscape evaluation system

[0056] The development of the low-altitude economy is inseparable from connections with the ground.

[0057] The establishment of a ground landscape evaluation system is to first meet the visual experience needs of low-altitude cultural tourism. The perspective of low-altitude flight is dynamic and wide-area, and it is necessary to systematically screen ground landscape resources to avoid the limitations of traditional static evaluation and ensure that the flight route can dynamically connect high-quality landscape nodes. The second is to balance the synergistic relationship between safety and landscape. By quantifying the distribution and quality of landscape resources, urban greenways and blueway systems are given priority. The above systems usually have the advantages of few obstacles and high landscape value, which can provide a scientific basis for path optimization. While avoiding risk factors such as no-fly zones and high-voltage lines, they pass through areas with high landscape value, enhancing the appeal of cultural tourism and economic added value. The third is to enhance the adaptability to dynamic environmental changes. By real-time monitoring of ground landscape indicators (such as seasonal changes in vegetation and thermal fluctuations in festival activities), dynamic adjustment of flight paths is supported to ensure emergency obstacle avoidance capabilities in emergencies.

[0058] Therefore, a ground landscape evaluation index system including greenway system, blueway system and social and cultural system is established, such as Figure 4 ,in:

[0059] ① Greenway system (vegetation coverage)

[0060] Greenway systems use vegetation cover as a quantitative indicator, and NDVI (Normalized Difference Vegetation Index) is a common tool for monitoring this indicator. Remote sensing image interpretation and GIS spatial analysis are used to categorize vegetation cover into high, medium, and low levels. A higher average NDVI value within a grid indicates a higher score, while a lower average indicates a lower score. This metric allows for the prioritization of high-vegetation areas during flight route selection. Furthermore, densely forested areas can be designated as emergency landing buffer zones, providing a safety advantage.

[0061] ②Blueway system (spatial distribution of water areas)

[0062] The Blueway system quantifies indicators by assessing water area and morphology (rivers / lakes / wetlands). Based on the spatial distribution vector data of urban water areas in a hydrological GIS, the greater the proportion of water area in the grid, the higher the score, and vice versa.

[0063] The adoption of this indicator can firstly transform the reflection and flow characteristics of the water area into an aerial visual focus, which has a unique landscape. Secondly, it can mark obstacles such as high-voltage towers and bridge heights around the water area, which serves as a safety warning.

[0064] Dynamic supplementation: Integrate hydrological monitoring data to avoid flooded areas during the rainy season and exposed riverbeds during the dry season.

[0065] ③ Social and humanities system

[0066] The social and cultural system includes three indicators: the distribution of ground cultural attractions, the population heat of festival activities, and the night light index, among which:

[0067] The distribution of cultural attractions on the ground refers to the distribution of cultural tourism sites within a city. Using GIS, the kernel density of cultural attractions is generated, revealing their spatial distribution. Within the grid, denser distribution indicates a higher score, while conversely, lower scores indicate a lower score. This metric facilitates the creation of "cultural routes," connecting iconic cultural nodes and enhancing the narrative nature of routes.

[0068] Festival activity demographics predict the spatiotemporal distribution and crowd density of festivals based on mobile phone signaling data and social media POI popularity. High-activity areas are identified using population kernel density analysis, with denser distribution within the grid giving higher scores and vice versa. This metric dynamically matches crowd hotspots, increasing the economic benefits of low-altitude sightseeing while also helping to avoid crowded areas and mitigate safety risks.

[0069] The Night Light Index is calculated by quantifying ground light brightness and categorizing nighttime lighting levels. Higher average Night Light Index values ​​within a grid indicate higher scores, while lower values ​​indicate lower scores. This index can provide visitors with differentiated daytime and nighttime landscapes, providing data support for nighttime excursions and enhancing the flight experience. Furthermore, it can assist with nighttime flight navigation and positioning through ground-based light landmarks, mitigating safety risks.

[0070] (2) Low-altitude landscape attractiveness evaluation system

[0071] ① Establish a low-altitude landscape attractiveness evaluation system:

[0072] Select index factors for the attractiveness of low-altitude landscapes. This system starts from the four aspects of the nature of the low-altitude landscape itself, the perspective from which people view the landscape, cultural value, and ecological value, and determines the four levels of landscape aesthetic value, dynamic viewing value, humanistic perception value, and environmental compatibility value. Among them, landscape aesthetic value includes indicators of the two attributes of landscape time and space: three-dimensional landscape richness, color contrast, and morphological uniqueness at the spatial level; seasonal change index and difference between day and night landscapes at the temporal level; dynamic viewing value includes visual continuity, distribution density of points of interest, and depth of field; humanistic perception value includes important cultural symbols, urban texture expression, and the perceived intensity of humanistic activities; and environmental compatibility value includes ecological sensitivity and meteorological impact coefficient.

[0073] The weight values ​​of the index factors of low-altitude landscape attraction are calculated using the hierarchical analysis method, and a low-altitude landscape attraction evaluation system is established, such as Figure 5 .

[0074] ② Obtain statistical data of low-altitude landscape attractiveness index factors and calculate the statistical data of index factors for low-altitude landscape attractiveness evaluation.

[0075] C1 is the three-dimensional landscape richness, representing the richness of the landscape types at the height layer. The land use data of the embodiment is obtained, and the three-dimensional landscape richness value is obtained by counting the number of patch types in each grid.

[0076] C2 represents color contrast, representing the degree of difference in the dominant color tones across the landscape. By calculating the standard deviation of the grayscale values ​​within each fishing net grid, we can determine the degree of brightness variation within the area. A larger standard deviation indicates a higher contrast, which is then used to determine the color contrast value.

[0077] C3 is morphological uniqueness, which represents the complexity of scenic spots and surface buildings. This indicator is calculated using the Landscape Shape Index (LSI), which is the total length of the patch edge within the unit grid divided by the area. The calculation formula is as follows:

[0078]

[0079] Where E is the total length of the patch edge (building projection) within the unit, and F is the area within the patch.

[0080] C4 is the seasonal variation index, which represents the magnitude of vegetation changes in different seasons. The NDVI (normalized difference vegetation index) time series data for Guangzhou City is obtained, and the seasonal variation index value is obtained based on the seasonal difference between the maximum and minimum NDVI values. The calculation formula is as follows:

[0081]

[0082] Among them: NDVI max is the maximum value of the normalized vegetation index, NDVImin is the minimum value of the normalized difference vegetation index.

[0083] C5 is the difference between day and night landscapes, representing the comparison of landscape recognizability between night light remote sensing data and daytime imagery. The daytime imagery data and NPP-VIIRS nighttime light data (500m resolution) were acquired separately. After registering them to the same coordinate system, the similarity (SSIM) between the two was calculated using Python (skimage library) and reverse normalized. The calculation formula is as follows:

[0084] C5=1-SSIM(D day ,D night )

[0085] Where: SSIM is the structural similarity index (0-1, the smaller the value, the greater the difference), SSIM (D day ,D night ) is the structural similarity index between daytime and nighttime in the embodiment.

[0086] C6 is visual continuity, representing the continuity of different types of patches. The adjacency ratio of each patch was calculated using the Focal Statistics tool in GIS.

[0087] C7 is the point of interest density, representing the number of tourist points of interest (POIs) per unit area. We obtained data from the AutoNavi Maps API and filtered out tourism POIs using the tag "tourism" in ArcGIS. We then calculated the total number of POIs within a grid and divided it by the grid area to obtain the point of interest density. The calculation formula is as follows:

[0088]

[0089] Among them: POI count is the total number of tourist points of interest (POIs) in a single grid, and S is the area of ​​a single grid.

[0090] C8 is the depth of field, which is the depth of the landscape that tourists see when they are taking a tour from the air. This indicator is calculated based on the proportion of the foreground in the image. Low-altitude photos of each node in the embodiment are obtained, and depth maps are batch rendered. The proportion of foreground in each depth map is analyzed by computer to obtain the depth of field value. The calculation formula is as follows:

[0091]

[0092] Among them: F area is the foreground (objects with a distance <100m) pixels in the image, and Image_Area is the entire image pixels.

[0093] C9 is the important cultural landmark, representing the aerial visibility of a city's cultural landmarks. By obtaining publicly available data on cultural heritage landmarks, supplementing their area and height data, and setting the view height in ArcGIS software, we performed a viewshed analysis on each grid point. We calculated the aerial visibility ratio of cultural landmarks, such as World Heritage sites and historical buildings, and divided the number of visible landmarks by the total number to obtain the important cultural landmark value. The calculation formula is as follows:

[0094]

[0095] Among them: CL visible To stipulate the number of cultural landmarks visible at flight altitude, CL total is the total number of cultural heritage landmarks in the study area.

[0096] C10 is the urban texture expression, representing the degree to which spatial features such as the urban road network pattern and the rhythm of building complexes can be discerned from the air. This value is derived by acquiring high-resolution remote sensing images of the city, along with vector data of road networks and building complexes, and performing texture analysis on the images using the gray-level co-occurrence matrix (GLCM). The texture entropy is then calculated to obtain the urban texture expression value. The calculation formula is as follows:

[0097] C10=Entropy(Texture)

[0098] Where: Entropy is the texture entropy value based on the gray-level co-occurrence matrix (GLCM).

[0099] C11 is the degree of visualization of human activities on the ground. It represents the degree of visualization of human activities on the ground. The Baidu map heat map is crawled to extract the heat value of the human flow density in the embodiment area. After rasterization, it is normalized. Combined with the text sentiment tendency of social platforms such as Weibo for this location, its positive ratio is calculated. The heat value of the human flow density (0.7) and the social media sentiment score (0.3) are added to obtain the value of the degree of visualization of human activities. The calculation formula is as follows:

[0100] C11=0.7×Heatmap+0.3×Sentiment score

[0101] Among them: Heatmap is the heat value of the crowd density in the area, Sentiment score Score social media sentiment.

[0102] C12 represents ecological sensitivity, which is expressed as ecological red line data such as nature reserves and bird migration corridors. The ecological red line data is obtained based on the Guangzhou City Master Plan and reversely assigned. That is, the ecological sensitivity value of the grid outside the ecological red line is assigned to 1, and the ecological sensitivity value of the grid inside the red line is assigned to 0.

[0103] C13 is the meteorological impact index, which represents the historical visibility and frequency of cloud and fog. Historical visibility and foggy day data were obtained from the official website of the China Meteorological Administration. The average number of foggy days and visibility for the past five years at regional weather stations were extracted. Visibility was reversed and normalized using a 10km full score. A weighted sum was then taken, and the number of foggy days (0.5) and visibility (0.5) were added together to obtain the meteorological impact index value. The calculation formula is as follows:

[0104] C13=0.5×Fog freq +0.5×Visibilit score

[0105] Among them: Fog freq The average number of foggy days and visibility in the past five years. score Score for historical visibility.

[0106] Subsequently, the calculated data of each index factor of low-altitude landscape attraction are normalized to obtain the standardized data of each index of low-altitude landscape. According to the weight of the index factor and the standardized data of each index factor of low-altitude landscape, the final value of low-altitude landscape attraction is calculated to form a visual raster map of low-altitude landscape attraction evaluation, such as Figure 7 .

[0107] 6. Superposition of ground landscape and low-altitude landscape evaluation results

[0108] The ground landscape evaluation system and the low-altitude landscape attractiveness evaluation system are superimposed. The expert scoring method is used to calculate the scoring results using the mean square root, and the weight ratio of ground landscape is 0.55 and the low-altitude landscape is 0.45. Based on the weight calculation, a comprehensive landscape attractiveness visualization map is formed, such as Figure 8 .

[0109] 7. Mechanism for passing through important landscape nodes

[0110] To further enhance the aerial tour experience for tourists, a mechanism for ensuring critical scenic spots are passed through during flight route selection, based on airspace gridding and landscape attractiveness evaluation. Dynamic offset calculations are implemented for highly attractive scenic spots. This constraint ensures optimal landscape views along the main low-altitude cultural and tourism routes, enhancing the scientific nature and user experience of cultural and tourism route design.

[0111] To determine essential points along a landscape-focused flight route, we need to determine a comfortable pitch angle for the human eye and an optimal landscape ratio within the aircraft's viewfinder. According to the book "The Aesthetics of Streets," a comfortable pitch angle for the human eye is 8°-10°. A review of actual aerial photos of the areas covered by the examples published online revealed that in the most visually appealing photos, the primary landscape and natural surroundings (such as the sky) are typically presented in a 2:1 ratio, adhering to a thirds composition.

[0112] Combining the comfortable pitch angle of the human eye and the thirds composition, the optimal viewing distance is obtained according to the formula at representative landscape points of interest.

[0113] Obtain the geographic coordinates, altitude h, and preset flight altitude H (120-300 meters) of important scenic spots. Based on the optimal pitch angle constraint of the human eye (8°-10°) and the visual composition ratio (thirds composition), divide the difference between the flight altitude and the altitude of the important scenic spot by the sine value of the pitch angle to calculate the horizontal offset distance D between the scenic spot and the must-pass point. This ensures that the aircraft avoids the airspace directly above the scenic spot and can obtain the best landscape visual angle, thereby enhancing the passenger experience.

[0114]

[0115] Where: D is the horizontal offset distance between the must-pass point and the scenic spot (meters);

[0116] H is the current flight altitude of the aircraft (meters);

[0117] h is the altitude of the scenic spot (meters);

[0118] α is the passenger’s vertical field of view (total angle, in degrees), α∈[8°, 10°].

[0119] A dynamic adaptation strategy is adopted for scenic spots at different heights. For high-rise scenic spots (h>H), the offset distance is calculated using the lower limit of the human eye's comfortable elevation angle α=8° to enhance the spacing redundancy between the aircraft and super-high buildings.

[0120] For low-level scenic spots (h≤H), the upper limit of the comfortable depression angle of the human eye α=10° is used to calculate the offset distance to expand the visible range of the ground landscape.

[0121] The flight path is checked against the obstacle avoidance zone within the radius of the horizontal offset distance D, and the flyable nodes are selected to obtain the necessary points on the route, providing high-confidence node support for the subsequent generation of a coherent and smooth main channel.

[0122] 8. Formation of the main low-altitude cultural tourism channel

[0123] Based on the conventional obstacle avoidance visualization grid map, comprehensive landscape attraction evaluation map, and necessary point coordinate system generated in the previous steps, the A* algorithm is used to plan the low-altitude cultural tourism main route. The specific implementation steps are as follows:

[0124] (1) Data loading

[0125] Read the raster data of the conventional obstacle avoidance visualization raster map as the minimum spatial unit for path search; load the vector data of the no-fly zone, starting and ending points, and must-pass points; read the ground landscape score and low-altitude landscape score respectively, and generate a comprehensive landscape score through weighted calculation (ground 55% + low-altitude 45%).

[0126] The landscape score is associated with the corresponding grid through a unique "serial number" field to generate a spatial grid dataset with landscape attributes.

[0127] (2) Path constraint processing

[0128] Traverse all grids, exclude grid cells covered by no-fly zone polygons, generate a valid search grid set, and ensure that the path does not cross the no-fly zone.

[0129] The necessary points are converted into corresponding grid cells. In this embodiment, the first route is connected in order of the east-west starting and ending points and the given seven necessary points; the second route is connected in order of the north-south starting and ending points and the given eight necessary points.

[0130] (3) Implementation of A* algorithm

[0131] First, determine the base cost, which is represented by the distance between the geometric centers of the grids.

[0132] To encourage the algorithm to favor paths with high-quality views (i.e., high overall scores), a movement cost is calculated and a reciprocal method is used to amplify differences in scores. Specifically, the movement cost is calculated by multiplying the base cost by the reciprocal of the current grid's overall score. A higher overall score results in a smaller reciprocal and, consequently, a lower movement cost. Therefore, in areas with high-quality views, the movement cost is reduced, making the algorithm more likely to choose these areas when searching for paths.

[0133] At the heart of the A* algorithm, the calculated movement cost is used to update the actual cost from the starting point to the current cell. When moving from the current cell to an adjacent cell, a temporary actual cost is calculated. If this temporary value is less than the adjacent cell's previous actual cost, the relevant path information is updated and the adjacent cell is added to the set to be searched.

[0134] The search path is segmented, breaking down the entire route into continuous sub-paths of "starting point → necessary point 1 → necessary point 2 →... → end point". The A* algorithm is called segment by segment, and the open set and scoring dictionary are dynamically maintained to record the optimal parent node.

[0135] Use shapely.touches to determine mesh adjacency (i.e. topological connectivity), allowing only cells adjacent to the current mesh edge to be neighbor nodes.

[0136] Finally, two main channels are generated, such as Figure 9 , its path will pass through as many grids with high comprehensive scores as possible, thereby realizing the low-altitude cultural and tourism main route planning with landscape priority.

[0137] 9. Guidelines for optimizing route selection for low-altitude cultural tourism flights

[0138] Based on the low-altitude cultural tourism main route generated by the A* algorithm, a three-in-one low-altitude cultural tourism flight route selection optimization guideline of "main route priority, shortest path, and safe obstacle avoidance" is established, such as Figure 10 , further ensuring flight safety and low-altitude cultural tourism experience, the specific guidelines are as follows:

[0139] (1) Main channel priority principle

[0140] When selecting routes for low-altitude cultural tourism flights, the primary consideration is to use the main low-altitude cultural tourism route as the backbone path, strictly flying within a ±50m range along the centerline of the main route to ensure that more than 80% of the flight distance covers areas with high landscape scores. Following this principle, first, in the application scenario of low-altitude cultural tourism, it can ensure that the landscape is prioritized, thereby enhancing the tourist experience; second, under the constraints of the main low-altitude cultural tourism route, the flight route changes less, facilitating low-altitude flight route control; third, when planning specific routes, it can reduce the repeated calculation of routes with similar cultural tourism needs. Only the route from the take-off and landing point to the main route, as well as obstacle avoidance during take-off and landing, needs to be calculated, greatly shortening planning time and helping to improve the tourist experience.

[0141] (2) Principle of the shortest distance between two points

[0142] ① Take-off and landing connection rules

[0143] The route of the aircraft from the take-off and landing point to the main channel follows the principle of the shortest distance between two points. The length of the connecting section shall not exceed 20% of the total flight distance. When encountering obstacles, local optimization shall be carried out according to the principle of "shortest detour path".

[0144] ②Dynamic shortcut mechanism

[0145] During flight route selection, if a detour is required over a large building complex, a dynamic shortcut mechanism based on time periods is implemented to optimize the flight experience and route continuity. Taking noise into consideration, flights over buildings are permitted during non-sensitive hours (09:00-12:00, 15:00-18:00), while detours are implemented during sensitive hours.

[0146] (3) Principle of graded obstacle avoidance

[0147] ① Conventional obstacle avoidance

[0148] Strictly enforce the no-entry rule in the restricted area (50m radius) of conventional obstacle avoidance maps. High-rise building complexes implement the "double safety distance" standard, that is, vertical spacing ≥30m and horizontal spacing ≥50m.

[0149] ②Dynamic obstacle avoidance

[0150] A "three-level response" obstacle avoidance mechanism is established to address unexpected obstacles, disasters, temporary obstacles, etc. that cannot be predicted in advance, thereby improving the dynamic optimization capabilities of the route:

[0151] Sudden obstacles: Sudden obstacles (such as unregistered drones) trigger 200m path reconstruction;

[0152] Disaster avoidance: When encountering a disaster-level obstacle (such as a high-rise building fire), emergency avoidance is initiated and the disaster reporting system is activated to provide real-time feedback;

[0153] Landing obstacle avoidance: When landing, encountering temporary obstacles (such as temporary structures, flocks of birds, etc.) will trigger a 50m radius avoidance.

[0154] The present invention introduces landscape factors in the application scenario of low-altitude cultural tourism, significantly improving the landscape experience, safety and dynamic adaptability of low-altitude cultural tourism flight routes.

[0155] In terms of landscape experience, a ground-based evaluation system encompassing greenway systems, blueway systems, and social and cultural systems is established, along with a low-altitude landscape attractiveness evaluation system encompassing landscape aesthetics, dynamic viewing value, cultural perception value, and environmental compatibility. Combining the human eye's comfortable viewing angle with the principle of thirds composition, essential points along the main low-altitude cultural and tourism routes are generated. This addresses the issue of existing technologies neglecting landscape connectivity due to a single obstacle avoidance objective, significantly enhancing the visitor experience and immersion. In terms of balancing safety and efficiency, a differentiated grid division strategy and hierarchical obstacle avoidance rules are employed to accurately avoid obstacles while optimizing computing resource allocation. Compared to traditional single-grid models, this significantly reduces the risk of missed obstacles and improves route planning efficiency. In terms of dynamic adaptability, the low-altitude landscape attractiveness evaluation system integrates real-time NDVI vegetation change and festival heat data to update landscape scores. For route optimization, a time-based dynamic shortcut mechanism and hierarchical obstacle avoidance guidelines are designed, overcoming the limitations of existing static models and enabling routes to efficiently respond to seasonal, event-related, and sudden environmental changes, ensuring long-term applicability.

[0156] The above embodiments are preferred implementation modes of the present invention, but the implementation modes of the present invention are not limited to the above embodiments. Any other changes, modifications, substitutions, combinations, and simplifications that do not deviate from the spirit and principles of the present invention should be considered as equivalent replacement methods and are included in the scope of protection of the present invention.

Claims

1. A method for selecting a low-altitude cultural tourism flight route with a priority on landscape, characterized by: The following steps are included: Rasterize the low-altitude cultural and tourism airspace and combine the basic data of the low-altitude cultural and tourism airspace to form a conventional obstacle avoidance visualization raster map; Establish a ground landscape evaluation system and a low-altitude landscape attractiveness evaluation system for low-altitude cultural and tourism airspace, and obtain a comprehensive landscape attractiveness visualization map based on the ground landscape evaluation system and the low-altitude landscape attractiveness evaluation system; Establish a coordinate system of must-go points based on the highly attractive scenic spots in the low-altitude cultural and tourism airspace; The main route of low-altitude cultural tourism is generated based on the conventional obstacle avoidance visualization raster map, the comprehensive landscape attraction visualization map and the coordinate system of the must-pass points.

2. The method according to claim 1, wherein: Conventional obstacle avoidance visualization grid maps use a differentiated grid division strategy: a 50m×50m fine grid is used in areas with dense high-rise buildings; a 100m×100m medium grid is used in areas with medium complexity; and a 200m×200m standard grid is used in other areas.

3. The method according to claim 1, wherein: The ground landscape evaluation system is established based on the greenway system, blueway system and social and cultural system. The greenway system uses vegetation coverage as a quantitative indicator, the blueway system quantifies indicators by evaluating water area and water morphology, and the social and cultural system includes three indicators: the distribution of ground cultural attractions, the population heat of festival activities, and the night light index.

4. The method according to claim 1, wherein: The low-altitude landscape attractiveness evaluation system is established by selecting landscape aesthetic value, dynamic viewing value, humanistic perception value and environmental compatibility value as indicator factors of low-altitude landscape attractiveness, obtaining standardized data of the indicator factors and using the hierarchical analysis method to calculate the weights of the indicator factors, and calculating the low-altitude landscape attractiveness value based on the weights of the indicator factors and the standardized data of the indicator factors to form a visual raster map of the low-altitude landscape attractiveness evaluation.

5. The method according to claim 1, wherein: The method for obtaining the comprehensive landscape attractiveness visualization map is to superimpose the ground landscape evaluation system and the low-altitude landscape attractiveness evaluation system, use the expert scoring method, calculate the scoring results using the mean square root, obtain the weight ratio of the ground landscape and the low-altitude landscape, and calculate the comprehensive landscape attractiveness visualization map based on the weight ratio.

6. The method according to claim 1, wherein: The method of establishing the coordinate system of the must-pass points includes obtaining the geographical coordinates, altitude h, and preset flight altitude H of the highly attractive scenic spots. Based on the human eye's pitch angle constraint and the visual composition ratio, the horizontal offset distance D between the scenic spots and the must-pass points is calculated using the following formula: Where: D is the horizontal offset distance between the must-pass point and the scenic spot; H is the current flight altitude of the aircraft; h is the altitude of the scenic spot; α is the passenger’s vertical field of view, α∈[8°, 10°].

7. The method according to claim 6, characterized in that: The coordinate system of the necessary points adopts a dynamic adaptation strategy for scenic spots at different heights. For high-rise scenic spots with h>H, the lower limit of the comfortable elevation angle of the human eye α=8° is used to calculate the horizontal offset distance; for low-rise scenic spots with h≤H, the upper limit of the comfortable depression angle of the human eye α=10° is used to calculate the horizontal offset distance. Within the radius of the horizontal offset distance D, the obstacle avoidance zone is superimposed and checked, and the flyable nodes are selected to obtain the necessary points of the route, providing high-confidence node support for the subsequent generation of a coherent and smooth main channel.

8. The method according to claim 1, wherein: The method for generating the main route of low-altitude cultural tourism includes loading the coordinate system of the starting point, end point, and necessary points in the conventional obstacle avoidance visualization grid map, obtaining the comprehensive landscape score based on the comprehensive landscape attraction visualization map, and associating the comprehensive landscape score with the grid corresponding to the conventional obstacle avoidance visualization grid map; connecting the starting point, necessary points, and end point in sequence to obtain multiple continuous sub-paths, updating the actual cost of each sub-path according to the movement cost, so that each sub-path passes through as many grids with high comprehensive scores as possible, thereby generating a low-altitude cultural tourism main route with landscape priority.

9. The method according to claim 1, wherein: When generating low-altitude cultural and tourism flight routes, the aircraft flies within ±50m of the center line of the main channel. The route from the take-off and landing point to the main channel follows the principle of the shortest distance between two points. When detour is required, local optimization is carried out according to the principle of the shortest detour path or a dynamic shortcut mechanism is adopted in different time periods. At the same time, conventional obstacle avoidance and dynamic obstacle avoidance mechanisms are established.

10. The method according to claim 9, characterized in that: The dynamic obstacle avoidance mechanism includes triggering 200m path reconstruction when encountering sudden obstacles; initiating emergency avoidance and providing instant feedback when encountering disaster-level obstacles; When encountering a landing obstacle, a 50m radius avoidance is triggered.

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