Site selection planning method based on visible range analysis

Abstract

The invention discloses a site selection planning method based on visual field analysis, and relates to the technical field of site selection planning. According to the method, in a visual field analysis link, a virtual sight line is emitted from a site selection candidate point to each grid of a target area to generate a visual field grid map, and a fishing net range is determined according to a predetermined constraint condition and the candidate points are screened; the visual performance index of each candidate point is determined by calculating multiple indexes including the visual rate, the average intervisibility distance and the intervisibility target ratio, multi-index comprehensive evaluation is more comprehensive and accurate, and the problems that in the prior art, site selection evaluation is not comprehensive enough, only related indexes of a single visual field are concerned, multiple factors influencing site selection are not comprehensively considered, and the site selection evaluation accuracy is poor are solved. And the actual condition of the site selection point is difficult to accurately evaluate.

Description

Technical Field

[0001] This invention relates to the field of site selection planning technology, specifically a site selection planning method based on visibility analysis. Background Technology

[0002] In today's various construction activities, site selection and planning are extremely critical links, and visibility analysis plays an indispensable role in them. In terms of communication base station layout, if scientific planning based on visibility is not carried out, signal coverage blind spots may occur, affecting communication quality.

[0003] However, existing site selection planning methods based on field-of-view analysis still have the following shortcomings in practical applications: On the one hand, the site selection assessment is not comprehensive enough, focusing only on indicators related to a single visible field, failing to comprehensively consider the various factors affecting site selection, and making it difficult to accurately assess the actual situation of the site selection point; On the other hand, existing methods are insufficient in their integration with the actual needs of site selection planning. They fail to fully consider the actual impacts caused by environmental changes in different seasons, resulting in analysis results that cannot provide strong and accurate support for site selection decisions. As a result, they are not effective in practical applications and cannot meet the growing demand for accurate site selection.

[0004] To address this, a site selection planning method based on visual field analysis is proposed. Summary of the Invention

[0005] The purpose of this invention is to solve the problems pointed out in the background art by proposing a site selection planning method based on visibility analysis.

[0006] The objective of this invention can be achieved through the following technical solution: a site selection planning method based on visual field analysis, comprising: Visual field construction: Load the pre-constructed DEM and various geographic feature data of the target area to generate a 3D terrain scene; automatically load DEM data through the raster data read and write interface, process geographic features using vector data parsing algorithms, and generate a 3D scene based on the 3D terrain rendering engine; Candidate point generation: Based on the spatial range of the target area, a fishing net is automatically generated using an equal-spacing grid division algorithm. Within the generated 3D terrain scene, X uniformly distributed grid points are generated using a spatial filling curve algorithm, taking into account the range of the fishing net. The target layers that the grid points need to connect to are determined, and the generated grid points are connected to the target layers that need to be connected. The connection conditions are defined using an SQL-like spatial query language, and grid points that meet the connection conditions are selected as a preliminary set of candidate points for site selection. Visuality analysis: Starting from each candidate point in the site selection candidate point set, a virtual line of sight is emitted to each grid in the target area and a visuality grid map is generated. The visuality grid map generated for each candidate point is analyzed and processed to determine the visual performance index Zi of each candidate point in the site selection candidate point set; where i represents the number of each candidate point in the site selection candidate point set.

[0007] In a preferred embodiment of the present invention, the analysis and processing of the view area raster generated for each candidate point specifically includes: A virtual line of sight is emitted to each grid cell of the target area and a visible field grid map is generated. The visible area is marked as 1 and the blind area is marked as 0. The area of ​​the visible area in the visible field grid map corresponding to each candidate point is counted to obtain the visible field area of ​​each candidate point. The visible field area of ​​each candidate point is divided by the area of ​​the target area to obtain the visibility rate of each candidate point. Calculate the distance from each candidate point to its corresponding visible area, and then average the distances to obtain the average line-of-sight distance for each candidate point. The target layer to which the pre-determined grid points need to be connected is taken as the target point. The target point is found in the visible raster corresponding to each candidate point. The total number of target points is recorded as a, and the number of target points that are visible areas is recorded as b. The see-through target ratio of each candidate point is obtained by calculating b / a.

[0008] In a preferred embodiment of the present invention, determining the visibility performance index Zi of each candidate point in the set of candidate site selection points specifically involves: The visibility, average line-of-sight distance, and line-of-sight ratio of each candidate point are respectively labeled as follows: The minimum allowable visibility, minimum allowable line-of-sight distance, and minimum allowable line-of-sight ratio corresponding to the preset visibility, average line-of-sight distance, and line-of-sight ratio are denoted as follows: ; The visibility performance index Zi for each candidate point is calculated based on the formula; where These are the weighting factors corresponding to visibility, average line-of-sight distance, and line-of-sight ratio, respectively.

[0009] As a preferred embodiment of the present invention, it further includes: Multi-factor evaluation: Collect vegetation cover data for the target area in spring, summer, autumn and winter, analyze the visibility performance index Zi of each candidate point in the candidate point set in different seasons, and perform corresponding steps to determine the annual visibility index Wi of each candidate point; Results push: Based on the annual visibility index Wi of each candidate point in the site selection candidate point set, the site selection planning report is intelligently sorted and pushed to the user.

[0010] In a preferred embodiment of the present invention, the analysis of the visibility performance index Zi of each candidate point in the set of candidate sites in different seasons, and the execution of corresponding steps, specifically include: For the four seasons, mark n evaluation time points respectively; where n>3; calculate the visibility index Zi of each candidate point for each evaluation time point in different seasons, and obtain the seasonal performance index of each candidate point in different seasons by averaging the results; Following the order of spring, summer, autumn and winter, the seasonal performance index corresponding to each candidate point for the four seasons is input into a Cartesian coordinate system. The horizontal axis represents the four seasons, and the vertical axis represents the seasonal performance index. The numerical points corresponding to the seasonal performance index in the Cartesian coordinate system are plotted. For two adjacent sets of numerical points, a vertical line segment is constructed, and the length of the vertical line segment is calculated as the visible span distance between the two adjacent sets of numerical points. After the visible span distance between each set of numerical points is calculated, the average value is taken to obtain the visible span value for each candidate point for the whole year; for the seasonal performance index of each candidate point in the four seasons, the average value is taken to obtain the visible comprehensive value for each candidate point for the whole year.

[0011] In a preferred embodiment of the present invention, determining the annual visibility index Wi of each candidate point specifically involves: The visual variation span value and visual composite value corresponding to each candidate point for the whole year are respectively labeled as follows: The maximum allowable visual variation span value and the minimum allowable visual composite value corresponding to the preset visual variation span value and visual composite value are denoted as follows: ; The annual visibility index Wi for each candidate point is calculated based on the formula; where These are the weighting factors corresponding to the visual variation span value and the visual composite value, respectively.

[0012] In a preferred embodiment of the present invention, the step of intelligently sorting and pushing a site selection planning report to the user based on the annual visibility index Wi of each candidate point in the site selection candidate point set specifically includes: Each candidate point in the set of site selection candidates is sorted from largest to smallest according to the annual visibility index Wi, and the sorting results are filled into a pre-built report template to generate a site selection planning report.

[0013] As a preferred embodiment of the present invention, the step of intelligently sorting and pushing a site selection planning report to the user based on the annual visibility index Wi of each candidate point in the site selection candidate point set further includes: Each candidate point in the site selection candidate point set is sorted from largest to smallest according to the annual visibility index Wi. After sorting, the top three groups of candidate points are selected as preferred points. The results of the sorting of each candidate point in the site selection candidate point set according to the annual visibility index Wi, the sorting of the annual visibility index Wi of the three preferred points, and the sorting of the comprehensive building visibility index of the three preferred points are filled into the pre-built report template to generate the site selection planning report.

[0014] In a preferred embodiment of the present invention, the specific steps for obtaining the preferred point-based comprehensive index are as follows: Obtain the locations of the three preferred sites within the target area, calculate the average transaction price per unit of land parcels within a defined range around the location, and use this as the estimated site selection cost for the three preferred sites; define the cost intervals for each group corresponding to the estimated site selection cost; each cost interval corresponds to a cost surcharge coefficient; after matching the estimated site selection cost of the three preferred sites with each cost interval, multiply the matched cost surcharge coefficient by the annual visibility index Wi of the corresponding preferred site to obtain the comprehensive building visibility index of the three preferred sites.

[0015] Compared with the prior art, the beneficial effects of the present invention are: This invention generates a visual field grid map by emitting virtual lines of sight from candidate sites to each grid cell in the target area during the visual field analysis stage. The range of the fishing net is determined and candidate sites are screened based on predetermined constraints. The visual performance index of each candidate site is determined by calculating multiple indicators such as visibility rate, average line-of-sight distance, and line-of-sight target ratio. The comprehensive evaluation of multiple indicators is more comprehensive and accurate, which solves the problem that the site selection evaluation in the prior art is not comprehensive enough, only focuses on a single visual field-related indicator, fails to comprehensively consider the multiple factors affecting the site selection, and is difficult to accurately evaluate the actual situation of the site selection site. This invention collects vegetation cover data of the target area in spring, summer, autumn and winter, creates an independent three-dimensional terrain scene for each season, calculates the visibility performance index of candidate points in different seasons, and generates a visible field raster map by emitting virtual lines of sight from candidate points in different seasons. Due to different vegetation growth, the visible area and blind area will change. By marking multiple evaluation time points, the seasonal performance index is calculated, and then the visible span distance and visible variation span value are obtained to determine the annual visibility index. This effectively reflects the impact of seasonal changes on site selection, allowing site selection personnel to intuitively and quantitatively understand the visibility changes of candidate points in different seasons and improve the scientific nature of site selection. This invention calculates the estimated site selection cost for the top three candidate sites during the results push phase. This cost is calculated by averaging the transaction prices of surrounding land parcels. A cost range and a cost surcharge coefficient are set, with the cost surcharge coefficient negatively correlated with the estimated site selection cost. The cost surcharge coefficient is then multiplied by the annual visibility index to obtain the comprehensive visibility index. By comprehensively considering performance and cost, and avoiding the selection of excessively expensive locations, this invention achieves a holistic approach to site selection, balancing communication visibility performance and economic cost. Attached Figure Description

[0016] To facilitate understanding by those skilled in the art, the present invention will be further described below with reference to the accompanying drawings.

[0017] Figure 1 This is a flowchart of the present invention. Detailed Implementation

[0018] The technical solution of the present invention will be clearly and completely described below with reference to the embodiments. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0019] Please see Figure 1 As shown, a site selection planning method based on visibility analysis includes: Define the objective: Determine the site selection constraints for communication base stations; these constraints include the purpose of site selection, core requirements, site selection scope, altitude restrictions, and land use type restrictions, etc. For example, the purpose of site selection is to build communication base stations in the target area to improve the coverage quality of the 4G communication network in that area; Core requirement: To achieve a set percentage of visual coverage for major residential areas, factories, and major transportation routes within the target area, ensuring stable signal and reducing signal blind spots; Site selection area: The area must be within the administrative boundaries of the target region, covering an area of ​​approximately 50 square kilometers; Altitude restrictions: 200-800 meters above sea level (avoiding ecological protection areas and steep cliffs); Land use restrictions: It is prohibited to build base stations in basic farmland protection areas and core areas of nature reserves; Data Processing: Topographic data of the current target area is acquired using satellite remote sensing. The collected data is cleaned to remove noise and errors. Data of different formats is uniformly converted to a format supported by GIS software, and coordinate system conversion and registration are performed. A 10m resolution DEM (Digital Elevation Model) is constructed in GIS (Geographic Information System) using the topographic data. Simultaneously, land cover data, including vegetation distribution, building locations, and water bodies, is collected. The locations of existing facilities, such as existing communication base stations, are identified. The road network distribution, including main roads, secondary roads, and rural paths, is determined. The boundary range is precisely delineated using GIS, and the analysis scope corresponding to the target area is determined based on the boundary range. The DEM is cropped, interpolated, and smoothed to remove outliers and improve data quality. Vector data such as buildings and vegetation are converted into raster format to support subsequent occlusion analysis. Visual field construction: DEM data is automatically loaded through raster data read / write interfaces (such as the GDAL library), geographic features are processed using vector data parsing algorithms (such as the Shapely library), and a 3D scene is generated based on a 3D terrain rendering engine (such as Three.js or ArcGIS Pro's 3D API); The geographic element data includes land cover data, existing base station locations, and road network distribution; In the ArcGIS platform, the processed DEM and various geographic feature data are loaded, and its 3D analysis function is used to generate realistic three-dimensional terrain scenes, which intuitively display the suburban topography and landforms and the distribution of land features, providing a foundation for subsequent visibility calculations. Candidate point generation: Based on the spatial range of the target area (represented by a latitude and longitude coordinate matrix), a fishing net is automatically generated using an equal-spacing grid division algorithm. Within the generated 3D terrain scene, combined with the fishing net range, a spatial filling curve algorithm (such as a Hilbert curve) is used to generate X uniformly distributed grid points. The target layers that the grid points need to connect to are determined, and the generated grid points are connected to the target layers that need to be connected. The connection conditions are defined using an SQL-like spatial query language, and grid points that meet the connection conditions are selected as a preliminary set of candidate points for site selection. Visibility analysis: A ray tracing algorithm is used to perform visibility analysis on each candidate point in the site selection candidate point set; such as the Z-Buffer algorithm. Starting from each candidate point in the site selection candidate point set, virtual lines of sight are emitted to each grid cell of the target area, generating a visibility grid map. The visible area is marked as 1, and the blind area is marked as 0. The visibility grid map generated for each candidate point is analyzed and processed to determine the visibility performance index Zi of each candidate point in the site selection candidate point set; where i represents the number of each candidate point in the site selection candidate point set, i=1,2,...,y, and y is the total number of candidate points in the site selection candidate point set. Specifically: S1: Perform area statistics on the visible area within the visible raster map corresponding to each candidate point to obtain the visible area of ​​each candidate point. Divide the visible area of ​​each candidate point by the area of ​​the target area to obtain the visibility rate of each candidate point. The higher the visibility, the better the coverage of the target area by the candidate point; S2: Calculate the distance from each candidate point to its corresponding visible area, and then calculate the average line-of-sight distance for each candidate point. The greater the average line-of-sight distance, the wider the range of signal propagation; S3: Take the target layer that the pre-determined grid points need to connect as the target points, find the target points in the visible raster map corresponding to each candidate point, count the total number of target points as a, count the number of target points that are visible areas as b, and calculate the visibility target ratio of each candidate point by b / a. For example, if a suburb has 5 main residential areas, 3 factories, and 4 main traffic arteries as target points, and an inspection shows that a candidate point is visible to 3 residential areas, 2 factories, and 3 main traffic arteries, then the visibility ratio is (3 + 2 + 3) ÷ (5 + 3 + 4) ≈ 66.7%. S4: Mark the visibility, average line-of-sight distance, and line-of-sight ratio of each candidate point as follows: Based on the core requirements of current communication base station site selection constraints, the minimum allowable visibility, minimum allowable line-of-sight distance, and minimum allowable line-of-sight ratio are preset, respectively, and denoted as follows: ; According to the formula The visibility performance index Zi for each candidate point is calculated; where These are the weighting factors corresponding to visibility, average line-of-sight distance, and line-of-sight ratio, respectively. The weighting factors can be set using an expert scoring method: Expert scoring method: Invite experts from the fields of communications and geographic information systems to score the three parameters of visibility, average line-of-sight distance, and line-of-sight target ratio based on their experience and expertise; for example, experts believe that visibility has the greatest impact on the visibility performance of communication base stations, so it can be given a high weight, such as 0.5; average line-of-sight distance is the second most important, with a weight of 0.3; and the line-of-sight target ratio has a weight of 0.2. Multi-factor evaluation: Using high-resolution satellite remote sensing imagery, vegetation cover data for the target area in spring, summer, autumn and winter are collected. The visibility performance index Zi of each candidate point in the candidate point set in different seasons is calculated, and the corresponding steps are performed to determine the annual visibility index Wi of each candidate point. When calculating the visibility performance index Zi of the site selection candidate points in different seasons, an independent three-dimensional terrain scene is created for each season, and the calculation is based on the vegetation data of the four seasons of spring, summer, autumn and winter. Specifically: Starting from each candidate point in the set of candidate sites in different seasons, virtual lines of sight are emitted to each grid in the target area and a visible field grid map is generated. The visible area and blind area will change due to vegetation growth. For the four seasons, n evaluation time points are marked respectively; where n>3, the duration interval and number between specific time points are preset by technical personnel according to the degree of influence of each season on the target area; calculate the visibility index Zi of each candidate point corresponding to each evaluation time point in different seasons, and obtain the seasonal performance index of each candidate point in different seasons by averaging the results. Following the order of spring, summer, autumn and winter, the seasonal performance index corresponding to each candidate point for the four seasons is input into a Cartesian coordinate system. The horizontal axis represents the four seasons, and the vertical axis represents the seasonal performance index. The numerical points corresponding to the seasonal performance index in the Cartesian coordinate system are plotted. For two adjacent sets of numerical points, a vertical line segment is constructed, and the length of the vertical line segment is calculated as the visible span distance between the two adjacent sets of numerical points. After the visible span distance between each set of numerical points is calculated, the average value is taken to obtain the visible span value for each candidate point for the whole year. The seasonal performance index of each season is plotted on a Cartesian coordinate system to visually show the fluctuations in the visibility performance of candidate points in different seasons. The visibility span distance and the visibility variation span value quantify this seasonal difference, allowing site selection personnel to clearly understand the degree of fluctuation in the visibility performance of each candidate point with the season. For example, a candidate point with a large visibility span distance means that its visibility performance changes drastically in adjacent seasons, which may be detrimental to stable communication. Such locations can be excluded first when selecting a site. For each candidate point, the seasonal performance index for each of the four seasons is averaged to obtain the overall visual value for the whole year for each candidate point. The visual variation span value and visual composite value corresponding to each candidate point for the whole year are respectively labeled as follows: Based on the signal stability requirements in the current communication base station site selection constraints, the maximum allowable visual variation span value and the minimum allowable visual comprehensive value corresponding to the preset visual variation span value and visual comprehensive value are denoted as follows: ; According to the formula The annual visibility index Wi for each candidate point is calculated; where These are the weighting factors corresponding to the visual variation span value and the visual composite value, respectively; Creating independent 3D terrain scenes for each season and calculating the visibility performance index based on vegetation data for different seasons can more accurately reflect the changes in visible area and blind spot caused by seasonal changes in the actual environment, making site selection more in line with the actual situation. By marking multiple evaluation time points to calculate the seasonal performance index, the visible span distance and visible variation span value are obtained, which quantifies the degree of fluctuation of the visibility performance of candidate points with the season. This helps site selection personnel to intuitively and quantitatively understand the changes in visibility of each candidate point in different seasons, and thus prioritize the elimination of locations with large fluctuations in visibility performance based on the signal stability requirements of communication base stations, thereby improving the scientificity and rationality of site selection. Results push: Based on the annual visibility index Wi of each candidate point in the site selection candidate point set, intelligent sorting is performed and a site selection planning report is pushed to the user; Specifically: Each candidate point in the site selection candidate point set is sorted from largest to smallest according to the annual visibility index Wi. After sorting, the top three groups of candidate points are selected as the preferred points. Obtain the location of the three preferred points within the target area, and calculate the average transaction price of the land parcels within a set range around the location as the estimated site selection cost corresponding to the three preferred points. Based on local land market conditions and referencing transaction prices of similar plots in the surrounding area, assess the land acquisition costs required for each preferred location. For example, land prices in preferred locations in the city center may be higher, while land prices in suburban or remote areas may be relatively lower. Set the cost ranges corresponding to the estimated site selection cost; each cost range corresponds to a cost surcharge coefficient; the cost surcharge coefficient is set in the range of 0.957-1.127. The higher the estimated site selection cost, the lower the corresponding cost surcharge coefficient. The specific range of each cost range and the range of the cost surcharge coefficient can be set according to the available construction cost and construction plan of the communication base station. After matching the estimated site selection costs of the three preferred sites with the cost ranges of each group, the cost surcharge coefficients obtained by matching are multiplied by the annual visibility index Wi of the corresponding preferred sites to obtain the comprehensive visibility index of the three preferred sites. The site selection planning report is generated by filling each candidate point in the site selection candidate point set into a pre-built report template according to the ranking results of the annual visibility index Wi, the ranking results of the annual visibility index Wi of the three groups of preferred points, and the ranking results of the comprehensive building visibility index of the three groups of preferred points. Site selection not only considers communication visibility performance but also economic costs, avoiding locations with good visibility but excessively high construction costs, thus achieving a comprehensive consideration of performance and cost.

[0020] The preferred embodiments of the present invention disclosed above are merely illustrative of the invention. These preferred embodiments do not exhaustively describe all details, nor do they limit the invention to specific implementations. Clearly, many modifications and variations can be made based on the content of this specification. This specification selects and specifically describes these embodiments to better explain the principles and practical applications of the invention, thereby enabling those skilled in the art to better understand and utilize the invention. The invention is limited only by the claims and their full scope and equivalents.

Claims

1. A site planning method based on visual field analysis, characterized by, The method comprises the following steps: Visual field construction: automatically load DEM data through the grid data read-write interface, process geographic elements by using a vector data analysis algorithm, and generate a three-dimensional scene based on a three-dimensional terrain rendering engine; Candidate point generation: based on the spatial range of the target area, automatically generate a fishing net by using an equidistant grid division algorithm, and generate X evenly distributed grid points in the generated three-dimensional terrain scene combined with the fishing net range by using a space-filling curve algorithm; determine the target layers required to be connected by the grid points, and connect the generated grid points with the target layers required to be connected; The connection conditions are defined by a SQL-like spatial query language, and the grid points that meet the connection conditions are selected as the preliminary site selection candidate point set; Visual field analysis: from each candidate point in the site selection candidate point set, emit a virtual line of sight to each grid of the target area and generate a visual field grid map, analyze and process the visual field grid map generated by each candidate point, and determine the visual performance index Zi of each candidate point in the site selection candidate point set. Wherein i represents the number of each candidate point in the site selection candidate point set.

2. The method of claim 1, wherein, The analysis and processing of the visual field grid map generated by each candidate point is specifically: Emit a virtual line of sight to each grid of the target area and generate a visual field grid map, mark the visual area as 1 and the blind area as 0; calculate the area of the visual area corresponding to each candidate point in the visual field grid map to obtain the visual area of each candidate point, and divide the visual area of each candidate point by the area of the target area to obtain the visual rate of each candidate point; Calculate the distance from each candidate point to each visual area, and then calculate the average to obtain the average line-of-sight distance of each candidate point; Determine the target layers required to be connected by the grid points as target points, find the target points in the visual field grid map corresponding to each candidate point, count the total number of target points as a, count the number of target points in the visual area as b, and calculate the ratio of b / a to obtain the line-of-sight target ratio of each candidate point.

3. The method of claim 2, wherein, The determination of the visual performance index Zi of each candidate point in the site selection candidate point set is specifically: The visibility, the average visibility distance, and the visibility target ratio of each candidate point are respectively marked as The preset allowable minimum visibility, the allowable minimum visibility distance, and the allowable minimum visibility target ratio corresponding to the visibility, the average visibility distance, and the visibility target ratio are respectively marked as ; According to the formula The visual performance index Zi of each candidate point is calculated; wherein The visual rate, the average visibility distance, and the visibility target ratio correspond to the weight factors, respectively.

4. The method of claim 3, wherein, Further comprising: Multi-factor evaluation: collect vegetation coverage data of the target area in spring, summer, autumn and winter, analyze the visual performance index Zi of each candidate point in the site selection candidate point set in different seasons, and execute corresponding steps to determine the annual visual index Wi of each candidate point; Result pushing: according to the annual visual index Wi of each candidate point in the site selection candidate point set, intelligently sort and push the site selection planning report to the user.

5. The method of claim 4, wherein, The analysis of the visual performance index Zi of each candidate point in the site selection candidate point set in different seasons and the execution of corresponding steps are specifically: For the four seasons, mark n evaluation time points; wherein n>3; calculate the visibility index Zi of each candidate point corresponding to each evaluation time point in different seasons, and obtain the seasonal performance index of each candidate point in different seasons by averaging. The method further comprises the following steps: Multi-factor evaluation: collect vegetation coverage data of the target area in spring, summer, autumn and winter, analyze the visual performance index Zi of each candidate point in the site selection candidate point set in different seasons, and execute corresponding steps to determine the annual visual index Wi of each candidate point; Result pushing: according to the annual visual index Wi of each candidate point in the site selection candidate point set, intelligently sort and push the site selection planning report to the user. The analysis of the visual performance index Zi of each candidate point in the site selection candidate point set in different seasons and the execution of corresponding steps are specifically: For the four seasons, mark n evaluation time points; wherein n>3; calculate the visibility index Zi of each candidate point corresponding to each evaluation time point in different seasons, and obtain the seasonal performance index of each candidate point in different seasons by averaging. According to the order of spring, summer, autumn and winter, the seasonal performance indexes of each candidate point corresponding to the four seasons are input into a plane rectangular coordinate system, the horizontal axis represents the four seasons of spring, summer, autumn and winter, and the vertical axis represents the seasonal performance index, the numerical points corresponding to the seasonal performance indexes in the plane rectangular coordinate system are drawn, a vertical line segment is constructed between two adjacent groups of numerical points, and the length of the vertical line segment is calculated as the visual span distance between the two adjacent groups of numerical points; Until the visual span distance between each group of numerical points is calculated, the average value is obtained as the visual span value of each candidate point corresponding to the whole year; for the seasonal performance indexes of each candidate point in the four seasons, the average value is obtained as the visual comprehensive value of each candidate point corresponding to the whole year.

6. The method of claim 5, wherein, The determination of the annual visual index Wi of each candidate point is specific to: The annual visual change span value and the visual comprehensive value corresponding to each candidate point are respectively marked as , and the preset visual change span value and the visual comprehensive value are respectively marked as ; According to the formula The annual visibility index Wi of each candidate point is calculated; wherein The weight factors corresponding to the visual variation span value and the visual comprehensive value, respectively.

7. The method of claim 6, wherein, The intelligent sorting of the annual visual index Wi of each candidate point in the site selection candidate point set and the push of the site selection planning report to the user are specific to: each candidate point in the site selection candidate point set is sorted from large to small according to the size of the annual visual index Wi, and the sorting result is filled into the pre-constructed report template, so as to generate the site selection planning report.

8. The method of claim 7, wherein, The intelligent sorting of the annual visual index Wi of each candidate point in the site selection candidate point set and the push of the site selection planning report to the user further include: Each candidate point in the site selection candidate point set is sorted from large to small according to the size of the annual visual index Wi, and the top three candidate points in the sorting are selected as preferred points, and the sorting results of the annual visual index Wi of each candidate point in the site selection candidate point set, the annual visual index Wi of the three preferred points and the building visual comprehensive index of the three preferred points are filled into the pre-constructed report template, so as to generate the site selection planning report.

9. The method of claim 8, wherein, The specific steps of obtaining the building visual comprehensive index of the preferred point are: The locations of the three groups of preferred points in the target area are obtained, the average transaction price of the land blocks within the range around the locations is calculated as the site selection estimated cost corresponding to the three groups of preferred points, the cost intervals corresponding to the site selection estimated cost are set, each cost interval corresponds to a cost additional coefficient, the site selection estimated cost of the three groups of preferred points is matched with each cost interval, the cost additional coefficients obtained by the matching are multiplied by the annual visual index Wi of the corresponding preferred point, and the building visual comprehensive indexes of the three groups of preferred points are obtained.

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