CN114219521A - Sports center site selection evaluation method based on multi-source data - Google Patents
Sports center site selection evaluation method based on multi-source data Download PDFInfo
- Publication number
- CN114219521A CN114219521A CN202111426036.2A CN202111426036A CN114219521A CN 114219521 A CN114219521 A CN 114219521A CN 202111426036 A CN202111426036 A CN 202111426036A CN 114219521 A CN114219521 A CN 114219521A
- Authority
- CN
- China
- Prior art keywords
- source data
- sports
- site selection
- index
- sports center
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce
- G06Q30/02—Marketing; Price estimation or determination; Fundraising
- G06Q30/0201—Market modelling; Market analysis; Collecting market data
- G06Q30/0204—Market segmentation
- G06Q30/0205—Location or geographical consideration
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/29—Geographical information databases
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/90—Details of database functions independent of the retrieved data types
- G06F16/95—Retrieval from the web
- G06F16/953—Querying, e.g. by the use of web search engines
- G06F16/9537—Spatial or temporal dependent retrieval, e.g. spatiotemporal queries
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/24—Classification techniques
Abstract
The invention discloses a sports center site selection evaluation method based on multi-source data, which comprises the following steps: establishing an index evaluation frame of the sports center site selection, and determining primary and secondary measurement indexes; determining a measure method of the secondary measure indexes, and determining the weight distribution of the secondary measure indexes by utilizing an analytic hierarchy process; acquiring multi-source data capable of reflecting the conditions of index elements in a preset research area range, and preprocessing the multi-source data; processing the preprocessed multi-source data and a measuring method to obtain measuring results of index elements at all levels; reclassifying and weighting superposition are carried out on the measurement results to obtain a comprehensive result of site selection evaluation; and carrying out difference set processing on the comprehensive results, and eliminating invalid or unreasonable site selection areas in the comprehensive results to obtain the optimal result of site selection of the sports center. The method solves the problems that the existing sports center site selection layout is dominant in subjectivity, lacks rational evaluation and the stadium construction result is unsatisfactory, and can rationally and objectively carry out the site selection work of the sports center.
Description
Technical Field
The invention relates to the technical field of site selection planning design, in particular to a sports center site selection evaluation method based on multi-source data.
Background
In recent years, the development of national economy and the continuous deepening of sports industrialization roads promote the domestic hot tide of building large-scale stadiums, and a plurality of large-scale and high-standard modern sports centers rapidly plan and land in cities at all levels. However, a large number of sports centers are often short in planning time and insufficient in balancing of benefits of each party, so that various stadium utilization and operation problems are exposed after the competition. The site selection planning of the sports center is an extremely important part of city development and is a key foundation for success or failure of later operation. A large number of examples show that improper site selection inevitably brings huge negative effects to cities, sports centers and people using the cities. The existing research on site selection of sports centers mainly focuses on establishment of a site selection principle and qualitative evaluation of a site selection target. Due to the influence of data shortage and technical barriers, the planning and site selection method is single, subjective evaluation occupies large components, and various influence factors are difficult to comprehensively and deeply consider.
Therefore, a method for quantitatively evaluating urban space by using a new data method and more scientifically and objectively completing the site selection work of a sports center is urgently needed.
Disclosure of Invention
The present invention is directed to solving, at least to some extent, one of the technical problems in the related art.
Therefore, the invention aims to provide a sports center site selection evaluation method based on multi-source data, and the method can rationally and objectively carry out site selection work of a sports center.
In order to achieve the purpose, the embodiment of the invention provides a sports center site selection evaluation method based on multi-source data, which comprises the following steps: step S1, establishing an index evaluation frame of the sports center site selection, determining index elements of each level, wherein, the index elements at each level comprise five first-level measurement indexes of urban and rural planning conformity, development location dominance, facility environment soundness, sports space fairness and site traffic convenience, wherein, the urban and rural planning conformity comprises two secondary measurement indexes of a development direction index and an industrial structure index, the development location dominance degree comprises five secondary measurement indexes of land utilization development degree, location condition index, area economic level, site cost and population factor, the facility environment soundness comprises two secondary measurement indexes of engineering infrastructure and social infrastructure, the sports space fairness comprises three secondary measurement indexes of walking fairness, vehicle driving fairness and bus fairness, and the site traffic convenience comprises two secondary measurement indexes of private traffic and public traffic; step S2, determining the measure method of the secondary measure index, and determining the weight distribution of the secondary measure index by using an analytic hierarchy process; step S3, multi-source data which can reflect the condition of index elements in a preset research area range is obtained, and the multi-source data is preprocessed; step S4, processing the preprocessed multi-source data and the measure method by ArcGIS, and sequentially calculating the measure result of the secondary measure index; step S5, reclassifying and weighting superposition are carried out on the measurement results to obtain a comprehensive result of site selection evaluation; and step S6, performing difference set processing on the comprehensive result to eliminate invalid or unreasonable address selection areas in the comprehensive result to obtain the optimal result of the address selection of the sports center.
According to the sports center site selection evaluation method based on the multi-source data, disclosed by the embodiment of the invention, an evaluation framework of the sports center site selection is established at first, all levels of element indexes influencing the site selection are determined, a calculation or evaluation method of each index is provided, and the weight distribution among the indexes is determined by utilizing an analytic hierarchy process; then, acquiring multi-source data capable of reflecting index information of each index of the sports center site selection in a research area, wherein the multi-source data comprises basic geographic information data, government planning data, statistical yearbook, POI data, public comment data, room price data, real-time road condition data and building outline data, and converting the multi-source data into a database through operations such as cleaning, preprocessing and the like; analyzing and evaluating the research area by relying on an ArcGIS geographic information system platform to obtain single and comprehensive measurement results of each index; and finally, the results are screened and rejected in regions, and the optimal region of the sports center site selection is finally obtained, so that the problems that the subjectivity of the existing sports center site selection layout is dominant, the rational evaluation is lacked, and the building result of the stadium is unsatisfactory are solved, the practicability and the operability are high, the site selection practice of the sports center can be reasonably and objectively carried out, and the sustainable construction work of a large-scale stadium is promoted.
In addition, the sports center location evaluation method based on multi-source data according to the above embodiment of the present invention may further have the following additional technical features:
further, in an embodiment of the present invention, the method for measuring the development direction index includes: determining a development direction axis according to a development direction in urban planning, wherein the development direction axis connects an urban center and a new city center to an urban area boundary; calculating a plurality of buffers perpendicular thereto at a fixed distance based on the direction of development axis; the measuring method of the industrial structure index comprises the following steps: selecting a facility type which is coordinated and promoted with the function of the sports center; in ArcGIS, the nuclear density analysis method is used for determining the gathering area of the facility types in cities to obtain the distribution condition of industrial structures.
Further, in an embodiment of the present invention, the method for measuring the land development degree is as follows: dividing a preset research area into a plurality of subareas by using urban street information, counting the ratio of the occupied area of the natural and unchangeable terrain to the total area of the subareas in the subareas by buildings and structures, and normalizing the results after calculating all the results; the measuring method of the zone bit condition index comprises the following steps: identifying the range of the urban center area and determining the boundary of the urban center area; performing buffer area analysis on the boundary of the urban central area to control the change of location conditions by distance factors; the method for measuring the regional economic level comprises the following steps: the distribution of commercial facilities represents the economic development level of a region, and the actual condition and the high-low distribution change of the commercial facilities are determined by using a nuclear density analysis method; the field cost measuring method comprises the following steps: acquiring the housing sale prices contained in all cells in a preset research area to calculate an average value and carry out standardization processing on the average value; calculating the geometric center of each cell, and copying the standardized result to the corresponding point; calculating the price subareas of the preset research area by utilizing a Thiessen polygon method, and covering all ranges; the method for measuring the population factors comprises the following steps: and solving the jurisdiction areas of the township streets by using the spatial positions of the township streets as basic centers and by using a Thiessen polygon method, and assigning the national demographic information to the corresponding areas.
Further, in an embodiment of the present invention, the method for measuring the engineering infrastructure includes: determining the construction condition of engineering infrastructure by using green space distribution, public toilet distribution and road network density, wherein the calculation method of the green space distribution comprises the following steps: obtaining the spatial position and the shape size of a green space, performing nuclear density analysis, and taking the area as a weight influence factor to obtain a quantitative result of green space distribution in a city; the method for calculating the public toilet distribution comprises the following steps: acquiring spatial position information, representing public toilets by points, and representing a road network by lines; then, analyzing by using a nuclear density analysis method, wherein the weight influence factors are respectively controlled by the area of the public toilet, the length of the road and the classification; the measuring method of the social infrastructure comprises the following steps: scientific and educational culture and medical and health facilities are selected as investigation ranges according to the site selection requirements of the sports center, the scientific and educational culture and the medical and health facilities are analyzed by using a nuclear density method, and the grade and the service capacity of the facilities are used as weight influence factors.
Further, in an embodiment of the present invention, the method for measuring the fairness of the sports space is as follows:
and counting various combination strategies that the urban residents can reach the sports space in different traffic modes within preset time, and weighting the obtained result according to the proportion that the residents adopt different traffic modes to obtain the fair distribution condition of the urban sports space.
Further, in an embodiment of the present invention, the method for measuring the convenience of the field traffic in step S2 is as follows: the method for measuring the private traffic comprises the following steps: solving the integration degree of the road network through space syntax software, calculating the spatial distribution attribute of the road network by using a kernel density analysis method, and taking the integration degree and the spatial distribution attribute as weight influence factors for calculation; the measuring method of the public traffic comprises the following steps: the method comprises the steps of carrying out function partitioning and influence grade division on four stations of a bus station, rail transit, a railway and aviation in advance, and adding information of the four stations as weight influence factors for calculation.
Further, in one embodiment of the present invention, the multi-source data includes basic geographic information data, government planning data, statistical yearbook, POI data, public opinion data, house price data, real-time road condition data, and building profile data.
Further, in an embodiment of the present invention, the preprocessing includes cleaning the multi-source data, eliminating invalid information, classifying data, converting a coordinate system, converting data into a form that can be analyzed in ArcGIS, and connecting and assigning field attributes.
Further, in an embodiment of the present invention, the step S5 specifically includes: step S501, reclassifying the measurement results to ensure that the measurement results are all positively added; and step S502, carrying out weighted superposition on the reclassified measurement results to obtain a comprehensive result of the site selection evaluation.
Further, in one embodiment of the invention, the invalid or unreasonable siting areas include areas within a city center, mandatory content not used in the siting index, unmovable terrain or fields in the city and stadiums within 5km range and having competitive relationships.
Additional aspects and advantages of the invention will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the invention.
Drawings
The foregoing and/or additional aspects and advantages of the present invention will become apparent and readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings of which:
FIG. 1 is a flow chart of a sports center siting evaluation method based on multi-source data according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of a sports center site selection evaluation framework of the present invention using Harbin as an example;
FIG. 3 is a diagram illustrating the land exploitation degree measurement result of the present invention using Harbin as an example;
FIG. 4 is a graph showing the population factor results of the present invention using Harbin as an example;
FIG. 5 is a diagram illustrating the results of a social infrastructure measurement using Harbin as an example of the present invention;
FIG. 6 is a diagram illustrating the calculation result of the index weight using Harbin as an example according to the present invention;
FIG. 7 is a graph showing the correspondence between measurement indexes and data used in the present invention, using Harbin as an example;
FIG. 8 is a schematic diagram illustrating reclassification of measurement results using Harbin as an example according to the present invention;
FIG. 9 is a diagram illustrating the weighted overlap-add result of the present invention using Harbin as an example.
Detailed Description
Reference will now be made in detail to embodiments of the present invention, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to the same or similar elements or elements having the same or similar function throughout. The embodiments described below with reference to the drawings are illustrative and intended to be illustrative of the invention and are not to be construed as limiting the invention.
The following describes a sports center location evaluation method based on multi-source data according to an embodiment of the present invention with reference to the accompanying drawings.
Fig. 1 is a flowchart of a sports center location evaluation method based on multi-source data according to an embodiment of the present invention.
As shown in fig. 1, the method for evaluating the location of a sports center based on multi-source data comprises the following steps:
in step S1, an index evaluation framework for the sports center addressing is established, and a secondary measure index is determined.
Specifically, as shown in fig. 2, an index evaluation framework for the sports center site selection taking harbin as an example is established in the embodiment of the present invention, wherein each level of index elements in the index evaluation framework for the sports center site selection specifically include five first-level measurement indexes, namely, five first-level measurement indexes of urban and rural planning compatibility, development site dominance, facility environment soundness, sports space fairness and site traffic convenience; furthermore, the urban and rural planning conformity comprises two secondary measurement indexes of a development direction index and an industrial structure index, the development location dominance comprises five secondary measurement indexes of land exploitation, a location condition index, a regional economic level, site cost and population factors, the facility environment soundness comprises two secondary measurement indexes of an engineering infrastructure and a social infrastructure, the sports space fairness comprises three secondary measurement indexes of walking fairness, vehicle running fairness and bus fairness, and the site traffic convenience comprises two secondary measurement indexes of private traffic and public traffic; besides, the other non-measure indexes are taken as the consideration factors for optimizing the final addressing result.
In step S2, a measure method of the secondary measure index is determined, and a weight distribution of the secondary measure index is determined using a hierarchical analysis method.
It should be noted that the development direction index indicates the deviation or dislocation degree between the location of the site selection and the main direction of urban development, and the higher the development direction index is, the more the site selection of the sports center is matched with the future development direction of the city, and conversely, the more the site selection is not matched with the development direction of the city, even the site is developed reversely.
The industrial structure index indicates the matching degree of the location of the site and the industrial structure of the nearby area, the higher the industrial structure index is, the more the site of the sports center is adapted to the industrial structure of the area, the closer the distance between the site and the industrial structure of the area is, and otherwise, the function of the sports center is not coordinated with the peripheral industry, and the development of the site and the industrial structure of the area are influenced.
The land utilization development degree refers to the development degree of a field around the sports center, wherein the lower the land utilization development degree is, the more remarkable the influence degree of the sports center on the periphery after the sports center is used, more room is provided for later development, and otherwise additional problems of space crowding, difficult traffic evacuation and the like can be faced;
the location condition index refers to the location condition, namely the position of an urban space where a sports center site is located relative to the urban center, the location optimal potential area of the sports center is defaulted to be located at the edge of the urban center area, and the higher the location condition calculation level is, the more the location position is in a compromise position, so that the perfect basic development of the urban center can be enjoyed, and an enough later-stage development space is provided;
the regional economic level refers to the economic development condition of the area around the sports center field, and can refract other multi-aspect information related to the development of the stadium, such as education degree, sports concept and the like, wherein the higher the regional economic development level is, the more advantageous the sports center develops at the place, otherwise, the construction of the stadium is relatively slowed down, and the mutual promotion effect with the periphery is not strong;
the field cost is one of the main costs for building the sports center, namely the purchase and use expenditure of the land, so that the region with lower land price is selected as much as possible in the selection process, and the financial expenditure is reduced;
the population factor refers to the distribution condition of population, which influences the use efficiency of the sports center after the sports center is built, and most of some sports centers with poor operation are lack of surrounding people because of being in suburbs of cities, wherein the population factor in the embodiment of the invention refers to the distribution condition of the space number of urban residents;
the engineering and social infrastructures mean infrastructures required by the construction and development of the sports center, and the spatial distribution condition and the matching perfection degree of the infrastructures have a profound influence on the whole life cycle of the sports center;
the fairness of walking, driving and public transportation refers to the fairness of the quantity and the quality of sports space which can be reached or enjoyed by urban residents in three travel modes within a certain time, and certain sports facilities are more likely to be added in areas with low fairness values to make up for the difference;
private transportation and public transportation generally refer to the convenience of travel that urban residents reach sports centers in different ways, and are related to road conditions, public transportation configuration and the like, and the sports centers are suitable to be built in areas or nearby where transportation is convenient.
Specifically, in the embodiment of the present invention, the method for measuring the secondary measurement index specifically includes the following steps:
the method for measuring the development direction index comprises the following steps: determining a development direction axis according to a development direction in the urban planning, wherein the development direction axis can be a straight line or a broken line, and the development direction axis connects the urban center and the new city center to the boundary of the urban area; then, a plurality of buffers perpendicular thereto are calculated at a fixed distance based on the development direction axis, wherein the score of the development direction index linearly decays in a direction perpendicular to the axis. The calculation formula is as follows:
in the formula, De is a development direction index, a is a constant of 100, D is a side length used for dividing the squares, and D is a total distance of the squares where the urban area farthest from the development axis is located, which is n times of D.
The method for measuring the industrial structure index comprises the following steps: selecting facility types which are coordinated and promoted with the functions of the sports center, wherein the facility types can comprise businesses, residential hotels and the like; in ArcGIS, a nuclear density analysis method is used for determining the concentration area of facility types in cities to obtain the distribution condition of industrial structures. Wherein, the calculation formula of the nuclear density is as follows:
where r is the bandwidth, i.e., the search radius, n is the total number of samples in the range, k is the kernel function, dijThe smaller the search radius is from the point i to the point j, the more the obtained analysis result can display density aggregation in a small range, and the more detailed the obtained information is; the larger the search radius is, the more the macroscopic rule of the spatial data can be reflected, and the smoother the result density grid is displayed. Therefore, the size of the search radius can be determined by those skilled in the art according to the actual situation of the research area, and the data value (including the figure) is used in the following description by taking harbin as an example and adopting the radius of 1000 m.
As shown in fig. 3 and 7, the method for measuring the land development degree is as follows: dividing a preset research area into a plurality of subareas by using urban road network data (eliminating the internal roads of various subareas such as a district, and taking secondary main roads as minimum grading), counting the ratio of the occupied area of buildings, structures and natural and unchangeable terrains (such as water areas and mountainous regions) in the subareas to the total area of the subareas, and normalizing the results after calculating all the results, wherein the specific calculation formula is as follows:
in the formula, the ratio of the developed land in the L (N) peripheral zone area; s1,s2,s3L snRespectively taking up the space occupied areas which have different purposes in the subareas and are included in the calculation; sNIs the total area of the partition unit; formula (4) is a labeled calculation method, nor (A) is a standard value of Amin、AmaxRespectively, represent the minimum and maximum values of all a values.
The measuring method of the zone bit condition index comprises the following steps: the range of the urban center area is identified, and the boundary of the urban center area is defined, so that the buffer analysis is carried out on the boundary of the urban center area, and the change of the position condition is controlled by a distance factor.
The method for identifying the urban central area comprises the following steps: based on techniques commonly used to describe local spatial autocorrelation
The method analyzes the urban street road network, and distinguishes cold and hot spot gathering areas of the urban road network, namely whether space gathering exists in the urban road or not, so as to obtain an approximate area containing an urban center; and then selecting POI points of specific types (in the embodiment of the invention, POIs of accommodation, catering, shopping, living services, science and education culture, transportation facilities and sports and leisure categories are selected), narrowing the range by utilizing a nuclear density analysis method, and extracting the accurate city center. And (3) the types of POI need to be further screened, if at least 70% of points of a certain type of POI exist in the approximate area obtained in the first step, the POI of the type is selected as a part of the calculation of the kernel density, otherwise, the POI of the type is removed.
The method for measuring the regional economic level comprises the following steps: the distribution of commercial facilities (commercial POI) is used for representing the economic development level of a region, and the actual condition and the distribution change of the height are determined by using a nuclear density analysis method.
The field cost measuring method comprises the following steps: acquiring the housing sale prices contained in all cells in a preset research area to calculate an average value and carry out standardization processing on the average value; calculating the geometric center of each cell, and copying the standardized result to the corresponding point; and calculating the price subareas of the preset research area by utilizing a Thiessen polygon method to cover all ranges.
As shown in fig. 4 and 7, the population factor measurement method is as follows: taking the space position (POI point data) of each town street as a basic center, solving the jurisdiction area of each town street by using a Thiessen polygon method, and assigning the national demographic information to the corresponding area.
The measuring method of the engineering infrastructure comprises the following steps: reflecting the construction condition of engineering infrastructure by using three factors of green space distribution, public toilet distribution and road network density, wherein the calculation method of the green space distribution comprises the following steps: obtaining the spatial position and the shape size of a green space, performing nuclear density analysis, and taking the area as a weight influence factor to obtain a quantitative result of green space distribution in a city; the public toilet distribution calculation method comprises the following steps: acquiring spatial position information, representing public toilets by points, and representing a road network by lines; then, analyzing by using a nuclear density analysis method, wherein the weight influence factors are respectively controlled by the area of the public toilet, the length of the road and the classification; the integration of the three factors represents the construction condition of the urban engineering infrastructure.
As shown in fig. 5 and 7, the social infrastructure (social infrastructure refers to facilities and services mainly serving social markets, social policies, social objectives, and mainly medical health, education, welfare services, public service facilities, etc.) is measured by: scientific and educational culture and medical health facilities (POI point data) are selected as investigation ranges according to the site selection requirements of the sports center, the scientific and educational culture and the medical health facilities are analyzed by using a nuclear density method, and the grade and the service capacity of the facilities are used as weight influence factors.
The method for measuring the fairness of the sports space comprises the following steps: and counting various combination strategies that the urban residents can reach the sports space in different traffic modes within preset time, and weighting the obtained result according to the proportion that the residents adopt different traffic modes to obtain the fair distribution condition of the urban sports space.
In particular, sports space fairness includes space fairness in walking, driving, and transit modes. The calculation method is to count the conditions that urban residents can reach the sports space by adopting different traffic modes within a certain time, and obtain the fair distribution condition of the urban sports space according to the result obtained by weighting the proportion that the residents adopt different traffic modes. Areas with low spatial equity values are more demanding for public stadiums. In the embodiment of the invention, the following formula is used for calculating the space fairness under walking and driving modes:
wherein A isjIs the public sports space equity value of the house j in walking mode; t is tijAs the shortest time to walk from residence j to sports space i, tij≤t0；t0The maximum time in the walking mode is 15min in the embodiment of the invention; siA service capability for a sports space i; piThe comprehensive evaluation value of the crowd to the sports space, namely the scores of the public critique; g (T)ij) For simplicity, the gaussian time decay function can represent the change of the influence of walking time on the spatial fairness. After all the results are calculated, the calculated values need to be standardized according to the category of the sports space.
The calculation formula in the driving situation is similar to the above, except that the calculation process is changed to driving, tijIs the shortest time from driving in a house to a sports space, the driving speed is calculated according to 40km/h, t0Increasing from 15min to 30 min; g (T)ij) And (3) representing the influence change function of the driving travel time on the space fairness.
In the embodiment of the invention, the following formula is used for calculating the space fairness under the public transportation mode:
Tij＝wi+pij+wj (8)
wherein A isjThe public sports space equity value of the residence in the public transportation mode; t is tijThe shortest bus travel time from the residence to the sports space; siAnd PiHas the same meaning as in formula (5); g (T)ij) Is calculated in the same manner as in the formula (6), t0The maximum time of the bus trip mode is 30min in the embodiment; n is a radical ofiIs the number of bus stations within 400m of the perimeter of the sports space, wiIs the average time of walking to all bus stations within range; n is a radical ofjIs the number of bus stations within 600m of the perimeter of the residence, wjIs walking to all bus stations in the rangeThe average time of (d); p is a radical ofijIs the travel time from the departure bus station to the destination bus station, and the bus travel speed is calculated at 10km/h in this embodiment. After all the results are calculated, the calculation results need to be standardized.
The method for measuring the private traffic comprises the following steps: solving the integration degree of the road network through space syntax software, calculating the spatial distribution attribute of the road network by using a kernel density analysis method, and taking the integration degree and the spatial distribution attribute as weight influence factors for calculation;
the measuring method of the public traffic comprises the following steps: the method comprises the steps of carrying out function partitioning and influence grade division on bus stations, rail transit, railways, aviation and other stations in advance, adding information of the four stations as weight influence factors for calculation, calculating the conditions of the bus stations and bus lines by adopting a kernel density method, and reflecting the distribution condition of urban public transport by combining the bus stations and the bus lines.
Further, although the embodiments of the present invention employ an analytic hierarchy process, those skilled in the art may select a more suitable type based on more modifications, and the methods are not limited thereto. It should be noted that, the use of the analytic hierarchy process should be specifically analyzed according to specific problems, and the obtained weights should be different for the practice of locating the sports center in different cases. In the embodiment of the invention, the analytic hierarchy process software yaahp is used for weight calculation.
After the determination of the measure method of the secondary measure index is completed, the weight distribution of the secondary measure index, which takes harbin as an example, is determined by using an analytic hierarchy process, and the result is shown in fig. 6.
In step S3, multi-source data that can reflect the condition of the index element within the preset study region range is obtained, and the multi-source data is preprocessed.
Specifically, the multi-source data of the embodiment of the invention comprises basic geographic information data, government planning data, statistical yearbook, POI data, public comment data, room price data, real-time road condition data and building outline data, and the fineness degree and the information content of the data can be determined according to the requirements of site selection indexes.
Further, in a preferred embodiment of the present invention, the preprocessing includes cleaning the multi-source data, eliminating invalid information, classifying data, converting coordinate system, converting data into a form that can be analyzed in ArcGIS, and connecting and assigning field attributes, which refers to corresponding preparation work related to the data before analysis.
In step S4, the preprocessed multi-source data and the measure method are processed by ArcGIS, and measure results of the two-level measure indexes are sequentially obtained.
In step S5, the measurement results are reclassified and weighted and superimposed to obtain a comprehensive result of site selection evaluation.
Specifically, as shown in fig. 8 and 9, in the embodiment of the present invention, the re-classification and weighted stacking are performed on the measurement results, and the re-classification results should adopt the same classification setting, including the classification method and the number of categories; after reclassification, the values of all measurement results are ensured to be added in the forward direction, namely high value areas of some measurement results possibly indicate that the measurement results are not suitable for site selection of a sports center, and new values are inverted during reclassification; in the embodiment of the invention, the reclassification method is equal intervals, and the classification is 10; and (4) weighted superposition, wherein the weight is determined by an analytic hierarchy process.
In step S6, difference set processing is performed on the integrated result to remove invalid or unreasonable addressing areas in the integrated result, so as to obtain the optimal result of the addressing of the sports center.
The method for eliminating invalid or unreasonable address selection areas in analysis results mainly comprises the following steps: range within a city center; mandatory content which is not used in the site selection index, namely land use property regulation in urban planning, and the range of a research area is required to be screened according to related content; unmovable terrains or sites in cities, including historic and cultural buildings and building groups, large public buildings, urban major infrastructure, mountain forest land rivers and lakes, and the like; other stadiums that may have significant competitive relationships with the sports center may have a range of 5km from them to be culled.
According to the sports center site selection evaluation method based on the multi-source data, disclosed by the embodiment of the invention, by firstly establishing an evaluation framework of the sports center site selection, all levels of element indexes influencing site selection are determined, a calculation or evaluation method of each index is provided, and the weight distribution among the indexes is determined by utilizing an analytic hierarchy process; then, acquiring multi-source data capable of reflecting index information of each index of the sports center site selection in a research area, wherein the multi-source data comprises basic geographic information data, government planning data, statistical yearbook, POI data, public comment data, room price data, real-time road condition data and building outline data, and converting the multi-source data into a database through operations such as cleaning, preprocessing and the like; analyzing and evaluating the research area by relying on an ArcGIS geographic information system platform to obtain single and comprehensive measurement results of each index; and finally, the results are screened and rejected in regions, and the optimal region of the sports center site selection is finally obtained, so that the problems that the subjectivity of the existing sports center site selection layout is dominant, the rational evaluation is lacked, and the building result of the stadium is unsatisfactory are solved, the practicability and the operability are high, the site selection practice of the sports center can be reasonably and objectively carried out, and the sustainable construction work of a large-scale stadium is promoted.
Furthermore, the terms "first", "second" and "first" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one such feature. In the description of the present invention, "a plurality" means at least two, e.g., two, three, etc., unless specifically limited otherwise.
In the description herein, references to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above are not necessarily intended to refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Furthermore, various embodiments or examples and features of different embodiments or examples described in this specification can be combined and combined by one skilled in the art without contradiction.
Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention, and that variations, modifications, substitutions and alterations can be made to the above embodiments by those of ordinary skill in the art within the scope of the present invention.
Claims (10)
1. A sports center site selection evaluation method based on multi-source data is characterized by comprising the following steps:
step S1, establishing an index evaluation frame of the sports center site selection, determining index elements of each level, wherein, the index elements at each level comprise five first-level measurement indexes of urban and rural planning conformity, development location dominance, facility environment soundness, sports space fairness and site traffic convenience, wherein, the urban and rural planning conformity comprises two secondary measurement indexes of a development direction index and an industrial structure index, the development location dominance degree comprises five secondary measurement indexes of land utilization development degree, location condition index, area economic level, site cost and population factor, the facility environment soundness comprises two secondary measurement indexes of engineering infrastructure and social infrastructure, the sports space fairness comprises three secondary measurement indexes of walking fairness, vehicle driving fairness and bus fairness, and the site traffic convenience comprises two secondary measurement indexes of private traffic and public traffic;
step S2, determining the measure method of the secondary measure index, and determining the weight distribution of the secondary measure index by using an analytic hierarchy process;
step S3, multi-source data which can reflect the condition of index elements in a preset research area range is obtained, and the multi-source data is preprocessed;
step S4, processing the preprocessed multi-source data and the measure method by ArcGIS, and sequentially calculating the measure result of the secondary measure index;
step S5, reclassifying and weighting superposition are carried out on the measurement results to obtain a comprehensive result of site selection evaluation;
and step S6, performing difference set processing on the comprehensive result to eliminate invalid or unreasonable address selection areas in the comprehensive result to obtain the optimal result of the address selection of the sports center.
2. The multi-source data-based sports center siting evaluation method according to claim 1,
the method for measuring the development direction index comprises the following steps: determining a development direction axis according to a development direction in urban planning, wherein the development direction axis connects an urban center and a new city center to an urban area boundary; calculating a plurality of buffers perpendicular thereto at a fixed distance based on the direction of development axis;
the measuring method of the industrial structure index comprises the following steps: selecting a facility type which is coordinated and promoted with the function of the sports center; in ArcGIS, the nuclear density analysis method is used for determining the gathering area of the facility types in cities to obtain the distribution condition of industrial structures.
3. The multi-source data-based sports center siting evaluation method according to claim 1,
the method for measuring the land exploitation degree comprises the following steps: dividing a preset research area into a plurality of subareas by using urban street information, counting the ratio of the occupied area of the natural and unchangeable terrain to the total area of the subareas in the subareas by buildings and structures, and normalizing the results after calculating all the results;
the measuring method of the zone bit condition index comprises the following steps: identifying the range of the urban center area and determining the boundary of the urban center area; performing buffer area analysis on the boundary of the urban central area to control the change of location conditions by distance factors;
the method for measuring the regional economic level comprises the following steps: the distribution of commercial facilities represents the economic development level of a region, and the actual condition and the high-low distribution change of the commercial facilities are determined by using a nuclear density analysis method;
the field cost measuring method comprises the following steps: acquiring the housing sale prices contained in all cells in a preset research area to calculate an average value and carry out standardization processing on the average value; calculating the geometric center of each cell, and copying the standardized result to the corresponding point; calculating the price subareas of the preset research area by utilizing a Thiessen polygon method, and covering all ranges;
the method for measuring the population factors comprises the following steps: and solving the jurisdiction areas of the township streets by using the spatial positions of the township streets as basic centers and by using a Thiessen polygon method, and assigning the national demographic information to the corresponding areas.
4. The multi-source data-based sports center siting evaluation method according to claim 1,
the measuring method of the engineering infrastructure comprises the following steps: determining the construction of the engineering infrastructure by green space distribution, public toilet distribution and road network density, wherein,
the method for calculating the greenbelt distribution comprises the following steps: obtaining the spatial position and the shape size of a green space, performing nuclear density analysis, and taking the area as a weight influence factor to obtain a quantitative result of green space distribution in a city;
the method for calculating the public toilet distribution comprises the following steps: acquiring spatial position information, representing public toilets by points, and representing a road network by lines; then, analyzing by using a nuclear density analysis method, wherein the weight influence factors are respectively controlled by the area of the public toilet, the length of the road and the classification;
the measuring method of the social infrastructure comprises the following steps: scientific and educational culture and medical and health facilities are selected as investigation ranges according to the site selection requirements of the sports center, the scientific and educational culture and the medical and health facilities are analyzed by using a nuclear density method, and the grade and the service capacity of the facilities are used as weight influence factors.
5. The multi-source data-based sports center site selection evaluation method of claim 1, wherein the sports space fairness measurement method is as follows:
and counting various combination strategies that the urban residents can reach the sports space in different traffic modes within preset time, and weighting the obtained result according to the proportion that the residents adopt different traffic modes to obtain the fair distribution condition of the urban sports space.
6. The multi-source data-based sports center siting evaluation method according to claim 1,
the method for measuring the private traffic comprises the following steps: solving the integration degree of the road network through space syntax software, calculating the spatial distribution attribute of the road network by using a kernel density analysis method, and taking the integration degree and the spatial distribution attribute as weight influence factors for calculation;
the measuring method of the public traffic comprises the following steps: the method comprises the steps of carrying out function partitioning and influence grade division on four stations of a bus station, rail transit, a railway and aviation in advance, and adding information of the four stations as weight influence factors for calculation.
7. The sports center site selection evaluation method based on multi-source data according to claim 1, wherein the multi-source data comprises basic geographic information data, government planning data, statistical yearbook, POI data, public comment data, house price data, real-time road condition data and building outline data.
8. The multi-source data-based sports center addressing evaluation method according to claim 1, wherein the preprocessing comprises cleaning the multi-source data, eliminating invalid information, classifying data, converting a coordinate system, converting data into a form that can be analyzed in ArcGIS, and connecting and assigning field attributes.
9. The multi-source data-based sports center addressing evaluation method according to claim 1, wherein step S5 specifically comprises:
step S501, reclassifying the measurement results to ensure that the measurement results are all positively added;
and step S502, carrying out weighted superposition on the reclassified measurement results to obtain a comprehensive result of the site selection evaluation.
10. The sports center siting evaluation method according to claim 1, wherein said invalid or unreasonable siting areas include areas within a city center, mandatory content not used in siting indexes, unmovable terrain or fields in a city and competitive stadiums within 5 km.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111426036.2A CN114219521A (en) | 2021-11-26 | 2021-11-26 | Sports center site selection evaluation method based on multi-source data |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111426036.2A CN114219521A (en) | 2021-11-26 | 2021-11-26 | Sports center site selection evaluation method based on multi-source data |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN114219521A true CN114219521A (en) | 2022-03-22 |
Family
ID=80698624
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202111426036.2A Pending CN114219521A (en) | 2021-11-26 | 2021-11-26 | Sports center site selection evaluation method based on multi-source data |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN114219521A (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117252745A (en) * | 2023-11-20 | 2023-12-19 | 河北省交通规划设计研究院有限公司 | Public service facility site selection method and device and computer equipment |
| CN117540939A (en) * | 2024-01-10 | 2024-02-09 | 武汉市规划编审中心(武汉规划展示馆) | Square dance floor site selection method based on space syntax and vision field segmentation method |
-
2021
- 2021-11-26 CN CN202111426036.2A patent/CN114219521A/en active Pending
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117252745A (en) * | 2023-11-20 | 2023-12-19 | 河北省交通规划设计研究院有限公司 | Public service facility site selection method and device and computer equipment |
| CN117252745B (en) * | 2023-11-20 | 2024-03-12 | 河北省交通规划设计研究院有限公司 | Public service facility site selection method and device and computer equipment |
| CN117540939A (en) * | 2024-01-10 | 2024-02-09 | 武汉市规划编审中心(武汉规划展示馆) | Square dance floor site selection method based on space syntax and vision field segmentation method |
| CN117540939B (en) * | 2024-01-10 | 2024-04-09 | 武汉市规划编审中心(武汉规划展示馆) | Square dance floor site selection method based on space syntax and vision field segmentation method |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109327841B (en) | Multi-dimensional evaluation and accurate construction evaluation method based on coverage and value association | |
| Parks et al. | Characterizing neighborhood pedestrian environments with secondary data | |
| CN108764193A (en) | Merge the city function limited region dividing method of POI and remote sensing image | |
| CN114219521A (en) | Sports center site selection evaluation method based on multi-source data | |
| WO2023050955A1 (en) | Urban functional zone identification method based on function mixing degree and ensemble learning | |
| Andersen et al. | Catchment areas for public transport | |
| CN108182196B (en) | Urban traffic demand prediction method based on POI | |
| CN112184282A (en) | Cinema site selection model establishing method, cinema site selection method and cinema site selection platform | |
| Ahmed et al. | A GIS-assisted optimal Baghdad metro route selection based on multi criteria decision making | |
| CN108876075A (en) | Urban Rail Transit Stations area preferably walkability evaluation method | |
| CN116308956B (en) | City region leading function and planning use difference detection method | |
| CN117151800A (en) | Rural land foundation land price assessment method | |
| Kazak et al. | Land use change in suburban zone: European context of urban sprawl | |
| CN114971061A (en) | Emergency rescue base site selection optimization method | |
| Thériault et al. | GIS-based simulation of accessibility to enhance hedonic modeling and property value appraisal: an application to the Quebec city metropolitan area | |
| Wibowo et al. | Harnessing open data and technology for the study of accessibility: The case of Indonesia’s capital site candidate | |
| Moudon et al. | A transportation-efficient land use mapping index | |
| Boitor et al. | A new tool for the evaluation of co2 emissions from road traffic: a case study in cluj-napoca, romania | |
| Blachowski et al. | Application of multi-criteria analysis in GIS for optimal planning of house development areas. Case study of Wrocław Functional Area | |
| Ertugay et al. | Understanding accessibility: Accessibility modeling with geographical information systems (GIS) | |
| Bhadra et al. | An objective assessment of walkability in Khulna City: A GIS based approach | |
| CN115909030A (en) | Small micro-green land supplementary addressing method based on machine learning | |
| Saghapour | Accessible neighbourhoods: towards active transportation | |
| CN118036820A (en) | Public charging pile site selection and configuration method, system and device considering air pollutants | |
| Saleh et al. | GIS for planning a sustainable and inclusive community: multi-criteria suitability analysis for siting low-income housing in a sustainable community and suitable neighborhood in Buffalo Metropolitan Area, New York |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |