A spatial decision-making method and device for the site selection and layout of indemnificatory housing

Abstract

The present invention discloses a spatial decision-making method and device for the site selection and layout of indemnificatory housing. Grid sampling is performed on the benchmark land price data of residential land to obtain benchmark land price sampling points; spatial interpolation is performed on the land price sampling points to obtain benchmark land price information; plots with a benchmark land price lower than a set value are selected from the land price information as the first area; a space with a distance from the city center less than or equal to a preset distance is selected as the second area; the intersection of the first area, the second area and the planned land is taken to obtain the indemnificatory housing candidate area; the accessibility scores of the plots in the candidate area are obtained, and the indemnificatory housing is laid out according to the accessibility scores, and the local spatial segregation index of each street is calculated to obtain the indemnificatory housing layout plan. The present invention can analyze and process geographical information and applicant family data, improving the accuracy of site selection and layout. By simulating different housing layout plans and calculating the spatial segregation index, the over-concentration of low- and middle-income families is avoided.

Description

Technical Field

[0001] The present invention relates to the technical field of the site selection and layout of indemnificatory housing, and particularly to a spatial decision-making method and device for the site selection and layout of indemnificatory housing. Background Art

[0002] With the rapid development of urbanization, the fair and effective allocation and configuration of indemnificatory housing have become an urgent challenge for many cities. The existing site selection and layout methods and technologies for indemnificatory housing often face the following problems: In terms of construction site selection, due to considerations of land costs and complex real estate market conditions, traditional indemnificatory housing projects are often built in the urban fringe areas, ignoring the needs of low- and middle-income residents for basic public services such as education, medical care, and transportation; in terms of construction layout, the existing technologies do not fully consider the possible residential space segregation and social class differentiation caused by large-scale concentrated construction of indemnificatory housing, which is likely to increase social problems. In view of the above problems, a systematic solution that takes into account both the site selection and layout processes of indemnificatory housing is urgently needed. Summary of the Invention

[0003] The present invention solves the above technical problems existing in the prior art by providing a spatial decision-making method and device for the site selection and layout of indemnificatory housing.

[0004] The present invention provides a spatial decision-making method for the site selection and layout of indemnificatory housing, including:

[0005] Performing grid sampling on the obtained benchmark land price data of residential land to obtain benchmark land price sampling points of residential land;

[0006] Performing spatial interpolation on the benchmark land price sampling points of residential land, and removing the areas corresponding to non-construction land to obtain benchmark land price information of residential land that can reflect the land supply cost;

[0007] Selecting the plots with benchmark land prices lower than the set upper limit value from the benchmark land price information of residential land as the first candidate areas;

[0008] Selecting a spatial range with a distance from the town center less than or equal to a preset distance as the second candidate area;

[0009] Taking the intersection of the first candidate area, the second candidate area, and the planned residential land plots to obtain a candidate area for indemnificatory housing construction;

[0010] Obtaining the accessibility scores of public service facilities for each plot in the candidate area for indemnificatory housing construction, arranging the indemnificatory housing in descending order according to the accessibility scores of public service facilities for each plot, and calculating the local spatial segregation index of each street through the formula where i and j are both street areas; n is the total number of streets in the city; bi is the number of households living in affordable housing in street i; a j is the number of households living in commercial housing in street j; c ij is the adjacent weight matrix; represents the degree of interaction between the affordable housing households in street i and the commercial housing households in the streets adjacent to i; represents the degree of interaction between the affordable housing households in street i and the commercial housing households in the whole city;

[0011] When the local spatial segregation index LSI of a certain street reaches or exceeds the preset upper limit value, stop arranging the construction quantity of affordable housing in this area, and at the same time increase the layout of affordable housing in other streets until an affordable housing layout plan is obtained in which the local spatial segregation index LSI of each street is within an acceptable range.

[0012] Specifically, the selected spatial range with a distance from the urban center less than or equal to the preset distance is used as the second candidate area, including:

[0013] According to the obtained POI data of various functional facilities, comprehensively identify the center of the city by using kernel density analysis, hot spot analysis and weighted overlay analysis methods;

[0014] Use buffer analysis to select the area within the preset maximum radiation distance from the center of the city as the second candidate area.

[0015] Specifically, obtaining the accessibility scores of public service facilities for each plot in the candidate area for affordable housing construction includes:

[0016] For the obtained POI data of various public service facilities, set multiple buffer distances and establish non-overlapping multi-ring buffers;

[0017] Assign scores to each buffer ring in the non-overlapping multi-ring buffers, with the scores decreasing from the center to the periphery to obtain the score information of the non-overlapping multi-ring buffer layer;

[0018] Mark the score information of the non-overlapping multi-ring buffer layer to the candidate area for affordable housing construction to obtain the accessibility scores of public service facilities for each plot in the candidate area for affordable housing construction.

[0019] Specifically, after obtaining the affordable housing layout plan in which the local spatial segregation index LSI of each street is within an acceptable range, it further includes:

[0020] Spatial interpolation is performed on the sample prices of commercial housing projects and the sample prices of affordable housing projects, and the areas corresponding to non-construction land are excluded to obtain commercial housing market price information and affordable housing guiding price information respectively;

[0021] Subtract the affordable housing guiding price information from the commercial housing market price information to obtain a spatial welfare score;

[0022] For the affordable housing with a relatively high spatial welfare score in the affordable housing layout plan, increase the purchase price, rental price and / or shorten the usage period to obtain an optimized affordable housing layout plan; for the affordable housing with a relatively low spatial welfare score in the affordable housing layout plan, reduce the purchase price, rental price and / or extend the usage period to obtain an optimized affordable housing layout plan.

[0023] Specifically, it further includes:

[0024] Obtain the application information of the applicants for affordable housing;

[0025] Calculate the demand degree scores of affordable housing for each applicant by weighted summation of the data in the application information;

[0026] Based on the housing preference information in the application information, allocate the affordable housing in the affordable housing layout plan to each applicant in descending order of the demand degree score.

[0027] The present invention also provides a spatial decision-making device for the site selection and layout of affordable housing, including:

[0028] A grid sampling unit for performing grid sampling on the obtained benchmark land prices of residential land to obtain benchmark land price sampling points of residential land;

[0029] A first spatial interpolation unit for performing spatial interpolation on the benchmark land price sampling points of residential land and excluding the areas corresponding to non-construction land to obtain benchmark land price information of residential land that can reflect the land supply cost;

[0030] A first candidate area screening unit for screening out the plots with benchmark land prices lower than the set upper limit value from the benchmark land price information of residential land as the first candidate areas;

[0031] A second candidate area selection unit for selecting a spatial range with a distance from the town center less than or equal to a preset distance as the second candidate area;

[0032] An affordable housing construction candidate area obtaining unit for taking the intersection of the first candidate area, the second candidate area and the planned residential land plots to obtain an affordable housing construction candidate area;

[0033] A public service facility accessibility score acquisition unit, which is used to acquire the public service facility accessibility scores of each plot in the candidate area for the construction of indemnificatory housing;

[0034] A local spatial segregation index calculation unit, which is used to layout indemnificatory housing in descending order according to the public service facility accessibility scores of each plot, and calculate the local spatial segregation index of each street through the formula where i and j are both street areas; n is the total number of streets in the city; b i is the number of indemnificatory housing families living in street i; a j is the number of commercial housing families living in street j; c ij is the adjacency weight matrix; represents the degree of interaction between indemnificatory housing families in street i and commercial housing families in adjacent streets of i; represents the degree of interaction between indemnificatory housing families in street i and commercial housing families in the whole city;

[0035] An indemnificatory housing layout plan acquisition unit, which is used to stop laying out the number of indemnificatory housing construction in a certain area when the local spatial segregation index LSI of a certain street reaches or exceeds the preset upper limit value, and at the same time increase the layout of indemnificatory housing in other streets until an indemnificatory housing layout plan is obtained in which the local spatial segregation index LSI of each street is within an acceptable range.

[0036] Specifically, the second candidate area selection unit includes:

[0037] An urban center identification subunit, which is used to comprehensively identify the center of the city according to the obtained point-of-interest data of various functional facilities by using kernel density analysis, hot spot analysis and weighted overlay analysis methods;

[0038] A second candidate area selection subunit, which is used to select, by using buffer analysis, an area within a preset maximum radiation distance from the center of the city as the second candidate area.

[0039] Specifically, the public service facility accessibility score acquisition unit includes:

[0040] A multi-ring buffer establishment subunit, which is used to set multiple buffer distances for the obtained point-of-interest data of various public service facilities and establish non-overlapping multi-ring buffers;

[0041] A buffer ring scoring subunit, which is used to assign scores to each buffer ring in the non-overlapping multi-ring buffers, and the scores decrease from the center to the periphery to obtain the score information of the non-overlapping multi-ring buffer layer;

[0042] A score information identification subunit, configured to identify the score information of the non-overlapping multi-ring buffer layers to the candidate areas for indemnificatory housing construction, so as to obtain the accessibility scores of public service facilities for each plot in the candidate areas for indemnificatory housing construction.

[0043] Specifically, it further includes:

[0044] A second spatial interpolation unit, configured to perform spatial interpolation on the obtained sample prices of commercial housing projects and sample prices of indemnificatory housing projects, and exclude the areas corresponding to non-construction land, so as to obtain commercial housing market price information and indemnificatory housing guiding price information respectively;

[0045] A spatial welfare score obtaining unit, configured to subtract the indemnificatory housing guiding price information from the commercial housing market price information to obtain a spatial welfare score;

[0046] An indemnificatory housing layout plan optimization unit, configured to increase the purchase price, rental price, and / or shorten the usage period for the indemnificatory housing with a higher spatial welfare score in the indemnificatory housing layout plan to obtain an optimized indemnificatory housing layout plan; for the indemnificatory housing with a lower spatial welfare score in the indemnificatory housing layout plan, reduce the purchase price, rental price, and / or extend the usage period to obtain an optimized indemnificatory housing layout plan.

[0047] Specifically, it further includes:

[0048] An application information obtaining unit, configured to obtain the application information of applicants for indemnificatory housing;

[0049] A demand degree score calculation unit, configured to calculate the demand degree scores of indemnificatory housing for each applicant in a weighted summation manner of the data items in the application information;

[0050] An indemnificatory housing allocation unit, configured to allocate the indemnificatory housing in the indemnificatory housing layout plan to each applicant in descending order of the demand degree scores based on the housing preference information in the application information.

[0051] One or more technical solutions provided in the present invention have at least the following technical effects or advantages:

[0052] 1. First, conduct grid sampling on the obtained residential land benchmark land price data to obtain residential land benchmark land price sampling points; then perform spatial interpolation on the residential land benchmark land price sampling points, excluding the areas corresponding to non-construction land, to obtain residential land benchmark land price information that can reflect the land supply cost; then screen out the plots with benchmark land prices lower than the set upper limit value from the residential land benchmark land price information as the first candidate area; select the spatial range with a distance less than or equal to the preset distance from the town center as the second candidate area; take the intersection of the first candidate area, the second candidate area, and the planned residential land plots to obtain the candidate area for affordable housing construction; then obtain the public service facility accessibility scores of each plot in the candidate area for affordable housing construction, arrange the affordable housing in descending order according to the public service facility accessibility scores of each plot, and calculate the local spatial segregation index of each street; when the local spatial segregation index of a certain street reaches or exceeds the preset upper limit value, stop arranging the number of affordable housing construction in this area, and at the same time increase the affordable housing layout in other streets until an affordable housing layout plan is obtained where the local spatial segregation index of each street is within an acceptable range. The present invention can analyze and process geographical information and applicant family data more precisely, be more dynamic and responsive to market and social changes, not only improve the accuracy of site selection and layout, but also make the allocation of affordable housing more reasonable, thereby optimizing the resource utilization efficiency and response speed. By simulating different housing layout plans and calculating the spatial segregation index, it effectively avoids the excessive concentration of low- and middle-income families, helps to achieve community diversity, and promotes social integration and harmony.

[0053] 2. By analyzing the specific needs and living preferences of applicant families, personalized allocation of housing resources can be achieved, which not only improves the fairness of housing allocation, but also enhances the satisfaction and quality of life of residents. At the same time, by accurately calculating spatial welfare and adjusting housing purchase (rent) prices and usage periods, the equal distribution of spatial welfare is promoted, fully considering the spatial welfare and differences in residents' needs at different spatial locations, making the allocation of public service resources more reasonable. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] Figure 1 is a flowchart of the spatial decision-making method for the site selection and layout of affordable housing provided by an embodiment of the present invention;

[0055] Figure 2 is a schematic diagram of the digital elevation model (DEM) of the residential land benchmark land price in an embodiment of the present invention;

[0056] Figure 3 is a schematic diagram for evaluating the accessibility of public service facilities in the candidate area for affordable housing construction in an embodiment of the present invention;

[0057] Figure 4It is a schematic diagram of calculating spatial welfare in an embodiment of the present invention;

[0058] Figure 5 It is a module diagram of a spatial decision-making device for the site selection and layout of indemnificatory housing provided by an embodiment of the present invention;

[0059] Figure 6 It is a module and flowchart of a spatial decision-making support system for the site selection, layout, and allocation of indemnificatory housing constructed by a spatial decision-making method and device for the site selection and layout of indemnificatory housing provided by an embodiment of the present invention. Detailed implementation manners

[0060] By providing a spatial decision-making method and device for the site selection and layout of indemnificatory housing, an embodiment of the present invention solves the technical problems existing in the prior art.

[0061] The technical solution in the embodiment of the present invention for solving the technical problems existing in the prior art has the following general idea:

[0062] A. Input of basic information

[0063] Input the information of indemnificatory housing applicant families and urban basic geographic information, screen out the applicant families with the qualification to purchase (rent) houses, and establish a database of indemnificatory housing to be built and a database of urban basic geographic information.

[0064] A1. Input of applicant family information: Initially input the basic information covering all indemnificatory housing applicant families in the city, including the economic status of the family, the existing housing status, family member information, and specific housing preference information.

[0065] A2. Examination of the qualification to purchase (rent) houses and establishment of the database to be built: According to the local indemnificatory housing policy, examine the qualification of applicant families to purchase (rent) houses, and the data that pass the examination are assigned IDs and stored in the database to be built.

[0066] A3. Input of urban basic geographic information: Input the land use planning data of the city, the base land price map of residential land, the sample price data of commercial housing projects, the sample price data of indemnificatory housing projects, and the point of interest (POI) data of facilities such as commerce, medical care, education, culture, public transportation, and financial services.

[0067] B. Processing of housing demand and housing preference

[0068] Sort the housing demands according to the economic status, housing status, and other factors of the family, and establish a database of housing preference information of applicant families on this basis. The specific steps are as follows:

[0069] B1. Calculate the housing demand degree and sort it to form a priority arrangement database to be built;

[0070] B2. Processing residential preference information: Extract residential preference information from the prioritized database to be built in step B1, organize its spatial preferences and housing type preferences respectively, and store them in the corresponding databases. At the same time, identify and adjust the preference information that does not meet the regulations, such as excessive room area or unreasonable location selection. Among them, the spatial preference information includes geographical location, and the housing type preference information includes spatial living area, room layout, floor, orientation, and lighting, etc. According to the family's spatial preference information, the family's need for job-housing balance can be accurately met, reducing traffic congestion and time costs. According to the housing type preference information, the needs of families in different family life cycles can be accurately met.

[0071] C. Preliminary site selection considering land cost and geographical location

[0072] Through Geographic Information System technology (GIS tool), comprehensively consider land cost and geographical location to determine reasonable candidate addresses for affordable housing. Considering economic benefits, the city center or other high-value areas are not suitable for building affordable housing projects, while overly remote geographical locations will affect the living convenience, job opportunities, and the ability of low- and middle-income families to access urban infrastructure. Therefore, the site selection will avoid the city center area with high land costs and ensure that it is not overly remote to guarantee the living convenience of residents. For this purpose, the preliminary site selection steps are as follows:

[0073] C1. Land cost assessment and preliminary screening: Comprehensively consider the actual demolition cost of the construction land for affordable housing (the demolition cost generated by demolishing the original building) and the potential opportunity cost (the loss of income generated by developing into other uses) to ensure the economic rationality of the site selection. Among them, the potential opportunity cost is reflected by the local benchmark land price of residential land. The specific steps of land cost assessment and preliminary screening are as follows:

[0074] C11. Constructing the land supply cost DEM: Conduct spatial interpolation on the sampling points of the benchmark land price of residential land to construct a digital elevation model (DEM) of the benchmark land price of residential land. The DEM of the benchmark land price of residential land can comprehensively consider land cost and geographical location factors.

[0075] C12. Setting the upper limit of land supply cost and preliminarily screening candidate areas: According to the project budget and local policies, set an upper limit value of the benchmark land price. This value should reflect the highest land cost that the government can accept to ensure the economic feasibility of the project. Use the GIS tool to extract the range value from the DEM of the benchmark land price of residential land, and screen out the plots with a benchmark land price lower than the set upper limit value as candidate area H1.

[0076] C2. Geographical location assessment and preliminary screening: Select a suitable spatial range from the distance to the town center as candidate area H2 to ensure the living convenience of residents.

[0077] C3. Generate candidate site selection areas considering land supply cost and geographical location comprehensively: On the basis of excluding high-opportunity-cost areas in the central region and avoiding overly remote areas, conduct the optimal site selection according to land cost and geographical location. Using GIS tools, take the intersection of candidate area H1 in step C1 and candidate area H2 in step C2 to obtain candidate area H3 that meets both conditions; take the intersection of candidate area H3 and the residential land plots in the land use planning data input in A3 to generate candidate areas H4 for the construction of indemnificatory housing.

[0078] D. Balanced layout considering facility accessibility and residential segregation

[0079] Based on candidate areas H4 for the construction of indemnificatory housing determined in step C, in the actual layout, it is necessary to meet the basic accessibility of public facilities and avoid the over-concentration of middle- and low-income groups to achieve a balanced layout. The specific steps are as follows:

[0080] D1. Evaluate the accessibility of public facilities: Use urban public facility POI data and the method of multi-ring buffers to evaluate the accessibility of various public service facilities to candidate areas.

[0081] D2. Layout indemnificatory housing one by one according to the accessibility size and monitor the local spatial segregation index in real time: Layout indemnificatory housing one by one according to the accessibility size. Based on administrative division data at the street scale, synchronously calculate the local spatial segregation index of each street using the number of families living in commercial housing and the number of families living in indemnificatory housing. To avoid residential segregation caused by the over-aggregation of low-income families, control the construction quantity of indemnificatory housing within the street range to prevent the local spatial segregation index from exceeding the upper limit value. Specifically, set an acceptable upper limit for the local spatial segregation index. When the local spatial segregation index of a certain street reaches or exceeds the upper limit value, stop laying out the construction quantity of indemnificatory housing in this area, and at the same time increase the layout in other streets. Specifically, use linear programming model solving to simulate different housing layout schemes to ensure that the local spatial segregation indices of all streets are within the acceptable range, avoid social segregation phenomena, and obtain the optimal indemnificatory housing layout scheme.

[0082] E. Micro-allocation of housing considering spatial welfare and residential preferences

[0083] On the basis of the balanced layout of the quantity of indemnificatory housing in step D, conduct housing allocation according to the spatial preference information of applicant families, and at the same time adjust the purchase, rental amount or usage period to achieve the efficient and fair allocation of housing spatial welfare. The specific steps are as follows:

[0084] E1. Spatial welfare evaluation: Use the difference between the market price of commercial housing and the guiding price of indemnificatory housing to reflect the spatial welfare value contained in indemnificatory housing in a certain area of the city, which is the spatial welfare.

[0085] E2. Adjust the purchase, rental prices and usage periods of indemnificatory housing to achieve an equal and reasonable distribution of housing space welfare. By this method, the space welfare obtained by different families when purchasing or renting indemnificatory housing can be balanced.

[0086] E3. Allocate housing according to space preferences and housing type preferences: On the basis of adjusting prices and usage periods in step E2, allocate housing according to the reasonable family space preference information in the to-be-built database arranged in the priority order in step B, so as to be as close as possible to the workplace or the preferred area to reduce commuting time and transportation costs. After allocating to the corresponding space area, then allocate specific housing types according to housing type preferences, and finally form an indemnificatory housing allocation plan that can meet the personalized needs of each applicant family for work and life convenience as much as possible.

[0087] To better understand the above technical solution, the above technical solution will be described in detail below in conjunction with the accompanying drawings of the specification and specific implementation manners.

[0088] As Figure 1 shown, the spatial decision-making method for the site selection and layout of indemnificatory housing provided by the embodiment of the present invention includes:

[0089] Step S110: Perform grid sampling on the obtained residential land base land price data to obtain residential land base land price sampling points;

[0090] Step S120: Perform spatial interpolation on the residential land base land price sampling points, and exclude the areas corresponding to non-construction land to obtain residential land base land price information that can reflect the land supply cost;

[0091] Specifically describe this step. Performing spatial interpolation on the residential land base land price sampling points and excluding the areas corresponding to non-construction land to obtain residential land base land price information that can reflect the land supply cost includes:

[0092] Perform spatial interpolation on the residential land base land price sampling points by the natural neighbor interpolation method, and exclude the areas corresponding to non-construction land such as rivers, lakes, etc., to obtain a digital elevation model (DEM) of the residential land base land price that can reflect the land supply cost, as Figure 2 shown.

[0093] Step S130: Screen out the plots with base land prices lower than the set upper limit value from the residential land base land price information as the first candidate areas;

[0094] Step S140: Select the spatial range with a distance from the town center less than or equal to the preset distance as the second candidate area;

[0095] Specifically describe this step. Select a spatial range with a distance less than or equal to the preset distance from the town center as the second candidate area, including:

[0096] Based on the obtained point-of-interest data of various functional facilities, comprehensively identify the center of the city using kernel density analysis, hot spot analysis, and weighted overlay analysis methods. It should be noted that the identified city center can be one or multiple.

[0097] Use buffer analysis to select an area within the preset maximum radiation distance from the center of the city as the second candidate area to ensure that the location of the affordable housing is not too remote, facilitating residents' commuting and daily life.

[0098] Step S150: Take the intersection of the first candidate area, the second candidate area, and the planned residential land plots to obtain the candidate area for affordable housing construction;

[0099] Step S160: Obtain the accessibility scores of public service facilities for each plot in the candidate area for affordable housing construction. Arrange the affordable housing in descending order according to the accessibility scores of public service facilities for each plot, that is, preferentially select locations with high accessibility of public facilities as the actual construction sites for affordable housing, and arrange the number of affordable housing one by one. And through the formula Calculate the local spatial segregation index for each street; where i and j are both street areas; n is the total number of streets in the city; b i is the number of affordable housing families living in street i; a j is the number of commercial housing families living in street j; c ij is the adjacency weight matrix; its value is 1 when i and j are adjacent, and its value is 0 when i and j are not adjacent, and i can be equal to j; represents the degree of interaction between affordable housing families in street i and commercial housing families in adjacent streets of i; represents the degree of interaction between affordable housing families in street i and commercial housing families throughout the city; The local spatial segregation index LSI refers to the degree of residential segregation of the affordable housing family group among spatial units, and the larger its value, the greater the degree of segregation.

[0100] Specifically, as Figure 3 shown, obtain the accessibility scores of public service facilities for each plot in the candidate area for affordable housing construction, including:

[0101] For the obtained point-of-interest data of various public service facilities, set multiple buffer distances and establish non-overlapping multi-ring buffers;

[0102] Assign scores to each buffer ring in the non-overlapping multi-ring buffer, with the scores decreasing from the center to the periphery to reflect the accessibility scores at different distances, and obtain the score information of the non-overlapping multi-ring buffer layer;

[0103] Identify the score information of the non-overlapping multi-ring buffer layer in the candidate areas for affordable housing construction, and obtain the accessibility scores of public service facilities for each plot in the candidate areas for affordable housing construction.

[0104] Step S170: When the local spatial isolation index LSI of a certain street reaches or exceeds the preset upper limit value, stop arranging the quantity of affordable housing construction in this area, and at the same time increase the layout of affordable housing in other streets until an affordable housing layout plan is obtained in which the local spatial isolation index LSI of each street is within an acceptable range.

[0105] Specifically, solve through a linear programming model to simulate the affordable housing layout plan of the entire city, and finally select an affordable housing layout plan with relatively small average and variance of the local spatial isolation index of each street.

[0106] In order to optimize the affordable housing layout plan, after obtaining an affordable housing layout plan in which the local spatial isolation index LSI of each street is within an acceptable range, it also includes:

[0107] Perform spatial interpolation on the obtained sample point prices of commercial housing projects and sample point prices of affordable housing projects, and exclude the areas corresponding to non-construction land to obtain commercial housing market price information and affordable housing guiding price information respectively;

[0108] Specifically explain this step. Perform spatial interpolation on the obtained sample point prices of commercial housing projects and sample point prices of affordable housing projects, and exclude the areas corresponding to non-construction land to obtain commercial housing market price information and affordable housing guiding price information respectively, including:

[0109] Based on GIS tools, perform spatial interpolation on the obtained sample point prices of commercial housing projects and sample point prices of affordable housing projects respectively through ordinary Kriging spatial interpolation method, and exclude the areas corresponding to non-construction land such as rivers, lakes, etc., to obtain commercial housing market price DEM and affordable housing guiding price DEM respectively.

[0110] Subtract the affordable housing guiding price information from the commercial housing market price information to obtain the spatial welfare score;

[0111] Specifically explain this step, as Figure 4 shown, subtract the affordable housing guiding price information from the commercial housing market price information to obtain the spatial welfare score, including:

[0112] Using the raster calculation tool, subtract the DEM of the guiding price of indemnificatory housing from the DEM of the market price of commercial housing to obtain the DEM of spatial welfare, and the value on the DEM of spatial welfare is the spatial welfare score.

[0113] For the indemnificatory housing with a relatively high spatial welfare score in the layout scheme of indemnificatory housing, increase the purchase price, rental price and / or shorten the usage period to obtain an optimized layout scheme of indemnificatory housing; for the indemnificatory housing with a relatively low spatial welfare score in the layout scheme of indemnificatory housing, reduce the purchase price, rental price and / or extend the usage period to obtain an optimized layout scheme of indemnificatory housing.

[0114] To reasonably allocate indemnificatory housing, it further includes:

[0115] Obtain the application information of the applicants for indemnificatory housing;

[0116] Calculate the demand degree scores of indemnificatory housing for each applicant in the way of weighted summation of the data in the application information;

[0117] Specifically, based on the indicators of the economic status, housing status and other factors of the applicant's family, calculate the housing demand degree of each family, and sort them according to the value size to ensure that the families most in need of housing are guaranteed first. Among them, the economic status indicators are per capita income of the family, per capita assets of the family, etc., the housing status indicators are per capita housing usage area of the family, safety of the building structure, etc., and the other factor indicators are special member needs, employment situation, etc.

[0118] The specific steps are as follows: ①Formulate a scoring standard and score single indicators: Formulate a scoring standard for each indicator, set the score range from 0 to 10 points, and then score each indicator of each family to obtain the single housing demand degree. For example, the scoring standard for the per capita income of the family indicator is: families with per capita income lower than 10% of the median per capita income of the city get 2 points, lower than 30% get 6 points, lower than 50% get 10 points, etc. ②Set the indicator weights: According to local policies and the specific needs of the target group, set weights for different indicators. For example, among all indicators, the weight of per capita income of the family can be set as a relatively large value. ③Calculate the total housing demand degree by weighted calculation: Weight and sum up the single housing demand degrees of all indicators to obtain the total housing demand degree of each family. ④Sort the total housing demand degrees: Sort all applicant families according to the size of the total housing demand degree to form a priority arrangement database for construction to be built. Among them, families with higher total housing demand degree scores will be given priority to obtain indemnificatory housing resources.

[0119] Based on the housing preference information in the application information, affordable housing in the affordable housing layout plan is allocated to each applicant in descending order of the demand score. Among them, the housing preference information includes: geographical location, spatial living area, room layout, floor, orientation, lighting, etc.

[0120] As Figure 5 shown, the spatial decision-making device for the site selection and layout of affordable housing provided by the embodiment of the present invention includes:

[0121] A grid sampling unit 100, configured to perform grid sampling on the obtained benchmark land price data of residential land to obtain benchmark land price sampling points of residential land;

[0122] A first spatial interpolation unit 200, configured to perform spatial interpolation on the benchmark land price sampling points of residential land, and exclude the areas corresponding to non-construction land to obtain benchmark land price information of residential land that can reflect the land supply cost;

[0123] Specifically, the first spatial interpolation unit 200 is specifically configured to perform spatial interpolation on the benchmark land price sampling points of residential land by using the natural neighbor interpolation method, and exclude the areas corresponding to non-construction land such as rivers and lakes to obtain a digital elevation model (DEM) of the benchmark land price of residential land that can reflect the land supply cost.

[0124] A first candidate area screening unit 300, configured to screen out the plots with benchmark land prices lower than the set upper limit value from the benchmark land price information of residential land as the first candidate area;

[0125] A second candidate area selection unit 400, configured to select a spatial range with a distance from the town center less than or equal to a preset distance as the second candidate area;

[0126] Specifically, the second candidate area selection unit 400 includes:

[0127] An urban center identification subunit, configured to comprehensively identify the center of the city according to the obtained point-of-interest data of various functional facilities by using kernel density analysis, hot spot analysis, and weighted overlay analysis methods; it should be noted that the identified urban center can be one or more.

[0128] A second candidate area selection subunit, configured to use buffer analysis to select an area within a preset maximum radiation distance from the center of the city as the second candidate area to ensure that the site selection location of affordable housing is not too remote and is convenient for residents' commuting and daily life.

[0129] An affordable housing construction candidate area obtaining unit 500, configured to take the intersection of the first candidate area, the second candidate area, and the planned residential land plots to obtain an affordable housing construction candidate area;

[0130] A public service facility accessibility score obtaining unit 600 is configured to obtain the public service facility accessibility scores of each plot in the candidate areas for indemnificatory housing construction;

[0131] Specifically, the public service facility accessibility score obtaining unit 600 includes:

[0132] A multi-ring buffer establishing subunit, which is configured to set multiple buffer distances for the obtained point-of-interest data of various public service facilities and establish non-overlapping multi-ring buffers;

[0133] A buffer ring scoring subunit, which is configured to assign scores to each buffer ring in the non-overlapping multi-ring buffers, and the scores decrease from the center to the periphery to reflect the accessibility scores at different distances, so as to obtain the score information of the non-overlapping multi-ring buffer layer;

[0134] A score information identifying subunit, which is configured to identify the score information of the non-overlapping multi-ring buffer layer in the candidate areas for indemnificatory housing construction, so as to obtain the public service facility accessibility scores of each plot in the candidate areas for indemnificatory housing construction.

[0135] A local spatial segregation index calculating unit 700 is configured to arrange indemnificatory housing in descending order of the public service facility accessibility scores of each plot, that is, preferentially select the locations with high public facility accessibility as the actual construction locations of indemnificatory housing, and arrange the number of indemnificatory housing one by one. And through the formula calculate the local spatial segregation index of each street; where i and j are both street areas; n is the total number of streets in the city; b i is the number of indemnificatory housing families living in street i; a j is the number of commercial housing families living in street j; c ij is the adjacent weight matrix; its value is 1 when i and j are adjacent, and its value is 0 when i and j are not adjacent, and i can be equal to j; represents the degree of interaction between the indemnificatory housing families in street i and the commercial housing families in the streets adjacent to i; represents the degree of interaction between the indemnificatory housing families in street i and the commercial housing families in the whole city; the local spatial segregation index LSI refers to the degree of residential segregation of the indemnificatory housing family group among spatial units, and the larger its value, the greater the degree of segregation.

[0136] An indemnificatory housing layout plan obtaining unit 800 is configured to stop arranging the number of indemnificatory housing construction in a certain street when the local spatial segregation index LSI of the street reaches or exceeds the preset upper limit value, and at the same time increase the indemnificatory housing layout in other streets until an indemnificatory housing layout plan is obtained in which the local spatial segregation index LSI of each street is within an acceptable range.

[0137] To optimize the layout plan of indemnificatory housing, it further includes:

[0138] A second spatial interpolation unit, configured to perform spatial interpolation on the obtained sample prices of commercial housing projects and the sample prices of indemnificatory housing projects, exclude the regions corresponding to non-construction lands, and respectively obtain the market price information of commercial housing and the guiding price information of indemnificatory housing;

[0139] Specifically, the second spatial interpolation unit is specifically configured to, based on a GIS tool, perform spatial interpolation on the obtained sample prices of commercial housing projects and the sample prices of indemnificatory housing projects respectively by using the ordinary Kriging spatial interpolation method, and exclude the regions corresponding to non-construction lands such as rivers, lakes, etc., and respectively obtain the market price DEM of commercial housing and the guiding price DEM of indemnificatory housing.

[0140] A spatial welfare score obtaining unit, configured to subtract the guiding price information of indemnificatory housing from the market price information of commercial housing to obtain a spatial welfare score;

[0141] Specifically, the spatial welfare score obtaining unit is specifically configured to use a raster calculation tool to subtract the guiding price DEM of indemnificatory housing from the market price DEM of commercial housing to obtain a spatial welfare DEM, and the values on the spatial welfare DEM are the spatial welfare scores.

[0142] An indemnificatory housing layout plan optimization unit, configured to, for the indemnificatory housing with a relatively high spatial welfare score in the indemnificatory housing layout plan, increase the purchase price, rental price, and / or shorten the usage period to obtain an optimized indemnificatory housing layout plan; for the indemnificatory housing with a relatively low spatial welfare score in the indemnificatory housing layout plan, reduce the purchase price, rental price, and / or extend the usage period to obtain an optimized indemnificatory housing layout plan.

[0143] To reasonably allocate indemnificatory housing, it further includes:

[0144] An application information obtaining unit, configured to obtain the application information of the applicants for indemnificatory housing;

[0145] A demand degree score calculation unit, configured to calculate the demand degree scores of the indemnificatory housing for each applicant in the way of weighted summation of the data items in the application information;

[0146] An indemnificatory housing allocation unit, configured to, based on the housing preference information in the application information, allocate the indemnificatory housing in the indemnificatory housing layout plan to each applicant in descending order of the demand degree scores. Among them, the housing preference information includes: geographical location, spatial living area, room layout, floor, orientation, lighting, etc.

[0147] Based on the spatial decision-making method and device for the location and layout of indemnificatory housing provided by the embodiments of the present invention, a spatial decision support system for the location, layout and allocation of indemnificatory housing is also designed. The system adopts a B / S architecture, with the front end built using HTML5, CSS and JavaScript technologies, the back end using Python and Django frameworks, the database using PostgreSQL, and the geographic information processing using ArcGIS Server. As Figure 6 shown, this system includes a data input module, a demand and preference processing module, a preliminary location module, a balanced layout module and a housing allocation module. Specifically as follows:

[0148] 1. Data input module

[0149] 1.1 Input of information of indemnificatory housing applicant families

[0150] The system interface provides a family information input module, including family basic information and living preference information. Among them, the family basic information includes family income status, family asset situation, existing housing situation, member basic information, etc., and the living preference information includes preferences for living areas (specific to districts or streets), spatial living area, room layout, floor, orientation and lighting, etc.

[0151] 1.2 Input of urban basic geographic information

[0152] The system administrator batch imports urban basic geographic information through the background, including administrative division data, land use planning data, residential land benchmark land price maps, sample price data of commercial housing projects, sample price data of indemnificatory housing projects, and POI data of facilities such as commerce, medical care, education, culture, public transportation, and financial services.

[0153] 2. Demand and preference processing module

[0154] 2.1 Calculate housing demand degree

[0155] Based on the input family economic status, housing status, etc., the system scores each family according to a preset scoring standard. For example, a family with an income lower than 50% of the urban median gets 10 points, and a family with an income lower than 30% of the median gets 6 points, and so on.

[0156] The system calculates the total housing demand degree by weighting each score and sorts the applicant families according to the demand degree.

[0157] 2.2 Process living preference information

[0158] Extract the spatial and housing type preference information of families from the demand ranking results, organize and store it in the residential preference information database. The system automatically identifies and adjusts unreasonable preference information. For example, if the selected room area exceeds the standard, the system automatically rejects it and notifies the applicant family to modify the preference information.

[0159] 3. Preliminary Site Selection Module

[0160] 3.1 Land Cost Assessment and Preliminary Screening

[0161] The system constructs a residential land benchmark price DEM based on the input residential land benchmark price map to evaluate the land costs of each plot. Set the upper limit value of the benchmark price, and screen out the plots with benchmark prices lower than the upper limit value as candidate areas.

[0162] 3.2 Geographical Location Assessment and Preliminary Screening

[0163] Conduct kernel density analysis and hotspot analysis on the public service facility POI data to identify the single / multi-center of the city, and set the maximum radiation distance parameter Dmax_service of the city center. According to the maximum radiation distance parameter Dmax_service, use GIS tools to perform buffer analysis on the plots around the city center, and screen out suitable candidate areas.

[0164] 3.3 Generation of Candidate Areas Considering Land Supply Costs and Geographical Locations

[0165] Take the intersection of the results of land cost assessment and geographical location assessment to generate candidate areas that meet the conditions, and then take the intersection of this area with the residential land in the land use plan to generate the final candidate areas for affordable housing.

[0166] 4. Balanced Layout Module

[0167] 4.1 Assessment of Public Facility Accessibility

[0168] Conduct multi-ring buffer analysis on the public service facilities around the candidate areas to evaluate the facility accessibility of each plot. Assign scores to each buffer ring, and calculate the total accessibility score of the plot to generate candidate areas containing public facility accessibility information.

[0169] 4.2 Calculation of Local Spatial Isolation Index and Layout Optimization

[0170] Use linear programming model to solve to simulate different housing layout schemes, and calculate the local spatial isolation index (LSI) of each street in real time. Dynamically adjust the layout of affordable housing according to the LSI index to avoid excessive concentration.

[0171] 5. Housing Allocation Module

[0172] 5.1 Spatial Welfare Assessment

[0173] Construct the DEM of the market price of commercial housing and the guiding price of affordable housing, and calculate the spatial welfare of different plots to obtain the DEM of spatial welfare.

[0174] 5.2 Adjust the purchase price, rental price and usage period

[0175] According to the level of spatial welfare, adjust the purchase price, rental price and usage period of affordable housing to balance the spatial welfare obtained by different families.

[0176] 5.3 Allocate housing according to housing preferences

[0177] On the basis of adjusting the price and usage period, allocate housing according to the spatial preference information and housing type preference information of families, and form an affordable housing allocation plan that can meet the personalized needs of each family for work and life convenience as much as possible.

[0178] System implementation effect

[0179] Through the integration of GIS and DSS technologies, this system can accurately analyze and process geographical information and application family data, provide decision support that is dynamic and responsive to market and social changes, effectively avoid the excessive concentration of middle - and low - income families, and promote social integration and harmony. By allocating housing resources in a personalized manner, it improves the fairness of housing allocation and the satisfaction of residents, and optimizes the utilization efficiency of resources.

[0180] In summary, the embodiments of the present invention propose a spatial decision - making support method, device and system for the site selection, layout and allocation of affordable housing, aiming to overcome the limitations of traditional affordable housing site - selection and layout methods, support more effective and fair site - selection, layout and allocation plans, and achieve reasonable spatial layout and reasonable spatial welfare distribution of affordable housing resources.

[0181] Those skilled in the art should understand that the embodiments of the present invention can be provided as a method, a system, or a computer program product. Therefore, the present invention can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present invention can take the form of a computer program product implemented on one or more computer - usable storage media (including but not limited to disk storage, CD - ROM, optical storage, etc.) containing computer - usable program code.

[0182] The present invention is described with reference to the flowcharts and / or block diagrams of methods, apparatuses (systems), and computer program products according to embodiments of the present invention. It should be understood that each flow and / or block in the flowchart and / or block diagram, and the combination of flows and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, such that the instructions executed by the processor of the computer or other programmable data processing devices generate means for implementing the functions specified in the flow Figure 1 one flow or multiple flows and / or blocks Figure 1 or means for implementing the functions specified in multiple blocks.

[0183] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, such that the instructions stored in the computer-readable memory generate a manufactured article including instruction means that implement the functions specified in the flow Figure 1 one flow or multiple flows and / or blocks Figure 1 or means for implementing the functions specified in multiple blocks.

[0184] These computer program instructions can also be loaded onto a computer or other programmable data processing device, such that a series of operation steps are executed on the computer or other programmable device to generate a computer-implemented process, so that the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in the flow Figure 1 one flow or multiple flows and / or blocks Figure 1 or means for implementing the functions specified in multiple blocks.

[0185] Details not described in the embodiments of the present invention are all well-known technologies to those skilled in the art. Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical solutions of the present invention can be modified or equivalently replaced without departing from the spirit and scope of the technical solutions of the present invention, and they should all be covered by the scope of the claims of the present invention.

Claims

1. A spatial decision-making method for the site selection and layout of indemnificatory housing, characterized in that Including: Performing grid sampling on the obtained base land price data of residential land to obtain base land price sampling points of residential land; Performing spatial interpolation on the base land price sampling points of residential land, excluding the areas corresponding to non-construction land, to obtain base land price information of residential land that can reflect the land supply cost; Selecting the plots with base land price lower than the set upper limit value from the base land price information of residential land as the first candidate areas; Selecting the spatial range with the distance from the town center less than or equal to the preset distance as the second candidate area; Taking the intersection of the first candidate area, the second candidate area and the planned residential land plots to obtain the candidate areas for affordable housing construction; Obtain the accessibility scores of public service facilities for each plot in the candidate areas for indemnificatory housing construction, arrange the indemnificatory housing in descending order according to the accessibility scores of public service facilities for each plot, and use the formula to calculate the local spatial segregation index for each street; where i and j are both street areas; n is the total number of streets in the city; b i is the number of indemnificatory housing families living in street i; a j is the number of commercial housing families living in street j; c ij is the adjacency weight matrix; represents the degree of interaction between indemnificatory housing families in street i and commercial housing families in the streets adjacent to i; represents the degree of interaction between indemnificatory housing families in street i and commercial housing families across the city; Obtaining the public service facility accessibility scores of each plot in the candidate areas for affordable housing construction, including: For the obtained point-of-interest data of various public service facilities, setting multiple buffer distances and establishing non-overlapping multi-ring buffers; Assigning scores to each buffer ring in the non-overlapping multi-ring buffers, with the scores decreasing from the center to the periphery, to obtain the score information of the non-overlapping multi-ring buffer layer; Identifying the score information of the non-overlapping multi-ring buffer layer to the candidate areas for affordable housing construction to obtain the public service facility accessibility scores of each plot in the candidate areas for affordable housing construction; When the local spatial isolation index LSI of a certain street reaches or exceeds the preset upper limit value, stop arranging the number of affordable housing construction in this area, and at the same time increase the affordable housing layout in other streets until an affordable housing layout plan is obtained in which the local spatial isolation index LSI of each street is within the acceptable range.

2. The spatial decision-making method for the site selection and layout of indemnificatory housing according to claim 1, wherein The selecting the spatial range with the distance from the town center less than or equal to the preset distance as the second candidate area includes: Based on the obtained point-of-interest data of various functional facilities, comprehensively identifying the town center by using kernel density analysis, hot spot analysis and weighted overlay analysis methods; Using buffer analysis, selecting the area with the distance from the town center within the preset maximum radiation distance as the second candidate area.

3. The spatial decision-making method for the site selection and layout of indemnificatory housing as claimed in claim 1, wherein After obtaining the affordable housing layout plan in which the local spatial isolation index LSI of each street is within the acceptable range, it further includes: Performing spatial interpolation on the sample housing project prices and affordable housing project sample prices obtained, excluding the areas corresponding to non-construction land, to obtain the commercial housing market price information and affordable housing guidance price information respectively; Subtracting the affordable housing guidance price information from the commercial housing market price information to obtain the spatial welfare score; For the affordable housing with a higher spatial welfare score in the affordable housing layout plan, increasing the purchase price, rental price and / or shortening the usage period to obtain an optimized affordable housing layout plan; for the affordable housing with a lower spatial welfare score in the affordable housing layout plan, reducing the purchase price, rental price and / or extending the usage period to obtain an optimized affordable housing layout plan.

4. The spatial decision-making method for the site selection and layout of indemnificatory housing according to any one of claims 1-3, characterized in that, It further includes: Obtaining the application information of the applicants for affordable housing; Calculate the demand degree scores of affordable housing for each applicant by means of weighted summation of various data in the application information; Based on the housing preference information in the application information, allocate the affordable housing in the affordable housing layout plan to each applicant in descending order according to the demand degree scores.

5. A spatial decision-making device for the site selection and layout of indemnificatory housing, characterized in that, Including: A grid sampling unit for performing grid sampling on the obtained benchmark land price data of residential land to obtain benchmark land price sampling points of residential land; A first spatial interpolation unit for performing spatial interpolation on the benchmark land price sampling points of residential land, excluding the areas corresponding to non-construction land, to obtain benchmark land price information of residential land that can reflect the land supply cost; A first candidate area screening unit for screening out plots with a benchmark land price lower than the set upper limit value from the benchmark land price information of residential land as the first candidate area; A second candidate area selection unit for selecting a spatial range with a distance from the town center less than or equal to a preset distance as the second candidate area; An affordable housing construction candidate area obtaining unit for taking the intersection of the first candidate area, the second candidate area and the planned residential land plots to obtain an affordable housing construction candidate area; A public service facility accessibility score obtaining unit for obtaining the public service facility accessibility scores of each plot in the affordable housing construction candidate area; The public service facility accessibility score obtaining unit includes: A multi-ring buffer establishment subunit for setting multiple buffer distances for the obtained point-of-interest data of various public service facilities and establishing non-overlapping multi-ring buffers; A buffer ring scoring subunit for assigning scores to each buffer ring in the non-overlapping multi-ring buffers, with the scores decreasing from the center to the periphery, to obtain the score information of the non-overlapping multi-ring buffer layer; A score information identification subunit for identifying the score information of the non-overlapping multi-ring buffer layer to the affordable housing construction candidate area to obtain the public service facility accessibility scores of each plot in the affordable housing construction candidate area; The local spatial segregation index calculation unit is used to layout indemnificatory housing in descending order according to the accessibility scores of public service facilities of each plot, and calculate the local spatial segregation index of each street through the formula where i and j are both street areas; n is the total number of streets in the city; b i is the number of indemnificatory housing families living in street i; a j is the number of commercial housing families living in street j; c ij is the adjacent weight matrix; represents the degree of interaction between indemnificatory housing families in street i and commercial housing families in the adjacent streets of i; represents the degree of interaction between indemnificatory housing families in street i and commercial housing families in the whole city; An affordable housing layout plan obtaining unit for stopping the layout of the number of affordable housing construction in a certain area when the local spatial isolation index LSI of a certain street reaches or exceeds the preset upper limit value, and at the same time increasing the affordable housing layout in other streets until an affordable housing layout plan is obtained in which the local spatial isolation index LSI of each street is within an acceptable range.

6. The spatial decision-making device for the site selection and layout of indemnificatory housing according to claim 5, wherein The second candidate area selection unit includes: A city center identification subunit for comprehensively identifying the town center according to the obtained point-of-interest data of various functional facilities by using kernel density analysis, hot spot analysis and weighted overlay analysis methods; A second candidate area selection subunit for using buffer analysis to select an area with a distance from the town center within the preset maximum radiation distance as the second candidate area.

7. The spatial decision-making device for the site selection and layout of indemnificatory housing according to claim 5, characterized in that It also includes: A second spatial interpolation unit for performing spatial interpolation on the obtained sample point prices of commercial housing projects and affordable housing projects, excluding the areas corresponding to non-construction land, to obtain commercial housing market price information and affordable housing guiding price information respectively; A spatial welfare score acquisition unit, configured to subtract the guidance price information of the indemnificatory housing from the market price information of the commodity housing to obtain a spatial welfare score; An indemnificatory housing layout plan optimization unit, configured to, for the indemnificatory housing with a relatively high spatial welfare score in the indemnificatory housing layout plan, increase the purchase price, rental price, and / or shorten the usage period to obtain an optimized indemnificatory housing layout plan; for the indemnificatory housing with a relatively low spatial welfare score in the indemnificatory housing layout plan, reduce the purchase price, rental price, and / or extend the usage period to obtain an optimized indemnificatory housing layout plan.

8. The spatial decision-making device for the site selection and layout of indemnificatory housing according to any one of claims 5-7, characterized in that It further includes: An application information acquisition unit, configured to acquire the application information of the applicants for indemnificatory housing; A demand degree score calculation unit, configured to calculate the demand degree scores of the indemnificatory housing for each applicant in a weighted summation manner of the data items in the application information; An indemnificatory housing allocation unit, configured to allocate the indemnificatory housing in the indemnificatory housing layout plan to each applicant in descending order of the demand degree scores based on the housing preference information in the application information.

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