Analysis methods, layout methods and equipment for the relationship between retail enterprise spatial layout and population

Abstract

The present invention discloses a method, layout method, and device for analyzing the relationship between the spatial layout and population of retail enterprises. The method comprises the following steps: obtaining a dataset to be analyzed, the dataset comprising POI data and night light remote sensing data; calculating the kernel density value for each enterprise category corresponding to each subdivision in the area to be analyzed based on the POI data; calculating the night light brightness value for each subdivision in the area to be analyzed based on the night light remote sensing data; calculating the coupling degree between each subdivision and each retail enterprise category in the area to be analyzed based on the kernel density value and the night light brightness value; determining the proportion of each industry type in each subdivision in the area to be analyzed based on the geographic data and industry type; and generating a comparison table of the proportion of each industry type in each subdivision and the coupling degree between each subdivision and each retail enterprise category in the area to be analyzed. The method can significantly improve the accuracy of the spatial layout of retail enterprises and increase commercial profits.

Description

Technical Field

[0001] The present invention belongs to the technical field of enterprise space layout, and specifically relates to a retail enterprise space layout and population relationship analysis method, layout method and equipment. Background Art

[0002] The concept of decentralization of urban spatial structure is a key concept in geography and urban planning. Its goal is to decentralize overconcentrated urban social functions, thereby alleviating and eliminating the problems of mega-city diseases. As part of a city's commercial landscape, the layout of retail businesses is directly related to the convenience of urban life. A reasonable layout not only improves residents' quality of life but also generates reasonable or objective profits for businesses. While existing layout theories can deduce the laws governing retail layout, actual retail layout differs from theoretical layouts, and there are still discrepancies between layouts in cities of different sizes. The differences in distribution across cities of different tiers, the layout models of different retail formats, and the development of physical layout within new retail formats are all worthy of discussion.

[0003] The existing retail point layout method uses a prediction model for prediction. Although its prediction reference data is wide, its accuracy is poor. Summary of the Invention

[0004] In order to solve the problem of low accuracy in achieving retail enterprise layout using existing methods, the present invention provides a method for analyzing the relationship between retail enterprise spatial layout and population, a layout method and equipment.

[0005] The purpose of the present invention is achieved through the following technical solutions:

[0006] A first aspect of the present invention provides a method for analyzing the relationship between the spatial layout and population of a retail enterprise, comprising the following steps:

[0007] Obtaining a data set to be analyzed, the data set to be analyzed including POI data and night light remote sensing data, the POI data including geographic data, industry type, retail enterprise category, and enterprise name;

[0008] Calculate the kernel density value of each enterprise category corresponding to each partition in the area to be analyzed according to the POI data;

[0009] Calculate the night light brightness value of each subarea in the area to be analyzed based on the night light remote sensing data;

[0010] Calculate the coupling degree between each partition and each retail enterprise category in the analyzed area based on the kernel density value and the night light brightness value;

[0011] Determine the proportion of each industry type in each sub-area of ​​the area to be analyzed based on the geographic data and industry types;

[0012] A comparison table of the relationship between the proportion of each industry type in each partition and the coupling degree of each partition and each retail enterprise category in the area to be analyzed.

[0013] A second aspect of the present invention provides a retail enterprise space layout method, comprising the following steps:

[0014] Obtaining a relationship comparison table obtained using the method described in the first aspect;

[0015] Calculate the proportion of each industry type in the zone to be laid out;

[0016] Calculate the distance between the proportion of each industry type in the zone to be laid out and the proportion of each industry type in the relationship comparison table, and determine the coupling degree of the retail enterprise category to be laid out in the zone to be laid out based on the principle of shortest distance;

[0017] The number of retail enterprises that need to be arranged is determined based on the night light remote sensing data of the zone to be arranged, the area of ​​the zone to be arranged, the coupling degree of the categories of retail enterprises to be arranged in the zone to be arranged, and the number of retail enterprises to be arranged in the zone to be arranged.

[0018] The third aspect of the present invention provides a device comprising a memory and a controller communicatively connected in sequence, wherein the memory stores a computer program, and the controller is used to read the computer program and execute the method for analyzing the spatial layout and population relationship of a retail enterprise described in the first aspect or the method for analyzing the spatial layout of a retail enterprise described in the second aspect.

[0019] Compared with the prior art, the present invention has at least the following advantages and beneficial effects:

[0020] Based on the night light remote sensing data and POI data of a relatively mature city, the present invention generates a comparison table of the relationship between industry types, partitions and the coupling degree of each retail enterprise category. When spatially arranging retail enterprises in another relatively immature area, after achieving partition matching based on the proportion of industry types, the layout quantity planning is implemented based on the corresponding coupling degree. This can greatly improve the accuracy of the spatial layout quantity of retail enterprises and increase commercial profits. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0022] Figure 1 This is a flow chart of the method for analyzing the relationship between retail enterprise spatial layout and population according to the present invention. DETAILED DESCRIPTION

[0023] To make the objectives, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions of the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Generally, the components of the embodiments of the present invention described and shown in the drawings herein can be arranged and designed in various different configurations.

[0024] Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the invention as claimed, but rather merely represents selected embodiments of the present invention. All other embodiments derived by persons of ordinary skill in the art based on the embodiments of the present invention without creative effort are also within the scope of protection of the present invention.

[0025] It should be noted that, in the absence of conflict, the embodiments and features of the embodiments of the present invention can be combined with each other.

[0026] It should be noted that similar reference numerals and letters denote similar items in the following drawings, and therefore, once an item is defined in one drawing, it does not need to be further defined or explained in subsequent drawings.

[0027] In the description of the present invention, it should be noted that the terms "center," "upper," "lower," "left," "right," "vertical," "horizontal," "inner," "outer," etc., indicating orientations or positional relationships, are based on the orientations or positional relationships shown in the accompanying drawings, or are the orientations or positional relationships in which the inventive product is typically placed when in use, or are the orientations or positional relationships commonly understood by those skilled in the art. These terms are intended only to facilitate the description of the present invention and to simplify the description, and are not intended to indicate or imply that the device or element referred to must have a specific orientation, be constructed, or operate in a specific orientation. Therefore, they should not be construed as limiting the present invention. Furthermore, the terms "first," "second," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0028] In the description of the present invention, it should also be noted that, unless otherwise expressly specified or limited, the terms "disposed," "installed," "connected," and "connected" should be understood in a broad sense. For example, they may refer to fixed connections, detachable connections, or integral connections; they may refer to mechanical connections or electrical connections; they may refer to direct connections or indirect connections through an intermediate medium; and they may refer to internal communication between two components. Those skilled in the art will understand the specific meanings of the above terms in the present invention based on the specific circumstances.

[0029] The present invention discloses a method for analyzing the spatial layout and population relationship of a retail enterprise. The method can be performed, but is not limited to, by a device for analyzing the spatial layout and population relationship of a retail enterprise. The device for analyzing the spatial layout and population relationship of a retail enterprise can be software, or a combination of software and hardware. The device for analyzing the spatial layout and population relationship of a retail enterprise can be integrated into smart devices such as smart mobile terminals, tablets, and computers. Specifically, Figure 1 As shown, the retail enterprise spatial layout and population relationship analysis method includes the following steps S11 to S16. It should be noted that the step identifiers in this solution are only for the convenience of explaining the method and do not constitute a limitation on the order of sequence. The order of each step is based on the language description and the sequence of each signal.

[0030] Step S11: Acquire a data set to be analyzed, wherein the data set to be analyzed includes POI data and night light remote sensing data, and the POI data includes geographic data, industry type, retail enterprise category and name.

[0031] POI data is used to describe the distribution of retail business entities. It includes geographic data, industry type, retail business category, and business name. Geographic data includes latitude and longitude data. POI data can be crawled from the Internet using Python and ArcGIS.

[0032] Industrial types are divided into primary, secondary and tertiary industries. In order to improve the accuracy of analysis, the three major industries can be further refined. The primary industry is refined into four dimensions, namely agriculture, forestry, animal husbandry and fishery; the secondary industry is refined into six dimensions, namely mining, manufacturing, electricity, heat, gas and water production and supply, and construction; the tertiary industry is refined into 14 dimensions, namely wholesale and retail, transportation, accommodation and catering, information transmission, software and information technology services, finance, real estate, leasing and business services, scientific research and technical services, water conservancy and public facilities management, education, health and social work, culture, sports and entertainment, public administration and social organizations.

[0033] The retail business categories include home building materials markets, shopping malls, specialty commercial streets, special trading places, sporting goods stores, cultural goods stores, specialty stores, comprehensive markets, clothing, shoes and leather goods stores, personal goods / cosmetics stores, convenience stores, flower, bird, insect and fish markets, and home appliance and electronics stores, totaling 13 categories.

[0034] Night light remote sensing data is obtained through night light remote sensing satellites, such as Luojia 01.

[0035] Step S12: Calculate the kernel density value of each retail enterprise category corresponding to each partition in the area to be analyzed based on the POI data.

[0036] In this scheme, the zones can be freely designed or based on administrative areas. For example, a city can be divided into multiple districts based on administrative areas.

[0037] There are many existing methods for calculating kernel density values ​​in this step. To improve accuracy, this step prioritizes calculations based on the optimal bandwidth. Specifically, the optimal bandwidth is first determined using the POI data. Then, based on this optimal bandwidth and the POI data, the kernel density value for each retail business category in each subarea within the analyzed area is calculated.

[0038] Among them, the optimal bandwidth h is:

[0039] ,

[0040] Where h is the optimal bandwidth; SD is the standard distance; D m is the median distance; n is the number of sample points within the bandwidth. The kernel density value of the jth retail enterprise category in the i-th partition is for:

[0041] ,

[0042] Where K is the kernel function, 、 are the horizontal and vertical coordinates of the sample point in the center of the ith partition, and x and y are the horizontal and vertical coordinates of the points in the ith partition except the sample point.

[0043] Step S13: Calculate the night light brightness value of each partition in the area to be analyzed based on the night light remote sensing data.

[0044] In order to improve the accuracy of the analysis, the metal geo-registration and denoising processing of the night light remote sensing data are first performed.

[0045] The calculation of the night light brightness value in this step can be directly processed using existing methods.

[0046] Step S14: Calculate the coupling degree between each partition and each enterprise type in the area to be analyzed based on the standardized kernel density value and the night light brightness value.

[0047] The coupling degree is calculated as:

[0048] ,

[0049] Where, is the coupling degree between the i-th partition and the j-th enterprise type, is the night light brightness value of the i-th partition.

[0050] Step S15: Determine the proportion of each industry type in each sub-area in the area to be analyzed based on the geographic data and industry types.

[0051] For example, the total number of industries in the 20 dimensions of industry types in a partition is 5168, while the wholesale and retail industry, transportation industry, and accommodation and catering industry are 365, 45, and 1280 respectively. Then the proportion of wholesale and retail industry in this partition is 365 / 5168, and the proportion of transportation industry and accommodation and catering industry are 45 / 5168 and 1280 / 5168 respectively.

[0052] Step S16: Generate a table comparing the proportion of each industry type in each partition and the degree of coupling between each partition and each retail enterprise category in the area to be analyzed.

[0053] Based on the relationship comparison table obtained by the method in the first aspect, the second aspect of the present invention discloses a retail enterprise space layout method, which can be but is not limited to being executed by a retail enterprise space layout device. Similarly, the retail enterprise space layout device can be software, or a combination of software and hardware. The retail enterprise space layout device can be integrated into smart mobile terminals, tablets, computers and other smart devices. Specifically, the retail enterprise space layout method includes the following steps S21 to S24. Similarly, it should be noted that the step identifiers in this solution are only for the convenience of explaining the method and do not constitute a limitation on the order of sequence. The order of the steps is based on their language descriptions and the sequence of the signals.

[0054] Step S21: Obtain a relationship comparison table obtained by adopting the first method.

[0055] The relationship comparison table is used as a standard table. In order to improve the accuracy of the layout, the relationship comparison table is preferably prepared using data from large cities.

[0056] Step S22: Calculate the proportion of each industry type in the zone to be laid out.

[0057] The calculation method of this step is the same as that of step S16 and will not be described in detail here.

[0058] Step S23: Calculate the distance between the proportion of each industry type in the zone to be arranged and the proportion of each industry type in the relationship comparison table, and determine the coupling degree of the retail enterprise category to be arranged in the zone to be arranged based on the shortest distance principle.

[0059] Specifically, in this step, the partition with the shortest distance is first determined in the relationship comparison table as the most similar area of ​​the partition to be arranged; then the coupling degree corresponding to the category of retail enterprises to be arranged in the most similar area is used as the coupling degree of the category of retail enterprises to be arranged in the partition to be arranged.

[0060] Specifically, the distance may be Euclidean distance.

[0061] For example, if the category of retail enterprises to be arranged is convenience stores, the proportion of each industry type in the zone to be arranged is 0.098, and the proportion with the smallest distance from it in the comparison table is 0.097, then the zone A corresponding to 0.097 will be used as the most similar area of ​​the zone to be arranged; and the coupling coefficient of the convenience stores in zone A will be used as the coupling coefficient of the convenience stores in the zone to be arranged.

[0062] Step S24: Determine the number of retail enterprises that need to be arranged based on the night light remote sensing data of the zone to be arranged, the area of ​​the zone to be arranged, the coupling degree of the categories of retail enterprises to be arranged in the zone to be arranged, and the number of retail enterprises to be arranged in the zone to be arranged.

[0063] Specifically, this step first calculates the total number of retail enterprises to be arranged in the zone based on the night light remote sensing data L, the area S of the zone to be arranged, and the coupling degree f(x) of the categories of retail enterprises to be arranged in the zone to be arranged. The total number N is:

[0064] .

[0065] Then, based on the total number N and the number of retail enterprises that have been deployed, determine the number of retail enterprises that need to be deployed.

[0066] In this solution, the relationship table is derived from data from City A, a commercially mature city. The commercial maturity of the proposed subdistrict is lower than that of City A. Market research has shown that City A is reasonable and offers reasonable, even objective, commercial profits. Therefore, when planning retail space layout for a less mature subdistrict, this method matches the subdistricts based on the proportion of industry types and then plans the number of retail spaces based on the corresponding coupling degree. This method significantly improves the accuracy of the number of retail space layouts, avoids over- or insufficient layouts, and ultimately increases commercial profits.

[0067] A third aspect of the present invention provides a device comprising a memory and a controller communicatively connected in sequence, the memory storing a computer program, the controller configured to read the computer program and execute the method for analyzing the spatial layout and population relationship of a retail enterprise described in the first aspect and any possible embodiment thereof, or the method for analyzing the spatial layout of a retail enterprise described in the second aspect. Specifically, the memory may include, but is not limited to, random-access memory (RAM), read-only memory (ROM), flash memory, first-input first-output (FIFO), or first-input last-output (FILO) memory; the controller may include, but is not limited to, a microcontroller of the STM32F105 series. Furthermore, the computer device may include, but is not limited to, a power supply unit, a display screen, and other necessary components.

[0068] Although the present invention has been described in detail with reference to the aforementioned embodiments, it is still possible for those skilled in the art to modify the technical solutions described in the aforementioned embodiments, or to make equivalent substitutions for some of the technical features therein. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A retail enterprise space layout method, characterized in that: The following steps are involved: Obtain a relationship comparison table, which is obtained using the following method: Obtaining a data set to be analyzed, the data set to be analyzed includes POI data and night light remote sensing data, the POI data includes geographic data, industry type, retail enterprise category and enterprise name, Calculate the kernel density value of each enterprise category corresponding to each partition in the area to be analyzed based on the POI data. Calculate the night light brightness value of each partition in the area to be analyzed based on the night light remote sensing data, The coupling degree between each partition and each retail enterprise category in the analyzed area is calculated based on the kernel density value and the night light brightness value. Determine the proportion of each industry type in each sub-area in the area to be analyzed based on the geographic data and industry types. Generate a comparison table of the proportion of each industry type in each zone and the degree of coupling between each zone and each retail enterprise category in the area to be analyzed; Calculate the proportion of each industry type in the zone to be laid out; Calculate the distance between the proportion of each industry type in the zone to be laid out and the proportion of each industry type in the relationship comparison table, and determine the coupling degree of the retail enterprise category to be laid out in the zone to be laid out based on the principle of shortest distance; The number of retail enterprises that need to be arranged is determined based on the night light remote sensing data of the zone to be arranged, the area of ​​the zone to be arranged, the coupling degree of the categories of retail enterprises to be arranged in the zone to be arranged, and the number of retail enterprises to be arranged in the zone to be arranged.

2. A retail enterprise space layout method according to claim 1, characterized in that: The method of determining the coupling degree of the categories of retail enterprises to be arranged in the zone to be arranged based on the shortest distance principle includes: Determine the partition with the shortest distance in the relationship comparison table as the most similar area to the partition to be laid out; The coupling degree corresponding to the category of retail enterprises to be arranged in the most similar area is used as the coupling degree of the category of retail enterprises to be arranged in the partition to be arranged.

3. A device comprising a memory and a controller in communication with each other, wherein the memory stores a computer program, characterized in that: The controller is used to read the computer program and execute the retail enterprise space layout method described in claim 1 or 2.

Images