Method and device for determining building density information, electronic equipment and program product

Abstract

The invention provides a method and device for determining building density information, electronic equipment and a program product, and the method comprises the steps: determining a building region based on boundary information corresponding to a building set, the building region being a region to which a plurality of buildings included in the building set belong; based on the pre-selected division modes, grid division is carried out on the building area to obtain a plurality of grids, and the accuracy of the grids obtained through division in different pre-selected division modes is different; for any building in the building set, determining a target grid to which the building belongs in the plurality of grids; according to the method, the building density information of the building set is determined based on the target grids corresponding to the multiple buildings and the total number of the buildings in the building set, the building density information capable of accurately representing the sparse degree of building space distribution can be obtained, and the accuracy of data analysis based on the building density information can be improved.

Description

Technical Field

[0001] This disclosure relates to computer technology, and in particular to a method, apparatus, electronic device, and program product for determining building density information. Background Technology

[0002] In the fields of urban planning and real estate development, it is necessary to determine the building density of certain areas in order to conduct regional development analysis, layout of regional public facilities, and allocation of regional service resources.

[0003] In related technologies, statistics rely on human experience, such as manually dividing areas, calculating the building area of ​​buildings within the area, and determining the building density of the area based on the building area of ​​the buildings and the total area of ​​the area. However, this method is difficult to accurately reflect the spatial clustering characteristics of buildings and cannot meet the density analysis needs in different scenarios. Summary of the Invention

[0004] This disclosure provides a method, apparatus, electronic device, and program product for determining building density information, in order to solve the above-mentioned technical problems to a certain extent.

[0005] One aspect of this disclosure provides a method for determining building density, the method comprising: Based on the boundary information corresponding to the set of properties, the property area is determined, where the property area is the region to which multiple properties included in the property set belong; Based on the pre-selected division mode, the building area is divided into grids to obtain multiple grids. The accuracy of the grids obtained under different pre-selected division modes is different. For any property in the set of properties, determine the target grid to which the property belongs among the plurality of grids; Based on the target grid corresponding to each of the multiple properties and the total number of properties in the property set, the property density information of the property set is determined.

[0006] In an exemplary embodiment, the building area is divided into multiple grids based on a pre-selected partitioning pattern, including: In response to the pre-selected division mode being a quantity control mode, the building area is divided into grids based on a dynamic quantity factor to obtain the multiple grids. The dynamic quantity factor is positively correlated with the total number of grids obtained. In response to the pre-selected division mode being scale control mode, the building area is divided into grids based on a preset latitude and longitude scale to obtain multiple grids, wherein the latitude and longitude span of each grid is the same as the preset latitude and longitude scale.

[0007] In an exemplary embodiment, the grid division of the property area based on a dynamic quantity factor to obtain the plurality of grids includes: Determine the longitude span and latitude span of the area corresponding to the property development; Based on the regional longitude span value and the dynamic quantity factor, the grid longitude span value corresponding to the grid is determined; Based on the regional latitudinal span value and the dynamic quantity factor, the latitudinal span value of the corresponding grid is determined; Based on the grid longitude span value and the grid latitude span value, the building area is divided into the multiple grids.

[0008] In an exemplary embodiment, the step of dividing the building area into grids based on a preset latitude and longitude scale to obtain the plurality of grids includes: Based on the preset latitude and longitude scale, determine the grid longitude span value and grid latitude span value corresponding to the grid; Based on the grid longitude span value and the grid latitude span value, the building area is divided into the multiple grids.

[0009] In an exemplary embodiment, determining the target grid to which the property belongs among the plurality of grids includes: Determine the latitude and longitude coordinates corresponding to the building and the latitude and longitude range corresponding to each of the multiple grids; Based on the latitude and longitude coordinates corresponding to the building and the latitude and longitude ranges corresponding to each grid, the target grid to which the building belongs is determined.

[0010] In an exemplary embodiment, determining the target grid to which the building belongs based on the latitude and longitude coordinates corresponding to the building and the latitude and longitude ranges corresponding to each grid includes: In response to the fact that the latitude and longitude coordinates corresponding to the building belong to the latitude and longitude range of the target grid, it is determined that the building belongs to the target grid; In response to the boundary value of the latitude and longitude coordinates corresponding to the property belonging to the latitude and longitude range of multiple candidate grids, it is determined that the property belongs to the target grid among the multiple candidate grids.

[0011] In an exemplary embodiment, determining the building density information of the building set based on the target grid corresponding to each of the plurality of buildings and the total number of buildings in the building set includes: Based on the target grid corresponding to each of the multiple properties, the number of effective grids is determined; Based on the number of effective grids and the total number of buildings, the building density information is determined.

[0012] In another aspect of this embodiment, a device for determining building density information is provided, the device comprising: The area determination module is used to determine the building area based on the boundary information corresponding to the set of buildings with a density to be determined. The building area includes multiple buildings included in the set of buildings. The grid division module is used to divide the building area into multiple grids. The grid determination module is used to determine the target grid to which any building belongs among the multiple grids for any building in the set of buildings; The density determination module is used to determine the building density information of the building set based on the target grid corresponding to each of the multiple buildings and the total number of buildings in the building set.

[0013] In another aspect of this embodiment, an electronic device is provided, comprising: Memory, used to store computer programs; A processor is configured to execute a computer program stored in the memory, and when the computer program is executed, to implement the method for determining building density information as described in any of the above embodiments.

[0014] In another aspect of this embodiment, a computer-readable storage medium is provided, on which a computer program is stored, which, when executed by a processor, implements the method for determining building density information as described in any of the above embodiments.

[0015] In another aspect of this embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the method for determining building density information as described in any of the above embodiments.

[0016] In this embodiment of the disclosure, for a set of buildings whose density needs to be determined, the building area corresponding to the building set can be determined based on the boundary information of the building set. Then, according to a pre-selected partitioning mode, the building area is divided into multiple grids corresponding to the building area. Thus, for any building in the building set, the target grid to which each building belongs can be determined. The building density information corresponding to the building set is determined based on the target grid to which each building belongs and the total number of buildings in the building set. In this way, determining the target grid to which each building belongs can determine the spatial distribution of each building in the building set. Determining the building density information of the building set based on the target grid to which each building belongs and the total number of buildings in the building set can obtain building density information that can accurately characterize the sparsity of the spatial distribution of buildings, which helps to improve the accuracy of data analysis based on building density information.

[0017] Furthermore, different pre-selected grid partitioning modes correspond to different grid partitioning accuracies. The accuracy and computational efficiency of building density information calculated based on grids of different accuracies vary. Different partitioning modes can be selected for grid partitioning according to business needs, thereby achieving dynamic adjustment of computational accuracy and efficiency. Moreover, different building density information determined based on grids of different accuracies can be applied to different business scenarios, improving the universality of density calculation.

[0018] The technical solutions of this disclosure will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0019] The accompanying drawings, which form part of this specification, illustrate embodiments of this disclosure and, together with the description, serve to explain the principles of this disclosure.

[0020] This disclosure will become clearer with reference to the accompanying drawings and the following detailed description, wherein: Figure 1 A flowchart illustrating a method for determining building density information provided as an exemplary embodiment of this disclosure; Figure 2 A flowchart for dividing a building area into multiple grids is provided as an exemplary embodiment of this disclosure; Figure 3 A flowchart for dividing a building area into multiple grids is provided as another exemplary embodiment of this disclosure; Figure 4 A flowchart for determining the target grid to which a building belongs, provided as an exemplary embodiment of this disclosure; Figure 5 A grid diagram of the target grid to which the building belongs, provided as an exemplary embodiment of this disclosure; Figure 6 A flowchart for determining building density information provided as an exemplary embodiment of this disclosure; Figure 7 A flowchart illustrating a method for determining building density information as provided in another exemplary embodiment of this disclosure; Figure 8 This disclosure provides a schematic diagram of the structure of a device for determining building density information according to an exemplary embodiment; Figure 9 A schematic diagram of the structure of an electronic device provided for an exemplary embodiment of this disclosure. Detailed Implementation

[0021] Various exemplary embodiments of the present disclosure will now be described in detail with reference to the accompanying drawings. It should be noted that, unless otherwise specifically stated, the relative arrangement, numerical expressions, and values ​​of the components and steps set forth in these embodiments do not limit the scope of the present disclosure.

[0022] Those skilled in the art will understand that the terms "first," "second," etc., in the embodiments of this disclosure are only used to distinguish different steps, devices, or modules, and do not represent any specific technical meaning, nor do they indicate a necessary logical order between them.

[0023] It should also be understood that in the embodiments disclosed herein, "a plurality of" may refer to two or more, and "at least one" may refer to one, two or more.

[0024] It should also be understood that any component, data or structure mentioned in the embodiments of this disclosure can generally be understood as one or more unless expressly defined or given to the contrary in the context.

[0025] Furthermore, the term "and / or" in this disclosure is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. Additionally, the character " / " in this disclosure generally indicates that the preceding and following related objects have an "or" relationship.

[0026] It should also be understood that the description of the various embodiments in this disclosure emphasizes the differences between the various embodiments, and the similarities or similarities can be referred to each other. For the sake of brevity, they will not be described in detail.

[0027] At the same time, it should be understood that, for ease of description, the dimensions of the various parts shown in the accompanying drawings are not drawn according to actual scale.

[0028] The following description of at least one exemplary embodiment is merely illustrative and is in no way intended to limit this disclosure or its application or use.

[0029] Techniques, methods, and equipment known to those skilled in the art may not be discussed in detail, but where appropriate, such techniques, methods, and equipment should be considered part of the specification.

[0030] It should be noted that similar labels and letters in the following figures indicate similar items; therefore, once an item is defined in one figure, it does not need to be discussed further in subsequent figures.

[0031] The embodiments disclosed herein can be applied to electronic devices such as terminal devices, computer systems, and servers, and can operate together with a wide range of other general-purpose or special-purpose computing system environments or configurations. Examples of well-known terminal devices, computing systems, environments, and / or configurations suitable for use with electronic devices such as terminal devices, computer systems, and servers include, but are not limited to: personal computer systems, server computer systems, thin clients, thick clients, handheld or laptop devices, microprocessor-based systems, set-top boxes, programmable consumer electronics, network PCs, minicomputer systems, mainframe computer systems, and distributed cloud computing environments including any of the above systems, etc.

[0032] Electronic devices such as terminal devices, computer systems, and servers can be described in the general context of computer system executable instructions (such as program modules) executed by a computer system. Typically, program modules can include routines, programs, object programs, components, logic, data structures, etc., which perform specific tasks or implement specific abstract data types. Computer systems / servers can be implemented in distributed cloud computing environments, where tasks are executed by remote processing devices linked through communication networks. In distributed cloud computing environments, program modules can reside on local or remote computing system storage media, including storage devices.

[0033] In related technologies, building density information relies on manual experience for statistical analysis, but this method is difficult to accurately reflect the spatial clustering characteristics of buildings. Alternatively, a fixed method can be used to divide building areas and calculate density based on these areas. However, this requires flexible adjustment of the analysis granularity for different scenarios. Both the manual experience-based statistical method and the fixed area division method are difficult to adjust the analysis granularity, making it impossible to meet the density analysis needs of different scenarios and to achieve a balance between computational accuracy and efficiency.

[0034] In this embodiment of the disclosure, the area of ​​the building collection can be dynamically divided into grids based on a pre-selected partitioning mode. Then, the building density information can be determined according to the target grid to which each building belongs and the total number of buildings in the building collection. The determined building density information can accurately characterize the sparsity of the building collection in space, and can realize the dynamic adjustment of calculation accuracy and calculation efficiency to achieve a balance between calculation accuracy and calculation efficiency.

[0035] This embodiment can be applied to any scenario that requires determining building density information, such as regional planning management, regional comparative analysis, site selection for building construction, land development and planning, etc. This embodiment does not limit it.

[0036] In one possible implementation, such as Figure 1The diagram illustrates a flowchart of a method for determining building density information provided in an exemplary embodiment of this disclosure. The method provided in this disclosure can be used in the electronic devices described in the above embodiments, such as... Figure 1 As shown, it includes the following steps 110-140: Step 110: Based on the boundary information corresponding to the property collection, determine the property area. The property area is the region to which multiple properties included in the property collection belong.

[0037] Optionally, the building set can be a collection of multiple buildings within a preset geographical area where density needs to be calculated. For example, it can be a preset administrative planning area (e.g., a street, a community), a preset range centered on a preset location (e.g., a shopping mall, a subway station), or a preset custom-defined area. Optionally, the multiple buildings included in the building set can include any building within the preset geographical area (e.g., residential units, commercial units), or buildings with specific attributes, such as residential buildings, buildings from a specific era, or buildings currently for sale / to be sold. These can be customized according to density calculation requirements. In one possible implementation, for the building set whose density needs to be determined, boundary information of the building set can be obtained. This boundary information can be determined based on the geographical location of the outermost building among the multiple buildings included in the building set. Specifically, the boundary information of the building set can be determined based on the latitude and longitude coordinates of the multiple buildings included in the building set. Optionally, the latitude and longitude coordinates of the buildings can be obtained from data sources such as map data determined by satellite navigation systems or geographic information public service platforms. Optionally, the latitude and longitude coordinates of multiple properties included in the property set can be obtained. Based on these coordinates, the longitude and latitude ranges corresponding to the property set can be determined. The longitude range can be [minLon, maxLon], where minLon is the minimum longitude among the multiple properties and maxLon is the maximum longitude. The latitude range can be [minLat, maxLat], where minLat is the minimum latitude among the multiple properties and maxLat is the maximum latitude among the multiple properties.

[0038] In one possible implementation, the longitude and latitude ranges corresponding to the aforementioned set of properties can be determined as the boundary information of the property set. Then, based on the longitude and latitude ranges, the property area to which multiple properties belong can be determined. The property area refers to a specific geographical area that includes multiple properties. The longitude range is the longitude span of the property area, and the latitude range is the latitude span of the property area.

[0039] Step 120: Based on the pre-selected division mode, the building area is divided into grids to obtain multiple grids.

[0040] The required granularity of analysis for a building area varies in different scenarios. For example, the required granularity differs between macro-analysis of a region and micro-analysis of a street block, and correspondingly, the required precision of grid division also differs.

[0041] Optionally, the pre-selected grid division mode indicates the method of dividing the building area into grids. Different pre-selected grid division modes correspond to different division methods, and the user can pre-select one of multiple division modes. In one possible implementation, multiple different division modes can be set, where the accuracy of the grids obtained under different division modes is different. The accuracy of the grids obtained is positively correlated with the accuracy of the building density information determined based on the divided grids; that is, the higher the grid accuracy, the higher the accuracy of the calculated building density information. Furthermore, the accuracy of the grids obtained is negatively correlated with the efficiency of determining the building density information based on the divided grids; the lower the grid accuracy, the higher the efficiency of calculating the building density information.

[0042] In one possible implementation, the grids obtained under different partitioning modes have different latitude and longitude spans. Different latitude and longitude spans result in different numbers of grids and different grid precisions. The latitude and longitude span of the grid is negatively correlated with the number of grids; the smaller the latitude and longitude span, the more grids are obtained, and the higher the precision of the grids. Optionally, the pre-set partitioning mode may include a quantity control mode to control the number of grids obtained, dynamically controlling the number of grids in the multiple partitions. Optionally, the pre-set partitioning mode may also include a scale control mode to control the latitude and longitude span of the partitioned grids, precisely controlling the grid boundaries.

[0043] Before calculating building density information, users can choose from multiple grid division modes based on their business needs to ensure that the resulting grid accuracy meets the analytical requirements of the current business scenario, such as the requirements for computational accuracy and efficiency. During the calculation of building density information, the user-selected grid division mode (i.e., the pre-selected grid division mode) can be determined, and the building area is divided into multiple grids according to the selected pre-selected grid division mode.

[0044] In one possible implementation, under any pre-selected partitioning mode, the grid areas of the building area are the same for all grids obtained by gridding the building area. That is, under any pre-selected partitioning mode, the building area can be divided equally to obtain multiple grids with equal areas.

[0045] Step 130: For any property in the property collection, determine the target grid to which the property belongs in multiple grids.

[0046] In this embodiment of the disclosure, the target grid to which the building belongs is the grid to which the building is located. The target grid to which the building belongs can be determined based on the building's latitude and longitude coordinates.

[0047] In one possible implementation, after dividing the grid into multiple grids, a corresponding grid index can be set for each grid, with different grid indices for different grids, to be used to label the corresponding grids. For example, the grids can be numbered, and different grids can be labeled with different numbers (such as 1, 2, 3, etc.). Alternatively, a two-dimensional index (i, j) can be used to label the grids, where i represents the row number of the grid and j represents the column number of the grid.

[0048] In one possible implementation, for a set of properties, the target grid to which each property belongs can be determined, i.e., the grid index corresponding to each property can be determined and recorded. Determining the target grid to which a property belongs determines its spatial distribution within the property area. Statistics on the target grids to which multiple properties belong can be used to analyze the sparsity of the spatial distribution of properties. For example, if most properties in the property set belong to the same grid, it indicates a relatively dense distribution of properties.

[0049] Step 140: Determine the building density information of the building set based on the target grid corresponding to each of the multiple buildings and the total number of buildings in the building set.

[0050] In one possible implementation, the building density information of a building set can be determined based on the target grid corresponding to each of the multiple buildings and the total number of buildings in the building set (i.e., the total number of buildings included in the building set). The obtained building density information can be used to accurately reflect the sparsity of the building set in the corresponding building area.

[0051] In this embodiment, for a set of buildings whose density needs to be determined, the building area corresponding to the set can be determined based on the boundary information of the set. Then, according to a pre-selected partitioning mode, the building area is divided into multiple grids, thus allowing the determination of the target grid to which each building belongs for any given building in the set. The building density information corresponding to the set is determined based on the target grids to which each building belongs and the total number of buildings in the set. Determining the target grids to which each building belongs determines the spatial distribution of the buildings in the set. Determining the building density information based on the target grids to which each building belongs and the total number of buildings in the set provides building density information that accurately characterizes the sparsity of the spatial distribution of buildings, helping to improve the accuracy of data analysis based on building density information. Furthermore, different pre-selected partitioning modes correspond to different grid partitioning accuracies. The accuracy and computational efficiency of the building density information calculated based on grids of different accuracies vary. Different partitioning modes can be selected for grid partitioning according to business needs to achieve dynamic adjustment of computational accuracy and efficiency. Furthermore, different building density information obtained based on grids of varying precision can be applied to different business scenarios, thereby improving the universality of density calculation.

[0052] In one example, in the context of regional planning management and development analysis, the method for determining building density information provided in this disclosure can be used to calculate the density of a set of buildings within a preset administrative region, thereby determining the building density information within the preset administrative region. Then, based on the degree of clustering of the spatial distribution of buildings indicated by the building density information, regional management and development can be carried out in the administrative region (e.g., statistics on the distribution of buildings of different natures, estimating population flow and residential density based on building density for the allocation of resources such as education, medical care, and transportation).

[0053] In another example, in the scenario of selecting a building construction address (such as the location of public facilities or service outlets), the method for determining building density information provided in this disclosure can be used to calculate the density of the set of buildings included in the selected area (such as a street) to determine the building density information of the set of buildings in the selected area. Then, based on the degree of aggregation of the spatial distribution of buildings indicated by the building density information, a suitable address can be selected in the selected area for facility layout.

[0054] In one possible implementation, when the pre-selected division mode is the quantity control mode, in step 120, the building area is divided into multiple grids based on the pre-selected division mode. The building area can be divided into multiple grids based on a dynamic quantity factor.

[0055] The quantity control mode can be used to control the total number of grids obtained from multiple grid divisions. In the quantity control mode, a dynamic quantity factor can be preset. The dynamic quantity factor is used to control the total number of grids obtained from multiple grid divisions, and the dynamic quantity factor is positively correlated with the total number of grids obtained.

[0056] In one possible implementation, the dynamic quantity factor can be user-defined. The user interface can provide options for selecting a pre-selected partitioning mode. In response to the selection of a quantity control mode, and confirming that the pre-selected partitioning mode is quantity control mode, settings for setting the dynamic quantity factor can be displayed in the user interface for user customization. Optionally, a recommended range of values ​​for the dynamic quantity factor can be provided, allowing users to set values ​​based on this range. For example, the recommended range could be 5 ≤ N ≤ 500, where N is the dynamic quantity factor and is a positive integer.

[0057] In one possible implementation, if the user does not set a dynamic quantity factor, a pre-set default value can be used as the dynamic quantity factor, for example, the default value can be 50.

[0058] In one possible implementation, such as Figure 2 As shown, the process of dividing a building area into multiple grids based on a dynamic quantity factor can include the following steps: Step 1201: Determine the longitude span and latitude span of the area corresponding to the property development.

[0059] Optionally, the regional longitude span value corresponding to the building area is used to characterize the size of the longitude span of the building area. It can be determined according to the longitude range corresponding to the above set of buildings. For example, the regional longitude span value can be the difference between the maximum and minimum longitudes included in the longitude range (i.e., maxLon-minLon).

[0060] Optionally, the latitude span value corresponding to the property area is used to characterize the size of the latitude span of the property area. It can be determined based on the latitude range corresponding to the above property set. For example, the latitude span value can be the difference between the maximum and minimum latitudes included in the latitude range (i.e., maxLat-minLat).

[0061] Step 1202: Determine the grid longitude span value corresponding to the grid based on the regional longitude span value and the dynamic quantity factor.

[0062] In one possible implementation, the regional longitude span value can be equally divided based on a dynamic quantity factor to determine the grid longitude span value corresponding to each grid, wherein the grid longitude span value corresponding to each grid after equal division is the same.

[0063] In one example, the grid longitude span value can be the ratio of the region longitude span value to the dynamic quantity factor, which is (maxLon-minLon) / N.

[0064] Step 1203: Determine the grid latitude span value corresponding to the grid based on the regional latitude span value and the dynamic quantity factor.

[0065] In one possible implementation, the latitudinal span value of the region can be equally divided based on a dynamic quantity factor to determine the grid latitudinal span value corresponding to each grid, with each grid having the same grid latitudinal span value. For example, the grid latitudinal span value can be the ratio of the regional latitudinal span value to the dynamic quantity factor, i.e., (maxLat-minLat) / N.

[0066] Step 1204: Based on the grid longitude span value and grid latitude span value, divide the building area into multiple grids.

[0067] Based on the determined grid longitude span and grid latitude span values, the property area can be divided into multiple grids of equal area. Referring to the example above, based on the grid longitude span value (maxLon - minLon) / N and the grid latitude span value (maxLat - minLat) / N, the property area can be divided into N×N grids of equal area.

[0068] In this embodiment, under the quantity control mode, the number of grids to be divided can be controlled by a dynamic quantity factor. By adjusting the dynamic quantity factor, the longitude of the grid to be divided can be quickly adjusted, thereby controlling the analysis granularity for determining building density information. This allows for the determination of building density information at different analysis granularities, enabling the rapid and accurate acquisition of building density information at different analysis granularities.

[0069] In another possible implementation, when the pre-selected division mode is the scale control mode, in step 120, the building area is divided into multiple grids based on the pre-selected division mode. The building area can be divided into multiple grids based on the preset latitude and longitude scale, and the latitude and longitude span of each grid in the multiple grids is the same as the preset latitude and longitude scale.

[0070] The scale control mode can be used to control the latitude and longitude span of multiple grids obtained from the division. In scale control mode, latitude and longitude scales can be set, which can be used to control the latitude and longitude span of each grid, so that the boundary coordinates of the divided grids are accurately aligned with the actual geographic coordinates, thereby achieving accurate division of the region. It can be applied to scenarios such as cross-regional comparative analysis or high-precision site selection.

[0071] In one possible implementation, the latitude and longitude scale may include a longitude scale and a latitude scale, where the longitude scale can serve as the grid's longitude span value, and the latitude scale can serve as the grid's latitude span value. Optionally, the latitude and longitude scales may be the same or different.

[0072] In one possible implementation, the latitude and longitude scale can be user-defined. The user interface can provide options for selecting a pre-selected division mode. In response to the selection operation of the scale control mode, and confirming that the pre-selected division mode is the scale control mode, settings for setting the latitude and longitude scale can be displayed in the user interface for user customization. Optionally, separate settings for setting the longitude scale and latitude scale can be included, for setting the longitude and latitude scales respectively. Alternatively, a single setting can be included, using the set scale value as both the longitude and latitude scales; that is, in this method, the longitude and latitude scales use the same preset scale value. Optionally, a recommended range of values ​​for the latitude and longitude scales can be provided, allowing users to set values ​​based on the recommended range. For example, the recommended range could be... ,in, This indicates latitude and longitude scales, which may include longitude scales. with latitude scale .

[0073] In one possible implementation, if the user does not set the latitude and longitude scale, a pre-set default value can be used as the latitude and longitude scale. For example, the default value could be... (Approximately 1 meter distance), both longitude and latitude scales can be used. .

[0074] In one possible implementation, such as Figure 3 As shown, the area of ​​the building complex is divided into multiple grids based on a preset latitude and longitude scale, including: Step 120a: Based on the preset latitude and longitude scale, determine the grid longitude span value and grid latitude span value corresponding to the grid.

[0075] In one possible implementation, a preset latitude and longitude scale can be obtained. If the preset latitude and longitude scale includes a preset scale value, this preset scale value can be determined as the grid's longitude span value and grid's latitude span value. For example, the preset latitude and longitude scale is... In this case, determine the latitude and longitude span of the grid as [ , ].

[0076] In one possible implementation, if the preset latitude and longitude scale includes a preset longitude scale... and latitude scale Longitude scale can be Determine the grid's longitude span value, and then set the latitude scale. The grid's latitude span value is determined as the grid's latitude and longitude span value. .

[0077] Step 120b: Based on the grid longitude span value and the grid latitude span value, divide the building area into multiple grids.

[0078] In one possible implementation, after determining the grid longitude span value and the grid latitude span value, the regional longitude span value of the building area can be equally divided based on the grid longitude span value, and the regional latitude span value of the building area can be equally divided based on the grid latitude span value, resulting in multiple grids.

[0079] In one possible implementation, during the process of dividing the latitude and longitude span of a building area, if the remaining boundary values ​​are insufficient to meet a preset latitude and longitude scale when dividing to the boundary values, the boundary values ​​can be automatically expanded to obtain a complete grid. For example, when dividing the longitude span, if the remaining longitude boundary values ​​are insufficient to meet the preset longitude scale, the longitude boundary area can be expanded to ensure that the remaining longitude boundary values ​​meet the preset longitude scale. Similarly, when dividing the latitude span, if the remaining latitude boundary values ​​are insufficient to meet the preset latitude scale, the latitude boundary area can be expanded to ensure that the remaining latitude boundary values ​​meet the preset latitude scale. Through this method, the building area can be divided into multiple grids with the same latitude and longitude span.

[0080] In this embodiment, under the scale control mode, the building area can be divided based on the preset latitude and longitude scale, so that the latitude and longitude boundaries of each grid are strictly aligned with the geographic coordinates. This can improve the accuracy of the divided grids, which helps to improve the accuracy of determining the building density information and achieve high-precision analysis.

[0081] In one possible implementation, such as Figure 4 As shown, the process of determining the target grid to which a building belongs among multiple grids may include the following steps: Step 1301: Determine the latitude and longitude coordinates of the building and the latitude and longitude range of each grid in the multiple grids.

[0082] In one possible implementation, after dividing the property area into multiple grids based on a pre-selected division mode, the longitude boundary coordinates of each grid can be determined based on the grid longitude span value and the minimum longitude value of the property area. Similarly, the latitude boundary coordinates of each grid can be determined based on the grid latitude span value and the minimum latitude value of the property area. Thus, the latitude and longitude range corresponding to each grid in the multiple grids can be determined, i.e., the latitude and longitude boundary coordinates.

[0083] For any property in the property collection, its latitude and longitude coordinates can be obtained. Then, based on the property's latitude and longitude coordinates and the latitude and longitude range of each grid, the target grid to which the property belongs can be determined.

[0084] Step 1302: Based on the latitude and longitude coordinates of the building and the latitude and longitude range of each grid, determine the target grid to which the building belongs.

[0085] Optionally, the latitude and longitude range corresponding to a grid includes the minimum longitude coordinates and maximum longitude coordinates of the grid, as well as the minimum latitude coordinates and maximum latitude coordinates of the grid. Based on the latitude and longitude coordinates corresponding to the property and the latitude and longitude range corresponding to each grid, the latitude and longitude range to which the property belongs can be determined, thereby determining the target grid to which the property belongs.

[0086] In one possible implementation, the latitude and longitude coordinates of the building can be rounded based on the grid's precision (i.e., the latitude and longitude span) to accurately determine the corresponding latitude and longitude range. In one example, the grid's latitude and longitude span value is... In this case, the latitude and longitude coordinates of the property can be rounded down or rounded to three decimal places. For example, if the latitude and longitude coordinates of the property (Lon, Lat) are ( , In the case of a grid, the latitude and longitude span values ​​can be rounded to obtain the rounded latitude and longitude coordinates of the geographic coordinates. , ).

[0087] In one possible implementation, the target grid to which each building belongs can be determined based on the rounded latitude and longitude coordinates of the geographical coordinates corresponding to the building and the latitude and longitude range of each grid.

[0088] In one possible implementation, the property is determined to belong to the target grid in response to the fact that the property's latitude and longitude coordinates fall within the latitude and longitude range of the target grid. Specifically, if the Lon value in the property's latitude and longitude coordinates (Lon, Lat) is greater than the minimum longitude value and less than the maximum longitude value of the target grid, and the Lat value is greater than the minimum latitude value and less than the maximum latitude value of the target grid, then the property is determined to belong to the target grid.

[0089] In one example, such as Figure 5 As shown, the latitude and longitude coordinates of building 51 belong to the latitude and longitude range of grid A, thus confirming that building 51 belongs to grid A.

[0090] In one possible implementation, in response to the fact that the latitude and longitude coordinates corresponding to the property belong to the boundary values ​​of the latitude and longitude ranges corresponding to multiple candidate grids, it is determined that the property belongs to the target grid among the multiple candidate grids. Here, the candidate grid is the grid to which the grid boundary where the latitude and longitude coordinates are located belongs. That is, in one possible case, the latitude and longitude coordinates corresponding to the property are located at the grid boundary where multiple candidate grids intersect. In this case, the default grid among the multiple candidate grids can be determined as the target grid to which the property belongs.

[0091] Optionally, the default grid in the candidate grids can be any grid among multiple candidate grids.

[0092] Alternatively, the default grid in the candidate grids can be the last grid among multiple candidate grids, where the last grid can be the grid containing the maximum latitude and longitude coordinates. In one example, such as... Figure 5 As shown, the latitude and longitude coordinates of building 52 are located at the boundary of grid A and grid B. Grid B is the last grid among the two (grid A and grid B), so grid B can be identified as the target grid to which building 52 belongs. Similarly, the latitude and longitude coordinates of building 54 are located at the boundary of grid B and grid D. Grid D is the last grid among the two (grid B and grid D), so grid D can be identified as the target grid to which building 54 belongs. Likewise, the latitude and longitude coordinates of building 53 are located at the boundary of grids A, B, C, and D. Grid D is the last grid among the four, so grid D can be identified as the target grid to which building 53 belongs.

[0093] In this embodiment, the target grid to which each building belongs is determined based on the latitude and longitude coordinates of the building and the latitude and longitude range of each grid. The target grid to which each building belongs can be accurately determined based on the geographical location of the building, that is, the spatial distribution location of the building in the building area can be accurately determined. Then, the building density information can be determined by combining the spatial distribution location of each building, which can improve the accuracy of determining the building density information.

[0094] In one possible implementation, such as Figure 6 As shown, the execution process of step 140 above may include the following steps: Step 1401: Determine the number of effective grids based on the target grids corresponding to each of the multiple buildings.

[0095] In one possible implementation, after determining the target grid to which each building belongs, the number of effective grids can be counted. Here, an effective grid refers to a grid that contains at least one building, and the number of effective grids refers to the total number of grids that contain at least one building.

[0096] In one possible implementation, after determining the target grid to which each building belongs, records can be made based on the grid index of the target grid, that is, the grid index corresponding to each building can be recorded. When counting the number of valid grids, the total number of different indexes in the grid index corresponding to each building can be determined, and the total number of different indexes can be determined as the number of valid grids.

[0097] Step 1402: Determine building density information based on the number of effective grids and the total number of buildings.

[0098] In one possible implementation, the ratio of the total number of buildings to the number of effective grids can be defined as building density, which reflects the spatial sparseness of the building cluster. That is, building density = total number of buildings / number of effective grids. This represents the average number of buildings per effective grid and reflects the degree of clustering of buildings within the area corresponding to the effective grid. A higher building density value indicates a higher degree of building clustering.

[0099] In this embodiment, based on the effective grids containing buildings and the total number of buildings in the multiple grids obtained by division, the building density is determined. The building density information corresponding to the effective grids can be determined, thereby eliminating the interference of invalid grids (i.e. invalid areas) on the building density calculation. The building density information reflecting the degree of building agglomeration in the effective area can be determined efficiently and accurately, improving the accuracy and efficiency of building density calculation.

[0100] In one possible implementation, such as Figure 7 The diagram illustrates a flowchart of a method for determining building density information provided in another exemplary embodiment of this disclosure. The method includes the following steps: Step 710: Obtain the set of building coordinates.

[0101] The set of building coordinates is the set of latitude and longitude coordinates of multiple buildings included in the building set.

[0102] Step 720: Determine the latitude and longitude boundaries of the property area.

[0103] In one possible implementation, the latitude and longitude boundaries of the property area can be determined based on the set of property coordinates, including the longitude range and the latitude range.

[0104] Step 730: Determine the pre-selected partitioning mode.

[0105] After obtaining the latitude and longitude boundaries of the property area, the user-defined pre-selected division mode can be obtained to divide the property area into grids according to the pre-selected division mode.

[0106] Step 740: In response to the pre-selected division mode being the quantity control mode, obtain the dynamic quantity factor, and divide the building area into multiple grids based on the dynamic quantity factor.

[0107] Step 750: In response to the pre-selected division mode being scale control mode, obtain the preset latitude and longitude scale, and divide the building area into multiple grids based on the preset latitude and longitude scale.

[0108] Step 760: Determine the number of valid grids and the total number of buildings corresponding to the building set.

[0109] After dividing the area into multiple grids, we can determine the target grid to which each property belongs, and then count the number of grids in the target grid to obtain the number of effective grids.

[0110] Step 770: Determine the building density information.

[0111] After determining the number of effective grids and the total number of buildings, the building density can be determined based on the number of effective grids and the total number of buildings.

[0112] The specific implementation methods for steps 710-770 can be referred to the above embodiments, and will not be repeated here.

[0113] In one possible implementation, such as Figure 8 The diagram illustrates a structural schematic of a building density information determination device provided in an exemplary embodiment of this disclosure. This device can be deployed in the aforementioned electronic device to implement the building density information determination method described in any of the above embodiments. The device includes: The area determination module 810 is used to determine the building area based on the boundary information corresponding to the building set with density to be determined, wherein the building area includes multiple buildings included in the building set; The grid division module 820 is used to divide the building area into multiple grids. The grid determination module 830 is used to determine the target grid to which any building belongs among the plurality of grids for any building in the set of buildings; The density determination module 840 is used to determine the building density information of the building set based on the target grid corresponding to each of the multiple buildings and the total number of buildings in the building set.

[0114] In one possible implementation, the mesh division module 820 described above is further used for: In response to the pre-selected division mode being a quantity control mode, the building area is divided into grids based on a dynamic quantity factor to obtain the multiple grids. The dynamic quantity factor is positively correlated with the total number of grids obtained. In response to the pre-selected division mode being scale control mode, the building area is divided into grids based on a preset latitude and longitude scale to obtain multiple grids, wherein the latitude and longitude span of each grid is the same as the preset latitude and longitude scale.

[0115] In one possible implementation, the mesh division module 820 described above is further used for: Determine the longitude span and latitude span of the area corresponding to the property development; Based on the regional longitude span value and the dynamic quantity factor, the grid longitude span value corresponding to the grid is determined; Based on the regional latitudinal span value and the dynamic quantity factor, the latitudinal span value of the corresponding grid is determined; Based on the grid longitude span value and the grid latitude span value, the building area is divided into the multiple grids.

[0116] In one possible implementation, the mesh division module 820 described above is further used for: Based on the preset latitude and longitude scale, determine the grid longitude span value and grid latitude span value corresponding to the grid; Based on the grid longitude span value and the grid latitude span value, the building area is divided into the multiple grids.

[0117] In one possible implementation, the mesh determination module 830 described above is further configured to: Determine the latitude and longitude coordinates corresponding to the building and the latitude and longitude range corresponding to each of the multiple grids; Based on the latitude and longitude coordinates corresponding to the building and the latitude and longitude ranges corresponding to each grid, the target grid to which the building belongs is determined.

[0118] In one possible implementation, the mesh determination module 830 described above is further configured to: In response to the fact that the latitude and longitude coordinates corresponding to the building belong to the latitude and longitude range of the target grid, it is determined that the building belongs to the target grid; In response to the boundary value of the latitude and longitude coordinates corresponding to the property belonging to the latitude and longitude range of multiple candidate grids, it is determined that the property belongs to the target grid among the multiple candidate grids.

[0119] In one possible implementation, the density determination module 840 is further configured to: Based on the target grid corresponding to each of the multiple properties, the number of effective grids is determined; Based on the number of effective grids and the total number of buildings, the building density information is determined.

[0120] The device for determining building density information in this disclosure corresponds to the embodiment of the method for determining building density information described above, and the relevant content can be referred to each other, which will not be repeated here. The beneficial technical effects of the device for determining building density information in this disclosure can be referred to the corresponding beneficial technical effects in the above-described exemplary method section, which will not be repeated here.

[0121] In addition, this disclosure also provides an electronic device, including: Memory, used to store computer programs; A processor is configured to execute a computer program stored in the memory, and when the computer program is executed, to implement the method for determining building density information as described in any of the above embodiments of this disclosure.

[0122] Figure 9 This is a schematic diagram illustrating the structure of an application embodiment of the electronic device disclosed herein. Below, reference is made to… Figure 9 To describe an electronic device according to embodiments of this disclosure. For example... Figure 9 As shown, the electronic device includes one or more processors and memory.

[0123] A processor can be a central processing unit (CPU) or other form of processing unit with data processing and / or instruction execution capabilities, and can control other components in an electronic device to perform desired functions.

[0124] The memory may include one or more computer program products, which may include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. The volatile memory may include, for example, random access memory (RAM) and / or cache memory. The non-volatile memory may include, for example, read-only memory (ROM), hard disk, flash memory, etc. One or more computer program instructions may be stored on the computer-readable storage medium, and a processor may execute the program instructions to implement the methods for determining building density information according to the various embodiments of this disclosure described above, and / or other desired functions.

[0125] In one example, the electronic device may also include input devices and output devices, which are interconnected via a bus system and / or other forms of connection mechanism (not shown).

[0126] In addition, the input device may include, for example, a keyboard, a mouse, etc.

[0127] This output device can output various information to the outside, including determined distance information, direction information, etc. The output device may include, for example, a display, a speaker, a printer, and a communication network and its connected remote output devices, etc.

[0128] Of course, for the sake of simplicity, Figure 9 Only some of the components of the electronic device relevant to this disclosure are shown, omitting components such as buses, input / output interfaces, etc. In addition, the electronic device may include any other suitable components depending on the specific application.

[0129] In addition to the methods and devices described above, embodiments of this disclosure may also be computer program products, including computer program instructions that, when executed by a processor, cause the processor to perform the steps in the methods for determining building density information according to various embodiments of this disclosure as described in the foregoing portion of this specification.

[0130] The computer program product can be written in any combination of one or more programming languages ​​to perform the operations of the embodiments of this disclosure. The programming languages ​​include object-oriented programming languages ​​such as Java and C++, as well as conventional procedural programming languages ​​such as C or similar languages. The program code can be executed entirely on a user's computing device, partially on a user's computing device, as a standalone software package, partially on a user's computing device and partially on a remote computing device, or entirely on a remote computing device or server.

[0131] Furthermore, embodiments of this disclosure may also be computer-readable storage media storing computer program instructions that, when executed by a processor, cause the processor to perform the steps in the methods for determining building density information according to various embodiments of this disclosure as described in the foregoing portion of this specification.

[0132] The computer-readable storage medium may be any combination of one or more readable media. A readable medium may be a readable signal medium or a readable storage medium. A readable storage medium may be, for example, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of readable storage media (a non-exhaustive list) include: an electrical connection having one or more wires, a portable disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof.

[0133] Those skilled in the art will understand that all or part of the steps of the above method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When the program is executed, it performs the steps of the above method embodiments. The aforementioned storage medium includes various media that can store program code, such as ROM, RAM, magnetic disk, or optical disk.

[0134] The basic principles of this disclosure have been described above with reference to specific embodiments. However, it should be noted that the advantages, benefits, and effects mentioned in this disclosure are merely examples and not limitations, and should not be considered as essential features of each embodiment of this disclosure. Furthermore, the specific details disclosed above are for illustrative and facilitative purposes only, and are not limitations. These details do not limit the scope of this disclosure to the necessity of employing the aforementioned specific details for implementation.

[0135] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For system embodiments, since they largely correspond to method embodiments, the description is relatively simple; relevant parts can be referred to the descriptions in the method embodiments.

[0136] The block diagrams of devices, apparatuses, devices, and systems disclosed herein are merely illustrative examples and are not intended to require or imply that they must be connected, arranged, or configured in the manner shown in the block diagrams. As those skilled in the art will recognize, these devices, apparatuses, devices, and systems can be connected, arranged, and configured in any manner. Words such as “comprising,” “including,” “having,” etc., are open-ended terms meaning “including but not limited to,” and are used interchangeably with them. The terms “or” and “and” as used herein refer to the terms “and / or,” and are used interchangeably with them unless the context clearly indicates otherwise. The term “such as” as used herein refers to the phrase “such as but not limited to,” and is used interchangeably with it.

[0137] The methods and apparatus of this disclosure may be implemented in many ways. For example, they may be implemented by software, hardware, firmware, or any combination of software, hardware, and firmware. The above-described order of steps for the methods is for illustrative purposes only, and the steps of the methods of this disclosure are not limited to the order specifically described above unless otherwise specifically stated. Furthermore, in some embodiments, this disclosure may also be implemented as a program recorded on a recording medium, the program including machine-readable instructions for implementing the methods according to this disclosure. Thus, this disclosure also covers recording media storing programs for performing the methods according to this disclosure.

[0138] It should also be noted that in the apparatus, devices, and methods of this disclosure, the components or steps can be disassembled and / or recombined. These disassemblies and / or recombinations should be considered as equivalent solutions to this disclosure.

[0139] The above description of the disclosed aspects is provided to enable any person skilled in the art to make or use this disclosure. Various modifications to these aspects will be readily apparent to those skilled in the art, and the general principles defined herein may be applied to other aspects without departing from the scope of this disclosure. Therefore, this disclosure is not intended to be limited to the aspects shown herein, but rather to be carried out within the widest scope consistent with the principles and novel features disclosed herein.

[0140] The above description has been given for purposes of illustration and description. Furthermore, this description is not intended to limit the embodiments of this disclosure to the forms disclosed herein. Although numerous exemplary aspects and embodiments have been discussed above, those skilled in the art will recognize certain variations, modifications, alterations, additions, and sub-combinations therein.

Claims

1. A method for determining building density information, characterized in that, The method includes: Based on the boundary information corresponding to the set of properties, the property area is determined, where the property area is the region to which multiple properties included in the property set belong; Based on the pre-selected division mode, the building area is divided into grids to obtain multiple grids. The accuracy of the grids obtained under different pre-selected division modes is different. For any property in the set of properties, determine the target grid to which the property belongs among the plurality of grids; Based on the target grid corresponding to each of the multiple properties and the total number of properties in the property set, the property density information of the property set is determined.

2. The method according to claim 1, characterized in that, The building area is divided into multiple grids based on a pre-selected partitioning pattern, including: In response to the pre-selected division mode being a quantity control mode, the building area is divided into grids based on a dynamic quantity factor to obtain the multiple grids. The dynamic quantity factor is positively correlated with the total number of grids obtained. In response to the pre-selected division mode being scale control mode, the building area is divided into grids based on a preset latitude and longitude scale to obtain multiple grids, wherein the latitude and longitude span of each grid is the same as the preset latitude and longitude scale.

3. The method according to claim 2, characterized in that, The grid division of the property area based on a dynamic quantity factor yields the multiple grids, including: Determine the longitude span and latitude span of the area corresponding to the property development; Based on the regional longitude span value and the dynamic quantity factor, the grid longitude span value corresponding to the grid is determined; Based on the regional latitudinal span value and the dynamic quantity factor, the latitudinal span value of the corresponding grid is determined; Based on the grid longitude span value and the grid latitude span value, the building area is divided into the multiple grids.

4. The method according to claim 2, characterized in that, The process of dividing the property area into grids based on a preset latitude and longitude scale to obtain the multiple grids includes: Based on the preset latitude and longitude scale, determine the grid longitude span value and grid latitude span value corresponding to the grid; Based on the grid longitude span value and the grid latitude span value, the building area is divided into the multiple grids.

5. The method according to any one of claims 1 to 4, characterized in that, Determining the target grid to which the property belongs among the multiple grids includes: Determine the latitude and longitude coordinates corresponding to the building and the latitude and longitude range corresponding to each of the multiple grids; Based on the latitude and longitude coordinates corresponding to the building and the latitude and longitude ranges corresponding to each grid, the target grid to which the building belongs is determined.

6. The method according to claim 5, characterized in that, The process of determining the target grid to which the building belongs based on the latitude and longitude coordinates corresponding to the building and the latitude and longitude ranges corresponding to each grid includes: In response to the fact that the latitude and longitude coordinates corresponding to the building belong to the latitude and longitude range of the target grid, it is determined that the building belongs to the target grid; In response to the boundary value of the latitude and longitude coordinates corresponding to the property belonging to the latitude and longitude range of multiple candidate grids, it is determined that the property belongs to the target grid among the multiple candidate grids.

7. The method according to any one of claims 1 to 4, characterized in that, The process of determining the building density information of the building set based on the target grid corresponding to each of the multiple building sets and the total number of building sets includes: Based on the target grid corresponding to each of the multiple properties, the number of effective grids is determined; Based on the number of effective grids and the total number of buildings, the building density information is determined.

8. A device for determining building density information, characterized in that, The device includes: The area determination module is used to determine the building area based on the boundary information corresponding to the set of buildings with a density to be determined. The building area includes multiple buildings included in the set of buildings. The grid division module is used to divide the building area into multiple grids. The grid determination module is used to determine the target grid to which any building belongs among the multiple grids for any building in the set of buildings; The density determination module is used to determine the building density information of the building set based on the target grid corresponding to each of the multiple buildings and the total number of buildings in the building set.

9. An electronic device, characterized in that, include: Memory, used to store computer programs; A processor is configured to execute a computer program stored in the memory, wherein when the computer program is executed, it implements the method for determining building density information as described in any one of claims 1-7.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, it implements the method for determining building density information as described in any one of claims 1-7.

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