CN111260521A - City boundary acquisition method and device, intelligent terminal and storage medium - Google Patents
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Abstract
The invention discloses a city boundary acquisition method, a city boundary acquisition device, an intelligent terminal and a storage medium. The method comprises the following steps: acquiring a road intersection point set according to road network data, constructing a quadtree for road intersections in the point set, wherein each leaf node of the quadtree stores one road intersection point; calculating a density value according to the geometric information of the rectangle corresponding to the leaf node, and classifying the rectangle corresponding to the leaf node according to the density value; and carrying out non-transregional fusion Dissolve processing on the classified rectangles according to the adjacent topological relation to obtain the city boundary. The invention improves the spatial quad-tree index processing method for the spatial information of the urban big data, and clusters according to the nonlinear density characteristic of the data of the type. Compared with the traditional urban data clustering method, the method does not need to set parameters in advance, and is high in speed and strong in expandability.
Description
Technical Field
The invention relates to the technical field of spatial data analysis, in particular to a city boundary acquisition method and device, an intelligent terminal and a storage medium.
Background
The urban calculation shows that valuable information is mined from urban multi-source heterogeneous big data by using a computer technology, and scientific laws of connotation in cities are explored, so that efficient and healthy operation of the cities is promoted for human life service better.
The city represents an area with highly concentrated human living life, and the accurate description of the city boundary can help the government to monitor whether the city construction area is expanded disorderly or not and coordinate and plan the relationship between city resident travel and public facility configuration, thus contributing to the sustainable development of the city, and being an important content of city calculation.
Currently, the boundaries of cities are determined by local authorities or governments, and this top-down approach may be in and out of areas of real human activity. In addition, some technologies define the boundary of the city by methods such as an information entropy method, a breakpoint analysis method, remote sensing night light interpretation and the like, and the methods mainly have two disadvantages: 1. the definition of artificial threshold values is fuzzy, the efficiency and the subjectivity are strong, and the accuracy and the objectivity are difficult to achieve 2. the construction efficiency of a data structure (such as a triangular surface) supported in the range definition is very low, and an ideal result cannot be obtained when the data volume is large.
Accordingly, the prior art is yet to be improved and developed.
Disclosure of Invention
In view of the defects of the prior art, the invention aims to provide a method and a device for acquiring an urban boundary, an intelligent terminal and a storage medium, and aims to solve the problems of low efficiency and strong subjectivity of an urban boundary dividing method in the prior art.
The technical scheme adopted by the invention for solving the technical problems is as follows:
in a first aspect, an embodiment of the present invention provides a method for acquiring a city boundary, where the method includes:
acquiring a road intersection point set according to road network data, constructing a quadtree for road intersection points in the road intersection point set, wherein each leaf node of the quadtree stores one road intersection point;
calculating a density value according to the geometric information of the rectangle corresponding to each leaf node, and dividing the rectangle corresponding to each leaf node into a target rectangle and a background rectangle according to the density value; the density value is the reciprocal of the area of the rectangle;
and carrying out non-transregional fusion processing on the classified target rectangles according to the adjacent topological relation to obtain the city boundary.
The urban boundary acquisition method comprises the following specific construction processes of constructing the quadtree:
calculating the outer envelope rectangles of all the road intersections, and taking the outer envelope rectangles as root nodes;
generating a quadtree with the depth of N, calculating the relation between each road intersection and a leaf node rectangle, and storing the rectangles with the number of points less than or equal to 1 in the leaf node rectangles; n is a natural number which is more than 1 and less than 9;
independently generating a quadtree for rectangles with each point number larger than 1 until the point number in all leaf node rectangles is less than or equal to 1, and storing the rectangles; and integrating all rectangles with the point number less than or equal to 1, and finishing.
The city boundary obtaining method includes the steps of calculating density values according to geometric information of rectangles corresponding to the leaf nodes, and dividing the rectangles corresponding to the leaf nodes into a target rectangle and a background rectangle according to the density values, and specifically includes:
dividing all rectangles into a target rectangle-like part and a background rectangle-like part by using formula (1)
Where d is the segmentation threshold of the target and background, σwIs the difference between the target and background density values, w0The number of target points in the image scale, sigma0Is the variance of the target point number in the image proportion, w1The number of background points in the image scale, σ1The variance of the background points in the image proportion is taken as the variance; all rectangle information in the target class is extracted.
The urban boundary acquisition method comprises the following steps of performing non-trans-regional fusion processing on the classified target rectangles according to an adjacent topological relation to obtain an urban boundary, wherein the non-trans-regional fusion processing comprises the following steps:
screening out adjacent rectangles of the sorted target rectangles from any one of the sorted target rectangles, and storing the adjacent rectangles into a preset set;
traversing each adjacent rectangle, repeating the steps to screen out the adjacent rectangle with the rectangle, and storing the adjacent rectangle into a preset set until no new adjacent rectangle exists;
and eliminating the common edges of all the rectangles in the set, generating a city boundary and ending.
The city boundary obtaining method, wherein N is 7.
In a second aspect, an urban boundary acquisition device, the device comprising:
the system comprises a quadtree construction unit, a data processing unit and a data processing unit, wherein the quadtree construction unit is used for acquiring a road intersection point set according to road network data and constructing a quadtree for road intersections in the road intersection point set, and each leaf node of the quadtree stores one road intersection point;
the rectangle classification unit is used for calculating a density value according to the geometric information of the rectangle corresponding to each leaf node and classifying the rectangle corresponding to each leaf node into a target class and a background class according to the density value; the density value is the reciprocal of the area of the rectangle;
and the processing unit is used for carrying out non-transregional fusion processing on the classified target rectangles according to the adjacent topological relation to obtain the city boundary.
The apparatus described above, wherein the quadtree construction unit includes:
the calculation subunit is used for calculating the outer envelope rectangles of all the road intersections and taking the outer envelope rectangles as root nodes;
a generating subunit, which generates a quadtree with the depth of N, calculates the relationship between each road intersection and a leaf node rectangle, and stores rectangles with the number of points less than or equal to 1 in the leaf node rectangles; n is a natural number which is more than 1 and less than 9;
the storage subunit is used for independently generating a quadtree for the rectangles with each point number larger than 1 until the point number in all leaf node rectangles is less than or equal to 1, and storing the rectangles; and integrating all rectangles with the point number less than or equal to 1, and finishing.
The apparatus of, wherein the processing unit comprises:
a screening unit for screening out adjacent rectangles from any one of the classified target rectangles, and storing the adjacent rectangles into a preset set;
the traversal subunit is used for traversing each adjacent rectangle, repeating the steps to screen out the adjacent rectangle with the rectangle, and storing the adjacent rectangle into a preset set until no new adjacent rectangle exists;
and the elimination self-unit is used for eliminating the common edges of all the rectangles in the set, generating the city boundary and ending.
In a third aspect, an embodiment of the present invention also provides an intelligent terminal, including a memory, and one or more programs, where the one or more programs are stored in the memory, and configured to be executed by one or more processors includes a processor configured to execute the method described above.
In a fourth aspect, embodiments of the present invention also provide a non-transitory computer-readable storage medium, where instructions of the storage medium, when executed by a processor of an electronic device, enable the electronic device to perform the method as described above.
The invention has the beneficial effects that: the method for rapidly clustering road intersections nationwide and generating the urban boundary range by establishing the spatial quadtree can accurately describe the relationship between disordered expansion of the urban construction area monitored by the government and urban resident running and public facility configuration coordinated and planned, and has important significance for urban sustainable development.
Drawings
Fig. 1 is a flowchart of a preferred embodiment of a city boundary acquisition method provided by the present invention.
Fig. 2 is a flowchart of step S100 of the city boundary obtaining method according to the preferred embodiment of the present invention.
Fig. 3 is a schematic diagram of constructing a quadtree according to a preferred embodiment of the city boundary obtaining method provided in the present invention.
Fig. 4 is a schematic diagram of the national city space range after dispolve processing in the preferred embodiment of the city boundary obtaining method provided in the present invention.
Fig. 5 is a functional schematic diagram of the intelligent terminal provided by the invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention clearer and clearer, the present invention is further described in detail below with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
In the prior art, the following modes are mostly adopted for dividing and acquiring the urban boundary:
firstly, related departments plan and set, and by adopting the planning and setting mode, the subjectivity is strong, and the obtained city boundary has access to the actual city boundary. And secondly, by means of data information and methods such as an information entropy method, a breakpoint analysis method, remote sensing night light interpretation and the like, the construction efficiency of the data structure depending on the methods in a defined range is very low, and a desired result cannot be obtained when the data volume is large.
In order to solve the above technical problem, in the embodiment of the present invention, when a certain city needs to be bounded, national road network data or province road network data of the city may be acquired first. Road intersections (road intersection points) are analyzed according to the road network data, the road intersection points are gathered together to form a point set, then a full quadtree is constructed for the road intersection points, and each leaf node on the quadtree only stores one corresponding road intersection point. The area of the rectangle corresponding to the leaf node is calculated, so that the point density value is calculated, the rectangles corresponding to the leaf node are classified according to the point density value, the classification can be divided into two types, such as a target (city) and a background (non-city), and the points in the point set can be divided into the target type and the background type according to the point density value. And carrying out non-transregional fusion Dissolve processing on the rectangles in the target class according to the adjacent topological relation to obtain the city boundary.
The method for rapidly clustering road intersections nationwide and generating the urban boundary range by establishing the spatial quadtree can accurately describe the relationship between disordered expansion of the urban construction area monitored by the government and urban resident running and public facility configuration coordinated and planned, and has important significance for urban sustainable development.
For example, if a user wants to define the boundary of Shenzhen, the road network data of the whole Guangdong province or the whole Guangdong province is only used to obtain the road intersection point set, and then the boundaries of all cities (including Shenzhen city) of the whole Guangdong province or the whole China are generated according to the steps. Since city boundaries represent areas where human activity is relatively concentrated, to determine the boundary of a city, a larger range of regions must be selected to bound it. Otherwise, if only the road intersection in Shenzhen city is used, the obtained result is not the Shenzhen city boundary but the boundary of each region of Shenzhen.
Various non-limiting embodiments of the present invention are described in detail below with reference to the accompanying drawings.
Exemplary method
Referring to fig. 1, the present embodiment provides a method for acquiring a city boundary, including the following steps:
step 100, acquiring a road intersection point set according to road network data, and constructing a quadtree for road intersection points in the road intersection point set, wherein each leaf node of the quadtree stores one road intersection point.
Specifically, the road network data is mainly road network data, and may also be combined with railway network data, the road network data may be acquired through big data, and the specific acquisition of the road network data may be any one of the methods in the prior art as long as the requirements are met. Intersections of roads are analyzed from known road network data, each intersection in the road network data is marked as a point, and all the obtained road intersection points form a point set. A quadtree is constructed for all points in the set of points.
In this embodiment, the road intersection point set in the road network is obtained because the road intersection density reflects the construction condition of the urban infrastructure, and the actual spatial development of the urban land can be effectively determined by clustering the road intersection density.
Referring to fig. 2, in step S100, the construction of the quadtree includes:
s110, calculating outer envelope rectangles of all the road intersections, and taking the outer envelope rectangles as root nodes;
s120, generating a quadtree with the depth of N, calculating the relation between each road intersection and a leaf node rectangle, and storing the rectangles with the number of points less than or equal to 1 in the leaf node rectangles; n is a natural number which is more than 1 and less than 9;
s130, independently generating a quadtree for rectangles with each point number larger than 1 until the point number in all leaf node rectangles is less than or equal to 1, and storing the rectangles; and integrating all rectangles with the point number less than or equal to 1, and finishing.
In particular, in general, geospatial partitioning often uses a full quadtree structure to visualize spatial information (such as grid slices) of different scales, but the disadvantages of this approach are obvious. Generally, the map level is from the global scope to the street scale as high as 15-20 layers, if the map level is constructed in a full quadtree manner, the number of the needed rectangles reaching the sixteenth layer is as high as 50 hundred million, and the occupied space is as high as several TB bytes, which often exceeds the processing capacity of the computer memory. The invention adopts a construction method of a quadtree with breadth first and then depth, specifically, a full quadtree with N layers (such as 7-9 layers) is generated by a breadth-first method, space entity information is stored in a child node at the last layer, and then a depth-first mode recursion is carried out on an area containing more elements in the child node until only one space element exists. In order to avoid the imbalance of the quadtree structure and the waste of storage space, the geographic entity information is stored in the minimum rectangular node completely containing the geographic entity information and is not stored in the parent node of the geographic entity information, and each geographic entity is stored in the tree only once, so that the waste of storage space is avoided.
In this embodiment, the constructed quadtree is a full quadtree with a depth of 7, where the number of nodes of the full quadtree at 7 levels is 16384, and subsequent steps can be smoothly performed on this level, for example, if the quadtree is a depth of 9 levels, about 32G of memory is required.
S200, calculating a density value according to the geometric information of the rectangle corresponding to each leaf node, and dividing the rectangle corresponding to each leaf node into a target rectangle and a background rectangle according to the density value; the density value is the inverse of the area of the rectangle.
Step S200 is to calculate a threshold value by considering each rectangle as a pixel and calculating a density value (1/rectangular area) corresponding to each point as a pixel value, where the threshold value is a result calculated by the maximum inter-class variance (formula 1). Equation (1) is as follows:
where d is the segmentation threshold of the target and background, σwIs the difference between the target and background density values, w0The number of target points in the image scale, sigma0Is the variance of the target point number in the image proportion, w1The number of background points in the image scale, σ1The variance of the background points in the image proportion is taken as the variance;
when the pixel value is smaller than the pixel threshold value calculated by the formula (1), the rectangle is taken as a target, and when the pixel value is larger than the pixel threshold value calculated by the formula (1), the rectangle is taken as a background, namely all the rectangle information in the foreground class is extracted by adopting the method. Because of the two classes of classification, the background rectangle information can also be obtained after all the rectangle information in the foreground class.
And S300, performing non-trans-regional fusion processing on the classified rectangles according to the adjacent topological relation to obtain the city boundary.
Specifically, non-transregional fusion dispol processing is performed on the classified rectangles according to a topological relation, wherein the dispol processing represents fusion of adjacent (common) target rectangles, and the flow is as follows: and in the foreground type rectangle, finding a rectangle adjacent to the rectangle from any rectangle, storing the rectangle into a specified set, traversing each adjacent rectangle, and repeating the steps until no new adjacent rectangle exists. And eliminating the common edges of all rectangles in the set to form a new polygon, wherein the obtained new polygon is the city boundary.
As shown in fig. 3-4, fig. 3 is a schematic diagram of constructing a quadtree at all intersection points of roads according to national road network data. Fig. 4 is a schematic diagram of the spatial range of the cities nationwide after the dispolve processing in fig. 3, and the darker part in fig. 4 represents the range of the cities.
Based on the above embodiment, the present invention further provides an intelligent terminal, and a schematic block diagram thereof may be as shown in fig. 5. The intelligent terminal comprises a processor, a memory, a network interface, a display screen and a temperature sensor which are connected through a system bus. Wherein, the processor of the intelligent terminal is used for providing calculation and control capability. The memory of the intelligent terminal comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The network interface of the intelligent terminal is used for being connected and communicated with an external terminal through a network. The computer program is executed by a processor to implement a city boundary acquisition method. The display screen of the intelligent terminal can be a liquid crystal display screen or an electronic ink display screen, and the temperature sensor of the intelligent terminal is arranged inside the intelligent terminal in advance and used for detecting the current operating temperature of internal equipment.
It will be understood by those skilled in the art that the block diagram shown in fig. 5 is only a block diagram of a part of the structure related to the solution of the present invention, and does not constitute a limitation to the intelligent terminal to which the solution of the present invention is applied, and a specific intelligent terminal may include more or less components than those shown in the figure, or combine some components, or have a different arrangement of components.
In one embodiment, an intelligent terminal is provided that includes a memory, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs including instructions for:
acquiring a road intersection point set according to road network data, constructing a quadtree for road intersection points in the road intersection point set, wherein each leaf node of the quadtree stores one road intersection point;
calculating a density value according to the geometric information of the rectangle corresponding to each leaf node, and classifying the rectangles corresponding to the leaf nodes according to the density value; the density value is the reciprocal of the area of the rectangle;
and carrying out non-transregional fusion processing on the classified rectangles according to the adjacent topological relation to obtain the city boundary.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware instructions of a computer program, which can be stored in a non-volatile computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. Any reference to memory, storage, databases, or other media used in embodiments provided herein may include non-volatile and/or volatile memory. Non-volatile memory can include read-only memory (ROM), Programmable ROM (PROM), Electrically Programmable ROM (EPROM), Electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), Dynamic RAM (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDRSDRAM), Enhanced SDRAM (ESDRAM), Synchronous Link DRAM (SLDRAM), Rambus Direct RAM (RDRAM), direct bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).
In summary, the invention discloses a city boundary acquisition method, a city boundary acquisition device, an intelligent terminal and a storage medium. The method comprises the following steps: acquiring a road intersection point set according to road network data, constructing a quadtree for road intersections in the point set, wherein each leaf node of the quadtree stores one road intersection point; calculating a density value according to the geometric information of the rectangle corresponding to the leaf node, and classifying the rectangle corresponding to the leaf node according to the density value; the density value is the reciprocal of the area of the rectangle; and carrying out non-transregional fusion Dissolve processing on the classified rectangles according to the adjacent topological relation to obtain the city boundary. The invention improves the spatial quad-tree index processing method for the spatial information of the urban big data, and clusters according to the nonlinear density characteristic of the data of the type. Compared with the traditional urban data clustering method, the method does not need to set parameters in advance, is high in speed and expandability, and can effectively help to mine the non-linear spatial law of urbanization or human urban activities.
It is to be understood that the invention is not limited to the examples described above, but that modifications and variations may be effected thereto by those of ordinary skill in the art in light of the foregoing description, and that all such modifications and variations are intended to be within the scope of the invention as defined by the appended claims.
Claims (10)
1. A city boundary acquisition method, characterized in that the method comprises the steps of:
acquiring a road intersection point set according to road network data, constructing a quadtree for road intersection points in the road intersection point set, wherein each leaf node of the quadtree stores one road intersection point;
calculating a density value according to the geometric information of the rectangle corresponding to each leaf node, and dividing the rectangle corresponding to each leaf node into a target rectangle and a background rectangle according to the density value; the density value is the reciprocal of the square area of the moment;
and carrying out non-transregional fusion processing on the classified target rectangles according to the adjacent topological relation to obtain the city boundary.
2. The city boundary acquisition method according to claim 1, wherein the construction of the quadtree specifically comprises the following construction steps:
calculating the outer envelope rectangles of all the road intersections, and taking the outer envelope rectangles as root nodes;
generating a quadtree with the depth of N, calculating the relation between each road intersection and a leaf node rectangle, and storing the rectangles with the number of points less than or equal to 1 in the leaf node rectangles; n is a natural number which is more than 1 and less than 9;
independently generating a quadtree for rectangles with each point number larger than 1 until the point number in all leaf node rectangles is less than or equal to 1, and storing the rectangles; and integrating all rectangles with the point number less than or equal to 1, and finishing.
3. The method according to claim 1, wherein the step of calculating the density value according to the geometric information of the rectangle corresponding to the leaf node, and the step of dividing the rectangle corresponding to the leaf node into a target-like rectangle and a background-like rectangle according to the density value specifically comprises:
dividing all rectangles into a target rectangle-like part and a background rectangle-like part by using formula (1)
Where d is the segmentation threshold of the target and background, σwIs the difference between the target and background density values, w0The number of target points in the image scale, sigma0Is the variance of the target point number in the image proportion, w1The number of background points in the image scale, σ1The variance of the background points in the image proportion is taken as the variance; all rectangle information in the target class is extracted.
4. The urban boundary acquisition method according to claim 1, wherein the step of performing non-transregional fusion processing on the classified target rectangles according to the adjacent topological relation to obtain the urban boundary, the non-transregional fusion processing comprises the steps of:
screening out adjacent rectangles of the sorted target rectangles from any one of the sorted target rectangles, and storing the adjacent rectangles into a preset set;
traversing each adjacent rectangle, repeating the steps to screen out the adjacent rectangle with the rectangle, and storing the adjacent rectangle into a preset set until no new adjacent rectangle exists;
and eliminating the common edges of all the rectangles in the set, generating a city boundary and ending.
5. The city boundary acquisition method of claim 2, wherein N is 7.
6. An urban border acquisition device, characterized in that the device comprises:
the system comprises a quadtree construction unit, a data processing unit and a data processing unit, wherein the quadtree construction unit is used for acquiring a road intersection point set according to road network data and constructing a quadtree for road intersections in the road intersection point set, and each leaf node of the quadtree stores one road intersection point;
the rectangle classification unit is used for calculating a density value according to the geometric information of the rectangle corresponding to each leaf node and classifying the rectangles corresponding to the leaf nodes into a target rectangle and a background rectangle according to the density value; the density value is the reciprocal of the square area of the moment;
and the processing unit is used for carrying out non-transregional fusion processing on the classified target rectangles according to the adjacent topological relation to obtain the city boundary.
7. The apparatus of claim 6, wherein the quadtree construction unit comprises:
the calculation subunit is used for calculating the outer envelope rectangles of all the road intersections and taking the outer envelope rectangles as root nodes;
a generating subunit, which generates a quadtree with the depth of N, calculates the relationship between each road intersection and a leaf node rectangle, and stores rectangles with the number of points less than or equal to 1 in the leaf node rectangles; n is a natural number which is more than 1 and less than 9;
the storage subunit is used for independently generating a quadtree for the rectangles with each point number larger than 1 until the point number in all leaf node rectangles is less than or equal to 1, and storing the rectangles; and integrating all rectangles with the point number less than or equal to 1, and finishing.
8. The apparatus of claim 6, wherein the processing unit comprises:
a screening unit for screening out adjacent rectangles from any one of the classified target rectangles, and storing the adjacent rectangles into a preset set;
the traversal subunit is used for traversing each adjacent rectangle, repeating the steps to screen out the adjacent rectangle with the rectangle, and storing the adjacent rectangle into a preset set until no new adjacent rectangle exists;
and the eliminating subunit is used for eliminating the common edges of all the rectangles in the set, generating the city boundary and ending.
9. An intelligent terminal comprising a memory, and one or more programs, wherein the one or more programs are stored in the memory, and wherein the one or more programs being configured to be executed by the one or more processors comprises instructions for performing the method of any of claims 1-5.
10. A storage medium, wherein instructions in the storage medium, when executed by a processor of an electronic device, enable the electronic device to perform the method of any of claims 1-5.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN112257207A (en) * | 2020-10-27 | 2021-01-22 | 智慧足迹数据科技有限公司 | Road network boundary determining method and device, electronic equipment and storage medium |
| CN113591192A (en) * | 2021-07-30 | 2021-11-02 | 北京软通智慧科技有限公司 | Urban ventilation system analysis method and device, storage medium and electronic equipment |
| CN113591192B (en) * | 2021-07-30 | 2024-03-22 | 北京软通智慧科技有限公司 | Urban ventilation system analysis method and device, storage medium and electronic equipment |
| CN117272914A (en) * | 2023-10-31 | 2023-12-22 | 北京智芯仿真科技有限公司 | Method and device for quickly determining copper-clad shape to form topological structure based on quadtree |
| CN117272914B (en) * | 2023-10-31 | 2024-03-12 | 北京智芯仿真科技有限公司 | Method and device for quickly determining copper-clad shape to form topological structure based on quadtree |
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