Method and device for organizing and retrieving multi-level and multi-topic spatial data

Abstract

The embodiment of the present invention discloses a method and device for organizing and retrieving multi-level and multi-topic spatial data, the method comprising: obtaining the layer information of spatial data; generating an index library according to the layer information; obtaining the user's search information; determining the layer information of the spatial layer to which the target spatial data belongs from the index library according to the search information; determining the first spatial element object set, the first associated layer set and the first associated spatial element object set corresponding to the target spatial data according to the layer information; determining the second spatial element object set, the second associated layer set and the second associated spatial element object set corresponding to the target spatial data according to the layer information and the preset spatial association rules. The present invention realizes the organic association of cross-level and cross-topic spatial data, solves the retrieval of cross-level and cross-topic spatial data through the methods of spatial data coding backtracking, spatial association rule constraints and spatial relationship reasoning, and realizes the integrated collaborative management of multi-level and multi-topic spatial data.

Description

Technical Field

[0001] The present invention relates to the field of computer technology, and in particular to a method and device for organizing and retrieving multi-level and multi-topic spatial data. Background Art

[0002] Spatial data is the mapping of spatial objects in the real geographical world in computers, and is a conceptual abstraction of spatial objects in the real world. The real geographical world is complex, with various macro and micro geographical phenomena superimposed and interacting with each other, so spatial data itself has multi-level and multi-topic properties.

[0003] The multi-level nature of spatial data refers to the different degrees of abstraction of spatial objects at different scales, reflecting different geographical laws and phenomena. At the data level, it is manifested as different levels of detail and spatial forms of spatial objects at different spatial scales or scales. For example, a house is abstracted as a point without a specific shape and size on a small-scale map, while it is a polygon with a specific shape on a large-scale map. The multi-thematic nature of spatial data refers to the fact that different spatial objects have certain thematic attributes. For example, a curve may represent a river or a road. Only when the curve is given certain thematic attributes can spatial data have specific geographical meaning.

[0004] The existing spatial data organization method mainly organizes spatial objects with the same spatial scale and thematic attributes into one layer, and the layers are independent of each other. The traditional spatial data organization method with layers as the basic unit has a simple structure. This method breaks the inherent connection between spatial objects at multiple levels and multiple themes, making it difficult to organize, manage, retrieve and analyze cross-scale and cross-thematic spatial data.

[0005] In addition, the in-depth development of spatial information applications such as spatial big data and smart cities has promoted the development of spatial information applications from specialization to scale, integration, and systematization, requiring the organic integration of various types of spatial data to support the comprehensive analysis of multi-source spatial data. The spatial data organization method with layers as the basic unit lacks the organic connection between spatial data levels and topics, and it is difficult to meet the requirements of integrated analysis, processing, and mining of various types of spatial data across levels and topics.

[0006] In summary, due to the limitations of existing technologies, spatial data lacks associations between levels and topics. Therefore, there is an urgent need for a multi-level and multi-topic spatial data organization and retrieval technology to solve the problems of the above existing technologies. Summary of the invention

[0007] Since the existing methods have the above problems, the embodiments of the present invention provide a method and device for organizing and retrieving multi-level and multi-topic spatial data.

[0008] In a first aspect, an embodiment of the present invention provides a method for organizing and retrieving multi-level and multi-topic spatial data, including:

[0009] Get the layer information of spatial data;

[0010] Generate an index library according to the layer information;

[0011] Get the user's search information;

[0012] Determining layer information of the spatial layer to which the target spatial data belongs from the index library according to the search information; wherein the spatial layer includes a plurality of spatial element objects;

[0013] Determine, according to the layer information of the spatial layer to which the target spatial data belongs, a first spatial element object set, a first associated layer set, and a first associated spatial element object set corresponding to the target spatial data;

[0014] The second spatial element object set, the second associated layer set and the second associated spatial element object set corresponding to the target spatial data are determined according to the layer information of the spatial layer to which the target spatial data belongs and a preset spatial association rule.

[0015] Furthermore, the obtaining of the layer information of the spatial data includes:

[0016] Acquire the spatial attributes, thematic attributes and data types of the spatial data;

[0017] Determining hierarchical information of the spatial data according to the spatial attribute;

[0018] Determine the thematic information of the spatial data according to the thematic attributes;

[0019] Determine data type information of the spatial data according to the data type;

[0020] The layer information of the spatial data is determined according to the level information, the topic information and the data type information.

[0021] Furthermore, before determining the first spatial element object set, the first associated layer set, and the first associated spatial element object set corresponding to the target spatial data according to the layer information of the spatial layer to which the target spatial data belongs, the method further includes:

[0022] For the same spatial element object, the spatial element ID of the spatial element object on the spatial layer is determined according to the spatial layer to which the spatial element object belongs.

[0023] Further, the search information includes a search condition, and the determining the first spatial element object set, the first associated layer set, and the first associated spatial element object set corresponding to the target spatial data according to the layer information of the spatial layer to which the target spatial data belongs includes:

[0024] Determine the target layer corresponding to the target spatial data according to the layer information of the spatial layer to which the target spatial data belongs;

[0025] Determine a first set of spatial element objects that meet the search condition from the target layer according to the search information;

[0026] Determine the first associated layer set according to the target layer;

[0027] Obtaining a first spatial element ID set corresponding to the first spatial element object set;

[0028] A first associated spatial element object set is determined according to the first spatial element ID set.

[0029] Furthermore, the preset spatial association rule is determined by a spatial relationship operator and a constraint condition, and the second spatial element object set, the second associated layer set and the second associated spatial element object set corresponding to the target spatial data are determined according to the layer information of the spatial layer to which the target spatial data belongs and the preset spatial association rule, including:

[0030] The spatial relationship between the spatial element objects on different spatial layers is calculated by the spatial relationship operator; wherein the spatial relationship operator includes a geometric relationship operator and a semantic relationship operator;

[0031] Determining a calculation result of the spatial relationship operator according to the constraint condition;

[0032] The second spatial element object set, the second associated layer set and the second associated spatial element object set corresponding to the target spatial data are determined according to the calculation result of the spatial relationship operator and the layer information of the spatial layer to which the target spatial data belongs.

[0033] In a second aspect, an embodiment of the present invention provides a device for organizing and retrieving multi-level and multi-topic spatial data, including:

[0034] The acquisition module is used to obtain the layer information of spatial data;

[0035] A processing module is used to generate an index library according to the layer information; obtain the user's search information; and determine the layer information of the spatial layer to which the target spatial data belongs from the index library according to the search information; wherein the spatial layer includes a plurality of spatial element objects;

[0036] The processing module is further used to determine the first spatial element object set, the first associated layer set and the first associated spatial element object set corresponding to the target spatial data according to the layer information of the spatial layer to which the target spatial data belongs;

[0037] The processing module is further used to determine the second spatial element object set, the second associated layer set and the second associated spatial element object set corresponding to the target spatial data according to the layer information of the spatial layer to which the target spatial data belongs and the preset spatial association rule.

[0038] Furthermore, the processing module is specifically used for:

[0039] Obtain spatial attributes, thematic attributes and data types of spatial data;

[0040] Acquire the spatial attributes, thematic attributes and data types of the spatial data;

[0041] Determining hierarchical information of the spatial data according to the spatial attribute;

[0042] Determine the thematic information of the spatial data according to the thematic attributes;

[0043] Determine data type information of the spatial data according to the data type;

[0044] The layer information of the spatial data is determined according to the level information, the topic information and the data type information.

[0045] Furthermore, the processing module is also used for:

[0046] Before determining the first spatial element object set, the first associated layer set and the first associated spatial element object set corresponding to the target spatial data according to the layer information of the spatial layer to which the target spatial data belongs, for the same spatial element object, the spatial element ID of the spatial element object on the spatial layer is determined according to the spatial layer to which the spatial element object belongs.

[0047] Furthermore, the search information includes search conditions, and the processing module is specifically used to:

[0048] Determine the target layer corresponding to the target spatial data according to the layer information of the spatial layer to which the target spatial data belongs;

[0049] Determine a first set of spatial element objects that meet the search condition from the target layer according to the search information;

[0050] Determine the first associated layer set according to the target layer;

[0051] Obtaining a first spatial element ID set corresponding to the first spatial element object set;

[0052] A first associated spatial element object set is determined according to the first spatial element ID set.

[0053] Furthermore, the preset spatial association rule is determined by a spatial relationship operator and a constraint condition, and the processing module is specifically used for:

[0054] The spatial relationship between the spatial element objects on different spatial layers is calculated by the spatial relationship operator; wherein the spatial relationship operator includes a geometric relationship operator and a semantic relationship operator;

[0055] Determining a calculation result of the spatial relationship operator according to the constraint condition;

[0056] The second spatial element object set, the second associated layer set and the second associated spatial element object set corresponding to the target spatial data are determined according to the calculation result of the spatial relationship operator and the layer information of the spatial layer to which the target spatial data belongs.

[0057] In a third aspect, an embodiment of the present invention further provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the method for organizing and retrieving multi-level and multi-topic spatial data as described in the first aspect is implemented.

[0058] In a fourth aspect, an embodiment of the present invention further provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method for organizing and retrieving multi-level and multi-topic spatial data as described in the first aspect.

[0059] It can be seen from the above technical scheme that the method and device for organizing and retrieving multi-level and multi-topic spatial data provided by the embodiment of the present invention realize the organic association of cross-level and cross-topic spatial data, solve the problems of organizing, retrieving and acquiring cross-level and cross-topic spatial data through the methods of spatial data coding organization, spatial association rule constraints and spatial relationship reasoning, and realize the integrated collaborative management of multi-level and multi-topic spatial data. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0061] Figure 1 A system framework for a method of organizing and retrieving multi-level and multi-topic spatial data provided by an embodiment of the present invention;

[0062] Figure 2 A schematic flow chart of a method for organizing and retrieving multi-level and multi-topic spatial data provided by an embodiment of the present invention;

[0063] Figure 3 A schematic flow chart of a method for organizing and retrieving multi-level and multi-topic spatial data provided by an embodiment of the present invention;

[0064] Figure 4 A schematic diagram of a method for organizing and retrieving multi-level and multi-topic spatial data provided by an embodiment of the present invention;

[0065] Figure 5 A schematic diagram of a method for organizing and retrieving multi-level and multi-topic spatial data provided by an embodiment of the present invention;

[0066] Figure 6 A schematic flow chart of a method for organizing and retrieving multi-level and multi-topic spatial data provided by an embodiment of the present invention;

[0067] Figure 7 A schematic diagram of a method for organizing and retrieving multi-level and multi-topic spatial data provided by an embodiment of the present invention;

[0068] Figure 8 A schematic diagram of a method for organizing and retrieving multi-level and multi-topic spatial data provided by an embodiment of the present invention;

[0069] Fig. 9 A schematic diagram of a method for organizing and retrieving multi-level and multi-topic spatial data provided by an embodiment of the present invention;

[0070] Fig.10 A schematic diagram of a method for organizing and retrieving multi-level and multi-topic spatial data provided by an embodiment of the present invention;

[0071] Fig.11 A schematic diagram of a method for organizing and retrieving multi-level and multi-topic spatial data provided by an embodiment of the present invention;

[0072] Fig.12A schematic diagram of the structure of a device for organizing and retrieving multi-level and multi-topic spatial data provided by an embodiment of the present invention;

[0073] Fig.13 A schematic diagram of the structure of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0074] The specific implementation of the present invention is further described below in conjunction with the accompanying drawings. The following embodiments are only used to more clearly illustrate the technical solution of the present invention, and cannot be used to limit the protection scope of the present invention.

[0075] In order to better explain the present invention, it is necessary to first distinguish two concepts: space objects and space element objects.

[0076] Specifically, spatial objects refer to spatial objects in the real geographical world, and spatial element objects refer to conceptualized objects mapped in computers from spatial objects in the real geographical world.

[0077] The multi-level and multi-topic spatial data organization and retrieval method provided by the embodiment of the present invention can be applied to Figure 1 In the system architecture shown, the system architecture includes a client 100 , a spatial data organization and retrieval server 200 , and an index library 300 .

[0078] Specifically, the client 100 is used to obtain the layer information of the spatial data and the search information of the user.

[0079] Specifically, the spatial data organization and retrieval server 200 is used to determine the layer information of the spatial layer to which the target spatial data belongs from the index library 300 according to the retrieval information from the client 100 .

[0080] Specifically, the index library 300 is used to store layer information.

[0081] It should be noted that Figure 1 This is only an example of the system architecture of the embodiment of the present invention, and the present invention does not make any specific limitation to this.

[0082] Based on the system architecture shown above, Figure 2 A flowchart corresponding to a method for organizing and retrieving multi-level and multi-topic spatial data provided by an embodiment of the present invention is shown in FIG. Figure 2 As shown, the method includes:

[0083] Step 201, obtaining layer information of spatial data.

[0084] Step 202: Generate an index library based on the layer information.

[0085] Step 203: Obtain the user's search information.

[0086] Step 204: determine the layer information of the spatial layer to which the target spatial data belongs from the index library according to the search information.

[0087] It should be noted that the spatial layer contains multiple spatial feature objects.

[0088] Step 205 : determining a first spatial element object set, a first associated layer set, and a first associated spatial element object set corresponding to the target spatial data according to the layer information of the spatial layer to which the target spatial data belongs.

[0089] Step 206: Determine a second spatial element object set, a second associated layer set, and a second associated spatial element object set corresponding to the target spatial data according to the layer information of the spatial layer to which the target spatial data belongs and a preset spatial association rule.

[0090] In step 202 of the embodiment of the present invention, the spatial layer is used as the basic unit to integrate the multi-level spatial data of cities, counties (districts), towns, and multi-thematic spatial data such as land, planning, and forests into a unified spatial data framework for integrated organization and management. The specific steps are as follows: Figure 3 As shown below:

[0091] Step 301, obtaining spatial attributes, thematic attributes and data types of spatial data.

[0092] It should be noted that, in the embodiment of the present invention, for a spatial layer, its basic attributes include spatial attributes, thematic attributes and data types.

[0093] Step 302: determine the level information of the spatial data according to the spatial attributes.

[0094] Step 303: determine the thematic information of the spatial data according to the thematic attributes.

[0095] Step 304: determine data type information of the spatial data according to the data type.

[0096] Step 305: determine the layer information of the spatial data according to the level information, thematic information and data type information.

[0097] In step 301 of the embodiment of the present invention, the data type describes the type of the spatial layer, such as vector data, remote sensing image data, laser point cloud data, etc.

[0098] Specifically, the thematic attribute describes the thematic type to which the spatial layer belongs, for example, a spatial layer is forest land, grassland, cultivated land, etc.

[0099] Furthermore, the spatial attributes include spatial projection, for example, the spatial layer adopts the National 2000 projection coordinate system, and the spatial scale is the scale or resolution of the spatial layer.

[0100] It should be noted that all spatial layers in the embodiment of the present invention have been converted to the same spatial projection reference after data preprocessing. Therefore, in the embodiment of the present invention, a spatial layer can be fully described by data type, administrative level and thematic attributes.

[0101] Based on this, the layer information in the embodiment of the present invention is composed of four parts, namely: layer description code, layer code, theme code and data type code.

[0102] Specifically, the vertical level description code is used to describe the administrative level to which the current level code belongs.

[0103] In a possible implementation, according to the national administrative divisions, the levels are divided into 6 levels: country, province, city, county, town, and village, which are described by 0 to 6 in the embodiment of the present invention. Therefore, the level code only needs 1 byte, as shown in Table 1.

[0104] Table 1

[0105]

[0106] It should be noted that spatial data has multiple scales or resolutions. In urban management, departments at different administrative levels have different business issues. The scale and level of detail of spatial data are usually closely related to the administrative level at which they are located. Urban spatial data usually corresponds to a certain administrative level. For example, city-level business departments pay more attention to macro statistics, while town-level departments pay more attention to micro management.

[0107] Furthermore, in step 302, the embodiment of the present invention uses administrative levels to vertically encode spatial data, rather than the scale or resolution of the spatial data itself. The vertical administrative level coding constructs the vertical association relationship between different spatial layers. The vertical administrative level coding is encoded according to the administrative division level.

[0108] In a possible implementation, a 6-level coding format from country to village is adopted, such as Figure 4 A complete vertical hierarchical information code can be fully represented by a 6-level code. For applications limited to a certain area, fewer levels of code can be used. Taking Chongqing as an example, only "province-county-town-village" is needed.

[0109] Table 2

[0110]

[0111] For example, as shown in Table 2 above, the administrative division of Chongqing is taken as an example. According to the city, county (district), and town administrative levels, a hierarchical code is constructed. Each administrative level such as city, county (district), and town is encoded with 1 byte, and its value range is [0,255]. Each level can describe 256 administrative units.

[0112] In a possible implementation, in order to simplify the coding, the 0 value of each level is set to a null value, that is, an invalid value, which does not represent any administrative unit. Therefore, in the embodiment of the present invention, the coding of each level of administrative unit starts from 1, and 255 administrative units can be described.

[0113] Furthermore, taking "Ganshui Town, Qijiang District, Chongqing City" as an example, as shown in Table 3, its hexadecimal code is 0x050302.

[0114] Table 3

[0115]

[0116] Furthermore, the encoding of “Chongqing City - Qijiang District” in the embodiment of the present invention is shown in Table 4.

[0117] Table 4

[0118]

[0119] It should be noted that since it does not reach the town level, the town level code value is 0x00. Therefore, the hexadecimal code of "Qijiang District, Chongqing City" is 0x000300.

[0120] Furthermore, the vertical multi-level coding in the embodiment of the present invention itself has multiple levels of information of an administrative unit. By masking the corresponding administrative level coding, the vertical level coding of the city, county (district), and town to which the administrative unit belongs and the affiliation between the levels can be extracted, thereby realizing the organic association of multi-level spatial data.

[0121] For example, the code of "Chongqing City-Qijiang District-Ganshui Town" is 0x050302. By performing an "AND" operation with the mask 0xFF0000, the code of the province (city, district) to which Guanshui Town belongs, that is, 0x050000, can be extracted.

[0122] In step 303 of the embodiment of the present invention, the thematic information of the spatial data is determined according to the thematic attributes.

[0123] It should be noted that urban management involves various thematic spatial data. Spatial data usually adopts a tree classification system to achieve thematic classification management of spatial data.

[0124] Furthermore, as shown in Table 5 , an example of a three-level thematic classification system for urban spatial data is presented.

[0125] Table 5

[0126]

[0127] In a possible implementation, according to the horizontal thematic classification of spatial data established by thematic business applications, the embodiment of the present invention constructs the thematic data classification specification that is commonly followed by the city, county (district), and town levels. As shown in Table 5, the themes are divided into three levels: level one, level two, and level three.

[0128] Specifically, using 1 byte, 255 first-level categories can be managed. The value range is [0,255]. Similarly, using 1 byte, 255 second-level categories can be managed. The value range is [0,255]. Using 1 byte, 255 third-level categories can be managed. The value range is [0,255].

[0129] In a possible implementation, the complete spatial data thematic coding consists of primary classification, secondary classification, and tertiary classification.

[0130] For example, as shown in Table 6, the complete hexadecimal thematic classification code for "Surface Data - Land Use - Unused Land" is: 0x000103.

[0131] Table 6

[0132]

[0133] It should be noted that, in the embodiment of the present invention, similar to the vertical administrative level code, the horizontal level code itself has a classification level code, and through mask operation, the first and second category classification codes to which the layer belongs can be extracted.

[0134] In the embodiment of the present invention, in step 304, the spatial data type encoding describes the data type information of the spatial data. The data type information of the spatial data includes: vector, remote sensing image, three-dimensional model, real-time sensing, etc.

[0135] In a possible implementation, 1 byte is used to describe the data type information, as shown in Table 7.

[0136] Table 7

[0137] Data Types coding 1 Vector Data 0x01 2 Remote sensing images 0x02 3 Elevation data 0x03 4 Geographic entity data 0x04 5 3D model data 0x05 6 Laser point cloud 0x06 7 BIM Data 0x07 8 Intelligent perception data 0x08 9 Place name address data 0x09

[0138] In step 305, the embodiment of the present invention determines the layer information of the spatial data according to the level information, thematic information and data type information.

[0139] For example, taking "Ganshui Town, Qijiang District, Chongqing City" and "Surface Data Land Use Unused Land" as examples, the complete encoding of the layer information is: 0x0500030200010301, as shown in Table 8.

[0140] Table 8

[0141] Hierarchical Description Code Hierarchical coding Thematic Code Data Types Hexadecimal encoding 0x05 0x000302 0x000103 0x01

[0142] The above scheme incorporates the spatial layers corresponding to spatial data of different levels and topics into a unified system for integrated management. The spatial layers corresponding to the target spatial data can be quickly and accurately retrieved and located through the coding system.

[0143] The above-mentioned spatial data encoding at the layer level establishes the association relationship between layers, but does not establish the association between spatial feature objects within different spatial layers.

[0144] Furthermore, before step 205, the present invention determines, for the same spatial element object, the spatial element ID of the spatial element object on the spatial layer according to the spatial layer to which the spatial element object belongs.

[0145] It should be noted that spatial objects in a real geographic environment have different levels of abstraction at different levels, which is manifested in that spatial feature objects have different levels of detail and forms on maps of different scales or resolutions.

[0146] Specifically, Figure 5 The spatial feature objects shown in the figure are simple rectangles at the city level, polygons with richer details at the county (district) level, and multiple separated polygons with richer details at the town level. However, the three are semantically the same spatial objects. From the city level to the county level, the spatial objects of the building are no longer one-to-one corresponding, but one-to-many. Therefore, the feature-level spatial object coding should establish the organic association of the same spatial feature object at different scales or levels, and form a cross-level context feature-level multi-level spatial object coding to ensure semantic consistency, so as to meet the needs of multi-level spatial information application from macro-control at the city level to fine management at the town level.

[0147] In the embodiment of the present invention, the feature-level multi-level spatial object encoding assigns a unique spatial element ID to the spatial element object. Therefore, the same geographic spatial object on different scale layers can be judged as the same geographic spatial object through the same spatial element ID, thereby establishing a cross-level association relationship between spatial element objects.

[0148] Furthermore, as the morphology of spatial objects changes as the scale decreases, they may be decomposed into multiple sub-parts, each of which is an independent spatial object on the small-scale layer. Therefore, it is not appropriate to assign the same spatial element ID to each spatial element object of the same geographic spatial object. Therefore, it is necessary to establish a new spatial element ID coding system that can describe the whole and the sub-parts.

[0149] In the embodiment of the present invention, a multi-level spatial element coding method is used to construct a code for each spatial element object, and the association between spatial element objects at different scales is realized through the reasoning of the code.

[0150] For example, the spatial feature ID of a spatial feature object F consists of the following three parts:

[0151] 1. City-level code: The city-level code is the spatial element ID of the spatial element object corresponding to F on the city-level layer.

[0152] 2. County (district) level code: The county (district) level code is F, which is the spatial element ID of the spatial element object corresponding to it on the county (district) level layer.

[0153] 3. Town-level code: The town-level code is the spatial element ID of the spatial element object corresponding to F on the town-level layer.

[0154] In a possible implementation, the spatial element ID format of a complete spatial element object is: city code-county code-town code. Figure 5 As shown, the spatial element ID of the spatial object in the circle is composed of city-level and county-level codes, and its complete code is: 001-031-002.

[0155] Specifically, 001 is the spatial element ID corresponding to the spatial element object on the city-level layer; 001-031 is the spatial element ID corresponding to the spatial element object on the county (district) level layer; 001-031-002 is the complete spatial element ID of the spatial element object on the town-level layer.

[0156] In the above scheme, multi-level spatial element coding constructs the association relationship between geographic spatial objects at multiple levels. By tracing back the element coding, the spatial element objects corresponding to the same geographic spatial object on different levels of spatial layers can be found, solving the problem of integrated association and organizational management of spatial objects across levels at the element level.

[0157] Based on the relatively stable deterministic relationship between spatial data, the spatial organization system that can integrate various types of spatial data into a unified management framework is constructed through layer information and spatial element ID. In addition, there are a large number of implicit spatial relationships between spatial objects that cannot be described by coding.

[0158] For example, a bridge is usually located above a river, and the relationship between the two is a crossing relationship. The relationship between such spatial objects cannot be accurately described by coding, and needs to be dynamically obtained through spatial relationship calculation.

[0159] In the embodiment of the present invention, the preset spatial association rule is determined by the spatial relationship operator and the constraint condition. In step 206, the specific steps are as follows: Figure 6 As shown below:

[0160] Step 601, calculating the spatial relationship between spatial feature objects on different spatial layers by using a spatial relationship operator.

[0161] It should be noted that the spatial relationship operators include geometric relationship operators and semantic relationship operators.

[0162] Step 602: Determine the calculation result of the spatial relationship operator according to the constraint conditions.

[0163] Step 603: determine a second spatial element object set, a second associated layer set, and a second associated spatial element object set corresponding to the target spatial data according to the calculation result of the spatial relationship operator and the layer information of the spatial layer to which the target spatial data belongs.

[0164] In step 601 of the embodiment of the present invention, in a possible implementation manner, the spatial relationship between spatial objects can be divided into two categories: geometric relationship and semantic relationship.

[0165] Specifically, geometric relationships refer to the relationships between spatial objects determined by geometric methods, including topological relationships, orientation relationships, etc.

[0166] Furthermore, topological relationships refer to the relationships between spatial objects that remain unchanged under topological transformations such as stretching, compression, and rotation. Therefore, topological relationships are the inherent relationships between spatial objects. In geographic information systems, the main topological relationships are shown in Table 9.

[0167] Table 9

[0168] Operator illustrate 1 Intersects intersect 2 Disjoint Separation 3 Contain Include 4 Within Included 5 Covers cover 6 Crosses Crossing 7 Equals equal 8 Touches touch

[0169] In the embodiment of the present invention, the semantic relationship refers to a relationship other than the geometric relationship of spatial objects, including an attribute relationship and a thematic business relationship.

[0170] Specifically, the attribute relationship is based on associating certain attributes with the spatial object itself.

[0171] For example, the name, address and other attributes of a spatial object. The attributes of a spatial object themselves imply certain spatial relationships, especially the address attribute.

[0172] For example, the address of XXX Research Institute is: No. YY, Datun Road, Chaoyang District, Beijing. The address attribute describes:

[0173] 1. Location information: No. YY, Datun Road, Chaoyang District, Beijing.

[0174] 2. Affiliation information: No. YY, Datun Road belongs to Chaoyang District, and Chaoyang District belongs to Beijing.

[0175] Furthermore, through the hierarchical relationship of the address attributes between the spatial objects themselves, a vertical hierarchical relationship between different spatial objects is established.

[0176] Specifically, associations and affiliations between different spatial objects can be established based on address attributes.

[0177] For example, based on the two addresses of "Building 1 in the Park" and "Building 2 in the Park", the following Figure 7 That is, there is a "park", and both Building 1 and Building 2 belong to the "park".

[0178] Furthermore, the subject business relationship is a special attribute relationship that is closely related to the specific business field requirements.

[0179] For example, some thematic layer data in the planning field are closely related, but in the monitoring field these thematic layers are no longer related. It is necessary to define specific thematic business relationships according to the needs of the thematic business field.

[0180] Based on the above description of spatial relationships, the following specifically describes how to calculate the spatial relationships between spatial feature objects on different spatial layers by using a spatial relationship operator in step 601 of the embodiment of the present invention.

[0181] First, the concept of spatial relationship reasoning is introduced. Spatial relationship reasoning is to use spatial relationship operators to calculate the relationship between spatial objects to achieve spatial relationship reasoning. In the present invention, the schematic diagram of spatial relationship reasoning is as follows Figure 8 As shown, it mainly includes:

[0182] 1. Source layer Source refers to the main layer in spatial relationship reasoning.

[0183] 2. Target layer Target.

[0184] It should be noted that the spatial relationship between the spatial feature objects on the Target layer and the spatial feature objects on the Source map is calculated in spatial relationship reasoning.

[0185] 3. Spatial relationship operator Operator is used to calculate the spatial relationship between spatial feature objects on the Source and Target layers. The calculation result of the spatial relationship operator generates a Result object.

[0186] In a possible implementation, in the Result object, the result status is recorded as a Boolean variable True / False to indicate whether two spatial feature objects meet the conditions defined by the spatial relationship operator.

[0187] It should be noted that, in the embodiment of the present invention, spatial relationship reasoning requires the support of a spatial relationship operator library. The definition of the spatial relationship operator library is as follows: Fig. 9 shown.

[0188] Specifically, the base class is Operator, from which the geometry operator (GeometryOperator) and the semantic operator (SemanticOperator) are derived. The semantic operator further derives the attribute operator (AttributeOperator) and the theme operator (ThemeOperator).

[0189] Furthermore, the geometric relationship operators mainly include topological relationship operators as shown in Table 9.

[0190] Specifically, in the embodiment of the present invention, address is a relatively common type of attribute data, and many spatial element objects are associated with a certain address. Address data is also a relatively independent type of attribute data and can be used as an independent spatial relationship operator. The relationship between other attribute data is usually related to spatial data, and the user needs to customize the attribute relationship operator according to the specific situation of the spatial data.

[0191] Furthermore, the address relationship operator includes functions such as address resolution and address matching.

[0192] In the embodiment of the present invention, the topic relationship operator is customized by the user according to the topic business needs.

[0193] Specifically, spatial relationship operators are defined using object-oriented technology. The base class Operator defines the operator framework, and the derived classes implement specific spatial relationship operators. A spatial relationship operator library is built through interfaces to solve spatial relationship reasoning problems.

[0194] Specifically, the definition of the Operator class is as follows.

[0195] Class Operator

[0196] {

[0197] private:

[0198] Layer source;

[0199] Layer target;

[0200] public:

[0201] Result Execute();

[0202] };

[0203] In the above scheme, the Operator class defines the input source and target, and defines the relationship calculation function Execute. Users can derive custom spatial relationship subclasses from the Operator class and register them in the spatial relationship operator library so that users can define spatial relationships for spatial relationship reasoning.

[0204] In the embodiment of the present invention, based on spatial relationship reasoning, spatial association rules are constructed to achieve association between spatial objects.

[0205] Specifically, the spatial association rules are as follows: Fig.10 shown.

[0206] In the embodiment of the present invention, the spatial association rules include:

[0207] 1. Spatial relationship operator: The spatial relationship operator defines the spatial reasoning method used by the association rule, as well as the input source layer Source and target layer Target. The spatial relationship operator is used to establish the association relationship between the spatial feature objects of the source layer and the target layer.

[0208] 2. Constraint: Constraints define the conditions for valid relationships.

[0209] Specifically, taking the spatial relationship between rivers and bridges as an example, by performing the Crosses spatial relationship operation on the river layer and the bridge layer, a Crossing relationship can be established between each river and each bridge. Only pairs of rivers and bridges that satisfy the True result of the Crossing relationship calculation are valid.

[0210] The above scheme, when performing spatial data retrieval, realizes the retrieval of spatial feature objects across source layers and target layers through spatial association rules.

[0211] For example, through the above spatial association rules between rivers and bridges, cross-layer retrieval from the river layer to the bridge layer is performed.

[0212] In the embodiment of the present invention, the calculation result of the spatial relationship operator is determined according to the constraint conditions.

[0213] For example, taking the spatial relationship between buildings and farmland as an example, by performing an intersection spatial relationship operation on the building layer and the farmland layer, the intersection relationship between each building and each piece of farmland can be established. Only the pairs of buildings and farmland for which the intersection relationship calculation result is False are valid.

[0214] The above scheme realizes the association of spatial feature objects of multiple spatial layers through spatial association rule chains.

[0215] In addition, in a possible implementation of the embodiment of the present invention, the user can customize the spatial association rule library that meets specific needs based on the spatial association rule framework defined in the embodiment of the present invention to achieve integrated collaborative management of spatial data for thematic business applications.

[0216] The index library in the embodiment of the present invention is composed of a spatial data resource directory, which can be divided into a vertical multi-level view and a horizontal multi-topic view, with vertical multi-level coding and horizontal multi-topic coding as the main coding, respectively, so that users can browse spatial data from multiple angles.

[0217] In a possible implementation, Fig.11 As shown in the figure, it is the directory organization form of the spatial data resource directory with horizontal thematic classification code as the main code. The spatial data resource directory first organizes the tree structure of spatial data with three-level multi-thematic classification code. The third-level classification node in the tree is associated with the actual spatial layer, and the multi-level structure of the thematic classification layer is organized according to the three administrative levels of city, district (county), and town where the spatial layer is located.

[0218] Furthermore, the metadata of the spatial data layers corresponding to the city, district (county), and town are recorded in the metadata table corresponding to Table 10. At the same time, the metadata of the layer and its layer path are registered in the directory tree to realize the association between the layer data and the multi-level and multi-thematic directory structure, thereby realizing the aggregation and integrated management of loosely coupled multi-level and multi-thematic spatial data.

[0219] It should be noted that metadata is data about data, which is used to describe the attributes of data, such as the accuracy of data, creation time, etc. The embodiment of the present invention extracts metadata of spatial data to further describe the multi-level and multi-topic information of spatial data, and combines spatial data encoding, spatial operator library, spatial relationship reasoning and association rules to realize multi-level and multi-topic spatial data association, management and retrieval based on spatial reasoning.

[0220] In a possible implementation, the core structure of spatial data metadata is defined as shown in Table 10. The core metadata includes name, alias, data type, data format, spatial range, data time, spatial reference, and level and theme. The core metadata meets the spatial data discovery in the multi-level and multi-theme spatial data collaborative management model.

[0221] It should be noted that different types of spatial data have their own characteristics. Based on the metadata listed in Table 10, a metadata structure matching the characteristics of a specific spatial data type can be derived, and the embodiment of the present invention does not specifically limit this.

[0222] Table 10

[0223] Metadata illustrate 1 r_uuid Globally unique identifier 2 r_version Version 3 r_name name 4 r_alias Aliases 5 r_tyope Data Types 6 r_format Data Format 7 r_extent Spatial range 8 r_time Data time 9 r_srid Spatial reference SRID 10 r_level Level 11 r_theme Related topics

[0224] Furthermore, in step 205, the embodiment of the present invention determines the target layer corresponding to the target spatial data according to the layer information of the spatial layer to which the target spatial data belongs;

[0225] Determine a first set of spatial element objects that meet the retrieval condition from the target layer according to the retrieval information;

[0226] Determine a first associated layer set according to the target layer;

[0227] Obtain a first spatial element ID set corresponding to the first spatial element object set;

[0228] A first associated spatial element object set is determined according to the first spatial element ID set.

[0229] Specifically, the target layer is located based on the user's search information and search conditions, and the target layer that meets the user's search conditions is retrieved in the index library built according to the metadata table, the level and subject of the target layer are located in the spatial data resource directory, and the spatial feature objects that meet the conditions are queried.

[0230] Furthermore, in the embodiment of the present invention, the retrieval of the associated layers utilizes the hierarchical information coding to retrieve the spatial layers and spatial feature objects of the hierarchical and thematic levels related to the above retrieval results, to form a first associated layer set and a first spatial feature object set.

[0231] Based on the above retrieval, further related data retrieval is performed through spatial relationship reasoning.

[0232] Specifically, the search results are further extended using spatial association rules to form a second association layer set and a second spatial element object set that meet the search conditions, and then further analyzed and processed.

[0233] The above scheme realizes the organic association of cross-level and cross-topic spatial data. It solves the problem of retrieval and acquisition of cross-level and cross-topic spatial data through the methods of spatial data coding backtracking, spatial association rule constraints and spatial relationship reasoning, and realizes the integrated collaborative management of multi-level and multi-topic spatial data.

[0234] Based on the same inventive concept, Fig.12 An apparatus for organizing and retrieving multi-level and multi-topic spatial data provided by an embodiment of the present invention is exemplarily shown. The apparatus may be a process of a method for organizing and retrieving multi-level and multi-topic spatial data.

[0235] The device comprises:

[0236] An acquisition module 1201 is used to acquire layer information of spatial data;

[0237] Processing module 1202 is used to generate an index library according to the layer information; obtain the user's search information; determine the layer information of the spatial layer to which the target spatial data belongs from the index library according to the search information; wherein the spatial layer includes multiple spatial element objects;

[0238] The processing module 1202 is further configured to determine a first spatial element object set, a first associated layer set, and a first associated spatial element object set corresponding to the target spatial data according to layer information of the spatial layer to which the target spatial data belongs;

[0239] The processing module 1202 is further used to determine a second spatial element object set, a second associated layer set and a second associated spatial element object set corresponding to the target spatial data according to layer information of the spatial layer to which the target spatial data belongs and a preset spatial association rule.

[0240] Furthermore, the processing module 1202 is specifically used for:

[0241] Obtain spatial attributes, thematic attributes and data types of spatial data;

[0242] Acquire the spatial attributes, thematic attributes and data types of the spatial data;

[0243] Determining hierarchical information of the spatial data according to the spatial attribute;

[0244] Determine the thematic information of the spatial data according to the thematic attributes;

[0245] Determine data type information of the spatial data according to the data type;

[0246] The layer information of the spatial data is determined according to the level information, the topic information and the data type information.

[0247] Furthermore, the processing module 1202 is also used for:

[0248] Before determining the first spatial element object set, the first associated layer set and the first associated spatial element object set corresponding to the target spatial data according to the layer information of the spatial layer to which the target spatial data belongs, for the same spatial element object, the spatial element ID of the spatial element object on the spatial layer is determined according to the spatial layer to which the spatial element object belongs.

[0249] Furthermore, the search information includes search conditions, and the processing module 1202 is specifically used for:

[0250] Determine the target layer corresponding to the target spatial data according to the layer information of the spatial layer to which the target spatial data belongs;

[0251] Determine a first set of spatial element objects that meet the search condition from the target layer according to the search information;

[0252] Determine the first associated layer set according to the target layer;

[0253] Obtaining a first spatial element ID set corresponding to the first spatial element object set;

[0254] A first associated spatial element object set is determined according to the first spatial element ID set.

[0255] Furthermore, the preset spatial association rule is determined by a spatial relationship operator and a constraint condition, and the processing module 1202 is specifically used for:

[0256] The spatial relationship between the spatial element objects on different spatial layers is calculated by the spatial relationship operator; wherein the spatial relationship operator includes a geometric relationship operator and a semantic relationship operator;

[0257] Determining a calculation result of the spatial relationship operator according to the constraint condition;

[0258] The second spatial element object set, the second associated layer set and the second associated spatial element object set corresponding to the target spatial data are determined according to the calculation result of the spatial relationship operator and the layer information of the spatial layer to which the target spatial data belongs.

[0259] Based on the same inventive concept, another embodiment of the present invention provides an electronic device, see Fig.13 , the electronic device specifically includes the following contents: a processor 1301, a memory 1302, a communication interface 1303 and a communication bus 1304;

[0260] The processor 1301, the memory 1302, and the communication interface 1303 communicate with each other through the communication bus 1304; the communication interface 1303 is used to realize information transmission between various devices; the processor 1301 is used to call the computer program in the memory 1302, and the processor implements all the steps of the above-mentioned site selection method when executing the computer program. For example, the processor implements the following steps when executing the computer program: obtaining layer information of spatial data; generating an index library according to the layer information; obtaining user's search information; determining the layer information of the spatial layer to which the target spatial data belongs from the index library according to the search information; wherein the spatial layer includes multiple spatial element objects; determining the first spatial element object set, the first associated layer set, and the first associated spatial element object set corresponding to the target spatial data according to the layer information of the spatial layer to which the target spatial data belongs; determining the second spatial element object set, the second associated layer set, and the second associated spatial element object set corresponding to the target spatial data according to the layer information of the spatial layer to which the target spatial data belongs and a preset spatial association rule.

[0261] Based on the same inventive concept, another embodiment of the present invention provides a non-transitory computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, all the steps of the above-mentioned site selection method are implemented. For example, when the processor executes the computer program, the following steps are implemented: obtaining layer information of spatial data; generating an index library based on the layer information; obtaining user's search information; determining layer information of the spatial layer to which the target spatial data belongs from the index library based on the search information; wherein the spatial layer includes multiple spatial element objects; determining a first spatial element object set, a first associated layer set, and a first associated spatial element object set corresponding to the target spatial data based on the layer information of the spatial layer to which the target spatial data belongs; determining a second spatial element object set, a second associated layer set, and a second associated spatial element object set corresponding to the target spatial data based on the layer information of the spatial layer to which the target spatial data belongs and a preset spatial association rule.

[0262] In addition, the logic instructions in the above-mentioned memory can be implemented in the form of software functional units and can be stored in a computer-readable storage medium when sold or used as an independent product. Based on this understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art or the part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including several instructions to enable a computer device (which can be a personal computer, a user life pattern prediction device, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk and other media that can store program codes.

[0263] The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the embodiments of the present invention. Those of ordinary skill in the art may understand and implement them without creative effort.

[0264] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a user life pattern prediction device, or a network device, etc.) to execute the user life pattern prediction method described in each embodiment or some parts of the embodiment.

[0265] In addition, in the present invention, terms such as "first" and "second" are only used for descriptive purposes and cannot be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of the features. In the description of the present invention, the meaning of "plurality" is at least two, such as two, three, etc., unless otherwise clearly and specifically defined.

[0266] In addition, in the present invention, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the statement "comprise a ..." do not exclude the presence of other identical elements in the process, method, article or device including the elements.

[0267] In addition, in the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, without contradiction.

[0268] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some of the technical features therein by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for organizing and retrieving multi-level and multi-topic spatial data, characterized in that: include: Get the layer information of spatial data; Generate an index library according to the layer information; Get the user's search information; Determining layer information of the spatial layer to which the target spatial data belongs from the index library according to the search information; wherein the spatial layer includes a plurality of spatial element objects; Determine, according to the layer information of the spatial layer to which the target spatial data belongs, a first spatial element object set, a first associated layer set, and a first associated spatial element object set corresponding to the target spatial data; Determine a second spatial element object set, a second associated layer set, and a second associated spatial element object set corresponding to the target spatial data according to the layer information of the spatial layer to which the target spatial data belongs and a preset spatial association rule; The step of obtaining the layer information of the spatial data includes: Acquire the spatial attributes, thematic attributes and data types of the spatial data; Determining hierarchical information of the spatial data according to the spatial attribute; Determine the thematic information of the spatial data according to the thematic attributes; Determine data type information of the spatial data according to the data type; Determine the layer information of the spatial data according to the level information, the topic information and the data type information; Before determining the first spatial element object set, the first associated layer set and the first associated spatial element object set corresponding to the target spatial data according to the layer information of the spatial layer to which the target spatial data belongs, the method further includes: For the same spatial element object, determining the spatial element ID of the spatial element object on the spatial layer according to the spatial layer to which the spatial element object belongs; The search information includes a search condition, and the determining, according to the layer information of the spatial layer to which the target spatial data belongs, the first spatial element object set, the first associated layer set, and the first associated spatial element object set corresponding to the target spatial data includes: Determine the target layer corresponding to the target spatial data according to the layer information of the spatial layer to which the target spatial data belongs; Determine a first set of spatial element objects that meet the search condition from the target layer according to the search information; Determine the first associated layer set according to the target layer; Obtaining a first spatial element ID set corresponding to the first spatial element object set; Determine a first associated spatial element object set according to the first spatial element ID set; The preset spatial association rule is determined by a spatial relationship operator and a constraint condition, and the second spatial element object set, the second associated layer set, and the second associated spatial element object set corresponding to the target spatial data are determined according to the layer information of the spatial layer to which the target spatial data belongs and the preset spatial association rule, including: The spatial relationship between the spatial element objects on different spatial layers is calculated by the spatial relationship operator; wherein the spatial relationship operator includes a geometric relationship operator and a semantic relationship operator; Determining a calculation result of the spatial relationship operator according to the constraint condition; The second spatial element object set, the second associated layer set and the second associated spatial element object set corresponding to the target spatial data are determined according to the calculation result of the spatial relationship operator and the layer information of the spatial layer to which the target spatial data belongs.

2. A device for organizing and retrieving multi-level and multi-topic spatial data based on the method for organizing and retrieving multi-level and multi-topic spatial data according to claim 1, characterized in that: include: The acquisition module is used to obtain the layer information of spatial data; A processing module, used for generating an index library according to the layer information; Get the user's search information; Determining layer information of the spatial layer to which the target spatial data belongs from the index library according to the search information; wherein the spatial layer includes a plurality of spatial element objects; The processing module is further used to determine the first spatial element object set, the first associated layer set and the first associated spatial element object set corresponding to the target spatial data according to the layer information of the spatial layer to which the target spatial data belongs; The processing module is further used to determine the second spatial element object set, the second associated layer set and the second associated spatial element object set corresponding to the target spatial data according to the layer information of the spatial layer to which the target spatial data belongs and the preset spatial association rule.

3. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the program, the steps of the method according to claim 1 are implemented.

4. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to claim 1 are implemented.

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