Geographic data model construction method, system, device and storage medium

Abstract

The application discloses a kind of geographic data model construction method, system, equipment and storage medium, its technical scheme main point is in, according to data object from multiple hierarchical geographic grid system determines the fitting level of each geographic spatial feature, data object refers to the geographic data of supporting various geographic spatial analysis;According to fitting level, determine the spatial position characteristics corresponding to all target grid units of geographic spatial feature, all target grid units form the grid object of geographic spatial feature;Attribute information is created to grid object and target grid unit;Establish the first data relationship between data object and grid object, establish the second data relationship between grid object and target grid unit, construct geographic data model according to the first data relationship and the second data relationship.The application can use large-scale geographic spatial data to carry out cross-task, cross-scale, efficient dynamic utilization, to realize the remodeling and isomorphism of the overall content of multi-source heterogeneous geographic spatial data.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of image processing, and particularly relates to a geographic data model construction method, system, device and storage medium. BACKGROUND

[0002] Geographic data is an information carrier for describing the characteristics, attributes, relationships and spatio-temporal changes of geographic features. Geographic data usually organizes and describes the spatial location characteristics, attribute characteristics and time characteristics of geographic features in a specific form. Among them, the spatial location characteristics are used to describe the location of the geographic features, such as geographic coordinates, routes, administrative boundaries, etc.; the attribute information is used to describe the qualitative or quantitative indicators of the characteristics of the geographic features, such as the name, type, size, etc. of the geographic features; and the time characteristics refer to the time or period of the collection of geographic data or the occurrence of geographic phenomena, such as the real-time position of a typhoon, the NDVI index of vegetation in different seasons, etc. Among them, the spatial location characteristics are the core of geographic data, and the attribute and time characteristics are closely related to specific geographic features, such as the attributes and time characteristics of geographic features in the fields of ecology, meteorology, transportation, etc. Geographic data is widely sourced and rich in content, and the structure and storage format of the data is also diverse. In order to ensure the integration and utilization capability of the data, existing GIS applications usually use various vector data structures and raster data structures to record spatial data in the form of files, and use the "database + file system" mode to store, organize, manage and apply large-scale geographic data. This way not only ensures the original details of the data to the greatest extent, but also meets the needs of collection, management, organization, sharing and application of various geographic data.

[0003] However, in the processing of geographic data, the traditional GIS application usually loads the data files in full amount in memory, and it is difficult to meet the needs of dynamic interactive analysis of data when processing large-scale data. In the existing technology, the original data files are processed by layering and blocking through raster tiles or vector tiles technology, which can solve the problem of dynamic loading of data, but in essence, the content of the data is not reorganized, so the efficiency of the execution of the calculation and analysis is still subject to the diversity and complexity of the geographic features. For example, to solve the area of an irregular vector polygon, the existing method essentially needs to decompose the polygon into smaller parts, and then obtain the result by summing up the areas of the parts. For a more complex shape, the decomposition and calculation process will have a significant negative impact on the efficiency. In addition, even for different analysis tasks, there are some common needs in the analysis process, and the analysis results also have the value of mutual comparison and further fusion and utilization. However, due to the differences in data precision, task boundary, spatial reference, projection method, etc. of different tasks, it is usually difficult to directly realize the alignment, comparison, fusion and utilization of cross-task data.

[0004] In summary, for the analysis of geospatial data, the existing data content organization form cannot unify the data organization, operation and application mode of different tasks at the analysis application level, so that the computing efficiency and analysis value of each task cannot be maximized, and the algorithm resource cannot be optimally configured as a whole, which greatly limits the dynamic utilization of large-scale geospatial data across tasks, scales and high efficiency. SUMMARY

[0005] The present application aims to provide a geographic data model construction method, system, device and storage medium, which can support the dynamic utilization of large-scale geospatial data across tasks, scales and high efficiency, thereby realizing the remodeling and isomorphism of the overall content of multi-source heterogeneous geospatial data.

[0006] The first aspect of the present application provides a geographic data model construction method, comprising:

[0007] determining the fitting level of each geospatial feature from the multi-level geographic grid system according to the data object, wherein the data object refers to the geographic data supporting various types of geospatial analysis;

[0008] determining all target grid cells corresponding to the spatial location characteristics of the geospatial feature according to the fitting level, and all target grid cells forming a grid object of the geospatial feature;

[0009] creating attribute information for the grid object and the target grid cell;

[0010] establishing a first data relationship between the data object and the grid object, and establishing a second data relationship between the grid object and the target grid cell.

[0011] In some embodiments, the fitting level of each geospatial feature is determined from the multi-level geographic grid system according to the data object, comprising:

[0012] In the case of vector data, the target accuracy is determined according to the application requirements of each geospatial feature;

[0013] selecting the level closest to each target accuracy from the multi-level geographic grid system as the fitting level of each geospatial feature.

[0014] In some embodiments, the fitting level is determined from the multi-level geographic grid system according to the data object, comprising:

[0015] In the case of raster data, the level with a grid aperture not less than the spatial scale of the pixel is selected from the multi-level geographic grid system as the fitting level;

[0016] In the case that the data object is text data, converting the data object into vector data, and determining the target grid cell according to the fitting level of the vector data.

[0017] In some embodiments, the determining all target grid cells corresponding to the spatial position feature of the geospatial element according to the fitting level comprises:

[0018] determining whether the data object is vector data;

[0019] If yes, determining all target grid cells corresponding to the spatial position feature from the multi-level geographic grid system according to the type and fitting level of the geospatial element;

[0020] If no, converting the data object into vector data, and determining the target grid cell according to the vector data.

[0021] In some embodiments, the determining all target grid cells corresponding to the spatial position feature from the multi-level geographic grid system according to the type and fitting level of the geospatial element comprises:

[0022] In the case that the type of the geospatial element is a point element, selecting the grid cell corresponding to the point element from the fitting level as the target grid cell;

[0023] In the case that the type of the geospatial element is a line element, selecting the grid cell corresponding to the line element from the fitting level as a basic grid cell, determining a mapping grid cell from a higher level according to the mapping relationship between the basic grid cell and the grid cells of each level, determining a replacement grid cell from the mapping grid cell according to the basic grid cell, updating the basic grid cell according to the replacement grid cell, until the corresponding at least one lower grid cell in each mapping grid cell is a non-basic grid cell, and taking the basic grid cell at this time as the target grid cell, wherein the higher level is a level above the level corresponding to the basic grid cell.

[0024] In some embodiments, the determining all target grid cells corresponding to the spatial position feature from the multi-level geographic grid system according to the type and fitting level of the geospatial element further comprises:

[0025] In the case that the type of the geospatial element is a surface element, determining whether the spatial scale of the surface element is greater than a preset scale threshold;

[0026] If yes, the minimum grid cell completely covering the geographic spatial element in space is extracted from the multi-level geographic grid system as a basic grid cell, the intersecting grid cell is determined from the lower level according to the mapping relationship between the basic grid cell and each level grid cell, the replacement grid cell is determined from the basic grid cell according to the intersecting grid cell, the intersecting grid cell is updated according to the replacement grid cell, the updated intersecting grid cell is taken as the basic grid cell, and the final basic grid cell is obtained by descending to the target level until the target level, and the final basic grid cell is taken as the target grid cell, wherein the lower level is the next level of the basic grid cell corresponding level, the target level is pre-set, and the target level is not greater than the fitting level.

[0027] If no, the target grid cell is determined by the determination step of the target grid cell of the line element.

[0028] In some embodiments, the first data relationship includes a one-to-one or one-to-many data relationship between the data object and the grid object, and the second data relationship includes a one-to-one, one-to-many or many-to-many data relationship between the grid object and the target grid cell.

[0029] The second aspect of the present application provides a geographic data processing system, comprising:

[0030] The level determination module is configured to determine the fitting level of each geographic spatial element from the multi-level geographic grid system according to the data object, wherein the data object refers to geographic data supporting various geographic spatial analysis;

[0031] The grid determination module is configured to determine all target grid cells corresponding to the spatial position characteristics of the geographic spatial element according to the fitting level, and all target grid cells constitute the grid object of the geographic spatial element.

[0032] The attribute creation module is configured to create attribute information for the grid object and the target grid cell.

[0033] The relationship establishment module is configured to establish a first data relationship between the data object and the grid object, and establish a second data relationship between the grid object and the target grid cell.

[0034] The third aspect of the present application provides a computer device, comprising a memory and a processor, the memory stores a computer program, and the processor implements the steps of the above method when executing the computer program.

[0035] The fourth aspect of the present application provides a computer readable storage medium, which stores a computer program, and the computer program is executed by a processor to implement the steps of the above method.

[0036] The technical scheme provided by the present application has the following advantages and effects: by converting various geographic spatial data into a geographic data model constructed by three interrelated concepts of "data object-grid object-grid unit", support can be provided for the dynamic use of large-scale geographic spatial data across tasks, across scales and with high efficiency, thereby realizing the remodeling and isomorphism of the overall content of multi-source heterogeneous geographic spatial data, and good versatility can be provided, and extensive support can be provided for the integration and use of various geographic spatial data. Meanwhile, the grid isomorphism of data can greatly improve the access and calculation efficiency of large-scale geographic spatial data, and can effectively balance the efficiency, accuracy and versatility requirements of large-scale geographic spatial data calculation. BRIEF DESCRIPTION OF DRAWINGS

[0037] Figure 1 is a flowchart of the geographic data model construction method provided by the present application;

[0038] Figure 2 is a schematic diagram of a multi-level geographic grid system and spatial fitting of the same polygon by using different levels provided by the present application;

[0039] Figure 3 is a schematic diagram of two grid degeneration in the surface element fitting process provided by the present application;

[0040] Figure 4 is a schematic diagram of converting a geographic vector data object into a grid data object provided by the present application;

[0041] Figure 5 is a schematic diagram of the data relationship of "data object-grid object-grid unit" provided by the present application;

[0042] Figure 6 is a structural block diagram of the geographic data model construction system provided by the present application;

[0043] Figure 7 is an internal structure diagram of the computer device provided by the embodiment of the present application. DETAILED DESCRIPTION

[0044] In order to facilitate the understanding of the present application, specific embodiments of the present application will be described in more detail below with reference to the accompanying drawings.

[0045] Unless specifically stated or defined otherwise, "first, second,..." used herein is only used for distinguishing names, and does not represent a specific quantity or order.

[0046] Unless specifically stated or defined otherwise, the term "and / or" used herein includes any and all combinations of one or more related listed items.

[0047] It should be noted that in this article, "fixed to" or "connected to" can mean directly fixed to or connected to a component, or indirectly fixed to or connected to a component.

[0048] like Figure 1 As shown, this embodiment provides a method for constructing a geographic data model, including the following steps S1 to S5:

[0049] Step S1: Determine the fitting level of each geospatial element from the multi-level geographic grid system based on the data object.

[0050] In practical applications, such as Figure 2 As shown, the multi-level geographic grid system refers to a global or regional geographic subdivision grid system with multi-level, structured characteristics. A geographic subdivision grid system divides the Earth's surface into multi-level geographic grids composed of grid cells according to specific rules. The higher the level of the grid, the smaller the spatial scale of the grid cells at that level. There are definite mathematical mapping relationships between grid cells at different levels; for example, grid cells at a higher level will cover (or approximately cover) a certain number of grid cells at a lower level, such as grid cells at the first level covering four specific grid cells at the second level. Multi-level geographic grid systems include, but are not limited to, various geographic grid systems constructed using a pyramid model, such as... Figure 2 As shown in Figure I; GeoSot, a global latitude and longitude subdivision grid based on a quadtree subdivision grid with equal degrees, equal divisions, and equal seconds; and the H3 geographic grid system with hexagonal grids, etc. Multi-level geographic grid systems can provide grid cells ranging from global to meter or centimeter scale, thus meeting the fitting accuracy requirements of various spatial location features.

[0051] Specifically, data objects refer to geographic data that supports various geospatial analyses. These can originate from specially collected data, such as plant distribution records from a botanical garden, or from existing data, such as publicly available remote sensing imagery. Data objects are typically driven by specific tasks or objectives, such as the regularly updated global bioclimatic variable data WorldClim or the Landsat series of data covering the entire land surface. Data objects often possess clear task attributes and application characteristics, thus serving as fundamental data collection and updating objects.

[0052] Geospatial elements refer to things or objects on the earth's surface with specific location, shape, size and spatial distribution characteristics. Specifically, the data types of data objects include: vector data, raster data and text data. For vector data, geospatial elements refer to any geospatial object composed of one or more single vector elements (points, lines, surfaces), such as the tree distribution data of a botanical garden composed of multiple point elements, a national highway composed of a line element, etc. For raster data, geospatial elements refer to any raster object composed of one or more pixels, which can be the entire raster data or a part of the raster data. In actual applications, raster data is often cut into multiple non-overlapping slices for storage, and a geospatial element can be composed of one or more raster slices, which can be continuous or discontinuous in space. In addition, a data object can usually be composed of one or more geospatial elements, such as a map of a park, which can be composed of multiple geospatial elements of multiple categories such as roads, buildings and green spaces. A large remote sensing raster image can also be abstracted into different geospatial elements according to zoning or task requirements. Geospatial elements belonging to the same data object can be non-overlapping or overlapping in space.

[0053] The fitting level refers to the maximum grid level that can be used to fit the spatial location characteristics of geospatial elements using grid cells in a multi-level geographic grid system to ensure fitting accuracy. Figure 2 In the above, I, II, III, IV and V respectively use 1st, 2nd, 3rd and 4th grid to perform spatial fitting on the same polygon, and by determining the fitting level of each geospatial element, the fitting accuracy can be ensured.

[0054] Further, the method according to the application comprises:

[0055] In the case where the data object is vector data, the target accuracy is determined according to the application requirements of each geospatial element;

[0056] The level closest to each target accuracy is selected from the multi-level geographic grid system as the fitting level of each geospatial element.

[0057] In practical applications, in the case of a data object being vector data, according to application requirements, such as in the case of an application requirement being that an error of a geospatial feature can be simulated to a certain extent, an error of data in the data object is taken as a target precision, and then a level closest to the target precision is selected from the multi-level geographic grid system as a fitting level of the geospatial feature, in the case of an application requirement being that a high-precision requirement such as an original distribution pattern, contour details, and the like of the geospatial feature can be restored, a first precision is selected as the target precision, and in the case of an application requirement being that a low-precision requirement such as a general trend, general contour, and the like of the geospatial feature can be restored, a second precision is selected as the target precision, the second precision being less than the first precision. Specifically, in the case of a spatial position feature of a geospatial feature being a point element, such as geolocation data of a wild plant, in which point elements are randomly distributed, an absolute error of longitude and latitude being 10 m, and a numerical precision being about 10 cm (for example, longitude and latitude coordinates being 113.359276, 23.190215), in the case of an application requirement being that an error of the point element can be simulated to a certain extent, 10 m is selected as the target precision, and a grid level with a grid aperture closest to 10 m is selected from the multi-level geographic grid system as a fitting level of the feature; in the case of an application requirement being that an original distribution pattern of a point element in the data can be restored, 10 cm is selected as the target precision, and a grid level with a grid aperture closest to 10 cm is selected from the multi-level geographic grid system as the fitting level. If the spatial position feature of the geospatial feature is a line element, such as a national road with a width of 8 m, in the case of an application requirement being that not only a general trend of the road can be fitted, but also a width of an actual road surface of the road can be covered by one to two grid cells as much as possible, a precision greater than 8 m can be selected as the target precision, a level with a grid aperture greater than or equal to 8 m and closest to 8 m is selected from the multi-level geographic grid system as the fitting level, and then the grid cells of the level can not only fit the general trend of the road, but also cover the width of the actual road surface of the road by one to two grid cells as much as possible; in the case of an application requirement being that different lanes on the road surface can be further distinguished on the grid, a precision less than 4 m can be selected as the target precision, a level with a grid aperture less than 4 m and closest to 4 m is selected from the multi-level geographic grid system as the fitting level. If the spatial position feature of the geospatial feature is a surface element, such as a building, in the case of an application requirement being that a general contour and a direction of an entrance and exit of the building can be fitted, a meter level is selected as the target precision, and a level with a grid aperture closest to the meter level is selected from the multi-level geographic grid system as the fitting level; in the case of an application requirement being that contour details of the building can be fitted, a centimeter level is selected as the target precision, and a level with a grid aperture reaching the centimeter level is selected from the multi-level geographic grid system as the fitting level.

[0058] Further, the determining the fitting level of the data object from the multi-level geographic grid system further comprises:

[0059] In the case that the data object is raster data, selecting a level with a grid aperture not less than the spatial scale of the pixel as the fitting level from the multi-level geographic grid system;

[0060] In the case that the data object is text data, converting the data object into vector data, and determining the fitting level according to the fitting level determination step of the vector data.

[0061] In practical applications, the data type of the data object includes raster data and text data in addition to vector data, and therefore, the fitting level of the geographic spatial element of the data object with the data type of raster data and text data needs to be determined. Specifically, for raster data, such as a remote sensing image with a spatial resolution of 30m per pixel, a fitting level with a grid aperture not less than 30m should be selected. By selecting a level with a grid aperture not less than the spatial scale of the pixel as the fitting level, the original data resolution can be preserved to the greatest extent, and redundant calculation can be avoided.

[0062] For the spatial location feature of the geographic spatial element in the text data, the text data can be converted into vector data first, and then the fitting level can be determined according to the logic of the vector data, that is, the fitting level can be determined according to the fitting level determination step of the vector data. For example, a plant species distribution record up to the county level can be converted into a corresponding county vector polygon first, and then the target accuracy can be determined according to the actual application requirement of the data, and the fitting level can be determined according to the target accuracy. In practical applications, the distribution of plants is neither possible to cover the entire county nor completely limited by the county boundary, and therefore, according to the research characteristics of the flora, a grid cell with an aperture close to 1km or 10km can be used as a basic unit for measuring the distribution area of plants, 1km or 10km can be selected as the target accuracy, and a level with a grid aperture close to 1km or 10km can be selected as the fitting level of each county vector polygon.

[0063] In practical applications, the grid cell in the fitting level is the smallest unit for fitting the specific spatial location feature, the fitting level controls the fitting details of the spatial location feature, and usually also determines the data size after the spatial location is converted into grid cell data. In this application, the fitting level is determined according to the application requirement and the actual situation of the data, so as to balance the actual situation of the data and the general requirement of the application.

[0064] Step S2, determining all target grid cells corresponding to the spatial location feature of the geographic spatial element according to the fitting level, and all the target grid cells form a grid object of the geographic spatial element.

[0065] In practical applications, the target grid cells in the grid object can include not only the grid cells of the fitting level, but also the grid cells of the remaining different levels, and the grid cells of the fitting level in the grid object at least intersect with the spatial position of the geospatial element to ensure boundary fitting accuracy.

[0066] Further, the determining of all target grid cells corresponding to the spatial position feature of the geospatial element according to the fitting level includes:

[0067] determining whether the data object is vector data;

[0068] if yes, determining all target grid cells corresponding to the spatial position feature from the multi-level geographic grid system according to the type and fitting level of the geospatial element;

[0069] if no, converting the data object into vector data, and determining the target grid cells by the target grid cell determination step.

[0070] In practical applications, after step S1, the text data is converted into vector data, but the raster data is not converted into vector data, so it is necessary to determine whether the data object is vector data, and in the case of vector data, all target grid cells corresponding to the geospatial element are determined from the vector data according to the type and fitting level of the geospatial element, and in the case of raster data, the geographic range covered by the raster data is first converted into vector data, and then all target grid cells corresponding to the geospatial element are determined from the vector data according to the type and fitting level of the geospatial element.

[0071] Further, the determining of all target grid cells corresponding to the spatial position feature from the multi-level geographic grid system according to the type and fitting level of the geospatial element includes:

[0072] in the case of the type of the geospatial element being a point element, selecting the grid cell corresponding to the point element from the fitting level as the target grid cell;

[0073] in the case of the type of the geospatial element being a line element, selecting the grid cell corresponding to the line element from the fitting level as a basic grid cell, determining a mapping grid cell from a higher level according to the mapping relationship between the basic grid cell and the grid cells of each level, determining a replacement grid cell from the mapping grid cell according to the basic grid cell, updating the basic grid cell according to the replacement grid cell, and repeating the above steps until the corresponding at least one lower grid cell in each mapping grid cell is a non-basic grid cell, and taking the basic grid cell at this time as the target grid cell, wherein the higher level is the upper level of the level corresponding to the basic grid cell.

[0074] In the case that the type of the geographic spatial element is a surface element, it is determined whether the spatial scale of the surface element is greater than a preset scale threshold. If yes, the smallest grid cell completely covering the geographic spatial element in space is extracted from the multi-level geographic grid system as a basic grid cell. The intersecting grid cells are determined from the lower level according to the mapping relationship between the basic grid cell and each level grid cell. The replacement grid cell is determined from the basic grid cell according to the intersecting grid cell. The intersecting grid cell is updated according to the replacement grid cell. The updated intersecting grid cell is taken as the basic grid cell. The final basic grid cell is obtained by descending to the target level. The final basic grid cell is taken as the target grid cell. The target level is preset. The target level is not greater than the fitting level. If no, the target grid cell is determined by the determination step of the target grid cell of the line element.

[0075] In actual application, if the geographic spatial element is composed of point elements, such as converting the planting distribution map of plants into a grid object, it is necessary to convert the point position of each plant into a grid cell that can cover the point position in space as a target grid cell. Usually, the grid point that can cover each plant point is selected from the fitting level as the target grid cell. All target grid cells form the grid object of the element.

[0076] If the geographic spatial element is composed of line elements, such as converting the line element representing the road into a grid object. When converting, all grid cells intersecting with the element can be extracted from the fitting level of the element as basic grid cells. Then, the basic grid cells are degenerated by the mapping relationship of each level grid cell of the target geographic grid system, that is, the basic grid cells are mapped to the grid cells of the upper level to obtain the mapping grid cells. At this time, the mapping grid cells represent the grid cells in the upper level having a mapping relationship with the basic grid cells. In the case that all lower level grid cells corresponding to a mapping grid cell are basic grid cells, the mapping grid cell is taken as a replacement grid cell. The basic grid cell corresponding to the replacement grid cell is taken as a grid cell to be replaced. The grid cell to be replaced is replaced by the replacement grid cell to update the basic grid cell. The upper level is continued to be ascended until at least one lower level grid cell corresponding to each mapping grid cell is a non-basic grid cell. At this time, the basic grid cell is taken as the target grid cell.

[0077] As Figure 3As shown, if a geospatial feature is composed of polygon elements, and the spatial scale of the polygon elements is no larger than a preset scale threshold, the spatial scale of the polygon elements is relatively small. Therefore, it can be converted using the same method as line elements, such as... Figure 3 As shown in Figure I, the spatial positional features of the surface elements are first converted into mesh cells of the fitting hierarchy, and then degenerated into target mesh cells, as shown in Figure I. Figure 3 The rightmost figure in section I shows: some mesh cells from the fitting level (level 4), level 3, and level 2; however, when transforming large-scale surface elements, that is, when transforming surface elements with a spatial scale greater than a preset scale threshold, in order to reduce the processing of a large amount of small-scale mesh cell information during the transformation process and improve transformation efficiency, such as... Figure 3 As shown in II, a basic grid unit can be selected from the multi-level geographic grid system to fully cover the geographic spatial elements. Then, based on the mapping relationship of the hierarchical structure of the multi-level geographic grid system, the basic grid unit is mapped to the grid units of the next lower level, resulting in mapped grid units. These mapped grid units represent grid units in the next lower level that have a mapping relationship with the basic grid unit. Grid units that intersect with the geographic spatial elements are selected from the mapped grid units, resulting in intersecting grid units. If all the lower-level grid units corresponding to a basic grid unit are intersecting grid units, the basic grid unit is used as a replacement grid unit, and the corresponding intersecting grid units are used as grid units to be replaced. The grid units to be replaced are replaced with replacement grid units to obtain updated intersecting grid units. These updated intersecting grid units are then used as basic grid units, and the process continues down to the next lower level until the target level is reached. The corresponding grid units to be replaced in the target level are then replaced with replacement grid units to obtain the final basic grid unit. This final basic grid unit is used as the target grid unit, where the target level cannot be greater than the fitted level. In addition, in some practical applications, the target grid cell may be directly or indirectly limited to grid cells from a specific level. For example, the aperture of the target grid cell must be as close as possible to 1km but not more than 10km. The grid level with the aperture closest to 1km can be used as the fitting level for spatial features, while the other grid levels cannot be used as the target levels. The target grid cell can be limited by setting the target level in advance.

[0078] In practical applications, such as Figure 4 As shown, a geographic vector data object is converted into a gridded data object, where Figure 4 In this context, 'I' represents the original data object, which includes a lake composed of polygon elements, a highway composed of line elements, and two types of spatial elements composed of point elements. Figure 4 (II) in the middle, convert them into mesh objects respectively.Figure 4 a new data object (IV) in logic can be finally obtained. Figure 4 The target grid cell in the grid object is essentially a degeneration of the fitted hierarchical grid cell, therefore, the grid object can not only maintain the boundary fitting precision of the geographic spatial feature to the greatest extent, but also reduce the number of grid cells of the grid object, thereby greatly simplifying the expression of the spatial position of various geographic features and improving the access efficiency of spatial data.

[0079] Step S3, attribute information of the grid object and the target grid cell is created.

[0080] In practical applications, one grid object corresponds to one or more target grid cells, and in addition to the pointer of the belonging data object and the identification of the grid object, the attribute information of the grid object can also directly inherit or write the attribute information possessed or implied by the geographic spatial feature, such as if the geographic spatial feature represents a lake, the water storage capacity, water surface area, maximum water depth, and data collection time of the lake can be written into the attribute of the grid object, if the geographic spatial feature represents a piece of forest, the number of trees, average diameter at breast height, average tree height, average crown width, and data collection time can be written into the attribute of the grid object, and if the geographic spatial feature represents the air temperature at a specific space-time, the minimum temperature, maximum temperature, average temperature, and data collection time of the region at the space-time can be written into the attribute of the grid object. In addition, the attribute information of the grid object also needs to contain some information related to the target grid cell, such as the fitted level of the grid object, the number of fitted hierarchical grid cells covered, the maximum and minimum row and column numbers of the fitted hierarchical grid cells covered, the maximum and minimum levels of the contained target grid cells, and the like, and the attribute information of the grid object can support the grid object to participate in the corresponding spatial operation.

[0081] Specifically, the target grid cell is a basic unit of the grid object, and the attribute of each target grid cell can include the direction of the grid object to which it belongs, the level of the target geographic grid system to which it belongs, the geographic grid code of the target grid cell, the actual spatial area of the target grid cell, the length, width and aperture of the grid cell, and the like. In addition, if the geographic spatial element is composed of a simple point element, the attribute of the target grid cell can also inherit the existing attributes of the point element. For example, if the geographic spatial element is a tree distribution map composed of point elements, the attribute information of each tree, such as tree height, diameter at breast height, and tree age, can be written into the attribute information of the corresponding target grid cell. The discrete, regular and hierarchical target grid cells can significantly improve the access and calculation performance of spatial data. For example, geographic spatial metrics such as area and distance can be converted into the sum of the areas or apertures of the geographic grid cells. The calculation of spatial topological relationships such as inclusion, intersection, adjacency and separation, as well as the calculation of spatial intersection, union, difference and complement, can be converted into set operations based on geographic grid codes. Discrete grid cells can also better support distributed access and parallel computing, and thus can further meet the needs of large-scale data dynamic interactive computing and analysis.

[0082] Step S4, establishing a first data relationship between the data object and the grid object, establishing a second data relationship between the grid object and the target grid cell, and constructing a geographic data model according to the first data relationship and the second data relationship.

[0083] Further, as shown in Figure 5 the first data relationship includes a one-to-one or one-to-many data relationship between the data object and the grid object, and the second data relationship includes a one-to-one, one-to-many or many-to-many data relationship between the grid object and the target grid cell.

[0084] In practical applications, the design of data relationship should be determined according to the specific relationship of business data, so as to simplify the data relationship as much as possible and improve the data access and computing analysis efficiency. For example, in some businesses, if the data object and the grid object are in a one-to-one relationship, the data object can be combined with the grid object, that is, one object includes the attributes of the data object and the attributes of the grid object; in some businesses, if the grid object and the target grid cell are in a one-to-one relationship, the grid object can also be combined with the target grid cell; if in actual business, one target grid cell can be associated with multiple grid objects, then according to the specific application design requirements, it is determined whether to adopt a one-to-many or a many-to-many relationship, the former can realize more efficient single table query, and the latter can provide more flexible relationship creation for business; in addition, if each data object is a point element, the data object, the grid object and the target grid cell can be integrated into one, that is, one target grid cell can represent one data object, and the target grid cell has the triple attributes of the data object, the grid object and the target grid cell. In summary, based on the "data object-grid object-grid cell" model of the multi-level structured geographic grid system, a unified integrated framework can be provided for heterogeneous geographic spatial data, and support can be provided for the best balance of precision, efficiency and universality in the computing analysis of large-scale geographic spatial data.

[0085] The geographic data model construction method of the application can convert various geographic spatial data into grid data composed of three concept models of "data object-grid object-grid cell" that are correlated with each other, thereby realizing the remodeling and isomorphism of the overall content of multi-source heterogeneous geographic spatial data, having good universality and being able to provide extensive support for the integration and utilization of various geographic spatial data. At the same time, the grid isomorphism of data can greatly improve the access and computing efficiency of large-scale geographic spatial data, and can effectively balance the efficiency, precision and universality requirements of large-scale geographic spatial data computing.

[0086] As shown in Figure 6 The geographic data model construction system provided by the embodiment of the application comprises:

[0087] The hierarchical determination module 10 is configured to determine the fitting level of each geographic spatial element from the multi-level geographic grid system according to the data object, wherein the data object refers to geographic data supporting various geographic spatial analysis;

[0088] The grid determination module 20 is configured to determine all target grid cells corresponding to the spatial position characteristics of the geographic spatial element according to the fitting level, and all the target grid cells constitute the grid object of the geographic spatial element.

[0089] An attribute creating module 30 is configured to create attribute information for the grid object and the target grid cell;

[0090] A model constructing module 40 is configured to establish a first data relationship between the data object and the grid object, establish a second data relationship between the grid object and the target grid cell, and construct a geographic data model according to the first data relationship and the second data relationship.

[0091] The modules of the geographic data model constructing system can be realized by software, hardware or a combination thereof. The modules and units can be embedded in or independent of a processor of a computer device in hardware form, or stored in a memory of the computer device in software form, so as to be called and executed by the processor to perform the operations of the modules.

[0092] As shown in Figure 7 , the embodiment of the present application discloses a computer device, which comprises a memory and a processor, and the memory stores a computer program.

[0093] The computer device can be a server, and its internal structure diagram can be as shown in Figure 7 . The computer device comprises a processor, a memory, a network interface and a database connected through a system bus. The processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device comprises a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operating system and the computer program in the non-volatile storage medium. The network interface of the computer device is configured to communicate with an external terminal through a network connection. The computer program is executed by the processor to implement the geographic data model constructing method described in the above embodiments.

[0094] Those skilled in the art can understand that Figure 7 the structure shown in the figure is only a block diagram of part of the structure related to the scheme of the present application, and does not constitute a limitation on the computer device to which the scheme of the present application is applied. The specific computer device can comprise more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0095] The embodiment of the present application also discloses a computer readable storage medium storing a computer program, wherein the computer program enables a computer to execute the geographic data model constructing method described in the above embodiments.

[0096] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a non-volatile computer readable storage medium, and when the computer program is executed, the processes of the above-mentioned embodiments of the methods can be included. Any reference to memory, storage, database or other medium used in the embodiments provided in the present application can 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. As an illustration but not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0097] The technical features of the above embodiments can be combined in any manner. In order to make the description simple, all possible combinations of the technical features in the above embodiments are not described, however, as long as the combinations of the technical features do not contradict, they should be considered as the scope of the present disclosure.

Claims

1. A method of building a geographic data model, characterized by, The method comprises the following steps: determining a fitting level of each geospatial element from a multi-level geographic grid system according to a data object, wherein the data object refers to geographic data supporting various types of geospatial analysis; determining all target grid cells corresponding to the spatial location features of the geospatial element according to the fitting level, wherein all the target grid cells form a grid object of the geospatial element; creating attribute information for the grid object and the target grid cells; establishing a first data relationship between the data object and the grid object, establishing a second data relationship between the grid object and the target grid cells, and constructing a geographic data model according to the first data relationship and the second data relationship.

2. The geographic data model building method of claim 1, wherein, The step of determining a fitting level of each geospatial element from a multi-level geographic grid system according to a data object comprises the following steps: in the case that the data object is vector data, determining a target precision according to the application requirements of each geospatial element; selecting a level closest to each target precision from the multi-level geographic grid system as the fitting level of each geospatial element.

3. The geographic data model building method of claim 2, wherein, The step of determining a fitting level of each geospatial element from a multi-level geographic grid system according to a data object comprises the following steps: in the case that the data object is raster data, selecting a level with a grid aperture not smaller than the spatial scale of a pixel from the multi-level geographic grid system as the fitting level; in the case that the data object is text data, converting the data object into vector data, and determining the fitting level by using the fitting level determination step for vector data.

4. The geographic data model building method of claim 1, wherein, The step of determining all target grid cells corresponding to the spatial location features of the geospatial element according to the fitting level comprises the following steps: determining whether the data object is vector data; if yes, determining all target grid cells corresponding to the spatial location features from the multi-level geographic grid system according to the type of the geospatial element and the fitting level; if no, converting the data object into vector data, and determining the target grid cells by using the target grid cell determination step for vector data.

5. The geographic data model building method of claim 4, wherein, The step of determining all target grid cells corresponding to the spatial location features from the multi-level geographic grid system according to the type of the geospatial element and the fitting level comprises the following steps: in the case that the type of the geospatial element is a point element, selecting a grid cell corresponding to the point element from the fitting level as a target grid cell; in the case that the type of the geospatial element is a line element, selecting a grid cell corresponding to the line element from the fitting level as a basic grid cell, determining a mapping grid cell from a higher level according to the mapping relationship between the basic grid cell and the grid cells of each level, determining a replacement grid cell from the mapping grid cell according to the basic grid cell, updating the basic grid cell according to the replacement grid cell, and repeating the above steps until the basic grid cell is a non-basic grid cell in at least one lower level corresponding to each mapping grid cell, and taking the basic grid cell at this time as a target grid cell, wherein the higher level is a level one level higher than the level corresponding to the basic grid cell.

6. The geographic data model building method of claim 5, wherein, The step of determining all target grid cells corresponding to the spatial location features from the multi-level geographic grid system according to the type of the geospatial element and the fitting level further comprises the following steps: In a case where the type of the geospatial element is a surface element, it is determined whether a spatial scale of the surface element is greater than a preset scale threshold; If yes, a minimum grid cell completely covering the geospatial element in space is extracted from the multi-level geographic grid system as a basic grid cell, an intersecting grid cell is determined from a lower level according to a mapping relationship between the basic grid cell and each level grid cell, a replacement grid cell is determined from the basic grid cell according to the intersecting grid cell, the intersecting grid cell is updated according to the replacement grid cell, the updated intersecting grid cell is taken as the basic grid cell, and the final basic grid cell is obtained by descending to a target level until a target grid cell is obtained, wherein the lower level is a next level of a level corresponding to the basic grid cell, the target level is preset, and the target level is not greater than a fitting level. If no, the target grid cell is determined by using the determination step of the target grid cell of the line element.

7. The geographic data model building method of claim 1, wherein, The first data relationship includes a one-to-one or one-to-many data relationship between the data object and the grid object, and the second data relationship includes a one-to-one, one-to-many or many-to-many data relationship between the grid object and the target grid cell.

8. A geographic data processing system, characterized by The method comprises the following steps: A level determination module is configured to determine a fitting level of each geospatial element from a multi-level geographic grid system according to a data object, wherein the data object refers to geographic data supporting various types of geospatial analysis; A grid determination module is configured to determine all target grid cells corresponding to spatial position characteristics of the geospatial element according to the fitting level, and all target grid cells form a grid object of the geospatial element; An attribute creation module is configured to create attribute information for the grid object and the target grid cell; A model construction module is configured to establish a first data relationship between the data object and the grid object, establish a second data relationship between the grid object and the target grid cell, and construct a geographic data model according to the first data relationship and the second data relationship.

9. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that, The processor executes the computer program to realize the steps of the method of any one of claims 1-7.

10. A computer readable storage medium having stored thereon a computer program, characterized in that The computer program is executed by the processor to realize the steps of the method of any one of claims 1-7.

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