CN117132738B - Spherical discrete grid multi-scale equidistant mode quantization method and system - Google Patents
Spherical discrete grid multi-scale equidistant mode quantization method and system Download PDFInfo
- Publication number
- CN117132738B CN117132738B CN202311394452.8A CN202311394452A CN117132738B CN 117132738 B CN117132738 B CN 117132738B CN 202311394452 A CN202311394452 A CN 202311394452A CN 117132738 B CN117132738 B CN 117132738B
- Authority
- CN
- China
- Prior art keywords
- grid
- equidistant
- spherical
- different scales
- category
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000000034 method Methods 0.000 title claims abstract description 58
- 238000013139 quantization Methods 0.000 title description 19
- 238000011160 research Methods 0.000 claims description 24
- 238000010586 diagram Methods 0.000 claims description 10
- 230000008569 process Effects 0.000 claims description 9
- 238000004458 analytical method Methods 0.000 claims description 7
- 238000010276 construction Methods 0.000 claims description 5
- 238000004590 computer program Methods 0.000 claims description 3
- 238000004088 simulation Methods 0.000 claims description 3
- 238000011002 quantification Methods 0.000 claims description 2
- 238000005094 computer simulation Methods 0.000 abstract description 12
- 238000012545 processing Methods 0.000 abstract description 6
- 210000004027 cell Anatomy 0.000 description 33
- 238000004891 communication Methods 0.000 description 7
- 238000005457 optimization Methods 0.000 description 6
- 238000004364 calculation method Methods 0.000 description 5
- 229910003460 diamond Inorganic materials 0.000 description 5
- 239000010432 diamond Substances 0.000 description 5
- 238000006243 chemical reaction Methods 0.000 description 4
- 230000005540 biological transmission Effects 0.000 description 3
- 230000008859 change Effects 0.000 description 2
- 238000007405 data analysis Methods 0.000 description 2
- 230000000694 effects Effects 0.000 description 2
- 238000011156 evaluation Methods 0.000 description 2
- 230000006870 function Effects 0.000 description 2
- 230000010354 integration Effects 0.000 description 2
- 238000010295 mobile communication Methods 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 238000012732 spatial analysis Methods 0.000 description 2
- 101100001674 Emericella variicolor andI gene Proteins 0.000 description 1
- 230000004075 alteration Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 210000003888 boundary cell Anatomy 0.000 description 1
- 230000000295 complement effect Effects 0.000 description 1
- 238000007796 conventional method Methods 0.000 description 1
- 238000013079 data visualisation Methods 0.000 description 1
- 230000007812 deficiency Effects 0.000 description 1
- 230000002950 deficient Effects 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000009472 formulation Methods 0.000 description 1
- 230000003993 interaction Effects 0.000 description 1
- 239000000203 mixture Substances 0.000 description 1
- 238000005381 potential energy Methods 0.000 description 1
- 238000003672 processing method Methods 0.000 description 1
- 230000000750 progressive effect Effects 0.000 description 1
- 239000007787 solid Substances 0.000 description 1
- 238000007619 statistical method Methods 0.000 description 1
- 230000000007 visual effect Effects 0.000 description 1
- 238000012800 visualization Methods 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T17/00—Three dimensional [3D] modelling, e.g. data description of 3D objects
- G06T17/20—Finite element generation, e.g. wire-frame surface description, tesselation
Landscapes
- Physics & Mathematics (AREA)
- Engineering & Computer Science (AREA)
- Computer Graphics (AREA)
- Geometry (AREA)
- Software Systems (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Image Analysis (AREA)
Abstract
The application relates to the technical field of general image data processing or generation, and provides a method and a system for quantifying a spherical discrete grid multi-scale equidistant mode. According to the method, according to the value of the equidistant index of the grid units, the equidistant characteristic reclassification is carried out on all the grid units in the spherical discrete grid under different scales; fitting the areas covered by all grid units of each classification obtained by reclassifying based on the spherical convex hull fitting principle to obtain boundary convex hulls of each classification under different scales; constructing a multi-scale equidistant mode of a spherical discrete grid based on boundary convex hulls of various categories under different scales; the multi-scale equidistant mode of the spherical discrete grid is a triple structure, and the triple structure comprises category codes, unit proportions and convex hull coding sets, wherein the convex hull coding sets are determined according to grid unit sets contained in boundary convex hulls of various categories under different scales. The method provides possibility for improving the dynamic simulation precision of the region.
Description
Technical Field
The present invention relates to the field of image data processing or generating technologies in general, and in particular, to a method, a system, a computer readable storage medium and an electronic device for quantization of a spherical discrete grid multi-scale equidistant pattern.
Background
The spherical discrete grid is a sphere fitting grid which infinitely subdivides the surface of the earth without changing its shape. The spherical discrete grid can store, manage and express space information according to the real existence mode of the earth, and can achieve the purpose of simulating the surface of the earth when the space information is subdivided to a certain degree, so that the space information can break through the limitation of a map projection plane, a solid foundation is provided for big data and a digital earth frame, and a data integration and analysis frame is also provided for large-area and even global scale research. The consistency of the distances between the spherical grid units is important for the precision of data integration and analysis, in other words, the equidistance between the grid units is important for dynamic modeling application taking the distances as independent variables, and the method can ensure the equal probability movement from one unit to any adjacent unit, thereby ensuring the precision of spatial data analysis and visualization. However, the topology of the sphere and the plane is different from each other, resulting in an incomplete agreement between the distance between the spherical mesh and its neighboring mesh center point, i.e. there is no exactly equidistant mesh on the sphere. The equidistant deformation characteristics of different spherical discrete grids are different, and the equidistant deformation characteristics of grid units at different positions of the same model are also different, so that the problems of spatial data overlapping, fracture and inconsistent spatial relationship can be caused by the differences in data analysis and dynamic simulation. It is necessary to study the equidistant deformation of the spherical discrete grid in depth and to define the equidistant deformation of the grid units at different positions. It will help in the determination of the grid equidistant optimization parameters while providing a grid selection basis for dynamic simulation applications with distance as an argument.
In the geospatial field, scales correspond to spatial resolution, both of which are generally considered synonyms, multiscale, i.e., multi-resolution representation of data. The multi-scale spherical discrete grids represent hierarchical nested relations of the spherical discrete grids, and the hierarchical nested relations are established between the discrete grids with different spatial resolutions, so that the grids with higher spatial resolutions are contained in the grids with lower spatial resolutions, data conversion and transmission under different scales are realized, and the hierarchical nested relations are the basis of dynamic analysis, simulation and visualization of spatial data.
Aiming at the multiscale equidistance of a spherical discrete grid, the existing research is generally limited to the research on the trend and the integrity of equidistant deformation under different resolutions, the change rule of the single grid unit is obtained through statistical analysis on the basis of the equidistant index value of the single grid unit, the association relation of equidistant deformation under the multiscale cannot be provided, the equidistant deformation condition of a research area under any scale cannot be directly determined in the dynamic simulation process, and the efficiency and the precision of the dynamic simulation of a geographical area are further deficient.
Accordingly, there is a need to provide an improved solution to the above-mentioned deficiencies of the prior art.
Disclosure of Invention
An object of the present application is to provide a method, a system, a computer-readable storage medium and an electronic device for quantifying a spherical discrete grid multi-scale equidistant pattern, so as to solve or alleviate the problems in the prior art.
In order to achieve the above object, the present application provides the following technical solutions:
the application provides a multi-scale equidistant mode quantization method of a spherical discrete grid, which comprises the following steps:
according to the value of the equidistant index of the grid units, carrying out equidistant characteristic reclassification on all the grid units in the spherical discrete grid under different scales;
fitting the areas covered by all grid units of each classification obtained by reclassifying based on the spherical convex hull fitting principle to obtain boundary convex hulls of each classification under different scales;
constructing a multi-scale equidistant mode of a spherical discrete grid based on boundary convex hulls of various categories under different scales;
the multi-scale equidistant mode of the spherical discrete grid is a triple structure, the triple structure comprises category codes, unit proportions and convex hull coding sets, the category codes are codes of all categories obtained by reclassifying, the unit proportions are proportions of grid units contained in boundary convex hulls of all categories under different scales to the total number of the grid units under the scales, and the convex hull coding sets are determined according to the grid unit sets contained in the boundary convex hulls of all the categories under different scales.
Preferably, based on the principle of fitting spherical convex hulls, fitting areas covered by all grid units of each classification obtained by reclassifying to obtain boundary convex hulls of each classification under different scales, including:
drawing an equidistant spatial distribution map of the spherical discrete grid based on the reclassification result;
determining the area covered by all grid units of each category according to the positions of all grid units of each category on the equidistant space distribution diagram of the spherical discrete grid, and taking the area as an equidistant area corresponding to each category;
and fitting the equidistant regions corresponding to the categories by using the spherical convex hull fitting principle to obtain boundary convex hulls of the categories under different scales.
Preferably, the principle of fitting the spherical convex hull is used for fitting the equidistant regions corresponding to the categories to obtain boundary convex hulls of the categories under different scales, and the method comprises the following steps:
extracting grid units from each category to obtain a grid unit set of each category;
traversing each grid unit in the grid unit sets of each category, determining the grid units at the boundary of the equidistant area, and forming a boundary unit set;
The minimum convex hull containing the set of boundary elements is calculated as the boundary convex hull.
Preferably, the convex hull coding set is determined by:
determining grid units on the boundary convex hull in each category under different scales to form a convex hull unit set;
and determining codes corresponding to each grid unit in the convex hull unit set on the basis of grid coding rules of different scales one by one category to obtain a convex hull coding set.
Preferably, before the equidistant feature reclassifying is performed on all grid cells in the spherical discrete grid under different scales, the method further comprises:
calculating the values of the equidistant indexes of all grid units of the spherical discrete grid with different scales;
determining an equidistant index interval;
and taking the equidistant index interval as a reclassification standard, and reclassifying equidistant characteristics of all grid units in the spherical discrete grid under different scales according to the value of the equidistant index of the grid units.
Preferably, the calculation formula of the equidistance index is as follows:
，
in the method, in the process of the invention,ed i representing grid cellscell i Is provided for the non-uniform spacing of (c),d ij representing grid cellscell i And adjacent grid unitscell j Is the distance between the center points of (a);N nei representation ofcell i The number of adjacent cells, except for pentagons at the vertices of an icosahedron, N nei Are all equal to 6.
Preferably, the determining the equidistant index interval specifically includes:
acquiring values of equidistant indexes of all grid units, and calculating corresponding statistics;
and determining the equidistant index interval according to the statistic.
The embodiment of the application provides a spherical discrete grid multiscale equidistant mode quantization system, which comprises:
the reclassification unit is configured to reclassify the equidistant characteristics of all grid units in the spherical discrete grid under different scales according to the values of the equidistant indexes;
the fitting unit is configured to fit the areas covered by all grid units of each category obtained by reclassifying based on the principle of spherical convex hull fitting, so as to obtain boundary convex hulls of each category under different scales;
the construction unit is configured to construct a multi-scale equidistant mode of the spherical discrete grid based on boundary convex hulls of various categories under different scales;
the multi-scale equidistant mode of the spherical discrete grid is a triple structure, the triple structure comprises category codes, unit proportions and convex hull coding sets, the category codes are codes of all categories obtained by reclassifying, the unit proportions are proportions of the total number of grid units contained in boundary convex hulls of all categories under different scales to the total number of grid units under the scales, and the convex hull coding sets are determined according to the grid unit sets contained in the boundary convex hulls of all the categories under different scales.
Embodiments of the present application also provide a computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements a spherical discrete grid multiscale equidistant pattern quantization method as described in any of the embodiments above.
The embodiment of the application also provides electronic equipment, which comprises: the device comprises a memory, a processor and a program stored in the memory and capable of running on the processor, wherein the processor executes the program to realize the multi-scale equidistant mode quantization method of the spherical discrete grid according to any embodiment.
The beneficial effects are that: according to the technical scheme, through carrying out equidistant characteristic reclassification and convex hull fitting on all grid units in the spherical discrete grid under different scales, a grid unit set covered by a boundary convex hull is extracted, a multi-scale equidistant mode of the spherical discrete grid is constructed, the mode takes the spherical discrete grid as a description object, the association relation of equidistant deformation of the spherical discrete grid under different scales can be quantitatively described through a triplet structure, the spatial relation of equidistant deformation distribution at different positions can be quantitatively described, and therefore in the process of geographic data spatial analysis and dynamic simulation, the equidistant deformation condition of the research area position can be directly, rapidly and accurately determined according to the association relation, and further whether the position can meet the precision requirement in data conversion and transmission under different scales can be judged. The present embodiment adopts a triple structure to represent a multiscale equidistant mode of a spherical discrete grid, and the triple comprises: the method comprises the steps of category codes, unit proportions and convex hull coding sets, wherein the convex hull coding sets have corresponding relations with grid unit sets contained in boundary convex hulls of all categories under different scales, so that grid unit codes at any given scale and any position can be determined to determine the equidistant category of the grid unit according to the corresponding relations, further, the equidistant optimization scheme and optimization parameters of the grid are rapidly determined, and the efficiency and the accuracy of dynamic simulation of the geographic area are improved. In addition, according to the corresponding relation, the space coverage range and the unit proportion of different categories of equidistant deformation conditions under different scales can be directly determined, and a grid selection basis is provided for dynamic simulation application taking distance as an independent variable.
Drawings
The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiments of the application and together with the description serve to explain the application and do not constitute an undue limitation to the application. Wherein:
fig. 1 is a flow diagram of a spherical discrete grid multi-scale equidistant pattern quantization method provided according to some embodiments of the present application;
FIG. 2 is a schematic illustration of a spherical surface normal icosahedron;
FIG. 3 is a flow chart of a method for quantization of spherical discrete grid multi-scale equidistant patterns according to some embodiments of the present application;
FIG. 4 is a schematic diagram of Gnomonic4H trellis encoding rules;
FIG. 5 is a graph of various scale deviations for a multiscale equidistant mode;
FIG. 6 is a schematic diagram of a spherical discrete grid multi-scale equidistant pattern quantization system provided in accordance with some embodiments of the present application;
fig. 7 is a schematic structural diagram of an electronic device according to an embodiment of the present application;
fig. 8 is a hardware configuration diagram of an electronic device according to an embodiment of the present application.
Detailed Description
In order to facilitate understanding of the technical solutions of the present application, the following description will explain related arts.
In recent years, the international academy and related application departments have conducted intensive researches on geometric features of a spherical discrete grid from different sides, including formulation of grid geometric feature evaluation standards, quantitative research of geometric feature indexes, construction of a geometric feature evaluation index system and the like.
Wherein, the widely accepted "Goodchild criterion" in the field of spherical discrete grid research describes the equidistance of grid units as "the distances between any adjacent grid reference points are equal"; the equal area of the cells is described as "split grid area uniform"; the shape of the cells is identically described as "split mesh geometry consistent". Based on the Goodchild criterion, partial scholars propose a series of quantifiable grid geometric characteristic indexes and analyze geometric characteristics of different spherical discrete grids. Such as: the fuzzy similarity of the spherical triangle grid based on the similar triangle principle can be used for comprehensively evaluating the geometric shape and area deformation of the grid unit; the indexes of the distance between any adjacent grid points and the included angle between the grid points and the connecting line between any two adjacent grid points, which are constructed by taking the grid points as objects, and the total potential energy of the spherical discrete grid reflect the uniformity of the distribution of the central points and the vertexes of the spherical discrete grid units to a certain extent. The geometric characteristics of the spherical discrete grid units have similarity and mutual restriction, and the uniformity of the distribution of the unit points can reflect the area, the shape and the equidistant characteristics of the units. The learner quantifies "the distances between the reference points of any adjacent grids are equal" as the coefficient of variation of the distances between the grid cells and the center points of their first-order adjacent cells. Based on the quantization index, the convergence of the equidistance of different spherical discrete grids (such as spherical equal-product triangle/diamond/hexagon discrete grids, spherical equal-angle triangle/diamond/hexagon discrete grids, direct spherical subdivision grids and the like), the similarity of spatial distribution characteristics and the like are analyzed. In addition, partial scholars analyze the geometric stability, geometric distribution characteristics, the change trend and convergence of geometric deformation at different levels and the like of different spherical discrete grids by using indexes such as area, side length, center point distance and the like.
The geometrical characteristics of the spherical discrete grids are researched from different angles, various quantifiable indexes are designed, and the equidistant deformation characteristics of different spherical discrete grids are analyzed. There is still a disadvantage in that the study of the equidistance of the spherical discrete grid is a trending and qualitative study. The main manifestations are:
(1) In the existing research, from a microscopic view, quantitative equidistant description is provided for grid units, and the research of the whole spherical discrete grid is limited to the trend research of equidistant deformation, namely, the research of the total range and convergence of equidistant deformation of all grid units of the spherical discrete grid under different resolutions. This can only reflect the worst case of equidistant deformation of the mesh as a whole, and is a trending, holistic study.
(2) The existing research is to describe the equidistant deformation spatial distribution characteristics of the spherical discrete grids in a qualitative expression, only the quantized values of the equidistant deformation of the units are used as unit filling values, the visual expression is carried out on the equidistant deformation results of the grids, and the equidistant deformation spatial distribution characteristics of the spherical discrete grids are not quantized.
In order to solve the problem that research on equidistant characteristics of a spherical discrete grid is limited to trend analysis and qualitative description, and inspired by a spherical convex hull fitting thought, the embodiment takes a spherical icosahedron hexagon discrete grid as an object, and provides a multi-scale equidistant mode quantization method of the spherical discrete grid.
The present application will be described in detail below with reference to the accompanying drawings in conjunction with embodiments. Various examples are provided by way of explanation of the present application and not limitation of the present application. Indeed, it will be apparent to those skilled in the art that modifications and variations can be made in the present application without departing from the scope or spirit of the application. For example, features illustrated or described as part of one embodiment can be used on another embodiment to yield still a further embodiment. Accordingly, it is intended that the present application include such modifications and alterations insofar as they come within the scope of the appended claims or the equivalents thereof.
Method embodiment:
the embodiment of the application provides a multi-scale equidistant mode quantization method of a spherical discrete grid, as shown in fig. 1-5, the method comprises the following steps:
according to the value of the equidistant index of the grid units, carrying out equidistant characteristic reclassification on all the grid units in the spherical discrete grid under different scales;
fitting the areas covered by all grid units of each classification obtained by reclassifying based on the spherical convex hull fitting principle to obtain boundary convex hulls of each classification under different scales;
constructing a multi-scale equidistant mode of a spherical discrete grid based on boundary convex hulls of various categories under different scales;
The multi-scale equidistant mode of the spherical discrete grid is a triple structure, the triple structure comprises category codes, unit proportions and convex hull coding sets, the category codes are codes of all categories obtained by reclassifying, the unit proportions are proportions of the number of grid units contained in boundary convex hulls of all categories under different scales to the total number of grid units under the scales, and the convex hull coding sets are determined according to the grid unit sets contained in boundary convex hulls of all the categories under different scales.
In this embodiment, a spherical icosahedron four-hole hexagonal grid (Gnomonic 4H grid) based on Gnomonic projection is taken as an example, and a proposed multi-scale equidistant mode quantization method of a spherical icosahedron hexagonal discrete grid is described in detail. The regular icosahedron is a basic geometric model of an earth sphere, as shown in fig. 2, the regular icosahedron is (a) in fig. 2, the regular icosahedron is (b) in fig. 2, the regular icosahedron is composed of 20 regular triangles (also called basic triangular faces, abbreviated as basic faces), the triangles are projected onto the earth surface through a projection rule of Gnomonic projection to form a spherical regular icosahedron, then the spherical regular icosahedron is split by a hexagonal grid, and different split levels are used for expressing unused spatial resolutions, so that the spherical icosahedron hexagonal discrete grid refers to a grid system which takes the regular icosahedron as a geometric model and divides the earth sphere into hexagonal grid units.
In the conventional method for researching equidistant deformation characteristics, the index for measuring the equidistance is generally determined first, the value of the equidistance index of each grid unit is calculated, then each grid unit is classified within a certain basic plane range under a specific scale, the process is called equidistant classification, and the equidistant classification result can determine the equidistant classification corresponding to each grid unit. In this embodiment, in order to obtain macroscopic level equidistant features of the spherical discrete grid, firstly, equidistant feature reclassification is performed on all grid units in the spherical discrete grid under different scales, so that equidistant classification attributes of the grid units in the original basic plane range are rewritten, and a grid unit reclassification result under a unified classification standard in the spherical discrete grid range is obtained.
The reclassification is to reclassify all grid units of the spherical discrete grid into a plurality of categories according to a unified classification standard, each category reflects the corresponding equidistant deformation characteristics of the category under the global view angle of the spherical discrete grid, and a foundation is provided for equidistant quantitative expression of the spherical discrete grid.
After reclassification, the grid cells of each category under different scales (corresponding to different subdivision levels of the spherical discrete grid) are covered on the earth surface to form a coverage area with the same equidistant characteristics under the classification standard. In order to express the geometric form characteristics of the coverage area, in this embodiment, the coverage area is fitted based on the principle of spherical convex hull fitting, so as to obtain boundary convex hulls of various categories under different scales. Based on the convex hull fitting principle, the boundary convex hull is a convex polygon, which contains the maximum boundary information of all grid units in a given category, that is, the boundary range of the boundary convex hull can cover the range of all grid units in a corresponding category. And determining boundary convex hulls of all classes, and simultaneously determining a set of all grid units intersected by the boundary convex hulls of all classes under different scales, so as to construct a multi-scale equidistant mode of the spherical discrete grid.
In this embodiment, the multiscale equidistant pattern of the spherical discrete grid is represented by triples (class codes, unit proportions, convex hull code sets), i.eed_Pattern={(m,P,CODE chcellbm ) And, in the formula (I),ed_Patternrepresenting a multi-scale equidistant pattern,mthe category code is represented by a code of the category,Pthe ratio of the units is indicated,CODE chcellbm representing a convex hull coding set. From the structure, the spherical discrete grids are abstracted into triples, the equidistant deformation characteristics of the spherical discrete grids of different categories are represented by the relation between category codes and equidistant indexes, the proportion of the total number of grid units of each category in different scales is quantitatively and definitely given by using the unit proportion, namely the specific proportion of the grid units meeting a certain equidistant classification standard in the scale is calculated, and the scale and the position information are reflected by using the convex hull coding set, namelyThe three-dimensional group takes the spherical discrete grids as description objects, not only can quantitatively describe the association relation of equidistant deformation of the spherical discrete grids with different scales, but also can quantitatively describe the spatial relation of equidistant deformation at different positions, so that in the process of geographic data spatial analysis and dynamic simulation, the equidistant deformation condition of the research area position can be directly, quickly and accurately determined according to the association relation only by determining the research area position, and further whether the data conversion and transmission at different scales at the position can meet the precision requirement can be judged.
The convex hull coding set is determined according to the grid unit set contained in the boundary convex hulls of all the categories under different scales, namely, the convex hull coding set has a corresponding relation with the grid unit set contained in the boundary convex hulls of all the categories under different scales, so that the equidistant category of the grid unit can be determined according to the corresponding relation by giving the grid unit codes at any scale and any position, the grid equidistant optimization scheme and optimization parameters can be determined rapidly, and the efficiency and the accuracy of dynamic simulation of the geographic area are improved.
It will be appreciated that there may be a variety of implementations of the spherical discrete grid equidistant feature reclassification, and in some alternative embodiments, prior to equidistant feature reclassification of all grid cells in the spherical discrete grid at different scales, reclassification may be accomplished by: calculating the values of the equidistant indexes of all grid units of the spherical discrete grid with different scales; determining an equidistant index interval; and taking the equidistant index interval as a reclassification standard, and reclassifying equidistant characteristics of all grid units in the spherical discrete grid under different scales according to the value of the equidistant index of the grid units.
Illustratively, for the firstNThe relationship between the mesh subdivision hierarchy and the number of mesh units and the unit area of the layer Gnomonic4H mesh is shown in table 1, and table 1 is as follows:
table 1 statistics of different grid split hierarchical grid cells
Calculating the value of the equidistant index of each grid unit according to the following formula:
（1）
in the method, in the process of the invention,ed i representing grid cellscell i Is used for the equidistant index of (1),d ij representing grid cellscell i And adjacent grid unitscell j Is the distance between the center points of (a);N nei representation ofcell i The number of adjacent cells, except for pentagons at the vertices of an icosahedron,N nei are all equal to 6.
Based on the above formula (1), for the firstNCalculating the value of the equidistant indexes of the Gnomonic4H grids one by one grid unit to obtain a Gnomonic4H grid equidistant index seted={ed i }，i<T. In the method, in the process of the invention,Trepresenting the total number of arbitrary grid cells.
edThe range of distances between the center point of a grid cell and the center points of adjacent grid cells is described, and the closer the value of the range is to 1, the stronger the equidistance of the grid cell is, and the smaller the equidistant deformation is; conversely, the closer the value is to 0, the greater the equidistant deformation of the grid cells.
Acquiring equidistant index setsedAnd then determining an equidistant index interval delta, and taking the equidistant index interval delta as a reclassifying standard, and reclassifying the equidistant characteristics of all grid units in the spherical discrete grids under different scales based on the equidistant index interval delta.
It is understood that the equidistant index interval Δ may be equal or may be set to be unequal. The equidistant index interval delta can be determined by various methods, for example, can be determined empirically, and can also be selected according to actual requirements. Guest for increasing equidistant index interval deltaObservability, the embodiment is based on equidistant index setedAnd determining the equidistance index interval by adopting the following steps: acquiring values of equidistant indexes of all grid units, and calculating corresponding statistics; from the statistics, an equidistance index interval is determined.
Specifically, a set of values of the equidistant indicators of all grid cells is calculatededCorresponding statistics, such as mean, standard deviation, and polar error, and then determining an equidistant index interval delta according to equidistant mode quantification requirements, for example, the interval delta can be set to be 0.1, 0.05, 0.025, and the like; then, based on the interval, toedReclassifying to obtainmCounting the unit proportion in each category to obtainP。
Illustratively, given Δ=0.05, gnomonic4H grids can be divided into 20 categories. Statistics of 5-12 layers of Gnomonic4H gridsed i The ratio in each section is shown in Table 2. Because the Gnomonic4H grid has higher equidistant characteristics, the unit edHigher values, statistics find the cells of the 5-12 layer Gnomonic4H gridedThe values are all greater than 0.775.
Table 2 reclassified individual interval (category) grid cells
And fitting a reclassified boundary convex hull on the basis of reclassification. In some alternative embodiments, based on the principle of spherical convex hull fitting, the regions covered by all grid cells of each category obtained by reclassifying are fitted to obtain boundary convex hulls of each category under different scales, and the boundary convex hulls can be realized by the following steps: drawing an equidistant spatial distribution map of the spherical discrete grid based on the reclassification result; determining the area covered by all grid units of each category according to the positions of all grid units of each category on the equidistant space distribution diagram of the spherical discrete grid, and taking the area as an equidistant area corresponding to each category; and fitting the equidistant regions corresponding to the categories by using the spherical convex hull fitting principle to obtain the boundary convex hulls of the categories under different scales.
In this embodiment, based on the reclassification result, a spherical discrete grid equidistant spatial distribution map is drawndistribution ed As can be seen from fig. 2, the geometric features of the spherical icosahedral hexagonal discrete grid are symmetrical about the icosahedral base plane, so that the equidistant spatial distribution map of the spherical discrete grid only analyzes the results of one base plane at layers 5-7.
Analysis finds that the grid units of each reclassified category have clear coverage areas on the equidistant space distribution diagram of the spherical discrete grid, the coverage areas are used as equidistant areas corresponding to each category, and then convex hulls are used for fitting the equidistant areas to obtain boundary convex hulls of each category under different scales.
In some alternative embodiments, fitting the reclassified boundary convex hull may be accomplished by: extracting grid units from each category to obtain a grid unit set of each category; traversing each grid unit in the grid unit sets of each category, determining the grid units at the boundary of the equidistant area, and forming a boundary unit set; the minimum convex hull containing the set of boundary elements is calculated as the boundary convex hull.
Illustratively, the above steps may be further refined as:
(1) Extracting the grid units category by category to obtain a grid unit setcell={cell 1 ，cell 2 ，…，cell m }, whereincell i Represent the firstiA collection of units of a category. For example, as can be seen from Table 1, for a layer 5 Gnomonic4H mesh, the proportion of mesh units belonging to category 17 is 0.045, i.ecell 17 The size of the set of units is 23; same reasoncell 18 、cell 19 、cell 20 Is 129, 261, 99, respectively.
(2) Traversing each group of unit sets, determining grid units at boundaries to form a boundary unit setboundary={cell bm }. Taking 5 th, 6 th and 7 th layers of Gnomonic4H grids and class 20 equidistant categories as examples,cell 20 represents a class 20 set of boundary cells, i.e., a set of cells within the class hexagon that is innermost in the icosahedron base plane.
(3) Computing a set comprising boundary cellsboundaryIs the minimum convex hull of (2)ch. Exemplary, the 20 th class of mesh units coverage of different split levels, including the 20 th class of 5 th layer Gnomonic4H mesh (i.e., 5 th layer Gnomonic mesh-ch 20 ) Class 20 of layer 6 Gnomonic4H grids (i.e., layer 6 Gnomonic grids)ch 20 ) Class 20 of layer 7 Gnomonic4H lattice (i.e., layer 7 Gnomonic lattice)ch 20 ) Taking class 20 equidistant categories of the 5, 6 and 7-layer Gnomonic4H mesh as an example, the calculation of the minimum convex hull can be realized by the following steps: firstly, sequentially connecting the center points of all kinds of boundary units to obtain initial convex hulls corresponding to the coverage areas of the grid units of the same kind in different subdivision layers. Then, the same type of initial convex hulls in different subdivision layers, such as three initial convex hulls corresponding to the 20 th type of the 5 th, 6 th and 7 th layers of Gnomonic4H grids, are overlapped, and the average value of the three initial convex hulls is calculated to obtain the equal-distance type optimized convex hull chTaking an optimized convex hullchAs a boundary convex hull to improve the versatility of the Gnomonic4H mesh equidistant mode.
(4) Determining grid units on convex hulls to form a convex hull unit setch cellbm . Respectively determining the convex hulls in each category and optimizing the convex hullschIntersecting grid cells are used as convex hull cell sets.
After acquisition as a set of convex hull units, the set of convex hull units may be encoded, for which purpose, in some alternative embodiments, the set of convex hull codes is determined by: determining grid units on the boundary convex hull in each category under different scales to form a convex hull unit set; and determining codes corresponding to each grid unit in the convex hull unit set on the basis of grid coding rules of different scales one by one category to obtain a convex hull coding set.
Specifically, a hierarchical encoding rule of the Gnomonic4H mesh is determined. Referring to FIG. 4, the left side of FIG. 4 isThe unfolded icosahedron is formed into a rhombus (also called a basic rhombus) by vertically adjacent triangles (basic triangular faces), and the number of the icosahedron is 1,2, … and 10; the right graph shows the arrangement rule of the grid units in the diamond shape, inI-O-JIn the coordinate system of the two-dimensional coordinate system,I max =J max =2 N ，（Nis a split hierarchy), andI max 、J max is the firstNThe maximum rank number of the layer subdivision hierarchy.
Based on the above hierarchical coding rule, in the Gnomonic4H grid, the coding of any unit can be expressed asQ，I，J) Wherein, the method comprises the steps of, wherein,Qrepresents a diamond surface formed by two adjacent base surfaces,Q=1，2，…，10；I、Jrespectively show the grid units in the firstNThe rank number of the layer is set,I max =J max =2 N . According to the existing code conversion rule, the method can realizeQ，I，J) And geographic coordinates [ ]λ，φ) And (3) converting the obtained result to correspond to the coordinates of the central point of the grid unit.
Determining the codes corresponding to the convex hull unit sets by category to obtain a convex hull code setCODE chcellbm ={code_ch cellbm }. The convex hull unit coding sets for each equidistant class of Gnomonic4H mesh are as follows (hereQFor example, =1, i.e. diamond 1) of:
in the equidistant mode described above,I max =J max =2 N ，Nrepresent the firstNAnd (5) dividing the hierarchy.
On the basis of the convex hull coding set, a spherical icosahedron hexagon discrete grid equidistant mode is established according to the corresponding relation among the convex hull coding set, the category and the unit proportion. That is, in combination with table 2 and the corresponding convex hull coding sets of each category, the multi-scale equidistant pattern quantization result of Gnomonic4H grid is as follows:
wherein,code_ch cellb17 \code_ch cellb18 representing a collectioncode_ch cellb17 Relative to a collectioncode_ch cellb17 Is a difference set of (c). Without loss of generality,A\Bis a collectionARelative to a collectionBMay also be referred to as a relative complement. Can be expressed as mathematical symbols A\B={x|x∈AAnd is also provided withx∉B}, i.e. belonging to a collectionABut not of a setBIs an element of (a). In the same way, the processing method comprises the steps of,code_ch cellb18 \code_ch cellb19 、code_ch cellb19 \code_ch cellb20 respectively represent the collectioncode_ch cellb18 Relative to a collectioncode_ch cellb19 Difference set, collection of (1)code_ch cellb19 Relative to a collectioncode_ch cellb20 Is a difference set of (c). The convex hull coding set uses the difference set to express that the coding length can be reduced, and therefore the computing resource is saved.
The method provided by the embodiment quantifies equidistant features of a spherical discrete grid (taking a Gnomonic4H grid as an example) and uses grid coding to quantitatively express the equidistant features, so that equidistant modes of the Gnomonic4H grid have multiscale.
In order to verify the accuracy of the multi-scale equidistant mode provided in this embodiment, an 8 th and 9 th layer Gnomonic4H mesh is used as an object, anded_Patterncalculating the proportion of units in each equidistant class group (i.e. equidistant deformation interval)PAnd compared with the actual statistical results in table 2, the results are shown in table 3, and the corresponding graph is shown in fig. 5. Because of the limitation of hardware, when the subdivision level is larger than 9, the Gnomonic4H grid cannot be displayed to be deformed equidistantly.
Table 3 Gnomonic4H grid equidistance vs. actual statistics
From the experimental results, the multi-scale equidistant mode based on Gnomonic4H grided_PatternThe unit occupation ratio deviation of each equidistant deformation zone is smaller than 0.1%, and the overlapping degree is larger than 99.2%.
Further to the description of the embodiment, the method can determine the equidistant deformation condition of the grid cells with arbitrary scale in the research area according to any research area on the earth surfaceAFor the object, assume that the study area needs to be checkedADynamic simulation of ecological environment with different scales can be performed by using a multiscale equidistant mode based on Gnomonic4H grided_Patternis calculation regionAEquidistant deformation of the inner grid cells. The calculation result shows the regionAThe equidistant deformations of the inner grid cells are all at [0.925, 0.975 ], and the spatial distribution discovery area is further drawnAIs entirely atcode_ch cellb19 \code_ch cellb20 In the method, the calculation result based on the equidistant mode is consistent, and the multi-scale equidistant mode is explained to accurately describe equidistant deformation conditions of grid cells in any area of the earth surface.
In summary, in this embodiment, by reclassifying the reclassifying characteristics of equidistant deformation of the spherical icosahedron hexagonal discrete grid, and according to the grid units in the spatial distribution boundary in each category, and combining the hierarchical nesting relationship of the grids, a multi-scale equidistant mode is constructed by means of grid coding, the equidistant deformation of the spherical icosahedron hexagonal discrete grid is quantitatively described, and the following technical effects are obtained:
(1) By utilizing the multiscale equidistant mode, the equidistant deformation values of the units at different positions of the high-resolution spherical discrete grid can be directly determined, the equidistant deformation of each unit is not required to be calculated independently according to an equidistant deformation formula, and the calculated amount is reduced to a certain extent.
(2) The multi-scale equidistant mode is utilized to directly determine the equidistant deformation condition of the research area, further screen out units needing equidistant optimization in the area, lay a foundation for improving the equidistant property of the grids in the research area, and further provide possibility for improving the dynamic simulation precision of the area.
(3) The model has expandability, and provides thought for quantitatively researching geometric features (such as area, angle, side length and the like) of different spherical discrete grids.
System embodiment:
an embodiment of the present application provides a spherical discrete grid multiscale equidistant mode quantization system, as shown in fig. 6, the system includes: a reclassification unit 1201, a fitting unit 1202 and a construction unit 1203. Wherein:
the reclassification unit 1201 is configured to reclassify the equidistant characteristics of all grid units in the spherical discrete grid under different scales according to the values of the equidistant indexes;
fitting unit 1202, configured to fit the regions covered by all grid units of each category obtained by reclassifying based on the principle of spherical convex hull fitting, so as to obtain boundary convex hulls of each category under different scales;
the construction unit 1203 is configured to construct a multi-scale equidistant mode of the spherical discrete grid based on the boundary convex hulls of the various categories under different scales;
The multi-scale equidistant mode of the spherical discrete grids is a triple structure, the triple structure comprises category codes, unit proportions and convex hull coding sets, the category codes are codes of all categories obtained by reclassifying, the unit proportions are proportions of the number of grid units contained in boundary convex hulls of all categories under different scales to the total number of grid units under the scales, and the convex hull coding sets are determined according to the grid unit sets contained in boundary convex hulls of all the categories under different scales.
The spherical discrete grid multi-scale equidistant mode quantization system provided by the embodiment of the application can realize the steps and the flow of the spherical discrete grid multi-scale equidistant mode quantization method provided by any embodiment, and achieve the same technical effects, and is not described in detail herein.
Device example:
fig. 7 is a schematic structural diagram of an electronic device provided according to some embodiments of the present application; as shown in fig. 7, the electronic device includes:
one or more processors 1301;
a computer readable medium may be configured to store one or more programs 1302, the one or more processors 1301, when executing the one or more programs 1302, implement the steps of: according to the value of the equidistant index of the grid units, carrying out equidistant characteristic reclassification on all the grid units in the spherical discrete grid under different scales; fitting the areas covered by all grid units of each classification obtained by reclassifying based on the spherical convex hull fitting principle to obtain boundary convex hulls of each classification under different scales; constructing a multi-scale equidistant mode of a spherical discrete grid based on boundary convex hulls of various categories under different scales; the multi-scale equidistant mode of the spherical discrete grid is a triple structure, the triple structure comprises category codes, unit proportions and convex hull coding sets, the category codes are codes of all categories obtained by reclassifying, the unit proportions are proportions of the number of grid units contained in boundary convex hulls of all categories under different scales to the total number of grid units under the scales, and the convex hull coding sets are determined according to the grid unit sets contained in boundary convex hulls of all the categories under different scales.
FIG. 8 is a hardware architecture of an electronic device provided in accordance with some embodiments of the present application; as shown in fig. 8, the hardware structure of the electronic device may include: a processor 1401, a communication interface 1402, a computer readable medium (also called memory) 1403, and a communication bus 1404.
Wherein the processor 1401, the communication interface 1402, and the computer readable medium 1403 communicate with each other via a communication bus 1404.
Computer readable media 1403 may be configured to store one or more programs.
Alternatively, the communication interface 1402 may be an interface of a communication module, such as an interface of a GSM module.
Wherein the processor 1401 may be specifically configured to: according to the value of the equidistant index of the grid units, carrying out equidistant characteristic reclassification on all the grid units in the spherical discrete grid under different scales; fitting the areas covered by all grid units of each classification obtained by reclassifying based on the spherical convex hull fitting principle to obtain boundary convex hulls of each classification under different scales; constructing a multi-scale equidistant mode of a spherical discrete grid based on boundary convex hulls of various categories under different scales; the multi-scale equidistant mode of the spherical discrete grid is a triple structure, the triple structure comprises category codes, unit proportions and convex hull coding sets, the category codes are codes of all categories obtained by reclassifying, the unit proportions are proportions of the number of grid units contained in boundary convex hulls of all categories under different scales to the total number of grid units under the scales, and the convex hull coding sets are determined according to the grid unit sets contained in boundary convex hulls of all the categories under different scales.
The processor 1401 may be a general purpose processor including a central processing unit (central processing unit, CPU for short), a network processor (Network Processor, NP for short), etc., and may also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf programmable gate array (FPGA) or other programmable logic device, discrete gate or transistor logic device, discrete hardware components. The disclosed methods, steps, and logic blocks in the embodiments of the present application may be implemented or performed. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The electronic device of the embodiments of the present application exist in a variety of forms including, but not limited to:
(1) A mobile communication device: such devices are characterized by mobile communication capabilities and are primarily aimed at providing voice, data communications. Such terminals include: smart phones (e.g., iPhone), multimedia phones, functional phones, and low-end phones, etc.
(2) Ultra mobile personal computer device: such devices are in the category of personal computers, having computing and processing functions, and generally also having mobile internet access characteristics. Such terminals include: PDA, MID, and UMPC devices, etc., such as iPad.
(3) Portable entertainment device: such devices may display and play multimedia content. The device comprises: audio, video players (e.g., iPod), palm game consoles, electronic books, and smart toys and portable car navigation devices.
(4) And (3) a server: the configuration of the server includes a processor, a hard disk, a memory, a system bus, and the like, and the server is similar to a general computer architecture, but is required to provide highly reliable services, and thus has high requirements in terms of processing capacity, stability, reliability, security, scalability, manageability, and the like.
(5) Other electronic devices with data interaction function.
It should be noted that, according to implementation requirements, each component/step described in the embodiments of the present application may be split into more components/steps, and two or more components/steps or part of operations of the components/steps may be combined into new components/steps, so as to achieve the purposes of the embodiments of the present application.
The above-described methods according to embodiments of the present application may be implemented in hardware, firmware, or as software or computer code storable in a recording medium such as a CD ROM, RAM, floppy disk, hard disk, or magneto-optical disk, or as computer code originally stored in a remote recording medium or a non-transitory machine storage medium and to be stored in a local recording medium downloaded through a network, so that the methods described herein may be stored on such software processes on a recording medium using a general purpose computer, a special purpose processor, or programmable or dedicated hardware such as an ASIC or FPGA. It is understood that a computer, processor, microprocessor controller, or programmable hardware includes a memory component (e.g., RAM, ROM, flash memory, etc.) that can store or receive software or computer code that, when accessed and executed by the computer, processor, or hardware, implements the spherical discrete grid multiscale equidistant mode quantization methods described herein. Furthermore, when a general purpose computer accesses code for implementing the methods illustrated herein, execution of the code converts the general purpose computer into a special purpose computer for performing the methods illustrated herein.
Those of ordinary skill in the art will appreciate that the elements and method steps of the examples described in connection with the embodiments disclosed herein can be implemented as electronic hardware, or as a combination of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the embodiments of the present application.
It should be noted that, in the present specification, each embodiment is described in a progressive manner, and identical and similar parts of each embodiment are all referred to each other, and each embodiment is mainly described in a different point from other embodiments. In particular, for the apparatus and system embodiments, since they are substantially similar to the method embodiments, the description is relatively simple, with reference to the description of the method embodiments in part.
The above-described apparatus and system embodiments are merely illustrative, in which elements illustrated as separate elements may or may not be physically separate, and elements illustrated as elements may or may not be physical elements, may be located in one place, or may be distributed over a plurality of network elements. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment. Those of ordinary skill in the art will understand and implement the present invention without undue burden.
Claims (10)
1. The method is applied to carrying out different-scale geographic data space analysis or ecological environment simulation on any research area on the surface of the earth, and comprises the following steps:
according to the value of the equidistant index of the grid units, carrying out equidistant characteristic reclassification on all the grid units in the spherical discrete grid under different scales;
the spherical discrete grid is a sphere fitting grid, after reclassification, grid units of each category under different scales are covered on the surface of the earth to form a coverage area with the same equidistant characteristics under the classification standard, and expressing the geometric form characteristics of the coverage area comprises the following steps: fitting the areas covered by all grid units of each classification obtained by reclassifying based on the spherical convex hull fitting principle to obtain boundary convex hulls of each classification under different scales;
constructing a multi-scale equidistant mode of a spherical discrete grid based on boundary convex hulls of various categories under different scales;
the multi-scale equidistant mode of the spherical discrete grid is a triple structure, the triple structure comprises category codes, unit proportions and convex hull coding sets, the category codes are codes of all categories obtained by reclassifying, the unit proportions are proportions of grid units contained in boundary convex hulls of all categories under different scales to the total number of the grid units under the scales, and the convex hull coding sets are determined according to the grid unit sets contained in the boundary convex hulls of all the categories under different scales;
And calculating the equidistant deformation condition of the grid units in the research area by utilizing the multiscale equidistant mode of the spherical discrete grid.
2. The method according to claim 1, wherein fitting the regions covered by all grid cells of each category obtained by reclassification based on the principle of spherical convex hull fitting to obtain boundary convex hulls of each category under different scales comprises:
drawing an equidistant spatial distribution map of the spherical discrete grid based on the reclassification result;
determining the area covered by all grid units of each category according to the positions of all grid units of each category on the equidistant space distribution diagram of the spherical discrete grid, and taking the area as an equidistant area corresponding to each category;
and fitting the equidistant regions corresponding to the categories by using the spherical convex hull fitting principle to obtain boundary convex hulls of the categories under different scales.
3. The method according to claim 2, wherein fitting the equidistant regions corresponding to the respective classes using the principle of spherical convex hull fitting, to obtain boundary convex hulls of the respective classes at different scales, comprises:
extracting grid units from each category to obtain a grid unit set of each category;
Traversing each grid unit in the grid unit sets of each category, determining the grid units at the boundary of the equidistant area, and forming a boundary unit set;
the minimum convex hull containing the set of boundary elements is calculated as the boundary convex hull.
4. The method of claim 1, wherein the set of convex hull codes is determined by:
determining grid units on the boundary convex hull in each category under different scales to form a convex hull unit set;
and determining codes corresponding to each grid unit in the convex hull unit set on the basis of grid coding rules of different scales one by one category to obtain a convex hull coding set.
5. The method of any one of claims 1 to 4, further comprising, prior to reclassifying equidistant features for all grid cells in the spherical discrete grid at different scales:
calculating the values of the equidistant indexes of all grid units of the spherical discrete grid with different scales;
determining an equidistant index interval;
and taking the equidistant index interval as a reclassification standard, and reclassifying equidistant characteristics of all grid units in the spherical discrete grid under different scales according to the value of the equidistant index of the grid units.
6. The method of claim 5, wherein the equidistant indicators are calculated as follows:
，
in the method, in the process of the invention,ed i representing grid cellscell i Is provided for the non-uniform spacing of (c),d ij representing grid cellscell i And adjacent grid unitscell j Is the distance between the center points of (a);N nei representation ofcell i The number of adjacent cells, except for pentagons at the vertices of an icosahedron,N nei are all equal to 6.
7. The method according to claim 5, wherein the determining of the equidistance indicator interval is in particular:
calculating corresponding statistics of the values of the equidistant indexes of all grid units;
and determining the equidistant index interval according to the statistic.
8. A spherical discrete grid multi-scale equidistant mode quantification system, wherein the system is applied to perform different scale geospatial analysis or ecological environment simulation on any research area on the surface of the earth, and comprises:
the reclassification unit is configured to reclassify the equidistant characteristics of all grid units in the spherical discrete grid under different scales according to the values of the equidistant indexes;
the spherical discrete grids are sphere fitting grids, and after reclassification, grid units of each category under different scales are covered on the surface of the earth to form coverage areas with the same equidistant characteristics under the classification standard; the fitting unit is used for expressing geometric form characteristics of the coverage area and is configured to fit all the areas covered by the grid units of each category obtained by reclassifying based on the principle of spherical convex hull fitting to obtain boundary convex hulls of each category under different scales;
The construction unit is configured to construct a multi-scale equidistant mode of the spherical discrete grid based on boundary convex hulls of various categories under different scales;
the multi-scale equidistant mode of the spherical discrete grid is a triple structure, the triple structure comprises category codes, unit proportions and convex hull coding sets, the category codes are codes of all categories obtained by reclassifying, the unit proportions are proportions of the total number of grid units contained in boundary convex hulls of all categories under different scales to the total number of grid units under the scales, and the convex hull coding sets are determined according to the grid unit sets contained in the boundary convex hulls of all the categories under different scales;
and the calculating unit is configured to calculate equidistant deformation conditions of the grid units in the research area by utilizing a multi-scale equidistant mode of the spherical discrete grid.
9. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the method of any of claims 1-7.
10. An electronic device, comprising: memory, a processor, and a program stored in the memory and executable on the processor, the processor implementing the method according to any one of claims 1-7 when executing the program.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311394452.8A CN117132738B (en) | 2023-10-26 | 2023-10-26 | Spherical discrete grid multi-scale equidistant mode quantization method and system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311394452.8A CN117132738B (en) | 2023-10-26 | 2023-10-26 | Spherical discrete grid multi-scale equidistant mode quantization method and system |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN117132738A CN117132738A (en) | 2023-11-28 |
| CN117132738B true CN117132738B (en) | 2024-02-13 |
Family
ID=88858526
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202311394452.8A Active CN117132738B (en) | 2023-10-26 | 2023-10-26 | Spherical discrete grid multi-scale equidistant mode quantization method and system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN117132738B (en) |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113114272A (en) * | 2021-04-12 | 2021-07-13 | 中国人民解放军战略支援部队信息工程大学 | Method and device for encoding data structure of hexagonal grid with consistent global tiles |
| CN113515525A (en) * | 2021-07-29 | 2021-10-19 | 郑州众合景轩信息技术有限公司 | Spatial data organization method based on global multi-scale grid |
| CN114580351A (en) * | 2022-03-03 | 2022-06-03 | 时空慧智(北京)科技有限公司 | Method for fusing and coding global subdivision grids and local relative position grids |
| CN115546443A (en) * | 2022-11-25 | 2022-12-30 | 西南林业大学 | Local equidistance optimization method and system for spherical hexagonal grid |
| CN115801024A (en) * | 2022-11-24 | 2023-03-14 | 西南林业大学 | Coding method, system, device and medium for local isometry optimization spherical grid |
| CN116433872A (en) * | 2023-06-01 | 2023-07-14 | 西南林业大学 | Vertex positioning method and system considering equidistant deformation characteristics of spherical equal-volume grid |
-
2023
- 2023-10-26 CN CN202311394452.8A patent/CN117132738B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113114272A (en) * | 2021-04-12 | 2021-07-13 | 中国人民解放军战略支援部队信息工程大学 | Method and device for encoding data structure of hexagonal grid with consistent global tiles |
| CN113515525A (en) * | 2021-07-29 | 2021-10-19 | 郑州众合景轩信息技术有限公司 | Spatial data organization method based on global multi-scale grid |
| CN114580351A (en) * | 2022-03-03 | 2022-06-03 | 时空慧智(北京)科技有限公司 | Method for fusing and coding global subdivision grids and local relative position grids |
| CN115801024A (en) * | 2022-11-24 | 2023-03-14 | 西南林业大学 | Coding method, system, device and medium for local isometry optimization spherical grid |
| CN115546443A (en) * | 2022-11-25 | 2022-12-30 | 西南林业大学 | Local equidistance optimization method and system for spherical hexagonal grid |
| CN116433872A (en) * | 2023-06-01 | 2023-07-14 | 西南林业大学 | Vertex positioning method and system considering equidistant deformation characteristics of spherical equal-volume grid |
Non-Patent Citations (3)
| Title |
|---|
| Fuli Luo 等 .Construction of quality evaluation indicator system for diamond discrete global grid systems.《International Journal of Digital Earth 》.2023,第16卷(第1期),3637-3660. * |
| Matthew J. Gregory 等.A comparison of intercell metrics on discrete global grid systems.《Computers, Environment and Urban Systems》.2008,第32卷(第3期),188-203. * |
| 赵学胜 等.全球离散格网的建模方法及基本问题.《地理与地理信息科学》.2012,第28卷(第1期),29-34. * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN117132738A (en) | 2023-11-28 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN107481311B (en) | Three-dimensional city model rendering method and device | |
| CN113628314B (en) | Visualization method, device and equipment for photographic measurement model in illusion engine | |
| CN102509339B (en) | Method for simplifying vertex clustering of three-dimensional models with texture constraint | |
| CN101976468B (en) | Method and system for visualizing multiresolution dynamic landform | |
| CN113781667A (en) | Three-dimensional structure simplified reconstruction method and device, computer equipment and storage medium | |
| CN112749244A (en) | Method and device for realizing digital twin city space coordinate system based on illusion engine and storage medium | |
| CN102117488B (en) | Method for constructing surface reflection characteristics of real object in virtual environment | |
| US20100086208A1 (en) | Almost rectangular triangulations | |
| CN111460193B (en) | Three-dimensional model classification method based on multi-mode information fusion | |
| Liu et al. | Memory-efficient modeling and slicing of large-scale adaptive lattice structures | |
| Kim et al. | Querying simplexes in quasi-triangulation | |
| CN115239784A (en) | Point cloud generation method and device, computer equipment and storage medium | |
| CN115994197A (en) | GeoSOT grid data calculation method | |
| US11417073B2 (en) | System and method for generating hierarchical level-of-detail measurements for runtime calculation and visualization | |
| Chaudhuri et al. | Scalable computation of distributions from large scale data sets | |
| Li et al. | R3MR: Region growing based 3D mesh reconstruction for big data platform | |
| CN117132738B (en) | Spherical discrete grid multi-scale equidistant mode quantization method and system | |
| CN113436223A (en) | Point cloud data segmentation method and device, computer equipment and storage medium | |
| CN111881919B (en) | Line element intelligent simplification method and device based on tracking type grid subdivision | |
| Dou et al. | An equal‐area triangulated partition method for parallel Xdraw viewshed analysis | |
| Tong et al. | A new effective hexagonal discrete global grid system: Hexagonal quad balanced structure | |
| CN112231800B (en) | BIM graph optimization method and device and computer storage medium | |
| Hu et al. | Voronoi cells of non-general position spheres using the GPU | |
| Morgan et al. | Using binary space partitioning to generate urban spatial patterns | |
| CN117237503B (en) | Geographic element data accelerated rendering and device |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |