CN103984748B - A kind of solar wind data partition, coding and the access method of large scale solar-terrestrial physics - Google Patents
A kind of solar wind data partition, coding and the access method of large scale solar-terrestrial physics Download PDFInfo
- Publication number
- CN103984748B CN103984748B CN201410225392.1A CN201410225392A CN103984748B CN 103984748 B CN103984748 B CN 103984748B CN 201410225392 A CN201410225392 A CN 201410225392A CN 103984748 B CN103984748 B CN 103984748B
- Authority
- CN
- China
- Prior art keywords
- grid
- subdivision
- pdqg
- data
- coding
- 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 27
- 238000005192 partition Methods 0.000 title claims 5
- 210000001624 hip Anatomy 0.000 claims description 6
- 238000000605 extraction Methods 0.000 claims 1
- 230000004304 visual acuity Effects 0.000 claims 1
- 238000012800 visualization Methods 0.000 claims 1
- 238000005070 sampling Methods 0.000 description 11
- 230000008520 organization Effects 0.000 description 9
- 238000010586 diagram Methods 0.000 description 8
- 238000001514 detection method Methods 0.000 description 5
- 238000011160 research Methods 0.000 description 4
- 238000011161 development Methods 0.000 description 3
- 230000018109 developmental process Effects 0.000 description 3
- 230000000007 visual effect Effects 0.000 description 3
- 230000003044 adaptive effect Effects 0.000 description 2
- 230000008901 benefit Effects 0.000 description 2
- 238000004364 calculation method Methods 0.000 description 2
- 238000013079 data visualisation Methods 0.000 description 2
- 239000002245 particle Substances 0.000 description 2
- 230000008569 process Effects 0.000 description 2
- 230000001360 synchronised effect Effects 0.000 description 2
- 238000004458 analytical method Methods 0.000 description 1
- 230000008859 change Effects 0.000 description 1
- 230000006835 compression Effects 0.000 description 1
- 238000007906 compression Methods 0.000 description 1
- 238000007405 data analysis Methods 0.000 description 1
- 230000007850 degeneration Effects 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 230000001788 irregular Effects 0.000 description 1
- 238000013507 mapping Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000009877 rendering Methods 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/22—Indexing; Data structures therefor; Storage structures
- G06F16/2228—Indexing structures
- G06F16/2246—Trees, e.g. B+trees
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/29—Geographical information databases
Landscapes
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Databases & Information Systems (AREA)
- Data Mining & Analysis (AREA)
- Physics & Mathematics (AREA)
- General Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Remote Sensing (AREA)
- Software Systems (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
本发明提供了一种大尺度日地空间的太阳风数据剖分、编码及存取方法,所述方法包含:接收三维太阳风模型输出的原始的太阳风数据;将黄道面或子午面用PDQG‑R格网进行划分,从而自动构建相应分辨率等级的PDQG‑R格网,其中所述PDQG‑R格网为:当径向剖分层次大于经向剖分层次时,在PDQG格网的基础上继续在径向进行独立细分;将PDQG‑R格网进行编码,即将每个剖分后的子网格给予唯一的标识,使得网格的坐标和编码形成一一对应的关联关系;计算每个PDQG‑R网格的中心点坐标;依据计算得到的PDQG‑R网格的中心点的坐标,将原始的太阳风数据放入PDQG‑R格网中,当原始数据匹配到一个PDQG‑R网格之后,则将原始的太阳风数据的属性值赋给该网格中心点。
The present invention provides a solar wind data subdivision, coding and access method in large-scale solar-terrestrial space. The method includes: receiving the original solar wind data output by a three-dimensional solar wind model; The PDQG-R grid of the corresponding resolution level is automatically constructed, wherein the PDQG-R grid is: when the radial subdivision level is greater than the meridional subdivision level, continue on the basis of the PDQG grid Carry out independent subdivision in the radial direction; code the PDQG-R grid, that is, give each divided sub-grid a unique identifier, so that the coordinates and codes of the grid form a one-to-one correspondence; calculate each Coordinates of the center point of the PDQG‑R grid; according to the calculated coordinates of the center point of the PDQG‑R grid, put the original solar wind data into the PDQG‑R grid, when the original data matches a PDQG‑R grid After that, the attribute value of the original solar wind data is assigned to the grid center point.
Description
技术领域technical field
本发明涉及日地空间物理场海量数据的快速组织领域,具体涉及一种大尺度日地空间的太阳风数据剖分、编码及存取方法。The invention relates to the field of rapid organization of mass data of solar-terrestrial space physical fields, in particular to a method for segmenting, encoding and accessing solar wind data in large-scale solar-terrestrial space.
背景技术Background technique
地理信息系统的发展,特别是数字地球技术的发展,使地球科学的研究有了强有力的数据组织和管理手段。而面对快速发展的空间科学,随着空间探测数据的海量增长,如何对其太阳系内探测数据进行组织和管理,如何提高数据存取效率和数据的可视化效果,成为摆在空间科学家面前迫切需要解决的问题,具有重要理论研究意义和广泛的应用前景。The development of geographic information system, especially the development of digital earth technology, has enabled the research of earth science to have a powerful means of data organization and management. In the face of the rapid development of space science, with the massive growth of space detection data, how to organize and manage the detection data in the solar system, how to improve the efficiency of data access and data visualization, has become an urgent need for space scientists. The problems solved have important theoretical research significance and broad application prospects.
由于目前尚未有实际探测的太阳风数据,则本发明采用的是我国空间天气学国家重点实验室SIGMA研究小组开发的太阳行星际守恒元解元(SIP-CESE)三维太阳风模型输出的数据,为今后太阳风的实际探测数据的组织、管理、分析提供技术支持。Since there is no actual solar wind data of actual detection at present, what the present invention adopts is the data output by the solar interplanetary conservation element solution element (SIP-CESE) three-dimensional solar wind model developed by the SIGMA research group of the State Key Laboratory of Space Weather in my country. Provide technical support for the organization, management, and analysis of the actual detection data of the solar wind.
整个太阳系空间庞大无比,太阳风数据量大的惊人,为提高海量数据的检索和存取速度,需要构建二维剖分模型,生成不同的分辨率等级的数据,从而提高整个太阳系球体空间的数据组织效率,从而达到对海量数据进行快速甚至实时渲染的目的。The space of the entire solar system is huge, and the amount of solar wind data is astonishingly large. In order to improve the retrieval and access speed of massive data, it is necessary to build a two-dimensional subdivision model and generate data of different resolution levels, thereby improving the data organization of the spherical space of the entire solar system Efficiency, so as to achieve the purpose of fast and even real-time rendering of massive data.
目前,有三种典型的二维空间剖分模型,分别是经纬度剖分模型、正多面体剖分模型和Voronoi球面自适应格网模型。At present, there are three typical two-dimensional space subdivision models, namely latitude and longitude subdivision model, regular polyhedron subdivision model and Voronoi spherical adaptive grid model.
要应用到太阳风的剖分中,可以排除多面体剖分模型和自适应格网模型,多面体模型的坐标计算相对比较复杂,组织形式与现有的测绘、遥感数据不同,集成起来困难,自适应剖分模型是单一比例尺的剖分,难以与多分辨率结合起来。To be applied to the subdivision of the solar wind, the polyhedral subdivision model and the adaptive grid model can be excluded. The coordinate calculation of the polyhedral model is relatively complicated, and the organization form is different from the existing surveying and mapping and remote sensing data, so it is difficult to integrate. The sub-model is a subdivision of a single scale, which is difficult to combine with multi-resolution.
发明内容Contents of the invention
本发明的目的在于,为克服上述问题,本发明提供一种大尺度日地空间的太阳风数据剖分、编码及存取方法。The object of the present invention is to provide a method for segmenting, encoding and accessing solar wind data in large-scale solar-terrestrial space in order to overcome the above-mentioned problems.
为实现上述目的,本发明提供一种大尺度日地空间的太阳风数据剖分、编码及存取方法,所述方法包含:In order to achieve the above purpose, the present invention provides a method for segmenting, encoding and accessing solar wind data in large-scale solar-terrestrial space. The method includes:
步骤101)接收三维太阳风模型输出的原始的太阳风数据;Step 101) receiving the original solar wind data output by the three-dimensional solar wind model;
步骤102)将黄道面或子午面用PDQG-R格网进行剖分,根据需求设置要剖分的LOD等级,从而自动构建相应分辨率等级的PDQG-R格网,其中所述PDQG-R格网为:当径向剖分层次大于经向剖分层次时,在PDQG格网的基础上继续在径向进行独立细分;Step 102) subdivide the ecliptic plane or the meridian plane with the PDQG-R grid, and set the LOD level to be subdivided according to the requirements, thereby automatically constructing the PDQG-R grid of the corresponding resolution level, wherein the PDQG-R grid Grid: when the radial subdivision level is greater than the meridional subdivision level, continue to subdivide independently in the radial direction on the basis of the PDQG grid;
步骤103)将PDQG-R格网进行编码,即将每个剖分后的子网格给予唯一的标识,使得网格的坐标和编码形成一一对应的关联关系;Step 103) Coding the PDQG-R grid, that is, giving each divided sub-grid a unique identifier, so that the coordinates of the grid and the coding form a one-to-one correspondence;
步骤104)计算每个PDQG-R网格的中心点对应的坐标位置,所述坐标位置表示为:(纬度、经度、半径);Step 104) calculate the coordinate position corresponding to the center point of each PDQG-R grid, and the coordinate position is expressed as: (latitude, longitude, radius);
步骤105)依据步骤104)计算得到的PDQG-R网格的中心点的坐标,将原始的太阳风数据放入PDQG-R格网中,当原始数据匹配到一个PDQG-R网格之后,则将原始的太阳风数据的属性值赋给该网格中心点;Step 105) According to the coordinates of the center point of the PDQG-R grid calculated in step 104), the original solar wind data is put into the PDQG-R grid, and when the original data is matched to a PDQG-R grid, the The attribute value of the original solar wind data is assigned to the center point of the grid;
步骤106)step 106)
基于步骤103)的网格编码检索原始的太阳风数据,即查找该编码对应的网格位置,并将该网格内放置的内容提取出来;用于多分辨率数据的可视化显示,给出不同分辨率等级的数据的直观显示。Based on the grid code in step 103), the original solar wind data is retrieved, that is, the grid position corresponding to the code is searched, and the content placed in the grid is extracted; it is used for the visual display of multi-resolution data, and different resolutions are given. Visual display of rate-level data.
可选的,上述步骤102)进一步包含:Optionally, the above step 102) further includes:
步骤102-1)将黄道面进行PDQG格网的剖分,具体步骤如下:Step 102-1) Subdividing the ecliptic plane into a PDQG grid, the specific steps are as follows:
步骤102-1-1)将黄道面一分为四,每部分是经度范围是0°~90°且半径范围约为1AU(日地平均距离)的四分之一圆面;Step 102-1-1) Dividing the ecliptic plane into four parts, each part is a quarter circle with a longitude range of 0° to 90° and a radius of about 1AU (average distance between the sun and the earth);
步骤102-1-2)用PDQG格网对每个四分圆面进行递归细分,第1次剖分,即取四分圆面上的三条边的中点,得到3个新点;将四分圆两腰上的2个新点连成一条纬线,再将该纬线的中点与另一新点连成一条径线,形成1个新的子四分圆和2个子四边形;Step 102-1-2) Use the PDQG grid to recursively subdivide each quadrant face, and for the first subdivision, take the midpoints of the three sides on the quadrant face to obtain 3 new points; Two new points on the two waists of the quadrant are connected to form a parallel, and then the midpoint of the parallel and another new point are connected to form a radial line to form a new sub-quadrant and two sub-quadrilaterals;
步骤102-1-3)第2次剖分,则是对第1次产生的两种类型子网格的递归细分;对子三角形按第一次剖分的方法进行剖分即可,而对于子四边形剖分,则可用四叉树法取四条边的中点得到4个新点,将两腰上的中点和圆心用同心圆弧线连接,将两纬线的中点直接连直线,则又得到4个新的子四边形,进而就产生1个新的子三角形和10个四边形,实现对四分圆面更高分辨率的细分;Step 102-1-3) The second subdivision is the recursive subdivision of the two types of sub-grids generated for the first time; the sub-triangles can be subdivided according to the first subdivision method, and For the sub-quadrangle subdivision, the quadtree method can be used to get the midpoints of the four sides to obtain 4 new points, connect the midpoints on the two waists with the center of the circle with concentric arcs, and directly connect the midpoints of the two latitude lines to a straight line, Then get 4 new sub-quadrilaterals, and then generate 1 new sub-triangle and 10 quadrilaterals to achieve higher resolution subdivision of the quadrangular surface;
步骤102-1-4)重复步骤102-1-3),直到分辨率满足设定的要求;Step 102-1-4) Repeat step 102-1-3) until the resolution meets the set requirements;
步骤102-1-5)当径向分辨率大于经向分辨率时,即径向剖分层次大于经向剖分层次时,在PDQG格网的基础上继续在径向独立细分,得到PDQG-R格网。Step 102-1-5) When the radial resolution is greater than the meridional resolution, that is, when the radial subdivision level is greater than the meridional subdivision level, continue to subdivide independently in the radial direction on the basis of the PDQG grid to obtain PDQG -R grid.
进一步可选的,上述步骤103)PDQG-R格网的具体编码为:Further optionally, the specific coding of the above step 103) PDQG-R grid is:
步骤103-1)首先将一分为四的黄道面按照逆时针编号0、1、2、3,依次确定了每个四分圆面所在的象限;Step 103-1) First, the ecliptic plane divided into four is numbered 0, 1, 2, and 3 counterclockwise, and the quadrants in which each quadrant is located are sequentially determined;
步骤103-2)第1次剖分后,对于每一个四分圆面,外侧两个四边形按照逆时针依次编码为2、3,中心三角形编码为0;Step 103-2) After the first subdivision, for each quadrant, the outer two quadrilaterals are coded as 2 and 3 in counterclockwise order, and the central triangle is coded as 0;
步骤103-3)第2次剖分后,中心三角形编码与第1次剖分单元的编码方法相同,子四边形编码左下、左上分别为0、1,右下、右上分别为2、3,依此类推,并且剖分层次每增加1层,编码相应增加一位;Step 103-3) After the second subdivision, the coding method of the central triangle is the same as that of the first subdivision unit. The lower left and upper left subquadrons are coded as 0 and 1 respectively, and the lower right and upper right are respectively 2 and 3. By analogy, and every time the subdivision level increases by 1 layer, the code will increase by one bit;
步骤103-4)在径向上,每个PDQG格网都要经过径向3次剖分,1分为8,则任意一个格网在其本身编码后加上附加码,进而标识经过径向细分后格网具体位置;Step 103-4) In the radial direction, each PDQG grid has to be subdivided three times in the radial direction, and 1 is divided into 8, then any grid is coded with an additional code after its own code, and then it is identified that the grid has been subdivided in the radial direction. The specific position of the grid after division;
其中,从圆心往外的编号依次用0、1表示,第1次细分用0、1标识,第2次细分,依次用00、01、10、11表示,第3次细分依次用000、001、010、011、100、101、110、111表示;Among them, the numbers from the center of the circle to the outside are represented by 0 and 1 in sequence, the first subdivision is marked by 0 and 1, the second subdivision is represented by 00, 01, 10, 11 in sequence, and the third subdivision is sequentially represented by 000 , 001, 010, 011, 100, 101, 110, 111 means;
步骤103-5)分割线后面的位数标识半径细分位,其余Morton码的每位数字都是不大于3的四进制数,相应的Morton码位数越长可表示为:Step 103-5) the number of digits behind the dividing line identifies the subdivision of the radius, and every digit of the remaining Morton codes is a quaternary number not greater than 3, and the corresponding Morton code digits are longer and can be expressed as:
Morton=q1q2q3…qnqn+1—pMorton=q 1 q 2 q 3 ...q n q n+1 —p
其中,q1是四分体象限标识位,“—”是分隔符,p是PDQG格网基础上在径向3次细分后的径向区分标识位。Among them, q 1 is the tetrad quadrant identification bit, "—" is the separator, and p is the radial distinguishing identification bit after three radial subdivisions based on the PDQG grid.
可选的,上述步骤105)进一步包含:Optionally, the above step 105) further includes:
步骤105-1)从原始数据出发,先判断半径,找到所在的网格对应的半径层;在基于网格半径层,匹配经度范围;具体为:Step 105-1) Starting from the original data, first judge the radius, and find the radius layer corresponding to the grid; in the grid-based radius layer, match the longitude range; specifically:
a)网格中心点的半径与原始采样点的半径之差小于该网格半径跨度的一半;a) The difference between the radius of the grid center point and the radius of the original sampling point is less than half of the grid radius span;
b)网格中心点的经度与原始采样点的经度之差小于该网格经度跨度的一半b) The difference between the longitude of the grid center point and the longitude of the original sampling point is less than half of the longitude span of the grid
若同时满足以上两个条件,则找到原始数据对应的网格;If the above two conditions are met at the same time, find the grid corresponding to the original data;
步骤105-2)匹配到网格之后,则将原始数据的属性值赋给该网格中心点,循环所有的原始数据,将所有原始数据一一映射到PDQG-R网格中。Step 105-2) After matching to the grid, assign the attribute value of the original data to the center point of the grid, cycle all the original data, and map all the original data to the PDQG-R grid one by one.
可选的,上述步骤106)进一步包含:Optionally, the above step 106) further includes:
步骤106-1)对接收的网格编码进行解码,推算编码对应的格网格坐标位置;Step 106-1) Decode the received grid code, and calculate the grid coordinate position corresponding to the code;
步骤106-2)根据编码,从剖分得到的网格中提取对应的数据。Step 106-2) According to the code, extract the corresponding data from the divided grid.
由于网格编码,已经使得每个网格都有唯一的标识,而每个网格又有唯一的坐标,因此从网格编码则可以直接计算出网格坐标,同时也可以检索出该网格中存放了哪些属性数据。Due to the grid code, each grid has a unique identifier, and each grid has a unique coordinate, so the grid coordinates can be directly calculated from the grid code, and the grid can also be retrieved Which attribute data is stored in .
上述本发明使用的数据是由三维太阳风模型(我国空间天气学国家重点实验室SIGMA研究小组开发的太阳行星际守恒元解元(SIP-CESE)三维太阳风模型)输出的数据,该数据是在极坐标下的,三个坐标轴分别是纬度、经度、半径。该太阳风数据具有不规则采样的特点,在以太阳为中心的球体采样空间中,纬度范围是-90°~90°,采样55次,经度范围是0~360°,采样80次,径向采样范围是大约1AU(天文单位,日地平均距离,1AU=149597870.691km),采样154次。The above-mentioned data used in the present invention is the data output by a three-dimensional solar wind model (the solar interplanetary conservation element solution element (SIP-CESE) three-dimensional solar wind model developed by my country's State Key Laboratory of Space Weather Science SIGMA research group). Under coordinates, the three coordinate axes are latitude, longitude, and radius. The solar wind data has the characteristics of irregular sampling. In the sampling space of a sphere centered on the sun, the latitude range is -90° to 90°, and the sampling time is 55 times. The longitude range is 0 to 360°, and the sampling time is 80 times, radial sampling The range is about 1AU (astronomical unit, the mean distance between the sun and the earth, 1AU=149597870.691km), and 154 samples are taken.
与现有技术相比,本发明的技术优势在于:Compared with prior art, the technical advantage of the present invention is:
由于普通经纬格网在两极经纬线密集,两极与赤经上所分的格网的比例不收敛,从而导致格网绘制效果变形严重。为解决此问题,本发明引入退化四叉树剖分思想,针对黄道面和子午面两种典型平面,根据太阳风数据特点,提出了一种新的PDQG-R格网模型,并针对该格网模型提出了相应的编码方案。Due to the dense latitude and longitude lines at the two poles of the ordinary latitude and longitude grid, the ratio of the grid divided by the two poles and the right ascension does not converge, resulting in serious deformation of the grid drawing effect. In order to solve this problem, the present invention introduces the idea of degenerate quadtree subdivision, and proposes a new PDQG-R grid model for the two typical planes of the ecliptic plane and the meridian plane, according to the characteristics of solar wind data, and for the grid The model proposes a corresponding encoding scheme.
该剖分模型不仅很好地解决了太阳质心附近格网过密的问题,还可以满足径向分辨率与经(纬)向分辨率不同步的需求。而且能提供多种分辨率层次的数据,显著地提高了数据检索效率,适用于太阳风不规则采样数据的剖分。This subdivision model not only solves the problem of too dense grid near the sun's barycenter, but also meets the requirement that the radial resolution is not synchronized with the longitude (latitude) resolution. Moreover, it can provide data of multiple resolution levels, which significantly improves the efficiency of data retrieval, and is suitable for the subdivision of irregularly sampled data of the solar wind.
附图说明Description of drawings
图1-a是本发明提供的太阳风数据剖分流程图;Fig. 1-a is the flow chart of splitting solar wind data provided by the present invention;
图1-b是本发明提供的太阳风数据可视化流程图;Fig. 1-b is the flow chart of solar wind data visualization provided by the present invention;
图2是黄道面示意图;Figure 2 is a schematic diagram of the ecliptic plane;
图3是子午面示意图;Figure 3 is a schematic diagram of the meridian plane;
图4是PDQG格网三次细分示意图;Figure 4 is a schematic diagram of the three subdivisions of the PDQG grid;
图5是PDQG-R格网饿3次剖分示意图;Fig. 5 is a schematic diagram of the three subdivisions of the PDQG-R grid;
图6是四分圆面编码示意图;Fig. 6 is a schematic diagram of quadrant coding;
图7是PDQG格网编码示意图;Fig. 7 is a schematic diagram of PDQG grid coding;
图8是径向3次剖分示意图。Fig. 8 is a schematic diagram of three divisions in the radial direction.
具体实施方式detailed description
下面结合附图和实施例对本发明所述方法进行详细说明。The method of the present invention will be described in detail below in conjunction with the accompanying drawings and embodiments.
在以太阳为中心的日地空间,为了研究磁场、温度和抛出粒子密度随着距日心的距离远近的变化情况,以及在这个平面数据的变化情况,需要对过太阳质心的两种典型切平面(即黄道面、子午面)构建平面网格剖分模型,将数据划分成不同的分辨率层次,并且对网格进行编码,从而实现巨大圆形平面的数据组织,进而提高海量数据的存取效率。In the solar-terrestrial space with the sun as the center, in order to study the changes of the magnetic field, temperature and density of ejected particles with the distance from the heliocenter, as well as the change of data on this plane, it is necessary to compare two typical The tangent plane (ie ecliptic plane, meridian plane) constructs a plane grid subdivision model, divides the data into different resolution levels, and encodes the grid, so as to realize the data organization of a huge circular plane, thereby improving the quality of massive data. access efficiency.
本发明支持海量、大尺度日地空间的太阳风数据的快速组织,在太阳风二维空间的剖分模型的基础上,建立金字塔模型,能提供不同分辨率等级的数据,用户在使用时可以根据自身需求选择合适分辨率的数据。The invention supports the rapid organization of massive and large-scale solar wind data in the solar-terrestrial space. On the basis of the subdivision model of the two-dimensional space of the solar wind, a pyramid model is established, which can provide data of different resolution levels. Users can use it according to their own It is necessary to select the data with appropriate resolution.
本专利的主要功能包括:The main functions of this patent include:
1.基于太阳风的二维空间剖分模型1. Two-dimensional space subdivision model based on solar wind
为研究过太阳中心的平面上太阳风数据的分布特征,针对黄道面和子午面两种平面的空间剖分,针对巨大的圆形平面,提出一种新的PDQG-R模型,即径向细分的平面退化四叉树网格剖分模型,该剖分模型不仅解决了球心处网格过密的问题,还能满足径向分辨率大于经(纬)向分辨率的需求。In order to study the distribution characteristics of solar wind data on the plane that has passed the center of the sun, a new PDQG-R model is proposed for the spatial division of the ecliptic plane and the meridian plane, and for the huge circular plane, that is, the radial subdivision The planar degenerate quadtree meshing model, which not only solves the problem of too dense mesh at the center of the sphere, but also meets the requirement that the radial resolution is greater than the longitude (latitudinal) resolution.
2.剖分模型对应的编码方案2. The coding scheme corresponding to the subdivision model
针对PDQG-R格网,用改进的退化Z曲线进行编码,提出对应的编码方案,For the PDQG-R grid, the improved degenerate Z curve is used for encoding, and the corresponding encoding scheme is proposed.
Morton=q1q2q3…qnqn+1—pMorton=q 1 q 2 q 3 ...q n q n+1 —p
其中,q1是四分体象限标识位,“—”是分隔符,p是PDQG格网基础上在径向3次细分后的径向区分标识位。Among them, q 1 is the tetrad quadrant identification bit, "—" is the separator, and p is the radial distinguishing identification bit after three radial subdivisions based on the PDQG grid.
通过对5次剖分后的网格数量进行统计,对比如下:By counting the number of grids after 5 subdivisions, the comparison is as follows:
可归纳为,当剖分层次为n时,四分之一圆面剖分生成的格网个数即为num,则满足如下公式:It can be summarized that when the subdivision level is n, the number of grids generated by quarter-circle subdivision is num, and the following formula is satisfied:
即num=1+21+…+22n-1n≥1That is, num=1+2 1 +...+2 2n-1 n≥1
即 which is
而普通的经纬模型的格网个数为num=4n(n>0),则可以计算出PDQG格网数压缩极限为 While the number of grids in the common latitude and longitude model is num=4 n (n>0), it can be calculated that the PDQG grid number compression limit is
当用传统经纬格网剖分时,格网数量以22速度增长。经过退化之后球心处数量明显减少,球心与外围的网格大小比例缩小。有效地改善了日心处格网过密的缺点,使得格网大小趋于均匀化。When the traditional latitude and longitude grid is used for subdivision, the number of grids increases at a rate of 2 2 . After the degeneration, the number at the center of the ball is significantly reduced, and the ratio of the grid size between the center and the periphery is reduced. It effectively improves the shortcoming of too dense grid at the center of the sun, making the grid size tend to be uniform.
在PDQG格网的基础上,为了满足径向分辨率比经(纬)向要大的需求,则在径向继续细分,形成PDQG-R格网,既能保留PDQG格网的优点,球心处网格不至于过密,又能最大的保留径向的数据特点。On the basis of the PDQG grid, in order to meet the requirement that the radial resolution is larger than that of the longitude (latitude) direction, it is further subdivided in the radial direction to form a PDQG-R grid, which can not only retain the advantages of the PDQG grid, The grid at the center is not too dense, and the radial data characteristics can be preserved to the greatest extent.
实施例Example
下面以黄道面为例,以某一时刻太阳风模型输出的粒子密度数据为例,详细说明剖分、编码、检索的步骤。Taking the ecliptic plane as an example and the particle density data output by the solar wind model at a certain moment as an example, the steps of subdivision, encoding, and retrieval are described in detail.
步骤101)接收三维太阳风模型输出的数据,并提取出黄道面的数据;Step 101) receiving the output data of the three-dimensional solar wind model, and extracting the data of the ecliptic plane;
步骤102)将黄道面用PDQG-R格网进行划分,根据需求设置要剖分的LOD等级,从而自动构建相应分辨率等级的PDQG-R格网,所述PDQG-R格网为:Step 102) Divide the ecliptic plane with PDQG-R grid, set the LOD level to be divided according to requirements, thereby automatically constructing the PDQG-R grid of corresponding resolution level, the PDQG-R grid is:
PDQG格网是指平面退化四叉树格网模型(Plane Degenerated Quadtree Grid),它引入退化四叉树的思想,结合普通经纬格网,形成的更高质量的格网模型。为了解决两维度分辨率不一致的问题,当径向剖分层次大于经向剖分层次时,在PDQG格网的基础上继续在径向进行独立细分,以解决径向分辨率与经向分辨率不同步的问题,即PDQG-R格网。PDQG grid refers to the plane degenerated quadtree grid model (Plane Degenerated Quadtree Grid), which introduces the idea of degenerated quadtree and combines with ordinary latitude and longitude grids to form a higher quality grid model. In order to solve the problem of inconsistency in two-dimensional resolution, when the radial subdivision level is greater than the meridional subdivision level, continue to subdivide independently in the radial direction on the basis of the PDQG grid to solve the problem of radial resolution and meridional resolution. The problem of rate desynchronization, that is, the PDQG-R grid.
下面太阳黄道面为例,先介绍PDQG格网的剖分方法,拟采用的剖分方法步骤如下:Let’s take the solar ecliptic plane as an example, first introduce the subdivision method of the PDQG grid, and the steps of the subdivision method to be used are as follows:
1)首先,将黄道面一分为四,每部分是经度范围是0°~90°、半径范围约为1AU的四分之一圆面如图2所示。1) First, the ecliptic plane is divided into four parts, each part is a quarter circle with a longitude range of 0°-90° and a radius range of about 1AU, as shown in Figure 2.
2)用PDQG格网对每个四分圆面进行递归细分,第1次剖分,即取四分圆面上的三条边的中点,得到3个新点,将四分圆两腰上的2个新点连成一条纬线,再将该纬线的中点与另一新点连成一条径线,形成1个新的子四分圆(可近似认为是三角形)和2个子四边形,详细见图4,其中,实线代表的是第1次剖分的结果。2) Use the PDQG grid to recursively subdivide each quadrant face. For the first subdivision, take the midpoints of the three sides on the quadrant face to obtain 3 new points, and divide the quarter circle two waists 2 new points on the above are connected into a latitude line, and then the midpoint of the latitude line is connected with another new point to form a radial line, forming a new sub-quadrant circle (which can be approximately considered as a triangle) and 2 sub-quadrilaterals, See Figure 4 for details, where the solid line represents the result of the first division.
3)第2次剖分,则是对第1次产生的两种类型子网格的递归细分。对子三角形按第一次剖分的方法进行剖分即可,而对于子四边形剖分,则可用普通的四叉树法,取四条边的中点,得到4个新点,将两腰上的中点和圆心用同心圆弧线连接,将两纬线的中点直接连直线,则又得到4个新的子四边形,这样就产生1个新的子三角形和10(即2+4+4)个四边形,实现对四分圆面更高分辨率的细分。图4点划线代表的是第2次剖分。3) The second subdivision is the recursive subdivision of the two types of sub-grids generated in the first time. Sub-triangles can be subdivided according to the first subdivision method, and for subquadrangle subdivision, the ordinary quadtree method can be used to obtain 4 new points from the midpoints of the four sides, and the two waists The midpoint and the center of the circle are connected by concentric circular arcs, and the midpoints of the two latitudes are directly connected with a straight line, and then 4 new sub-quadrilaterals are obtained, thus producing 1 new sub-triangle and 10 (that is, 2+4+4 ) quadrilaterals to achieve a higher resolution subdivision of the quadrant. The dotted line in Figure 4 represents the second subdivision.
4)重复步骤3,直到分辨率满足要求。其中,图4虚线代表的是第3次剖分的结果。4) Repeat step 3 until the resolution meets the requirements. Among them, the dotted line in Figure 4 represents the result of the third division.
为了解决两维度分辨率不一致的问题,主要是径向分辨率大于经向分辨率时,即径向剖分层次大于经向剖分层次时,可以考虑在PDQG格网的基础上继续在径向独立细分,以满足径向分辨率与经向分辨率不同步的需求。因此,在此提出PDQG-R格网。In order to solve the problem of inconsistency in two-dimensional resolution, mainly when the radial resolution is greater than the meridional resolution, that is, when the radial subdivision level is greater than the meridional subdivision level, it can be considered to continue on the basis of the PDQG grid. Independent subdivision to meet the needs of radial resolution and meridional resolution not synchronized. Therefore, the PDQG-R grid is proposed here.
由于四分圆面数据维度是25*28,可以看出径向采样密度是经向的23倍。所以,在PDQG的基础上继续在径向进行3次细分即可达到分辨率要求,如图5所示。Since the data dimension of the quadrant is 2 5 *2 8 , it can be seen that the sampling density in the radial direction is 2 3 times that in the meridional direction. Therefore, on the basis of PDQG, continue to subdivide three times in the radial direction to meet the resolution requirement, as shown in Figure 5.
图5中是在PDQG格网3次剖分的基础上,对某一个网格在径向3次细分的示意图,其中,实线是径向第1次细分,点划线是径向第2次细分,虚线是径向第3次细分。由此,一个PDQG网格则变成8个子网格。于是,PDQG-R格网生成了。Figure 5 is a schematic diagram of a certain grid subdivided three times in the radial direction based on the three subdivisions of the PDQG grid. The solid line is the first subdivision in the radial direction, and the dashed line is the radial The second subdivision, the dotted line is the third radial subdivision. Thus, a PDQG grid becomes 8 sub-grids. Thus, the PDQG-R grid was generated.
每一个层次上的PDQG-R格网都是在对应层次的PDQG格网基础上生成的,其中径向细分的次数也可以根据需要改变,当径向细分次数为0时,即是PDQG格网。The PDQG-R grid at each level is generated on the basis of the PDQG grid at the corresponding level, and the number of radial subdivisions can also be changed as needed. When the number of radial subdivisions is 0, it is PDQG grid.
该步骤是将黄道面、子午面的巨大圆形平面划分成不同分辨率等级的小网格,以便于该平面的太阳风数据的组织和管理。可以用于处理实际探测的数据,也可以是模型输出的太阳风数据。This step is to divide the huge circular plane of the ecliptic plane and the meridian plane into small grids of different resolution levels, so as to facilitate the organization and management of the solar wind data of this plane. It can be used to process the actual detection data, or the solar wind data output by the model.
步骤103)将PDQG-R格网进行编码,所述编码方式为:Step 103) encode the PDQG-R grid, the encoding method is:
该编码是要将每个剖分后的子网格给予唯一的标识,使得网格中的坐标、属性数据和编码形成一一对应的关联关系,为了进行高效的数据索引,PDQG-R格网的具体编码规则如下:The code is to give each divided sub-grid a unique identifier, so that the coordinates, attribute data and codes in the grid form a one-to-one correspondence relationship. In order to perform efficient data indexing, the PDQG-R grid The specific encoding rules are as follows:
1)首先将一分为四的黄道面按照逆时针编号0、1、2、3,依次确定了每个四分圆面所在的象限。1) First, the ecliptic plane divided into four is numbered 0, 1, 2, and 3 counterclockwise, and the quadrants of each quadrant are sequentially determined.
2)第1次剖分后,对于每一个四分圆面,外侧两个四边形按照逆时针依次编码为2、3,中心三角形编码为0,可以认为是0、1合并形成0,如图7a。2) After the first subdivision, for each quadrangular surface, the outer two quadrilaterals are coded as 2 and 3 in counterclockwise order, and the central triangle is coded as 0, which can be considered as 0 and 1 combined to form 0, as shown in Figure 7a .
3)第2次剖分后,中心三角形编码与第1次剖分单元的编码方法相同,子四边形编码左下、左上分别为0、1,右下、右上分别为2、3,依此类推。并且,剖分层次每增加1层,编码相应增加一位。3) After the second subdivision, the coding method of the central triangle is the same as that of the first subdivision unit. The lower left and upper left subquadrons are coded as 0 and 1, respectively, and the lower right and upper right are 2 and 3, respectively, and so on. And, every time the subdivision layer increases by one layer, the code increases by one bit accordingly.
4)在径向上,每个PDQG格网都要经过径向3次剖分,1分为8,则任意一个格网可以在其本身编码后加上附加码,来标识经过径向细分后格网具体位置,如图8中编号为010的格网是经过PDQG-R剖分后生成的8个子网格之一。可以在本身编码后用分割线分开,后面的位数标识半径细分位,用二进制码表示,1位代表细分1次,2位代表细分2次,并且每经过一次细分,编码增加一位,剖分的次数越多,所得子区域越小。4) In the radial direction, each PDQG grid has to be subdivided three times in the radial direction, and 1 is divided into 8, then any grid can add an additional code after its own code to identify the radial subdivision The specific location of the grid, the grid numbered 010 in Figure 8 is one of the eight sub-grids generated after PDQG-R subdivision. It can be separated by a dividing line after encoding itself, and the following digits identify the subdivision of the radius, expressed in binary code, 1 digit represents 1 subdivision, 2 digits represent 2 subdivisions, and each time subdivision, the code increases One bit, the more times of subdivision, the smaller the obtained sub-region.
从圆心往外的编号依次用0、1表示,第1次细分用0、1标识,第2次细分,依次用00、01、10、11表示,第3次细分依次用000、001、010、011、100、101、110、111表示。可以根据编码位数确定径向细分的次数,并且编码是动态的,不但具有遗传性,且能与多分辨率层次很好地结合起来。The numbers from the center of the circle to the outside are represented by 0 and 1 in sequence, the first subdivision is marked by 0 and 1, the second subdivision is represented by 00, 01, 10, 11 in sequence, and the third subdivision is represented by 000 and 001 in sequence , 010, 011, 100, 101, 110, 111 said. The number of radial subdivisions can be determined according to the number of coding bits, and the coding is dynamic, not only hereditary, but also well combined with multi-resolution levels.
5)分割线后面的位数标识半径细分位,是二进制码,其余Morton码的每位数字都是不大于3的四进制数,相应的Morton码位数越长,可表示为:5) The number of digits behind the dividing line identifies the subdivision of the radius, which is a binary code, and each digit of the remaining Morton codes is a quaternary number not greater than 3. The longer the corresponding Morton code digits, it can be expressed as:
Morton=q1q2q3…qnqn+1—pMorton=q 1 q 2 q 3 ...q n q n+1 —p
其中,q1是四分体象限标识位,“—”是分隔符,p是PDQG格网基础上在径向3次细分后的径向区分标识位。Among them, q 1 is the tetrad quadrant identification bit, "—" is the separator, and p is the radial distinguishing identification bit after three radial subdivisions based on the PDQG grid.
该步骤是给每个网格编码,从而网格中的数据也与编码对应起来,从而支持数据检索,支持数据组织,为后面的数据应用乃至数据分析都提供了支持。This step is to code each grid, so that the data in the grid corresponds to the code, so as to support data retrieval, support data organization, and provide support for subsequent data applications and even data analysis.
步骤104)计算每个PDQG-R网格的中心点对应的坐标位置(半径、纬度、经度)(radius,latitude,longitude),下面是[0,pi/2]范围内,坐标的计算方式,其他象限的依此类推。Step 104) Calculate the coordinate position (radius, latitude, longitude) (radius, latitude, longitude) corresponding to the center point of each PDQG-R grid, the following is the calculation method of coordinates in the range of [0, pi/2], And so on for the other quadrants.
Radius=maxradius*2^(-lod)*(i-1)+maxradius*2^(-lod-1)Radius=maxradius*2^(-lod)*(i-1)+maxradius*2^(-lod-1)
lontitude=0.25*pi/lon_num(i)+(0.5*pi/lon_num(i))*(j-1)lontitude=0.25*pi/lon_num(i)+(0.5*pi/lon_num(i))*(j-1)
Latitude=0Latitude=0
其中,maxradius是黄道面最大半径,lod是设置的剖分等级lod值,lon_num(i)是径向第i层所划分的网格的个数,j是指第i层的第j个网格。Among them, maxradius is the maximum radius of the ecliptic plane, lod is the lod value of the subdivision level set, lon_num(i) is the number of grids divided by the i-th layer in the radial direction, and j refers to the j-th grid of the i-th layer .
步骤105)将原始数据放入PDQG-R格网中,即计算网格的属性值:Step 105) Put the original data into the PDQG-R grid, that is, calculate the attribute value of the grid:
对原始数据中每一个数据的坐标和PDQG-R格网的中心坐标对比,将原始数据放入离自己最近的格网中,即每个数据只放入离自己最近的一个格网中。这样可能导致的结果有:有的网格只有一个数据;有的网格可能有多个数据,可以根据某种合适的算法最后计算出该网格的属性值;有的网格没有数据,则置空即可,以保证数据的完整性和一致性。Comparing the coordinates of each data in the original data with the central coordinates of the PDQG-R grid, put the original data into the nearest grid, that is, each data is only placed in the nearest grid. The possible results of this are: some grids have only one data; some grids may have multiple data, and the attribute value of the grid can be finally calculated according to a certain suitable algorithm; Just leave it empty to ensure data integrity and consistency.
1)从原始数据出发,先判断半径,找到所在的网格半径层,在基于该层,去匹配的经度范围,满足的条件是:1) Starting from the original data, first judge the radius, find the grid radius layer where it is located, and based on this layer, to match the longitude range, the conditions to be satisfied are:
a)网格中心点的半径与原始采样点的半径之差小于该网格半径跨度的一半;a) The difference between the radius of the grid center point and the radius of the original sampling point is less than half of the grid radius span;
b)网格中心点的经度与原始采样点的经度之差小于该网格经度跨度的一半。b) The difference between the longitude of the grid center point and the longitude of the original sampling point is less than half of the longitude span of the grid.
若两者同时满足,则找到该原始数据对应的网格。If both are satisfied at the same time, find the grid corresponding to the original data.
2)匹配到网格之后,则将原始数据的属性值赋给该网格。循环所有的原始数据,将所有原始数据映射到PDQG-R网格中。2) After matching to the grid, the attribute value of the original data is assigned to the grid. Loop through all raw data and map all raw data into a PDQG-R grid.
以数据为例(L,B,R,den)(3.673205e-068.246700e-014.732900e+07Take the data as an example (L, B, R, den) (3.673205e-068.246700e-014.732900e+07
3.585800e-10),单位分别为(弧度,弧度,千米),以采样数据最远距离0.15391E+09km为半径作为空间剖分的基础,以该范围进行递归剖分。(一个日地空间距离为1AU=1.469E+8km)。3.585800e-10), the units are (radian, radian, kilometer), the radius of the farthest sampling data is 0.15391E+09km as the basis for spatial division, and the recursive division is performed based on this range. (A space distance between the sun and the earth is 1AU=1.469E+8km).
经过上述步骤,可以找到该数据对应的PDQG-R网格为:After the above steps, the PDQG-R grid corresponding to the data can be found as:
002113-1103.673205e-068.246700e-014.732900e+073.585800e-10002113-1103.673205e-068.246700e-014.732900e+073.585800e-10
从左到右分别是:编码、纬度、经度、半径、密度属性值From left to right are: code, latitude, longitude, radius, density attribute value
同理,3.673205e-062.081300e+001.080500e+081.026500e-10对应的网格编码是:Similarly, the grid code corresponding to 3.673205e-062.081300e+001.080500e+081.026500e-10 is:
121221-011121221-011
步骤106)基于编码检索二维太阳风模型的数据。Step 106) Retrieve the data of the two-dimensional solar wind model based on the code.
该步骤实际上是解码过程,同时将该编码对应的网格位置找出来,并将该网格放置的内容提取出来。This step is actually a decoding process. At the same time, find out the grid position corresponding to the code, and extract the content placed on the grid.
以编码033123-100为例,寻找该编码对应的数据。Take the code 033123-100 as an example to find the data corresponding to the code.
1)解码,分析该编码,推算该编码对应的格网位置。第一位0表示第一象限,[0,pi/2]范围内,33123五位表示剖分等级为5,径向细分编码100有3位,表示径向细分了3次,且是径向细分的第5层。1) Decoding, analyzing the code, and estimating the grid position corresponding to the code. The first digit 0 indicates the first quadrant, within the range of [0,pi/2], the five digits of 33123 indicate that the subdivision level is 5, and the radial subdivision code 100 has 3 digits, indicating that the radial subdivision has been subdivided 3 times, and is Layer 5 of radial subdivision.
下面计算33123对应的坐标(纬度、经度、半径)。The coordinates (latitude, longitude, radius) corresponding to 33123 are calculated below.
第1位3对应的网格中心点:The grid center point corresponding to the first digit 3:
Radius(1)=maxradius*2^(-1-1)Radius(1)=maxradius*2^(-1-1)
Lontitude(1)=0.25*pi/2+(0.5*pi/2)*(2-1)Lontitude(1)=0.25*pi/2+(0.5*pi/2)*(2-1)
第2位3对应的网格中心点:The grid center point corresponding to the second digit 3:
Radius(2)=Radius(1)+maxradius*2^(-2-1)Radius(2)=Radius(1)+maxradius*2^(-2-1)
Lontitude(2)=Lontitude(1)+0.25*pi*2^(-2-1)Lontitude(2)=Lontitude(1)+0.25*pi*2^(-2-1)
第3位1对应的网格中心点:The grid center point corresponding to the third digit 1:
Radius(3)=Radius(2)-maxradius*2^(-3-1)Radius(3)=Radius(2)-maxradius*2^(-3-1)
Lontitude(3)=Lontitude(2)+0.25*pi*2^(-3-1)Lontitude(3)=Lontitude(2)+0.25*pi*2^(-3-1)
第4位2对应的网格中心点:The grid center point corresponding to the 4th bit 2:
Radius(4)=Radius(3)+maxradius*2^(-4-1)Radius(4)=Radius(3)+maxradius*2^(-4-1)
Lontitude(4)=Lontitude(3)-0.25*pi*2^(-4-1)Lontitude(4)=Lontitude(3)-0.25*pi*2^(-4-1)
第5位3对应的网格中心点:The grid center point corresponding to the 5th bit 3:
Radius(5)=Radius(4)+maxradius*2^(-5-1)Radius(5)=Radius(4)+maxradius*2^(-5-1)
Lontitude(5)=Lontitude(4)+0.25*pi*2^(-5-1)Lontitude(5)=Lontitude(4)+0.25*pi*2^(-5-1)
加上径向细分位,最终的坐标值为:Adding radial subdivision, the final coordinate value is:
Radius=Radius(5)-maxradius*2^(-5-1)+maxradius*2^(-5-3-1)*5Radius=Radius(5)-maxradius*2^(-5-1)+maxradius*2^(-5-3-1)*5
Lontitude=Lontitude(5)Lontitude=Lontitude(5)
坐标值为:3.673205e-061.055379e+001.325670e+08The coordinate value is: 3.673205e-061.055379e+001.325670e+08
由于网格编码,已经使得每个网格都有唯一的标识,而每个网格又有唯一的坐标,所以从网格编码则可以直接检索到步骤104)计算的网格坐标,同时也可以通过编码这个索引检索出该网格中有哪些属性数据。总之因为有了之前的若干步骤,所以使得该步骤是最简单的,其实不需要推算坐标,就可以完成数据检索,因为编码是唯一的,通过编码,坐标和属性数据关联起来了。但是推算坐标可以作为本发明的一个功能。Due to the grid coding, each grid has a unique identifier, and each grid has unique coordinates, so the grid coordinates calculated in step 104) can be directly retrieved from the grid coding, and can also be Retrieve which attribute data is in the grid by encoding this index. In short, because of the previous steps, this step is the simplest. In fact, the data retrieval can be completed without calculating the coordinates, because the code is unique, and the coordinates and attribute data are associated through the code. But extrapolated coordinates can be used as a function of the present invention.
2)根据编码,则可以从网格中提取对应的数据。2) According to the code, the corresponding data can be extracted from the grid.
编码为003031-001对应的原始数据是,有2个:The original data corresponding to code 003031-001 is, there are 2:
3.673205e-061.129010e+004.899869e+073.491200e-101.381500e+053.673205e-061.129010e+004.899869e+073.491200e-101.381500e+05
3.673205e-061.129010e+004.899869e+073.649800e-101.391600e+053.673205e-061.129010e+004.899869e+073.649800e-101.391600e+05
编码为231121@010对应的原始数据是,有1个:The original data corresponding to the code 231121@010 is, there is 1:
3.673205E-064.589671E+008.807740E+073.783500E-103.104800E+053.673205E-064.589671E+008.807740E+073.783500E-103.104800E+05
上述模型和编码除了用于检索之外,还可用于多分辨率数据的可视化显示,给出不同分辨率等级的数据的直观显示,便于使用者直观的了解数据特性,从而快速定位感兴趣区域的数据。In addition to being used for retrieval, the above-mentioned models and codes can also be used for visual display of multi-resolution data, giving intuitive display of data of different resolution levels, which is convenient for users to intuitively understand the characteristics of data, so as to quickly locate the area of interest. data.
最后所应说明的是,以上实施例仅用以说明本发明的技术方案而非限制。尽管参照实施例对本发明进行了详细说明,本领域的普通技术人员应当理解,对本发明的技术方案进行修改或者等同替换,都不脱离本发明技术方案的精神和范围,其均应涵盖在本发明的权利要求范围当中。Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than limit them. Although the present invention has been described in detail with reference to the embodiments, those skilled in the art should understand that modifications or equivalent replacements to the technical solutions of the present invention do not depart from the spirit and scope of the technical solutions of the present invention, and all of them should be included in the scope of the present invention. within the scope of the claims.
Claims (4)
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201410225392.1A CN103984748B (en) | 2014-05-26 | 2014-05-26 | A kind of solar wind data partition, coding and the access method of large scale solar-terrestrial physics |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201410225392.1A CN103984748B (en) | 2014-05-26 | 2014-05-26 | A kind of solar wind data partition, coding and the access method of large scale solar-terrestrial physics |
Publications (2)
Publication Number | Publication Date |
---|---|
CN103984748A CN103984748A (en) | 2014-08-13 |
CN103984748B true CN103984748B (en) | 2017-10-03 |
Family
ID=51276721
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN201410225392.1A Active CN103984748B (en) | 2014-05-26 | 2014-05-26 | A kind of solar wind data partition, coding and the access method of large scale solar-terrestrial physics |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN103984748B (en) |
Families Citing this family (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN106021480B (en) * | 2016-05-19 | 2019-09-17 | 福建农林大学 | A kind of parallel spatial division methods and its system based on grid dividing |
CN110706304B (en) * | 2019-09-23 | 2023-02-03 | 中国科学院海洋研究所 | A Visualization Algorithm for Polar Water Vapor Transport Flux |
CN111046005B (en) * | 2019-11-01 | 2023-09-01 | 宝略科技(浙江)有限公司 | Gridding coding method for urban three-dimensional live-action data |
Citations (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN102117494A (en) * | 2009-12-30 | 2011-07-06 | 新奥特(北京)视频技术有限公司 | Method and device for delaminating and blocking data in three-dimensional modeling |
CN102609525A (en) * | 2012-02-10 | 2012-07-25 | 北京大学 | Method for unifying existing longitude and latitude subdividing grids |
-
2014
- 2014-05-26 CN CN201410225392.1A patent/CN103984748B/en active Active
Patent Citations (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN102117494A (en) * | 2009-12-30 | 2011-07-06 | 新奥特(北京)视频技术有限公司 | Method and device for delaminating and blocking data in three-dimensional modeling |
CN102609525A (en) * | 2012-02-10 | 2012-07-25 | 北京大学 | Method for unifying existing longitude and latitude subdividing grids |
Non-Patent Citations (2)
Title |
---|
基于经纬度剖分的空间信息编码研究;李康容,李奇;《四川师范大学学报(自然科学版)》;20100915(第2010年05期);全文 * |
网络环境下全球地形数据组织;周勇;《地理空间信息》;20070628(第2007年03期);全文 * |
Also Published As
Publication number | Publication date |
---|---|
CN103984748A (en) | 2014-08-13 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
CN102609525B (en) | Method for dissecting and unifying geographic grid based on longitude and latitude | |
CN104199986B (en) | Vector data space index method based on hbase and geohash | |
CN103136371B (en) | Subdivision mark generating method and the data retrieval method of multi-source Spatial Data | |
CN106898045B (en) | Large-area true three-dimensional geographic scene self-adaptive construction method based on SGOG tiles | |
CN111475597B (en) | Non-rigid grid coding, unique identification of spatial objects, query method and device | |
CN109992636A (en) | Spatiotemporal coding method, spatiotemporal index and query method and device | |
WO2016095749A1 (en) | Method and device for querying spatial object and establishing spatial index of electronic map | |
CN113010620B (en) | Natural resource data index statistical method and system based on geographic multilevel grid | |
CN110321443B (en) | Three-dimensional live-action model database construction method and device and data service system | |
CN107908646B (en) | An Image Retrieval Method Based on Hierarchical Convolutional Neural Network | |
CN114332366A (en) | Digital city single house point cloud facade 3D feature extraction method | |
CN114049462B (en) | Three-dimensional model monomer method and device | |
CN108717729A (en) | A kind of online method for visualizing of landform multi-scale TIN of the Virtual earth | |
CN110826454A (en) | A method and device for detecting changes in remote sensing images | |
CN104182475B (en) | A kind of positional information method for quickly retrieving of encoding based on mask technology and subdivision | |
CN117520470A (en) | Meteorological data management method and device based on GeoSOT grid coding and electronic equipment | |
CN103984748B (en) | A kind of solar wind data partition, coding and the access method of large scale solar-terrestrial physics | |
CN114970216A (en) | Electromagnetic environment visual expression method based on subdivision grids | |
CN115719410A (en) | Slicing method of space model data | |
CN101964157B (en) | Sphere rhombic grid recursive subdivision method | |
CN115408382B (en) | Vector space information grid storage and management method for large-scale satellite data | |
CN116318541A (en) | Network space multidimensional information subdivision grid coding method, device, equipment and medium | |
CN107273466A (en) | The discrete grid of spherical triangle encodes the fast conversion method to geographical latitude and longitude coordinates | |
CN102103600B (en) | Map building method and map system | |
CN110096484A (en) | A kind of 3D model batch deriving method based on Revit |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
C06 | Publication | ||
PB01 | Publication | ||
C10 | Entry into substantive examination | ||
SE01 | Entry into force of request for substantive examination | ||
GR01 | Patent grant | ||
GR01 | Patent grant | ||
CP01 | Change in the name or title of a patent holder | ||
CP01 | Change in the name or title of a patent holder |
Address after: 100190 No. two south of Zhongguancun, Haidian District, Beijing 1 Patentee after: NATIONAL SPACE SCIENCE CENTER, CAS Address before: 100190 No. two south of Zhongguancun, Haidian District, Beijing 1 Patentee before: Space Science & Applied Research Centre, Chinese Academy of Sciences |