CN111198975B - Grid-based space-time big data visualization method and system - Google Patents
Grid-based space-time big data visualization method and system Download PDFInfo
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- CN111198975B CN111198975B CN201911359426.5A CN201911359426A CN111198975B CN 111198975 B CN111198975 B CN 111198975B CN 201911359426 A CN201911359426 A CN 201911359426A CN 111198975 B CN111198975 B CN 111198975B
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- 238000000034 method Methods 0.000 title claims abstract description 25
- 238000013079 data visualisation Methods 0.000 title claims abstract description 21
- 238000009877 rendering Methods 0.000 claims abstract description 17
- 230000003993 interaction Effects 0.000 claims abstract description 14
- 238000007794 visualization technique Methods 0.000 claims abstract description 6
- 238000004422 calculation algorithm Methods 0.000 claims description 16
- 238000009499 grossing Methods 0.000 claims description 10
- 230000002452 interceptive effect Effects 0.000 claims description 7
- 238000004590 computer program Methods 0.000 claims description 6
- 238000012545 processing Methods 0.000 claims description 6
- 238000004364 calculation method Methods 0.000 abstract description 11
- 230000000694 effects Effects 0.000 description 3
- 230000004043 responsiveness Effects 0.000 description 2
- 238000012800 visualization Methods 0.000 description 2
- 235000001275 Bouea macrophylla Nutrition 0.000 description 1
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- 238000004458 analytical method Methods 0.000 description 1
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- 238000006243 chemical reaction Methods 0.000 description 1
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- 238000005516 engineering process Methods 0.000 description 1
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/90—Details of database functions independent of the retrieved data types
- G06F16/904—Browsing; Visualisation therefor
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/90—Details of database functions independent of the retrieved data types
- G06F16/907—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually
- G06F16/909—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using geographical or spatial information, e.g. location
Abstract
The invention relates to a grid-based space-time big data visualization method and a grid-based space-time big data visualization system, wherein the visualization method is only processed at a browser end and comprises the following steps: acquiring raster data; based on the received first interaction instruction, carrying out additional graphic calculation on the raster data, wherein the additional graphic comprises a contour line and/or a contour surface; obtaining a corresponding grid pattern based on the grid data rendering; and based on the received second interaction instruction, overlaying and rendering the additional graphic on the grid graph. Compared with the prior art, the method and the device have the advantages of good instantaneity, good user experience and the like.
Description
Technical Field
The invention relates to a data visualization method and system, in particular to a grid-based space-time big data visualization method and system.
Background
In the traditional space-time big data visualization method, raster data based visualization is an important technical means. The grid is an important data format for processing space-time big data, and can store discrete data, which represents the characteristics of land utilization or soil data and the like. The method has wide application in the processing and displaying technology of raster data in the fields of China and weather.
In the GIS system of the existing B/S architecture, there are three main modes of visualization of raster data, one is to generate raster data into pictures, register the pictures to actual geographic positions in a browser for display, and as the map of the GIS system is enlarged, the pictures are distorted; secondly, through the service of the back end, the raster data picture in the geographical range displayed in the current GIS system is requested to be loaded in real time, and although distortion is not caused, frequent network data exchange exists, the performance is low, certain delay exists when raster data is browsed, and the user experience is poor. Thirdly, vectorizing raster data and displaying the raster by vector data, wherein the method needs to convert the raster data into the vector data, has the problem of high data conversion difficulty, and has the problem of relative splitting of original raster data and the converted vector data in practical application.
In addition, all three existing modes require the use of specialized software support. Professional software such as ArcGIS, superMap needs to be installed at a server side, professional technicians need to participate in the installation of the software, background service is issued, the environment of the whole system is complex, and the professional software needs to be purchased because the professional software is a private product, and the cost is high.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provide a grid-based space-time big data visualization method and a grid-based space-time big data visualization system with good real-time performance and good user experience.
The aim of the invention can be achieved by the following technical scheme:
a space-time big data visualization method based on a grid is only processed at a browser side and comprises the following steps:
acquiring raster data;
based on the received first interaction instruction, carrying out additional graphic calculation on the raster data, wherein the additional graphic comprises a contour line and/or a contour surface;
obtaining a corresponding grid pattern based on the grid data rendering;
and based on the received second interaction instruction, overlaying and rendering the additional graphic on the grid graph.
Further, the raster data is acquired in a binary format.
Further, after the raster data is acquired, the raster data is stored in a local memory of the browser side.
Further, the first interactive instruction includes whether to calculate an additional pictorial instruction, an additional pictorial type instruction, and an additional pictorial calculation parameter instruction.
Further, when the additional graphic calculation is performed, an interpolation algorithm is adopted to perform smoothing.
Further, when the grid graph is rendered, smoothing is carried out on the grid data by adopting an interpolation algorithm.
Further, the interpolation algorithm is a bilinear interpolation algorithm, and a linear interpolation algorithm is adopted in an edge area and a data missing area.
Further, when the grid graph is rendered, color matching data are obtained based on the third interaction instruction, and the color matching data are overlapped on the grid graph.
Further, the grid graphic and/or additional pictorial representations are rendered using an H5-based canvas.
The invention also provides a grid-based space-time big data visualization system, which comprises a processor and a memory, wherein the memory stores a computer program, and the processor calls the computer program to execute the steps of the visualization method.
Compared with the prior art, the invention has the following beneficial effects:
1. the method and the device are realized at the browser end, so that the interactive instruction can be conveniently acquired, the real-time performance is high, and the user experience is good.
2. The invention can conveniently superimpose and render the contour line and the contour surface on the grid graph, so that the data are fused and displayed, and the user experience is improved.
3. The invention adopts binary format to obtain raster data, and accelerates the performance of loading data.
4. According to the method, the local storage is performed after the raster data are acquired, when the same raster data are displayed, the whole process of rendering the same raster data is off-line, the original data are exchanged only once through the network, no frequent network request is generated, the real-time responsiveness is high, and the user experience is improved.
5. In the invention, during calculation and rendering processing, contour lines, contour surfaces, grid patterns and the like are all subjected to smoothing processing, so that the smoothing effect of the edge area is optimized, and the display effect is good.
6. The invention can modify the calculation parameters and the color matching scheme in real time, thereby meeting the personalized requirements of users.
7. The invention adopts the B/S mode, is not limited by hardware and an operating system used by a client platform, and has good expansibility.
Drawings
FIG. 1 is a schematic flow chart of the present invention.
Detailed Description
The invention will now be described in detail with reference to the drawings and specific examples. The present embodiment is implemented on the premise of the technical scheme of the present invention, and a detailed implementation manner and a specific operation process are given, but the protection scope of the present invention is not limited to the following examples.
Example 1
The embodiment provides a grid-based space-time big data visualization method, which is only processed at a browser end and comprises the following steps:
1) Raster data is acquired. In this embodiment, raster data is acquired in binary format, so as to accelerate the performance of loading data, and adapt to different map ranges in a GIS system. After raster data is obtained, the raster data is stored in a local memory of a browser end, when the same raster data is displayed, original data is exchanged only once through a network, no frequent network request exists, and the real-time responsiveness is high.
2) Based on the received first interactive instruction input by the user, carrying out additional graphic calculation on the raster data, wherein the additional graphic comprises a contour line and/or a contour surface.
In this embodiment, the first interaction instruction includes an additional graphic instruction, an additional graphic type instruction, and an additional graphic calculation parameter instruction, so as to implement real-time calculation.
And when the additional graphic calculation is performed, performing smoothing processing by adopting an interpolation algorithm. In this embodiment, smoothing may be performed by using various interpolation algorithms.
3) And obtaining a corresponding grid graph based on the grid data rendering. And when the grid graph is rendered, smoothing the grid data by adopting an interpolation algorithm.
In this embodiment, the interpolation algorithm is a bilinear interpolation algorithm, and a linear interpolation algorithm is adopted in the edge area and the data missing area, so as to ensure the smoothing effect of the edge area.
In this embodiment, when the grid pattern is rendered, color matching data is obtained based on the third interaction instruction input by the user, the color matching data is superimposed on the grid pattern, and the rendering result is dynamically adjusted.
4) And based on the received second interactive instruction input by the user, overlaying and rendering the additional graphic on the grid graph.
The visualization method may further include: and re-executing the steps 3) and 4) based on the received fourth interaction instruction, so as to realize the rendering of different graphic ranges.
In this embodiment, the second interaction instruction includes whether to superimpose the additional graphic and the type of the additional graphic.
In this embodiment, the H5-based canvas is adopted to render the grid pattern and/or the additional graphic, so that the complex pattern (the response time is lower than 1.5 seconds) can be drawn with high performance, the background service support is not required, the network interaction is not required, the calculation parameters of the contour line and the contour surface set by the user can be responded in real time, the color scheme of the grid pattern, the contour line and the contour surface can be responded in real time, the overall user experience is improved, and the personalized requirements of the user are met.
A specific implementation process of the grid-based space-time big data visualization method is as follows:
step 401: the browser side requests raster data from the back side;
step 402: waiting and receiving raster data fed back by a back end;
step 403: judging whether raster data is received or not, if so, executing step 405; if not, execute step 404;
step 404: judging whether the time-out is over, if the time-out is over, executing step 401, and if the time-out is not over, executing step 402;
step 405: judging whether the contour line is calculated or not, if the contour line is calculated, executing step 406, and if the contour line is not calculated, executing step 407;
step 406: calculating the contour line of the grid;
step 407: judging whether the isosurface is calculated or not, if so, executing step 408, and if not, executing step 409;
step 408: calculating an isosurface of the grid;
step 409: rendering a grid pattern;
step 410: judging whether the contour line needs to be rendered, if yes, executing step 411, and if no, executing step 412;
step 411: rendering the contour line;
step 412: judging whether the isosurface needs to be rendered, if yes, executing step 413, and if no, executing step 414;
step 413: rendering the isosurface;
step 414: judging whether the graph range is updated or not, if the graph range is required to be updated, executing step 409, and if the graph range is not required to be updated, executing step 415;
step 415: and judging whether to end the drawing, if so, ending, otherwise, returning to the step 414.
Example 2
The present embodiment provides a grid-based spatio-temporal big data visualization system, comprising a processor and a memory, the memory storing a computer program, the processor invoking the computer program to perform the steps of the visualization method as described in embodiment 1.
The foregoing describes in detail preferred embodiments of the present invention. It should be understood that numerous modifications and variations can be made in accordance with the concepts of the invention by one of ordinary skill in the art without undue burden. Therefore, all technical solutions which can be obtained by logic analysis, reasoning or limited experiments based on the prior art by the technical personnel in the field according to the inventive concept are within the protection scope determined by the present invention.
Claims (7)
1. A space-time big data visualization method based on a grid is characterized in that the method is only processed at a browser end and comprises the following steps:
1) Acquiring raster data;
2) Performing additional graphic computation on the raster data based on a received first interactive instruction, wherein the first interactive instruction comprises an additional graphic instruction, an additional graphic type instruction and an additional graphic computation parameter instruction, the additional graphic comprises a contour line and/or a contour surface, and when the additional graphic computation is performed, an interpolation algorithm is adopted to perform smoothing processing;
3) Obtaining a corresponding raster pattern based on the raster data rendering, and smoothing raster data by adopting an interpolation algorithm when the raster pattern is rendered;
4) Superposing and rendering the additional graphic on the grid graphic based on a received second interaction instruction, wherein the second interaction instruction comprises whether to superimpose the additional graphic and the type of the additional graphic;
the visualization method further comprises the following steps: and re-executing the steps 3) and 4) based on the received fourth interaction instruction, and realizing the rendering of different graphic ranges, wherein the grid graphic ranges are updated based on the received fourth interaction instruction.
2. The grid-based spatio-temporal big data visualization method of claim 1, wherein the raster data is acquired in a binary format.
3. The grid-based spatio-temporal big data visualization method of claim 1, wherein after the grid data is acquired, the grid data is stored in a local memory at a browser end.
4. The grid-based spatio-temporal big data visualization method of claim 1, wherein the interpolation algorithm is a bilinear interpolation algorithm, and a linear interpolation algorithm is employed in the edge region and the data missing region.
5. The grid-based spatiotemporal big data visualization method of claim 1, wherein color matching data is obtained based on a third interactive instruction when rendering the grid pattern, and the color matching data is superimposed on the grid pattern.
6. The grid-based spatiotemporal big data visualization method of claim 1, wherein the grid graphic and/or additional pictorial representations are rendered using an H5-based canvas.
7. A grid-based spatio-temporal big data visualization system comprising a processor and a memory, said memory storing a computer program, characterized in that said processor invokes said computer program to perform the steps of the visualization method according to any of claims 1-6.
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| CN111694930B (en) * | 2020-06-11 | 2023-11-14 | 中国农业科学院农业信息研究所 | Dynamic knowledge hot-spot evolution and trend analysis method |
| CN111782745B (en) * | 2020-06-28 | 2021-08-03 | 中国矿业大学(北京) | Space-time big data grid coding efficient visualization method and system |
| CN112233205B (en) * | 2020-10-14 | 2021-05-28 | 山东省工程地震研究中心 | Electronic map making method and system for partitioning and cutting based on discrete data |
| CN116342820A (en) * | 2023-03-01 | 2023-06-27 | 北京数识科技有限公司 | Raster data color distribution system, method and computer readable storage medium |
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