CN111858792A - Grid data front-end visual comprehensive analysis method - Google Patents

Grid data front-end visual comprehensive analysis method Download PDF

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CN111858792A
CN111858792A CN202010507810.1A CN202010507810A CN111858792A CN 111858792 A CN111858792 A CN 111858792A CN 202010507810 A CN202010507810 A CN 202010507810A CN 111858792 A CN111858792 A CN 111858792A
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data
processing
displayed
level
overview
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孙波
靳卫华
张雷
李志栋
胡大勇
董勇
朱宇
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Beijing Institute of Spacecraft System Engineering
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Beijing Institute of Spacecraft System Engineering
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    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/29Geographical information databases
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/50Information retrieval; Database structures therefor; File system structures therefor of still image data
    • G06F16/54Browsing; Visualisation therefor
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F9/00Arrangements for program control, e.g. control units
    • G06F9/06Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
    • G06F9/46Multiprogramming arrangements
    • G06F9/50Allocation of resources, e.g. of the central processing unit [CPU]
    • G06F9/5083Techniques for rebalancing the load in a distributed system
    • G06F9/5088Techniques for rebalancing the load in a distributed system involving task migration

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Abstract

The invention discloses a grid data front-end visual comprehensive analysis method, which is characterized in that virtual slicing is carried out on grid data by calculating metadata information of a multi-level overview chart of the grid data, and when a browser end requests for displaying the data, only corresponding slice data is selected for processing and displaying according to a display level and a display range in the request, so that the processing time of the grid data is effectively shortened, and the real-time performance of the grid data processing and displaying is improved.

Description

Grid data front-end visual comprehensive analysis method
Technical Field
The invention belongs to the technical field of geographical big data analysis and display, and particularly relates to a grid data front-end visual comprehensive analysis method.
Background
The existing remote sensing data has the characteristics of large data volume and time consumption in processing. In actual needs, the whole image is generally not required to be processed, and in most cases, the processing result needs to be checked quickly in real time, so that the model processing parameters can be adjusted conveniently.
The general processing mode is mainly to carry out full-width processing through desktop software such as ERDAS, PCI, ENVI and the like, and has three disadvantages: firstly, the processing time is long, and the processing result cannot be checked in real time; vector data and raster data are inconvenient to comprehensively analyze in the desktop software; thirdly, the desktop software cannot utilize new computing means such as cloud computing to accelerate the processing speed.
In addition, many service scenes need to conveniently carry out comprehensive analysis on vector and raster data, real-time rendering of the raster data is a premise for realizing block-based hierarchical rapid processing, a main mode for viewing the raster data by the conventional browser end is a map publishing service, the mode has high limitation, once the raster data is published, the rendering mode cannot be changed, and the effect of data processing cannot be viewed in real time by using the mode. With the development of high-performance server and cloud computing technologies, the processing of geographic data also needs to improve the processing efficiency of data by using the high and new technologies.
Disclosure of Invention
The grid data front-end visualization comprehensive analysis method provided by the invention can only select corresponding slice data to process and display according to the display level and the display range in the request.
The invention provides a grid data front end visual comprehensive analysis method, which comprises the following steps:
step 1, converting raster data to be processed into a multi-level overview chart according to a pyramid principle, and calculating the overview chart to obtain metadata information, wherein the metadata information is index information comprising byte positions and row and column numbers of all levels of overview charts; according to the required display range and the data level, searching an index of the to-be-displayed slice data in the metadata information, and then selecting the to-be-displayed slice data from the overview chart according to the index;
And 2, selecting a required data processing script from a series of data processing scripts to process the to-be-displayed slice data to obtain to-be-displayed data, and displaying the to-be-displayed data.
Further, when the data display mode needs to be changed, a new data processing script is selected from a series of data processing scripts to execute the step 2 to change the data display mode.
Further, the size of the slice data to be displayed is 256 × 256 pixels.
Has the advantages that:
1. according to the method and the device, the metadata information of the multi-level overview chart of the raster data is calculated, the raster data is virtually sliced, when a browser requests for displaying the data, corresponding sliced data is only selected for processing and displaying according to the display level and the display range in the request, the processing time of the raster data is effectively shortened, and the real-time performance of processing and displaying of the raster data is improved.
2. According to the invention, different data processing scripts are adopted to process the slice data, so that the display effect of the raster data can be changed in real time.
Detailed Description
The present invention will be described in detail below with reference to examples.
The invention provides a grid data front end visualization comprehensive analysis method, which has the basic idea that: converting raster data to be processed into a multi-level overview chart according to a pyramid principle, and calculating the overview chart to obtain metadata information, wherein the metadata information is index information comprising byte positions and row and column numbers of the overview chart at each level; according to the required display range and the data level, the index of the to-be-displayed slice data is found in the metadata information, and then the to-be-displayed slice data is selected from the overview chart according to the index; and processing the to-be-displayed slice data by adopting a predefined data processing script to obtain to-be-displayed data, and displaying the to-be-displayed data.
The invention provides a grid data front-end visual comprehensive analysis method which specifically comprises the following steps:
step 1, converting raster data to be processed into a multi-level overview chart according to a pyramid principle, and calculating the overview chart to obtain metadata information, wherein the metadata information is index information comprising byte positions and row and column numbers of the overview charts at all levels.
Specifically, an overview map of raster data is created according to the pyramid principle, for example, 29 levels of overview layers are generated, and the overview layers are written into a random access file by object. Calculating the overview chart to obtain metadata information, wherein the definition of the metadata information can be shown in table 1, that is, the identification bit is a letter CAST and occupies 4 bytes; byte bits of the overview map of each level, accounting for 29 x 4 bytes; the number of overview rows and columns per level is calculated in bytes 29 × 2 × 4, for a total of 232 bytes. The metadata information can be written into the original raster data in the form of header information. The main purposes of the above treatment process are: the required data can be rapidly read according to a hierarchical block information reading mode instead of reading all data into the memory at one time, so that the data reading efficiency is improved, meanwhile, hierarchical block index information of the raster data is recorded, actual slicing is not carried out on the data, actual slicing is carried out only when the data is read, the processing efficiency can be effectively improved, and the real-time performance of data processing is improved.
Serial number Information Number of bytes
1 Identification bit 4
2 Word of overview chart of level 1Node position 4
...... Byte bits of the N level overview chart 4
30 Byte bits of overview chart at level 29 4
31 Level 1 overview line number 8
...... Number of overview rows at level N 8
59 Overview line number at level 29 8
TABLE 1 Pre-processing record information Table
And 2, searching the index of the to-be-displayed slice data in the metadata information according to the required display range and the required data level, and selecting the to-be-displayed slice data from the overview chart according to the index.
When the browser side requests to display data, the level and the display range of the data to be displayed in the page are determined according to the information in the request, and therefore the level and the range of the raster data to be processed are determined. For example, the determination method is to acquire the display range and level of the map base map in the page, and each time the map is zoomed and dragged by the mouse, the update of the display range and level is triggered. Meanwhile, in order to improve the browsing experience of the front-end web page and prevent blank areas from appearing when the map is dragged, the range obtained each time is expanded outwards 1/5 of the current range, and the preloading strategy can improve the browsing experience to a great extent.
In the implementation, the display range and the data level can be sent to the background in the form of web requests, and a concurrent request mode can be adopted to improve the processing efficiency. After the background acquires the display range and the data level, firstly, the slice data to be displayed, which needs to be processed, is acquired according to the metadata information recorded in the step 1. Assuming that the slice corresponding to the overview chart of each level has M rows and N columns, knowing the coordinates (X _1, Y _1) of the left lower vertex and the coordinates (X _2, Y _2) of the right upper vertex of the raster data, the coordinates (X _ LL, Y _ LL) of the left lower vertex and the coordinates (X _ RU, Y _ RU) of the right upper vertex of each slice can be calculated as follows:
XLL=X1+n(X2-X1)/N
YLL=Y1+m(Y2-Y1)/M
XRU=X1+(n+1)(X2-X1)/N
YRU=Y1+(m+1)(Y2-Y1)/M
thus, the coordinates of the four corner points can be further calculated. And comparing the coordinates of the four corner points of each slice with the transmitted page range, wherein when one of the four corner points falls into the transmitted page range, the slice needs to be processed.
And 3, processing the to-be-displayed slice data by adopting a predefined data processing script to obtain to-be-displayed data, and displaying the to-be-displayed data.
The data processing script is used for realizing various specialized processing of raster data. The input of the data processing script needs to match the size of the slice data defined in step 1, for example, typically 256 × 256 pixels of slice data. Meanwhile, the result returned by the data processing script is 256 × 256 slice data. The method is beneficial to split processing of remote sensing data with large data volume, and processing efficiency is improved. Sample scripts are as follows:
Figure RE-GDA0002644809070000051
In addition, in order to meet the requirement of processing large data volume generated by high concurrency, data processing in the background is supported to be deployed on the cloud platform, so that the characteristics of high load and high availability of the cloud platform can be utilized, but a task scheduling mechanism is required to distribute processing tasks. For example, a service dispatch center plus N data processing centers may be used. The method comprises the steps that message queue service is set in a service dispatching center, all processing requests are sent to the message center in a message queue mode, the dispatching service obtains the requests from the message center, and the requests are sent to the processing center with small load preferentially according to the load condition of each data processing center, so that load balance is achieved. The task message includes id to be processed, id of the processing script, level to be processed, and a number list of slice data at the processing level, and through these information, the processing center can also clearly know which script is used to process specific slice data, and an example of the task message is shown below.
Figure RE-GDA0002644809070000052
Figure RE-GDA0002644809070000061
The feedback message mainly contains result information of task processing, whether the task is successful or not, and simple additional information, and examples of the feedback message are shown below.
Figure RE-GDA0002644809070000062
The above description is only a preferred embodiment of the present invention, and is not intended to limit the scope of the present invention. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims (3)

1. The grid data front-end visualization comprehensive analysis method is characterized by comprising the following steps of:
step 1, converting raster data to be processed into a multi-level overview chart according to a pyramid principle, and calculating the overview chart to obtain metadata information, wherein the metadata information is index information comprising byte positions and row and column numbers of all levels of overview charts; according to the required display range and the data level, searching an index of the to-be-displayed slice data in the metadata information, and then selecting the to-be-displayed slice data from the overview chart according to the index;
and 2, selecting a required data processing script from a series of data processing scripts to process the to-be-displayed slice data to obtain to-be-displayed data, and displaying the to-be-displayed data.
2. The method according to claim 1, wherein when the data display mode needs to be changed, a new data processing script selected from a series of data processing scripts is used to execute the step 2 to change the data display mode.
3. The method of claim 1, wherein the size of the slice data to be displayed is 256 x 256 pixels.
CN202010507810.1A 2020-06-05 2020-06-05 Grid data front-end visual comprehensive analysis method Pending CN111858792A (en)

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Cited By (1)

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CN115375868A (en) * 2022-10-25 2022-11-22 阿里巴巴(中国)有限公司 Map display method, remote sensing map display method, computing device and storage medium

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CN107220302A (en) * 2017-05-10 2017-09-29 江苏速度信息科技股份有限公司 Auto slice storage system and method based on QT technologies
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CN110399446A (en) * 2019-07-26 2019-11-01 广州市城市规划勘测设计研究院 Method for visualizing, device, equipment and the storage medium of extensive space-time data
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US20100156889A1 (en) * 2008-12-18 2010-06-24 Microsoft Corporation Bi-directional update of a grid and associated visualizations
CN105069020A (en) * 2015-07-14 2015-11-18 国家信息中心 3D visualization method and system of natural resource data
CN106873931A (en) * 2017-02-15 2017-06-20 北京佳格天地科技有限公司 Raster data visualization device, method and computer system
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