CN110781240A - Visual mining and application method of red tide data - Google Patents
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Abstract
A visual mining and application method of red tide data relates to the technical field of marine environment science. 1) Carrying out normalized processing on the information of the original red tide event; 2) analyzing the history of the red tide events, checking and screening out independent red tide events, and finishing data preprocessing; 3) designing and drawing a data pivot table and a perspective view of various contents based on the data preprocessed in the step 2), identifying and analyzing the composition, relation, hierarchy and distribution of red tide information, and selecting and optimizing various chart types; 4) based on the data preprocessed in the step 2), designing a multi-source visual fusion mode of a dynamic time line and a three-dimensional map, and verifying the feasibility and effectiveness of the red tide information mining; 5) based on the steps 3) and 4), an instrument panel model is constructed, and a relatively universal red tide dynamic analysis chart is designed and used for red tide information mining analysis. The method can effectively screen out the nodes in the red tide subareas and time periods, and is widely applied to the red tide information mining.
Description
Technical Field
The invention relates to the technical field of marine environment science, in particular to a visual mining and application method of red tide data, which combines the data preprocessing of Matlab programming and various visual fusion modes based on the added Excel function to form a mode of layering and visually displaying a data structure by only using one chart so as to further deeply mine data information.
Background
The red tide data is visualized by adopting software related to professional fields such as remote sensing or GIS and the like after prediction and forecast (slow wave and the like, Zhejiang university declaration (science edition), 1008-. The intersection of different disciplines or domains can burst new ideas and views.
Chinese patent CN201810966994.0 discloses a red tide data query method based on graph model construction, which comprises: constructing a red tide data graph model and constructing a red tide data query language; the red tide data graph model RTGraph comprises three data: point data, edge data, red tide edge data; the red tide edge data is point data and is marked by point attributes; the red tide data query language comprises: create statements, query statements, update statements, insert statements, delete statements. The red tide data are stored in the graph model according to a specific stage, the edge data of the red tide are established, the association between the red tide data can be represented, common point and edge query can be carried out on the graph model, meanwhile, various model queries can be carried out, the query speed and precision are improved, and the red tide data can be fully utilized for research. Researchers can predict the time and place of the phase transition, and take corresponding measures to reduce economic and ecological loss.
How to tightly buckle the concept of recognizing oceans and serving the masses in the 'smart oceans' engineering, the red tide information is deeply mined from different visual angles and ways through multi-source visual expression such as diversification, static dynamic chart combinability and the like, a visual mode which can help a user to analyze and find out the internal rules and the use value of data is explored, effective and objective red tide information with values is obtained, and therefore the technical problem that technical support is provided for scientific research and related departments in innovation and application is the current stage is solved.
Disclosure of Invention
The invention aims to provide a visual red tide data mining and application method, which combines non-professional software Excel and professional software Matlab to design a relatively universal visual expression fusion mode capable of realizing effective red tide information mining and analysis, more effectively helps a user to analyze and extract the internal rules of red tide data, and provides technical support for relevant departments such as scientific research and management.
The invention comprises the following steps:
1) carrying out normalized processing on the information of the original red tide event; reading files in batches by utilizing matlab programming, identifying the structure and the name of each project of data, correcting the data in batches according to the specified data project, and finally outputting the files;
2) analyzing the history of the red tide events, checking and screening out independent red tide events, and finishing data preprocessing;
3) designing and drawing a data pivot table and a perspective view of various contents based on the data preprocessed in the step 2), identifying and analyzing the composition, relation, hierarchy and distribution of red tide information, and selecting and optimizing various chart types;
4) based on the data preprocessed in the step 2), designing a multi-source visual fusion mode of a dynamic time line and a three-dimensional map, and verifying the feasibility and effectiveness of the red tide information mining;
5) based on the step 3) and the step 4), an instrument panel model is constructed, and a relatively universal red tide dynamic analysis chart is designed and used for red tide information mining analysis.
In step 1), the specific method for performing the normalization processing on the information of the original red tide event may be:
firstly, reading data in batches by utilizing Matlab programming, identifying the structure and the item names of original data through software, then checking and inputting the title names of each column in a red tide event history record file according to a standard data item, correspondingly supplementing and sequencing by utilizing a Matlab modification program, and outputting the batch modified data in batches by programming; the data items of the specification, i.e., the column header names, are set to: sequence number, occurrence time, death time, duration, location, longitude, latitude, sea area of occurrence, specific sea area, maximum area of influence, species of biological dominance, highest density, loss condition.
In step 2), the specific method for preprocessing the data may be:
the method comprises the steps of detecting and screening independent red tide events, wherein two red tide events of single algae species red tide and mixed algae species red tide exist in original data due to different statistical modes, in part of original files, one mixed algae species red tide event is divided into a plurality of single algae species red tide events, repeated statistics of the red tide events is caused, in order to avoid the situation, the starting and ending time and the occurrence place of the red tide events are detected, the red tide events of the mixed algae species are unified, and repeated information of branch statistics is deleted.
In step 3), the specific method for identifying and analyzing the composition, relationship, hierarchy and distribution of the red tide information may be:
the data perspective table enhancement function of Excel is utilized to realize that a complex model is easily built across data, the data are automatically grouped according to time, a user checks the content as required, and selects corresponding sea areas, regions and the like through a screening button to carry out data statistics, and the time grouping of the data comprises the modes of second, minute, hour, day, month, quarter, year or the combination of the modes; analyzing and designing a data pivot table with various contents, taking the pivot table as a dynamic data source, selecting and optimizing various chart types, and generating a perspective view; inserting perspective views, grouping and zooming in and out other hierarchies in the data in a time-span mode, and selecting corresponding sea areas, regions and the like for graphical display according to contents which a user needs to view.
In step 4), the design of the dynamic timeline and the multi-source visual fusion mode of the three-dimensional map verifies the feasibility and effectiveness of the red tide information mining, and the specific steps can be as follows:
(1) screening the nodes of the red tide information in different periods by using an Excel dynamic time line: based on the function of the Excel calendar, according to the user requirements, selecting a dynamic time range of a single year or a plurality of continuous years for carrying out data statistics and visual display. The time slider on the animation control toolbar is dragged, so that the distribution condition of the red tide information in different periods can be displayed. Based on the function of the Excel dynamic graph, selecting a corresponding project (such as a time node or a subarea) for visual display after data screening, and facilitating a user to split, check and analyze a data single-point project;
(2) analyzing the spatial position relation and the rule of the red tide information by using an Excel three-dimensional map: for red tide data containing position information, the data are quickly mapped onto a virtual earth through acquisition and identification of data space coordinate information, contents to be expressed by the data are displayed in a two-dimensional plane map or a three-dimensional map and other suitable maps, a thematic map is dynamically analyzed and three-dimensionally displayed, form data with space information are converted into the thematic map, a data space visualization product is realized, and the visibility and analysis efficiency of the data are improved. For example: in the spatial distribution of the red tide algae species along with the time change, the dynamic changes of the positions and the frequency of the red tide algae species in the past can be demonstrated according to the time sequence by the time shaft.
(3) And verifying the effectiveness and feasibility of the mining of the red tide information by the fusion mode based on the red tide event historical record original data.
In step 5), a specific method for constructing an instrument panel model and designing a relatively universal red tide dynamic analysis chart is as follows: the method comprises the steps of designing a dynamic chart aiming at the red tide occurrence conditions of different alga species and different months, constructing a red tide occurrence frequency instrument panel model, integrating various visual designs such as a perspective table screening design, a mini-graph display design and an instrument panel model according to user requirements, dynamically displaying the distribution characteristics of the red tide occurrence conditions, simultaneously newly adding two alga species red tide outbreak condition comparison chart designs, and enabling a user to independently select two alga species according to requirements to perform comparison analysis and search for the occurrence rules of the different alga species red tides.
In order to more completely and more mine the value information of the red tide with less omission, the invention utilizes and fuses the multi-source visualization functions of an Excel dynamic time line, a dynamic chart and the like, identifies and analyzes the composition, the relation, the hierarchy and the distribution of the red tide information, judges the slight difference of a data time node or a space boundary and the like, constructs an instrument panel model and the like, designs various visualization expression fusion modes capable of realizing the mining analysis of the effective information of the red tide, and detects the effectiveness of the design through an example.
The invention has the beneficial effects that:
according to the method, firstly, Matlab is used for realizing data preprocessing in batches, then based on the design of several visual charts in Excel, nodes of time change characteristics of different periods of the red tide are effectively screened out by using a dynamic time line, and then the nodes of red tide partition and time sharing periods are effectively screened out by combining with static display and dynamic time display of space distribution of red tide outbreak in a three-dimensional map, so that the feasibility and effectiveness of various visual expression fusion designs on red tide information mining are verified. Then, combining functions of a data pivot table, a mini-graph and the like in a data rapid analysis module in Excel, fusing multiple visualization modes such as a perspective view, a mini-graph, a dynamic graph and the like, constructing an instrument panel model, and designing two relatively generalized visualization expression modes, namely 'one graph': the instrument panel model of the red tide occurrence frequency distribution of different algae species and the A/B algae species comparison dynamic chart model can quickly carry out layered screening on a data structure, are beneficial to discovering fine characteristics in red tide information, have important significance for discussing the evolution rule and mechanism of red tide outbreak, and provide technical support for relevant departments such as scientific research and management. The method can be widely applied to the information mining of the red tide.
Drawings
FIG. 1 is a flow chart of a visual mining and application method of red tide data;
FIG. 2 is an enlargement of the layered structure based on a perspective view of the red tide data in year 2000-2016;
FIG. 3 is a layer structure reduction based on 2000-2016 red tide data perspective;
FIG. 4 is a diagram of a dynamic chart based on red tide information in Fujian province of 2000-2016;
FIG. 5 is an Excel dynamic timeline showing the spatiotemporal distribution of Fujian province red tide durations;
FIG. 6 is a three-dimensional map showing the spatial distribution of red tide outbreak frequency;
FIG. 7 is a three-dimensional map showing the spatial distribution of red tide algae species over time;
FIG. 8 is a three-dimensional area diagram showing the maximum area grading distribution of red tide outbreaks in each sea area;
FIG. 9 is information mining of a division time-phased outbreak situation of Fujian near-shore red tide based on multi-source visualization mode fusion;
FIG. 10 is a dynamic chart based on a red tide occurrence frequency dashboard model;
FIG. 11 is a graph comparing the red tide outbreaks of two species of algae.
Detailed Description
The following examples will further illustrate the present invention with reference to the accompanying drawings.
Referring to fig. 1, an embodiment of the present invention includes the steps of:
1) carrying out normalized processing on the information of the original red tide event;
in this embodiment, the red tide event history data of 2000-2016 year is selected, the Matlab programming is used to read the data in batch, the structure and distribution of the original data are identified by software, then the names of the columns of titles in the input red tide event history file are checked according to the normative data items, and the columns of titles are supplemented and sequentially arranged. The canonical data items and ordering may include the following: sequence number, occurrence time, extinction time, duration, location, sea area of occurrence, specific sea area, maximum area of influence (square kilometer), species of biological dominance, highest density, loss condition.
As a part of the column title of the 'place' in the original file is marked by a place name, and the other part is marked by latitude and longitude; the column heading 'sea area' marks that the place names are mostly county-level or smaller place names, and although some regions point to the same place, the place names are not uniform; in summary, in order to facilitate subsequent data analysis, the data is normalized, the data structure and name are unified, and the column title "sea area" is divided into two columns "sea area of occurrence" and "specific sea area". Wherein, the 'occurrence sea area' is marked with the name above the market level, and the 'specific sea area' is marked with the name of the specific sea area; the "location" is labeled with a specific latitude and longitude.
To facilitate the spatially distributed display of the occurrence of red tide events, two columns of "longitude" and "latitude" are provided. After the title names of the columns of 'sea area of occurrence' are unified, the central position of the red tide event is determined according to the position of the city place in combination with the 'specific sea area', and two columns of information of 'longitude' and 'latitude' are supplemented, as shown in table 1.
TABLE 1
And performing corresponding supplement, sequencing and the like by using a Matlab modification program. The corrected data is output in bulk by programming.
2) And analyzing the red tide event history record, checking and screening out independent red tide events, and finishing data preprocessing.
And (5) checking and screening out independent red tide events. The original data has two red tide events of single algae species red tide and mixed algae species red tide due to different statistical modes. In part of the original documents, there is a method of dividing a mixed algae species red tide event into a plurality of single algae species red tide events, resulting in repeated statistics of the red tide events. In order to avoid the occurrence of the situation, the starting and ending time and the occurrence place of the red tide event are detected, the red tide events of the mixed algae species are unified, and repeated information of branch statistics is deleted;
3) designing and drawing a data pivot table and a perspective view of various contents based on the data preprocessed in the step 2), identifying and analyzing the composition, relation, hierarchy and distribution of red tide information, and selecting and optimizing various chart types.
Firstly, a complex model is easily constructed by using a data perspective table enhancement function of an Excel 2016 edition, data are automatically grouped according to time, a user checks contents as required, and corresponding sea areas, regions and the like are selected through a screening button for data statistics. For example: the grouping of the display modes of the year, the quarter, the month and the like can be seen by clicking the corresponding year and quarter. And analyzing and designing a pivot table with various contents, taking the pivot table as a dynamic data source, selecting and optimizing various chart types, and generating a perspective view. For example: based on the pivot table, insert a perspective view, the "+, -" button in the lower right corner of the perspective view, which allows you to group and zoom in and out on other hierarchies in the data across time (FIGS. 2 and 3).
The two filtering labels on the right side of the perspective view can select corresponding sea areas, regions and the like for graphical display according to contents which a user needs to view.
4) Based on the data preprocessed in the step 2), the effectiveness and feasibility of the red tide information mining are verified by utilizing the design of combining the dynamic time line and the multi-source visualization of the three-dimensional map.
And screening the nodes of the red tide information in different periods by using an Excel dynamic time line. The method comprises the following specific steps: based on the function of the Excel calendar, according to the user requirements, a dynamic time range of a single year or a plurality of continuous years is selected for carrying out statistics and visual display of data (figure 4). The time slider on the animation control toolbar below the screen is dragged, so that the distribution condition of the red tide information in different periods can be displayed. Based on the function of the Excel dynamic graph, corresponding projects (such as time nodes or subareas) are selected for visual display after data screening, and a user can split, view and analyze the data single-point projects.
And analyzing the spatial position relation and the rule of the red tide information by using an Excel three-dimensional map. The method comprises the following specific steps: for red tide data containing position information, the data are quickly mapped onto a virtual earth through acquisition and identification of data space coordinate information, contents to be expressed by the data are displayed in a two-dimensional plane map or a three-dimensional map and other suitable maps, a thematic map is dynamically analyzed and three-dimensionally displayed, form data with space information are converted into the thematic map, a data space visualization product is realized, and the visibility and the analysis efficiency of the data are improved (fig. 5-7). For example: in the spatial distribution of the red tide algae species along with the time change, the dynamic changes of the positions and the frequency of the red tide algae species in the past can be demonstrated according to the time sequence by the time shaft.
In the embodiment, the red tide data based on the history records of red tide events in 2000-2016 are designed by combining the dynamic time line and the multi-source visualization of the three-dimensional map, and the characteristics of the red tide distinguishing period in the period are successfully mined. Firstly, designing a three-dimensional map and a three-dimensional area map of a high-incidence area and an accumulated maximum area of red tide distribution, and dividing an explosion distribution area into A, B, C areas in total. Wherein the area A is mainly the great tripod, Xiapu and Lianjiang in the northern sea area of Changjiang river; zone B is the middle part, Fuqing, Tan, Pu Tian and Quanzhou in the south area of Yangtze river; region C is southern, gulf sea, Xiamen and east mountain Bay. Meanwhile, a dynamic time line and a dynamic chart of the red tide outbreak times in 2000-2016 years are designed and drawn, and results show that the red tide outbreak times in 2009 are remarkably reduced in most sea areas, and the red tide outbreak times are obviously increased by 2010, and the period is probably a turning point. In addition, the A, B, C three sections are distributed year by year, the section B obviously increases 6 times in 2010 and the area also obviously increases, so the sections are divided into two periods of 2000-2009 and 2010-2016. Based on the information fusion of the multiple visual expressions, the time and space difference (figure 8) that the outbreak frequency and the accumulated maximum area of the red tide are obvious is obtained, and the outbreak frequency and the accumulated maximum area of the red tide in two periods of 2000-2009 and 2010-2016 are opposite in trend in each subarea, wherein the north part (area A) descends, the middle part (area B) ascends, and the south part (area C) descends (figure 9).
5) Based on the step 3) and the step 4), an instrument panel model is constructed, and a relatively universal red tide dynamic analysis chart is designed and used for red tide information mining analysis.
And designing a dynamic chart aiming at the red tide occurrence conditions of different algae species and months, and constructing a red tide occurrence frequency instrument panel model. According to the requirements of users, various designs such as perspective table screening, mini-picture display, instrument panel models and the like are integrated, and the distribution characteristics of the red tide occurrence situation are dynamically displayed (figure 10). Meanwhile, a comparison graph (shown in figure 11) of the red tide outbreak situation of the two algae species is newly designed, and a user can independently select the two algae species for comparison and analysis according to the requirement to find out the rule of the red tide happening of the different algae species.
According to the method, red tide data are subjected to standardized processing based on an Excel functional module, and then combined with a data perspective table and a perspective view cross-time grouping and data structure layering method, a complex model is easily constructed cross-data, the composition, the relation, the hierarchy and the distribution of red tide information are identified and analyzed, and the difference of fine information such as data time nodes or space delimitation is judged; stripping data information layer by fusing various visualization modes such as a dynamic time line, a three-dimensional map and the like, and evaluating the effectiveness of the fusion mode by an example; and finally, fusing a plurality of visualization modes such as a perspective view, a mini-graph, a dynamic chart and the like, constructing an instrument panel model, and designing a relatively universal visualization mode of red tide dynamic analysis, namely 'a chart', for red tide information mining. The examples prove that the method can effectively screen out the nodes of red tide subareas and time-sharing periods, more effectively help users analyze and extract the internal rules of red tide data, and provide technical support for relevant departments such as scientific research and management.
Claims (7)
1. A visual mining and application method of red tide data is characterized by comprising the following steps:
1) carrying out normalized processing on the information of the original red tide event; reading files in batches by utilizing matlab programming, identifying the structure and the name of each project of data, correcting the data in batches according to the specified data project, and finally outputting the files;
2) analyzing the history of the red tide events, checking and screening out independent red tide events, and finishing data preprocessing;
3) designing and drawing a data pivot table and a perspective view of various contents based on the data preprocessed in the step 2), identifying and analyzing the composition, relation, hierarchy and distribution of red tide information, and selecting and optimizing various chart types;
4) based on the data preprocessed in the step 2), designing a multi-source visual fusion mode of a dynamic time line and a three-dimensional map, and verifying the feasibility and effectiveness of the red tide information mining;
5) based on the step 3) and the step 4), an instrument panel model is constructed, and a relatively universal red tide dynamic analysis chart is designed and used for red tide information mining analysis.
2. The method for mining and applying the visualization of red tide data as claimed in claim 1, wherein in step 1), the specific method for performing the normalization processing on the information of the original red tide event comprises:
firstly, reading data in batches by utilizing Matlab programming, identifying the structure and the item names of original data through software, then checking the title names of all columns in an input red tide event history record file according to a standard data item, correspondingly supplementing and sequencing by utilizing a Matlab modification program, and outputting the batch modified data in batches by programming.
3. The visual mining and application method of red tide data as claimed in claim 2, wherein the canonical data items, i.e. the column header names, are set as: sequence number, occurrence time, death time, duration, location, longitude, latitude, sea area of occurrence, specific sea area, maximum area of influence, species of biological dominance, highest density, loss condition.
4. The method for mining and applying the visualization of red tide data as claimed in claim 1, wherein in step 2), the specific method for preprocessing the data is: the method comprises the steps of detecting and screening independent red tide events, wherein two red tide events of single algae species red tide and mixed algae species red tide exist in original data due to different statistical modes, in part of original files, one mixed algae species red tide event is divided into a plurality of single algae species red tide events, repeated statistics of the red tide events is caused, in order to avoid the situation, the starting and ending time and the occurrence place of the red tide events are detected, the red tide events of the mixed algae species are unified, and repeated information of branch statistics is deleted.
5. The method as claimed in claim 1, wherein in step 3), the specific method for identifying and analyzing the composition, relationship, hierarchy and distribution of red tide information is as follows: the data perspective table enhancement function of Excel is utilized to realize that a complex model is easily built across data, the data are automatically grouped according to time, a user checks the content according to the requirement, selects a corresponding sea area and area through a screening button to carry out data statistics, and the time grouping of the data comprises the modes of second, minute, hour, day, month, quarter, year or the combination of the modes; analyzing and designing a data pivot table with various contents, taking the pivot table as a dynamic data source, selecting and optimizing various chart types, and generating a perspective view; inserting perspective, grouping and zooming in and out other hierarchies in the data in a time-span mode, and selecting corresponding sea areas and regions for graphical display according to contents which a user needs to view.
6. The visual mining and application method of red tide data according to claim 1, wherein in step 4), the feasibility and the effectiveness of the red tide information mining are verified by designing a multi-source visual fusion mode of a dynamic timeline and a three-dimensional map, and the specific steps are as follows:
(1) screening the nodes of the red tide information in different periods by using an Excel dynamic time line: based on the function of an Excel calendar, selecting a dynamic time range of a single year or a plurality of continuous years for data statistics and visual display according to the user requirements; dragging the time slider on the animation control toolbar can display the distribution condition of the red tide information in different periods; based on the function of the Excel dynamic chart, selecting a corresponding project for visual display after data screening, and facilitating a user to split, check and analyze a data single-point project; the corresponding project is a time node or a partition area;
(2) analyzing the spatial position relation and the rule of the red tide information by using an Excel three-dimensional map: for red tide data containing position information, the data are quickly mapped onto a virtual earth through acquisition and identification of data space coordinate information, contents to be expressed by the data are displayed in a two-dimensional plane map or a three-dimensional map, the thematic map is dynamically analyzed and three-dimensionally displayed, form data with space information are converted into the thematic map, a data space visualization product is realized, and the visibility and the analysis efficiency of the data are improved;
(3) and verifying the effectiveness and feasibility of the mining of the red tide information by the fusion mode based on the red tide event historical record original data.
7. The visual mining and application method of red tide data as claimed in claim 1, wherein in step 5), an instrument panel model is constructed, and the specific method for designing a relatively universal red tide dynamic analysis chart is as follows: the method comprises the steps of designing a dynamic chart aiming at the red tide occurrence conditions of different alga species and different months, constructing a red tide occurrence frequency instrument panel model, integrating perspective table screening, mini-graph display and multiple visual designs of the instrument panel model according to user requirements, dynamically displaying the distribution characteristics of the red tide occurrence conditions, simultaneously newly adding two alga species red tide outbreak condition comparison chart designs, and enabling a user to independently select two alga species according to requirements to perform comparison analysis and search the rules of the red tide occurrence of different alga species.
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| 曹敏杰: "浙江近岸海域海洋生态环境时空分析及预测关鍵抆术研究", 《中国优秀博硕士学位论文全文数据库(博士) 工程科技Ⅰ辑》 * |
| 李金花: "利用数据透视表进行多角度动态分析", 《中国管理信息化》 * |
| 黄海波: "Excel2016三维地图的地理数据可视化与教学应用", 《中学地理教学参考》 * |
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| CN111639149A (en) * | 2020-05-29 | 2020-09-08 | 山东浪潮通软信息科技有限公司 | Ocean data visualization method and device |
| CN111639149B (en) * | 2020-05-29 | 2023-07-25 | 浪潮通用软件有限公司 | Ocean data visualization method and device |
| CN113312375A (en) * | 2021-05-18 | 2021-08-27 | 南京中科水治理股份有限公司 | Visual mining and implementing method for water ecological restoration engineering data |
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